Molecular Classification Of Breast Cancer Research Articles

Breast cancer molecular subtype classification according to immunohistochemistry markers and its association with pathological characteristics among women attending tertiary hospitals in Tanzania

BackgroundBreast cancer immunohistochemistry is a biological characteristic of the tumour which has a role to diagnose molecular subtype, prognosticate and guide treatment and is categorised into 4 subtypes. Data in Tanzania was lacking and was based off data extrapolated from studies in Western Africa thus hypothesizing that women of African ancestry predominately develop Triple Negative Breast Cancer (TNBC). MethodsA retrospective cross-sectional study was carried out at two tertiary referral hospitals on participants who were recruited from the cancer registries from 2015 to 2022. Prevalence of each molecular subtype was determined and association between molecular subtype to demographic and pathological characteristics were evaluated. Predictors of molecular subtypes was then determined using logistic regression. ResultsTotal number of participants were 1214, median age was 50 (IQR: 41–61), median tumor size was 5 cm (IQR: 4–7) with lymph node positivity in 73.7 %. Immunohistochemistry studies showed estrogen, progesterone and Human Epidermal Growth Factor Receptor 2 (HER2) receptor positivity in 54.4 %, 34.4 % and 27.8 % of cases respectively. Molecular subtype classification prevalence for Luminal A was 21.17 % (95 % CI: 18.87–23.47), for Luminal B 35.75 % (95 % CI: 33.05–38.45), for HER2 enriched 11.86 % (95 % CI: 10.04–13.68) and for TNBC 31.22 % (95 % CI: 28.61–33.83). Significant association was seen between molecular subtype with age, tumor size, tumor grade and lymph node involvement. Predictors of Luminal tumors were larger tumor size (aOR 1.217, 95 % CI: 1.149–1.291) no lymph node involvement (aOR 0.429, 95 % CI: 0.313–0.589) while an advanced tumor grade reduced likelihood (aOR 0.041, 95 % CI: 0.011–0.019). ConclusionIn Tanzania Luminal B was most predominant subtype presenting at an earlier age and associated with more favorable pathological characteristics.

Abstract C101: Shared gene expression pattern among breast cancer subtypes and its association with prognostic variables in Colombian patients

Abstract Introduction: The current molecular classification of breast cancer has significantly improved treatment targeting and disease prognosis. However, the heterogeneity among subtypes also poses a limitation when proposing new targets that integrate common biological processes, hindering their applicability across the entire spectrum of the disease. In that sense, it is essential to gain a deeper understanding of the similarities and common mechanisms involved in the molecular subtypes of breast cancer. Therefore, in this study, we aimed to identify shared differentially expressed genes (DEGs) and biological processes among the different breast cancer subtypes that could potentially impact the presentation of clinically significant variables in Colombian patients diagnosed at the National Cancer Institute (NCI). Methods: We included 97 women diagnosed with breast cancer at the NCI in Colombia. From each patient, we collected tumor biopsy and adjacent non-tumoral tissue for RNA extraction and sequencing (RNA-seq). A comparative analysis of DEGs and gene set enrichment (GSE) was performed between tumor tissue and its corresponding adjacent non-tumor tissue for each subtype independently to identify common DEGs and enriched biological processes. Shared over- and under-expressed genes in at least two subtypes were tested for their association with clinically significant prognostic variables. Results: Among breast cancer subtypes, ER-/HER2+ and ER-/HER2- tumors showed the highest number of shared DEGs (22 genes), of which 19 were over-expressed and 3 under-expressed. In contrast, GSE analysis revealed a high proportion of shared biological processes (5), molecular functions (3), and cellular component classification (11) between ER+/HER2+ and ER-/HER2+ tumors, corresponding to mechanisms involved in tissue homeostasis and extracellular matrix structural constituents. Furthermore, the association with clinically significant prognostic variables was assessed for 22 over-expressed genes and 9 under-expressed genes shared in at least two subtypes. Of this set of 31 genes, 9 were significantly associated with the degree of tumor differentiation measured by the Bloom-Richardson (BR) score. Interestingly, tumor suppressor genes like ADAMTS18 showed a decline in expression as the BR score increased (fold-change (FC) in BR I: 14 vs BR II: 11; BR III: 5, p-value: 0.028). Conversely, oncogenes like EFNA4 showed the opposite trend, with an increase in expression as the BR score also increased (FC in BR I: 9 vs. BR II: 11 vs. BR III: 17, p-value: 0.019). Another identified shared over-expressed gene, JPT1, which is involved in β-catenin signaling, was found to be associated not only with higher BR scores but also with a higher proliferation index Ki67 (FC in <20%: 16.5 vs. ≥20%: 23; p-value: 0.05). Conclusions: Despite the high degree of molecular heterogeneity among subtypes, it is still possible to identify shared over and under-expressed genes in at least 2 subtypes with significant prognostic implications in breast cancer subtypes. Citation Format: Laura Rey-Vargas, Lina Maria Bejarano, Diego Felipe Ballen-Lozano, Silvia J. Serrano-Gomez. Shared gene expression pattern among breast cancer subtypes and its association with prognostic variables in Colombian patients [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C101.

