TNBCtype: A Subtyping Tool for Triple-Negative Breast Cancer

Targeting BCL-xL improves the efficacy of bromodomain and extra-terminal protein inhibitors in triple-negative breast cancer by eliciting the death of senescent cells

Inhibitors of bromodomain and extra-terminal proteins (BETi) suppress oncogenic gene expression and have been shown to be efficacious in many in vitro and murine models of cancer, including triple-negative breast cancer (TNBC), a highly aggressive disease. However, in most cancer models, responses to BETi can be highly variable. We previously reported that TNBC cells either undergo senescence or apoptosis in response to BETi, but the specific mechanisms dictating these two cell fates remain unknown. Using six human TNBC cell lines, we show that the terminal response of TNBC cells to BETi is dictated by the intrinsic expression levels of the anti-apoptotic protein B-cell lymphoma-extra large (BCL-xL). BCL-xL levels were higher in cell lines that senesce in response to BETi compared with lines that primarily die in response to these drugs. Moreover, BCL-xL expression was further reduced in cells that undergo BETi-mediated apoptosis. Forced BCL-xL overexpression in cells that normally undergo apoptosis following BETi treatment shifted them to senescence without affecting the reported mechanism of action of BETi in TNBC, that is, mitotic catastrophe. Most importantly, pharmacological or genetic inhibition of BCL-xL induced apoptosis in response to BETi, and inhibiting BCL-xL, even after BETi-induced senescence had already occurred, still induced cell death. These results indicate that BCL-xL provides a senescent cell death-inducing or senolytic target that may be exploited to improve therapeutic outcomes of TNBC in response to BETi. They also suggest that the basal levels of BCL-xL should be predictive of tumor responses to BETi in current clinical trials.

Rates of immune cell infiltration in patients with triple-negative breast cancer by molecular subtype

In patients with triple-negative breast cancer (TNBC), tumor-infiltrating lymphocytes (TILs) are associated with improved survival. Lehmann et al. identified 4 molecular subtypes of TNBC [basal-like (BL) 1, BL2, mesenchymal (M), and luminal androgen receptor (LAR)], and an immunomodulatory (IM) gene expression signature indicates the presence of TILs and modifies these subtypes. The association between TNBC subtype and TILs is not known. Also, the association between inflammatory breast cancer (IBC) and the presence of TILs is not known. Therefore, we studied the IM subtype distribution among different TNBC subtypes. We retrospectively analyzed patients with TNBC from the World IBC Consortium dataset. The molecular subtype and the IM signature [positive (IM+) or negative (IM-)] were analyzed. Fisher’s exact test was used to analyze the distribution of positivity for the IM signature according to the TNBC molecular subtype and IBC status. There were 88 patients with TNBC in the dataset, and among them 39 patients (44%) had IBC and 49 (56%) had non-IBC. The frequency of IM+ cases differed by TNBC subtype (p = 0.001). The frequency of IM+ cases by subtype was as follows: BL1, 48% (14/29); BL2, 30% (3/10); LAR, 18% (3/17); and M, 0% (0/21) (in 11 patients, the subtype could not be determined). The frequency of IM+ cases did not differ between patients with IBC and non-IBC (23% and 33%, respectively; p = 0.35). In conclusion, the IM signature representing the underlying molecular correlate of TILs in the tumor may differ by TNBC subtype but not by IBC status.

Identification of highly penetrant Rb-related synthetic lethal interactions in triple negative breast cancer

Although defects in the RB1 tumour suppressor are one of the more common driver alterations found in triple-negative breast cancer (TNBC), therapeutic approaches that exploit this have not been identified. By integrating molecular profiling data with data from multiple genetic perturbation screens, we identified candidate synthetic lethal (SL) interactions associated with RB1 defects in TNBC. We refined this analysis by identifying the highly penetrant effects, reasoning that these would be more robust in the face of molecular heterogeneity and would represent more promising therapeutic targets. A significant proportion of the highly penetrant RB1 SL effects involved proteins closely associated with RB1 function, suggesting that this might be a defining characteristic. These included nuclear pore complex components associated with the MAD2 spindle checkpoint protein, the kinase and bromodomain containing transcription factor TAF1, and multiple components of the SCFSKP Cullin F box containing complex. Small-molecule inhibition of SCFSKP elicited an increase in p27Kip levels, providing a mechanistic rationale for RB1 SL. Transcript expression of SKP2, a SCFSKP component, was elevated in RB1-defective TNBCs, suggesting that in these tumours, SKP2 activity might buffer the effects of RB1 dysfunction.

Co-expressed genes enhance precision of receptor status identification in breast cancer patients

PURPOSE

Therapeutic decisions in breast cancer patients crucially depend on the status of estrogen receptor, progesterone receptor and HER2, obtained by immunohistochemistry (IHC). These are known to be inaccurate sometimes, and we demonstrate how to use gene-expression to increase precision of receptor status.

METHODS

We downloaded data from 3241 breast cancer patients out of 36 clinical studies. For each receptor, we modelled the mRNA expression of the receptor gene and a co-gene by logistic regression. For each patient, predictions from logistic regression were merged with information from IHC on a probabilistic basis to arrive at a fused prediction result.

RESULTS

We introduce Sankey diagrams to visualize the step by step increase of precision as information is added from gene expression: IHC-estimates are qualified as 'confirmed', 'rejected' or 'corrected'. Additionally, we introduce the category 'inconclusive' to spot those patients in need for additional assessments so as to increase diagnostic precision and safety.

CONCLUSIONS

We demonstrate a sound mathematical basis for the fusion of information, even if partly contradictive. The concept is extendable to more than three sources of information, as particularly important for OMICS data. The overall number of undecidable cases is reduced as well as those assessed falsely. We outline how decision rules may be extended to also weigh consequences, being different in severity for false-positive and false-negative assessments, respectively. The possible benefit is demonstrated by comparing the disease free survival between patients whose IHC could be confirmed versus those for which it was corrected.

Integrative 3' Untranslated Region-Based Model to Identify Patients with Low Risk of Axillary Lymph Node Metastasis in Operable Triple-Negative Breast Cancer

BACKGROUND

Sentinel lymph node biopsy is the standard surgical staging approach for operable triple-negative breast cancer (TNBC) with clinically negative axillae. In this study, we sought to develop a model to predict TNBC patients with negative nodal involvement, who would benefit from the exemption of the axillary staging surgery.

MATERIALS AND METHODS

We evaluated 3' untranslated region (3'UTR) profiles using microarray data of TNBC from two Gene Expression Omnibus datasets. Samples from GSE31519 were divided into training set (n = 164) and validation set (n = 163), and GSE76275 was used to construct testing set (n = 164). We built a six-member 3'UTR panel (ADD2, COL1A1, APOL2, IL21R, PKP2, and EIF4G3) using an elastic net model to estimate the risk of lymph node metastasis (LNM). Receiver operating characteristic and logistic analyses were used to assess the association between the panel and LNM status.

RESULTS

The six-member 3'UTR-panel showed a high distinguishing power with an area under the curve of 0.712, 0.729, and 0.708 in the training, validation, and testing sets, respectively. After adjustment by tumor size, the 3'UTR panel retained significant predictive power in the training, validation, and testing sets (odds ratio = 4.93, 4.58, and 3.59, respectively; p < .05 for all). A combinatorial analysis of the 3'UTR panel and tumor size yielded an accuracy of 97.2%, 100%, and 100% in training, validation, and testing set, respectively.

CONCLUSION

This study established an integrative 3'UTR-based model as a promising predictor for nodal negativity in operable TNBC. Although a prospective study is needed to validate the model, our results may permit a no axillary surgery option for selected patients.

IMPLICATIONS FOR PRACTICE

Currently, sentinel lymph node biopsy is the standard approach for surgical staging in breast cancer patients with negative axillae. Prediction estimation for lymph node metastasis of breast cancer relies on clinicopathological characteristics, which is unreliable, especially in triple-negative breast cancer (TNBC)-a highly heterogeneous disease. The authors developed and validated an effective prediction model for the lymph node status of patients with TNBC, which integrates 3'UTR markers and tumor size. This is the first 3'UTR-based model that will help identify TNBC patients with low risk of nodal involvement who are most likely to benefit from exemption axillary surgery.

A Population of Heterogeneous Breast Cancer Patient-Derived Xenografts Demonstrate Broad Activity of PARP Inhibitor in BRCA1/2 Wild-Type Tumors

Background: Breast cancer patients who do not respond to neoadjuvant therapy have a poor prognosis. There is a pressing need for novel targets and models for preclinical testing. Here we report characterization of breast cancer patient-derived xenografts (PDX) largely generated from residual tumors following neoadjuvant chemotherapy.Experimental Design: PDXs were derived from surgical samples of primary or locally recurrent tumors. Normal and tumor DNA sequencing, RNASeq, and reverse phase protein arrays (RPPA) were performed. Phenotypic profiling was performed by determining efficacy of a panel of standard and investigational agents.Results: Twenty-six PDXs were developed from 25 patients. Twenty-two were generated from residual disease following neoadjuvant chemotherapy, and 24 were from triple-negative breast cancer (TNBC). These PDXs harbored a heterogeneous set of genomic alterations and represented all TNBC molecular subtypes. On RPPA, PDXs varied in extent of PI3K and MAPK activation. PDXs also varied in their sensitivity to chemotherapeutic agents. PI3K, mTOR, and MEK inhibitors repressed growth but did not cause tumor regression. The PARP inhibitor talazoparib caused dramatic regression in five of 12 PDXs. Notably, four of five talazoparib-sensitive models did not harbor germline BRCA1/2 mutations, but several had somatic alterations in homologous repair pathways, including ATM deletion and BRCA2 alterations.Conclusions: PDXs capture the molecular and phenotypic heterogeneity of TNBC. Here we show that PARP inhibition can have activity beyond germline BRCA1/2 altered tumors, causing regression in a variety of molecular subtypes. These models represent an opportunity for the discovery of rational combinations with targeted therapies and predictive biomarkers. Clin Cancer Res; 23(21); 6468-77. ©2017 AACR.

