Classification and gene selection of triple-negative breast cancer subtype embedding gene connectivity matrix in deep neural network.

Triple-negative breast cancer (TNBC) has been a challenging breast cancer subtype for oncological therapy. Normally, it can be classified into different molecular subtypes. Accurate and stable classification of the six subtypes is essential for personalized treatment of TNBC. In this study, we proposed a new framework to distinguish the six subtypes of TNBC, and this is one of the handful studies that completed the classification based on mRNA and long noncoding RNA expression data. Particularly, we developed a gene selection approach named DGGA, which takes correlation information between genes into account in the process of measuring gene importance and then effectively removes redundant genes. A gene scoring approach that combined GeneRank scores with gene importance generated by deep neural network (DNN), taking inter-subtype discrimination and inner-gene correlations into account, was came up to improve gene selection performance. More importantly, we embedded a gene connectivity matrix in the DNN for sparse learning, which takes additional consideration with weight changes during training when obtaining the measurement of the relative importance of each gene. Finally, Genetic Algorithm was used to simulate the natural evolutionary process to search for the optimal subset of TNBC subtype classification. We validated the proposed method through cross-validation, and the results demonstrate that it can use fewer genes to obtain more accurate classification results. The implementation for the proposed method is available at https://github.com/RanSuLab/TNBC.

Differences in the Immune Response of the Nonmetastatic Axillary Lymph Nodes between Triple-Negative and Luminal A Breast Cancer Surrogate Subtypes.

Breast cancer (BC) comprises four immunohistochemical surrogate subtypes of which triple-negative breast cancer (TNBC) has the highest risk of mortality. Axillary lymph nodes (ALNs) are the regions where BC cells first establish before distant metastasis, and the presence of tumor cells in the ALN causes an immune tolerance profile that contrasts with that of the nonmetastatic ALN (ALN-). However, few studies have compared the immune components of the ALNs- in BC subtypes. The present study aimed to determine whether differences between immune populations in the primary tumor and ALNs- were associated with the luminal A or TNBC subtype. We evaluated a retrospective cohort of 144 patients using paraffin-embedded biopsies. The TNBC samples tended to have a higher histologic grade and proliferation index and had higher levels of immune markers compared with luminal A in primary tumors and ALNs-. Two methods for validating the multivariate analysis found that histologic grade, intratumoral S100 dendritic cells, and CD8 T lymphocytes and CD57 natural killer cells in the ALNs- were factors associated with TNBC, whereas CD83 dendritic cells in the ALNs- were associated with the luminal A subtype. In conclusion, we found that intratumoral regions and ALNs- of TNBC contained higher concentrations of markers related to immune tolerance than luminal A. This finding partially explains the worse prognosis of patients with TNBC.

ER-/PR+ breast cancer: A distinct entity, which is morphologically and molecularly close to triple-negative breast cancer.

Determining the status of steroid hormone receptors [oestrogen (ER) and progesterone receptors (PR)] is a crucial part of the breast cancer workup. Thereby, breast cancers can be classified into four subtypes. However, the existence of ER-/PR+ tumours, often reported to be ill-classified due to technical errors, remains controversial. In order to address this controversy, we reviewed the hormone receptor status of 49 breast tumours previously classified as ER-/PR+ by immunohistochemistry, and compared clinical, pathological and molecular characteristics of confirmed ER-/PR+ tumours with those of ER+ and triple-negative tumours. We unequivocally confirmed the ER-/PR+ status in 27 of 49 tumours (0.3% of all breast cancers diagnosed in our institution between 2000 and 2014). We found that ER-/PR+ were morphologically and histologically similar to triple-negative tumours, but very distinct from ER+ tumours, with more aggressive phenotypes and more frequent basal marker expression than the latter. On the molecular level, RNA sequencing revealed different gene expression profiles between the three groups. Of particular interest, several genes controlled by the suppressor of zest 12 (SUZ12) were upregulated in ER-/PR+ tumours. Overall, our results confirm that ER-/PR+ breast cancers are an extremely rare but 'real' tumour subtype that requires careful diagnosis and has distinct features warranting different responsiveness to therapies and different clinical outcomes. Studies on larger cohorts are needed to further characterise these tumours. The likely involvement of SUZ12 in their biology is an interesting finding which may - in a long run - give rise to the development of new therapeutic alternatives.

Enhancer transcription reveals subtype-specific gene expression programs controlling breast cancer pathogenesis.

