Triple-negative breast cancer molecular subtyping and treatment progress.
Ontology highlight
ABSTRACT:
SUBMITTER: Yin L
PROVIDER: S-EPMC7285581 | biostudies-literature | 2020 Jun
REPOSITORIES: biostudies-literature
Publications
Triple-negative breast cancer molecular subtyping and treatment progress.
Yin Li L Duan Jiang-Jie JJ Bian Xiu-Wu XW Yu Shi-Cang SC
Breast cancer research : BCR 20200609 1
Triple-negative breast cancer (TNBC), a specific subtype of breast cancer that does not express estrogen receptor (ER), progesterone receptor (PR), or human epidermal growth factor receptor 2 (HER-2), has clinical features that include high invasiveness, high metastatic potential, proneness to relapse, and poor prognosis. Because TNBC tumors lack ER, PR, and HER2 expression, they are not sensitive to endocrine therapy or HER2 treatment, and standardized TNBC treatment regimens are still lacking. ...[more]
Similar Datasets
Project description:IntroductionTriple-negative breast cancer (TNBC) is considered the most aggressive type of breast cancer (BC) with limited options for therapy. TNBC is a heterogeneous disease and tumors have been classified into TNBC subtypes using gene expression profiling to distinguish basal-like 1, basal-like 2, immunomodulatory, mesenchymal, mesenchymal stem-like, luminal androgen receptor (LAR), and one nonclassifiable group (called unstable).ObjectivesThe aim of this study was to verify the clinical relevance of molecular subtyping of TNBCs to improve the individual indication of systemic therapy.Patients and methodsMolecular subtyping was performed in 124 (82%) of 152 TNBC tumors that were obtained from a prospective, multicenter cohort including 1,270 histopathologically confirmed invasive, nonmetastatic BCs (NCT01592825). Treatment was guideline-based. TNBC subtypes were correlated with recurrence-free interval (RFI) and overall survival (OS) after 5 years of observation.ResultsUsing PAM50 analysis, 87% of the tumors were typed as basal with an inferior clinical outcome compared to patients with nonbasal tumors. Using the TNBCtype-6 classifier, we identified 23 (15%) of TNBCs as LAR subtype. After standard adjuvant or neoadjuvant chemotherapy, patients with LAR subtype showed the most events for 5-year RFI (66.7 vs. 80.6%) and the poorest probability of 5-year OS (60.0 vs. 84.4%) compared to patients with non-LAR disease (RFI: adjusted hazard ratio [aHR] = 1.87, 95% confidence interval [CI] 0.69-5.05, p = 0.211; OS: aHR = 2.74, 95% CI 1.06-7.10, p = 0.037).ConclusionMolecular analysis and subtyping of TNBC may be relevant to identify patients with LAR subtype. These cancers seem to be less sensitive to conventional chemotherapy, and new treatment options, including androgen receptor-blocking agents and immune checkpoint inhibitors, have to be explored.
| S-EPMC8740062 | biostudies-literature
Project description:'Precision medicine' is a concept that by utilizing modern molecular diagnostics, an effective therapy is accurately applied for each cancer patient to improve their survival rates. The aim of this study was to compare the molecular subtypes of triple negative breast cancer (TNBC) between Taiwanese and other datasets.
2017-06-13 | GSE95700 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2017-08-27 | GSE103091 | GEO
Project description:As the field of translational 'omics has progressed, refined classifiers at both genomic and proteomic levels have emerged to decipher the heterogeneity of breast cancer in a clinically-applicable way. The integration of 'omics knowledge at the DNA, RNA and protein levels is further expanding biologic understanding of breast cancer and opportunities for customized treatment, a particularly pressing need in clinically triple negative tumors. For this group of aggressive breast cancers, work from multiple groups has now validated at least four major biologically and clinically distinct omics-based subtypes. While to date most clinical trial designs have considered triple negative breast cancers as a single group, with an expanding arsenal of targeted therapies applicable to distinct biological pathways, survival benefits may be best realized by designing and analyzing clinical trials in the context of major molecular subtypes. While RNA-based classifiers are the most developed, proteomic classifiers proposed for triple negative breast cancer based on new technologies have the potential to more directly identify the most clinically-relevant biomarkers and therapeutic targets. Phospho-proteomic data further identify targetable signalling pathways in a unique subtype-specific manner. Single cell profiling of the tumor microenvironment represents a promising way to allow a better characterization of the heterogeneity of triple negative breast cancer which could be integrated in a spatially resolved context to build an ecosystem-based patient classification. Multi-omic data further allows in silico analysis of genetic and pharmacologic screens to map therapeutic vulnerabilities in a subtype-specific context. This review describes current knowledge about molecular subtyping of triple negative breast cancer, recent advances in omics-based genomics and proteomics diagnostics addressing the diversity of this disease, key advances made through single cell analysis approaches, and developments in treatments including targeted therapeutics being tested in major clinical trials.