Non-genetic heterogeneity and immune subtyping in breast cancer: Implications for immunotherapy and targeted therapeutics

Breast cancer (BC) is a complex and multifactorial disease, driven by genetic alterations that promote tumor growth and progression. However, recent research has highlighted the importance of non-genetic factors in shaping cancer evolution and influencing therapeutic outcomes. Non-genetic heterogeneity refers to diverse subpopulations of cancer cells within breast tumors, exhibiting distinct phenotypic and functional properties. These subpopulations can arise through various mechanisms, including clonal evolution, genetic changes, epigenetic changes, and reversible phenotypic transitions. Although genetic and epigenetic changes are important points of the pathology of breast cancer yet, the immune system also plays a crucial role in its progression. In clinical management, histologic and molecular classification of BC are used. Immunological subtyping of BC has gained attention in recent years as compared to traditional techniques. Intratumoral heterogeneity revealed by immunological microenvironment (IME) has opened novel opportunities for immunotherapy research. This systematic review is focused on non-genetic variability to identify and interlink immunological subgroups in breast cancer. This review provides a deep understanding of adaptive methods adopted by tumor cells to withstand changes in the tumor microenvironment and selective pressure imposed by medications. These adaptive methods include alterations in drug targets, immune system evasion, activation of survival pathways, and alterations in metabolism. Understanding non-genetic heterogeneity is essential for the development of targeted therapies.

Molecular Classification of Breast Cancer Using Weakly Supervised Learning

Molecular Classification of Breast Cancer Using Weakly Supervised Learning

Breast cancer in northern Peru: molecular subtypes and HER2 low.

This study aimed to understand the immunohistochemical profile of breast cancer and to identify the HER2 low subgroup in the northern macro-region of Peru. A cross-sectional study was conducted in 1176 patients from the Regional Institute of Neoplastic Diseases Northern Peru, from January 2016 to December 2023. We analyzed the data (age, histological type, grade and complementary results), with frequencies and percentages. The profile corresponded to: luminal B (45.6%); luminal A (24.7%); triple negative (18.2%); and HER2 positive non luminal (11.5%). In addition, 215 patients presented HER2 low (25.1% of those previously considered negative). This study provides evidence that the subtyping of breast cancer has changed, being luminal B the most frequent. It is essential to involve health policies to acquire targeted therapies considering HER2 low patients. Motivation for the study. Molecular classification of breast cancer allows the use of targeted treatments. Information on this profile in the northern macroregion of Peru is unknown. In addition, new therapies have appeared for a subgroup of patients. Main findings. In this study, the most frequent molecular subtypes were: luminal B, luminal A, triple negative and non-luminal HER2. Also, 18.3% of patients had low HER2 expression. Implications. Health policies should be aligned with scientific advances, to guarantee targeted therapies and to update the information in health manuals or protocols.

