Next Article in Journal
Optimization of Large Vessel Occlusion Detection in Acute Ischemic Stroke Using Machine Learning Methods
Previous Article in Journal
Predicting Heart Cell Types by Using Transcriptome Profiles and a Machine Learning Method
Previous Article in Special Issue
Potential Role of Diabetes Mellitus-Associated T Cell Senescence in Epithelial Ovarian Cancer Omental Metastasis
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Landscape of Immunotherapy Options for Colorectal Cancer: Current Knowledge and Future Perspectives beyond Immune Checkpoint Blockade

by
Alecsandra Gorzo
1,2,
Diana Galos
1,2,
Simona Ruxandra Volovat
3,
Cristian Virgil Lungulescu
4,*,
Claudia Burz
1,5 and
Daniel Sur
1,2,*
1
Department of Medical Oncology, The Oncology Institute “Prof. Dr. Ion Chiricuţă”, 400015 Cluj-Napoca, Romania
2
Department of Medical Oncology, University of Medicine and Pharmacy “Iuliu Hatieganu”, 400000 Cluj-Napoca, Romania
3
Department of Medical Oncology, University of Medicine and Pharmacy “Grigore T. Popa” Iasi, 700115 Iasi, Romania
4
Department of Medical Oncology, University of Medicine and Pharmacy Craiova, 200349 Craiova, Romania
5
Department of Allergology and Immunology, University of Medicine and Pharmacy “Iuliu Hatieganu”, 400000 Cluj-Napoca, Romania
*
Authors to whom correspondence should be addressed.
Life 2022, 12(2), 229; https://doi.org/10.3390/life12020229
Submission received: 16 December 2021 / Revised: 21 January 2022 / Accepted: 31 January 2022 / Published: 2 February 2022
(This article belongs to the Special Issue Cancer Immunotherapy)

Abstract

:
Colorectal cancer is the third most prevalent malignancy in Western countries and a major cause of death despite recent improvements in screening programs and early detection methods. In the last decade, a growing effort has been put into better understanding how the immune system interacts with cancer cells. Even if treatments with immune checkpoint inhibitors (anti-PD1, anti-PD-L1, anti-CTLA4) were proven effective for several cancer types, the benefit for colorectal cancer patients is still limited. However, a subset of patients with deficient mismatch repair (dMMR)/microsatellite-instability-high (MSI-H) metastatic colorectal cancer has been observed to have a prolonged benefit to immune checkpoint inhibitors. As a result, pembrolizumab and nivolumab +/− ipilimumab recently obtained the Food and Drug Administration approval. This review aims to highlight the body of knowledge on immunotherapy in the colorectal cancer setting, discussing the potential mechanisms of resistance and future strategies to extend its use.

1. Introduction

Colorectal cancer (CRC) is the third most prevalent malignancy in Western countries and still a major cause of cancer-related death worldwide [1]. Even if high-income nations show a greater incidence in CRC, less developed countries are encountering significant increases in CRC cases [2]. Extensive studies have observed differences in risk factors, incidence and cancer-related deaths between ethnic groups, with African Americans, in particular, showing a higher frequency of CRC cases as well as death rates [3,4,5]. Although sustained efforts have been made in improving screening and early detection approaches, about 25% of the CRC patients are diagnosed with metastatic disease and, therefore, have a very poor prognosis [1]. With drug combination optimization, mortality has been reduced; however, the five-year overall survival (OS) remains only 20% [6].
In early-stage CRC, surgery represents the elective treatment [7]. The five-year survival rate following surgical resection is 99% in stage I, 68–83% in stage II, and 45–65% in stage III [8,9]. Therefore, adjuvant chemotherapy is administered in stage III and high-risk stage II (T4 stage, less than 12 lymph nodes examined, positive resection margins, lymphovascular emboli, perineural invasion, obstruction, and perforation) CRC patients to prolong overall survival. The standard of care in the adjuvant setting is the combination of fluoropyrimidine and oxaliplatin (FOLFOX or CAPOX), which was shown to significantly improve disease-free survival (DFS), compared to fluoropyrimidine alone [10]. Moreover, the addition of oxaliplatin resulted in improved OS and reduced risk of death with 17%, 16%, and 12% in the studies conducted by XELODA, MOSAIC, and NSABP C-07, respectively [11,12,13].
In the metastatic setting (mCRC), the median OS is approximately 30 months. In selected patients, surgical resection of metastases is advisable either upfront or following downsizing systemic treatment [14,15]. If surgical resection does not represent a realistic goal, systemic therapy with chemotherapy and targeted agents has been shown to substantially increase overall survival [16]. Standard chemotherapies are represented by fluoropyrimidines, oxaliplatin, irinotecan, and trifluridine/tripiracil [17]. The efficacy of chemotherapy agents is further improved by the addition of targeted agents, such as the anti-EGFR mAbs (cetuximab and panitumumab) in RAS-wt tumor or anti-VEGF agent bevacizumab, regardless of RAS status [6,18,19]. Ramucirumab (anti-VEGFR-2) and aflibercept (a synthetic receptor for VEGF-A, VEGF-B, and PIGF) have demonstrated efficacy in the second-line setting, in combination with chemotherapy [20,21]. Regorafenib, a multikinase inhibitor, has also demonstrated efficacy in further lines such as monotherapy [22].
Throughout the last decade, the immune system was deeply studied to understand how it interacts with cancer cells. Immune checkpoint inhibitors (ICIs) manipulate the immune system to reactivate the antitumor immune response by blocking the immune checkpoint proteins (PD-1 and CTLA-4) or their ligands (PD-L1). Consequently, ICIs, such as anti-PD-L1 monoclonal antibodies (mAbs-Atezolizumab, Avelumab, and Durvalumab), anti-PD-1 mAbs (Nivolumab and Pembrolizumab), and anti-CTLA-4 mAbs (Ipilimumab) led to marked therapeutic efficacy in melanoma, as well as lung, head and neck, and urothelial cancers [23,24,25].
Furthermore, to correlate the phenotype of cancer cells with the clinical behavior and guide treatment, CRC has been classified into four consensus molecular subtypes (CMS): CMS1 (14%)—MSI Immune, with strong immune activation, hypermutated, MS unstable; CMS2 (37%)—canonical, epithelial, chromosomally unstable, with marked WNT and MYC signaling activation; CMS3 (13%)—metabolic, epithelial with metabolic dysregulation; and CMS4 (23%)—mesenchymal, prominent transforming growth factor-beta activation, stromal invasion, and angiogenesis, with a remaining unclassified group (13%) with mixed features [26]. Recent studies have confirmed an increased response rate to ICIs in patients whose tumors are highly microsatellite unstable (MSI-H) and are DNA mismatch repair-deficient (dMMR) [27,28]. This subset of patients with this unique phenotype represents about 15% of all sporadic CRC and only 5% of mCRC [29]. To date, based on the result of phase III KEYNOTE-177 and phase II Checkmate-142 trial, the NCCN guideline recommends the use of pembrolizumab and nivolumab ± ipilimumbab in the first-line and non-first-line settings in MSI-H/dMMR mCRC patients. Moreover, the checkpoint inhibitors regimens are also recommended in the neoadjuvant setting for resectable mCRC with MSH-I/dMMR status [30,31].
This article aims to review the existing data for applying immunotherapy in CRC, more precisely in a subset of patients with MSI-H tumors. We addressed the importance of biomarkers in selecting CRC patients for immunotherapy. The review also discusses the challenges due to resistance mechanisms and potential future strategies to extend immunotherapy uses.

2. Predictive/Prognostic Biomarkers for Selecting CRC for Immunotherapy

2.1. Microsatellite Status

Microsatellites are repeated non-coding DNA sequences, ranging in length from 1 to 10 base pairs. During DNA replication, microsatellites are frequent sites for mutations [32]. The role in detecting and correcting these errors is assigned to the mismatch-repair system (MMR) [33]. The presence of microsatellite instability (MSI-H) due to deficiency in the MMR (dMMR) is found in about 15% of all CRCs and 4% of mCRC cases [34]. MSI-H status is the hallmark of Lynch syndrome; however, 70–85% of patients with MSI-H/dMMR tumors have somatic mutations, most frequently inactivating the MLH1 gene [35]. The MSI status can be detected either by polymerized chain reaction (PCR), next-generation sequencing (NGS), or by the absence of immunohistochemical staining of the MMR proteins (MSH2, MLH1, MSH6, and PMS2) [36].
This phenotype is characterized by a widespread accumulation of mutations, which generate frame-shifted proteins (neoantigens) with great immunogenic potential. MSI-H/dMMR tumors frequently involve the proximal colon, are poorly differentiated, and have mucinous histology [37]. Population-based studies have investigated the susceptibility of MSI-H/dMMR mutations in certain ethnic groups presenting with CRC. Studies show the MSI-H/dMMR phenotype has a significantly higher prevalence in the African American (AA) population (up to 45%) [38,39,40], while the Caucasian and Asian populations show a lower incidence of MSI-H rates, no higher than 20% [41,42]. A study conducted on an Indian cohort observed similar frequencies of MSI-H/dMMR CRC in their studied population when compared to the West, despite having an inferior incidence of CRC cases [43]. MSI-H/dMMR tumors are highly infiltrated with immune cells, including CD4+ TILs (tumor-infiltrating lymphocytes), CD8+ TILs, Th1 (T helper 1), and macrophages [37]. Moreover, these tumors have an up-regulated expression of immune checkpoints (PD-1, PD-L1, CTLA4) [44]. Therefore, based on these observations, it was suggested that MSI-H/dMMR CRCs might have a good response to ICIs. Following the results of several stage II trials, ICIs are considered a breakthrough strategy in the treatment of MSI-H/dMMR mCRC [45,46]. However, not all MSI-H/dMMR mCRC patients respond to ICIs, suggesting that a deeper knowledge of immune-related mechanisms is needed [47]. In stage II CRC, MSI-H/dMMR is associated with a lower recurrence rate than MSI-L/pMMR tumors, with an HR estimated for OS correlated with MSI of 0.65 (95% CI: 0.59–0.71) [48].

2.2. Tumor Mutational Burden

The success linked to ICIs was associated with the hypermutated phenotype due to many DNA replication errors, alongside the consequent inflamed TME [49]. Hence, an emerging biomarker to predict the tumor’s response to immunotherapy is the calculation of tumor mutational burden (TMB), which quantifies the nonsynonymous mutations per coding area in a tumor genome [50]. The relationship between immunotherapy response and TMB could be explained by the fact that a higher number of mutations generates higher mutation-associated neoantigens, with increased lymphocyte infiltration in the TME [51]. The Food and Drug Administration (FDA) approved treatment with Pembrolizumab in patients with any refractory and unresectable or metastatic solid tumors that harbor a high TMB (TMB-H), defined as ≥10 mutations per megabase (Mut/Mb) [52]. The decision was based on the analysis of 10 cohorts of patients with metastatic solid tumors enrolled in the KEYNOTE-158 trial, which investigated the treatment with pembrolizumab until disease progression or unacceptable toxicities occurred. Among all patients (n = 790), 13% (n = 102) were defined as TMB-H. The results showed a 29% RR in TMB-H patients, compared to 6% in those with TMB <10 mut/Mb [53]. The relationship between TMB and other clinicopathologic variables that are already known to influence immunotherapy response remains to be elucidated.

2.3. Immunoscore

Increasing evidence has shown that cancer evolution is strongly dependent on the TME consisting of various cell entities, including blood vessels, endothelial cells, fibroblasts, and cells of the immune system. It was demonstrated that adaptive immune cell infiltration is a better prognostic marker than grading, staging, and metastatic status [54,55]. The immunoscore is a digital pathology and immunohistochemistry-based assay which translates the immune contexture into a feasible prognostic biomarker for stage I-III CRC [56]. The immunoscore summarizes the density of the lymphocyte population, CD3+ and CD8+ T cells in the tumor core, and invasive margins, which provides a scoring system from low immune cell density (immunoscore 0) to high density (immunoscore 4). At the center of this mechanism, the more a tumor is defined as immunogenic, the more it is able to attract a T-cell mediated immune response, which is associated with a higher neoantigen load, often found in MSI-H/dMMR tumors [57]. Consequently, a high immunoscore correlates with a longer patient’s survival [58], while patients with low immunoscore and minimal tumor invasion are more likely to undergo disease relapse [59,60]. In terms of prognostic ability, the immunoscore tends to outperform the classical gold-standard TNM system in predicting DFS and OS for stage I, II, III CRC [61,62]. A high immunocore was associated with the highest DFS and OS in stage II colon cancer. The five-year recurrence rate was 8% in high, 14% in intermediate, and 23% in low immunoscore. A multivariable analysis had similar results (p < 0.0001 for high Immunoscore vs. low) [63]. Regarding stage III colon cancer, according to the NCCTG NO157 trial, a high immunoscore was correlated with a longer three-year DFS compared to a low immunoscore (p < 0.05) [64]. In the phase III IDEA trial, high and intermediate immunoscore significantly predict a DFS benefit of prolonged adjuvant chemotherapy with FOLFOX regimen in stage III colon cancer patients. (HR = 0.53; 95% CI 0.37–0.75; p = 0.0004) [65]. Apart from representing a good prognostic marker, the immune contexture could also predict the response to ICIs [66]. The CD8+ T cells’ density was directly correlated with the clinical response to anti-PD1 agents. Moreover, CD8+ T cells were also suggested to be a good predictor of the response to anti CTLA4 molecules in melanoma patients [67]. The validation of the consensus immunoscore [58] and its introduction in the fifth edition of the World Health Organization classification of digestive tumors among the “Essential and Desirable Diagnostic Criteria” for CRC [68] makes it a step closer to the proposed notion of TNM-I classification (“I” from “immune”) [69].

2.4. POLD1/POLE

DNA polymerase delta (POLD1) and DNA polymerase epsilon (POLE) are two key enzymes responsible for the accurate replication of the genome in the cell cycle. Mutations that occur in the POLE and POLD1 genes generate a deficit in DNA repair [44]. Therefore, they lead to an ultra-mutated phenotype, with up to 10 times more mutations than in MSI-H CRC. Germline mutations in the exonuclease domain of POLD1 and POLE affect the proofreading abilities of these polymerases, predispose to multiple colorectal carcinomas and adenomas, and generate polymerase proofreading-associated polyposis (PPAP) [70]. PPAP represents 0.1–0.4% of familial cancer cases [71]. Moreover, other extracolonic tumors were described, including brain, endometrial, ovarian, breast, skin tumors [72]. Most of these mutations represent, however, somatic events [73]. This type of tumor has similar characteristics with the dMMR CRC, including up-regulation of immune checkpoint molecule, high level of TILs, and increased cytotoxic T cells markers [74]. Clinically, POLE-mutated CRC patients usually have a good prognosis. The tumors are characterized by an early stage at presentation, right-sided location, male sex, and younger age [75]. Given the similarities with the MSI-H/dMMR CRCs, the therapeutic potential of ICIs in POLE-mutated CRCs is clinically relevant. To date, very few scientific works are available about the efficacy of ICIs in mCRC harboring POLE or POLD1 mutations [76,77]. Further data are needed to assess if mutations in POLE and POLD1 might predict benefits from ICIs.

2.5. PD-1/PD-L1 Expression

The PD-1 molecules are expressed by activated NK cells, B-cells, and T-cells, and they can bind to their ligands, PD-L1, expressed on cancerous cells [78]. One of the most extensively studied biomarkers is probably the tumor expression of PD-L1 determined by immunohistochemistry [79]. Even if in esophageal, gastric, and NSCLC the PD-L1 expression could be a valuable predictor of response to anti-PD-1 therapy [79,80], it was not formally demonstrated to be associated with survival or response to immunotherapy in CRC [81,82]. Several issues are preventing the expression of PD-L1 from being a reliable biomarker. Firstly, PD-L1 expression represents a dynamic process that adapts according to the tumor stage and microenvironment, and it can also be influenced by treatment. The tumor expression is not uniform; therefore, the sampling location and time could affect the results of PD-L1 staining [83]. Nonetheless, lacking a standard evaluation for PD-L1 expression limits its clinical significance [84].

3. Immunotherapy in CRC

One of the strategies that have been revolutionizing cancer treatment in the last few decades revolves around targeting the immune system. Immunotherapy aims at overcoming the limitations of chemotherapy and radiotherapy while targeting the host’s own immune system. Once administered, immunotherapy alerts the innate and adaptive immune responses about the presence of cancerous cells and guides the immune response toward eradicating them, leaving healthy cells unaffected [85]. These drugs can be administered as passive immunotherapy (immunostimulatory cytokines, immunomodulatory mAbs, dendritic cell-based immunotherapies, anti-cancer vaccines, inhibitors of immunosuppressive metabolism, pattern recognition receptors, and immunogenic cell-death inducers) or as active immunotherapy (adoptive cell transfer, oncolytic viruses, or tumor-targeting mAbs), with some of these strategies finding their utility in CRC treatment [86].

