Abstract
Background
We aimed to investigate the clinical implications of the tumor mutation burden (TMB) and insertion–deletion (indel) rate in gastric cancer patients treated with nivolumab.
Methods
A total of 105 patients with advanced gastric cancer who were treated with nivolumab as third or later line of therapy were included as the study population. The indel rate was defined as the proportion of indels making up the TMB.
Results
The median age was 58 (32–78 years), and 65 (61.9%) were men. Patients with TMB > 18.03/Mb showed superior progression-free survival (PFS) and overall survival (OS) compared to those with TMB ≤ 18.03/Mb. Patients with a high indel rate (> 40%) had a favorable PFS and OS compared to those with a lower indel rate (≤ 40%) (P = 0.009 and P = 0.007, respectively). The association between a high indel rate and favorable PFS and OS was prominent in a subgroup with TMB > 18.03/Mb (P < 0.001 and P = 0.007 for PFS and OS, respectively), but not in that with TMB ≤ 18.03/Mb. All five patients with deficient-MMR fell into the category of ‘TMB > 18.03/Mb with an indel rate of > 40%. TMB ≥ 18.03/Mb with an indel rate of > 40% was independently associated with a favorable PFS (hazard ratio [HR] 0.07, P = 0.012) and OS (HR 0.09, P = 0.023).
Conclusion
TMB and indel rate should be jointly considered to better predict survival outcomes of gastric cancer patients treated with nivolumab. Our findings deserve further investigation and validation in future studies.
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Introduction
Immune checkpoint inhibitors (ICIs), such as nivolumab and pembrolizumab, have recently emerged as an important systemic therapeutic modality for patients with advanced gastric cancer [1]. The ATTRACTION-2 study was the first phase 3 trial that demonstrated an overall survival (OS) benefit of nivolumab compared to placebo in 3rd or later lines of systemic treatment [2]. Recently, the phase 3 CheckMate-649 study demonstrated a progression-free survival (PFS) and OS benefit of adding nivolumab to chemotherapy in the frontline setting [3]. Similarly, the phase 3 ATTRACTION-4 study showed that first-line nivolumab in combination with chemotherapy led to a PFS benefit in a PD-L1 unselected population, whereas an OS benefit was not demonstrated [4]. It is important to note that only a fraction of patients derive clinical benefit from ICIs. Therefore, the development and identification of biomarkers predictive of ICI efficacy are warranted. To this end, PD-L1 positivity assessed based on the PD-L1 combined positive score (CPS) [5, 6], Epstein–Barr virus (EBV) positivity [6] and deficient mismatch repair protein (dMMR)/microsatellite instability (MSI)-high [7, 8] have been suggested as potential biomarkers for gastric cancer patients. However, the sub-optimal predictive capacities of these biomarkers and the occurrence of an objective response in tumors negative for these biomarkers warrant further investigation of additional biomarkers.
Among the recently highlighted biomarkers predictive of an ICI response is the tumor mutation burden (TMB). The rationale for the use of TMB as a predictive biomarker is that higher levels of TMB leading to higher numbers of neo-antigens and thus greater chances of eliciting immunogenic T cell responses by involving more diverse repertoires of T cells [9]. Indeed, a higher TMB has been shown to be associated with a better ICI efficacy [10] and a prolonged OS [11] in various cancer types. Recently, the US FDA approved pembrolizumab for the treatment of patients with solid tumors that had a high TMB, which was defined by ≥ 10 mutations /mega-bases (Mb) in the target lesion as determined by an FDA-approved sequencing panel. This was based on the Keynote-158 study that showed a higher objective response rate (ORR) in TMB-high tumors (29%) versus that of TMB-low tumors (6%) [12]. However, the Keynote-158 study included heterogenous cancer types with different lines of treatment and patients with gastric cancer were not included in that study [12], which may limit the generalizability of the findings to gastric cancer patients. Furthermore, a higher TMB may not always be associated with a good response to ICI [13] and its value may vary by cancer type [11].