Comparative Study of Breast Cancer in Women Under 40 Compared to Older Women: The Experience of the Mohammed VI Center

Context: Breast cancer in young women is relatively rare worldwide, with patients under the age of 35 accounting for only 2% to 25% of all women diagnosed with this cancer. The objective of this study is to describe the epidemiological, clinical and histological profile of breast cancer in patients under 40 years of age. Methods: This is a comparative study between young and older patients at the Mohammed VI Center for Cancer Treatments. This study covered various aspects, including sociodemographic data and family history of cancer, gyneco-obstetrics, and circumstances of discovery of breast cancer, histopathological characteristics and molecular classification of breast cancer. Results: Among the 305 patients treated, 64 were aged 40 or younger, or 20.98% of the total. Breast cancer in our younger patients did not appear to differ significantly from that in older women, both in terms of sociodemographic factors and histopathological and molecular characteristics. The average age at first pregnancy was 23.85 years and the average parity was 1.58 children. 37.5% of young women were nulliparous. Among multiparous women, 95% breastfed their children. The average age of menarche was 13.34 years in young patients compared to 13.30 years in older patients (p = 0.85). Among the 6 postmenopausal patients (9.3% young women), the average age of onset of menopause was 39.17 years. 59.4% of young women used oral contraceptives, compared to 60.2% of older women. A family history of breast cancer was noted in 21.9% of young patients. The circumstances of discovery of breast cancer, most cases in both groups were identified by self-palpation or during a screening mammogram. The most common tumors were stage T2, involving lymph node invasion, and high-grade SBR II and III in 73.7% and 22.8% of cases, respectively. These were mainly invasive ductal carcinomas expressing hormonal receptors (ER and RP). About 30% were HER2+. No cases of bilateral cancer were observed in younger patients. Conclusion: Breast cancer in young women is a significant problem in our study population and its incidence is increasing worldwide. The absence of a systematic screening program before the age of 40 may explain the aggressive behavior of tumors in this age group.

Abstract A017: Perturbation and stability of PAM50 subtyping in population-based primary invasive breast cancer

Abstract PAM50 gene expression subtypes represent a cornerstone in molecular classification of breast cancer and are included in risk prediction models to guide therapy. We aimed to illustrate the impact of included genes and biological processes on subtyping while considering a tumor’s underlying clinical subgroup defined by ER, PR and HER2 status. To do this we used a population-representative and clinically annotated primary breast tumor cohort of 6233 samples profiled by RNA sequencing and applied a perturbation strategy of excluding co-expressed genes (gene sets). We demonstrate how PAM50 nearest centroid classification depends on biological processes present across, but also within, ER/PR/HER2 subgroups and PAM50 subtypes themselves. Our analysis highlights several key aspects of PAM50 classification. Firstly, we observed a tight connection between a tumor’s nearest and second nearest PAM50 centroid. Additionally, we show that second-best subtype is associated with overall survival in ER-positive, HER2-negative, and node negative disease. We also note that ERBB2 has little impact on PAM50 classification in HER2-positive disease regardless of ER-status, and that the Basal subtype is highly stable in contrast to the Normal subtype. Improved consciousness of the commonly used PAM50 subtyping scheme will aid in our understanding and interpretation of breast tumors that have seemingly conflicting PAM50 classification when compared to clinical biomarkers. Finally, our study adds further support in challenging the common misconception that PAM50 subtypes are distinct classes by illustrating that PAM50 subtypes in tumors represent a continuum that may have clinical implications. Citation Format: Srinivas Veerla, Lennart Hohmann, Deborah F. Nacer, Johan Vallon-Christersson, Johan Staaf. Perturbation and stability of PAM50 subtyping in population-based primary invasive breast cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A017.

Subtyping of Breast Carcinoma According to ER/PR and HER2/neu Expression: A Cross-Sectional Study from Southern Part of Assam, India