3.1. Immunomodulatory mAbs

Immune checkpoints represent a set of regulatory pathways of the immune system whose primary role is to ensure modulation and control of the immune response while maintaining self-tolerance [87]. Two such pathways are PD-1/PD-L1/2 and CTLA-4/CD80-CD86 and they represent encouraging targets for immunotherapies. These molecules are present on tumor cells, T cells, and antigen-presenting cells (APC). Once the co-inhibitory receptor (PD-1, CTLA4) interacts with its ligand (PD-L1/2 and CD80-CD86, respectively), the T-cell function is inhibited, leading to a suppressed immune response [88,89]. Cancerous cells exploit this mechanism by hyperactivating immune checkpoints and overexpressing ligands; therefore, evading the immune response. ICIs attempt to dampen the PD-1/PD-L1/1 and CTLA-4/CD80-CD86 interaction, restore immunosurveillance and aid the host’s immune system in fighting cancer [90].
ICIs targeting PD-1 and CTLA4 have demonstrated significant activity in solid tumors, such as melanomas, non-small-cell lung cancer (NSCLC), and renal cell carcinoma [91]. The initial studies showed limited clinical activity of ICIs in non-selected CRC patients. A phase I trial (NCT00730639) investigating the role of nivolumab (anti-PD-1) in advanced solid tumors, including 19 CRC patients, reported a complete response that lasted over three years in just one of the CRC patients with an MSI-H/dMMR phenotype [92,93]. Based on these results and understanding of tumor microenvironment in MSI-H/dMMR tumors, the interest in immunotherapy in CRC was further expanded. The mechanism behind the ICIs is depicted in Figure 1.
Pembrolizumab is a PD-1 blocking humanized, IgG4 monoclonal antibody which prevents the interaction between PD-1 and its ligands, PD-L1, and PD-L2 [94]. The phase II trial, KEYNOTE-028, investigated the clinical activity of pembrolizumab (10 mg/kg) in MSI-H tumors. Of the 41 patients included, 32 cases had mCRC with or without MSI-H/dMMR phenotype. Among the MSI-H/dMMR mCRC patients, the objective response rate (ORR) was 40%, and a disease-control rate >12 weeks was observed in 90% of cases. The possibility of achieving a response to therapy was significantly associated with the number of somatic mutations (p = 0.02) [27]. Considering these outcomes, in May 2017, the FDA approved pembrolizumab to treat MSI-H/dMMR advanced CRC patients that progressed on conventional chemotherapy [95].
Furthermore, the randomized, open-label phase III study KEYNOTE-177 demonstrated a significant improvement in median progression-free survival (PFS) and ORR after administration of pembrolizumab in MSI-H/dMMR mCRC when compared to 5-fluorouracil-based chemotherapy alone or in combination with bevacizumab or cetuximab, with acceptable toxicity. Median PFS was significantly longer in the pembrolizumab arm (16.5 months), compared to the chemotherapy arm (8.2 months). Confirmed ORR reached 43.8% with pembrolizumab vs. 33.1% with chemotherapy. Based on these data, pembrolizumab was recommended as the first-line treatment for patients with mCRC and MSI-H/dMMR [96].
Nivolumab, a human IgG4 mAbs, is another PD-1 inhibitor approved for mCRC with MSI-H/dMMR [97]. CheckMate-142, a phase II open-label trial, investigated the efficacy of nivolumab (3 mg/kg, every 2 weeks) in 74 previously treated MSI-H/dMMR mCRC patients. The 12-month PFS was reported to be 50% (95% CI: 38–61), and the 12-month OS was 73% (95% CI: 62–82) [98]. Based on these outcomes, in 2017, the FDA approved nivolumab to treat MSI-H/dMMR mCRC with progressive disease after chemotherapy [99]. The trial further evaluated the combination of nivolumab + low-dose ipilimumab (anti-CTLA4 mAb). At a median follow-up of 13.4 months, the results showed an improved clinical benefit with an ORR of 55%. Regardless of the PD-L1 tissue expression, 71% of the patients remain progression-free at 12 months. Moreover, the 12-month median OS was 85% (95% CI: 77.0–90.2) [100]. In 2018, these results led to the FDA approval of nivolumab + low-dose ipilimumab for previously treated MSI-H/dMMR mCRC patients [101].
In addition, the trial further evaluated the role of the combination therapy as first-line treatment for MSI-H/dMMR mCRC. After a median follow-up of 29.0 months, the study showed a significant ORR (69%) and CR (13%), but with OS and median PFS not yet reached [102]. Based on these results, to date, nivolumab is approved as the first-line therapy option for MSI-H/dMMR mCRC, either as monotherapy or in combination with ipilimumab [103].
Avelumab is an anti-PD-L1 inhibitor evaluated in mCRC with MSI-H/dMMR status. A recently conducted phase II study evaluated monotherapy with avelumab in patients with MSI-H/dMMR or POLE-mutated metastatic or unresectable CRC and presented encouraging results with manageable toxicities. The primary endpoint of the study was ORR, which was evaluated at 24.2% overall and 28.6% in patients with MSI-H/dMMR. In terms of secondary endpoints, PFS rates were 3.9 and 8.1 months in the MSI-H/dMMR patients, and the median OS was 13.2 months. The results presented by this trial showed that avelumab efficacy in the mCRC setting is comparable with that of FDA-approved pembrolizumab and nivolumab [104]. Several combination therapies between avelumab and other therapeutical agents are being investigated at the moment [105].
Another ICI regimen is the one combining an anti-PD-L1 agent (durvalumab) with the anti-CTLA-4 drug tremelimumab in mCRC. A randomized phase II study demonstrated prolonged OS with durvalumab+tremelimumab vs. best supportive care (BSC). Moreover, the study analyzed the possibility of using plasma TMB for selecting patients for immunotherapy. Patients with elevated TMB would most likely benefit from durvalumab and tremelimumab combination. After a median follow-up of 15.2 months, the median OS of the combination ICI therapy was 6.6 months, while the median OS for the BSC arm was 4.1 months [106].
Atezolizumab, an anti-PD-L1 mAb, is currently being investigated in the adjuvant CRC setting. The phase III ATOMIC trial compares the combination of atezolizumab and FOLFOLX vs. FOLFOX alone in MSI-H stage III CRC patients. The study has DFS as the primary endpoint and will establish if ICIs might be added to the oxaliplatin-based regime in this setting [107].

3.2. Neoadjuvant Setting

Immune checkpoint blockade has also been discussed as a neoadjuvant strategy, although studies have reported only a few cases. One case report had shown significant benefits when pembrolizumab was administered in the neoadjuvant setting in a Lynch syndrome patient, who after that qualified for surgical resection [108]. A retrospective study on two patients with locally advanced CRC has shown that nivolumab in the neoadjuvant setting can induce complete responses, either as a single treatment option or followed by surgery [109]. Moreover, nivolumab has proved to induce a significant pathological response as neoadjuvant treatment for early stage CRC, when administered in combination with ipilimumab, as demonstrated by a different clinical trial (NCT03026140) conducted in Europe [110]. Even if, to date, no clinical trials are supporting this approach, the NCCN guideline recommends the administration of pembrolizumab or nivolumab ± ipilimumab as an option for neoadjuvant setting in resectable MSI-H/dMMR mCRC [111].

3.3. Adoptive Cell Transfer

Neoantigens represent an emerging target for immunotherapeutic approaches attempting to overcome the toxicities and narrowed response rates of non-antigen-specific treatments [112]. Neoantigens are altered peptides derived from non-synonymous somatic mutations otherwise absent in normal tissues. These tumor-specific antigens are presented by major histocompatibility complex I (MHC) proteins and then recognized by T-cells and triggering an anti-tumor T-cell immune response [113]. Next-generation sequencing technologies are utilized with the purpose of identifying neoantigens suited to activate tumor-specific T-cell recognition [114].
Adoptive cell transfer (ACT) describes the neoantigen-targeting strategy that requires immune cells derived from patients (autologous transfer), donors (allergenic transfer), or cells differentiated from stem cells. These cells are activated and expanded in vitro through gene modification processes in order to make them better suited to target cancerous cells and eradicate them, thereby improving the immune functions once infused into the patient as therapy [115]. ACT technologies include the manipulation of the host’s tumor-infiltrating lymphocytes (TILs) and the host’s T-cells that have been genetically altered to express a T-cell receptor or a chimeric antigen receptor (CAR) [116]. Research into ACT therapy has objectified clinical responses in the settings of cholangiocarcinoma [117], breast cancer [118], metastatic melanoma [119,120], and CRC [121]. During a phase II clinical trial (NCT01174121) assessing the efficacy of adoptive transfer of autologous TILs in certain solid tumors (digestive tract, urothelial, breast, ovarian, and endometrial cancers), one patient with mCRC showed objective regression. Following one infusion with TILs reactive to KRAS G12D mutation identified in the tumor, the patient presented with regression of all seven lung metastases. Nine months after therapy, one of the seven lesions showed progression, and it was subjected to resection. After the removal of the lung lesion, the patient remained clinically disease-free for four months [121].
CAR-T cell therapy has also been explored in the setting of CRC. CAR-T cells can be manipulated to target a series of tumor-associated antigens (TAAs) highly expressed by CRC tumors, most notably carcinoembryonic antigen CEA [122]. A phase I clinical trial (NCT02349724) indicated that CEA CAR-T cell therapy has some efficacy in mCRC patients with CEA positive tumors, with an acceptable toxicity profile. The authors reported stable disease in 70% of the patients who received infusions with CAR-T cells, while two patients showed tumor regression. In addition, the study observed a sustained decline in the levels of serum CEA [123]. Furthermore, other phase I clinical trials have addressed the efficacy of CAR-T cells targeting CEA as a regional treatment for liver metastases (NCT01373047, NCT02416466) from CRC. The study conducted at Boston University concluded that percutaneous hepatic artery infusions of anti-CEA CAR-T cells showed promising signs of clinical response in patients who underwent multiple lines of systemic therapy, with a safe toxicity profile [124]. The use of anti-CEA CAR-T cell therapy as local treatment of peritoneal carcinomatosis from mCRC has also been studied in pre-clinical trials [125] and several other studies are underway analyzing the further clinical impact of ACT in CRC (NCT03935893, NCT03970382, NCT04426669).

3.4. Cancer Vaccines

In mCRC, several types of tumor vaccines were studied, including peptide vaccines, autologous vaccines, dendritic cell transplants, and oncolytic viral vector vaccines, but with limited efficacy [126]. The rationale behind viral antigen vaccines is based on the pathogenicity of the virus, which can generate a robust immune response [127]. Therefore, oncolytic virotherapy demonstrated antitumor efficacy when administered alone, or alongside conventional chemotherapy [128]. Further research has identified potential targets for peptide vaccine-based immunotherapy in TAAs over-expressed on the surface of tumor cells. In the case of CRC, the targeted molecules were CEA, melanoma-associated antigen, and MUC1 [129]. A phase II trial assessed the survival benefit of autologous dendritic cells modified with a pox vector encoding MUC1 and CEA (PANVAC) in mCRC who were disease-free after metastasectomy and perioperative chemotherapy. The survival was longer in the group of patients who received active immunotherapy [130]. Although cancer vaccine TAAs have demonstrated their capacity to strengthen the immune system and presented low toxicities, the evidence showing a reliable survival benefit is limited [131,132,133].
As aforementioned, deficiencies in the MMR proteins generate genomic instability at the sites of microsatellite coding sequences. This phenomenon results in frameshift antigens considered to be highly immunogenic and a good target for vaccines [130]. Therapeutic vaccines targeting tumor-specific neoantigens intend to enhance the existing effector T-cells, expend new antitumor T-cells clones, and contribute to tumor destruction [134]. These vaccines are formulated as RNA or DNA coding for neoantigens, virus-based systems, synthetic peptides, or dendritic cells loaded with neoantigens [135]. After the encouraging results from mouse models, the first-in-human trials investigating neoantigen vaccines demonstrated their safety and efficacy in glioblastoma and melanoma patients [136,137]. To date, neoantigen-based vaccines with or without ICIs have been investigated in various solid tumors, including CRC (NCT04087252, NCT03289962, NCT03639716, NCT0355271). Furthermore, we summarize the current immunotherapeutic options in CRC in Figure 2.

3.5. Highlights on Randomized Clinical Trials

Immunotherapy has shown great efficacy in MSI-H/dMMR CRC [102,138]. However, it is still a challenge to identify the optimal line of therapy and possible novel combinations. The ongoing and completed clinical trials investigating anti-PD1, anti-PD-L1, and anti-CTLA4 are listed in Table 1 and Table 2, respectively.

4. Resistance to Immunotherapy

Even if the administration of ICIs in MSI-H/dMMR CRC patients is relatively recent, resistance to treatment was already reported. The clinical studies investigating ipilimumab-nivolumab and pembrolizumab showed objective responses of 54.6% [45] and 40% [27], respectively. The results suggest that a group of MSI-H/dMMR CRC patients harbor mechanisms of resistance that impair immune antitumor activity [139]. One of the mechanisms by which cancer cells avoid immune surveillance is altering the expression of the human leukocyte antigen (HLA) complex, leading to inadequate antigen processing and presentation [140]. A study including 179 MSI-H/dMMR CRC patients from the Nurse Health Study, Tumor Cancer Genome Atlas, and the Health Professionals Follow-up Study cohorts investigated the potential immune evasion mechanism [141]. The study described alterations in the immune-response-related genes correlated to B-cells development, T-cells response, and NK cell function. Most of the MSI-H tumors harbored at least one mutation that could impair antigen presentation. Although in, the majority of cases, these initial mutations were not sufficient to confer resistance to ICIs, they suggest that immune editing is preceding the treatment and tumors are on a resistance continuum. β-2 microglobulin (B2M) is known to be an important part of the HLA-class I complex. Mutations in the B2M gene result in the complete loss of HLA class I molecules on the cell surface [142]. Therefore, B2M deficiency was considered a negative prognostic factor in various tumor types and linked to immune escape [143,144]. B2M somatic mutations were found in about 30% of the dMMR CRCs and less than 2% in pMMR tumors [145]. These mutations occur very often in the coding microsatellites as a result of microsatellite instability and were correlated with resistance to anti-PD-1 molecules [146,147]. It is currently unclear if new clones with defect antigen-presenting machinery evolve due to MSI and genomic instability during the immune checkpoint treatment or the selection of preexisting clones with B2M alterations leads to resistance [148].
Tumor-specific antigen expression plays a significant role when talking about the persistence of antitumor immune response. MSI-H/dMMR tumors generate about 50 times more neoantigens than MSS tumors due to frameshift mutations resulting from MMR deficiency [149]. This aspect brings up an important issue regarding the quality of mutations. Point mutations, causing limited amino acid changes in the protein structure, are less likely to generate a solid immune response, compared to mutations affecting the antigenic structure of proteins [150]. For instance, KRAS point mutations are an important step in developing many solid tumors; however, they show poor immunogenic activity [151]. It is essential to mention that the loss of MMR-gene expression might not always represent MSI status. Consequently, patients could present with an MSI-L disease similar to the MMS phenotype, and therefore with inadequate response to immunotherapy [152].
Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population represented by immature myeloid cells with immune regulatory functions in various diseases, such as chronic inflammation, autoimmune diseases, and viral infections [153]. Accumulating evidence suggested that, in cancer-bearing hosts, MDSCs actively contribute to resistance to immunotherapy [154,155]. MDSCs inhibit the activation and cytotoxicity of T cells and were also shown to favor Treg differentiation and expansion [156]. Additionally, they were shown to be involved in an array of non-immunologic processes, including promotion, angiogenesis, and metastasis [157]. In breast cancer models, the accumulation of circulating MDSCs was associated with unresponsiveness to anti-CTLA4/anti-PD-1 [158]. In melanoma patients, low circulating MDSCs levels are common among clinical responders to ipilimumab [159]. In CRC, MSI-L/pMMR tumors were reported to be highly infiltrated with MDSCs and Treg, compared to MSI-H/dMMR, which might explain the poor outcome of ICIs [160]. To better select the population who could most benefit from immune checkpoint inhibitors, further studies are needed to determine if negative regulatory cells should be included in biomarker systems, such as immunoscore [58].
In patients who developed resistance to PD-1 blockade, the whole-exome sequencing of the tumors showed mutations in Janus kinases 1 and 2 (JAK1 and JAK2) [161]. Truncating mutations in JAK 1/2 were correlated to a lack of IFN-γ responsiveness in cancer cells and, consequently, with secondary resistance to ICIs [162,163]. Additionally, in JAK mutated MSI CRCs, melanoma, endometrial cancer, the expression of the PD-L1 gene was significantly down-regulated [164,165]. In melanoma cells, it was shown that the IFN-γ signaling pathway regulates the expression of PD-L1 through JAK1/2. Therefore, cancer cells might evade IFN-γ-immune response throughout JAK1/2 mutations, leading to impaired IFN-y signaling and preventing PD-L1 expression [166]. Signal transducer and activator of transcription proteins (STATs 1/2), members of this pathway, which function downstream of JAK signaling, are potent mediators of IFN-γ. Mutations in STAT proteins resulting in loss of function could generate impaired IFN-γ signaling and, therefore, immune escape [167].
It was recently discovered that the Wnt/β-catenin pathway coordinates the tumor microenvironment and immune cell infiltration [168]. A preclinical study using murine melanoma models demonstrated that increased expression of the Wnt/β-catenin pathway could decrease IFN-γ levels and T-cell function as a consequence [169]. Another study on melanoma cells also showed that hyperactivation of the Wnt/β-catenin pathway reduces T-cell infiltration in the TME, leading to reduced efficacy of ICIs [170]. Regarding MSI-H/dMMR CRC patients, the WNT signaling pathway should be further analyzed in the context of ICIs responsiveness.