The TGFα-EGFR-Akt signaling axis plays a role in enhancing proinflammatory chemokines in triple-negative breast cancer cells

Triple-negative breast cancer (TNBC) is aggressive and typically has a poor prognosis. Chemokines have chemoattractant potential for cancer metastasis. Here, we investigated the chemokine signatures in BC subtypes and the underlying mechanisms that enhance proinflammatory chemokines in TNBC. Analysis from microarray dataset revealed that basal-like BC subtype including TNBC expressed dominantly proinflammatory chemokines, such as CXCL1 and 8, compared to non-TNBC. Chemokine PCR array confirmed the dominant chemokines in TNBC cells. To identify a driving factor for proinflammatory chemokines in TNBC cells, we determined the expression and signaling profiles of epidermal growth factor receptor (EGFR) family members. TNBC cells expressed higher levels of EGFR and phosphorylated Akt/Erk than non-TNBC cells. In addition, EGF further enhanced the proinflammatory chemokines in TNBC cells, including CXCL2. Knockdown of Akt reduced the CXCL2 promoter activity, while overexpression of Akt enhanced it. MK2206, an Akt inhibitor, reduced the CXCL2 promoter activity, while inhibition and knockdown of Erk did not reduce its activity. We found that transforming growth factor alpha (TGFα) could serve as a main ligand for EGFR to drive EGFR-mediated Akt activation in TNBC cells. MK2206 decreased TGFα promoter activity, while overexpression of Akt increased it. MK2206 also reduced TGFα release from TNBC cells. Moreover, MK2206 downregulated CXCL2 mRNA expression, while TGFα upregulated it. Taken together, the TGFα-EGFR-Akt signaling axis can play a role in enhancing proinflammatory chemokine expression in TNBC, subsequently contributing to the inflammatory burden that ultimately lead to cancer progression and a higher mortality rate among TNBC patients.

Subtyping Of Triple Negative Breast Carcinoma On The Basis Of RTK Expression

Background: "Triple-negative breast cancers" (TNBC) comprise a heterogeneous group of about 15% of invasive BCs lacking the expression of estrogen and progesterone receptors (ER, PR) and the expression of HER2 (ERBB2) and are therefore no established candidates for targeted treatment options in BC, i.e., endocrine and anti-HER2 therapy. The aim of the present study was to use gene expression profiling and immunohistochemical (IHC) characterization to identify receptor tyrosine kinase (RTK) profiles that would allow patient stratification for the purposes of target-oriented personalized tumor therapy in TNBC. Methods: Twenty-nine cases of TNBC selected according to routine diagnostic IHC/cytogenetic criteria were examined by reverse transcription polymerase chain reaction (RT-PCR). RTK mRNA expression profiles were generated for a total of 31 tumor-relevant biomarkers, mainly belonging to the IGF- and EGF-receptor families but also including biomarkers related to downstream signaling. Protein expression of selected biomarkers was investigated by IHC. Results: Hierarchical cluster analysis revealed a dichotomous differentiation pattern amongst TNBCs. A significant difference in gene expression was observed for 16 of the 31 RTK-associated tumor relevant biomarkers between the two newly identified TNBC subgroups. The findings were verified at the posttranslational level by the IHC data. The RTKs HER4, IGF-1R and IGF-2R and the hormone receptors ER and PR below the IHC detection limit play a central role in the differentiation of the two TNBC subgroups. Observed survival was reported as Kaplan-Meier estimates and point towards an improved survival of patients with RTK-high with superior three-year survival rate of 100% compared to RTK-low gene signatures with superior three-year survival rate of 60% (log-rank test, p-value = 0.022). Conclusion: Gene-expression and IHC analysis of the EGF and IGF receptor families and biomarkers associated with downstream signaling point to the existence of two distinct TNBC subtypes. The RTKs HER4, IGF-1R, IGF-2R and the hormone receptors ER and PR appear to be of particular importance here. Based on survival analysis the differentiation of TNBC with RTK-high and RTK-low gene signatures seems to be of prognostic relevance. Additionally, correlation analysis of the relationship between RTKs and ER suggests co-regulatory mechanisms that may have potential significance in new therapeutic approaches.

Systems modelling of the EGFR-PYK2-c-Met interaction network predicts and prioritizes synergistic drug combinations for triple-negative breast cancer

Prediction of drug combinations that effectively target cancer cells is a critical challenge for cancer therapy, in particular for triple-negative breast cancer (TNBC), a highly aggressive breast cancer subtype with no effective targeted treatment. As signalling pathway networks critically control cancer cell behaviour, analysis of signalling network activity and crosstalk can help predict potent drug combinations and rational stratification of patients, thus bringing therapeutic and prognostic values. We have previously showed that the non-receptor tyrosine kinase PYK2 is a downstream effector of EGFR and c-Met and demonstrated their crosstalk signalling in basal-like TNBC. Here we applied a systems modelling approach and developed a mechanistic model of the integrated EGFR-PYK2-c-Met signalling network to identify and prioritize potent drug combinations for TNBC. Model predictions validated by experimental data revealed that among six potential combinations of drug pairs targeting the central nodes of the network, including EGFR, c-Met, PYK2 and STAT3, co-targeting of EGFR and PYK2 and to a lesser extent of EGFR and c-Met yielded strongest synergistic effect. Importantly, the synergy in co-targeting EGFR and PYK2 was linked to switch-like cell proliferation-associated responses. Moreover, simulations of patient-specific models using public gene expression data of TNBC patients led to predictive stratification of patients into subgroups displaying distinct susceptibility to specific drug combinations. These results suggest that mechanistic systems modelling is a powerful approach for the rational design, prediction and prioritization of potent combination therapies for individual patients, thus providing a concrete step towards personalized treatment for TNBC and other tumour types.

We applied a systems modelling approach combining mechanistic modelling and biological experimentation to identify effective drug combinations for triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer with no approved targeted treatment. The model predicted and prioritized the synergistic combinations as confirmed by experimental data, demonstrating the power of this approach. Moreover, analysis of clinical data of TNBC patients and patient-specific modelling simulation enabled us to stratify the patients into subgroups with distinct susceptibility to specific drug combinations, and thus defined a subset of patient that could benefit from the combined treatments.

Clinicopathological, immunohistochemical and molecular correlation of neural crest transcription factor SOX10 expression in triple-negative breast carcinoma

The transcription factor SOX10 mediates the differentiation of neural crest-derived cells, and SOX10 by immunohistochemistry (IHC) is used primarily for the diagnosis of melanoma. SOX10 expression has been previously documented in benign breast myoepithelial cells. However there is limited literature on its expression in triple-negative breast carcinoma (TNBC). The aim was to study the clinical, pathologic and molecular profiles of SOX10+ tumors in TNBC. Tissue microarrays of TNBC were evaluated for SOX10 expression in 48 cases. SOX10 expression was correlated with clinical and pathologic features such as age, grade, and stage. Gene expression was analyzed on RNA extracted from formalin-fixed paraffin-embedded (FFPE) specimens with Affymetrix 2.0 HTA. Co-expression of SOX10 with androgen receptor (AR), WT1, gross cystic disease fluid protein-15 (GCDFP-15), mammaglobin, epidermal growth factor receptor (EGFR), CK5/6 and GATA transcription factor 3 (GATA3) were also assessed. The mean age was 59.38 (range, 28-90 years). Overall, 37.5% cases (18/48) were SOX10+. There was no association between SOX10 expression and age, grade or stage of patients; 6 of 10 (60%) cases of basal-like 1 (BL1), and 5 of 8 cases of unstable (UNS) molecular subtype were SOX10+. One of 5 basal-like-2 (BL2), 1 of 6 immunomodulatory (IM), 1 of 4 mesenchymal (M), 1 of 5 luminal androgen receptor (LAR) and 2 of 8 mesenchymal stem cell (MSL) showed lower frequencies of SOX10 expression. There was negative correlation between SOX10 and AR+ subtypes (P < .002). SOX10 was positively correlated with WT1 (P = .05). SOX10 did not show significant correlation with mammaglobin, GCDFP15, EGFR, CK5/6 and GATA3. SOX10 expression in the basal-like and unstable molecular subtypes supports the concept that these neoplasms show myoepithelial differentiation.