Insertion–deletion (Indel) is a qualitative aspect of TMB that is linked to the generation of high levels of immunogenic neo-antigens by frameshift mutations [14, 15]. High levels of an indel burden in renal cell carcinoma have been suggested as one of the mechanisms leading to higher response rates to ICI-based treatments despite moderate levels of TMB in this cancer type [14]. In addition, previous studies of other cancer types, such as melanoma [14], non-small cell lung cancer [16] and cholangiocarcinoma [17], have suggested that the indel burden may be associated with better clinical outcomes of patients treated with ICIs. However, the clinical value of the indel burden remains unknown in gastric cancer patients, especially in the context of ICI.
In this retrospective study, we aimed to investigate the clinical implications of the qualitative and quantitative aspects of TMB in advanced gastric cancer patients treated with nivolumab as 3rd or later line of therapy. In particular, we focused on the clinical value of the proportion of indel as a qualitative aspect of TMB.
Patients and methods
Study patients and treatments
A total of 105 patients who were treated with nivolumab as the third or later line of therapy at Asan Medical Center (Seoul, Korea) between July 2015 and October 2020 and had panel sequencing data were included as the study population. Patients were treated with 3 mg/kg nivolumab every 2 weeks. Tumor responses were assessed every 6–8 weeks according to Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1.
The Institutional Review Board approved the study protocol, and informed consent was obtained. All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1964 and its later versions.
Panel sequencing and the assessment of the tumor mutation burden
Genomic DNA was extracted from archived formalin-fixed, paraffin-embedded (FFPE) tumor specimens. Targeted next-generation sequencing (NGS) was performed using the NextSeq platform (Illumina, San Diego, CA, USA) with OncoPanel AMC version 3 (OP AMCv3) and version 4 (OP AMC v4) [18,19,20,21]. The OncoPanel AMC version 3 (OP AMC v3) and version 4 (OP AMC v4) captured 383 and 323 cancer-related genes, respectively (OP AMC v3, 199 genes for entire exons, 8 genes for partial introns and 184 genes for hotspots; OP AMC v4, 225 genes for entire exons and 6 genes for partial introns and 99 hotspots). TMB was determined as the sum of the number of single-nucleotide variations (SNVs) and the indel mutations per mega-base in the targeted region. The indel rate was defined as the proportion of indel mutations among the total TMB. The (frameshift) indel burden was defined as the number of (frameshift) indel mutations per mega-base in the targeted region.
Immunohistochemical assessment of PD-L1 expression and mismatch repair proteins
PD-L1 staining was done using the PD-L1 22C3 pharmDx kit on the Link 48 system autostainer (Agilent Technologies, USA) according to the manufacturer’s instructions. Combined positive score (CPS) was calculated as the number of PD-L1-expressing tumor and intra- or peri-tumoral inflammatory cells divided by the number of viable tumor cells and then multiplied by 100.
For the assessment of mismatch repair (MMR) status, tissue specimens were stained using MLH1 (Novo, Newcastle, UK), MSH2 (Cell Marque, CA, USA), MSH6 (Cell Marque, CA, USA), and PMS2 (Cell Marque, CA, USA) using a Bench Mark XT automatic immunostaining device with an OptiView DAB IHC Detection Kit (Ventana Medical System). dMMR was defined as the loss of expression of one or more of the MMR proteins (i.e., MLH1, MSH2, MSH6, and PMS2).
Assessment of EBV positivity
In situ hybridization for EBV was performed using the auto-stainer Bench Mark XT (Ventana Medical System, Tucson, AZ) with a Ventana ISH iVIEW Blue Detection Kit (Ventana Medical System) according to the manufacturer’s instructions. Briefly, the prepared tissue sections were incubated with the EBER probe (800–2842, Ventana Medical Systems) and dark blue/purple at the site of the hybridization (nucleus) was interpreted as positive.