5. The Future of Immunotherapy in CRC

5.1. A New Generation of Immune Checkpoint Inhibitors

The interest over other immune checkpoints increased significantly in the last years, and new potential targets were identified, such as LAG-3, TIM-3, TIGIT, or VISTA [171]. These receptors were shown to be highly expressed on TILs, compared to circulating T-cells found in CRC patients [172]. In several tumors, such as ovarian, melanoma, NSCLC, and gastrointestinal cancers, PD-1 was usually co-expressed with LAG-3, TIM-3, TIGIT, and VISTA on TILs In ovarian cancer, the number of PD-1+LAG-3+CD8+T-cells expressing TNF-α and IFN-γ were significantly decreased, compared to their equivalents without the co-inhibitory receptors [173,174,175,176]. Similarly, in CRC, it was shown that the amount of tumor-infiltrating CD8+ lymphocytes producing IFN-γ was reduced when expressing both TIM-3 and PD-1 [177]. Considering these observations, it might be assumed that using a single anti-PD-1 agent is not always enough to restore T-cells’ functionality. Based on this rationale, many clinical studies investigating new generation checkpoint inhibitors were implemented. V-domain Ig Suppressor of T cell Activation (VISTA) is an immune inhibitory receptor involved in maintaining peripheral tolerance, and it also inhibits the effector function of T cells [178]. Le Mercier et al. demonstrated that VISTA blockade altered the suppressive hallmark of the TME and enhanced specific T-cell response in tumor cells [179]. To date, there is an ongoing phase I clinical study with a fully human mAb anti-VISTA tested in advanced solid tumors (NCT04475523). Preliminary results showed that the administration of the anti-LAG-3 antibody, R3767, led to stable disease in 11 out of 27 patients with advanced solid tumors [180]. Anti-TIM-3 antibodies MBG42 and LY3321367 were well tolerated in monotherapy or when combined with other ICIs [181,182].
Another approach to improve immunotherapy outcomes is to combine ICIs with co-stimulatory checkpoint molecules, such as anti-ICOS, CD28, TNFRSF7, TNFRSF9, and glucocorticoid-induced TNFR-related protein. OX40 antigen (CD134) is a part of the tumor necrosis factor receptors family, and alongside its ligand, OX40L stimulates the activation and proliferation of CD4+ and CD8+ [183]. Various clinical trials are investigating the activity and safety of OX40 agonists in monotherapy or combined with ICIs [184,185].
In order to extend the curative potential of cancer immunotherapies, novel delivery systems are needed. Ongoing research investigates various delivery platforms such as implants, nanoparticles, biomaterials, and scaffolds [186]. Among their many benefits, we can mention the following: protecting and keeping the cargo inactive until it accumulates in the targeted cells, allowing localized and controlled drug delivery to minimize toxicities [187]. For example, to reduce the side effects following systemic administration, ICIs were linked to a peptide derived from PLGF2 (placental growth factor 2) with a good affinity for numerous matrix proteins. In melanoma and breast cancer models, these conjugates remained more localized near the tumor site after peritumoral administration [188]. Moreover, new delivery platforms, such as nanoparticles, could attenuate drug exposure of particular tissues caused by therapeutic combinations (chemotherapy and immunotherapy) that would otherwise be toxic for the patient [187,189]. Besides the many benefits already mentioned, new delivery technologies could address the limitations set by resistance mechanisms. For instance, delivery systems could be expanded to modulate immunogenicity in tumors with cold microenvironments and enhance the response to ICIs [190]. As immunotherapy is evolving very fast, all the advances made in drug delivery will significantly contribute to personalized medicine.

5.2. Synergy of Immunotherapy with Other Therapies for MSI-L/pMMR

In most mCRC cases (about 95%) defined as pMMR, ICIs failed to provide clinical benefits due to the immune deserted TME [191]. Clinical trials have focused on several combination strategies between ICIs and chemotherapy, radiotherapy, or targeted molecules for this group of patients (Table 3).

5.2.1. Immunotherapy with Radiotherapy

Although the MSI-H/dMMR tumors in the ICIs have achieved a significant and durable response, the results in pMMR tumors are disappointing [192]. However, it was hypothesized that radiotherapy (RT) combined with immunotherapy might be able to overcome primary resistance to ICIs in MSS CRC [193]. There is growing evidence that by damaging DNA and inducing tumor death using RT to a single site, it would be possible to enlarge the neoantigen repertoire and to up-regulate pro-inflammatory cytokines, thereby enhancing the immunotherapy effect. This phenomenon is described by the abscopal effect [194]. To date, the combination of immunotherapy and RT is being investigated in two clinical fields. The first one is the oligometastatic setting when locoregional RT is administered with curative intent, and immunotherapy can prevent distant and local relapse and enhance the response within the irradiation field. The second field involves the metastatic setting when RT to a metastatic site is expected to synergize with immunotherapy [195]. Duffy et al. investigated the combination of an anti-PD-1 agent (AMP224) with stereotactic body radiation directed against liver metastasis in mCRC patients. The treatment was feasible and safe; however, the preliminary results showed no objective response [196]. In a phase II study including 40 refractory pMMR mCRC patients, the administration of nivolumab + ipilimumab in combination with RT (to a single metastatic site) showed promising results in terms of efficiency and feasibility [24,197]. A different study conducted by Zhou et al. followed the response to ICI in combination with chemoradiotherapy (CRIT) of five advanced and metastatic CRC patients harboring MSI-H/dMMR. The ORR was 100%, with three patients achieving CR and two patients with PR, with acceptable toxicity. This retrospective study hints that CRIT could enhance the efficacy of anti-PD-1 immunotherapy and overcome potential resistance mechanisms [198].

5.2.2. Immunotherapy with Chemotherapy

Similarly, the addition of chemotherapy to pMMR tumors could modify the immune contexture by generating immunogenic cell death, releasing neoantigens, and therefore activating an immune response against cancer cells [199]. Starting from this biological rationale, some preclinical studies have shown the role of chemotherapy in sensitizing malignant cells to ICIs in lung cancer models, supporting such studies in other malignancies [200]. A phase II study evaluated the efficacy of the FOLFOX regimen in combination with pembrolizumab in untreated mCRC, including 22 pMMR cases, 3 dMMR, and 5 patients with no available data. The results showed an ORR of 53% and a DCR of 100% at eight weeks [201].
Moreover, temozolomide (TMZ) is an oral alkylating agent that can generate a high number of somatic mutations in cancer cells, and therefore induce an MSI-phenotype in pMMR mCRC. TMZ methylates DNA strands, inhibits replication, and induces apoptosis [202]. The efficacy of TMZ is reduced by the O6-methylguanine methyltransferase enzyme (MGMT), which is coded by the MGMT gene. Therefore, silencing the MGMT gene could enhance the sensitivity of tumor cells to TMZ [203]. The MAYA trial (NCT03832621) evaluates the efficacy of nivolumab, ipilimumab, and TMZ in pMMR and MGMT-silenced mCRC patients, who did not progress following two cycles of TMZ [204]. The ARETHUSA trial (NCT003519412) is a phase II non-randomized study in which dMMR mCRC patients are treated with pembrolizumab until disease progression; moreover, the mCRC patients with dMMR, RAS-mutated, and MGMT IHC-negative/promoter hypermethylation positive are treated with TMZ until disease progression. By the time of progression, a tumor biopsy is performed to determine TMB. If it is >20 mutations/Mb, the patients receive pembrolizumab. The study’s primary endpoint is ORR in pMMR mCRC patients who received pembrolizumab [205].

5.2.3. Immunotherapy with Chemotherapy and Targeted Agents

There are accumulating pieces of evidence that anti-vascular endothelial growth factor (VEGF) monoclonal antibody and bevacizumab could have immunomodulatory properties. It is known that VEGF can trigger T regulatory cell proliferation, increase MDSCs infiltration in the TME, and it can also favor CTLs exhaustion by the upregulation of the suppressive immune checkpoint molecule [206]. Therefore, it is a compelling rationale for the association of anti-VEGF with ICIs [207,208]. From this perspective, a clinical study evaluated the activity of the combination between bevacizumab and anti-PD-L1 atezolizumab (cohort A), or the same combination associated with modified FOLFOX6 chemotherapy (cohort B) in mCRC patients. In cohort A, one patient achieved partial response (ORR 1/14), and nine patients had stable disease. In cohort B, the ORR was 52% (12/23), and a median PFS was 14.1 months. The phase Ib REGONUVO trial assessed the efficacy and safety of regorafenib (80–160 mg/day) and nivolumab (3 mg/kg) in metastatic gastric cancer and mCRC. The study included 25 mCRC, from whom 24 (96%) cases had MSS/pMMR phenotype. The results showed an ORR of 36% in the mCRC cohort. The median PFS was 7.9 months, and the median OS was not reached [209]. These preliminary results suggesting a potential synergistic activity must be confirmed in more extensive randomized trials [210].
Moreover, early phase trials are ongoing using ICIs and antiangiogenic molecules in mCRC: NCT03396926 (pembrolizumab + capecitabine + bevacizumab), NCT03081494 (anti-PD-1 inhibitor (PDR001) + regorafenib), and NCT02848443 (nivolumab + TAS-2+oxaliplatin + bevacizumab).

5.2.4. Immunotherapy with MEK Inhibition

MEK is an essential signaling molecule in the MARK pathway. Preclinical and clinical trials suggested that the inhibition of MEK in association with ICIs could up-regulate MHC class I and increase CD8+ infiltration in the tumor microenvironment, thereby generating a more effective antitumor activity [211,212]. Promising results came from an early phase I clinical trial in chemo-refractory mCRC patients evaluating the combination of the MEK inhibitor Cobimetinib with Atezolizumab, with an ORR of 17% (4/21). However, a confirmatory phase III clinical study investigating the use of atezolizumab with or without cobimetinib failed to replicate the clinical benefit over regorafenib (a multi-tyrosine kinase inhibitor) in patients with chemo-refractory MSI-L/pMMR mCRC (Table 3). The CheckMate 9N9 phase 1/2 trial is currently evaluating the efficacy and safety of nivolumab ± ipilimumab in combination with tremelimumab (MEK inhibitor) in recurrent mCRC patients (NCT03377361).

5.2.5. Immunotherapy with Colony-Stimulating Factor 1 Receptor

MDSCs represent a heterogeneous population of relatively immature myeloid cells demonstrated to display a powerful immunosuppressive activity in numerous solid tumors, including CRC [213,214,215]. Colony-stimulating Factor 1 Receptor (CSF1R) is present on the monocyte surface, and its activation by the colony-stimulating factor (CSF) could promote the differentiation in MDSCc. It was hypothesized that inhibiting CSF1R will lead to suppression of MDSCc, and therefore delayed tumor growth [213]. A phase I clinical study including patients with pancreatic and CRC found the association between durvalumab (anti-PD-L1) and pexidartinib (CSF1 R inhibitor) to have an acceptable toxicity profile with no unexpected events. Further clinical data are expected in this regard [216].

5.2.6. Immunotherapy with Carcinoembryonic Antigen T-Cell Bispecific

Carcinoembryonic antigen (CEA), part of the immunoglobulin supergene family, is overexpressed in most mCRC. CEA CD3 T-cell bispecific (TCB) represents a TCB antibody that can bind simultaneously at CD3 of T-cells and CEA on tumor cells. Tabernero et al. evaluated the efficacy of CEA TCB alone or combined with atezolizumab in chemo-refractory mCRC. In the monotherapy cohort (31 patients), two (6%) patients had a partial response, and the disease control rate was 45%. In the second cohort (11 patients), seven (64%) patients had stable disease, and two (18%) cases had a partial response. However, CEA TCB treatment had a complex safety profile which might be an issue for its future development [217].

6. Conclusions

Despite notable improvements in the diagnosis and treatment of CRC patients, the metastatic disease still has a poor prognosis with a median OS of 30 months. In recent years, we have witnessed the remarkable impact generated by immunotherapy in selected tumors. To date, most digestive tumors benefit very little from these therapeutic strategies. MSI-H/dMMR mCRC patients demonstrated an objective and sustained response to immunotherapy. However, given the heterogeneity of tumors and environmental conditions, even in this selected subset of patients, intrinsic and acquired resistance was described. Furthermore, predictive, and prognostic biomarkers and genetic alterations that could impair the efficacy of ICIs are still suboptimal. The current evidence regarding the response to ICIs suggests that predictive models would be more helpful than single biomarkers. Moreover, to enhance the efficacy of immunotherapy, we need an improved phenotypic description of the immune cells and a comprehensive understanding of the TME.
Future technological progress is expected to deepen our knowledge of the immune system by focusing on the entire genome, detecting new immune cells with clinical relevance, and developing new approaches to target cancer cells precisely. Further insight into innate and acquired resistance will lead to optimal combinatorial strategies to counteract immune escape.

Author Contributions

Conceptualization, A.G., D.G. and D.S.; methodology A.G. and D.S.; investigation A.G., D.G. and D.S.; writing—original draft preparation, A.G., D.G., S.R.V., C.V.L. and D.S.; writing—review and editing A.G., D.G., S.R.V., C.V.L. and D.S; visualization A.G. and D.S.; supervision D.S, S.R.V., C.V.L. and C.B.; funding acquisition A.G, D.S. and C.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Acknowledgments

The authors would like to acknowledge the support of the National Romanian Society of Medical Oncology for the payment of the APC.

Conflicts of Interest

The authors declare no conflict of interest.

Glossary

AAAfrican American
AEadverse events
B. FragilisBacillus Fragilis
B2Mβ2 microglobulin
BRAFv-raf murine sarcoma viral oncogene homolog B1
CARchimeric antigen receptor
CEAcarcinoembryonic antigen
CIMPCpG island methylator phenotype
CRcomplete response
CRCcolorectal cancer
AEadverse events
B. FragilisBacillus Fragilis
B2Mβ2 microglobulin
BRAFv-raf murine sarcoma viral oncogene homolog B1
CARchimeric antigen receptor
CEAcarcinoembryonic antigen
CIMPCpG island methylator phenotype
CRcomplete response
CRCcolorectal cancer
CSFcolony-stimulating factor
CSF1Rcolony-stimulating factor 1 receptor
CTLA4cytotoxic T lymphocyte-associated antigen 4
DCRdisease control rate
DFSdisease-free survival
dMMRmismatch repair
F. nucleatumFusobacterium Nucleatum
HDACihistone deacetylase inhibitors
HER2human epidermal growth factor 2
HLAhuman leukocyte antigen
HMAsmethyltransferase inhibitors
ICIimmune checkpoint inhibitors
ICOSinducible T-cell costimulator
IFN-γinterferon-γ
IgG4immunoglobulin G4
JAKJanus kinase
JAK1 and JAK2Janus kinases 1 and 2
KRASKirsten rat sarcoma 2 viral oncogene homolog

Abbreviations

mAbsmonoclonal antibodies
MAGEmelanoma associated antigen
mCRCmetastatic colorectal cancer
MDSCcmyeloid-derivated suppressor cells
MEKacronym for MAPK/ERK Kinase-extracellular signal-regulated kinase/extracellular signal-regulated kinase
MHC Imajor histocompatibility complex I
MLH1human mutL homolog 1
MLH6human mutL homolog 6
MMRmismatch repair
MSH2MutS Homolog 2
MSImicrosatellite instability
MSI-Hmicrosatellite instability-high
MSI-Lmicrosatellite instability-low
MSSmicrosatellite stable
NCRsnegative checkpoint regulators
NGSnext generation sequencing
NKnatural killer
NRASneuroblastoma RAS viral oncogene homolog
NTRKNeurotrophic tyrosine receptor kinase
ORRoverall response rate
OSoverall survival
PD-1programmed cell death-1
PD-Lprogrammed cell death-ligand 1
PFSprogression free survival
PI3K-AKT-mTORPhosphoinositide 3-kinases-Protein kinase B-mechanistic target of rapamycin
PLGF2placental growth factor 2
POLD1 DNApolymerase delta
POLE DNApolymerase epsilon
RASrat sarcoma 2 viral oncogene homolog
RP2Drecommended phase 2 dose
RRresponse rate
STATssignal transducer and activator of transcription proteins
TAAtumor associated antigens
TCGATumor Cancer Genome Atlas
TCRT-cell receptor
TILtumor infiltrating lymphocytes
TMBtumor mutational burden
TMB-Htumor mutational burden-high
TMEtumor microenvironment
TNFRSFtumor necrosis factor receptor superfamily
TNFαtumor necrosis factor-α
TNMtumor node metastasis
TSAstumor specific antigens
VEGFvascular endothelial growth factor
VISTA Vdomain Ig suppressor of T cell activation
WHOworld health organization