Noncoding transcription is a defining feature of active enhancers, linking transcription factor (TF) binding to the molecular mechanisms controlling gene expression. To determine the relationship between enhancer activity and biological outcomes in breast cancers, we profiled the transcriptomes (using GRO-seq and RNA-seq) and epigenomes (using ChIP-seq) of 11 different human breast cancer cell lines representing five major molecular subtypes of breast cancer, as well as two immortalized ("normal") human breast cell lines. In addition, we developed a robust and unbiased computational pipeline that simultaneously identifies putative subtype-specific enhancers and their cognate TFs by integrating the magnitude of enhancer transcription, TF mRNA expression levels, TF motif P-values, and enrichment of H3K4me1 and H3K27ac. When applied across the 13 different cell lines noted above, the Total Functional Score of Enhancer Elements (TFSEE) identified key breast cancer subtype-specific TFs that act at transcribed enhancers to dictate gene expression patterns determining growth outcomes, including Forkhead TFs, FOSL1, and PLAG1. FOSL1, a Fos family TF, (1) is highly enriched at the enhancers of triple negative breast cancer (TNBC) cells, (2) acts as a key regulator of the proliferation and viability of TNBC cells, but not Luminal A cells, and (3) is associated with a poor prognosis in TNBC breast cancer patients. Taken together, our results validate our enhancer identification pipeline and reveal that enhancers transcribed in breast cancer cells direct critical gene regulatory networks that promote pathogenesis.

Src Kinase Is Biphosphorylated at Y416/Y527 and Activates the CUB-Domain Containing Protein 1/Protein Kinase C δ Pathway in a Subset of Triple-Negative Breast Cancers.

Targeted therapeutics are needed for triple-negative breast cancer (TNBC). In this study, we investigated the activation of Src family of cytoplasmic tyrosine kinases (SFKs) and two SFK substrates-CUB-domain containing protein 1 (CDCP1) and protein kinase C δ (PKCδ)-in 56 formalin-fixed, paraffin-embedded (FFPE) TNBCs. Expression of SFK phosphorylated at Y416 (SFK_pY416+) in tumor cells was strongly associated with phosphorylation of CDCP1 and PKCδ (CDCP1_ pY743+ and PKCδ_pY311+), as assessed by immunohistochemistry, indicating increased SFK activity in situ. To enable biochemical analysis, protein extraction from FFPE tissue was optimized. Cleaved CDCP1 isoform (70 kDa) was expressed to a varying degree in all samples but only phosphorylated in TNBC tumor cells that expressed SFK_pY416. Interestingly, active SFK was found to be biphosphorylated (SFK_pY416+/pY527+). Biphosphorylated active SFK was observed more frequently in forkhead box protein A1 (FOXA1)- TNBCs. In addition, in SFK_pY416- samples, FOXA1+ TNBC tended to be SFK_pY527+ (classic inactive SFK), and FOXA1- TNBC tended to be SFK_pY527- (SFK poised for activation). Strong SFK_pY416 staining was also observed in tumor-infiltrating lymphocytes in a subset of TNBCs with high tumor-infiltrating lymphocyte content. This report will facilitate protein biochemical analysis of FFPE tumor samples and justifies the development of therapies targeting the SFK/CDCP1/PKCδ pathway for TNBC treatment.

Identification of microRNA clusters cooperatively acting on epithelial to mesenchymal transition in triple negative breast cancer.

MicroRNAs play important roles in many biological processes. Their aberrant expression can have oncogenic or tumor suppressor function directly participating to carcinogenesis, malignant transformation, invasiveness and metastasis. Indeed, miRNA profiles can distinguish not only between normal and cancerous tissue but they can also successfully classify different subtypes of a particular cancer. Here, we focus on a particular class of transcripts encoding polycistronic miRNA genes that yields multiple miRNA components. We describe 'clustered MiRNA Master Regulator Analysis (ClustMMRA)', a fully redesigned release of the MMRA computational pipeline (MiRNA Master Regulator Analysis), developed to search for clustered miRNAs potentially driving cancer molecular subtyping. Genomically clustered miRNAs are frequently co-expressed to target different components of pro-tumorigenic signaling pathways. By applying ClustMMRA to breast cancer patient data, we identified key miRNA clusters driving the phenotype of different tumor subgroups. The pipeline was applied to two independent breast cancer datasets, providing statistically concordant results between the two analyses. We validated in cell lines the miR-199/miR-214 as a novel cluster of miRNAs promoting the triple negative breast cancer (TNBC) phenotype through its control of proliferation and EMT.

