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XLSX file - 285KB, Predicted activated pathways by ICD ERBB4 versus VEC.

XLSX file - 60KB, Predicted activation of Transcriptional regulators.

XLSX file - 42KB, Canonical pathways altered by FL and ICD ERBB4.

PDF file - 2955KB, IPA analysis.

XLSX file - 41KB, Gene list altered by FL and ICD ERBB4 by transcriptional prolifing.

XLSX file - 169KB, ChIP Seq-RNA Overlapping genes.

PDF file - 33KB

PDF file - 135KB, Validation of transcriptional microarray results by qRT-PCR in MCF10A and T47D cells. A) Full-length (FL) and ICD (B) ERBB4 microarray gene validation in MCF10A cells. Total RNA was isolated from Vector-MCF10A, CYT-1 MCF10A and CYT-2 MCF10A cells after 2h exposure to 100ng/ml NRG1 (Vector+, CYT-1+ and CYT-2+) in serum-free OptiMEM media, or from ICD Vector, CYT-1 and CYT-2 MCF10A cells grown in serum containing medium. C) T47D ERBB4 3'-UTR KD, pInducer20 ERBB4 validation of genes from MCF10A microarray in a luminal cell background. T47D cells were starved for 24hrs and stimulated with NRG1 for 2hrs in the presence of DOX (24hrs). Graphs show relative expression of genes as measured by qRT-PCR normalized to GAPDH.

PDF file - 89KB, Genes altered by expressing ERBB4 isoforms.

Triple-negative breast cancer (TNBC) remains an aggressive disease without effective targeted therapies. In this study, we addressed this challenge by testing 128 FDA-approved or investigational drugs as either single agents or in 768 pairwise drug combinations in TNBC cell lines to identify synergistic combinations tractable to clinical translation. Medium-throughput results were scrutinized and extensively analyzed for sensitivity patterns, synergy, anticancer activity, and were validated in low-throughput experiments. Principal component analysis revealed that a fraction of all upregulated or downregulated genes of a particular targeted pathway could partly explain cell sensitivity toward agents targeting that pathway. Combination therapies deemed immediately tractable to translation included ABT-263/crizotinib, ABT-263/paclitaxel, paclitaxel/JQ1, ABT-263/XL-184, and paclitaxel/nutlin-3, all of which exhibited synergistic antiproliferative and apoptotic activity in multiple TNBC backgrounds. Mechanistic investigations of the ABT-263/crizotinib combination offering a potentially rapid path to clinic demonstrated RTK blockade, inhibition of mitogenic signaling, and proapoptotic signal induction in basal and mesenchymal stem–like TNBC. Our findings provide preclinical proof of concept for several combination treatments of TNBC, which offer near-term prospects for clinical translation. Cancer Res; 77(2); 566–78. ©2016 AACR.

Final MTS dataset used for analysis.

Supplementary Figure 1. Flow diagram of patients and samples used in analysis. Blue boxes represent sub-cohorts used for various parts of the study.

Low-throughput validation dataset.

Purpose:We performed whole-exome sequencing (WES) of pre- and posttreatment cancer tissues to assess the somatic mutation landscape of tumors before and after neoadjuvant taxane and anthracycline chemotherapy with or without bevacizumab.Experimental Design:Twenty-nine pretreatment biopsies from the SWOG S0800 trial were subjected to WES to identify mutational patterns associated with response to neoadjuvant chemotherapy. Nine matching samples with residual cancer after therapy were also analyzed to assess changes in mutational patterns in response to therapy.Results:In pretreatment samples, a higher proportion of mutation signature 3, a BRCA-mediated DNA repair deficiency mutational signature, was associated with higher rate of pathologic complete response (pCR; median signature weight 24%, range 0%–38% in pCR vs. median weight 0%, range 0%–19% in residual disease, Wilcoxon rank sum, Bonferroni P = 0.007). We found no biological pathway level mutations associated with pCR or enriched in posttreatment samples. We observed statistically significant enrichment of high functional impact mutations in the “E2F targets” and “G2–M checkpoint” pathways in residual cancer samples implicating these pathways in resistance to therapy and a significant depletion of mutations in the “myogenesis pathway” suggesting the cells harboring these variants were effectively eradicated by therapy.Conclusions:These results suggest that genomic disturbances in BRCA-related DNA repair mechanisms, reflected by a dominant mutational signature 3, confer increased chemotherapy sensitivity. Cancers that survive neoadjuvant chemotherapy frequently have alterations in cell-cycle–regulating genes but different genes of the same pathways are affected in different patients.