References

  1. Ganesh, K.; Stadler, Z.K.; Cercek, A.; Mendelsohn, R.B.; Shia, J.; Segal, N.H.; Diaz, L.A., Jr. Immunotherapy in colorectal cancer: Rationale, challenges and potential. Nat. Rev. Gastroenterol. Hepatol. 2019, 16, 361–375. [Google Scholar] [CrossRef] [PubMed]
  2. Hull, R.; Francies, F.Z.; Oyomno, M.; Dlamini, Z. Colorectal Cancer Genetics, Incidence and Risk Factors: In Search for Targeted Therapies. Cancer Manag. Res. 2020, 12, 9869–9882. [Google Scholar] [CrossRef]
  3. Sharma, I.; Kim, S.; Sridhar, S.; Basha, R. Colorectal Cancer: An Emphasis on Factors Influencing Racial/Ethnic Disparities. Crit. Rev. Oncog. 2020, 25, 151–160. [Google Scholar] [CrossRef] [PubMed]
  4. Ollberding, N.J.; Nomura, A.M.; Wilkens, L.R.; Henderson, B.E.; Kolonel, L.N. Racial/ethnic differences in colorectal cancer risk: The multiethnic cohort study. Int. J. Cancer 2010, 129, 1899–1906. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Siegel, R.; DeSantis, C.; Jemal, A. Colorectal cancer statistics, 2014. CA A Cancer J. Clin. 2014, 64, 104–117. [Google Scholar] [CrossRef] [PubMed]
  6. Loupakis, F.; Cremolini, C.; Masi, G.; Lonardi, S.; Zagonel, V.; Salvatore, L.; Cortesi, E.; Tomasello, G.; Ronzoni, M.; Spadi, R.; et al. Initial Therapy with FOLFOXIRI and Bevacizumab for Metastatic Colorectal Cancer. N. Engl. J. Med. 2014, 371, 1609–1618. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Xynos, E.; Gouvas, N.; Triantopoulou, C.; Tekkis, P.; Vini, L.; Tzardi, M.; Boukovinas, I.; Androulakis, N.; Athanasiadis, A.; Christodoulou, C.; et al. Clinical practice guidelines for the surgical management of colon cancer: A consensus statement of the hellenic and cypriotolorectal cancer study group by the HeSMO. Ann. Gastroenterol. 2016, 29, 3–17. [Google Scholar] [PubMed]
  8. Bertero, L.; Massa, F.; Metovic, J.; Zanetti, R.; Castellano, I.; Ricardi, U.; Papotti, M.; Cassoni, P. Eighth Edition of the UICC Classification of Malignant Tumours: An overview of the changes in the pathological TNM classification criteria—What has changed and why? Virchows Arch. 2018, 472, 519–531. [Google Scholar] [CrossRef]
  9. Wells, K.O.; Hawkins, A.T.; Krishnamurthy, D.M.; Dharmarajan, S.; Glasgow, S.C.; Hunt, S.R.; Mutch, M.G.; Wise, P.; Silviera, M.L. Omission of Adjuvant Chemo-therapy Is Associated with Increased Mortality in Patients with T3N0 Colon Cancer with Inadequate Lymph Node Harvest. Dis. Colon Rectum 2017, 15–21. [Google Scholar] [CrossRef]
  10. Loree, J.M.; Mulder, K.E.; Ghosh, S.; Spratlin, J.L. CAPOX Associated with Toxicities of Higher Grade but Improved Disease-Free Survival When Compared with FOLFOX in the Adjuvant Treatment of Stage III Colon Cancer. Clin. Colorectal Cancer 2014, 13, 172–177. [Google Scholar] [CrossRef]
  11. André, T.; Boni, C.; Navarro, M.; Tabernero, J.; Hickish, T.; Topham, C.; Bonetti, A.; Clingan, P.; Bridgewater, J.; Rivera, F.; et al. Improved Overall Survival with Oxaliplatin, Fluorouracil, and Leucovorin as Adjuvant Treatment in Stage II or III Colon Cancer in the MOSAIC Trial. J. Clin. Oncol. 2009, 27, 3109–3116. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Yothers, G.; O’Connell, M.J.; Allegra, C.J.; Kuebler, J.P.; Colangelo, L.H.; Petrelli, N.J.; Wolmark, N. Oxaliplatin as Adjuvant Therapy for Colon Cancer: Updated Results of NSABP C-07 Trial, Including Survival and Subset Analyses. J. Clin. Oncol. 2011, 29, 3768–3774. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Schmoll, H.-J.; Tabernero, J.; Maroun, J.; de Braud, F.G.M.; Price, T.; Van Cutsem, E.; Hill, M.; Hoersch, S.; Rittweger, K.; Haller, D.G. Capecitabine Plus Oxaliplatin Compared with Fluorouracil/Folinic Acid as Adjuvant Therapy for Stage III Colon Cancer: Final Results of the NO16968 Randomized Controlled Phase III Trial. J. Clin. Oncol. 2015, 33, 3733–3740. [Google Scholar] [CrossRef]
  14. Punt, C.J.A.; Koopman, M.; Vermeulen, L. From tumour heterogeneity to advances in precision treatment of colorectal cancer. Nat. Rev. Clin. Oncol. 2016, 14, 235–246. [Google Scholar] [CrossRef]
  15. Huiskens, J.; Van Gulik, T.M.; Van Lienden, K.P.; Engelbrecht, M.R.; Meijer, G.A.; Van Grieken, N.C.; Schriek, J.; Keijser, A.; Mol, L.; Molenaar, I.Q.; et al. Treatment strategies in colorectal cancer patients with initially unresectable liver-only metastases: The randomized phase III CAIRO5 study of the Dutch Colorectal Cancer Group. J. Clin. Oncol. 2015, 33, TPS3622. [Google Scholar] [CrossRef]
  16. Modest, D.P.; Pant, S.; Sartore-Bianchi, A. Treatment sequencing in metastatic colorectal cancer. Eur. J. Cancer 2019, 109, 70–83. [Google Scholar] [CrossRef] [PubMed]
  17. Goodwin, R.A.; Asmis, T.R. Overview of Systemic Therapy for Colorectal Cancer. Clin. Colon Rectal Surg. 2009, 22, 251–256. [Google Scholar] [CrossRef] [Green Version]
  18. Douillard, J.Y.; Siena, S.; Cassidy, J.; Tabernero, J.; Burkes, R.; Barugel, M.; Humblet, Y.; Bodoky, G.; Cunningham, D.; Jassem, J.; et al. Final results from PRIME: Randomized phase III study of panitumumab with FOLFOX4 for first-line treatment of metastatic colorectal cancer. Ann. Oncol. 2014, 25, 1346–1355. [Google Scholar] [CrossRef]
  19. Van Cutsem, E.; Köhne, C.H.; Hitre, E.; Zaluski, J.; Chang Chien, C.R.; Makhson, A.; D’Haens, G.; Pintér, T.; Lim, R.; Bodoky, G.; et al. Cetuximab and Chemotherapy as Initial Treatment for Metastatic Colorectal Cancer. N. Engl. J. Med. 2009, 360, 1408–1417. [Google Scholar] [CrossRef] [Green Version]
  20. Verdaguer, H.; Tabernero, J.; Macarulla, T. Ramucirumab in metastatic colorectal cancer: Evidence to date and place in therapy. Ther. Adv. Med. Oncol. 2016, 8, 230–242. [Google Scholar] [CrossRef] [Green Version]
  21. Syed, Y.Y.; McKeage, K. Aflibercept: A Review in Metastatic Colorectal Cancer. Drugs 2015, 75, 1435–1445. [Google Scholar] [CrossRef]
  22. Grothey, A.; Van Cutsem, E.; Sobrero, A.; Siena, S.; Falcone, A.; Ychou, M.; Humblet, Y.; Bouché, O.; Mineur, L.; Barone, C.; et al. Regorafenib monotherapy for previously treated metastatic colorectal cancer (CORRECT): An international, multicentre, randomised, placebo-controlled, phase 3 trial. Lancet 2013, 381, 303–312. [Google Scholar] [CrossRef]
  23. Borghaei, H.; Paz-Ares, L.; Horn, L.; Spigel, D.R.; Steins, M.; Ready, N.E.; Chow, L.Q.; Vokes, E.E.; Felip, E.; Holgado, E.; et al. Nivolumab versus Docetaxel in Advanced Nonsquamous Non-Small-Cell Lung Cancer. N. Engl. J. Med. 2015, 373, 1627–1639. [Google Scholar] [CrossRef]
  24. Bellmunt, J.; De Wit, R.; Vaughn, D.J.; Fradet, Y.; Lee, J.-L.; Fong, L.; Vogelzang, N.J.; Climent, M.A.; Petrylak, D.P.; Choueiri, T.K.; et al. Pembrolizumab as Second-Line Therapy for Advanced Urothelial Carcinoma. N. Engl. J. Med. 2017, 376, 1015–1026. [Google Scholar] [CrossRef] [Green Version]
  25. Choueiri, T.K.; Larkin, J.; Oya, M.; Thistlethwaite, F.; Martignoni, M.; Nathan, P.; Powles, T.; McDermott, D.; Robbins, P.B.; Chism, D.D.; et al. Preliminary results for avelumab plus axitinib as first-line therapy in patients with advanced clear-cell renal-cell carcinoma (JAVELIN Renal 100): An open-label, dose-finding and dose-expansion, phase 1b trial. Lancet Oncol. 2018, 19, 451–460. [Google Scholar] [CrossRef]
  26. Müller, M.F.; Ibrahim, A.E.K.; Arends, M.J. Molecular pathological classification of colorectal cancer. Virchows Arch. 2016, 469, 125–134. [Google Scholar] [CrossRef] [Green Version]
  27. Le, D.T.; Uram, J.N.; Wang, H.; Bartlett, B.R.; Kemberling, H.; Eyring, A.D.; Skora, A.D.; Luber, B.S.; Azad, N.S.; Laheru, D.; et al. PD-1 Blockade in Tumors with Mismatch-Repair Deficiency. N. Engl. J. Med. 2015, 372, 2509–2520. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Sumransub, N.; Vantanasiri, K.; Prakash, A.; Lou, E. Advances and new frontiers for immunotherapy in colorectal cancer: Setting the stage for neoadjuvant success? Mol. Ther. Oncolytics 2021, 2, 1–12. [Google Scholar] [CrossRef] [PubMed]
  29. Sun, B.L. Current microsatellite instability testing in management of colorectal cancer. Clinical Colorectal Cancer. 2021, 20, e12–e20. [Google Scholar] [CrossRef]
  30. Ding, Y.; Weng, S.; Li, X.; Zhang, D.; Aisa, A.; Yuan, Y. General treatment for metastatic colorectal cancer: From KEYNOTE 177 study. Transl. Oncol. 2021, 14, 101122. [Google Scholar] [CrossRef]
  31. Kanani, A.; Veen, T.; Søreide, K. Neoadjuvant immunotherapy in primary and metastatic colorectal cancer. Br. J. Surg. 2021, 108, 1417–1425. [Google Scholar] [CrossRef] [PubMed]
  32. De la Chapelle, A. Microsatellite Instability. N. Engl. J. Med. 2009, 349, 209–210. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Jascur, T.; Boland, C.R. Structure and function of the components of the human DNA mismatch repair system. Int. J. Cancer 2006, 119, 2030–2035. [Google Scholar] [CrossRef] [PubMed]
  34. Battaglin, F.; Naseem, M.; Lenz, H.J.; Salem, M.E. Microsatellite Instability in Colorectal Cancer: Overview of Its Clinical Signifi-cance and Novel Perspectives. Clin. Adv. Hematol. Oncol. 2018, 16, 735. [Google Scholar] [PubMed]
  35. Gelsomino, F.; Barbolini, M.; Spallanzani, A.; Pugliese, G.; Cascinu, S. The evolving role of microsatellite instability in colorectal cancer: A review. Cancer Treat. Rev. 2016, 51, 19–26. [Google Scholar] [CrossRef] [Green Version]
  36. McConechy, M.; Talhouk, A.; Li-Chang, H.; Leung, S.; Huntsman, D.; Gilks, C.; McAlpine, J. Detection of DNA mismatch repair (MMR) deficiencies by immunohistochemistry can effectively diagnose the microsatellite instability (MSI) phenotype in endometrial carcinomas. Gynecol. Oncol. 2015, 137, 306–310. [Google Scholar] [CrossRef] [PubMed]
  37. Boland, C.R.; Goel, A. Microsatellite Instability in Colorectal Cancer. Gastroenterology 2010, 138, 2073–2087. [Google Scholar] [CrossRef]
  38. Ashktorab, H.; Smoot, D.T.; Carethers, J.M.; Rahmanian, M.; Kittles, R.; Vosganian, G.; Doura, M.; Nidhiry, E.; Naab, T.; Momen, B.; et al. High incidence of microsatellite instability in colorectal cancer from African Americans. Clin. Cancer Res. 2003, 9. [Google Scholar]
  39. Brim, H.; Mokarram, P.; Naghibalhossaini, F.; Saberi-Firoozi, M.; Al-Mandhari, M.; Al-Mawaly, K.; Al-Mjeni, R.; Al-Sayegh, A.; Raeburn, S.; Lee, E.; et al. Impact of BRAF, MLH1 on the incidence of microsatellite instability high colorectal cancer in populations based study. Mol. Cancer 2008, 7, 68. [Google Scholar] [CrossRef] [Green Version]
  40. Ashktorab, H.; Smoot, D.T.; Farzanmehr, H.; Fidelia-Lambert, M.; Momen, B.; Hylind, L.; Iacosozio-Dononue, C.; Carethers, J.M.; Goel, A.; Boland, C.R.; et al. Clinicopathological features and microsatellite instability (MSI) in colorectal cancers from African Americans. Int. J. Cancer 2005, 116, 914–919. [Google Scholar] [CrossRef] [Green Version]
  41. Bai, W.; Ma, J.; Liu, Y.; Liang, J.; Wu, Y.; Yang, X.; Xu, E.; Li, Y.; Xi, Y. Screening of MSI detection loci and their heterogeneity in East Asian colorectal cancer patients. Cancer Med. 2019, 8, 2157–2166. [Google Scholar] [CrossRef] [Green Version]
  42. Soliman, A.S.; Bondy, M.L.; El-Badawy, S.A.; Mokhtar, N.; Eissa, S.; Bayoumy, S.; Seifeldin, I.A.; Houlihan, P.S.; Lukish, J.R.; Watanabe, T.; et al. Contrasting molecular pathology of colorectal carcinoma in Egyptian and Western patients. Br. J. Cancer 2001, 85, 1037–1046. [Google Scholar] [CrossRef] [Green Version]
  43. Pandey, V.; Prabhu, J.S.; Payal, K.; Rajan, V.; Deepak, C.; Barde, S.; Jagannath, P.; Borges, A.; Sridhar, T.S. Assessment of microsatellite instability in colorectal carci-noma at an Indian center. Int. J. Colorectal Dis. 2007, 22, 777–872. [Google Scholar] [CrossRef]
  44. Ciardiello, D.; Vitiello, P.P.; Cardone, C.; Martini, G.; Troiani, T.; Martinelli, E.; Ciardiello, F. Immunotherapy of colorectal cancer: Challenges for therapeutic efficacy. Cancer Treat. Rev. 2019, 76, 22–32. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Fan, A.; Wang, B.; Wang, X.; Nie, Y.; Fan, D.; Zhao, X.; Lu, Y. Immunotherapy in colorectal cancer: Current Achievements and Future Perspective. Int. J. Biol. Sci. 2021, 17, 3837–3849. [Google Scholar] [CrossRef]
  46. Le, D.T.; Kim, T.W.; Van Cutsem, E.; Geva, R.; Jäger, D.; Hara, H.; Burge, M.; O’Neil, B.; Kavan, P.; Yoshino, T.; et al. Phase II Open-Label Study of Pembrolizumab in Treatment-Refractory, Microsatellite Instability-High/Mismatch Repair-Deficient Metastatic Colorectal Cancer: KEYNOTE-164. J. Clin. Oncol. 2019, 38, 11–19. [Google Scholar] [CrossRef] [PubMed]
  47. De’angelis, G.L.; Bottarelli, L.; Azzoni, C.; De’angelis, C.; Leandro, N.; Di Mario, G.; Gaiani, F.; Negri, F. Microsatellite instability in colorectal cancer. Acta Biomed. 2018, 89, 97–101. [Google Scholar]
  48. Popat, S.; Hubner, R.; Houlston, R.S. Systematic Review of Microsatellite Instability and Colorectal Cancer Prognosis. J. Clin. Oncol. 2005, 23, 609–618. [Google Scholar] [CrossRef]
  49. Gupta, R.; Sinha, S.; Paul, R.N. The impact of microsatellite stability status in colorectal cancer. Curr. Probl. Cancer 2018, 42, 548–559. [Google Scholar] [CrossRef]
  50. Goodman, A.M.; Kato, S.; Bazhenova, L.; Patel, S.P.; Frampton, G.M.; Miller, V.; Stephens, P.J.; Daniels, G.A.; Kurzrock, R. Tumor Mutational Burden as an Independent Predictor of Response to Immunotherapy in Diverse Cancers. Mol. Cancer Ther. 2017, 16, 2598–2608. [Google Scholar] [CrossRef] [Green Version]
  51. Kim, J.Y.; Kronbichler, A.; Eisenhut, M.; Hong, S.H.; Van Der Vliet, H.J.; Kang, J.; Shin, J.I.; Gamerith, G. Tumor Mutational Burden and Efficacy of Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis. Cancers 2019, 11, 1798. [Google Scholar] [CrossRef] [Green Version]
  52. Subbiah, V.; Solit, D.; Chan, T.; Kurzrock, R. The FDA approval of pembrolizumab for adult and pediatric patients with tumor mutational burden (TMB) ≥10: A decision centered on empowering patients and their physicians. Ann. Oncol. 2020, 31, 1115–1118. [Google Scholar] [CrossRef]