Immunohistochemical analysis of adipokine and adipokine receptor expression in the breast tumor microenvironment: associations of lower leptin receptor expression with estrogen receptor-negative status and triple-negative subtype.

BACKGROUND: The molecular mechanisms underlying the association between increased adiposity and aggressive breast cancer phenotypes remain unclear, but likely involve the adipokines, leptin (LEP) and adiponectin (ADIPOQ), and their receptors (LEPR, ADIPOR1, ADIPOR2). METHODS: We used immunohistochemistry (IHC) to assess LEP, LEPR, ADIPOQ, ADIPOR1, and ADIPOR2 expression in breast tumor tissue microarrays among a sample of 720 women recently diagnosed with breast cancer (540 of whom self-identified as Black). We scored IHC expression quantitatively, using digital pathology analysis. We abstracted data on tumor grade, tumor size, tumor stage, lymph node status, Ki67, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) from pathology records, and used ER, PR, and HER2 expression data to classify breast cancer subtype. We used multivariable mixed effects models to estimate associations of IHC expression with tumor clinicopathology, in the overall sample and separately among Blacks. RESULTS: Larger proportions of Black than White women were overweight or obese and had more aggressive tumor features. Older age, Black race, postmenopausal status, and higher body mass index were associated with higher LEPR IHC expression. In multivariable models, lower LEPR IHC expression was associated with ER-negative status and triple-negative subtype (P < 0.0001) in the overall sample and among Black women only. LEP, ADIPOQ, ADIPOR1, and ADIPOR2 IHC expression were not significantly associated with breast tumor clinicopathology. CONCLUSIONS: Lower LEPR IHC expression within the breast tumor microenvironment might contribute mechanistically to inter-individual variation in aggressive breast cancer clinicopathology, particularly ER-negative status and triple-negative subtype.

PD-L1 diagnostics in the neoadjuvant setting: implications of intratumoral heterogeneity of PD-L1 expression in triple negative breast cancer for assessment in small biopsies.

PURPOSE: PD-L1 expression is a predictive biomarker for anti-PD-L1 immunotherapy in triple negative breast cancer (TNBC). In the neoadjuvant setting, immunohistochemical (IHC) evaluation of PD-L1 expression can only be performed on small tissue biopsies. In our study we investigated heterogeneity of PD-L1 expression in TNBC, and how reliably PD-L1 expression in small tissue samples reflects PD-L1 expression in larger tumor sections in TNBC. METHODS: Tissue microarrays (TMAs) were constructed from surgical specimens of 110 patients with TNBC. TMAs contained 4 cores (1 mm in diameter) per patient. To evaluate PD-L1 expression, TMAs were stained with PD-L1 IHC 22C3 PharmDx. Single-core PD-L1 expression was compared to overall PD-L1 expression of each patient's tumor, to ascertain how often small samples of tumor tissue show the same PD-L1 expression as larger tumor samples. RESULTS: Our study found substantial heterogeneity of PD-L1 expression between different TMA cores from the same patient. Heterogeneity was greater in immune cells (ICs) than in tumor cells, in large part due to the uneven distribution of ICs in the tumor. For IC PD-L1 expression, we found that sensitivity can be as low as 0.81 for detecting PD-L1 expression at the 1% threshold most commonly used in breast cancer. Negative predictive value for ICs was 0.7. CONCLUSIONS: There is substantial heterogeneity of PD-L1 expression between small tissue samples from the same TNBC tumor, especially for IC expression. This poses challenges for evaluation of PD-L1 expression in the neoadjuvant setting. Negative biopsies should prompt further investigation, and multiple biopsies might be necessary.

A cumulative index of exposure to endogenous estrogens and breast cancer by molecular subtypes in northern Mexican women.