Revised Supplementary Methods and Legends

List of direct and indirect targets of agents from each drug category.

Supplementary Figure 1. Effect of panel A drugs on TNBC cell growth in 96-well format. Supplementary Figure 2. Effect of panel B drugs alone and in combination with panel A drugs on TNBC cell growth. Supplementary Figure 3. Summary of growth inhibition by pairwise drug combinations. Supplementary Figure 4. Hierarchical clustering of cell lines based on response to drug treatments and based on expression of drug targets. Supplementary Figure 5. Principal component analysis to associate patterns of target expression with patterns of drug response. Supplementary Figure 6. Assessment of superadditivity of drug combinations. Supplementary Figure 7. A: Comparison of crizotinib versus XL-184 dose response curves when combined with ABT-263 in the six TNBC cell lines. Supplementary Figure 8. ABT-263 and crizotinib induce apoptosis in TNBC cells. Supplementary Figure 9. Expression of MET and AXL in a cohort of 59 TNBC samples from the TCGA breast cancer cohort relative to the median expression of each gene in all breast cancer samples in TCGA.

Supplementary Table 1. Single doses selected for each drug from panel A. Supplementary Table 2. Layout of the two 384-well masterplates containing Panel B drugs. Supplementary Table 4. List of Top Synergistic Drug Combinations. Supplementary Table 5. Combination Index (CI) and Dose Reduction Index (DRI) values for the top drug combinations.

Figure S3, Related to Figure 4. A, c-SRC expression in normal (HFF and MCF-10A), luminal-A (MCF-7), LAR-TNBC (MDA-MB-453), and mesenchymal-TNBC (MDA-MB-231, BT-549, and Hs578T) cell lines. Expression was normalized to GAPDH and made relative to c-SRC expression in HFF lines. B-C, Clonogenic assays in Hs578T (B), and MDA-MB-436 (C) TNBC cells after miR-34a transfection and treatment with Dasatnib (left panels) and paclitaxel (right panel) or as a control HeLa cells after dasatinib treatment (C, right panel). D-E, Assessment of miR-34a target genes in MDA-MB-231 cells after 72 hours of dasatinib treatment (D), or miR-34a levels after 72 hours paclitaxel treatment (E). F, miR-34a promoter luciferase assays in MDA-MB-31 cells after dasatinib treatment. G-H, Spearman rank correlation analysis of SRC levels in cell lines described in Figure 1A (G), and in all breast cancer samples in the Metabric dataset (H). I, Comparable decreases in phospho-Tyr416 active c-SRC, non-phospho-Tyr527 c-SRC, and total c-SRC are observed in MDA-MB-231 cells transfected with 15nM miR-34a versus miR-Scr control, as determined by Western blot analysis. J, Schematic highlighting the miR-34a-c-SRC double-negative feedback loop present in MSL TNBC cells, which can be influenced by exogenous addition of miR-34a, or by dasatinib treatment. * Indicates p

Figure S1, Related to Figure 1. A, miRNA microarray data of the top 50 most variant miRNAs across 17 breast cancer cell lines representing either basal/TNBC (top left blue bar) or luminal (top right red bar) breast cancer subgroups. Amongst these miRNAs, miR-34a (red asterisk) was found to be uniquely downregulated in basal lines. B-C, qPCR validation of array data in TNBC and Luminal-A cancer cell lines as compared to normal mammary epithelial lines (CRCs were cultured using the ROCK inhibitor and condition medium from the 3T3 feeder system as previously described(20)). D, Schematic of WebGestalt 2 analysis of Affymetrix microarray data across 19 cell lines. ¬¬miR-34a is one of several miRNAs with target enrichment in the TNBC overexpressed gene set. E, Results of hypergeometric analysis of miR-34a targets using a more stringent context score cutoff of -0.27. F, SRB growth assays on additional TNBC and normal cell lines.

Figure S4, Related to Figure 5. A-F, Further characterization of c-SRC siRNA treatments in TNBC cell lines. A, Crystal violet staining of MDA-MB-231 and Hs578T cells post 15nM si-SRC and si-Neg transfection (Day 6 images, left panel), and quantification of staining abundance is shown on right panels). B, SRB results on Hs578T cell line. C, Analysis of a second siRNA to c-SRC in MDA-MB-231 cells. SRB assays are shown in the left panel and western blot analysis confirming c-SRC knockdown (72 hour post-transfection) is shown on the right panel. D, Crystal violet staining of HFF cells. E, SA-β-gal assays in the indicated cell lines 5 days after 15nM si-SRC transfection. F, miR-34a levels 72 hours after 15nM si-SRC transfection in Hs578T cells. G, Assessment of SRC mRNA levels in the indicated cell lines 72 hours after 15nM si-SRC transfection.