  53. Chung, H.C.; Ros, W.; Delord, J.P.; Perets, R.; Italiano, A.; Shapira-Frommer, R.; Manzuk, L.; Piha-Paul, S.A.; Xu, L.; Zeigenfuss, S.; et al. Efficacy and safety of pembrolizumab in pre-viously treated advanced cervical cancer: Results from the phase II KEYNOTE-158 study. J. Clin. Oncol. 2019, 37, 1470–1478. [Google Scholar] [CrossRef] [PubMed]
  54. Galon, J.; Costes, A.; Sanchez-Cabo, F.; Kirilovsky, A.; Mlecnik, B.; Lagorce-Pagès, C.; Tosolini, M.; Camus, M.; Berger, A.; Wind, P.; et al. Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome. Science 2006, 313, 1960–1964. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Galon, J.; Fridman, W.H.; Pagès, F. The Adaptive Immunologic Microenvironment in Colorectal Cancer: A Novel Perspective: Figure 1. Cancer Res. 2007, 67, 1883–1886. [Google Scholar] [CrossRef] [Green Version]
  56. Angell, H.K.; Bruni, D.; Barrett, J.C.; Herbst, R.; Galon, J. The Immunoscore: Colon Cancer and Beyond. Clin. Cancer Res. 2019, 26, 332–339. [Google Scholar] [CrossRef] [Green Version]
  57. Walkowska, J.; Kallemose, T.; Jönsson, G.; Jönsson, M.; Andersen, O.; Andersen, M.H.; Svane, I.M.; Langkilde, A.; Nilbert, M.; Therkildsen, C. Immunoprofiles of colorectal cancer from Lynch syndrome. OncoImmunology 2018, 8, e1515612. [Google Scholar] [CrossRef] [PubMed]
  58. Galon, J.; Lanzi, A. Immunoscore and its introduction in clinical practice. Q. J. Nucl. Med. Mol. Imaging 2020, 64, 152–161. [Google Scholar] [CrossRef]
  59. Galon, J.; Mlecnik, B.; Marliot, F.; Ou, F.-S.; Bifulco, C.B.; Lugli, A.; Zlobec, I.; Rau, T.T.; Hartmann, A.; Masucci, G.V.; et al. Validation of the Immunoscore (IM) as a prognostic marker in Stage I/II/III colon cancer: Results of a worldwide consortium-based analysis of 1,336 patients. J. Clin. Oncol. 2016, 34 (Suppl. 15), 3500. [Google Scholar] [CrossRef]
  60. Kirilovsky, A.; Marliot, F.; El Sissy, C.; Haicheur, N.; Galon, J.; Pagès, F. Rational bases for the use of the Immunoscore in routine clinical settings as a prognostic and predictive biomarker in cancer patients. Int. Immunol. 2016, 28, 373–382. [Google Scholar] [CrossRef] [Green Version]
  61. Marliot, F.; Chen, X.; Kirilovsky, A.; Sbarrato, T.; El Sissy, C.; Batista, L.; Eynde, M.V.D.; Haicheur-Adjouri, N.; Anitei, M.-G.; Musina, A.-M.; et al. Analytical validation of the Immunoscore and its associated prognostic value in patients with colon cancer. J. Immunother. Cancer 2020, 8, e000272. [Google Scholar] [CrossRef]
  62. Marliot, F.; Lafontaine, L.; Galon, J. Immunoscore assay for the immune classification of solid tumors: Technical aspects, improvements and clinical perspectives. Methods Enzymol. 2019, 636, 109–128. [Google Scholar] [CrossRef] [PubMed]
  63. Pagès, F.; Mlecnik, B.; Marliot, F.; Bindea, G.; Ou, F.-S.; Bifulco, C.; Lugli, A.; Zlobec, I.; Rau, T.T.; Berger, M.D.; et al. International validation of the consensus Immunoscore for the classification of colon cancer: A prognostic and accuracy study. Lancet 2018, 391, 2128–2139. [Google Scholar] [CrossRef]
  64. Sinicrope, F.A.; Shi, Q.; Hermitte, F.; Heying, E.N.; Benson, A.B.; Gill, S.; Goldberg, R.M.; Kahlenberg, M.S.; Nair, S.; Shields, A.F.; et al. Association of immune markers and Immunoscore with survival of stage III colon carcinoma (CC) patients (pts) treated with adjuvant FOLFOX: NCCTG N0147 (Alliance). J. Clin. Oncol. 2017, 35, 3579. [Google Scholar] [CrossRef]
  65. Pagès, F.; André, T.; Taieb, J.; Vernerey, D.; Henriques, J.; Borg, C.; Marliot, F.; Jannet, R.B.; Louvet, C.; Mineur, L.; et al. Prognostic and predictive value of the Immunoscore in stage III colon cancer patients treated with oxaliplatin in the prospective IDEA France PRODIGE-GERCOR cohort study. Ann. Oncol. 2020, 31, 921–929. [Google Scholar] [CrossRef]
  66. Bruni, D.; Angell, H.K.; Galon, J. The immune contexture and Immunoscore in cancer prognosis and therapeutic efficacy. Nat. Cancer 2020, 20, 662–680. [Google Scholar] [CrossRef] [PubMed]
  67. Subrahmanyam, P.B.; Dong, Z.; Gusenleitner, D.; Giobbie-Hurder, A.; Severgnini, M.; Zhou, J.; Manos, M.; Eastman, L.M.; Maecker, H.T.; Hodi, F.S. Distinct predictive biomarker candidates for response to anti-CTLA-4 and anti-PD-1 immunotherapy in melanoma patients. J. Immunother. Cancer 2018, 6, 18. [Google Scholar] [CrossRef]
  68. Quezada-Marín, J.I.; Lam, A.K.; Ochiai, A.; Odze, R.D.; Washington, K.M.; Fukayama, M.; Rugge, M.; Klimstra, D.S.; Nagtegaal, I.D.; Tan, P.-H.; et al. Gastrointestinal tissue-based molecular biomarkers: A practical categorisation based on the 2019 World Health Organization classification of epithelial digestive tumours. Histopathology 2020, 77, 340–350. [Google Scholar] [CrossRef]
  69. Galon, J.; Mlecnik, B.; Bindea, G.; Angell, H.K.; Berger, A.; Lagorce, C.; Lugli, A.; Zlobec, I.; Hartmann, A.; Bifulco, C.; et al. Towards the introduction of the “Immunoscore” in the clas-sification of malignant tumours. J. Pathol. 2014, 232, 199–209. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  70. Wimmer, K.; Beilken, A.; Nustede, R.; Ripperger, T.; Lamottke, B.; Ure, B.; Steinmann, D.; Reineke-Plaass, T.; Lehmann, U.; Zschocke, J.; et al. A novel germline POLE mutation causes an early onset cancer prone syndrome mimicking constitutional mismatch repair deficiency. Fam. Cancer 2016, 16, 67–71. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  71. Magrin, L.; Fanale, D.; Brando, C.; Fiorino, A.; Corsini, L.R.; Sciacchitano, R.; Filorizzo, C.; Dimino, A.; Russo, A.; Bazan, V. POLE, POLD1, and NTHL1: The last but not the least hereditary cancer-predisposing genes. Oncogene 2021, 40, 5893–5901. [Google Scholar] [CrossRef]
  72. Mur, P.; García-Mulero, S.; del Valle, J.; Magraner-Pardo, L.; Vidal, A.; Pineda, M.; Cinnirella, G.; Martín-Ramos, E.; Pons, T.; López-Doriga, A.; et al. Role of POLE and POLD1 in familial cancer. Genet. Med. 2020, 22, 2089–2100. [Google Scholar] [CrossRef]
  73. Palles, C.; Cazier, J.-B.; Howarth, K.M.; Domingo, E.; Jones, A.M.; Broderick, P.; Kemp, Z.; Spain, S.L.; Almeida, E.G.; Salguero, I.; et al. Germline mutations affecting the proofreading domains of POLE and POLD1 predispose to colorectal adenomas and carcinomas. Nat. Genet. 2013, 45, 136–143. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Heitzer, E.; Tomlinson, I. Replicative DNA polymerase mutations in cancer. Curr. Opin. Genet. Dev. 2014, 24, 107–113. [Google Scholar] [CrossRef] [Green Version]
  75. Domingo, E.; Freeman-Mills, L.; Rayner, E.; Glaire, M.; Briggs, S.; Vermeulen, L.; Fessler, E.; Medema, J.P.; Boot, A.; Morreau, H.; et al. Somatic POLE proofreading domain mutation, immune response, and prognosis in colorectal cancer: A retrospective, pooled biomarker study. Lancet Gastroenterol. Hepatol. 2016, 1, 207–216. [Google Scholar] [CrossRef] [Green Version]
  76. Fakih, M.; Gong, J.; Wang, C.; Lee, P.P.; Chu, P. Molecular Insights in Patient Care Response to PD-1 Blockade in Microsatellite Stable Metastatic Colorectal Cancer Harboring a POLE Mutation. JNCCN—J. Natl. Compr. Cancer Netw. 2017, 15, 142–147. [Google Scholar]
  77. Van Gool, I.C.; Eggink, F.A.; Freeman-Mills, L.; Stelloo, E.; Marchi, E.; de Bruyn, M.; Palles, C.; Nout, R.A.; de Kroon, C.D.; Osse, E.M.; et al. POLE proofreading mutations elicit an antitumor immune response in endometrial cancer. Clin. Cancer Res. 2015, 21, 3347–3355. [Google Scholar] [CrossRef] [Green Version]
  78. Gandini, S.; Massi, D.; Mandalà, M. PD-L1 expression in cancer patients receiving anti PD-1/PD-L1 antibodies: A systematic review and meta-analysis. Crit. Rev. Oncol./Hematol 2016, 100, 88–98. [Google Scholar] [CrossRef]
  79. Patel, S.P.; Kurzrock, R. PD-L1 Expression as a Predictive Biomarker in Cancer Immunotherapy. Mol. Cancer Ther. 2015, 14, 847–856. [Google Scholar] [CrossRef] [Green Version]
  80. Hersom, M.; Jørgensen, J.T. Companion and complementary diagnostics-focus on PD-L1 expression assays for PD-1/PD-L1 checkpoint inhibitors in non-small cell lung cancer. Ther. Drug Monit. 2018, 40, 9–16. [Google Scholar] [CrossRef]
  81. André, T.; Overman, M.; Lonardi, S.; Aglietta, M.; McDermott, R.; Wong, K.Y.M.; Morse, M.; Hendlisz, A.; Moss, R.A.; Ledeine, J.-M.; et al. Analysis of tumor PD-L1 expression and biomarkers in relation to clinical activity in patients (PTS) with deficient DNA mismatch repair (dmmr)/high microsatellite instability (MSI-h) metastatic colorectal cancer (MCRC) treated with nivolumab (NIVO) + ipilimumab (IPI): Checkmate 142. Ann. Oncol. 2017, 28, v163. [Google Scholar] [CrossRef] [Green Version]
  82. Yang, L.; Xue, R.; Pan, C. Prognostic and clinicopathological value of PD-L1 in colorectal cancer: A systematic review and me-ta-analysis. OncoTargets Ther. 2019, 12, 3671–3682. [Google Scholar] [CrossRef] [PubMed]
  83. Yu, J.; Wang, X.; Teng, F.; Kong, L. PD-L1 expression in human cancers and its association with clinical outcomes. OncoTargets Ther. 2016, 9, 5023–5039. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  84. Huyghe, N.; Baldin, P.; Van Den Eynde, M. Immunotherapy with immune checkpoint inhibitors in colorectal cancer: What is the future beyond deficient mismatch-repair tumours? Gastroenterol. Rep. 2020, 8, 11–24. [Google Scholar] [CrossRef] [Green Version]
  85. Johdi, N.A.; Sukor, N.F. Colorectal Cancer Immunotherapy: Options and Strategies. Front. Immunol. 2020, 11. [Google Scholar] [CrossRef] [PubMed]
  86. Galluzzi, L.; Vacchelli, E.; Bravo-San Pedro, J.M.; Buqué, A.; Senovilla, L.; Baracco, E.E.; Bloy, N.; Castoldi, F.; Abastado, J.P.; Agostinis, P. Classification of current anticancer immuno-therapies. Oncotarget 2014, 5, 12472. [Google Scholar] [CrossRef] [Green Version]
  87. Li, X.; Shao, C.; Shi, Y.; Han, W. Lessons learned from the blockade of immune checkpoints in cancer immunotherapy. J. Hematol. Oncol. 2018, 11, 1–26. [Google Scholar] [CrossRef]
  88. Jain, P.; Jain, C.; Velcheti, V. Role of immune-checkpoint inhibitors in lung cancer. Ther. Adv. Respir. Dis. 2018, 12. [Google Scholar] [CrossRef] [Green Version]
  89. Jung, G.; Benítez-Ribas, D.; Sánchez, A.; Balaguer, F. Current Treatments of Metastatic Colorectal Cancer with Immune Check-point Inhibitors—2020 Update. J. Clin. Med. 2020, 9, 3520. [Google Scholar] [CrossRef]
  90. Buchbinder, E.I.; Desai, A. CTLA-4 and PD-1 Pathways: Similarities, Differences, and Implications of Their Inhibition. Am. J. Clin. Oncol. 2016, 39, 98. [Google Scholar] [CrossRef] [Green Version]
  91. Topalian, S.L.; Hodi, F.S.; Brahmer, J.R.; Gettinger, S.N.; Smith, D.C.; McDermott, D.F.; Powderly, J.D.; Carvajal, R.D.; Sosman, J.A.; Atkins, M.B. Safety, Activity, and Immune Correlates of Anti–PD-1 Antibody in Cancer. N. Engl. J. Med. 2012, 366, 2443–2454. [Google Scholar] [CrossRef] [PubMed]
  92. Brahmer, J.R.; Drake, C.G.; Wollner, I.; Powderly, J.D.; Picus, J.; Sharfman, W.H.; Stankevich, E.; Pons, A.; Salay, T.M.; McMiller, T.L.; et al. Phase I study of single-agent anti-programmed death-1 (MDX-1106) in refractory solid tumors: Safety, clinical activity, pharmacodynamics, and immunologic correlates. J. Clin. Oncol. 2010, 28, 3167–3175. [Google Scholar] [CrossRef]
  93. Lipson, E.J.; Sharfman, W.H.; Drake, C.G.; Wollner, I.; Taube, J.M.; Anders, R.A.; Xu, H.; Yao, S.; Pons, A.; Chen, L.; et al. Durable Cancer Regression Off-Treatment and Effective Reinduction Therapy with an Anti-PD-1 Antibody. Clin. Cancer Res. 2012, 19, 462–468. [Google Scholar] [CrossRef] [Green Version]
  94. Khoja, L.; Butler, M.O.; Kang, S.P.; Ebbinghaus, S.; Joshua, A.M. Pembrolizumab. J. Immunother. Cancer 2015, 31, 1–13. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  95. Food and Drug Administration. In FDA Grants Accelerated Approval to Pembrolizumab for First Tissue/Site Agnostic Indication. Available online: https://www.fda.gov/drugs/resources-information-approved-drugs/fda-grants-accelerated-approval-pembrolizumab-first-tissuesite-agnostic-indication (accessed on 4 April 2021).
  96. André, T.; Shiu, K.-K.; Kim, T.W.; Jensen, B.V.; Jensen, L.H.; Punt, C.; Smith, D.; Garcia-Carbonero, R.; Benavides, M.; Gibbs, P.; et al. Pembrolizumab in Microsatellite-Instability–High Advanced Colorectal Cancer. N. Engl. J. Med. 2020, 383, 2207–2218. [Google Scholar] [CrossRef]
  97. Franke, A.J.; Skelton, W.P.; Starr, J.S.; Parekh, H.; Lee, J.J.; Overman, M.J.; Allegra, C.; George, T.J. Immunotherapy for colorectal cancer: A review of current and novel Therapeutic approaches. JNCI J. Natl. Cancer Inst. 2019, 111, 1131–1141. [Google Scholar] [CrossRef] [Green Version]
  98. Overman, M.J.; McDermott, R.; Leach, J.L.; Lonardi, S.; Lenz, H.-J.; Morse, M.A.; Desai, J.; Hill, A.; Axelson, M.; Moss, R.A.; et al. Nivolumab in patients with metastatic DNA mismatch repair-deficient or microsatellite instability-high colorectal cancer (CheckMate 142): An open-label, multicentre, phase 2 study. Lancet Oncol. 2017, 18, 1182–1191. [Google Scholar] [CrossRef]
  99. FDA Grants Nivolumab Accelerated Approval for MSI-H or dMMR Colorectal Cancer | FDA. Available online: https://www.fda.gov/drugs/resources-information-approved-drugs/fda-grants-nivolumab-accelerated-approval-msi-h-or-dmmr-colorectal-cancer (accessed on 15 December 2021).
  100. Overman, M.J.; Lonardi, S.; Wong, K.Y.M.; Lenz, H.-J.; Gelsomino, F.; Aglietta, M.; Morse, M.A.; Van Cutsem, E.; McDermott, R.; Hill, A.; et al. Durable Clinical Benefit with Nivolumab Plus Ipilimumab in DNA Mismatch Repair–Deficient/Microsatellite Instability–High Metastatic Colorectal Cancer. J. Clin. Oncol. 2018, 36, 773–779. [Google Scholar] [CrossRef]
  101. FDA Grants Accelerated Approval to Ipilimumab for MSI-H or dMMR Metastatic Colorectal Cancer | FDA [Internet]. Available online: https://www.fda.gov/drugs/resources-information-approved-drugs/fda-grants-accelerated-approval-ipilimumab-msi-h-or-dmmr-metastatic-colorectal-cancer (accessed on 7 August 2021).
  102. Lenz, H.-J.; Lonardi, S.; Zagonel, V.; Van Cutsem, E.; Limon, M.L.; Wong, K.Y.M.; Hendlisz, A.; Aglietta, M.; Garcia-Alfonso, P.; Neyns, B.; et al. Nivolumab plus low-dose ipilimumab as first-line therapy in microsatellite instability-high/DNA mismatch repair deficient metastatic colorectal cancer: Clinical update. J. Clin. Oncol. 2020, 38, 11. [Google Scholar] [CrossRef]