Statistical analysis
PFS was defined as the interval from the initial date of nivolumab administration (index date) to the date of disease progression (as per RECIST v1.1) or death. OS was defined as the interval between the index date and the date of death from any cause. The Kaplan–Meier method was used to estimate the survival outcomes, and the log-rank test was used to compare these survival outcomes among the subgroups. Cox proportional hazard modeling was used to examine the associations of the factors including age, sex, previous gastrectomy, ECOG PS, metastatic site, number of metastatic sites, line of nivolumab treatment, neutrophil-to-lymphocyte ratio (NLR), histologic type, time-to-progression with 1st- and 2nd-line systemic treatments, PD-L1 CPS, EBV positivity and ‘TMB and indel rate’ with PFS and OS. The maximal chi-square method was used to determine the optimal cut-off value of the TMB, indel rate and (frameshift) indel burden that best segregated the OS outcomes. A P value of < 0.05 was considered statistically significant. Statistical analyses were performed using R software version 3.6.2 (R Foundation for Statistical Computing, Vienna, Austria).
Results
Study patients
Baseline characteristics of the study patients are summarized in Table 1. Their median age was 58 (32–78 years), and 65 patients (61.9%) were men. There were 26 (24.8%), 55 (52.4%) and 24 (22.8%) patients with ECOG PS 0, 1 ≥ 2, respectively. The peritoneum was the most common site of metastasis (n = 54, 51.4%). There were five patients (4.8%) with dMMR. Among patients whose PD-L1 and EBV status was examined, 27.3% (24 of 88 patients) and 5.1% (5 of 99) were PD-L1 CPS ≥ 1 and positive for EBV, respectively.
During a median follow-up duration of 9.5 months among the surviving patients, their median PFS and OS were 1.61 months (95% confidence interval [CI]: 1.48–1.84 months) and 4.67 months (95% CI 3.09–8.02 months), respectively (Supplementary Fig. 1).
Survival outcomes according to the different TMB levels
We then examined the survival outcomes of patients with different TMB levels. Using an optimal TMB cut-off of 18.03/Mb, patients with a high TMB (> 18.03/Mb) showed a superior PFS (median 12.46 vs. 1.54 months, P = 0.007) and OS (median 29.16 vs. 4.24 months, P = 0.015) compared to those with a low TMB (≤ 18.03/Mb) (Fig. 1).
Survival outcomes according to different indel rates
We next investigated the clinical value of the indel rate as a qualitative aspect of TMB. For a conceptual comparison, we subdivided the study patients according to an indel rate cut-off of 40%, which best segregated the survival outcomes, into a high indel group (indel rate > 40%, n = 15) and a low indel group (indel rate ≤ 40%, n = 90). Compared to the low indel group, the high indel group showed significantly superior PFS (median 12.46 vs. 1.58 months, P = 0.009) (Fig. 2A) and OS (median 13.84 vs. 3.85 months, P = 0.007) (Fig. 2B).
To further evaluate the clinical value of the indel rate in the context of different TMB levels, we compared the survival outcomes according to the indel rate in subgroups with different TMB levels. Among patients with TMB > 18.03/Mb, the high indel group exhibited superior PFS (median not reached vs. 1.81 months, P < 0.001) and OS (median 35.4 vs. 3.48 months, P = 0.007) compared to the low indel group (Fig. 3A). In contrast, among patients with TMB ≤ 18.03/Mb, PFS and OS were comparable between the high and low indel groups (median 1.22 vs. 1.54, P = 0.930 and median 4.40 vs. 3.85 months, P = 0.440, for PFS and OS, respectively) (Fig. 3B). Among patients in the high indel group (indel rate > 40%), those with a TMB > 18.03/Mb showed favorable PFS (P = 0.003) and OS (P = 0.031) compared to those with a TMB ≤ 18.03/Mb (Supplementary Fig. 2A). For those in the low indel group (indel rate ≤ 40%), there was no significant difference in PFS (P = 0.670) or OS (P = 0.850) (Supplementary Fig. 2B).