| S-EPMC9434975 | biostudies-literature
Project description:Triple negative breast cancer (TNBC) is characterized by the lack of estrogen and progesterone receptor expression and lacks HER2 overexpression or gene amplification. It accounts for 10-15% of incident breast cancers and carries the worst prognosis. TNBC is overrepresented among Black and pre-menopausal women and is associated with significant psychological and treatment-related burdens, including financial toxicity. Like other breast cancers, TNBC is biologically heterogeneous, leading to diverse clinical and epidemiological behaviors, however, unlike the other clinical subtypes, in TNBC we still lack tumor-specific targeted therapy. Early TNBC outcomes have improved due to the intensification of therapies, including improvements in polychemotherapy and the addition of immunotherapy. Future efforts are needed to identify targetable aberrations for specific drug therapy, prevent immune evasion, and increase social-economic support. Given that the name TNBC illustrates its lack of specifically targeted and effective therapy, we look forward to being able to retire the name in favor of a group of targetable entities within what is now called "TNBC".
| S-EPMC9392735 | biostudies-literature
Project description:MOTIVATION:Triple-negative breast cancer (TNBC) is a heterogeneous breast cancer group, and identification of molecular subtypes is essential for understanding the biological characteristics and clinical behaviors of TNBC as well as for developing personalized treatments. Based on 3,247 gene expression profiles from 21 breast cancer data sets, we discovered six TNBC subtypes from 587 TNBC samples with unique gene expression patterns and ontologies. Cell line models representing each of the TNBC subtypes also displayed different sensitivities to targeted therapeutic agents. Classification of TNBC into subtypes will advance further genomic research and clinical applications. RESULT:We developed a web-based subtyping tool TNBCtype for candidate TNBC samples using our gene expression meta data and classification methods. Given a gene expression data matrix, this tool will display for each candidate sample the predicted subtype, the corresponding correlation coefficient, and the permutation P-value. We offer a user-friendly web interface to predict the subtypes for new TNBC samples that may facilitate diagnostics, biomarker selection, drug discovery, and the more tailored treatment of breast cancer.
| S-EPMC3412597 | biostudies-literature
Project description:Triple-negative breast cancer (TNBC) is considered the most aggressive type of breast cancer with limited options for therapy. TNBC is a heterogeneous disease and tumours has been classified into TNBC subtypes using gene expression profiling to distinguish basal-like1 (BL1), basal-like2 (BL2), immunomodulatory (IM), mesenchymal (M), mesenchymal/stem-like (MSL), luminal androgen receptor (LAR) and one non-classifiable group (called unstable, UNS). The aim of this study was to verify the clinical relevance of molecular subtyping of TNBCs by expression analysis to improve the individual indication of systemic therapy.
2021-07-31 | GSE167213 | GEO
Project description:IntroductionTriple-negative breast cancers need to be refined in order to identify therapeutic subgroups of patients.MethodsWe conducted an unsupervised analysis of microarray gene-expression profiles of 107 triple-negative breast cancer patients and undertook robust functional annotation of the molecular entities found by means of numerous approaches including immunohistochemistry and gene-expression signatures. A triple-negative external cohort (n=87) was used for validation.ResultsFuzzy clustering separated triple-negative tumours into three clusters: C1 (22.4%), C2 (44.9%) and C3 (32.7%). C1 patients were older (mean=64.6 years) than C2 (mean=56.8 years; P=0.03) and C3 patients (mean=51.9 years; P=0.0004). Histological grade and Nottingham prognostic index were higher in C2 and C3 than in C1 (P<0.0001 for both comparisons). Significant event-free survival (P=0.03) was found according to cluster membership: patients belonging to C3 had a better outcome than patients in C1 (P=0.01) and C2 (P=0.02). Event-free survival analysis results were confirmed when our cohort was pooled with the external cohort (n=194; P=0.01). Functional annotation showed that 22% of triple-negative patients were not basal-like (C1). C1 was enriched in luminal subtypes and positive androgen receptor (luminal androgen receptor). C2 could be considered as an almost pure basal-like cluster. C3, enriched in basal-like subtypes but to a lesser extent, included 26% of claudin-low subtypes. Dissection of immune response showed that high immune response and low M2-like macrophages were a hallmark of C3, and that these patients had a better event-free survival than C2 patients, characterized by low immune response and high M2-like macrophages: P=0.02 for our cohort, and P=0.03 for pooled cohorts.ConclusionsWe identified three subtypes of triple-negative patients: luminal androgen receptor (22%), basal-like with low immune response and high M2-like macrophages (45%), and basal-enriched with high immune response and low M2-like macrophages (33%). We noted out that macrophages and other immune effectors offer a variety of therapeutic targets in breast cancer, and particularly in triple-negative basal-like tumours. Furthermore, we showed that CK5 antibody was better suited than CK5/6 antibody to subtype triple-negative patients.