  103. Lenz, H.-J.; Van Cutsem, E.; Limon, M.L.; Wong, K.Y.M.; Hendlisz, A.; Aglietta, M.; García-Alfonso, P.; Neyns, B.; Luppi, G.; Cardin, D.B.; et al. First-Line Nivolumab Plus Low-Dose Ipilimumab for Microsatellite Instability-High/Mismatch Repair-Deficient Metastatic Colorectal Cancer: The Phase II CheckMate 142 Study. J. Clin. Oncol. 2022, 40, 161–170. [Google Scholar] [CrossRef] [PubMed]
  104. Kim, J.H.; Kim, S.Y.; Baek, J.Y.; Cha, Y.J.; Ahn, J.B.; Kim, H.S.; Lee, K.-W.; Kim, J.-W.; Kim, T.-Y.; Chang, W.J.; et al. A Phase II Study of Avelumab Monotherapy in Patients with Mismatch Repair-Deficient/Microsatellite Instability-High or POLE-Mutated Metastatic or Unresectable Colorectal Cancer. Cancer Res. Treat. 2020, 52, 1135–1144. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  105. Bourhis, J.; Stein, A.; de Boer, J.P.; Eynde, M.V.D.; Gold, K.A.; Stintzing, S.; Becker, J.C.; Moran, M.; Schroeder, A.; Pennock, G.; et al. Avelumab and cetuximab as a therapeutic combination: An overview of scientific rationale and current clinical trials in cancer. Cancer Treat. Rev. 2021, 97, 102172. [Google Scholar] [CrossRef]
  106. Chen, E.X.; Jonker, D.J.; Loree, J.; Kennecke, H.F.; Berry, S.R.; Couture, F.; Ahmad, C.E.; Goffin, J.R.; Kavan, P.; Harb, M.; et al. Effect of Combined Immune Checkpoint Inhibition vs Best Supportive Care Alone in Patients with Advanced Colorectal Cancer. JAMA Oncol. 2020, 6, 831–838. [Google Scholar] [CrossRef]
  107. Sinicrope, F.A.; Ou, F.-S.; Zemla, T.; Nixon, A.B.; Mody, K.; Levasseur, A.; Dueck, A.C.; Dhanarajan, A.R.; Lieu, C.H.; Cohen, D.J.; et al. Randomized trial of standard chemotherapy alone or combined with atezolizumab as adjuvant therapy for patients with stage III colon cancer and deficient mismatch repair (ATOMIC, Alliance A021502). J. Clin. Oncol. 2019, 37 (Suppl. S15), e15169. [Google Scholar] [CrossRef]
  108. Baimas-George, M.; Baker, E.; Kamionek, M.; Salmon, J.S.; Sastry, A.; Levi, D.; Vrochides, D. A Complete Pathological Response to Pem-brolizumab following ex vivo Liver Resection in a Patient with Colorectal Liver Metastases. Chemotherapy 2018, 63, 90–94. [Google Scholar] [CrossRef]
  109. Zhang, J.; Cai, J.; Deng, Y.; Wang, H. Complete response in patients with locally advanced rectal cancer after neoadjuvant treatment with nivolumab. OncoImmunology 2019, 8, e1663108. [Google Scholar] [CrossRef] [Green Version]
  110. Chalabi, M.; Fanchi, L.; Berg, J.V.D.; Beets, G.; Lopez-Yurda, M.; Aalbers, A.; Grootscholten, C.; Snaebjornsson, P.; Maas, M.; Mertz, M.; et al. Neoadjuvant ipilimumab plus nivolumab in early stage colon cancer. Ann. Oncol. 2018, 29, viii731. [Google Scholar] [CrossRef]
  111. Benson, A.B.; Venook, A.P.; Al-Hawary, M.M.; Arain, M.A.; Chen, Y.-J.; Ciombor, K.K.; Cohen, S.; Cooper, H.S.; Deming, D.; Farkas, L.; et al. Colon cancer, version 2.2021, NCCN clinical practice guidelines in oncology. J. Natl. Compr. Cancer Netw. 2021, 19, 329–359. [Google Scholar] [CrossRef] [PubMed]
  112. Wang, R.-F.; Wang, H.Y. Immune targets and neoantigens for cancer immunotherapy and precision medicine. Cell Res. 2016, 27, 11–37. [Google Scholar] [CrossRef] [Green Version]
  113. Smith, C.C.; Selitsky, S.R.; Chai, S.; Armistead, P.M.; Vincent, B.G.; Serody, J.S. Alternative tumour-specific antigens. Nat. Rev. Cancer 2019, 19, 465–478. [Google Scholar] [CrossRef]
  114. Richters, M.M.; Xia, H.; Campbell, K.M.; Gillanders, W.E.; Griffith, O.L.; Griffith, M. Best practices for bioinformatic characterization of neoantigens for clinical utility. Genome Med. 2019, 11, 1–21. [Google Scholar] [CrossRef]
  115. Fan, J.; Shang, D.; Han, B.; Song, J.; Chen, H.; Yang, J.-M. Adoptive cell transfer: Is it a promising immunotherapy for colorectal cancer? Theranostics. 2018, 8, 5784–5800. [Google Scholar] [CrossRef]
  116. Rosenberg, S.A.; Restifo, N.P. Adoptive cell transfer as personalized immunotherapy for human cancer. Science 2015, 348, 62–68. [Google Scholar] [CrossRef] [Green Version]
  117. Tran, E.; Turcotte, S.; Gros, A.; Robbins, P.F.; Lu, Y.-C.; Dudley, M.E.; Wunderlich, J.R.; Somerville, R.P.; Hogan, K.; Hinrichs, C.S.; et al. Cancer Immunotherapy Based on Mutation-Specific CD4+ T Cells in a Patient with Epithelial Cancer. Science 2014, 344, 641–645. [Google Scholar] [CrossRef]
  118. Zacharakis, N.; Chinnasamy, H.; Black, M.; Xu, H.; Lu, Y.-C.; Zheng, Z.; Pasetto, A.; Langhan, M.; Shelton, T.; Prickett, T.; et al. Immune recognition of somatic mutations leading to complete durable regression in metastatic breast cancer. Nat. Med. 2018, 24, 724–730. [Google Scholar] [CrossRef] [PubMed]
  119. Dudley, M.E.; Yang, J.C.; Sherry, R.; Hughes, M.S.; Royal, R.; Kammula, U.; Robbins, P.F.; Huang, J.; Citrin, D.E.; Leitman, S.F.; et al. Adoptive Cell Therapy for Patients with Metastatic Melanoma: Evaluation of Intensive Myeloablative Chemoradiation Preparative Regimens. J. Clin. Oncol. 2008, 26, 5233–5239. [Google Scholar] [CrossRef] [PubMed]
  120. Robbins, P.F.; Lu, Y.C.; El-Gamil, M.; Li, Y.F.; Gross, C.; Gartner, J.; Lin, J.C.; Teer, J.K.; Cliften, P.; Tycksen, E.; et al. Mining exomic sequencing data to identify mutated antigens recognized by adoptively transferred tumor-reactive T cells. Nat. Med. 2013, 19, 747–752. [Google Scholar] [CrossRef]
  121. Tran, E.; Robbins, P.F.; Lu, Y.-C.; Prickett, T.D.; Gartner, J.J.; Jia, L.; Pasetto, A.; Zheng, Z.; Ray, S.; Groh, E.M.; et al. T-Cell Transfer Therapy Targeting Mutant KRAS in Cancer. N. Engl. J. Med. 2016, 375, 2255–2262. [Google Scholar] [CrossRef] [Green Version]
  122. Li, H.; Yang, C.; Cheng, H.; Huang, S.; Zheng, Y. CAR-T cells for Colorectal Cancer: Target-selection and strategies for improved activity and safety. J. Cancer 2021, 12, 1804–1814. [Google Scholar] [CrossRef]
  123. Zhang, C.; Wang, Z.; Yang, Z.; Wang, M.; Li, S.; Li, Y.; Zhang, R.; Xiong, Z.; Wei, Z.; Shen, J.; et al. Phase I Escalating-Dose Trial of CAR-T Therapy Targeting CEA+ Met-astatic Colorectal Cancers. Mol. Ther. 2017, 25, 1248–1258. [Google Scholar] [CrossRef] [PubMed]
  124. Katz, S.C.; Burga, R.A.; McCormack, E.; Wang, L.J.; Mooring, W.; Point, G.R.; Khare, P.D.; Thorn, M.; Ma, Q.; Stainken, B.F.; et al. Phase I Hepatic Immunotherapy for Metastases Study of Intra-Arterial Chimeric Antigen Receptor–Modified T-cell Therapy for CEA+ Liver Metastases. Clin. Cancer Res. 2015, 21, 3149–3159. [Google Scholar] [CrossRef] [Green Version]
  125. Katz, S.; Point, G.R.; Cunetta, M.; Thorn, M.; Guha, P.; Espat, N.J.; Boutros, C.; Hanna, N.; Junghans, R.P. Regional CAR-T cell infusions for peritoneal carcinomatosis are superior to systemic delivery. Cancer Gene Ther. 2016, 23, 142–148. [Google Scholar] [CrossRef] [PubMed]
  126. Thomas, S.; Prendergast, G.C. Cancer Vaccines: A Brief Overview. In Vaccine Design; Springer: New York, NY, USA, 2016; Volume 1403, pp. 755–761. [Google Scholar] [CrossRef]
  127. Geevarghese, S.K.; Geller, D.A.; de Haan, H.A.; Hörer, M.; Knoll, A.E.; Mescheder, A.; Nemunaitis, J.; Reid, T.R.; Sze, D.Y.; Tanabe, K.K.; et al. Phase I/II Study of Oncolytic Herpes Simplex Virus NV1020 in Patients with Extensively Pretreated Refractory Colorectal Cancer Metastatic to the Liver. Hum. Gene Ther. 2010, 21, 1119. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  128. Kana, S.I.; Essani, K. Immuno-Oncolytic Viruses: Emerging Options in the Treatment of Colorectal Cancer. Mol. Diagn. Ther. 2021, 25, 301–313. [Google Scholar] [CrossRef] [PubMed]
  129. Shahnazari, M.; Samadi, P.; Pourjafar, M.; Jalali, A. Therapeutic vaccines for colorectal cancer: The progress and future prospect. Int. Immunopharmacol. 2020, 88, 106944. [Google Scholar] [CrossRef] [PubMed]
  130. Morse, M.A.; Niedzwiecki, D.; Marshall, J.L.; Garrett, C.; Chang, D.Z.; Aklilu, M.; Crocenzi, T.S.; Cole, D.J.; Dessureault, S.; Hobeika, A.C.; et al. A Randomized Phase II Study of Immunization with Dendritic Cells Modified with Poxvectors Encoding CEA and MUC1 Compared with the Same Poxvectors Plus GM-CSF for Resected Metastatic Colorectal Cancer. Ann. Surg. 2013, 258, 879–886. [Google Scholar] [CrossRef]
  131. Bednarczyk, R.A. Addressing HPV vaccine myths: Practical information for healthcare providers. Hum. Vaccines Immunother. 2019, 15, 1628–1638. [Google Scholar] [CrossRef]
  132. Berry, J.; Vreeland, T.; Trappey, A.; Hale, D.; Peace, K.; Tyler, J.; Walker, A.; Brown, R.; Herbert, G.; Yi, F.; et al. Cancer vaccines in colon and rectal cancer over the last decade: Lessons learned and future directions. Expert Rev. Clin. Immunol. 2016, 13, 235–245. [Google Scholar] [CrossRef]
  133. Jiang, S.; Good, D.; Wei, M.Q. Vaccinations for Colorectal Cancer: Progress, Strategies, and Novel Adjuvants. Int. J. Mol. Sci. 2019, 20, 3403. [Google Scholar] [CrossRef] [Green Version]
  134. De Mattos-Arruda, L.; Blanco-Heredia, J.; Aguilar-Gurrieri, C.; Carrillo, J.; Blanco, J. New emerging targets in cancer immuno-therapy: The role of neoantigens. ESMO Open 2020, 4 (Suppl. 3), e000684. [Google Scholar]
  135. Melero, I.; Gaudernack, G.; Gerritsen, W.R.; Huber, C.; Parmiani, G.; Scholl, S.; Thatcher, N.; Wagstaff, J.; Zielinski, C.C.; Faulkner, I.; et al. Therapeutic vaccines for cancer: An overview of clinical trials. Nat. Rev. Clin. Oncol. 2014, 11, 509–524. [Google Scholar] [CrossRef]
  136. Sahin, U.; Derhovanessian, E.; Miller, M.; Kloke, B.-P.; Simon, P.; Löwer, M.; Bukur, V.; Tadmor, A.D.; Luxemburger, U.; Schrörs, B.; et al. Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer. Nature 2017, 547, 222–226. [Google Scholar] [CrossRef] [PubMed]
  137. Castle, J.C.; Kreiter, S.; Diekmann, J.; Löwer, M.; van de Roemer, N.; de Graaf, J.; Selmi, A.; Diken, M.; Boegel, S.; Paret, C.; et al. Exploiting the Mutanome for Tumor Vaccination. Cancer Res. 2012, 72, 1081–1091. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  138. Andre, T.; Shiu, K.-K.; Kim, T.W.; Jensen, B.V.; Jensen, L.H.; Punt, C.J.; Smith, D.M.; Garcia-Carbonero, R.; Benavides, M.; Gibbs, P.; et al. Pembrolizumab versus chemotherapy for microsatellite instability-high/mismatch repair deficient metastatic colorectal cancer: The phase 3 KEYNOTE-177 Study. J. Clin. Oncol. 2020, 38, LBA4. [Google Scholar] [CrossRef]
  139. Sahin, I.H.; Akce, M.; Alese, O.; Shaib, W.; Lesinski, G.B.; El-Rayes, B.; Wu, C. Immune checkpoint inhibitors for the treatment of MSI-H/MMR-D colorectal cancer and a perspective on resistance mechanisms. Br. J. Cancer 2019, 121, 809–818. [Google Scholar] [CrossRef]
  140. Kloor, M.; Michel, S.; von Knebel Doeberitz, M. Immune evasion of microsatellite unstable colorectal cancers. Int. J. Cancer 2010, 127, 1001–1010. [Google Scholar] [CrossRef]
  141. Grasso, C.S.; Giannakis, M.; Wells, D.K.; Hamada, T.; Mu, X.J.; Quist, M.; Nowak, J.A.; Nishihara, R.; Qian, Z.R.; Inamura, K.; et al. Genetic Mechanisms of Immune Evasion in Colorectal Cancer. Cancer Discov. 2018, 8, 730–749. [Google Scholar] [CrossRef] [Green Version]
  142. Wang, H.; Liu, B.; Wei, J. Beta2-microglobulin(b2M) in cancer immunotherapies: Biological function, resistance and Remedy. Cancer Letters. 2021, 517, 96–104. [Google Scholar]
  143. Gettinger, S.; Choi, J.; Hastings, K.; Truini, A.; Datar, I.; Sowell, R.; Wurtz, A.; Dong, W.; Cai, G.; Melnick, M.A.; et al. Impaired HLA Class I Antigen Processing and Presentation as a Mechanism of Acquired Resistance to Immune Checkpoint Inhibitors in Lung Cancer. Cancer Discov. 2017, 7, 1420–1435. [Google Scholar] [CrossRef] [Green Version]
  144. del Campo, A.B.; Kyte, J.A.; Carretero, J.; Zinchencko, S.; Méndez, R.; González-Aseguinolaza, G.; Ruiz-Cabello, F.; Aamdal, S.; Gaudernack, G.; Garrido, F.; et al. Immune escape of cancer cells with beta2-microglobulin loss over the course of metastatic melanoma. Int. J. Cancer 2014, 134, 102–103. [Google Scholar] [CrossRef] [PubMed]
  145. Lagos, G.G.; Izar, B.; Rizvi, N.A. Beyond Tumor PD-L1: Emerging Genomic Biomarkers for Checkpoint Inhibitor Immunotherapy. Am. Soc. Clin. Oncol. Educ. Book 2020, 40, e47–e57. [Google Scholar] [CrossRef] [PubMed]
  146. Kloor, M.; Becker, C.; Benner, A.; Woerner, S.M.; Gebert, J.; Ferrone, S.; von Knebel Doeberitz, M. Immunoselective pressure and human leukocyte antigen class I antigen machinery defects in microsatellite unstable colorectal cancers. Cancer Res. 2005, 65, 6418–6424. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  147. Le, D.T.; Durham, J.N.; Smith, K.N.; Wang, H.; Bartlett, B.R.; Aulakh, L.K.; Lu, S.; Kemberling, H.; Wilt, C.; Luber, B.S.; et al. Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade. Science 2017, 357, 409–413. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  148. Restifo, N.P.; Smyth, M.J.; Snyder, A. Acquired resistance to immunotherapy and future challenges. Nat. Rev. Cancer. 2016, 16, 121–126. [Google Scholar] [CrossRef]
  149. John Rieth, S.S. Mechanisms of Intrinsic Tumor Resistance to Immunotherapy. Int. J. Mol. Sci. 2018, 19, 1393. [Google Scholar]
  150. Mardis, E.R. Neoantigens and genome instability: Impact on immunogenomic phenotypes and immunotherapy response. Genome Med. 2019, 11, 1–12. [Google Scholar] [CrossRef] [PubMed]
  151. Tran, E.; Ahmadzadeh, M.; Lu, Y.-C.; Gros, A.; Turcotte, S.; Robbins, P.F.; Gartner, J.J.; Zheng, Z.; Li, Y.F.; Ray, S.; et al. Immunogenicity of somatic mutations in human gastrointestinal cancers. Science 2015, 350, 1387–1390. [Google Scholar] [CrossRef] [PubMed]
  152. Latham, A.; Srinivasan, P.; Kemel, Y.; Shia, J.; Bandlamudi, C.; Mandelker, D.; Middha, S.; Hechtman, J.; Zehir, A.; Dubard-Gault, M.; et al. Microsatellite Instability Is Associated with the Presence of Lynch Syndrome Pan-Cancer. J. Clin. Oncol. 2019, 37, 286–295. [Google Scholar] [CrossRef]
  153. Chesney, J.A.; Mitchell, R.A.; Yaddanapudi, K. Myeloid-derived suppressor cells—A new therapeutic target to overcome resistance to cancer immunotherapy. J. Leukoc. Biol. 2017, 102, 727–740. [Google Scholar] [CrossRef] [Green Version]