Triple-negative breast cancer (TNBC) is an aggressive subtype with no clinically proven biologically targeted treatment options. The molecular heterogeneity of TNBC and lack of high frequency driver mutations other than TP53 have hindered the development of new and effective therapies that significantly improve patient outcomes. miRNAs, global regulators of survival and proliferation pathways important in tumor development and maintenance, are becoming promising therapeutic agents. We performed miRNA-profiling studies in different TNBC subtypes to identify miRNAs that significantly contribute to disease progression. We found that miR-34a was lost in TNBC, specifically within mesenchymal and mesenchymal stem cell–like subtypes, whereas expression of miR-34a targets was significantly enriched. Furthermore, restoration of miR-34a in cell lines representing these subtypes inhibited proliferation and invasion, activated senescence, and promoted sensitivity to dasatinib by targeting the proto-oncogene c-SRC. Notably, SRC depletion in TNBC cell lines phenocopied the effects of miR-34a reintroduction, whereas SRC overexpression rescued the antitumorigenic properties mediated by miR-34a. miR-34a levels also increased when cells were treated with c-SRC inhibitors, suggesting a negative feedback exists between miR-34a and c-SRC. Moreover, miR-34a administration significantly delayed tumor growth of subcutaneously and orthotopically implanted tumors in nude mice, and was accompanied by c-SRC downregulation. Finally, we found that miR-34a and SRC levels were inversely correlated in human tumor specimens. Together, our results demonstrate that miR-34a exerts potent antitumorigenic effects in vitro and in vivo and suggests that miR-34a replacement therapy, which is currently being tested in human clinical trials, represents a promising therapeutic strategy for TNBC. Cancer Res; 76(4); 927–39. ©2015 AACR.

Figure S5, Related to Figure 6. A, Assessment of SRC mRNA levels in MDA-MB-231 SRC-ORF, EMPTY-ORF, or parental cell lines. Data is normalized in RPL19 levels. B, Crystal violet staining assays on day 5 post-transfection confirms the ability of c-SRC to rescue miR-34a-induced anti-tumor growth. C-D, Examples of Pearson correlation analysis indicating MDA-MB-231 cells were not similar to BT-549 and MDA-MB-436 cells, and therefore were not included in the initial K-Means clustering analysis (results shown in D). E, The fold knockdown by miR-34a as compared to the miR-Scr treatments of the indicated genes in Clusters 1-3 in both BT-549 and MDA-MB-436 cells using a 2-fold change cut-off. None of the genes in Cluster 4 were downregulated by miR-34a (data not shown). F, Schematic of the KEGG pathway (hsa04510: Focal Adhesion) with miR-34a downregulated genes highlighted in red. G-H, Represents further analysis of the miR-34a gene signature in breast cancer. G, Indicates correlation analyses of miR-34a target genes in TNBC patients from Metabric data. H, Confirmation of prognostic importance of mIR-34a gene signature using a PROGgeneV2 algorithm on the TCGA data set.

Supplementary Materials and Methods and Supplementary Figure Legends

Figure S2, Related to Figure 2. A-F, Functional characterization of miR-34a re-introduction in additional TNBC and non-TNBC cell lines by way of Matrigel-invasion (A), soft agar growth (B), and BrdU labeling (C) experiments. For BrdU assays, we observed only a 5-10% accumulation of BrdU-positive cells 4 days post-transfection. SA-β-gal assays on MDA-MB-157 (D), and BT-20 (E, left panel) TNBC cells, as compared to MCF-7 luminal-A cells (E, right panel). F, MCF-7 cells stably transfected with either a miR-34a (miR-34a SP) or a control (Empty SP) reporter/sponge construct was assayed for SA-β-gal activity. Two independent miR-34a SP pools were generated. G, Luciferase reporter assays indicative of miR-34a activity in all TNBC, luminal, and normal cell lines used in this study. H, miRNA levels in MDA-MB-231, MDA-MB-436, and BT-549 TNBC cells or BT-474 and MCF-7 Luminal-A cells 72 hours after 10nM miR-34a or miR-Scr transfection. In TNBC cells miR-34a expressing lines harbored lower levels of miR-17/92 family members as compared to miR-Scr treated lines. * Indicates p