| S-EPMC4389408 | biostudies-literature
Project description:BackgroundMolecular subtyping of triple-negative breast cancers (TNBCs) via gene expression profiling is essential for understanding the molecular essence of this heterogeneous disease and for guiding individualized treatment. We aim to devise a clinically practical method based on immunohistochemistry (IHC) for the molecular subtyping of TNBCs.Materials and methodsBy analyzing the RNA sequencing data on TNBCs from Fudan University Shanghai Cancer Center (FUSCC) (n = 360) and The Cancer Genome Atlas data set (n = 158), we determined markers that can identify specific molecular subtypes. We performed immunohistochemical staining on tumor sections of 210 TNBCs from FUSCC, established an IHC-based classifier, and applied it to another two cohorts (n = 183 and 214).ResultsWe selected androgen receptor (AR), CD8, FOXC1, and DCLK1 as immunohistochemical markers and classified TNBCs into five subtypes based on the staining results: (a) IHC-based luminal androgen receptor (IHC-LAR; AR-positive [+]), (b) IHC-based immunomodulatory (IHC-IM; AR-negative [-], CD8+), (c) IHC-based basal-like immune-suppressed (IHC-BLIS; AR-, CD8-, FOXC1+), (d) IHC-based mesenchymal (IHC-MES; AR-, CD8-, FOXC1-, DCLK1+), and (e) IHC-based unclassifiable (AR-, CD8-, FOXC1-, DCLK1-). The κ statistic indicated substantial agreement between the IHC-based classification and mRNA-based classification. Multivariate survival analysis suggested that our IHC-based classification was an independent prognostic factor for relapse-free survival. Transcriptomic data and pathological observations implied potential treatment strategies for different subtypes. The IHC-LAR subtype showed relative activation of HER2 pathway. The IHC-IM subtype tended to exhibit an immune-inflamed phenotype characterized by the infiltration of CD8+ T cells into tumor parenchyma. The IHC-BLIS subtype showed high expression of a VEGF signature. The IHC-MES subtype displayed activation of JAK/STAT3 signaling pathway.ConclusionWe developed an IHC-based approach to classify TNBCs into molecular subtypes. This IHC-based classification can provide additional information for prognostic evaluation. It allows for subgrouping of TNBC patients in clinical trials and evaluating the efficacy of targeted therapies within certain subtypes.Implications for practiceAn immunohistochemistry (IHC)-based classification approach was developed for triple-negative breast cancer (TNBC), which exhibited substantial agreement with the mRNA expression-based classification. This IHC-based classification (a) allows for subgrouping of TNBC patients in large clinical trials and evaluating the efficacy of targeted therapies within certain subtypes, (b) will contribute to the practical application of subtype-specific treatment for patients with TNBC, and (c) can provide additional information beyond traditional prognostic factors in relapse prediction.
| S-EPMC7543239 | biostudies-literature
Project description:Triple-negative (TN) breast cancers need to be refined in order to identify therapeutic subgroups of patients. We conducted an unsupervised analysis of microarray gene-expression profiles of 107 TN breast cancer patients and undertook robust functional annotation of the molecular entities found by means of numerous approaches including immunohistochemistry and gene-expression signatures. An 87 TN external cohort was used for validation. Fuzzy clustering separated TN tumours into three clusters: C1 (22.4%), C2 (44.9%) and C3 (32.7%). C1 patients were older (mean = 64.6 years) than C2 (mean = 56.8 years; P = 0.03) and C3 patients (mean = 51.9 years; P = 0.0004). Histological grade and Nottingham prognostic index were higher in C2 and C3 than in C1 (P < 0.0001 for both comparisons). Significant event-free survival (EFS) (P = 0.03) was found according to cluster membership: patients belonging to C3 had a better outcome than patients in C1 (P = 0.01) and C2 (P = 0.02). EFS analysis results were confirmed when our cohort was pooled with external cohort (n = 194; P = 0.01). Functional annotation showed that 22% of TN patients were not basal-like (C1). C1 was enriched in luminal subtypes and positive androgen receptor (luminal androgen receptor [LAR]). C2 could be considered as an almost pure basal-like cluster. C3, enriched in basal-like subtypes, but to a lesser extent, included 26% of claudin-low subtypes. Dissection of immune response showed that high immune response (HIR) and low M2-like macrophages were a hallmark of C3, and that these patients had a better EFS than C2 patients, characterized by low immune response (LIR) and high M2-like macrophages: P = 0.02 for our cohort, and P = 0.03 for pooled cohorts. We identified 3 subtypes of TN patients: LAR (22%), basal-like with LIR and high M2-like macrophages (45%) and basal-enriched with HIR and low M2-like macrophages (33%). We pointed out that macrophages and other immune effectors offer a variety of therapeutic targets in breast cancer, and particularly in TN basal-like tumours. Furthermore, we showed that CK5 antibody was better suited than CK5/6 antibody to subtype TN patients. Subtyping molecular characterization within a cohort of 107 TN-IHC by means of gene expression profiling
2015-05-19 | E-GEOD-58812 | biostudies-arrayexpress