On the other hand, patients with a high indel burden (> 3.28/Mb) showed favorable PFS (P = 0.036) and OS (P = 0.014) (Supplementary Fig. 3A). Those with a high frameshift indel burden (> 1.64/Mb) also showed a trend of favorable PFS (P = 0.055) and superior OS (P = 0.007) (Supplementary Fig. 3B). Among those with a high (frameshift) indel burden, the high indel group showed favorable survival outcomes (all P < 0.05) (Supplementary Fig. 4).
Association between TMB and/or indel rate and other tumor factors
Tumor factors including biomarkers previously suggested to be predictive of an anti-PD-1 response in gastric cancer patients were examined in terms of their association with the TMB and/or indel rate (Table 2). All 5 patients with dMMR fell into the category of TMB > 18.03/Mb, indel rate > 40% and TMB > 18.03/Mb and indel rate > 40%, respectively. In particular, 5 of 6 patients with TMB > 18.03/Mb and indel > 40% were dMMR. One patient with TMB > 18.03 and indel > 40% was confirmed as MMR-proficient (pMMR) by IHC, and experienced disease progression at 19.5 months and died at 35.4 months from the index date. The proportion of patients with PD-L1 CPS ≥ 1 and EBV-positive was similar among the subgroups with different TMB and/or indel rates (Table 2).
The proportion of patients with diffuse-type histology by Lauren classification tended to be higher in patients with indel rate > 40% (P = 0.081). The proportion of patients with a high indel rate (indel rate > 40%) was higher in patients with TMB > 18.03/Mb compared to those with TMB ≤ 18.03/Mb (54.5% vs. 9.6%, P < 0.001). The proportion of patients with a higher TMB (TMB > 18.03/Mb) was also higher in patients in the high indel group than in the low indel group (40.0% vs. 5.6%, P < 0.001).
Multivariate analysis for survival outcomes
Multivariate Cox proportional analysis revealed that ‘TMB > 18.03/Mb and indel > 40%’ were independently associated with a favorable PFS (hazard ratio [HR] 0.07, 95% CI 0.01–0.57, P = 0.011) and OS (HR 0.09, 95% CI 0.01–0.73, P = 0.023) (Table 3). PD-L1 CPS ≥ 1 was also an independent factor for a favorable PFS (HR 0.45, 95% CI 0.24–0.85, P = 0.015) and OS (HR 0.39, 95% CI 0.19–0.77, P = 0.006). In addition, NLR ≥ median (2.8) was independently associated with a poor PFS (HR 1.67, 95% CI 1.01–2.76, P = 0.048) and OS (HR 1.76, 95% CI 1.01–3.06, P = 0.046), while ECOG PS ≥ 2 was an independent factor for a poor OS (HR 2.68, 95% CI 1.42–5.05, P < 0.001).
Discussion
In this study, we investigated the clinical value of the indel rate as a qualitative aspect of TMB in gastric cancer patients treated with nivolumab as a 3rd or later line of therapy. While a high TMB (> 18.03/Mb) was associated with favorable PFS and OS, a higher indel rate (> 40%) was also associated with favorable PFS and OS compared to those with a lower indel rate (≤ 40%). In particular, the favorable PFS and OS of patients with a higher indel rate were more prominent in the subgroup with TMB > 18.03/Mb. ‘TMB > 18.03/Mb with an indel rate of > 40%’ was independently associated with a favorable PFS and OS, and all five patients with dMMR fell into this category. To our knowledge, this is the first study to evaluate the clinical implications of the indel rate in advanced gastric cancer patients treated with ICI.