Triple negative breast cancer subtypes and pathologic complete response rate to neoadjuvant chemotherapy

Triple negative breast cancer (TNBC) is a heterogeneous disease with distinct molecular subtypes that differentially respond to chemotherapy and targeted agents. The purpose of this study is to explore the clinical relevance of Lehmann TNBC subtypes by identifying any differences in response to neoadjuvant chemotherapy among them. We determined Lehmann subtypes by gene expression profiling in paraffined pre-treatment tumor biopsies from 125 TNBC patients treated with neoadjuvant anthracyclines and/or taxanes +/- carboplatin. We explored the clinicopathological characteristics of Lehmann subtypes and their association with the pathologic complete response (pCR) to different treatments. The global pCR rate was 37%, and it was unevenly distributed within Lehmann’s subtypes. Basal-like 1 (BL1) tumors exhibited the highest pCR to carboplatin containing regimens (80% vs 23%, p=0.027) and were the most proliferative (Ki-67>50% of 88.2% vs. 63.7%, p=0.02). Luminal-androgen receptor (LAR) patients achieved the lowest pCR to all treatments (14.3% vs 42.7%, p=0.045 when excluding mesenchymal stem-like (MSL) samples) and were the group with the lowest proliferation (Ki-67≤50% of 71% vs 27%, p=0.002). In our cohort, only tumors with LAR phenotype presented non-basal-like intrinsic subtypes (HER2-enriched and luminal A). TNBC patients present tumors with a high genetic diversity ranging from highly proliferative tumors, likely responsive to platinum-based therapies, to a subset of chemoresistant tumors with low proliferation and luminal characteristics.

shinySISPA: A web tool for defining sample groups using gene sets from multiple-omics data

As opposed to genome-wide testing of several hundreds of thousands of genes on very few samples, gene panels target as few as tens of genes and enable the simultaneous testing of many samples.  For example, some cancer gene panels test for 50 genes that can affect tumor growth and potentially identify treatment options directed against the genetic mutation.  The increasing popularity of gene panel testing has spurred the technological development of panels that test for diverse data types such as expression and mutation.   Once samples are tested, there is the desire to examine clinical associations based on the panel and for this purpose, one would like to identify, among the samples tested, which show support for a molecular profile (e.g., presence of mutation with increased expression) versus those samples that do not among the genes tested.  With user-specified molecular profile of interest, and gene panel data matrices (e.g., gene expression, variants, etc.) that define the profile, shinySISPA (Sample Integrated Set Profile Analysis) is a web-based shiny tool to define two sample groups with and without profile support based on our previously published method from which clinical associations may be readily examined. The shinySISPA can be accessed from http://shinygispa.winship.emory.edu/shinySISPA/.

shinySISPA: A web tool for defining sample groups using gene sets from multiple-omics data

As opposed to genome-wide testing of several hundreds of thousands of genes on very few samples, gene panels target as few as tens of genes and enable the simultaneous testing of many samples.  For example, some cancer gene panels test for 50 genes that can affect tumor growth and potentially identify treatment options directed against the genetic mutation.  The increasing popularity of gene panel testing has spurred the technological development of panels that test for diverse data types such as expression and mutation.   Once samples are tested, there is the desire to examine clinical associations based on the panel and for this purpose, one would like to identify, among the samples tested, which show support for a molecular profile (e.g., presence of mutation with increased expression) versus those samples that do not among the genes tested.  With user-specified molecular profile of interest, and gene panel data matrices (e.g., gene expression, variants, etc.) that define the profile, shinySISPA (Sample Integrated Set Profile Analysis) is a web-based shiny tool to define two sample groups with and without profile support based on our previously published method from which clinical associations may be readily examined. The shinySISPA can be accessed from http://shinygispa.winship.emory.edu/shinySISPA/.

Pathological Response in a Triple-Negative Breast Cancer Cohort Treated with Neoadjuvant Carboplatin and Docetaxel According to Lehmann's Refined Classification

Purpose: Triple-negative breast cancer (TNBC) requires the iden- tification of reliable predictors of response to neoadjuvant chemotherapy (NACT). For this purpose, we aimed to evaluate the performance of the TNBCtype-4 classifier in a cohort of patients with TNBC treated with neoadjuvant carboplatin and docetaxel (TCb).Methods: Patients with TNBC were accrued in a nonrandomized trial of neoadjuvant carboplatin AUC 6 and docetaxel 75 mg/m² for six cycles. Response was evaluated in terms of pathologic complete response (pCR, ypT0/is ypN0) and residual cancer burden by Symmans and colleagues. Lehmann's subtyping was performed using the TNBCtype online tool from RNAseq data, and germline sequencing of a panel of seven DNA damage repair genes was conducted.Results: Ninety-four out of the 121 patients enrolled in the trial had RNAseq available. The overall pCR rate was 44.7%. Lehmann subtype distribution was 34.0% BL1, 20.2% BL2, 23.4% M, 14.9% LAR, and 7.4% were classified as ER+. Response to NACT with TCb was significantly associated with Lehmann subtype (P = 0.027), even in multivariate analysis including tumor size and nodal involvement, with BL1 patients achieving the highest pCR rate (65.6%), followed by BL2 (47.4%), M (36.4%), and LAR (21.4%). BL1 was associated with a significant younger age at diagnosis and higher ki67 values. Among our 10 germline mutation carriers, 30% were BL1, 40% were BL2, and 30% were M.Conclusions: TNBCtype-4 is associated with significantly different pCR rates for the different subtypes, with BL1 and LAR displaying the best and worse responses to NACT, respectively. Clin Cancer Res; 24(8); 1845-52. ©2018 AACR.

Whole transcriptome profiling of patient-derived xenograft models as a tool to identify both tumor and stromal specific biomarkers

The tumor microenvironment is emerging as a key regulator of cancer growth and progression, however the exact mechanisms of interaction with the tumor are poorly understood. Whilst the majority of genomic profiling efforts thus far have focused on the tumor, here we investigate RNA-Seq as a hypothesis-free tool to generate independent tumor and stromal biomarkers, and explore tumor-stroma interactions by exploiting the human-murine compartment specificity of patient-derived xenografts (PDX).

Across a pan-cancer cohort of 79 PDX models, we determine that mouse stroma can be separated into distinct clusters, each corresponding to a specific stromal cell type. This implies heterogeneous recruitment of mouse stroma to the xenograft independent of tumor type. We then generate cross-species expression networks to recapitulate a known association between tumor epithelial cells and fibroblast activation, and propose a potentially novel relationship between two hypoxia-associated genes, human MIF and mouse Ddx6. Assessment of disease subtype also reveals MMP12 as a putative stromal marker of triple-negative breast cancer. Finally, we establish that our ability to dissect recruited stroma from trans-differentiated tumor cells is crucial to identifying stem-like poor-prognosis signatures in the tumor compartment.

In conclusion, RNA-Seq is a powerful, cost-effective solution to global analysis of human tumor and mouse stroma simultaneously, providing new insights into mouse stromal heterogeneity and compartment-specific disease markers that are otherwise overlooked by alternative technologies. The study represents the first comprehensive analysis of its kind across multiple PDX models, and supports adoption of the approach in pre-clinical drug efficacy studies, and compartment-specific biomarker discovery.

The Landscape of Small Non-Coding RNAs in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an operational term for breast cancers lacking targetable estrogen receptor expression and HER2 amplifications. TNBC is, therefore, inherently heterogeneous, and is associated with worse prognosis, greater rates of metastasis, and earlier onset. TNBC displays mutational and transcriptional diversity, and distinct mRNA transcriptional subtypes exhibiting unique biology. High-throughput sequencing has extended cancer research far beyond protein coding regions that include non-coding small RNAs, such as miRNA, isomiR, tRNA, snoRNAs, snRNA, yRNA, 7SL, and 7SK. In this study, we performed small RNA profiling of 26 TNBC cell lines, and compared the abundance of non-coding RNAs among the transcriptional subtypes of triple negative breast cancer. We also examined their co-expression pattern with corresponding mRNAs. This study provides a detailed description of small RNA expression in triple-negative breast cancer cell lines that can aid in the development of future biomarker and novel targeted therapies.

Interferon-beta represses cancer stem cell properties in triple-negative breast cancer

Triple-negative breast cancer (TNBC), the deadliest form of this disease, lacks a targeted therapy. TNBC tumors that fail to respond to chemotherapy are characterized by a repressed IFN/signal transducer and activator of transcription (IFN/STAT) gene signature and are often enriched for cancer stem cells (CSCs). We have found that human mammary epithelial cells that undergo an epithelial-to-mesenchymal transition (EMT) following transformation acquire CSC properties. These mesenchymal/CSCs have a significantly repressed IFN/STAT gene expression signature and an enhanced ability to migrate and form tumor spheres. Treatment with IFN-beta (IFN-β) led to a less aggressive epithelial/non-CSC-like state, with repressed expression of mesenchymal proteins (VIMENTIN, SLUG), reduced migration and tumor sphere formation, and reexpression of CD24 (a surface marker for non-CSCs), concomitant with an epithelium-like morphology. The CSC-like properties were correlated with high levels of unphosphorylated IFN-stimulated gene factor 3 (U-ISGF3), which was previously linked to resistance to DNA damage. Inhibiting the expression of IRF9 (the DNA-binding component of U-ISGF3) reduced the migration of mesenchymal/CSCs. Here we report a positive translational role for IFN-β, as gene expression profiling of patient-derived TNBC tumors demonstrates that an IFN-β metagene signature correlates with improved patient survival, an immune response linked with tumor-infiltrating lymphocytes (TILs), and a repressed CSC metagene signature. Taken together, our findings indicate that repressed IFN signaling in TNBCs with CSC-like properties is due to high levels of U-ISGF3 and that treatment with IFN-β reduces CSC properties, suggesting a therapeutic strategy to treat drug-resistant, highly aggressive TNBC tumors.