PURPOSE: To evaluate breast cancer (BC) molecular subtypes association with reproductive characteristics and an index of cumulative exposure to endogenous estrogens (EEI) in Mexican women. METHODS: We performed a study of incident cases and population controls in northern Mexico. We included BC cases with tumor molecular classification in their medical records (n = 509), and classified them as HR+/HER2- (ER+ and/or PR+ and HER2-) (n = 289), HER2+ (HR+ or HR-) (n = 117) or triple negative (TN) (n = 103). We matched controls (n = 1030) by age and place of residence with index cases. Women were interviewed about their reproductive history, from which the EEI was developed. We used logistic regression models to estimate BC molecular subtypes associations with reproductive characteristics and EEI. RESULTS: The EEI was higher in all subtypes compared to controls (Median HR+/HER2- 27.25, HER2+ 26.8, TN 24.2 vs. controls 22.8 years, p < 0.05), and was associated with HR+/HER2- (ORT3 vs. T1 = 2.58, 95% CI 1.77-3.55, p-trend < 0.001) and HER2+ (ORT3 vs. T1 = 4.17, 95% CI 2.15-8.08, p-trend < 0.001) BC. Additionally, HR+/HER2- tumors were positively associated with age at first pregnancy and age at menopause, and negatively with age at menarche, parity and breastfeeding. The HER2+ subtype was associated in the same direction as HR+/HER2- tumors with all the reproductive characteristics except for age at menarche. TN tumors were negatively associated with parity and breastfeeding. CONCLUSION: Endogenous estrogens exposure throughout Mexican women reproductive life may contribute to the development of all but TN BC, however, these findings should be confirmed in other Hispanic populations.

Histologic subtyping affecting outcome of triple negative breast cancer: a large Sardinian population-based analysis.

BACKGROUND: Triple Negative breast cancer (TNBC) includes a heterogeneous group of tumors with different clinico-pathological features, molecular alterations and treatment responsivity. Our aim was to evaluate the clinico-pathological heterogeneity and prognostic significance of TNBC histologic variants, comparing "special types" to high-grade invasive breast carcinomas of no special type (IBC-NST). METHODS: This study was performed on data obtained from TNBC Database, including pathological features and clinical records of 1009 TNBCs patients diagnosed between 1994 and 2015 in the four most important Oncology Units located in different hospitals in Sardinia, Italy. Kaplan-Meier analysis, log-rank test and multivariate Cox proportional-hazards regression were applied for overall survival (OS) and disease free survival (DFS) according to TNBC histologic types. RESULTS: TNBC "special types" showed significant differences for several clinico-pathological features when compared to IBC-NST. We observed that in apocrine carcinomas as tumor size increased, the number of metastatic lymph nodes manifestly increased. Adenoid cystic carcinoma showed the smallest tumor size relative to IBC-NST. At five-year follow-up, OS was 92.1, 100.0, and 94.5% for patients with apocrine, adenoid cystic and medullary carcinoma, respectively; patients with lobular and metaplastic carcinoma showed the worst OS, with 79.7 and 84.3%, respectively. At ten-years, patients with adenoid cystic (100.0%) and medullary (94.5%) carcinoma showed a favourable prognosis, whereas patients with lobular carcinoma showed the worst prognosis (73.8%). TNBC medullary type was an independent prognostic factor for DFS compared to IBC-NST. CONCLUSIONS: Our study confirms that an accurate and reliable histopathologic definition of TNBC subtypes has a significant clinical utility and is effective in the therapeutic decision-making process, with the aim to develop innovative and personalized treatments.

Integrative analysis of breast cancer profiles in TCGA by TNBC subgrouping reveals novel microRNA-specific clusters, including miR-17-92a, distinguishing basal-like 1 and basal-like 2 TNBC subtypes.

BACKGROUND: The term triple-negative breast cancer (TNBC) is used to describe breast cancers without expression of estrogen receptor, progesterone receptor or HER2 amplification. To advance targeted treatment options for TNBC, it is critical that the subtypes within this classification be described in regard to their characteristic biology and gene expression. The Cancer Genome Atlas (TCGA) dataset provides not only clinical and mRNA expression data but also expression data for microRNAs. RESULTS: In this study, we applied the Lehmann classifier to TCGA-derived TNBC cases which also contained microRNA expression data and derived subtype-specific microRNA expression patterns. Subsequent analyses integrated known and predicted microRNA-mRNA regulatory nodes as well as patient survival data to identify key networks. Notably, basal-like 1 (BL1) TNBCs were distinguished from basal-like 2 TNBCs through up-regulation of members of the miR-17-92 cluster of microRNAs and suppression of several known miR-17-92 targets including inositol polyphosphate 4-phosphatase type II, INPP4B. CONCLUSIONS: These data demonstrate TNBC subtype-specific microRNA and target mRNA expression which may be applied to future biomarker and therapeutic development studies.

