European School of Oncology – Review
Breast cancer, screening and diagnostic tools: All you need to know

https://doi.org/10.1016/j.critrevonc.2020.103174Get rights and content

Highlights

  • Nearly two million cases of breast cancer are diagnosed each year worldwide.

  • Multidisciplinary approaches are used to develop screening and diagnostic tools.

  • Key information is provided on breast cancer for medical and research professionals.

  • Breast cancer biology, standard and innovative detection tools are presented.

  • This information is needed to develop better diagnostic and screening tools.

Abstract

Breast cancer is one of the most frequent malignancies among women worldwide. Methods for screening and diagnosis allow health care professionals to provide personalized treatments that improve the outcome and survival. Scientists and physicians are working side-by-side to develop evidence-based guidelines and equipment to detect cancer earlier. However, the lack of comprehensive interdisciplinary information and understanding between biomedical, medical, and technology professionals makes innovation of new screening and diagnosis tools difficult. This critical review gathers, for the first time, information concerning normal breast and cancer biology, established and emerging methods for screening and diagnosis, staging and grading, molecular and genetic biomarkers. Our purpose is to address key interdisciplinary information about these methods for physicians and scientists. Only the multidisciplinary interaction and communication between scientists, health care professionals, technical experts and patients will lead to the development of better detection tools and methods for an improved screening and early diagnosis.

Introduction

Each year, 2.1 million women are diagnosed with breast cancer (WHO, 2020). In the United States (US), the five-year relative survival after diagnosis for localized breast cancer is 98.9 %, for regional cancer is 85.7 %, for distant cancer is 28.1 % and for unknown disease stage is 55.1 % (National Cancer Institute, 2020). Early diagnosis strategies aim to increase the number of accurately identified early stage breast cancers by increasing the access to diagnostic services and by providing opportune cancer treatment (WHO, 2020). Early diagnosis is key for improving patients' survival, as it gives insight regarding the most appropriate therapeutic strategy for each case (Rivera-Franco and Leon-Rodriguez, 2018). Breast cancer screening (BCS) is defined as testing women before any evident symptoms appear, generally by mammography and clinical breast examination (CBE) to detect and treat cancers or pre-cancers (WHO, 2020). Public and professional knowledge with patient awareness of the disease is necessary to take actions such as determining what cases need to use screening and diagnostic tools (Fig. 1). It is our opinion that multidisciplinary communication between technology experts, biomedical researchers and physicians should be improved with the goal to ameliorate the survival rate of patients by providing reliable screening and diagnostic tools.

The US National Comprehensive Cancer Network (NCCN) 2019 guidelines recommended performing an annual CBE and mammography for women over 40 years old, as there are no randomized studies that suggest a benefit in screening women under this age (Qaseem et al., 2007; Chetlen et al., 2016; Gradishar et al., 2020; Bevers et al., 2019). This recommendation is the preferred screening approach, making it the gold standard in the US (Qaseem et al., 2007; Chetlen et al., 2016; Gradishar et al., 2020). It has been observed that BCS for women of all ages, with an average risk of having the disease, is associated with a mortality reduction in the US (Myers et al., 2015). However, more studies regarding which specific populations in terms of age and ethnicity are recommended for early BCS as there is still uncertainty (Qaseem et al., 2007; Chetlen et al., 2016; Gradishar et al., 2020; Myers et al., 2015). The practice of BCS lies in the clinical judgement of health care professionals based on scientific evidence. Nevertheless, the interaction between physicians, researchers and technology experts is necessary to refine the application of BCS.

The results obtained from BCS and diagnostic tools could be misinterpreted leading to false positives, false negatives, re-tests, and overdiagnosis (Welch et al., 2016). Hence, artificial intelligence (AI) based algorithms are under constant development and evaluation by technology experts, biomedical researchers and physicians to decrease the possibility of misinterpretations. Another issue is the discomfort and stress generated during screening and diagnostic procedures which reduce the willingness of patients to perform the tests (Fang et al., 2014; Dullum et al., 2000; Aro et al., 1996; Mazzocco et al., 2019; Rutter et al., 1992). It is common that diagnostic equipment and tests are mostly accessible in specialized hospitals and cannot be easily reached by the population living in rural areas or that have transportation impairments (Iezzoni et al., 2010). Due to this possible obstacle, BCS campaigns have been done, emphasizing rural areas, which have helped women at risk to increase their survival rate (Poiseuil et al., 2019). In definitive terms, improving accessibility and comfort of BCS and diagnostic tools could improve the detection of patients living in rural areas allowing early therapy if required.