Differential prioritization of therapies to subtypes of triple negative breast cancer using a systems medicine method

Triple negative breast cancer (TNBC) is a group of cancers whose heterogeneity and shortage of effective drug therapies has prompted efforts to divide these cancers into molecular subtypes. Our computational platform, entitled GenEx-TNBC, applies concepts in systems biology and polypharmacology to prioritize thousands of approved and experimental drugs for therapeutic potential against each molecular subtype of TNBC. Using patient-based and cell line-based gene expression data, we constructed networks to describe the biological perturbation associated with each TNBC subtype at multiple levels of biological action. These networks were analyzed for statistical coincidence with drug action networks stemming from known drug-protein targets, while accounting for the direction of disease modulation for coinciding entities. GenEx-TNBC successfully designated drugs, and drug classes, that were previously shown to be broadly effective or subtype-specific against TNBC, as well as novel agents. We further performed biological validation of the platform by testing the relative sensitivities of three cell lines, representing three distinct TNBC subtypes, to several small molecules according to the degree of predicted biological coincidence with each subtype. GenEx-TNBC is the first computational platform to associate drugs to diseases based on inverse relationships with multi-scale disease mechanisms mapped from global gene expression of a disease. This method may be useful for directing current efforts in preclinical drug development surrounding TNBC, and may offer insights into the targetable mechanisms of each TNBC subtype.

Gene expression information improves reliability of receptor status in breast cancer patients

Immunohistochemical (IHC) determination of receptor status in breast cancer patients is frequently inaccurate. Since it directs the choice of systemic therapy, it is essential to increase its reliability.

We increase the validity of IHC receptor expression by additionally considering gene expression (GE) measurements. Crisp therapeutic decisions are based on IHC estimates, even if they are borderline reliable. We further improve decision quality by a responsibility function, defining a critical domain for gene expression. Refined normalization is devised to file any newly diagnosed patient into existing data bases. Our approach renders receptor estimates more reliable by identifying patients with questionable receptor status. The approach is also more efficient since the rate of conclusive samples is increased. We have curated and evaluated gene expression data, together with clinical information, from 2880 breast cancer patients. Combining IHC with gene expression information yields a method more reliable and also more efficient as compared to common practice up to now.

Several types of possibly suboptimal treatment allocations, based on IHC receptor status alone, are enumerated. A ‘therapy allocation check’ identifies patients possibly miss-classified. Estrogen: false negative 8%, false positive 6%. Progesterone: false negative 14%, false positive 11%. HER2: false negative 2%, false positive 50%. Possible implications are discussed.

We propose an ‘expression look-up-plot’, allowing for a significant potential to improve the quality of precision medicine.

Methods are developed and exemplified here for breast cancer patients, but they may readily be transferred to diagnostic data relevant for therapeutic decisions in other fields of oncology.

Single-Cell Dynamics Determines Response to CDK4/6 Inhibition in Triple-Negative Breast Cancer

Purpose: Triple-negative breast cancer (TNBC) is a heterogeneous subgroup of breast cancer that is associated with a poor prognosis. We evaluated the activity of CDK4/6 inhibitors across the TNBC subtypes and investigated mechanisms of sensitivity.Experimental Design: A panel of cell lines representative of TNBC was tested for in vitro and in vivo sensitivity to CDK4/6 inhibition. A fluorescent CDK2 activity reporter was used for single-cell analysis in conjunction with time-lapse imaging.Results: The luminal androgen receptor (LAR) subtype of TNBC was highly sensitive to CDK4/6 inhibition both in vitro (P < 0.001 LAR vs. basal-like) and in vivo in MDA-MB-453 LAR cell line xenografts. Single-cell analysis of CDK2 activity demonstrated differences in cell-cycle dynamics between LAR and basal-like cells. Palbociclib-sensitive LAR cells exit mitosis with low levels of CDK2 activity, into a quiescent state that requires CDK4/6 activity for cell-cycle reentry. Palbociclib-resistant basal-like cells exit mitosis directly into a proliferative state, with high levels of CDK2 activity, bypassing the restriction point and the requirement for CDK4/6 activity. High CDK2 activity after mitosis is driven by temporal deregulation of cyclin E1 expression. CDK4/6 inhibitors were synergistic with PI3 kinase inhibitors in PIK3CA-mutant TNBC cell lines, extending CDK4/6 inhibitor sensitivity to additional TNBC subtypes.Conclusions: Cell-cycle dynamics determine the response to CDK4/6 inhibition in TNBC. CDK4/6 inhibitors, alone and in combination, are a novel therapeutic strategy for specific subgroups of TNBC. Clin Cancer Res; 23(18); 5561-72. ©2017 AACR.

Nanogrid single-nucleus RNA sequencing reveals phenotypic diversity in breast cancer

Single cell RNA sequencing has emerged as a powerful tool for resolving transcriptional diversity in tumors, but is limited by throughput, cost and the ability to process archival frozen tissue samples. Here we develop a high-throughput 3' single-nucleus RNA sequencing approach that combines nanogrid technology, automated imaging, and cell selection to sequence up to ~1800 single nuclei in parallel. We compare the transcriptomes of 485 single nuclei to 424 single cells in a breast cancer cell line, which shows a high concordance (93.34%) in gene levels and abundance. We also analyze 416 nuclei from a frozen breast tumor sample and 380 nuclei from normal breast tissue. These data reveal heterogeneity in cancer cell phenotypes, including angiogenesis, proliferation, and stemness, and a minor subpopulation (19%) with many overexpressed cancer genes. Our studies demonstrate the utility of nanogrid single-nucleus RNA sequencing for studying the transcriptional programs of tumor nuclei in frozen archival tissue samples.Single cell RNA sequencing is a powerful tool for understanding cellular diversity but is limited by cost, throughput and sample preparation. Here the authors use nanogrid technology with integrated imaging to sequence thousands of cancer nuclei in parallel from fresh or frozen tissue.

UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses

Genomics data from The Cancer Genome Atlas (TCGA) project has led to the comprehensive molecular characterization of multiple cancer types. The large sample numbers in TCGA offer an excellent opportunity to address questions associated with tumo heterogeneity. Exploration of the data by cancer researchers and clinicians is imperative to unearth novel therapeutic/diagnostic biomarkers. Various computational tools have been developed to aid researchers in carrying out specific TCGA data analyses; however there is need for resources to facilitate the study of gene expression variations and survival associations across tumors. Here, we report UALCAN, an easy to use, interactive web-portal to perform to in-depth analyses of TCGA gene expression data. UALCAN uses TCGA level 3 RNA-seq and clinical data from 31 cancer types. The portal's user-friendly features allow to perform: 1) analyze relative expression of a query gene(s) across tumor and normal samples, as well as in various tumor sub-groups based on individual cancer stages, tumor grade, race, body weight or other clinicopathologic features, 2) estimate the effect of gene expression level and clinicopathologic features on patient survival; and 3) identify the top over- and under-expressed (up and down-regulated) genes in individual cancer types. This resource serves as a platform for in silico validation of target genes and for identifying tumor sub-group specific candidate biomarkers. Thus, UALCAN web-portal could be extremely helpful in accelerating cancer research. UALCAN is publicly available at http://ualcan.path.uab.edu.

Identification of Interacting Stromal Axes in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a molecularly heterogeneous cancer that is difficult to treat. Despite the role it may play in tumor progression and response to therapy, microenvironmental (stromal) heterogeneity in TNBC has not been well characterized. To address this challenge, we investigated the transcriptome of tumor-associated stroma isolated from TNBC (n = 57). We identified four stromal axes enriched for T cells (T), B cells (B), epithelial markers (E), or desmoplasia (D). Our analysis method (STROMA4) assigns a score along each stromal axis for each patient and then combined the axis scores to subtype patients. Analysis of these subtypes revealed that prognostic capacity of the B, T, and E scores was governed by the D score. When compared with a previously published TNBC subtyping scheme, the STROMA4 method better captured tumor heterogeneity and predicted patient benefit from therapy with increased sensitivity. This approach produces a simple ontology that captures TNBC heterogeneity and informs how tumor-associated properties interact to affect prognosis. Cancer Res; 77(17); 4673-83. ©2017 AACR.

Efficacy and Molecular Mechanisms of Differentiated Response to the Aurora and Angiogenic Kinase Inhibitor ENMD-2076 in Preclinical Models of p53-Mutated Triple-Negative Breast Cancer

Purpose

Triple-negative breast cancer (TNBC) is a subtype associated with poor prognosis and for which there are limited therapeutic options. The purpose of this study was to evaluate the efficacy of ENMD-2076 in p53-mutated TNBC patient-derived xenograft (PDX) models and describe patterns of terminal cell fate in models demonstrating sensitivity, intrinsic resistance, and acquired resistance to ENMD-2076.

Experimental design

p53-mutated, TNBC PDX models were treated with ENMD-2076 and evaluated for mechanisms of sensitivity or resistance to treatment. Correlative tissue testing was performed on tumor tissue to assess for markers of proliferation, apoptosis, senescence, and pathways of resistance after treatment and at the time of acquired resistance.

Results

Sensitivity to ENMD-2076 200 mg/kg daily was associated with induction of apoptosis while models exhibiting intrinsic or acquired resistance to treatment presented with a senescent phenotype. Response to ENMD-2076 was accompanied by an increase in p53 and p73 levels, even within the background of mutant p53. Treatment with ENMD-2076 resulted in a decrease in pAurA and an increase in pHH3. We observed a TNBC subtype switch from the luminal androgen receptor to the basal-like subtype at acquired resistance.

Conclusion

ENMD-2076 has antitumor activity in preclinical models of p53-mutated TNBC. Increased levels of p53 and p73 correlated with sensitivity whereas senescence was associated with resistance to ENMD-2076. The novel finding of a TNBC subtype switch at time of acquired resistance may provide mechanistic insights into the biologic effects of selective pressure of anticancer treatments on TNBC. ENMD-2076 is currently being evaluated in a Phase 2 clinical trial in patients with metastatic, previously treated TNBC where these biologic correlates can be further explored.

Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer

Single-cell transcriptome profiling of tumour tissue isolates allows the characterization of heterogeneous tumour cells along with neighbouring stromal and immune cells. Here we adopt this powerful approach to breast cancer and analyse 515 cells from 11 patients. Inferred copy number variations from the single-cell RNA-seq data separate carcinoma cells from non-cancer cells. At a single-cell resolution, carcinoma cells display common signatures within the tumour as well as intratumoral heterogeneity regarding breast cancer subtype and crucial cancer-related pathways. Most of the non-cancer cells are immune cells, with three distinct clusters of T lymphocytes, B lymphocytes and macrophages. T lymphocytes and macrophages both display immunosuppressive characteristics: T cells with a regulatory or an exhausted phenotype and macrophages with an M2 phenotype. These results illustrate that the breast cancer transcriptome has a wide range of intratumoral heterogeneity, which is shaped by the tumour cells and immune cells in the surrounding microenvironment.

Genetic heterogeneity in breast cancer has been demonstrated at a single-cell resolution with high levels of genome coverage. Here, the authors perform transcriptome analysis of 515 single cells from 11 patients and define core gene expression signatures for subtype-specific single breast cancer cells and tumour-infiltrating immune cells.

Expression of Nestin associates with BRCA1 mutations, a basal-like phenotype and aggressive breast cancer

We here examined whether Nestin, by protein and mRNA levels, could be a predictor of BRCA1 related breast cancer, a basal-like phenotype, and aggressive tumours. Immunohistochemical staining of Nestin was done in independent breast cancer hospital cohorts (Series I-V, total 1257 cases). Also, TCGA proteomic data (n = 103), mRNA microarray data from TCGA (n = 520), METABRIC (n = 1992), and 6 open access breast cancer datasets (n = 1908) were analysed. Patients with Nestin protein expression in tumour cells more often had BRCA1 germline mutations (OR 8.7, p < 0.0005, Series III), especially among younger patients (<40 years at diagnosis) (OR 16.5, p = 0.003). Nestin protein positivity, observed in 9–28% of our hospital cases (Series I-IV), was independently associated with reduced breast cancer specific survival (HR = 2.0, p = 0.035) and was consistently related to basal-like differentiation (by Cytokeratin 5, OR 8.7–13.8, p < 0.0005; P-cadherin OR 7.0–8.9, p < 0.0005; EGFR staining, OR 3.7–8.2, p ≤ 0.05). Nestin mRNA correlated significantly with Nestin protein expression (ρ = 0.6, p < 0.0005), and high levels were seen in the basal-like intrinsic subtype. Gene expression signalling pathways linked to high Nestin were explored, and revealed associations with stem-like tumour features. In summary, Nestin was strongly associated with germline BRCA1 related breast cancer, a basal-like phenotype, reduced survival, and stemness characteristics.

Cell state plasticity, stem cells, EMT, and the generation of intra-tumoral heterogeneity

Cellular heterogeneity in cancer represents a significant challenge. In order to develop effective and lasting therapies, it is essential to understand the source of this heterogeneity, and its role in tumor progression and therapy resistance. Here, we consider not only genetic and epigenetic mechanisms, but also inflammation and cell state reprogramming in creating tumor heterogeneity. We discuss similarities between normal mammary epithelial developmental states and various breast cancer molecular sub-types, and the cells that are thought to propagate them. We emphasize that while stem cell phenotypes and mesenchymal character have often been conflated, existing data suggest that the combination of intrinsic genetic and epigenetic changes, and microenvironmental influences generate multiple types of tumor propagating cells distinguishable by their positions along a continuum of epithelial to mesenchymal, stem to differentiated and embryonic to mature cell states. Consequently, in addition to the prospect of stem cell-directed tumor therapies, there is a need to understand interrelationships between stem cell, epithelial–mesenchymal, and tumor-associated reprogramming events to develop new therapies that mitigate cell state plasticity and minimize the evolution of tumor heterogeneity.

Comparison of triple-negative breast cancer molecular subtyping using RNA from matched fresh-frozen versus formalin-fixed paraffin-embedded tissue

BACKGROUND

Triple negative breast cancer (TNBC) is a heterogeneous disease that lacks unifying molecular alterations that can guide therapy decisions. We previously identified distinct molecular subtypes of TNBC (TNBCtype) using gene expression data generated on a microarray platform using frozen tumor specimens. Tumors and cell lines representing the identified subtypes have distinct enrichment in biologically relevant transcripts with differing sensitivity to standard chemotherapies and targeted agents. Since our initial discoveries, RNA-sequencing (RNA-seq) has evolved as a sensitive and quantitative tool to measure transcript abundance.

METHODS

To demonstrate that TNBC subtypes were similar between platforms, we compared gene expression from matched specimens profiled by both microarray and RNA-seq from The Cancer Genome Atlas (TCGA). In the clinical care of patients with TNBC, tumor specimens collected for diagnostic purposes are processed by formalin fixation and paraffin-embedding (FFPE). Thus, for TNBCtype to eventually have broad and practical clinical utility we performed RNA-seq gene expression and molecular classification comparison between fresh-frozen (FF) and FFPE tumor specimens.

RESULTS

Analysis of TCGA showed consistent subtype calls between 91% of evaluable samples demonstrating conservation of TNBC subtypes across microarray and RNA-seq platforms. We compared RNA-seq performed on 21-paired FF and FFPE TNBC specimens and evaluated genome alignment, transcript coverage, differential transcript enrichment and concordance of TNBC molecular subtype calls. We demonstrate that subtype accuracy between matched FF and FFPE samples increases with sequencing depth and correlation strength to an individual TNBC subtype.

CONCLUSIONS

TNBC subtypes were reliably identified from FFPE samples, with highest accuracy if the samples were less than 4 years old and reproducible subtyping increased with sequencing depth. To reproducibly subtype tumors using gene expression, it is critical to select genes that do not vary due to platform type, tissue processing or RNA isolation method. The majority of differentially expressed transcripts between matched FF and FFPE samples could be attributed to transcripts selected for by RNA enrichment method. While differentially expressed transcripts did not impact TNBC subtyping, they will provide guidance on determining which transcripts to avoid when implementing a gene set size reduction strategy.

TRIAL REGISTRATION

NCT00930930 07/01/2009.

A Randomized Phase II Neoadjuvant Study of Cisplatin, Paclitaxel With or Without Everolimus in Patients with Stage II/III Triple-Negative Breast Cancer (TNBC): Responses and Long-term Outcome Correlated with Increased Frequency of DNA Damage Response Gene Mutations, TNBC Subtype, AR Status, and Ki67

Purpose: Because of inherent disease heterogeneity, targeted therapies have eluded triple-negative breast cancer (TNBC), and biomarkers predictive of treatment response have not yet been identified. This study was designed to determine whether the mTOR inhibitor everolimus with cisplatin and paclitaxel would provide synergistic antitumor effects in TNBC.Methods: Patients with stage II/III TNBC were enrolled in a randomized phase II trial of preoperative weekly cisplatin, paclitaxel and daily everolimus or placebo for 12 weeks, until definitive surgery. Tumor specimens were obtained at baseline, cycle 1, and surgery. Primary endpoint was pathologic complete response (pCR); secondary endpoints included clinical responses, breast conservation rate, safety, and discovery of molecular features associated with outcome.Results: Between 2009 and 2013, 145 patients were accrued; 36% of patients in the everolimus arm and 49% of patients in the placebo arm achieved pCR; in each arm, 50% of patients achieved complete responses by imaging. Higher rates of neutropenia, mucositis, and transaminase elevation were seen with everolimus. Clinical response to therapy and long-term outcome correlated with increased frequency of DNA damage response (DDR) gene mutations, Basal-like1 and Mesenchymal TNBC-subtypes, AR-negative status, and high Ki67, but not with tumor-infiltrating lymphocytes.Conclusions: The paclitaxel/cisplatin combination was well tolerated and active, but addition of everolimus was associated with more adverse events without improvement in pCR or clinical response. However, discoveries made from correlative studies could lead to predictive TNBC biomarkers that may impact clinical decision-making and provide new avenues for mechanistic exploration that could lead to clinical utility. Clin Cancer Res; 23(15); 4035-45. ©2017 AACR.

Pentraxin-3 is a PI3K signaling target that promotes stem cell-like traits in basal-like breast cancers

Basal-like breast cancers (BLBCs) exhibit hyperactivation of the phosphoinositide 3-kinase (PI3K) signaling pathway because of the frequent mutational activation of the PIK3CA catalytic subunit and the genetic loss of its negative regulators PTEN (phosphatase and tensin homolog) and INPP4B (inositol polyphosphate-4-phosphatase type II). However, PI3K inhibitors have had limited clinical efficacy in BLBC management because of compensatory amplification of PI3K downstream signaling loops. Therefore, identification of critical PI3K mediators is paramount to the development of effective BLBC therapeutics. Using transcriptomic analysis of activated PIK3CA-expressing BLBC cells, we identified the gene encoding the humoral pattern recognition molecule pentraxin-3 (PTX3) as a critical target of oncogenic PI3K signaling. We found that PTX3 abundance is stimulated, in part, through AKT- and nuclear factor κB (NF-κB)-dependent pathways and that presence of PTX3 is necessary for PI3K-induced stem cell-like traits. We further showed that PTX3 expression is greater in tumor samples from patients with BLBC and that it is prognostic of poor patient survival. Our results thus reveal PTX3 as a newly identified PI3K-regulated biomarker and a potential therapeutic target in BLBC.