In patients with gastric cancer, a few studies have suggested that TMB may be clinically relevant in the context of ICI treatment. In an exploratory analysis from the Keynote-061 study, pembrolizumab (vs. paclitaxel) was associated with a reduced risk of death in a subgroup with TMB ≥ 10/Mb (HR 0.34, 95% CI 0.14–8.33), but not in a subgroup of TMB < 10/Mb (HR 0.97, 95% CI 0.70–1.34) [22]. Kim et al. reported that a higher TMB (≥ 14.31/Mb) as assessed by their in-house panel sequencing was associated with a favorable PFS [23]. In a phase Ib/II study of anti-PD-1 antibody toripalimab, patients with TMB ≥ 12/Mb assessed by whole-exome sequencing had a favorable OS compared to those with a lower TMB [24]. However, the interpretation of these studies of ICI-treated patients may be limited by their combining heterogeneous clinical settings (i.e., ICI as a first- to ≥ fourth-line treatment or the inclusion of patients with ICI plus chemotherapy) and the relatively small number of patients analyzed [23, 24]. In this study, based on a homogeneous cohort in terms of ICI treatment (nivolumab) and the line of therapy (3rd or later line), we were able to study the clinical outcomes according to different TMB levels, revealing favorable survival outcomes of patients with a high TMB (TMB > 18.03/Mb).
Since only a small fraction of non-synonymous mutations will lead to the generation of neo-antigens that can potentially be recognized by the host T cell repertoire, simple counting of the number of mutations may not fully represent the immunogenic mutation burden [9]. This may be an especially important issue for patients with gastric cancer, which reportedly harbors a relatively higher burden of SNV neo-antigens but a relatively lower burden of frameshift neo-antigens and strong mutant neo-antigens [14]. Given that indels are associated with the generation of highly immunogenic neo-antigens [9, 14, 15], previous studies have focused on the indel burden and revealed an association between the indel burden and favorable clinical outcomes with ICI in melanoma [14], non-small cell lung cancer [16] and intrahepatic cholangiocarcinoma [17]. In addition, MSI-high colorectal cancers had a significantly higher indel rate than MSS colorectal cancers [19]. Furthermore, it has been suggested that the extent of the response to anti-PD-1 therapy is associated with the indel burden in patients with MSI-high colorectal cancer [25]. However, there has been no previous report focusing on the clinical value of the indel burden in patients with gastric cancer. Therefore, our results may provide novel insights into the importance of considering the indel rate in addition to the TMB for gastric cancer patients.
While the high indel group showed favorable PFS (median 12.46 months) and OS (median 13.84 months) in the entire study population, this effect was particularly prominent in the subgroup of TMB > 18.03/Mb (median PFS not reached and median OS 35.4 months). Importantly, ‘TMB > 18.03/Mb with indel rate of > 40%’ was an independent factor for PFS and OS. Therefore, patients with a simultaneous high TMB and indel rate appear to be preferential candidates for nivolumab treatment. On the other hand, despite a high TMB level (> 18.03/Mb), patients with a lower indel rate (≤ 40%) exhibited a poor PFS (median 1.81 months) and OS (median 3.46 months). Therefore, a lower indel rate may be utilized to identify those with a high TMB who are expected to have poor clinical outcomes. Since the indel rate is easily obtainable with routine panel sequencing data by simply dividing the number of indel mutations by the total TMB, the predictive value of TMB in conjunction with the indel rate deserves further validation in independent cohorts and other clinical settings, such as first-line ICI plus chemotherapy combinations. The optimal cut-off point for the indel rate should be further investigated in future studies.
We also assessed the clinical impact of the indel burden itself, which is directly associated with the abundance of tumor-specific neo-antigens, revealing that a higher indel burden was associated with favorable PFS and OS. These results suggest that the indel burden may also serve as a predictor of favorable outcomes in this clinical setting. Nevertheless, we found that among patients with a high indel burden, those with a low indel rate still exhibited worse PFS and OS than those with a high indel rate. Although the exact biological mechanism of this finding remains unclear, jointly considering both TMB and indel rate appears to be practical in terms of predicting survival outcomes in this clinical context based on our analysis.