Molecular analysis such as the identification of mutations and gene expression profiling/signatures (GEP/S) are commonly used to determine breast cancer predisposition, subtype and aggressiveness, respectively. It has been observed that 5%–10% of breast cancer patients have a genetic predisposition to develop the disease (Claus et al., 1996). After initial screening, the analysis of GEP/S in breast biopsies is a complex task as each cancer develops differently in many aspects from one person to another, impairing the accuracy of the analysis (Dagogo-Jack and Shaw, 2018). The comprehension of gene-set expression abnormalities and their correlation with the aggressiveness involves an exhaustive and accurate task using bioinformatics and machine learning (ML) tools (Futschik et al., 2018). Recent studies support the use of GEP/S to improve treatment decisions which could lead to better patient outcomes (Gradishar et al., 2020; Katz et al., 2015; Özmen et al., 2019).

A great amount of patient’s data has been collected worldwide during different phases of breast cancer with the use of multiple screening and diagnostic tools (Graphical abstract). These data correspond to a variety of tests, including physical examination, imaging, immunohistochemical analysis, GEP/S, and large-scale genomics. The analysis of these data would help in the understanding of what is needed to develop devices or diagnostic algorithms updating clinical guidelines. Advances in systems biology could integrate the available information, to generate new biomarker panels and devices (Generalov et al., 2019). However, many low-to-middle income countries lack the capacity to condense information and integrate an international medical and scientific network such as the Global Cancer Observatory (GLOBOCAN) (Guerrero et al., 2018; de Souza et al., 2016; Ferlay et al., 2019). Combining different low-cost analysis procedures would lead to better access for more accurate recommendations and the treatment of cancer at an early stage in developing countries (Liedtke et al., 2018; van Seijen et al., 2018).

It is important to provide the necessary information concerning the most common diagnostic procedures and the use of new combinatorial approaches. This will support the decision of health professionals regarding the application of one tool over another. In addition, understanding the physiology of the breast and how it changes during cancer is key to develop new screening and diagnostic tools (Graphical abstract). In this comprehensive review, we introduce and summarize key information about the normal breast tissue, cancer biology, current methods of screening and detection, emerging methods of detection, staging, grading and classification of breast cancer, as well as molecular and genetic biomarkers (Fig. 2). Nowadays, the ability to comprehend the main aspects of breast cancer biology and the most used methods of detection will allow the development of innovations to satisfy patient needs in three aspects: accuracy, comfort and accessibility.

Section snippets

Normal breast tissue

Breast cancer awareness entails the understanding of the differences between the normal physiology of the breast and a lesion that could result benign, precancerous or cancerous (Sasaki et al., 2018; Waldman et al., 2019; Srivastava et al., 2018). The NCCN recommends that women should be familiar with their breast and be able to communicate with the health care provider to transmit any sign of alarm (Bevers et al., 2019). Strengthen the knowledge of the normal physiology would prevent or

Breast Cancer generalities

Cancer can be caused by a mix of genetic predisposition, environmental agents and lifestyle (Fig. 4) (National Cancer Institute, 2020). Age and breast density are naturally occurring factors that could increase the risk of developing the disease (Feng et al., 2018). In addition, it is well known that changes in the circadian rhythm, as well as alcohol and tobacco consumption are agents that augment the probability of having breast cancer (Lin et al., 2015; Stevens, 2005; Heitz et al., 2018).

Breast Cancer Screening recommendations

Recommendations for BCS depend on the risk factors of each woman. Nonetheless, patients can be classified into two major groups: average population risk and high associated risk (e.g. BRCA1/2 mutations).

Established methods of screening and diagnosis

Current methods of screening and detection in clinical practice include Breast Physical Examination (BPx), Mammography (including full-field digital mammography (FFDM) and DBT), Ultrasonography and MRI (Fig. 5). Positron Emission Tomography/Computed Tomography (PET/CT) is commonly used for diagnosis and staging. All these methods vary between one another regarding their utility, sensitivity and specificity.