Programmed Death Ligand 1 (PD-L1) Tumor Expression Is Associated with a Better Prognosis and Diabetic Disease in Triple Negative Breast Cancer Patients

Triple Negative Breast Cancers (TNBC) subtype is an aggressive disease with poor clinical outcome. The only treatment available is surgery followed by chemotherapy or radiotherapy. Programmed death-ligand 1 (PD-L1) is a trans-membrane protein expressed on a wide variety of cells including immune cells, epithelial and vascular endothelial cells. Recently, PD-1/PD-L1 pathway signaling was described as an adaptive immune resistance mechanism enacted by the tumor cells to evade the immune response. Its presence on tumor cell membranes, acquired for this reason, through time, is an important prognostic value. However, data available in the literature about PD-L1 immunohistochemical expression in breast cancer are often discordant and not uniform, probably for the use of different antibodies clones and the high molecular heterogeneity of the different tumor types. The absence of target therapies, in particular for TNBC, has shifted the clinical attention mainly on the role of PD-L1 in this subtype of breast cancer. In this study, we evaluated tumor and TIL (tumor infiltrating lymphocytes) PDL-1 expression in a series of TNBC, included in Tissue Micro Arrays (TMAs), to define its real prognostic value, optimizing immunohistochemistry method with an “approved for diagnostic assay” antibody. PD-L1 expression directly correlated with proliferation index (Ki-67), glycemia, the presence of diabetes and indirectly with menopausal status, presence of lymph node metastasis and relapse. The analysis of Kaplan–Meier showed that an increased PD-L1 expression was strongly associated with better disease-free survival (DFS) but not correlated with overall survival (OS). Our data confirmed that PD-L1 could be an important marker for prognostic stratification and for planning immune checkpoint inhibitors therapies in patients with TNBC.

A single-nucleotide polymorphism in the 3'-UTR region of the adipocyte fatty acid binding protein 4 gene is associated with prognosis of triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with poor prognosis and high heterogeneity. The aim of this study was to screen patients for single-nucleotide polymorphisms (SNPs) associated with the prognosis of TNBC. Database-derived SNPs (NextBio, Ensembl, NCBI and MirSNP) located in the 3′-untranslated regions (3′-UTRs) of genes that are differentially expressed in breast cancer were selected. The possible associations between 111 SNPs and progression risk among 323 TNBC patients were investigated using a two-step case-control study with a discovery cohort (n=162) and a validation cohort (n=161). We identified the rs1054135 SNP in the adipocyte fatty acid binding protein 4 (FABP4) gene as a predictor of TNBC recurrence. The G allele of rs1054135 was associated with a reduced risk of disease progression as well as a prolonged disease-free survival time (DFS), with a hazard ratio (HR) for recurrence in the combined sample of 0.269 [95%CI: 0.098−0.735;P=0.001]. Notably, for individuals having the rs1054135 SNP with the AA/AG genotype, the magnitude of increased tumour recurrence risk for overweight patients (BMI≥25kg/m²) was significantly elevated (HR2.53; 95%CI: 1.06–6.03). Immunohistochemical staining of adipocytes adjacent to TNBC tissues showed that the expression level of FABP4 was statistically significantly lower in patients with the rs1054135-GG genotype and those in the disease-free group (P=0.0004 and P=0.0091, respectively). These results suggested that the expression of a lipid metabolism-related gene and an important SNP in the 3′-UTR of FABP4 are associated with TNBC prognosis, which may aid in the screening of high-risk patients with TNBC recurrence and the development of novel chemotherapeutic agents.

Clinical and molecular relevance of mutant-allele tumor heterogeneity in breast cancer

PURPOSE

Intra-tumor heterogeneity (ITH) plays a pivotal role in driving breast cancer progression and therapeutic resistance. We used a mutant-allele tumor heterogeneity (MATH) algorithm to measure ITH and explored its correlation with clinical parameters and multi-omics data.

METHODS

We assessed 916 female breast cancer patients from The Cancer Genome Atlas. We calculated the MATH values from whole-exome sequencing data and further investigated their correlation with clinical characteristics, somatic mutations, somatic copy number alterations (SCNAs), and gene enrichment.

RESULTS

The patients were divided into low, intermediate, and high MATH groups. High T stage, African American race, and triple-negative or basal-like subtype were associated with a higher MATH level (all P < 0.001). In hormone receptor-positive and human epidermal growth factor receptor-negative patients, the high MATH group showed a tendency toward a worse overall survival (P = 0.052); Furthermore, the TP53 mutation rate increased as MATH was elevated (P < 0.001), whereas CDH1 mutations were correlated with a lower level of MATH (P = 0.002). Several focal and arm-level SCNA events were more common in the high MATH group (P < 0.05), including Chr8q24 with only the MYC gene in the "peak" region. Similarly, high MATH was associated with gene set enrichment related to the MYC pathway and proliferation.

CONCLUSION

Our integrative analysis reveals the clinical and genetic relevance of ITH in breast cancer. These results also suggest the origin and natural history of clonal evolution and intra-tumor genetic heterogeneity, which warrant further investigation.

Chemotherapy response and survival of inflammatory breast cancer by hormone receptor- and HER2-defined molecular subtypes approximation: an analysis from the National Cancer Database

PURPOSE

To study the impact of hormone receptor (HR)- and human epidermal growth factor receptor 2 (HER2)-defined subtypes on survival of inflammatory breast cancer (IBC), and to determine whether sensitivity to neoadjuvant chemotherapy (NAC) varies with subtypes in a large IBC population.

METHODS

We analyzed 593 IBCs with known HR/HER2 statuses between 2010 and 2011 from National Cancer Database. We compared pathologic complete response (pCR) rates among four molecular subtypes by Chi-square test. Overall survival (OS) was compared among four subtypes and patients with or without pCR using log-rank test. Multivariate Cox model was performed to identify the impact of molecular subtype and other prognostic factors on OS.

RESULTS

Of the 593 patients included, 231 (39.0 %) patients had HR+/HER2- tumors, 98 (16.5 %) had HR+/HER2+ disease, 112 (18.9 %) were HR-/HER2 + patients, and 152 (25.6 %) had triple-negative subtype. The pCR rates differed significantly by subtype (P < 0.001): HR-/HER2+ showed the highest, and HR+/HER2- exhibited the lowest. Multivariate analysis showed that triple-negative and HR+/HER2- IBCs had significantly worse survival compared with HR+/HER2+ or HR-/HER2+ subtype (P < 0.01 for all comparisons). Additional factors associated with worse OS included more comorbidities, lack or incomplete surgical resection, absence of radiotherapy, lack of hormone therapy, and more advanced stage.

CONCLUSIONS

IBC is an aggressive heterogeneous disease with distinct molecular subtypes associated with differential outcomes and sensitivities to NAC. Unlike in noninflammatory breast cancer, in IBC HR + disease was not associated with favorable prognosis. Triple-negative and HR+/HER2- subtypes are independent predictors for suboptimal OS in IBC.

Novel insight into triple-negative breast cancers, the emerging role of angiogenesis, and antiangiogenic therapy

Triple-negative breast cancer (TNBC) is a heterogeneous group of tumours characterised by lack of expression of oestrogen-, progesterone- and human epidermal growth factor receptors. TNBC, which represents approximately 15% of all mammary tumours, has a poor prognosis because of an aggressive behaviour and the lack of specific treatment. Accordingly, TNBC has become a major focus of research into breast cancer and is now classified into several molecular subtypes, each with a different prognosis. Pathological angiogenesis occurs at a late stage in the proliferation of TNBC and is associated with invasion and metastasis; there is an association with metabolic syndrome. Semaphorins are a versatile family of proteins with multiple roles in angiogenesis, tumour growth and metastasis and may represent a clinically useful focus for therapeutic targeting in this type of breast cancer. Another important field of investigation into the control of pathological angiogenesis is related to the expression of noncoding RNA (ncRNA) – these molecules can be considered as a therapeutic target or as a biomarker. Several molecular agents for intervening in the activity of different signalling pathways are being explored in TNBC, but none has so far proved effective in clinical trials and the disease continues to pose a defining challenge for clinical management as well as innovative cancer research.

RNA Sequencing of Formalin-Fixed, Paraffin-Embedded Specimens for Gene Expression Quantification and Data Mining

Background. Proper rRNA depletion is crucial for the successful utilization of FFPE specimens when studying gene expression. We performed a study to evaluate two major rRNA depletion methods: Ribo-Zero and RNase H. RNAs extracted from 4 samples were treated with the two rRNA depletion methods in duplicate and sequenced (N = 16). We evaluated their reducibility, ability to detect RNA, and ability to molecularly subtype these triple negative breast cancer specimens. Results. Both rRNA depletion methods produced consistent data between the technical replicates. We found that the RNase H method produced higher quality RNAseq data as compared to the Ribo-Zero method. In addition, we evaluated the RNAseq data generated from the FFPE tissue samples for noncoding RNA, including lncRNA, enhancer/super enhancer RNA, and single nucleotide variation (SNV). We found that the RNase H is more suitable for detecting high-quality, noncoding RNAs as compared to the Ribo-Zero and provided more consistent molecular subtype identification between replicates. Unfortunately, neither method produced reliable SNV data. Conclusions. In conclusion, for FFPE specimens, the RNase H rRNA depletion method performed better than the Ribo-Zero. Neither method generates data sufficient for SNV detection.