Another important aspect of this study is the delineation of the association between TMB and/or the indel rate and other tumor factors suggested to be predictive of an ICI response. While all five patients with dMMR fell into the category of ‘TMB > 18.03/Mb with an indel rate of > 40%’, one patient with pMMR also exhibited a similarly favorable PFS (19.5 months) and OS (35.4 months). These results imply that a high indel rate together with a TMB > 18.03/Mb may be a common feature associated with a favorable ICI response in both dMMR and pMMR tumors. While PD-L1 CPS ≥ 1 was another independent factor for favorable PFS and OS, the proportion of patients with PD-L1 CPS ≥ 1 was not different according to the different TMBs and/or indel rates. This is in line with previous studies showing a weak correlation between TMB and PD-L1 [23, 26, 27], indicating that these two independent factors may be complementarily utilized for the selection of patients for ICI treatment. The proportion of patients with diffuse-type histology tended to be higher in those with a higher indel rate in our analysis. Given that tumors with diffuse-type histology were reported to have a lower TMB than those with intestinal-type histology [28], the relationship between TMB and/or indel rate and the histologic classification requires further study.
One of the limitations of the current study is the use of our in-house NGS platform. Although our NGS platform has been shown to be a reliable modality [18,19,20,21], this requires further validation as a generalizable biomarker. Indeed, discrepancies among various sequencing platforms have been reported [29], and efforts are being made to achieve harmonization among different NGS platforms [30]. Another important drawback of this study is the fact that the tumor tissues used for the TMB analysis were not necessarily evaluated just prior to administrating nivolumab. Nevertheless, it would be difficult to obtain tumor tissue at that precise time point due to the need for an invasive procedure in an advanced setting and then obtain the NGS results in a timely manner considering the turn-around time of NGS.
In conclusion, TMB and the indel rate should be jointly considered to better predict the survival outcomes of gastric cancer patients treated with nivolumab. Our findings need to be validated in future studies based on independent cohorts, different NGS platforms and various clinical settings of ICI treatment in gastric cancer patients.
Abbreviations
- ICI:
-
Immune checkpoint inhibitors
- OS:
-
Overall survival
- CPS:
-
Combined positive score
- PFS:
-
Progression-free survival
- EBV:
-
Epstein–Barr virus
- dMMR:
-
Deficient mismatch repair protein
- MSI:
-
Microsatellite instability
- TMB:
-
Tumor mutation burden
- Mb:
-
Megabases in target lesion
- ORR:
-
Objective response rate
- Indel:
-
Insertion–deletion
- RECIST:
-
Response evaluation criteria in solid tumors
- FFPE:
-
Formalin-fixed, paraffin-embedded
- NGS:
-
Next-generation sequencing
- SNV:
-
Single-nucleotide variations
- HR:
-
Hazard ratio
- CI:
-
Confidence interval
- MMR:
-
Mismatch repair
- NLR:
-
Neutrophil-to-lymphocyte ratio
References
Sundar R, Smyth EC, Peng S, et al. Predictive Biomarkers of Immune Checkpoint Inhibition in Gastroesophageal Cancers. Front Oncol. 2020;10:763. https://doi.org/10.3389/fonc.2020.00763.
Kang YK, Boku N, Satoh T, et al. Nivolumab in patients with advanced gastric or gastro-oesophageal junction cancer refractory to, or intolerant of, at least two previous chemotherapy regimens (ONO-4538-12, ATTRACTION-2): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet. 2017;390:2461–71. https://doi.org/10.1016/s0140-6736(17)31827-5.
Janjigian YY, Shitara K, Moehler M, et al. First-line nivolumab plus chemotherapy versus chemotherapy alone for advanced gastric, gastro-oesophageal junction, and oesophageal adenocarcinoma (CheckMate 649): a randomised, open-label, phase 3 trial. Lancet. 2021;398:27–40. https://doi.org/10.1016/s0140-6736(21)00797-2.
Chen L, Kang Y, Tanimoto M, et al. ATTRACTION-04 (ONO-4538–37): A randomized, multicenter, phase 2/3 study of nivolumab (Nivo) plus chemotherapy in patients (Pts) with previously untreated advanced or recurrent gastric (G) or gastroesophageal junction (GEJ) cancer. Ann Oncol 2017;28:v266.