Introduction: Globally, breast carcinoma is the most prevalent and lethal form of cancer in women. Breast cancer is no longer considered a single disease but a complex heterogeneous disease with multiple genetic and epigenetic alterations. The prognosis and management of the disease depend on histological stage, type, grade, tumour size, lymph node status, and the status of hormonal receptors like ER, PR, and Her2/ neu. Recently, more attention has been given to the molecular classification of breast cancer. Aim: To analyse and compare the clinicopathological characteristics of invasive breast cancer in the four breast carcinoma subtypes defined by the immunohistochemical expression of Estrogen Receptor (ER), Progesterone Receptor (PR), and Human Epidermal Growth Factor Receptor 2 (Her2/neu). Materials and Methods: The cross-sectional study was conducted on 64 primary invasive breast carcinoma cases diagnosed on mastectomy specimens between February 1, 2018, and July 30, 2022, in the Department of Pathology at the histopathology section of Silchar Medical College and Hospital, Silchar, Assam, India. Age and tumour characteristics (morphology, grade, stage, and size) and nodal disease status were included in the data for analysis. Immunohistochemical markers were analysed on the sections of these diagnosed cases. IBM Statistical Packages for Social Sciences (SPSS) software was used for data analysis. Qualitative data was presented as frequency and percentage, while quantitative data was presented as mean ±{Standard Deviation (SD)}. The Chi- square test was used to determine the statistical significance of hormonal receptors with the various clinicopathological features. A p-value of <0.05 was considered statistically significant. Results: In present study of 64 cases of invasive breast carcinoma, the mean age of patients was 51.95±12.72 years. Subtyping was performed based on hormonal receptors. Authors found that the Luminal A variety 33 (51.6%) was the most common hormonal subtype in present study, followed by the basal subtype 24 (37.5%). The Luminal A subtype was found to be predominant among others. The majority of the patients (59.4%) had stage-I tumours, and Ductal type carcinoma was the most common (57.8%). Histologically, most of the tumours were poorly differentiated (28, 43.8%), and most were sized ≤2 cm (41, 64.1%). Lymph nodes were not palpable in most of the patients (43, 67.2%). Subtype comparison with respect to age, stage, histological grade, type, size, and nodal status revealed statistically significant outcomes (p-value of <0.05). Conclusion: Classification based on Immunohistochemistry (IHC) provides prognostic and therapeutic information that cannot be obtained from either ER/PR or Her2/Neu status alone. The present study provides the incidence of different molecular subtypes in the southern region of Assam, and comparison among them with statistical correlation offers improved and crucial treatment guidance. IHC classification as a clinical tool for ER/PR and Her2/Neu testing is widely accessible, reasonably priced, based on immunophenotype/biologic phenotype categorisation of breast cancer, and is prognostic as well as partly predictive and needs to be practiced invariably.

The Role of Serum Nestin in Diagnosis and Prognosis of Breast Cancer: A Prospective Observational Study.

The molecular classification of breast cancer has enabled targeted therapy for specific molecular subtypes. Nestin, which has been studied for its role in oncogenesis, could contribute to this direction. This study aimed to investigate the differences between serum nestin levels and molecular profiling, as well as histopathological tumor types, in women who underwent surgery for breast cancer. Women who underwent surgery for breast cancer at the Breast Unit of the 1st Propaedeutic Department of Surgery, Hippocration General Hospital, National and Kapodistrian University of Athens were prospectively included. Patients' demographic data were recorded and serum nestin levels were measured. Molecular biomarker analysis was performed, as well as histopathologic assessment. Seventy patients were included in the analysis. Among patients with breast cancer, 93% were estrogen receptor (ER) positive, 91% were progesterone receptor (PR) positive, and 43% were human epidermal growth factor receptor 2 (HER2) positive. Ki67 was expressed in 16% of patients and p53 was expressed in 32% of patients. Invasive ductal carcinoma was diagnosed in 80% of patients, with 44% of tumors classified as T1 and 46% as T2. Additionally, 43% were G1 and 56% were N0, while 34% were N1. No statistically significant difference was observed between serum nestin levels and ER, PR, HER2, Ki67, and p53 expression. Furthermore, no difference was observed between serum nestin levels and breast cancer histological type, size, N-stage, and grading. The diagnostic and prognostic role of circulating nestin for breast cancer was not confirmed and no correlation with immunohistochemistry results was observed. Thus, the necessity of larger prospective studies is enhanced.