Molecular Classification of Triple-Negative Breast Cancer

Tumor heterogeneity of triple-negative breast cancer (TNBC) has been the main barrier in conquering breast cancer. To dissect the molecular diversity of TNBC and discover therapeutic targets for TNBC, the molecular classification of TNBC is a prioritized issue in research area. Accordingly, recent studies have been successful in classifying TNBC into several distinct subtypes with specific biologic pathways. Despite the different methodologies used and varied number of final subtypes, these studies identically suggested that TNBC consists of four major subtypes: basal-like, mesenchymal, luminal androgen receptor, and immune-enriched. By reviewing these methods of classifications of TNBC, we highlight the unmet need to develop a molecular classifier suited for TNBC.

Development of mouse models of malignant phyllodes tumors by transplantation of syngeneic mammary gland cells expressing mutant H-Ras

Phyllodes tumors (PTs) are rare fibroepithelial tumors of the breast with epithelial and stromal components, and surgical resection is the standard and only available treatment for malignant PTs. To provide a better understanding of these tumors, we developed mouse models that recapitulate the pathological and clinical properties of human malignant PTs. Mouse undifferentiated mammary gland cells were infected with a retrovirus encoding the human oncoprotein H-Ras^G12V , and the infected cells were transplanted orthotopically into the mammary fat pads of syngeneic mice. The transplanted cells showed a high tumorigenic activity, with the resulting tumors manifesting pathological characteristics including stromal overgrowth similar to those of human malignant PTs. The tumors also showed high rates of both local recurrence and lung metastasis. Our models may prove useful for studies of the pathophysiology of malignant PTs as well as facilitate the development of new treatments.

Brain Metastasis Prediction by Transcriptomic Profiling in Triple-Negative Breast Cancer

BACKGROUND

Triple-negative breast cancer (TNBC) lacks expression of steroid hormone receptors (estrogen receptor α and progesterone) and epidermal growth factor receptor type 2. This phenotype shows high metastatic potential, with particular predilection to lungs and brain. Determination of TNBC transcriptomic profiles associated with high risk of brain metastasis (BM) might identify patients requiring alternative, more aggressive, or specific preventive and therapeutic approaches.

PATIENTS AND METHODS

Using a cDNA-mediated annealing, selection, extension, and ligation assay, we investigated expression of 29,369 gene transcripts in primary TNBC tumor samples from 119 patients-71 in discovery cohort A and 48 in independent cohort B-that included best discriminating genes. Expression of mRNA was correlated with the occurrence of symptomatic BM.

RESULTS

In cohort A, the difference at the noncorrected P < .005 was found for 64 transcripts (P = .23 for global test), but none showed significant difference at a preset level of false-discovery rate of < 10%. Of the 30 transcripts with the largest differences between patients with and without BM in cohort A, none was significantly associated with BM in cohort B.

CONCLUSION

Analysis based on the primary tumor gene transcripts alone is unlikely to predict BM development in advanced TNBC. Despite its negative findings, the study adds to the knowledge on the biology of TNBC and paves the way for future projects using more advanced molecular assays.

Maximiscin Induces DNA Damage, Activates DNA Damage Response Pathways, and Has Selective Cytotoxic Activity against a Subtype of Triple-Negative Breast Cancer

Triple-negative breast cancers are highly aggressive, and patients with these types of tumors have poor long-term survival. These breast cancers do not express estrogen or progesterone receptors and do not have gene amplification of human epidermal growth factor receptor 2; therefore, they do not respond to available targeted therapies. The lack of targeted therapies for triple-negative breast cancers stems from their heterogeneous nature and lack of a clear definition of driver defects. Studies have recently identified triple-negative breast cancer molecular subtypes based on gene expression profiling and representative cell lines, allowing for the identification of subtype-specific drug leads and molecular targets. We previously reported the identification of a new fungal metabolite named maximiscin (1) identified through a crowdsourcing program. New results show that 1 has selective cytotoxic efficacy against basal-like 1 MDA-MB-468 cells compared to cell lines modeling other triple-negative breast cancer molecular subtypes. This compound also exhibited antitumor efficacy in a xenograft mouse model. The mechanisms of action of 1 in MDA-MB-468 cells were investigated to identify potential molecular targets and affected pathways. Compound 1 caused accumulation of cells in the G1 phase of the cell cycle, suggesting induction of DNA damage. Indeed, treatment with 1 caused DNA double-strand breaks with concomitant activation of the DNA damage response pathways, indicated by phosphorylation of p53, Chk1, and Chk2. Collectively, these results suggest basal-like triple-negative breast cancer may be inherently sensitive to DNA-damaging agents relative to other triple-negative breast cancer subtypes. These results also demonstrate the potential of our citizen crowdsourcing program to identify new lead molecules for treating the subtypes of triple-negative breast cancer.

The Role of Proliferation in Determining Response to Neoadjuvant Chemotherapy in Breast Cancer: A Gene Expression-Based Meta-Analysis

PURPOSE

To provide further insight into the role of proliferation and other cellular processes in chemosensitivity and resistance, we evaluated the association of a diverse set of gene expression signatures with response to neoadjuvant chemotherapy (NAC) in breast cancer.

EXPERIMENTAL DESIGN

Expression data from primary breast cancer biopsies for 1,419 patients in 17 studies prior to NAC were identified and aggregated using common normalization procedures. Clinicopathologic characteristics, including response to NAC, were collected. Scores for 125 previously published breast cancer-related gene expression signatures were calculated for each tumor.

RESULTS

Within each receptor-based subgroup or PAM50 subtype, breast tumors with high proliferation signature scores were significantly more likely to achieve pathologic complete response to NAC. To distinguish "proliferation-associated" from "proliferation-independent" signatures, we used correlation and linear modeling approaches. Most signatures associated with response to NAC were proliferation associated: 90.5% (38/42) in ER⁺/HER2^- and 63.3% (38/60) in triple-negative breast cancer (TNBC). Proliferation-independent signatures predictive of response to NAC in ER⁺/HER2^- breast cancer were related to immune activity, while those in TNBC comprised a diverse set of signatures, including immune, DNA damage, signaling pathways (PI3K, AKT, Ras, and EGFR), and "stemness" phenotypes.

CONCLUSIONS

Proliferation differences account for the vast majority of predictive capacity of gene expression signatures in neoadjuvant chemosensitivity for ER⁺/HER2^- breast cancers and, to a lesser extent, TNBCs. Immune activation signatures are proliferation-independent predictors of pathologic complete response in ER⁺/HER2^- breast cancers. In TNBCs, significant proliferation-independent signatures include gene sets that represent a diverse set of cellular processes. Clin Cancer Res; 22(24); 6039-50. ©2016 AACR.

Refinement of Triple-Negative Breast Cancer Molecular Subtypes: Implications for Neoadjuvant Chemotherapy Selection

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.

RANKL/RANK control Brca1 mutation-

Breast cancer is the most common female cancer, affecting approximately one in eight women during their life-time. Besides environmental triggers and hormones, inherited mutations in the breast cancer 1 (BRCA1) or BRCA2 genes markedly increase the risk for the development of breast cancer. Here, using two different mouse models, we show that genetic inactivation of the key osteoclast differentiation factor RANK in the mammary epithelium markedly delayed onset, reduced incidence, and attenuated progression of Brca1;p53 mutation-driven mammary cancer. Long-term pharmacological inhibition of the RANK ligand RANKL in mice abolished the occurrence of Brca1 mutation-driven pre-neoplastic lesions. Mechanistically, genetic inactivation of Rank or RANKL/RANK blockade impaired proliferation and expansion of both murine Brca1;p53 mutant mammary stem cells and mammary progenitors from human BRCA1 mutation carriers. In addition, genome variations within the RANK locus were significantly associated with risk of developing breast cancer in women with BRCA1 mutations. Thus, RANKL/RANK control progenitor cell expansion and tumorigenesis in inherited breast cancer. These results present a viable strategy for the possible prevention of breast cancer in BRCA1 mutant patients.

A novel EGR-1 dependent mechanism for YB-1 modulation of paclitaxel response in a triple negative breast cancer cell line

Chemotherapy with taxanes such as paclitaxel (PTX) is a key component of triple negative breast cancer (TNBC) treatment. PTX is used in combination with other drugs in both the adjuvant setting and in advanced breast cancer. Because a proportion of patients respond poorly to PTX or relapse after its use, a greater understanding of the mechanisms conferring resistance to PTX is required. One protein shown to be involved in drug resistance is Y-box binding protein 1 (YB-1). High levels of YB-1 have previously been associated with resistance to PTX in TNBCs. In this study, we aimed to determine mechanisms by which YB-1 confers PTX resistance. We generated isogenic TNBC cell lines that differed by YB-1 levels and treated these with PTX. Using microarray analysis, we identified EGR1 as a potential target of YB-1. We found that low EGR1 mRNA levels are associated with poor breast cancer patient prognosis, and that EGR1 and YBX1 mRNA expression was inversely correlated in a TNBC line and in a proportion of TNBC tumours. Reducing the levels of EGR1 caused TNBC cells to become more resistant to PTX. Given that PTX targets cycling cells, we propose a model whereby high YB-1 levels in some TNBC cells can lead to reduced levels of EGR1, which in turn promotes slow cell cycling and resistance to PTX. Therefore YB-1 and EGR1 levels are biologically linked and may provide a biomarker for TNBC response to PTX.

Comprehensive transcriptome analysis identifies novel molecular subtypes and subtype-specific RNAs of triple-negative breast cancer

BACKGROUND

Triple-negative breast cancer (TNBC) is a highly heterogeneous group of cancers, and molecular subtyping is necessary to better identify molecular-based therapies. While some classifiers have been established, no one has integrated the expression profiles of long noncoding RNAs (lncRNAs) into such subtyping criterions. Considering the emerging important role of lncRNAs in cellular processes, a novel classification integrating transcriptome profiles of both messenger RNA (mRNA) and lncRNA would help us better understand the heterogeneity of TNBC.