Fashoyin-Aje L, Donoghue M, Chen H, et al. FDA Approval Summary: Pembrolizumab for Recurrent Locally Advanced or Metastatic Gastric or Gastroesophageal Junction Adenocarcinoma Expressing PD-L1. Oncologist. 2019;24:103–9. https://doi.org/10.1634/theoncologist.2018-0221.
Kim ST, Cristescu R, Bass AJ, et al. Comprehensive molecular characterization of clinical responses to PD-1 inhibition in metastatic gastric cancer. Nat Med. 2018;24:1449–58. https://doi.org/10.1038/s41591-018-0101-z.
van Velzen MJM, Derks S, van Grieken NCT, et al. MSI as a predictive factor for treatment outcome of gastroesophageal adenocarcinoma. Cancer Treat Rev. 2020;86: 102024. https://doi.org/10.1016/j.ctrv.2020.102024.
Le DT, Durham JN, Smith KN, et al. Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade. Science. 2017;357:409–13. https://doi.org/10.1126/science.aan6733.
Jardim DL, Goodman A, de Melo GD, et al. The Challenges of Tumor Mutational Burden as an Immunotherapy Biomarker. Cancer Cell. 2021;39:154–73. https://doi.org/10.1016/j.ccell.2020.10.001.
Yarchoan M, Hopkins A, Jaffee EM. Tumor Mutational Burden and Response Rate to PD-1 Inhibition. N Engl J Med. 2017;377:2500–1. https://doi.org/10.1056/NEJMc1713444.
Samstein RM, Lee CH, Shoushtari AN, et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat Genet. 2019;51:202–6. https://doi.org/10.1038/s41588-018-0312-8.
Marabelle A, Fakih M, Lopez J, et al. Association of tumour mutational burden with outcomes in patients with advanced solid tumours treated with pembrolizumab: prospective biomarker analysis of the multicohort, open-label, phase 2 KEYNOTE-158 study. Lancet Oncol. 2020;21:1353–65. https://doi.org/10.1016/s1470-2045(20)30445-9.
Paz-Ares L, Langer C, Novello S, et al. Pembrolizumab (pembro) plus platinum-based chemotherapy (chemo) for metastatic NSCLC: Tissue TMB (tTMB) and outcomes in KEYNOTE-021, 189, and 407. 2019;30:v917–v8.
Turajlic S, Litchfield K, Xu H, et al. Insertion-and-deletion-derived tumour-specific neoantigens and the immunogenic phenotype: a pan-cancer analysis. Lancet Oncol. 2017;18:1009–21. https://doi.org/10.1016/s1470-2045(17)30516-8.
Smith CC, Selitsky SR, Chai S, et al. Alternative tumour-specific antigens. Nat Rev Cancer. 2019;19:465–78. https://doi.org/10.1038/s41568-019-0162-4.
Chae YK, Viveiros P, Lopes G, et al. Clinical and Immunological Implications of Frameshift Mutations in Lung Cancer. J Thorac Oncol. 2019;14:1807–17. https://doi.org/10.1016/j.jtho.2019.06.016.
Sui M, Li Y, Wang H, et al. Two cases of intrahepatic cholangiocellular carcinoma with high insertion-deletion ratios that achieved a complete response following chemotherapy combined with PD-1 blockade. J Immunother Cancer. 2019;7:125. https://doi.org/10.1186/s40425-019-0596-y.
Kim M, Mun H, Sung CO, et al. Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening. Nat Commun. 2019;10:3991. https://doi.org/10.1038/s41467-019-11867-6.
Kim JE, Chun SM, Hong YS, et al. Mutation Burden and I Index for Detection of Microsatellite Instability in Colorectal Cancer by Targeted Next-Generation Sequencing. J Mol Diagn. 2019;21:241–50. https://doi.org/10.1016/j.jmoldx.2018.09.005.
Chae H, Kim D, Yoo C, et al. Therapeutic relevance of targeted sequencing in management of patients with advanced biliary tract cancer: DNA damage repair gene mutations as a predictive biomarker. Eur J Cancer. 2019;120:31–9. https://doi.org/10.1016/j.ejca.2019.07.022.