Perturbation and stability of PAM50 subtyping in population-based primary invasive breast cancer

PAM50 gene expression subtypes represent a cornerstone in the molecular classification of breast cancer and are included in risk prediction models to guide therapy. We aimed to illustrate the impact of included genes and biological processes on subtyping while considering a tumor’s underlying clinical subgroup defined by ER, PR, and HER2 status. To do this we used a population-representative and clinically annotated early-stage breast tumor cohort of 6233 samples profiled by RNA sequencing and applied a perturbation strategy of excluding co-expressed genes (gene sets). We demonstrate how PAM50 nearest-centroid classification depends on biological processes present across, but also within, ER/PR/HER2 subgroups and PAM50 subtypes themselves. Our analysis highlights several key aspects of PAM50 classification. Firstly, we demonstrate the tight connection between a tumor’s nearest and second-nearest PAM50 centroid. Additionally, we show that the second-best subtype is associated with overall survival in ER-positive, HER2-negative, and node-negative disease. We also note that ERBB2 expression has little impact on PAM50 classification in HER2-positive disease regardless of ER status and that the Basal subtype is highly stable in contrast to the Normal subtype. Improved consciousness of the commonly used PAM50 subtyping scheme will aid in our understanding and interpretation of breast tumors that have seemingly conflicting PAM50 classification when compared to clinical biomarkers. Finally, our study adds further support in challenging the common misconception that PAM50 subtypes are distinct classes by illustrating that PAM50 subtypes in tumors represent a continuum with prognostic implications.

Attention-based GCN integrates multi-omics data for breast cancer subtype classification and patient-specific gene marker identification.

Breast cancer is a heterogeneous disease and can be divided into several subtypes with unique prognostic and molecular characteristics. The classification of breast cancer subtypes plays an important role in the precision treatment and prognosis of breast cancer. Benefitting from the relation-aware ability of a graph convolution network (GCN), we present a multi-omics integrative method, the attention-based GCN (AGCN), for breast cancer molecular subtype classification using messenger RNA expression, copy number variation and deoxyribonucleic acid methylation multi-omics data. In the extensive comparative studies, our AGCN models outperform state-of-the-art methods under different experimental conditions and both attention mechanisms and the graph convolution subnetwork play an important role in accurate cancer subtype classification. The layer-wise relevance propagation (LRP) algorithm is used for the interpretation of model decision, which can identify patient-specific important biomarkers that are reported to be related to the occurrence and development of breast cancer. Our results highlighted the effectiveness of the GCN and attention mechanisms in multi-omics integrative analysis and the implement of the LRP algorithm can provide biologically reasonable insights into model decision.

Classifying Breast Cancer Metastasis Based on Imaging of Tumor Primary and Tumor Biology.

The molecular classification of breast cancer has allowed for a better understanding of both prognosis and treatment of breast cancer. Imaging of the different molecular subtypes has revealed that biologically different tumors often exhibit typical features in mammography, ultrasound, and MRI. Here, we introduce the molecular classification of breast cancer and review the typical imaging features of each subtype, examining the predictive value of imaging with respect to distant metastases.

Investigation of mRNA Expression Levels of Tip60 and Related DNA Repair Genes in Molecular Subtypes of Breast Cancer

IntroductionStudies in breast cancer (BC) have been shown that many tumor cells carry mutations that disrupt the DNA damage response mechanism. In eukaryotic cells, the overexpression or deprivation of DSBs repair genes is linked closely to a higher risk of cancer. Patients and MethodsIn this study, mRNA expression levels of some genes, such as Tip60, ATM, p53, CHK2, BRCA1, H2AX, which are associated with DNA damage repair, were measured using RT-PCR method in tumor and matched-normal tissues of 58 patients with BC. ResultsAccording to the study results, 55% in Tip60, 59% in ATM, 57% in BRCA1, 48% in H2AX, 66% in CHK2, and 43% in p53 decreased in tumor tissue of patients compared to the matched normal tissue. When evaluated according to molecular subtypes, expression of all genes in the pathway was found significantly higher in normal tissues than in tumor tissues especially in Luminal B and Luminal B+HER2 groups. One of the most important results of the study is that CHK2 mRNA expressions in normal tissues were higher than tumor tissue in 90% of patients in Luminal B and Luminal B-HER2 + groups. This is the first study showing DNA repair genes’ expressions in molecular subtypes of breast cancer. In general, the decrease in the expression of DNA damage repair genes in tumor tissue indicates that these genes may have a role in the development of BC. Our study results also suggest that CHK2 may be a candidate marker in the molecular classification of breast cancer

Frontiers in Breast Pathology.