  154. Hoechst, B.; Voigtlaender, T.; Ormandy, L.; Gamrekelashvili, J.; Zhao, F.; Wedemeyer, H.; Lehner, F.; Manns, M.P.; Greten, T.F.; Korangy, F. Myeloid derived suppressor cells inhibit natural killer cells in patients with hepatocellular carcinoma via the NKp30 receptor. Hepatology 2009, 50, 799–807. [Google Scholar] [CrossRef] [PubMed]
  155. Kumar, V.; Patel, S.; Tcyganov, E.; Gabrilovich, D.I. The Nature of Myeloid-Derived Suppressor Cells in the Tumor Microenvi-ronment. Trends Immunol. 2016, 37, 208–220. [Google Scholar] [CrossRef] [Green Version]
  156. Hou, A.; Hou, K.; Huang, Q.; Lei, Y.; Chen, W. Targeting Myeloid-Derived Suppressor Cell, a Promising Strategy to Overcome Resistance to Immune Checkpoint Inhibitors. Front. Immunol. 2020, 11, 783. [Google Scholar] [CrossRef]
  157. Gao, X.; Sui, H.; Zhao, S.; Gao, X.; Su, Y.; Qu, P. Immunotherapy Targeting Myeloid-Derived Suppressor Cells (MDSCs) in Tumor Microenvironment. Front. Immunol. 2021, 11. [Google Scholar] [CrossRef]
  158. Kim, K.; Skora, A.D.; Li, Z.; Liu, Q.; Tam, A.J.; Blosser, R.L.; Diaz, L.A., Jr.; Papadopoulos, N.; Kinzler, K.W.; Vogelstein, B.; et al. Eradication of metastatic mouse cancers resistant to immune checkpoint blockade by suppression of myeloid-derived cells. Proc. Natl. Acad. Sci. USA 2014, 111, 11774-9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  159. Martens, A.; Wistuba-Hamprecht, K.; Foppen, M.G.; Yuan, J.; Postow, M.A.; Wong, P.; Romano, E.; Khammari, A.; Dreno, B.; Capone, M.; et al. Baseline Peripheral Blood Biomarkers Associated with Clinical Outcome of Advanced Melanoma Patients Treated with Ipilimumab. Clin. Cancer Res. 2016, 22, 2908–2918. [Google Scholar] [CrossRef] [Green Version]
  160. Lichtenstern, C.R.; Ngu, R.K.; Shalapour, S.; Karin, M. Immunotherapy, Inflammation and Colorectal Cancer. Cells 2020, 9, 618. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  161. Yamaoka, K.; Saharinen, P.; Pesu, M.; Holt, V.E.T.; Silvennoinen, O.; O’Shea, J.J. The Janus kinases (Jaks). Genome Biol. 2004, 5, 1–6. [Google Scholar] [CrossRef] [Green Version]
  162. Shin, D.S.; Zaretsky, J.M.; Escuin-Ordinas, H.; Garcia-Diaz, A.; Hu-Lieskovan, S.; Kalbasi, A.; Grasso, C.S.; Hugo, W.; Sandoval, S.; Torrejon, D.Y.; et al. Primary resistance to PD-1 blockade mediated by JAK1/2 mutations. Cancer Discov. 2017, 7, 188–201. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  163. Sucker, A.; Zhao, F.; Pieper, N.; Heeke, C.; Maltaner, R.; Stadtler, N.; Real, B.; Bielefeld, N.; Howe, S.; Weide, B.; et al. Acquired IFNγ resistance impairs anti-tumor immunity and gives rise to T-cell-resistant melanoma lesions. Nat. Commun. 2017, 8, 15440. [Google Scholar] [CrossRef]
  164. Albacker, L.A.; Wu, J.; Smith, P.; Warmuth, M.; Stephens, P.J.; Zhu, P.; Yu, L.; Chmielecki, J. Loss of function JAK1 mutations occur at high frequency in cancers with microsatellite instability and are suggestive of immune evasion. PLoS ONE 2017, 12, e0176181. [Google Scholar] [CrossRef]
  165. Stelloo, E.; Versluis, M.; Nijman, H.W.; De Bruyn, M.; Plat, A.; Osse, E.M.; Van Dijk, R.H.; Nout, R.A.; Creutzberg, C.; de Bock, G.H.; et al. Microsatellite instability derived JAK1 frameshift mutations are associated with tumor immune evasion in endometrioid endometrial cancer. Oncotarget 2016, 7, 39885–39893. [Google Scholar] [CrossRef] [Green Version]
  166. Garcia-Diaz, A.; Shin, D.S.; Moreno, B.H.; Saco, J.; Escuin-Ordinas, H.; Rodriguez, G.A.; Zaretsky, J.M.; Sun, L.; Hugo, W.; Wang, X.; et al. Interferon Receptor Signaling Pathways Regulating PD-L1 and PD-L2 Expression. Cell Rep. 2017, 19, 1189–1201. [Google Scholar] [CrossRef] [Green Version]
  167. Nguyen, T.T.; Ramsay, L.; Ahanfeshar-Adams, M.; Lajoie, M.; Schadendorf, D.; Alain, T.; Watson, I.R. Mutations in the IFNγ-JAK-STAT Pathway Causing Resistance to Immune Checkpoint Inhibitors in Melanoma Increase Sensitivity to Oncolytic Virus Treatment. Clin Cancer Res. 2021, 27, 3432–3442. [Google Scholar] [CrossRef]
  168. Pai, S.G.; Carneiro, B.A.; Mota, J.M.; Costa, R.; Leite, C.A.; Barroso-Sousa, R.; Kaplan, J.B.; Chae, Y.K.; Giles, F.J. Wnt/beta-catenin pathway: Modulating anticancer immune response. J. Hematol. Oncol. 2017, 10, 1–12. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  169. Yaguchi, T.; Goto, Y.; Kido, K.; Mochimaru, H.; Sakurai, T.; Tsukamoto, N.; Kudo-Saito, C.; Fujita, T.; Sumimoto, H.; Kawakami, Y. Immune Suppression and Resistance Mediated by Constitutive Activation of Wnt/β-Catenin Signaling in Human Melanoma Cells. J. Immunol. 2012, 189, 2110–2117. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  170. Spranger, S.; Bao, R.; Gajewski, T.F. Melanoma-intrinsic β-catenin signalling prevents anti-tumour immunity. Nature 2015, 523, 231–235. [Google Scholar] [CrossRef] [PubMed]
  171. Popovic, A.; Jaffee, E.M.; Zaidi, N. Emerging strategies for combination checkpoint modulators in cancer immunotherapy. J. Clin. Investig. 2018, 128, 3209–3218. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  172. Blessin, N.C.; Simon, R.; Kluth, M.; Fischer, K.; Hube-Magg, C.; Li, W.; Makrypidi-Fraune, G.; Wellge, B.; Mandelkow, T.; Debatin, N.F.; et al. Patterns of TIGIT Expression in Lymphatic Tissue, Inflammation, and Cancer. Dis. Markers 2019, 2019, 5160565. [Google Scholar] [CrossRef]
  173. Granier, C.; Vinatier, E.; Colin, E.; Mandavit, M.; Dariane, C.; Verkarre, V.; Biard, L.; El Zein, R.; Lesaffre, C.; Galy-Fauroux, I.; et al. Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells. J. Vis. Exp. 2018. [Google Scholar] [CrossRef]
  174. Matsuzaki, J.; Gnjatic, S.; Mhawech-Fauceglia, P.; Beck, A.; Miller, A.; Tsuji, T.; Eppolito, C.; Qian, F.; Lele, S.; Shrikant, P.; et al. Tumor-infiltrating NY-ESO-1–specific CD8+T cells are negatively regulated by LAG-3 and PD-1 in human ovarian cancer. Proc. Natl. Acad. Sci. USA 2010, 107, 7875–7880. [Google Scholar] [CrossRef] [Green Version]
  175. Datar, I.; Sanmamed, M.F.; Wang, J.; Henick, B.S.; Choi, J.; Badri, T.; Dong, W.; Mani, N.; Toki, M.; Mejías, L.D.; et al. Expression Analysis and Significance of PD-1, LAG-3, and TIM-3 in Human Non–Small Cell Lung Cancer Using Spatially Resolved and Multiparametric Single-Cell Analysis. Clin. Cancer Res. 2019, 25, 4663–4673. [Google Scholar] [CrossRef] [PubMed]
  176. Chauvin, J.-M.; Pagliano, O.; Fourcade, J.; Sun, Z.; Wang, H.; Sander, C.; Kirkwood, J.M.; Chen, T.-H.T.; Maurer, M.; Korman, A.J.; et al. TIGIT and PD-1 impair tumor antigen–specific CD8+ T cells in melanoma patients. J. Clin. Investig. 2015, 125, 2046–2058. [Google Scholar] [CrossRef]
  177. Xu, B.; Yuan, L.; Gao, Q.; Yuan, P.; Zhao, P.; Yuan, H.; Fan, H.; Li, T.; Qin, P.; Han, L.; et al. Circulating and tumor-infiltrating Tim-3 in patients with colorectal cancer. Oncotarget 2015, 6, 20592–20603. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  178. ElTanbouly, M.; Croteau, W.; Noelle, R.J.; Lines, J.L. VISTA: A novel immunotherapy target for normalizing innate and adaptive immunity. Semin. Immunol. 2019, 42, 101308. [Google Scholar] [CrossRef] [PubMed]
  179. Marin-Acevedo, J.A.; Dholaria, B.; Soyano, A.E.; Knutson, K.L.; Chumsri, S.; Lou, Y. Next generation of immune checkpoint therapy in cancer: New developments and challenges. J. Hematol. Oncol. 2018, 11, 1–20. [Google Scholar] [CrossRef] [PubMed]
  180. Papadopoulos, K.P.; Lakhani, N.J.; Johnson, M.L.; Park, H.; Wang, D.; Yap, T.A.; Dowlati, A.; Maki, R.G.; Lynce, F.; Ulahannan, S.V.; et al. First-in-human study of REGN3767 (R3767), a human LAG-3 monoclonal antibody (mAb), ± cemiplimab in patients (pts) with advanced malignancies. J. Clin. Oncol. 2019, 37, 2508. [Google Scholar] [CrossRef]
  181. Curigliano, G.; Gelderblom, H.; Mach, N.; Doi, T.; Tai, W.M.D.; Forde, P.; Sarantopoulos, J.; Bedard, P.L.; Lin, C.; Hodi, S.; et al. Abstract CT183: Phase (Ph) I/II study of MBG453± spartalizumab (PDR001) in patients (pts) with advanced malignancies. Cancer Res. 2019, 79, CT183. [Google Scholar]
  182. Harding, J.J.; Patnaik, A.; Moreno, V.; Stein, M.; Jankowska, A.M.; de Mendizabal, N.V.; Liu, Z.T.; Koneru, M.; Calvo, E. A phase Ia/Ib study of an anti-TIM-3 antibody (LY3321367) monotherapy or in combination with an anti-PD-L1 antibody (LY3300054): Interim safety, efficacy, and pharmacokinetic findings in advanced cancers. J. Clin. Oncol. 2019, 37, 12. [Google Scholar] [CrossRef]
  183. Croft, M.; So, T.; Duan, W.; Soroosh, P. The significance of OX40 and OX40L to T-cell biology and immune disease. Immunol. Rev. 2009, 229, 173–191. [Google Scholar] [CrossRef] [Green Version]
  184. Fu, Y.; Lin, Q.; Zhang, Z.; Zhang, L. Therapeutic strategies for the costimulatory molecule OX40 in T-cell-mediated immunity. Acta Pharm. Sin. B 2020, 10, 414–433. [Google Scholar] [CrossRef] [PubMed]
  185. Poropatich, K.; Dominguez, D.; Chan, W.-C.; Andrade, J.; Zha, Y.; Wray, B.; Miska, J.; Qin, L.; Cole, L.; Coates, S.; et al. OX40+ plasmacytoid dendritic cells in the tumor microenvironment promote antitumor immunity. J. Clin. Investig. 2020, 130, 3528–3542. [Google Scholar] [CrossRef] [PubMed]
  186. Wang, C.; Ye, Y.; Hu, Q.; Bellotti, A.; Gu, Z. Tailoring Biomaterials for Cancer Immunotherapy: Emerging Trends and Future Outlook. Adv. Mater. 2017, 29. [Google Scholar] [CrossRef] [PubMed]
  187. Yang, F.; Shi, K.; Jia, Y.P.; Hao, Y.; Peng, J.R.; Qian, Z.Y. Advanced biomaterials for cancer immunotherapy. Acta Pharmacol. Sin. 2020, 41, 911–927. [Google Scholar] [CrossRef] [PubMed]
  188. Ishihara, J.; Fukunaga, K.; Ishihara, A.; Larsson, H.M.; Potin, L.; Hosseinchi, P.; Galliverti, G.; Swartz, M.A.; Hubbell, J.A. Matrix-binding checkpoint immunotherapies enhance antitumor efficacy and reduce adverse events. Sci. Transl. Med. 2017, 9. [Google Scholar] [CrossRef] [Green Version]
  189. Song, W.; Shen, L.; Wang, Y.; Liu, Q.; Goodwin, T.J.; Li, J.; Dorosheva, O.; Liu, T.; Liu, R.; Huang, L. Synergistic and low adverse effect cancer immunotherapy by immunogenic chemotherapy and locally expressed PD-L1 trap. Nat. Commun. 2018, 9, 2237. [Google Scholar] [CrossRef]
  190. Binnewies, M.; Roberts, E.W.; Kersten, K.; Chan, V.; Fearon, D.F.; Merad, M.; Coussens, L.M.; Gabrilovich, D.I.; Ostrand-Rosenberg, S.; Hedrick, C.C.; et al. Understanding the tumor immune microenvi-ronment (TIME) for effective therapy. Nat. Med. 2018, 24, 541–550. [Google Scholar] [CrossRef] [PubMed]
  191. Cohen, R.; Rousseau, B.; Vidal, J.; Colle, R.; Diaz, L.A.; André, T. Immune Checkpoint Inhibition in Colorectal Cancer: Microsatellite Instability and Beyond. Target. Oncol. 2019, 15, 11–24. [Google Scholar] [CrossRef] [PubMed]
  192. McCafferty, M.H. Advances in Treatment of Colorectal Cancer. Am. Surg. 2005, 71, 892–900. [Google Scholar] [CrossRef]
  193. Thomas, J.; Leal, A.; Overman, M.J. Clinical Development of Immunotherapy for Deficient Mismatch Repair Colorectal Cancer. Clin. Colorectal Cancer 2020, 19, 73–81. [Google Scholar] [CrossRef]
  194. Ngwa, W.; Irabor, O.C.; Schoenfeld, J.D.; Hesser, J.; Demaria, S.; Formenti, S.C. Using immunotherapy to boost the abscopal effect. Nat. Cancer 2018, 18, 313–322. [Google Scholar] [CrossRef]
  195. Weichselbaum, R.R.; Liang, H.; Deng, L.; Fu, Y.-X. Radiotherapy and immunotherapy: A beneficial liaison? Nat. Rev. Clin. Oncol. 2017, 14, 365–379. [Google Scholar] [CrossRef]
  196. Floudas, C.S.; Brar, G.; Mabry-Hrones, D.; Duffy, A.G.; Wood, B.; Levy, E.; Krishnasamy, V.; Fioravanti, S.; Bonilla, C.M.; Walker, M.; et al. A pilot study of AMP-224, a PD-L2 Fc fusion protein, in combination with stereotactic body radiation therapy (SBRT) in patients with metastatic colorectal cancer. Clin. Colorectal Cancer 2016, 34, 560. [Google Scholar]
  197. Young, K.H.; Baird, J.R.; Savage, T.; Cottam, B.; Friedman, D.; Bambina, S.; Messenheimer, D.J.; Fox, B.; Newell, P.; Bahjat, K.S.; et al. Optimizing Timing of Immunotherapy Improves Control of Tumors by Hypofractionated Radiation Therapy. PLoS ONE 2016, 11, e0157164. [Google Scholar] [CrossRef] [Green Version]
  198. Zhou, C.; Jiang, T.; Xiao, Y.; Wang, Q.; Zeng, Z.; Cai, P.; Zhao, Y.; Zhao, Z.; Wu, D.; Lin, H.; et al. Good tumor response to chemoradioimmunotherapy in dMMR/MSI-H Advanced Colorectal Cancer: A Case Series. Front. Immunol. 2021, 12. [Google Scholar] [CrossRef]
  199. Matos, A.I.; Carreira, B.; Peres, C.; Moura, L.I.F.; Conniot, J.; Fourniols, T.; Scomparin, A.; Martínez-Barriocanal, Á.; Arango, D.; Conde, J.P.; et al. Nanotechnology is an important strategy for combi-national innovative chemo-immunotherapies against colorectal cancer. J. Control. Release 2019, 307, 108–138. [Google Scholar] [CrossRef]
  200. Pfirschke, C.; Engblom, C.; Rickelt, S.; Cortez-Retamozo, V.; Garris, C.; Pucci, F.; Yamazaki, T.; Poirier-Colame, V.; Newton, A.; Redouane, Y.; et al. Immunogenic Chemotherapy Sensitizes Tumors to Checkpoint Blockade Therapy. Immunity 2016, 44, 343–354. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  201. Shahda, S.; Noonan, A.M.; Bekaii-Saab, T.S.; O’Neil, B.H.; Sehdev, A.; Shaib, W.L.; Helft, P.R.; Loehrer, P.J.; Tong, Y.; Liu, Z.; et al. A phase II study of pembrolizumab in combination with mFOLFOX6 for patients with advanced colorectal cancer. J. Clin. Oncol. 2017, 35, 3541. [Google Scholar] [CrossRef]
  202. Germano, G.; Lamba, S.E.; Rospo, G.; Barault, L.; Magrì, A.; Maione, F.; Russo, M.; Crisafulli, G.; Bartolini, A.; Lerda, G.; et al. Inactivation of DNA repair triggers neoantigen generation and impairs tumour growth. Nature 2017, 552, 116–120. [Google Scholar] [CrossRef] [PubMed]
  203. Fiano, V.; Trevisan, M.; Trevisan, E.; Senetta, R.; Castiglione, A.; Sacerdote, C.; Gillio-Tos, A.; De Marco, L.; Grasso, C.; Magistrello, M.; et al. MGMT promoter methylation in plasma of glioma patients receiving temozolomide. J. Neuro-Oncol. 2014, 117, 347–357. [Google Scholar] [CrossRef] [Green Version]
  204. NIVOLUMAB Plus IPILIMUMAB and TEMOZOLOMIDE in Microsatellite Stable, MGMT Silenced Metastatic Colorectal Cancer [Internet]. Available online: https://clinicaltrials.gov/ct2/show/NCT03832621 (accessed on 10 September 2021).