METHODS

Using human transcriptome microarrays, we analyzed the transcriptome profiles of 165 TNBC samples. We used k-means clustering and empirical cumulative distribution function to determine optimal number of TNBC subtypes. Gene Ontology (GO) and pathway analyses were applied to determine the main function of the subtype-specific genes and pathways. We conducted co-expression network analyses to identify interactions between mRNAs and lncRNAs.

RESULTS

All of the 165 TNBC tumors were classified into four distinct clusters, including an immunomodulatory subtype (IM), a luminal androgen receptor subtype (LAR), a mesenchymal-like subtype (MES) and a basal-like and immune suppressed (BLIS) subtype. The IM subtype had high expressions of immune cell signaling and cytokine signaling genes. The LAR subtype was characterized by androgen receptor signaling. The MES subtype was enriched with growth factor signaling pathways. The BLIS subtype was characterized by down-regulation of immune response genes, activation of cell cycle, and DNA repair. Patients in this subtype experienced worse recurrence-free survival than others (log rank test, P = 0.045). Subtype-specific lncRNAs were identified, and their possible biological functions were predicted using co-expression network analyses.

CONCLUSIONS

We developed a novel TNBC classification system integrating the expression profiles of both mRNAs and lncRNAs and determined subtype-specific lncRNAs that are potential biomarkers and targets. If further validated in a larger population, our novel classification system could facilitate patient counseling and individualize treatment of TNBC.

Expression of the MHC Class II Pathway in Triple-Negative Breast Cancer Tumor Cells Is Associated with a Good Prognosis and Infiltrating Lymphocytes

Triple-negative breast cancer (TNBC) is a subtype with heterogeneous patient outcomes. Approximately 40% of patients experience rapid relapse, while the remaining patients have long-term disease-free survival. To determine if there are molecular differences between primary tumors that predict prognosis, we performed RNA-seq on 47 macrodissected tumors from newly diagnosed patients with TNBC (n = 47; 22 relapse, 25 no relapse; follow-up median, 8 years; range, 2-11 years). We discovered that expression of the MHC class II (MHC II) antigen presentation pathway in tumor tissue was the most significant pathway associated with progression-free survival (HR, 0.36; log-rank P = 0.0098). The association between MHC II pathway expression and good prognosis was confirmed in a public gene expression database of 199 TNBC cases (HR, 0.28; log-rank P = 4.5 × 10(-8)). Further analysis of immunohistochemistry, laser-capture microdissected tumors, and TNBC cell lines demonstrated that tumor cells, in addition to immune cells, aberrantly express the MHC II pathway. MHC II pathway expression was also associated with B-cell and T-cell infiltration in the tumor. Together, these data support the model that aberrant expression of the MHC II pathway in TNBC tumor cells may trigger an antitumor immune response that reduces the rate of relapse and enhances progression-free survival. Cancer Immunol Res; 4(5); 390-9. ©2016 AACR.

Stratification of Prognosis of Triple-Negative Breast Cancer Patients Using Combinatorial Biomarkers

Background

Triple-negative breast cancer (TNBC) is highly diverse group of cancers, and generally considered an aggressive disease associated with poor survival. Stratification of TNBC is highly desired for both prognosis and treatment decisions to identify patients who may benefit from less aggressive therapy.

Methods

This study retrieved 192 consecutive non-metastasis TNBC patients who had undergone a resection of a primary tumor from 2008 to 2012. All samples were negative for ER, PR, and HER2/neu. Disease-free-survival (DFS) and overall-survival (OS) were evaluated for expression of immunohistochemical biomarkers (P53, Ki-67, CK5/6 and EGFR), as well as clinicopathological variables including age, tumor size, grade, lymph node status, pathologic tumor and nodal stages. The cutoff values of the basal biomarkers, EGFR and CK5/6, were estimated by time-dependent ROC curves. The prognostic values of combinatorial variables were identified by univariate and multivariate Cox analysis. Patients were stratified into different risk groups based on expression status of identified prognostic variables.

Results

Median age was 57 years (range, 28–92 years). Patients’ tumor stage and nodal stage were significantly associated with OS and DFS. EGFR and CK5/6 were significant prognostic variables at cutoff points of 15% (p = 0.001, AUC = 0.723), and 50% (p = 0.006, AUC = 0.675), respectively. Multivariate Cox analysis identified five significant variables: EGFR (p = 0.016), CK5/6 (p = 0.018), Ki-67 (p = 0.048), tumor stage (p = 0.010), and nodal stage (p = 0.003). Patients were stratified into low basal (EGFR≤15% and CK5/6≤50%) and high basal (EGFR>15% and/or CK5/6>50%) expression groups. In the low basal expression group, patients with low expressions of Ki-67, low tumor and nodal stage had significantly better survival than those with high expressions/stages of three variables, log-rank p = 0.015 (100% vs 68% at 50 months). In the high basal expression group, patient with high basal expression of both biomarkers (EGFR >15% and CK5/6 >50%) had worse survival (mean DFS = 25 months, 41.7% event rate) than those patient with high expression of either one marker (mean DFS = 34 months, 25.5% event rate).

Conclusions

Immunoexpression of basal biomarkers, EGFR and CK5/6, is useful in predicting survival of TNBC patients. Integrated with Ki-67, tumor and nodal stages, combinatorial biomarker analysis provides a feasible clinical solution to stratify patient risks and help clinical decision-making with respect to selecting the appropriate therapies for individual patients.

Response and survival of breast cancer intrinsic subtypes following multi-agent neoadjuvant chemotherapy

BACKGROUND

Predicting treatment benefit and/or outcome before any therapeutic intervention has taken place would be clinically very useful. Herein, we evaluate the ability of the intrinsic subtypes and the risk of relapse score at diagnosis to predict survival and response following neoadjuvant chemotherapy. In addition, we evaluated the ability of the Claudin-low and 7-TNBCtype classifications to predict response within triple-negative breast cancer (TNBC).

METHODS

Gene expression and clinical-pathological data were evaluated in a combined dataset of 957 breast cancer patients, including 350 with TNBC, treated with sequential anthracycline and anti-microtubule-based neoadjuvant regimens. Intrinsic subtype, risk of relapse score based on subtype and proliferation (ROR-P), the Claudin-low subtype and the 7-TNBCtype subtype classification were evaluated. Logistic regression models for pathological complete response (pCR) and Cox models for distant relapse-free survival (DRFS) were used.

RESULTS

Basal-like, Luminal A, Luminal B, and HER2-enriched subtypes represented 32.7%, 30.6%, 18.2%, and 10.3% of cases, respectively. Intrinsic subtype was independently associated with pCR in all patients, in hormone receptor-positive/HER2-negative disease, in HER2-positive disease, and in TNBC. The pCR rate of Basal-like disease was >35% across all clinical cohorts. Neither the Claudin-low nor the 7-TNBCtype subtype classifications predicted pCR within TNBCs after accounting for intrinsic subtype. Finally, intrinsic subtype and ROR-P provided independent prognostic information beyond clinicopathological variables and type of pathological response. A 5-year DRFS of 97.5% (92.8-100.0%) was observed in these neoadjuvant-treated and clinically node-negative patients predicted to be low risk by ROR-P (i.e. 57.4% of Luminal A tumors with clinically node-negative disease).

CONCLUSIONS

Intrinsic subtyping at diagnosis provides prognostic and predictive information for patients receiving neoadjuvant chemotherapy. Although we could not exclude a survival benefit of neoadjuvant chemotherapy in patients with early breast cancer with clinically node-negative and ROR-low disease at diagnosis, the absolute benefit of cytotoxic therapy in this group might be rather small (if any).

ΔNp63α induces quiescence and downregulates the BRCA1 pathway in estrogen receptor-positive luminal breast cancer cell line MCF7 but not in other breast cancer cell lines

Despite apparent resection of tumors, breast cancer patients often suffer relapse due to remnant dormant tumor cells. Although quiescence of cancer stem cells is thought as one of the mechanisms regulating dormancy, the mechanism underlying quiescence is unclear. Since ΔNp63α, an isoform of p51/p63, is crucial in the maintenance of stem cells within mammary epithelium, we investigated its roles in the regulation of dormancy in normal and malignant breast cells. Inducible expression of ΔNp63α in MCF7 estrogen receptor positive (ER+) luminal breast cancer cells led to quiescence and acquisition of progenitor-like properties. Judging from mRNA-microRNA microarray analysis, activation of bone morphogenetic protein (BMP) signaling and inhibition of Wnt signaling emerged as prominent mechanisms underlying ΔNp63α-dependent induction of quiescence and acquisition of stemness in MCF7. More interestingly, through Ingenuity Pathway analysis, we found for the first time that BRCA1 pathway was the most significantly downregulated pathway by ΔNp63α expression in quiescent MCF7 cells, where miR-205 was a downstream mediator. Furthermore, ΔNp63α-expressing MCF7 cells exhibited resistance to paclitaxel and doxorubicin. Expression of ΔNp63α in normal MCF10A basal cells increased proliferation and stemness, but did not affect more aggressive luminal (T47D) and basal (MDA-MB-231) cells with p53 mutation. Gene expression datasets analyses suggested that ΔNp63 expression is associated with relapse-free survival of luminal A/B-type patients, but not of the other subtypes. Our results established a cell type-specific function of ΔNp63α in induction of quiescence and downregulation of the BRCA1 pathway which suggested a role of ΔNp63α in the dormancy of luminal breast cancers.