As mentioned before, mammography is recommended for BCS by the ACR, Society of Breast

Emerging methods of screening and diagnosis

Besides current methods of BCS such as BPx, mammography, ultrasonography and MRI, new technologies have emerged fusing biophysics characteristics with clinical data (Yadav et al., 2019). For instance, tissue rigidity and other mechanical characteristics of the tumor during breast cancer progression may lead to novel diagnostic tools (Yadav et al., 2019; Lozano et al., 2020). It has been suggested that changes in the rigidity and stiffness of the extracellular matrix persist for longer periods

Biopsy

After the detection of an anomaly in breast tissue by imaging techniques, biopsies are required to provide an accurate diagnosis. A biopsy is an invasive procedure where abnormal breast fluid or tissue is removed for cytological, histological and molecular analyzes. The test is recommended only in suspected cases of cancer based on the BI-RADS lexicon scale used by radiologists (Elmore et al., 2015). Tumor biopsy is still the gold standard technique that confirms if a tumor is benign or

Staging and grading of breast tumors

Anatomical staging and grading methods are used to determine tumor characteristics such as size, growth rate and spread. They are usually performed after diagnosis by established imaging methods and biopsies to select the most appropriate treatment (Fig. 5). Grading refers to the appearance of cancer cells compared to healthy cells and how quickly they may grow and spread. Breast tumors can be low-grade (uniform like appearance and slow-growing cells), intermediate-grade (bigger cells with

Breast Cancer classification

Breast cancer can be classified according to the area and cell types that are originally affected. Based on these criteria, the two main categories are carcinomas and sarcomas.

Breast Cancer biomarkers

Breast cancers are phenotypically diverse among patients in terms of growth rate, aggressiveness, hormone dependance and therapy response. Molecular biomarkers have been identified in an attempt to characterize such heterogeneity and define molecular subtypes for a better prognosis and cancer management (Feng et al., 2018; Dai et al., 2016; Mosly et al., 2018; Hilton et al., 2018). The current established molecular biomarkers are those related to cell proliferation (Ki67) and receptor status:

Issues with current screening and diagnostic tools: the need for new or improved techniques

Breast cancer diagnosis and treatment could involve repeated visits of patients to fully equipped medical centers. It has been shown that living in rural areas can affect the access to breast cancer diagnostic tools, potentially resulting in delays in cancer diagnosis (Ambroggi et al., 2015). Additionally, being far from primary health centers and hospitals, prevents the availability of treatment, surgery, or appropriate interventions, decreasing the possibility of positive outcomes and patient

Conclusion

Even though breast cancer survival rate after 5 years of diagnosis is very high, it is still a disease difficult to diagnose and treat as its behavior differs from one person to another. Our capacity to detect cancer, define its stage and future aggressiveness is based on multiple tools for screening and diagnosis. This represents a multidisciplinary challenge for biomedical and technological scientists, as understanding tumor heterogeneity and physiological variations among patients requires

Data availability statement

The corresponding author can answer or provide information on request to any comments or questions regarding this publication.

Funding

Collaboration grants Universidad San Francisco de Quito, USFQ HUBi: 12468, 12467; School of Medicine Grant HUBi:16925. The funding source is the Universidad San Francisco de Quito, USFQ. This institution was not involved in the study design, in the collection, analysis and interpretation of data; in the writing of the manuscript; and in the decision to submit the manuscript for publication.

CRediT authorship contribution statement

Diego Barba: Methodology, Investigation, Visualization, Writing - review & editing. Ariana León-Sosa: Methodology, Investigation, Visualization, Writing - review & editing. Paulina Lugo: Methodology, Investigation, Visualization, Writing - review & editing. Daniela Suquillo: Methodology, Investigation, Visualization, Writing - review & editing. Fernando Torres: Investigation, Writing - review & editing, Funding acquisition. Frederic Surre: Methodology, Investigation, Writing - review & editing.

Declaration of Competing Interest

The authors report no declarations of interest.