  205. Pembrolizumab in MMR-Proficient Metastatic Colorectal Cancer Pharmacologically Primed to Trigger Hypermutation Status. Available online: https://clinicaltrials.gov/ct2/show/NCT03519412 (accessed on 10 September 2021).
  206. Garcia, J.; Hurwitz, H.I.; Sandler, A.B.; Miles, D.; Coleman, R.L.; Deurloo, R.; Chinot, O.L. Bevacizumab (Avastin®) in cancer treatment: A review of 15 years of clinical experience and future outlook. Cancer Treat. Rev. 2020, 86, 102017. [Google Scholar] [CrossRef]
  207. Rawla, P.; Barsouk, A.; Hadjinicolaou, A.V.; Barsouk, A. Immunotherapies and Targeted Therapies in the Treatment of Metastatic Colorectal Cancer. Med. Sci. 2019, 7, 83. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  208. Chen, D.S.; Hurwitz, H. Combinations of Bevacizumab with Cancer Immunotherapy. Cancer J. 2018, 24, 193–204. [Google Scholar] [CrossRef] [PubMed]
  209. Fukuoka, S.; Hara, H.; Takahashi, N.; Kojima, T.; Kawazoe, A.; Asayama, M.; Yoshii, T.; Kotani, D.; Tamura, H.; Mikamoto, Y.; et al. Regorafenib Plus Nivolumab in Patients with Advanced Gastric or Colorectal Cancer: An Open-Label, Dose-Escalation, and Dose-Expansion Phase Ib Trial (REGONIVO, EPOC1603). J. Clin. Oncol. 2020, 38, 2053–2061. [Google Scholar] [CrossRef]
  210. Wallin, J.; Pishvaian, M.J.; Hernandez, G.; Yadav, M.; Jhunjhunwala, S.; Delamarre, L.; He, X.; Powderly, J.; Lieu, C.; Eckhardt, S.G.; et al. Clinical activity and immune correlates from a phase Ib study evaluating atezolizumab (anti-PDL1) in combination with FOLFOX and bevacizumab (anti-VEGF) in meta-static colorectal carcinoma. Cancer Res. 2016, 2651. [Google Scholar]
  211. Ebert, P.J.R.; Cheung, J.; Yang, Y.; McNamara, E.; Hong, R.; Moskalenko, M.; Gould, S.E.; Maecker, H.; Irving, B.A.; Kim, J.M.; et al. MAP Kinase Inhibition Promotes T Cell and An-ti-tumor Activity in Combination with PD-L1 Checkpoint Blockade. Immunity 2016, 44, 609–621. [Google Scholar] [CrossRef] [Green Version]
  212. Bendell, J.C.; Kim, T.; Goh, B.C.; Wallin, J.; Oh, D.Y.; Han, S.; Lee, C.; Hellmann, M.D.; Desai, J.; Lewin, J.; et al. Clinical activity and safety of cobimetinib (cobi) and atezolizumab in colorectal cancer (CRC). J. Clin. Oncol. 2016, 34, 3502. [Google Scholar] [CrossRef]
  213. Sun, H.-L.; Zhou, X.; Xue, Y.-F.; Wang, K.; Shen, Y.-F.; Mao, J.-J.; Guo, H.-F.; Miao, Z.-N. Increased frequency and clinical significance of myeloid-derived suppressor cells in human colorectal carcinoma. World J. Gastroenterol. 2012, 18, 3303–3309. [Google Scholar] [CrossRef]
  214. Arihara, F.; Mizukoshi, E.; Kitahara, M.; Takata, Y.; Arai, K.; Yamashita, T.; Nakamoto, Y.; Kaneko, S. Increase in CD14+HLA-DR-/low myeloid-derived suppressor cells in hepatocellular carcinoma patients and its impact on prognosis. Cancer Immunol. Immunother. 2013, 62, 1421–1430. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  215. Jordan, K.R.; Amaria, R.N.; Ramirez, O.; Callihan, E.B.; Gao, D.; Borakove, M.; Manthey, E.; Borges, V.F.; McCarter, M.D. Myeloid-derived suppressor cells are associated with disease progression and decreased overall survival in advanced-stage melanoma patients. Cancer Immunol. Immunother. 2013, 62, 1711–1722. [Google Scholar] [CrossRef] [Green Version]
  216. Cassier, P.A.; Garin, G.; Eberst, L.; Delord, J.-P.; Chabaud, S.; Terret, C.; Montane, L.; Bidaux, A.-S.; Laurent, S.; Jaubert, L.; et al. MEDIPLEX: A phase 1 study of durvalumab (D) combined with pexidartinib (P) in patients (pts) with advanced pancreatic ductal adenocarcinoma (PDAC) and colorectal cancer (CRC). J. Clin. Oncol. 2019, 37, 2579. [Google Scholar] [CrossRef]
  217. Tabernero, J.; Melero, I.; Ros, W.; Argiles, G.; Marabelle, A.; Rodriguez-Ruiz, M.E.; Albanell, J.; Calvo, E.; Moreno, V.; Cleary, J.M.; et al. Phase Ia and Ib studies of the novel carci-noembryonic antigen (CEA) T-cell bispecific (CEA CD3 TCB) antibody as a single agent and in combination with atezolizumab: Preliminary efficacy and safety in patients with metastatic colorectal cancer (mCRC). J. Clin. Oncol. 2017, 35, 3002. [Google Scholar] [CrossRef]
Figure 1. Mechanism of immunotherapy checkpoint inhibitors. When PD-1 located on the surface of effectors T cells interacts with PD-L1 on the surface of tumor cells, downstream signaling pathways are activated, inhibiting apoptosis, and promoting the conversion of effector T-cells to Tregs. CTLA-4 on the surface of T-cells can bind preferentially to the receptors (B7-1; B7-2) on the surface of APC to limit T-cell activity and proliferation in a similar way.
Figure 1. Mechanism of immunotherapy checkpoint inhibitors. When PD-1 located on the surface of effectors T cells interacts with PD-L1 on the surface of tumor cells, downstream signaling pathways are activated, inhibiting apoptosis, and promoting the conversion of effector T-cells to Tregs. CTLA-4 on the surface of T-cells can bind preferentially to the receptors (B7-1; B7-2) on the surface of APC to limit T-cell activity and proliferation in a similar way.
Life 12 00229 g001
Figure 2. Current immunotherapeutic options in CRC.
Figure 2. Current immunotherapeutic options in CRC.
Life 12 00229 g002
Table 1. Ongoing clinical trials for MSI-H/dMMR CRC.
Table 1. Ongoing clinical trials for MSI-H/dMMR CRC.
Study NameStatusPhaseStudy PopulationTreatmentEndpointPurpose
NCT02982694RecruitingIIAdvanced chemotherapy resistant MSI-like CRCAtezolizumab +
bevacizumab
ORRTo determine the anti-tumor effect of atezolizumab in combination with bevacizumab in chemotherapy-resistant MSI-H/dMMR CRC
NCT02997228RecruitingIIIMSI-H/dMMR mCRCAtezolizumab vs. atezolizumab + bevacizumab + FOLFOXPFSTo compare mFOLFOX6/bevacizumab/atezolizumab with atezolizumab alone as the first-line treatment in MSI-H/dMMR mCRC
NCT04014530RecruitingI-IIdMMR and pMMR mCRC and dMMR endometrial carcinomaPembrolizumab + AtalurenAE and maximum tolerable dose of Ataluren
AE of the combination
ORR
Efficacy of pembrolizumab in combination with Alaturen in pMMR/dMMR mCRC and dMMR metastatic endometrial carcinoma
NCT03638297RecruitingIIMSI-H/dMMR CRCPembrolizumab + COX inhibitor (aspirin)RRSafety and efficacy of pembrolizumab in combination with COX inhibitor in MSI-H/dMMR or high TMB CRC
NCT04001101RecruitingIIMSI-H/dMMRmetastatic solid tumorsPembrolizumab + RT (metastatic site) vs. pembrolizumabORRTo determine if the ORR is improved by the addition of radiotherapy to pembrolizumab in MSI-H/dMMR metastatic solid tumors, compared to pembrolizumab alone
NCT04730544RecruitingIIMSI-H/dMMR mCRCNivolumab + ipilimumabAE PFSTo determine the safety and efficacy of two combination regiments of nivolumab + opilimumab in MSI-H/dMMR mCRC
NCT04008030RecruitingIIIMSI-H/dMMR mCRCNivolumab vs. nivolumab + ipilimumab
Nivolumab + ipilimumab vs. chemotherapy
PFSTo compare the clinical benefit of nivolumab alone, nivolumab + ipilimumab or investigator’s choice chemotherapy in MSI-H/dMMR mCRC
NCT03104439RecruitingIIMSI-H/dMMR CRC, MMS CRC, pancreatic cancerNivolumab + ipilimumab + RTDCRTo evaluate the combination of nivolumab, ipilimumab, and radiation therapy in MSS/MSI-H/dMMR CRC and pancreatic cancer
NCT02060188Active, not recruitingIIRecurrent or metastatic MSI-H and non-MSI-H CRCNivolumab
Nivolumab + ipilimumab
Nivolumab + ipiliumab + cobimetinib
Nivolumab + BMS-986016
Nivolumab + daratumumab
ORRTo evaluate nivolumab alone or in combination with other anti-cancer molecules in recurrent or metastatic MSI-H or non-MSI-H CRC
NCT03186326RecruitingIIMSI-H/dMMR mCRCAvelumabPFSTolerance and effectiveness of Avelumab, compared to the second line standard chemotherapy for MSI-H/dMMR mCRC
NCT03475953RecruitingI-IIAdvanced or metastatic solid tumors, including MSI-H/dMMR CRCAvelumab + regorafenibRP2D for regorafenib
ORR
PFS
To evaluate efficacy and safety of regorafenib in combination with avelumab in advanced/metastatic solid tumors
NCT03435107Active, not recruitingIIMSI-H/dMMR or POLE mutated mCRCDurvalumabORRTo investigate durvalumab in previously treated MSI-H/dMMR or POLE mutated mCRC
NCT02983578Active, not recruitingIIAdvanced pancreatic cancer
NSCLC
dMMR CRC
Danvatirsen+durvalumabAEs, SAEsTo evaluate danvatirsen and durvalumab in patients with advanced pancreatic cancer, NSCLC, and dMMR CRC refractory to standard therapy
Table 2. Completed clinical trials for MSI-H/dMMR CRC.
Table 2. Completed clinical trials for MSI-H/dMMR CRC.
Study NamePhaseStudy PopulationTreatmentPrimary EndpointResultsPurpose
NCT02460198IIPreviously treated LA unresectable or mCRC MSI-H/dMMRCohort A: pembrolizumab after ≥2 prior lines of therapy
Cohort B: pembrolizumab after ≥1 prior line of therapy
ORROR = 33%/33%To determine the efficacy of pembrolizumab monotherapy in previously treated LA unresectable or mCRC MSI-H/dMMR patients
NCT01876511IIMSI tumors (Cohort A: MSI + CRC; Cohort B: MSI − CRC; Cohort C: MSI + non-CRC)PembrolizumabirPFS (A,B), irORR (A,B), irPFS (C), ORR (A,C),
PFS (A,C)
IrORR
A = 40%, irPFS A = 78%; irORR B = 0%, irPFS B = 11%, Median PFS A = not reached; Median OS A = not reached; Median PFS B = 2.2 months; Median OS B = 5 months; irORR C = 71%, irPFS = 67%
To determine the anti-tumoral activity of pembrolizumab in MSI/MSS cohorts
NCT02178722I/IISelected cancers (including MSI-H CRC)Pembrolizumab +
epacadosat
I: TEAE; II: ORRAcceptable safety profile
ORR CRC = N/A
To assess the safety, tolerability, and efficacy of combination therapy pembrolizumab + epacadosat in patients with certain cancers.
NCT02335918I
II
Advanced refractory solid tumors
(including CRC)
Varlilumab +
nivolumab
I: TEAE
II: ORR
Acceptable safety profile
PR = 5% CRC
SD = 17% CRC
To determine the clinical benefit, safety, and tolerability of combination therapy between varlilumumab + nivolumab in certain advanced refractory solid tumors.
NCT02227667IIAdvanced MSI-H CRCDurvalumabORR22%To determine the effects of durvalumab therapy in advanced MSI-H CRC patients.
NCT02777710IMetastatic/
advanced CRC and PaC
Durvalumab +
pexidartinib
1.DLT
2.ORR
Acceptable safety profile
ORR (2 m) = 21%
To evaluate the safety and activity of durvalumab combined with pexidartinib in patients with metastatic/advanced pancreatic or CRC
Table 3. Completed clinical trials investigating immunotherapy in MMS/pMMR CRC.
Table 3. Completed clinical trials investigating immunotherapy in MMS/pMMR CRC.
Study NamePhaseStudy PopulationTreatmentPrimary EndpointResultsPurpose
NCT02981524IIAdvanced pMMR
CRC
Pembrolizumab+
cyclophosphamide+
Colon cancer vaccine
ORRNo OR with DCR = 18%To assess the efficacy (as measured by RECIST criteria) of therapy with CY/GVAX in combination with pembrolizumab in patients with advanced pMMR CRC
NCT03274804IRefractory MSS/
pMMR mCRC
Pembrolizumab +
Maraviroc
Feasibility rate of the combined therapyFR = 94.7%To determine the feasibility rate of combination therapy between pembrolizumab and maraviroc in previously treated subjects who have refractory MSS/pMMR mCRC
NCT02860546IIMSS CRCNivolumab +
tipiracil hydrochloride
irORRNo tumor responseTo evaluate the efficacy of nivolumab + tipiracil hydrochloride in patients with MSS refractory mCRC
NCT03258398IIMSS CRCAvelumab +
tomivosertib
vs.
tomivosertib
Part 1:
DLT during the first treatment cycle
Part 2: ORR
Part 1: Acceptable safety profile for combination therapy
Part 2: N/A
To evaluate the safety, tolerability, and anti-tumor activity of tomivosertib with or without avelumab in MSS CRC patients
NCT02811497IIAdvanced solid tumors
(including MSS CRC)
Azacitidine +
durvalumab
ORRNo OR with DCR = 7.1 and median PFS = 1.9 m and
OS = 5 m
To assess the antitumor activity of azacitidine in combination with druvalumab in advanced solid tumors
NCT03005002IMSS mCRC (Liver)Durvalumab + tremelimumab following radioembolization (RE) with SIR-spheres
Safety and hepatic response rateSafety of RE followed by D + T
Lack of clinical response
To determine the safety and the hepatic response rate of durvalumab+tremelimuma following RE in MSS CRC that has spread to the liver
NCT02876224IbNon MSI-H mCRCCobimetinib +
Bevacizumab +
atezolizumab
TEAEAcceptable safety profile and manageable AEsTo assess the safety, tolerability, and pharmacokinetics of oral cobimetinib with IV atezolizumab and bevacizumab in previously treated mCRC with non-MSI-H
NCT02260440IIChemo-refractory
MSS mCRC
Pembrolizumab +
azacitidine
ORROR = 3%To evaluate the anti-tumor activity, safety, and tolerability of pembrolizumab in combination with azacitidine in subjects with chemo-refractory MSS mCRC
NCT03168139I/IIMSS mCRC
mPaC
Olaptesed pegol
vs.
olaptesed pegol +
pembrolizumab
Pharmaco-dynamics
Safety and tolerability
Induction of immune response and
acceptable safety profile
To explore safety, tolerability, and efficacy of olaptesed monotherapy or in combination with pembrolizumab in patients with MSS mCRC and pancreatic cancer
NCT02788279IIImCRCAtezolizumab (A)
vs.
atezolizumab (A)+
cobimetinib (C)
vs.
regorafenib (R)
OSOS (A) = 7.10 m
OS (A + C)
= 8.87 m
OS (R) = 8.51 m
To compare regorafenib to cobimetinib + atezolizumab and atezolizumab monotherapy in the setting of mCRC
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Gorzo, A.; Galos, D.; Volovat, S.R.; Lungulescu, C.V.; Burz, C.; Sur, D. Landscape of Immunotherapy Options for Colorectal Cancer: Current Knowledge and Future Perspectives beyond Immune Checkpoint Blockade. Life 2022, 12, 229. https://doi.org/10.3390/life12020229

AMA Style

Gorzo A, Galos D, Volovat SR, Lungulescu CV, Burz C, Sur D. Landscape of Immunotherapy Options for Colorectal Cancer: Current Knowledge and Future Perspectives beyond Immune Checkpoint Blockade. Life. 2022; 12(2):229. https://doi.org/10.3390/life12020229

Chicago/Turabian Style

Gorzo, Alecsandra, Diana Galos, Simona Ruxandra Volovat, Cristian Virgil Lungulescu, Claudia Burz, and Daniel Sur. 2022. "Landscape of Immunotherapy Options for Colorectal Cancer: Current Knowledge and Future Perspectives beyond Immune Checkpoint Blockade" Life 12, no. 2: 229. https://doi.org/10.3390/life12020229

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop