Triple-negative breast cancer (TNBC) is a highly diverse group of cancers, and subtyping is necessary to better identify molecular-based therapies. In this study, we analyzed gene expression (GE) profiles from 21 breast cancer data sets and identified 587 TNBC cases. Cluster analysis identified 6 TNBC subtypes displaying unique GE and ontologies, including 2 basal-like (BL1 and BL2), an immunomodulatory (IM), a mesenchymal (M), a mesenchymal stem-like (MSL), and a luminal androgen receptor (LAR) subtype. Further, GE analysis allowed us to identify TNBC cell line models representative of these subtypes. Predicted "driver" signaling pathways were pharmacologically targeted in these cell line models as proof of concept that analysis of distinct GE signatures can inform therapy selection. BL1 and BL2 subtypes had higher expression of cell cycle and DNA damage response genes, and representative cell lines preferentially responded to cisplatin. M and MSL subtypes were enriched in GE for epithelial-mesenchymal transition, and growth factor pathways and cell models responded to NVP-BEZ235 (a PI3K/mTOR inhibitor) and dasatinib (an abl/src inhibitor). The LAR subtype includes patients with decreased relapse-free survival and was characterized by androgen receptor (AR) signaling. LAR cell lines were uniquely sensitive to bicalutamide (an AR antagonist). These data may be useful in biomarker selection, drug discovery, and clinical trial design that will enable alignment of TNBC patients to appropriate targeted therapies.

Growth factors and mitogens use the Ras/Raf/MEK/ERK signaling cascade to transmit signals from their receptors to regulate gene expression and prevent apoptosis. Some components of these pathways are mutated or aberrantly expressed in human cancer (e.g., Ras, B-Raf). Mutations also occur at genes encoding upstream receptors (e.g., EGFR and Flt-3) and chimeric chromosomal translocations (e.g., BCR-ABL) which transmit their signals through these cascades. Even in the absence of obvious genetic mutations, this pathway has been reported to be activated in over 50% of acute myelogenous leukemia and acute lymphocytic leukemia and is also frequently activated in other cancer types (e.g., breast and prostate cancers). Importantly, this increased expression is associated with a poor prognosis. The Ras/Raf/MEK/ERK and Ras/PI3K/PTEN/Akt pathways interact with each other to regulate growth and in some cases tumorigenesis. For example, in some cells, PTEN mutation may contribute to suppression of the Raf/MEK/ERK cascade due to the ability of activated Akt to phosphorylate and inactivate different Rafs. Although both of these pathways are commonly thought to have anti-apoptotic and drug resistance effects on cells, they display different cell lineage specific effects. For example, Raf/MEK/ERK is usually associated with proliferation and drug resistance of hematopoietic cells, while activation of the Raf/MEK/ERK cascade is suppressed in some prostate cancer cell lines which have mutations at PTEN and express high levels of activated Akt. Furthermore the Ras/Raf/MEK/ERK and Ras/PI3K/PTEN/Akt pathways also interact with the p53 pathway. Some of these interactions can result in controlling the activity and subcellular localization of Bim, Bak, Bax, Puma and Noxa. Raf/MEK/ERK may promote cell cycle arrest in prostate cells and this may be regulated by p53 as restoration of wild-type p53 in p53 deficient prostate cancer cells results in their enhanced sensitivity to chemotherapeutic drugs and increased expression of Raf/MEK/ERK pathway. Thus in advanced prostate cancer, it may be advantageous to induce Raf/MEK/ERK expression to promote cell cycle arrest, while in hematopoietic cancers it may be beneficial to inhibit Raf/MEK/ERK induced proliferation and drug resistance. Thus the Raf/MEK/ERK pathway has different effects on growth, prevention of apoptosis, cell cycle arrest and induction of drug resistance in cells of various lineages which may be due to the presence of functional p53 and PTEN and the expression of lineage specific factors.

Triple-negative breast cancer (TNBC) is a heterogeneous disease that can be classified into distinct molecular subtypes by gene expression profiling. Considered a difficult-to-treat cancer, a fraction of TNBC patients benefit significantly from neoadjuvant chemotherapy and have far better overall survival. Outside of BRCA1/2 mutation status, biomarkers do not exist to identify patients most likely to respond to current chemotherapy; and, to date, no FDA-approved targeted therapies are available for TNBC patients. Previously, we developed an approach to identify six molecular subtypes TNBC (TNBCtype), with each subtype displaying unique ontologies and differential response to standard-of-care chemotherapy. Given the complexity of the varying histological landscape of tumor specimens, we used histopathological quantification and laser-capture microdissection to determine that transcripts in the previously described immunomodulatory (IM) and mesenchymal stem-like (MSL) subtypes were contributed from infiltrating lymphocytes and tumor-associated stromal cells, respectively. Therefore, we refined TNBC molecular subtypes from six (TNBCtype) into four (TNBCtype-4) tumor-specific subtypes (BL1, BL2, M and LAR) and demonstrate differences in diagnosis age, grade, local and distant disease progression and histopathology. Using five publicly available, neoadjuvant chemotherapy breast cancer gene expression datasets, we retrospectively evaluated chemotherapy response of over 300 TNBC patients from pretreatment biopsies subtyped using either the intrinsic (PAM50) or TNBCtype approaches. Combined analysis of TNBC patients demonstrated that TNBC subtypes significantly differ in response to similar neoadjuvant chemotherapy with 41% of BL1 patients achieving a pathological complete response compared to 18% for BL2 and 29% for LAR with 95% confidence intervals (CIs; [33, 51], [9, 28], [17, 41], respectively). Collectively, we provide pre-clinical data that could inform clinical trials designed to test the hypothesis that improved outcomes can be achieved for TNBC patients, if selection and combination of existing chemotherapies is directed by knowledge of molecular TNBC subtypes.

Purpose The clinical relevancy of the 7-subtype classification of triple-negative breast cancer (TNBC) reported by Lehmann and Bauer et al is unknown. We investigated the clinical relevancy of TNBC heterogeneity by determining pathological complete response (pCR) rates after neoadjuvant chemotherapy, based on TNBC subtypes. Experimental Design We revalidated the Lehmann and Bauer et al. experiments using Affymetrix CEL files from public datasets. We applied these methods to 146 TNBC patients with gene expression microarrays obtained from June 2000 to March 2010 at our institution. Of those, 130 had received standard neoadjuvant chemotherapy and had evaluable pathological response data. We classified the TNBC samples by subtype, then correlated subtype and pCR status using Fisher’s exact test and a logistic regression model. We also assessed survival and compared the subtypes to PAM50 intrinsic subtypes and residual cancer burden (RCB) index. Results TNBC subtype and pCR status were significantly associated (P=0.04379). The basal-like 1 (BL1) subtype had the highest pCR rate (52%); basal-like 2 (BL2) and luminal androgen receptor (LAR) had the lowest (0% and 10%, respectively). TNBC subtype was an independent predictor of pCR status (P=0.022) by a likelihood ratio test. The subtypes better predicted pCR status than did the PAM50 intrinsic subtypes (basal-like vs non basal-like). Conclusions Classifying TNBC by 7 subtypes predicts high vs. low pCR rate. We confirm the clinical relevancy of the 7 subtypes of TNBC. We need to prospectively validate whether the pCR rate differences translate into long-term outcome differences. The 7-subtype classification may spur innovative personalized medicine strategies for TNBC patients.

Neoadjuvant chemotherapy (NAC) induces a pathologic complete response (pCR) in approximately 30% of patients with triple-negative breast cancers (TNBC). In patients lacking a pCR, NAC selects a subpopulation of chemotherapy-resistant tumor cells. To understand the molecular underpinnings driving treatment-resistant TNBCs, we performed comprehensive molecular analyses on the residual disease (RD) of 74 clinically-defined TNBCs after NAC including next-generation sequencing (NGS) on 20 matched pre-treatment biopsies. Combined NGS and digital RNA expression analysis identified diverse molecular lesions and pathway activation in drug-resistant tumor cells. Ninety percent of the tumors contained a genetic alteration potentially treatable with a currently available targeted therapy. Thus, profiling residual TNBCs after NAC identifies targetable molecular lesions in the chemotherapy-resistant component of the tumor which may mirror micro-metastases destined to recur clinically. These data can guide biomarker-driven adjuvant studies targeting these micro-metastases to improve the outcome of patients with TNBC who do not respond completely to NAC.

Triple negative breast cancer (TNBC) is a heterogeneous disease with distinct molecular subtypes that differentially respond to chemotherapy and targeted agents. The absence of high-frequency molecular alterations and a limited number of known biomarkers have limited the development of therapeutic strategies for the disease. Herein, we summarize the results of the first round of targeted therapy approaches in TNBC and discuss new preclinical strategies. Common themes emerge from the proposed strategies, such as the use of biomarkers to identify tumors with genomic instability, targeting adapted molecular states resulting from tumor suppressor loss, and targeting altered metabolic pathways.

Males of advanced age represent a rapidly growing population at risk for prostate cancer. In the contemporary setting of earlier detection, a majority of prostate carcinomas are still clinically localized and often treated using radiation therapy. Our recent studies have shown that premature cellular senescence, rather than apoptosis, accounts for most of the clonogenic death induced by clinically-relevant doses of irradiation in prostate cancer cells. We show here that this treatment-induced senescence was associated with a significantly increased release of exosome-like microvesicles. In premature senescence, this novel secretory phenotype was dependent on the activation of p53. In addition, the release of exosome-like microvesicles also increased during proliferative senescence in normal human diploid fibroblasts. These data support the hypothesis that senescence, initiated either by telomere attrition (e.g., aging) or DNA damage (e.g., radiotherapy), may induce a p53-dependent increase in the biogenesis of exosome-like vesicles. Ultrastructural analysis and RNAi-mediated knockdown of Tsg101 provided significant evidence that the additional exosomes released by prematurely senescent prostate cancer cells were principally derived from multivesicular endosomes (MVEs). Moreover, these exosomes were enriched in B7-H3 protein, a recently identified diagnostic marker for prostate cancer, and an abundance of what has recently been termed “exosomal shuttle RNA”. Our findings are consistent with the proposal that exosomes can transfer cargos, with both immunoregulatory potential and genetic information, between cells through a novel mechanism that may be recruited to increase exosome release during accelerated and replicative cellular senescence.

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.