Acknowledgments

We are thankful to the Universidad San Francisco de Quito - USFQ, and the School of Medicine - USFQ, for funding this project, their constant support to our work and initiatives. To the "Servicio de Cirugía" at the "Hospital de Los Valles," "Instituto de Investigaciones en Biomedicina - USFQ," to the Mico-Act Research Consortium, Quito, Ecuador and "Sistemas Médicos," SIME-USFQ. We would like to special thank Estefania Roldán for revising our article and comments, to Esther Wisdom, Serena

Diego Barba Medical Doctor, Biomedical Discovery Team Research Fellow. Universidad San Francisco de Quito USFQ, Colegio de Ciencias de la Salud, Escuela de Medicina. Diego obtained his medical doctor degree on October 4th, 2019 at the Universidad San Francisco de Quito, USFQ. He joined the Biomedical Discovery Team in 2016, his work is centered on bioinformatics, gene expression analysis, and development of genetic signatures for breast cancer diagnosis. Diego was a medical trainee in Oncology

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  • Cited by (0)

    Diego Barba Medical Doctor, Biomedical Discovery Team Research Fellow. Universidad San Francisco de Quito USFQ, Colegio de Ciencias de la Salud, Escuela de Medicina. Diego obtained his medical doctor degree on October 4th, 2019 at the Universidad San Francisco de Quito, USFQ. He joined the Biomedical Discovery Team in 2016, his work is centered on bioinformatics, gene expression analysis, and development of genetic signatures for breast cancer diagnosis. Diego was a medical trainee in Oncology and Rheumatology in Lapeyronie and Saint Éloi Hospitals in Montpellier, France. He also was part of the Oncology Team at the Hospital Metropolitano in Quito, Ecuador. Diego plans a career as an oncologist while doing research to support advances in the field and provide adequate help to cancer patients as a medical doctor and scientist.

    Ariana León-Sosa Biomedical Discovery Team Manager and Research Fellow. Universidad San Francisco de Quito USFQ, Colegio de Ciencias de la Salud, Escuela de Medicina.Ariana obtained her B.Sc. degree with an extended major in Biomedical Science from the University of Queensland, Australia in 2017. She was part of the Metabolism and Microbiome in Pregnancy lab from the School of Chemistry and Molecular Biosciences as an undergraduate student. In early 2019, she collaborated in the “Instituto Nacional de Salud Pública-INSPI” in Guayaquil- Ecuador developing research projects related to epidemiology and public health. Later in the same year, Ariana joined the Biomedical Discovery Team at USFQ. Her current work focuses on understanding cancer progression and the therapeutic potential of mitochondria in various diseases including tissue damage.

    Paulina Lugo Medical Doctor, General Surgeon, Breast Surgeon, Hospital de los Valles, Quito-Ecuador. Paulina is a general surgeon with eight years of experience in Spain and Ecuador. She completed her master’s degree in Senology at the University of Barcelona, ​​Spain, in 2018. She has completed internships in the Breast Unit of the Clínica Universidad de Navarra in Pamplona, ​​Spain; Hospital Clinic y Vall d’Hebron in Barcelona, ​​Spain, and the European Institute of Oncology in Milán, Italy. She is currently a member of the Surgery staff of the Hospital de Los Valles in Quito Ecuador being her main interest to improve hospital management and the application of high-quality standards for breast cancer screening, diagnostic, and treatments. Paulina also collaborates with the Biomedical Discovery Team at the USFQ, in research projects related to understanding breast cancer progression.

    Daniela Suquillo Biomedical Discovery Team Trainee. Universidad San Francisco de Quito USFQ, Colegio de Ciencias Biológicas y Ambientales, Escuela de Biotecnología. Daniela is a Biotechnology Engineering Student at the Universidad San Francisco de Quito, USFQ. She has been working with Andres Caicedo and the Biomedical Discovery Team since 2019 in research projects related to cancer progression. Daniela’s future perspectives are focused on continuing its research career in the biomedical field, specifically on understanding the biological processes involved in genetic diseases and cancer in order to provide effective therapies.