Personalized treatment in metastatic triple-negative breast cancer: The outlook in 2020.

Compared with other breast cancer subtypes, patients with triple-negative breast cancer (TNBC), and irrespective to their disease stage, were always recognized to have the worst overall survival data. Although this does not seem different at the present time, yet the last few years have witnessed many breakthrough genomic and molecular findings, that could dramatically improve our understanding of the biological complexity of TNBC. Based on genomic analyses, it was consistently evident that TNBC comprises a heterogeneous group of cancers, which have numerous diverse molecular aberrations. This-in return-has provided a platform for a new generation of clinical trials using many innovative therapies, directed against such novel targets. At the present time, two PARP inhibitors and one anti-PD-L1 monoclonal antibody (in combination with chemotherapy) have been approved in certain subpopulations of metastatic TNBC (mTNBC) patients, which have finally brought this disease into the era of personalized medicine. In the current review, we will explore the genomic landscape of TNBC, through which many actionable targets were graduated. We will also discuss the results of the key-practice changing-clinical studies, and some upcoming personalized treatment options for patients with mTNBC, that may be clinically adopted in the near future.

Genomic analysis of racial differences in triple negative breast cancer.

Triple negative breast cancer (TNBC) is more prevalent in African Americans (AAs), has a more aggressive clinical course including a higher mortality rate and an increased occurrence of metastases. This study was designed to determine if racial differences at the molecular level might explain the more aggressive phenotype in AAs. Mutation profiling, was performed on 51 AA and 77 CA tumor/ normal pairs. Transcript expression analysis was performed on 35AA and 37CA. Genes with high frequency mutation rates such as MUC4 and TP53 were common to both racial populations, however genes that were less frequently mutated differed between the races suggesting that those cause the more aggressive nature of TNBC in AA women. JAK-Stat and HER2 signaling were unique to the AA and PTEN and mTOR were unique to the CA profiles. Many pathways identified by the mutational profiles were predicted to be down-regulated by the transcript expression profiles.

iTRAQ-Based Quantitative Proteomic Analysis Strengthens Transcriptomic Subtyping of Triple-Negative Breast Cancer Tumors.

Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC). Therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study is to define robust TNBC subtypes with clinical relevance by means of proteomics and transcriptomics. As a first step, unsupervised analyses are conducted in parallel on proteomics and transcriptomics data of 83 TNBC tumors. Proteomics data unsupervised analysis did not permit separation of TNBC into different subtypes, whereas transcriptomics data are able to clearly and robustly identify three subtypes: molecular apocrine (C1), basal-like immune-suppressed (C2), and basal-like immune response (C3). Supervised analysis of proteomics data are then conducted based on transcriptomics subtyping. Thirty out of 62 proteins differentially expressed between C1, C2, and C3 belonged to biological categories which characterized these TNBC clusters: luminal and androgen-regulated proteins (C1), basal, invasion, and extracellular matrix (C2), and basal and immune response (interferon pathway and immunoglobulins) (C3). Although proteomics unsupervised analysis of TNBC tumors is unsuccessful at identifying clusters, the integrated approach is promising. Identification and measurement of 30 proteins strengthen subtyping of TNBC based on robust transcriptomics unsupervised analysis.

Impact of breast cancer molecular subtypes on the incidence, kinetics and prognosis of central nervous system metastases in a large multicentre real-life cohort.

BACKGROUND: Metastatic breast cancer (MBC) behaviour differs depending on hormone receptors (HR) and human epidermal growth factor receptor (HER2) statuses. METHODS: The kinetics of central nervous system (CNS) metastases (CNS metastasis-free survival, CNSM-FS) and subsequent patient's prognosis (overall survival, OS) according to the molecular subtype were retrospectively assessed in 16703 MBC patients of the ESME nationwide multicentre MBC database (Kaplan-Meier method). RESULTS: CNS metastases occurred in 4118 patients (24.6%) (7.2% at MBC diagnosis and 17.5% later during follow-up). Tumours were HER2-/HR+ (45.3%), HER2+/HR+ (14.5%), HER2+/HR- (14.9%) and triple negative (25.4%). Median age at CNS metastasis diagnosis was 58.1 years (range: 22.8-92.0). The median CNSM-FS was 10.8 months (95% CI: 16.5-17.9) among patients who developed CNS metastases. Molecular subtype was independently associated with CNSM-FS (HR = 3.45, 95% CI: 3.18-3.75, triple-negative and HER2-/HR+ tumours). After a 30-month follow-up, median OS after CNS metastasis diagnosis was 7.9 months (95% CI: 7.2-8.4). OS was independently associated with subtypes: median OS was 18.9 months (HR = 0.57, 95% CI: 0.50-0.64) for HER2+/HR+ , 13.1 months (HR = 0.72, 95% CI: 0.65-0.81) for HER2+/HR-, 4.4 months (HR = 1.55, 95% CI: 1.42-1.69) for triple-negative and 7.1 months for HER2-/HR+ patients (p <0.0001). CONCLUSIONS: Tumour molecular subtypes strongly impact incidence, kinetics and prognosis of CNS metastases in MBC patients. CLINICAL TRIAL REGISTRATION: NCT03275311.