Frontiers in Breast Pathology.

Molecular Classification of Breast Cancer: Relevance and Challenges.

Appropriate patient management requires precise and meaningful tumor classification. Breast cancer classification continues to evolve from traditional morphologic evaluation to more sophisticated systems with the integration of new knowledge from research being translated into practice. Breast cancer is heterogeneous at the molecular level, with diversified patterns of gene expression, which is presumably responsible for the difference in tumor behavior and prognosis. Since the beginning of this century, new molecular technology has been gradually applied to breast cancer research on issues pertinent to prognosis (prognostic signature) and therapeutic prediction (predictive signature), and much progress has been made. To summarize the current state and the prospective future of molecular classification of breast cancer. Sources include recent medical literature on molecular classification of breast cancer. Identification of intrinsic tumor subtypes has set a foundation for refining the breast cancer molecular classification. Studies have explored the genetic features within the intrinsic cancer subtypes and have identified novel molecular targets that led to the innovation of clinical assays to predict a patient's prognosis and to provide specific guidelines for therapeutic decisions. With the development and implication of these molecular tools, we have remarkably advanced our knowledge and enhanced our power to provide optimal management to patients. However, challenges still exist. Besides accurate prediction of prognosis, we are still in urgent need of more molecular predictors for tumor response to therapeutic regimes. Further exploration along this path will be critical for improving a patient's prognosis.

Evaluation of the Sensitivity of Breast Cancer Cell Lines to Cardiac Glycosides Unveils ATP1B3 as a Possible Biomarker for the Personalized Treatment of ERα Expressing Breast Cancers.

The molecular classification of breast cancer (BC) dictates pharmacological treatment. Estrogen receptor α (ERα) expressing tumors are treated with 4OH-tamoxifen or fulvestrant, which inhibits the receptor, or with aromatase inhibitors (i.e., anastrozole, letrozole, and exemestane) that reduce the 17β-estradiol (E2) circulating blood levels. Besides such endocrine therapy (ET) drugs, ERα-positive BCs can be treated with epidermal growth factor receptor (EGF-R) inhibitors (i.e., gefitinib, erlotinib, and lapatinib) according to HER2 expression. Notwithstanding these anti-BC drugs, novel personalized approaches for BC treatment are required because prolonged administration of those pharmaceutics determines resistant phenotypes, which result in metastatic BC. We have recently reported that the cardiac glycoside (CG) (i.e., Na/K ATPase inhibitor) ouabain could be repurposed for ERα-positive primary and metastatic BC treatment as it induces ERα degradation and kills BC cells. Here, we evaluated if other CGs could represent additional treatment options for ERα-positive BCs and if the Na/K ATPase could be considered a biomarker for ERα-positive BC treatment. The results indicate that the ATP1B3 Na/K ATPase isoform can educate the choice for the personalized treatment of ERα-positive BC with CGs and that CGs could be more efficacious if they are administered in association with gefitinib.

Investigation of the differences of breast cancer molecular subtypes in radiological and histopathological parameters and their effects on lymphovascular invasion

Introduction: Breast cancer has heterogeneous tumor biology. Therefore, breast cancer is divided into molecular subtypes. However, molecular subtypes also show heterogeneity within themselves. In our study, we compared whether there were radiological and pathological differences between breast cancer molecular subtypes. Methods: The data of 569 patients operated on for breast cancer in our General Surgery clinic during an 8-year period were analyzed retrospectively. After dividing the patients into groups consisting of molecular subtypes, their radiological and pathological findings were compared. Results: According to the molecular classification of breast cancer, 47.6% of the patients were in the luminal A group, 23.9% in luminal B, 7.7% in HER2-enriched, and 12% in TN, and 8.8% in normal-like groups. DCIS and LCIS were significantly less common in the TN group than in the others (p=0.015). Tumor diameter and grade were considerably higher in the normal-like, HER2-enriched, and TN groups than in the other groups (p<0.001, p<0.001). LVI was significantly lower in luminal A and significantly higher in luminal B (p<0.001). Mortality was significantly higher in the luminal B and TN groups than in the other groups (p = 0.029). Conclusion: The addition of the basal-like group when classifying breast cancer into molecular subtypes showed histopathological differences. More studies are needed to investigate its effects on treatment and prognosis. Keywords: Breast cancer, Molecular subtype, Genotype, Immunohistochemistry, Survival