    Fernando Torres Medical Doctor, Surgeon, Hospital de los Valles, Quito-Ecuador. Professor at the Universidad San Francisco de Quito USFQ, Colegio de Ciencias de la Salud, Escuela de Medicina. Fernando is a Doctor of Medicine and Surgery who graduated from the Central University of Ecuador, and Surgeon General graduated from the International University of Ecuador. Fernando completed two medical degrees at the Catholic University of Chile in Advanced Laparoscopy and Esophageal-Gastric Bariatric Surgery; he is Fellow of the American College of Surgeons since 2014; Instructor in Medical Simulation endorsed by the Harvard Medical Simulation Center and the Valdecilla Virtual Hospital and the Francisco de Vitoria University of Madrid. Regional director of the ATLS program (advanced life support for trauma) and director of the Program of Experimental Surgery and Surgical Research (CEIQ). Fernando is Professor and Coordinator within the School of Medicine of the Universidad San Francisco de Quito in the subjects of Anatomy, Surgery, Surgical Techniques as well as support in the coordination of the international rotary at the Hospital de Los Valles. He shows great interest in surgical and technological research directing the manufacture of medical simulation equipment for the region.

    Frederic Surre Assistant Professor and Researcher at the University of Glasgow. Frederic has been working on designing sensors systems for applications in gas sensing, biomedical and civil engineering. He received the French MEng, Master of Advanced Studies and PhD in Electronic Engineering (computational electromagnetics) from Toulouse INP, France in 1998, 1998 and 2003, respectively. After post-doctoral positions at Queen Mary, University of London, Trinity College Dublin, and Dublin City University, he was appointed Assistant Professor in Optical Systems at City, University of London. His research interests include modelling of light matter interactions and the design of optical sensor systems using optical fibers and integrated photonic circuits.

    Lionel Trojman Professor Electrical and Electronics Engineering Department of the USFQ, Ecuador. Professor Institut Supérieur d’Électronique de Paris (ISEP) in France. Lionel Trojman was born in Marseille, France. He received the B.Sc. degree in physics from the Faculty of Saint-Charles, University of Provence, Marseille, France, in 2002. He received the M.Sc. degree in physics applied to micro- and nano-electronics and in electrical engineering in microelectronic and Telecommunication from the Ecole Polytechnique Universitaire de Marseille, University of Provence, in 2004. He received his Ph.D. degree in Electrical Engineering at the KULeuven in partnership with the IMEC, Belgium, in 2009. He was working as full time Professor to the electrical and electronics engineering department of the USFQ, Ecuador, since 2009 and he is currently working as professor for Isep, France, since 2019. His current research interests include transport for ultra-scaled MOSFET (down to 22nm) with UTEOT high-k dielectrics with conventional and novel architectures (FDSOI) for CMOS technologies. He is also working on memory devices such as ReRAM, MTJ, and finally power electronic devices implemented in GaN technology. Recently he is involved in Integrated circuit topic using 180, 90 and 32/28nm technology node for IoT application.

    Andrés Caicedo Professor at the Universidad San Francisco de Quito USFQ, Colegio de Ciencias de la Salud, Escuela de Medicina. Andrés obtained his Ph.D. with Honors in Biomedicine in 2013, he has a specialization in Regenerative Medicine by the Biomedicine Research Institute and Biotherapies (IRMB) and a specialization in Management, all of them from the University of Montpellier. From 2016 to the present, he is a Professor and Researcher at the School of Medicine of the San Francisco University of Quito (USFQ). He is the leader of the “Biomedical Discovery Team”. His team is interested in the generation of new therapies for the repair of tissue affected by age, environmental stress, or damage. He also has experience in the understanding of the tumor microenvironment especially in how stem cells could affect its progression. In 2017 he was part of the awarded Innovators Under 35 in Latin America prize by the Massachusetts Institute of Technology Review with the technique of "Artificial transplantation of mitochondria for medical purposes, MitoCeption". Winner of the 2017 Innovation Call “Ecuador Changes the World” for the Alliance for Entrepreneurship and Innovation of Ecuador (AEI) with the project “Prediction of susceptibility to Diabetes and Metabolic Syndrome by the Measurement of Circulating Mitochondrial DNA”. Member and Chairman of the Scientific Commission of the National Institute of Transplantation of Tissue Organs and Cells (INDOT) in 2019. Since 2018, he has been responsible for the R&D department at “Sistemas Médicos USFQ”. In 2020 he was elected Regional Secretary of the International Society for Gene and Cell Therapy (ISCT), https://isctglobal.org/. He seeks to develop solid ventures with the support and interaction between the private sector, academia and the Government to position Ecuador and the region as leaders in the application of effective and safe stem cells-based therapies.

    1

    Diego Barba and Ariana León-Sosa are co-first authors.

    2

    Paulina Lugo and Daniela Suquillo are co-second authors.

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