Chun SM, Sung CO, Jeon H, et al. Next-Generation Sequencing Using S1 Nuclease for Poor-Quality Formalin-Fixed. Paraffin-Embedded Tumor Specimens J Mol Diagn. 2018;20:802–11. https://doi.org/10.1016/j.jmoldx.2018.06.002.
Shitara K, Özgüroğlu M, Bang Y-J, et al. The association of tissue tumor mutational burden (tTMB) using the Foundation Medicine genomic platform with efficacy of pembrolizumab versus paclitaxel in patients (pts) with gastric cancer (GC) from KEYNOTE-061. American Society of Clinical Oncology; 2020.
Kim J, Kim B, Kang SY, et al. Tumor Mutational Burden Determined by Panel Sequencing Predicts Survival After Immunotherapy in Patients With Advanced Gastric Cancer. Front Oncol. 2020;10:314. https://doi.org/10.3389/fonc.2020.00314.
Wang F, Wei XL, Wang FH, et al. Safety, efficacy and tumor mutational burden as a biomarker of overall survival benefit in chemo-refractory gastric cancer treated with toripalimab, a PD-1 antibody in phase Ib/II clinical trial NCT02915432. Ann Oncol. 2019;30:1479–86. https://doi.org/10.1093/annonc/mdz197.
Mandal R, Samstein RM, Lee KW, et al. Genetic diversity of tumors with mismatch repair deficiency influences anti-PD-1 immunotherapy response. Science. 2019;364:485–91. https://doi.org/10.1126/science.aau0447.
Ott PA, Bang YJ, Piha-Paul SA, et al. T-Cell-Inflamed Gene-Expression Profile, Programmed Death Ligand 1 Expression, and Tumor Mutational Burden Predict Efficacy in Patients Treated With Pembrolizumab Across 20 Cancers: KEYNOTE-028. J Clin Oncol. 2019;37:318–27. https://doi.org/10.1200/jco.2018.78.2276.
Yarchoan M, Albacker LA, Hopkins AC, et al. PD-L1 expression and tumor mutational burden are independent biomarkers in most cancers. JCI Insight 2019;4. https://doi.org/10.1172/jci.insight.126908.
Cai H, Jing C, Chang X, et al. Mutational landscape of gastric cancer and clinical application of genomic profiling based on target next-generation sequencing. J Transl Med. 2019;17:189. https://doi.org/10.1186/s12967-019-1941-0.
Budczies J, Allgäuer M, Litchfield K, et al. Optimizing panel-based tumor mutational burden (TMB) measurement. Ann Oncol. 2019;30:1496–506. https://doi.org/10.1093/annonc/mdz205.
Vokes NI, Liu D, Ricciuti B, et al. Harmonization of Tumor Mutational Burden Quantification and Association With Response to Immune Checkpoint Blockade in Non-Small-Cell Lung Cancer. JCO Precis Oncol 2019;3. https://doi.org/10.1200/po.19.00171.
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HDK, MHR and YKK contributed to the conceptual design of the study. HDK, RMH, YSP, SYL, MM and YKK were involved in data acquisition. HDK, MHR, YSP and YKK were involved in data analysis and interpretation. HDK and YKK were involved in writing and editing the manuscript. HDK, RMH, YSP, SYL, MM and YKK reviewed the manuscript. This study was supervised by YKK.
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Nothing directly related to this work. Outside of this work, YKK has served as a consultant for ALX Oncology, Zymeworks, Amgen, Novartis, Macrogenics, Daehwa, Blueprint, Surface Oncolgy, BMS, and Merck (MSD).
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Kim, HD., Ryu, MH., Park, Y.S. et al. Insertion–deletion rate is a qualitative aspect of the tumor mutation burden associated with the clinical outcomes of gastric cancer patients treated with nivolumab. Gastric Cancer 25, 226–234 (2022). https://doi.org/10.1007/s10120-021-01233-1
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DOI: https://doi.org/10.1007/s10120-021-01233-1