Immunohistochemical Features of Breast Cancer Seen in Women in Kinshasa, Democratic Republic of the Congo: A Six-Year Retrospective Study.

Introduction The molecular classification of breast cancer (BC) based on gene expression and then protein profile has made it possible to distinguish different molecular subtypes. The objective of this study was to describe immunohistochemical features of BC infiltrating women at the Nganda Hospital Center in Kinshasa, Democratic Republic of the Congo (DRC). Methods A retrospective study from 2014 to 2019 involved 190 patients with invasive BC who were enrolled at the Nganda Hospital Center. The tumors were analyzed histologically and classified after an immunohistochemical study into subtypes: luminal A, luminal B, HER2-overexpressed, and triple-negative. A chi-square test was performed to assess the relationship between age, histological grade, and these subtypes. Results The luminal A subtype (44.74%) was the most common, followed by luminal B (40.53%), triple-negative (10.53%), and HER2-overexpressed (4.20%). The mean age of the patients at diagnosis was 48.27 years. Of all cases, 94.21% were ductal, 2.63% were mucinous, and 2.11% were lobular. They were classified as grade I in 68.82% of the cases, grade II in 28.42% of the cases, and grade III in 3.16% of the cases. There was a significant association between histological grade and breast cancer subtypes (p < 0.0001), but no correlation was found with age (p = 0.467). Conclusion In our BC patients, the luminal A was predominant, while HER2-overexpressed was the least found. A strong association was noted between histological grade and molecular subtypes. These results should allow for important clinical and policy implications for BC control in the DRC.

Modern breast cancer diagnostic methods

Abstract World wide, breast cancer is the most common malignancy in women. Despite an increased incidence of this cancer, the mortality rates have been maintained at the same level. This is due to the continuous development of therapeutic, as well as diagnostic methods because appropriate, effective treatment is dependent on accurate diagnosis. At the same time, the success is that more and more patients undergo breast- and axillary lymph nodes-sparing surgeries, therefore, determining the initial advancement stage of breast cancer is absolutely essential for ensuring proper therapy. This is a review of current guidelines for both early and advanced stages of breast cancer diagnostics. The principles described are largely based on the work of the European School of Oncology (ESO) and the European Society for Medical Oncology (ESMO). The review includes the rule of imaging studies, especially mammography screening and histopathological evaluation with molecular classification of breast cancer.

Breast cancer in the era of precision medicine.

Breast cancer is a heterogeneous disorder with different molecular subtypes and biological characteristics for which there are diverse therapeutic approaches and clinical outcomes specific to any molecular subtype. It is a global health concern due to a lack of efficient therapy regimens that might be used for all disease subtypes. Therefore, treatment customization for each patient depending on molecular characteristics should be considered. Precision medicine for breast cancer is an approach to diagnosis, treatment, and prevention of the disease that takes into consideration the patient's genetic makeup. Precision medicine provides the promise of highly individualized treatment, in which each individual breast cancer patient receives the most appropriate diagnostics and targeted therapies based on the genetic profile of cancer. The knowledge about the molecular features and development of breast cancer treatment approaches has increased, which led to the development of new targeted therapeutics. Tumor genomic profiling is the standard of care for breast cancer that could contribute to taking steps to better management of malignancies. It holds great promise for accurate prognostication, prediction of response to common systemic therapies, and individualized monitoring of the disease. The emergence of targeted treatment has significantly enhanced the survival of patients with breast cancer and contributed to reducing the economic costs of the health system. In this review, we summarized the therapeutic approaches associated with the molecular classification of breast cancer to help the best treatment selection specific to the target patient.