Combining Glucose Units, m/z, and Collision Cross Section Values: Multiattribute Data for Increased Accuracy in Automated Glycosphingolipid Glycan Identifications and Its Application in Triple Negative Breast Cancer.

Glycan head-groups attached to glycosphingolipids (GSLs) found in the cell membrane bilayer can alter in response to external stimuli and disease, making them potential markers and/or targets for cellular disease states. To identify such markers, comprehensive analyses of glycan structures must be undertaken. Conventional analyses of fluorescently labeled glycans using hydrophilic interaction high-performance liquid chromatography (HILIC) coupled with mass spectrometry (MS) provides relative quantitation and has the ability to perform automated glycan assignments using glucose unit (GU) and mass matching. The use of ion mobility (IM) as an additional level of separation can aid the characterization of closely related or isomeric structures through the generation of glycan collision cross section (CCS) identifiers. Here, we present a workflow for the analysis of procainamide-labeled GSL glycans using HILIC-IM-MS and a new, automated glycan identification strategy whereby multiple glycan attributes are combined to increase accuracy in automated structural assignments. For glycan matching and identification, an experimental reference database of GSL glycans containing GU, mass, and CCS values for each glycan was created. To assess the accuracy of glycan assignments, a distance-based confidence metric was used. The assignment accuracy was significantly better compared to conventional HILIC-MS approaches (using mass and GU only). This workflow was applied to the study of two Triple Negative Breast Cancer (TNBC) cell lines and revealed potential GSL glycosylation signatures characteristic of different TNBC subtypes.

Systemic treatment and radiotherapy, breast cancer subtypes, and survival after long-term clinical follow-up.

BACKGROUND: It remains unclear whether breast cancer subtypes are associated with clinical outcome in patients without any treatment including systemic and radiation therapy as an independent entity. Understanding the survival profiles among subtypes by treatment status could impact optimal selection of treatments. METHODS: Patients were diagnosed with invasive breast cancer from the community hospitals across four geographical regions of the United States. Expression of hormone receptor (HR) and HER2 in tumor specimens from 1169 patients was centrally determined by immunohistochemistry and fluorescence in situ; breast cancer was classified into HR+/HER2-, HR+/HER2+, triple-negative, and HER2+ subtypes. Overall survival (OS) at a median follow-up of about 15 years among subtypes in untreated patients and those with systemic treatments and radiotherapy was analyzed by Kaplan-Meier method and multivariable analysis adjusting for age, tumor size and grade, number of positive nodes, stage and breast cancer subtypes. RESULTS: Without treatment, breast cancer subtypes were not associated with OS (P = 0.983) and remained insignificant for prognosis by multivariable analysis after adjusting for confounders. This contrasted with a significant survival difference across the subtypes in patients with conventional therapies (P < 0.0001). Compared with HR+/HER2- subtype, triple-negative subtype (HR 1.5, 95% CI 1.11-2.04; P = 0.009) and HER2+ subtype (HR 2.18, 95% CI 1.48-3.28; P = 0.0001) were significantly associated with worse survival by multivariable analyses. CONCLUSION: Breast cancer subtypes are not associated with survival in untreated patient population and, in contrast, significantly associated with prognosis in patients with conventional therapy. The data provide evidence of treatment-associated differential outcomes among breast cancer subtypes.

Clinicopathological Features of Triple-Negative Breast Cancer Epigenetic Subtypes.

BACKGROUND/OBJECTIVE: Triple-negative breast cancer (TNBC) is a heterogeneous collection of breast tumors with numerous differences including morphological characteristics, genetic makeup, immune-cell infiltration, and response to systemic therapy. DNA methylation profiling is a robust tool to accurately identify disease-specific subtypes. We aimed to generate an epigenetic subclassification of TNBC tumors (epitypes) with utility for clinical decision-making. METHODS: Genome-wide DNA methylation profiles from TNBC patients generated in the Cancer Genome Atlas project were used to build machine learning-based epigenetic classifiers. Clinical and demographic variables, as well as gene expression and gene mutation data from the same cohort, were integrated to further refine the TNBC epitypes. RESULTS: This analysis indicated the existence of four TNBC epitypes, named as Epi-CL-A, Epi-CL-B, Epi-CL-C, and Epi-CL-D. Patients with Epi-CL-B tumors showed significantly shorter disease-free survival and overall survival [log rank; P = 0.01; hazard ratio (HR) 3.89, 95% confidence interval (CI) 1.3-11.63 and P = 0.003; HR 5.29, 95% CI 1.55-18.18, respectively]. Significant gene expression and mutation differences among the TNBC epitypes suggested alternative pathway activation that could be used as ancillary therapeutic targets. These epigenetic subtypes showed complementarity with the recently described TNBC transcriptomic subtypes. CONCLUSIONS: TNBC epigenetic subtypes exhibit significant clinical and molecular differences. The links between genetic make-up, gene expression programs, and epigenetic subtypes open new avenues in the development of laboratory tests to more efficiently stratify TNBC patients, helping optimize tailored treatment approaches.

Differences in molecular features of triple-negative breast cancers based on the age at diagnosis.

BACKGROUND: Although the proportion of triple-negative breast cancers (TNBCs) diagnosed among older women is low, the number of TNBC cases is substantial because of the high incidence of breast cancer after the age of 65 years. The molecular features of TNBC in this age group have not been well described. METHODS: This study examined a population-based cohort of women with stage I to III TNBC diagnosed between the ages of 25 and 91 years with the PAM50 gene expression subtyping assay. The concordance between the TNBC classification by immunohistochemistry and the gene expression classification by PAM50, the expression of individual genes, and 5-year recurrence and breast cancer mortality in older women (≥65 years old) and younger women (<50 years old) was assessed. RESULTS: The molecular subtype distribution in TNBC was significantly different according to the age at diagnosis. TNBC was more likely to be classified as basal-like in women younger than 50 years (sensitivity, 0.91; 95% confidence interval, 0.77-0.97) than women 65 years old or older (sensitivity, 0.72; 95% confidence interval, 0.48-0.87); 35% of clinical TNBC cases in the latter group were the human epidermal growth factor receptor 2 (HER2)-enriched subtype by molecular classification. Older women with TNBC also had significantly higher expression of ERBB2 and lower expression of all 10 proliferation-associated genes tested (P < .01). The risk of breast cancer death within 5 years was significantly higher in women with TNBC in comparison with women with hormone receptor-positive cancers in all age groups. CONCLUSIONS: This study revealed differences in molecular subtypes among clinical TNBC cases based on patient age. A potentially targetable HER2-enriched group raises the possible need for intrinsic subtyping in older women with TNBC.

Prognostic value of androgen receptor and FOXA1 co-expression in non-metastatic triple negative breast cancer and correlation with other biomarkers.

BACKGROUND: In luminal androgen receptor (AR) tumours, FOXA1 may direct AR to sites occupied by ER in luminal tumours, thus stimulating proliferation. METHODS: AR and FOXA1 expression were evaluated by immunohistochemistry in 333 non-metastatic triple-negative breast cancers (TNBC). Positivity threshold was set at ≥ 1% staining. Lymphocytic infiltration, PD-L1expression, PIK3CA mutations, PTEN defects and BRCA1 promoter methylation were assessed. RESULTS: AR + /FOXA1 + tumours (42.4%) were more frequently: found in older patients, lobular, of lower nuclear grade, with more frequently PIK3CA mutations; exhibited less frequently BRCA1 promoter methylation, defects of PTEN and PD-L1 expression than others. Recurrence-free and overall survivals were significantly lower for AR + /FOXA1 + TNBC (median follow-up: 7.8 years). CONCLUSIONS: AR + /FOXA1 + expression defines a luminal-like TNBC subgroup affected with a worse outcome compared to other TNBC and a higher risk of late recurrences. This subgroup appears enriched in PIK3CA mutations, suggesting a role for PI3K inhibitors in this subgroup.