The effect of scheduling of targeted therapy combinations on drug resistance is underexplored in triple-negative breast cancer (TNBC). TNBC constitutes heterogeneous cancer cell populations the composition of which can change dynamically during treatment resulting in the selection of resistant clones with a fitness advantage. We evaluated crizotinib (ALK/MET inhibitor) and navitoclax (ABT-263; Bcl-2/Bcl-xL inhibitor) combinations in a large design consisting of 696 two-cycle sequential and concomitant treatment regimens with varying treatment dose, duration, and drug holiday length over a 26-day period in MDA-MB-231 TNBC cells and found that patterns of resistance depend on the schedule and sequence in which the drugs are given. Further, we tracked the clonal dynamics and mechanisms of resistance using DNA-integrated barcodes and single-cell RNA sequencing. Our study suggests that longer formats of treatment schedules in vitro screening assays are required to understand the effects of resistance and guide more realistically in vivo and clinical studies.

Background Inflammatory breast cancer (IBC) has a highly invasive and metastatic phenotype. However, little is known about its genetic drivers. To address this, we report the largest cohort of whole-genome sequencing (WGS) of IBC cases. Methods We performed WGS of 20 IBC samples and paired normal blood DNA to identify genomic alterations. For comparison, we used 23 matched non-IBC samples from the Cancer Genome Atlas Program (TCGA). We also validated our findings using WGS data from the International Cancer Genome Consortium (ICGC) and the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We examined a wide selection of genomic features to search for differences between IBC and conventional breast cancer. These include (i) somatic and germline single-nucleotide variants (SNVs), in both coding and non-coding regions; (ii) the mutational signature and the clonal architecture derived from these SNVs; (iii) copy number and structural variants (CNVs and SVs); and (iv) non-human sequence in the tumors (i.e., exogenous sequences of bacterial origin). Results Overall, IBC has similar genomic characteristics to non-IBC, including specific alterations, overall mutational load and signature, and tumor heterogeneity. In particular, we observed similar mutation frequencies between IBC and non-IBC, for each gene and most cancer-related pathways. Moreover, we found no exogenous sequences of infectious agents specific to IBC samples. Even though we could not find any strongly statistically distinguishing genomic features between the two groups, we did find some suggestive differences in IBC: (i) The MAST2 gene was more frequently mutated (20% IBC vs. 0% non-IBC). (ii) The TGF β pathway was more frequently disrupted by germline SNVs (50% vs. 13%). (iii) Different copy number profiles were observed in several genomic regions harboring cancer genes. (iv) Complex SVs were more frequent. (v) The clonal architecture was simpler, suggesting more homogenous tumor-evolutionary lineages. Conclusions Whole-genome sequencing of IBC manifests a similar genomic architecture to non-IBC. We found no unique genomic alterations shared in just IBCs; however, subtle genomic differences were observed including germline alterations in TGFβ pathway genes and somatic mutations in the MAST2 kinase that could represent potential therapeutic targets.

Simple Summary Triple negative breast cancer is a disease with limited treatment options and the poorest outcome across all breast cancer subtypes, thus the need for new effective therapies is high. We recently found that navitoclax displays synergistic anti-proliferative and apoptotic activities with other drugs in treatment of triple negative breast cancer cells, but the resistance to treatment is still a limiting factor. Therefore, we investigated the effects of navitoclax treatment on the transcriptome, genome and epigenome in vitro to better understand the process of developing resistance. We discovered and validated a list of multiple, previously unknown markers of drug resistance that can help in patient selection in future clinical trials involving navitoclax. Abstract Cancer cells employ various defense mechanisms against drug-induced cell death. Investigating multi-omics landscapes of cancer cells before and after treatment can reveal resistance mechanisms and inform new therapeutic strategies. We assessed the effects of navitoclax, a BCL2 family inhibitor, on the transcriptome, methylome, chromatin structure, and copy number variations of MDA-MB-231 triple-negative breast cancer (TNBC) cells. Cells were sampled before treatment, at 72 h of exposure, and after 10-day drug-free recovery from treatment. We observed transient alterations in the expression of stress response genes that were accompanied by corresponding changes in chromatin accessibility. Most of these changes returned to baseline after the recovery period. We also detected lasting alterations in methylation states and genome structure that suggest permanent changes in cell population composition. Using single-cell analyses, we identified 2350 genes significantly upregulated in navitoclax-resistant cells and derived an 18-gene navitoclax resistance signature. We assessed the navitoclax-response-predictive function of this signature in four additional TNBC cell lines in vitro and in silico in 619 cell lines treated with 251 different drugs. We observed a drug-specific predictive value in both experiments, suggesting that this signature could help guiding clinical biomarker studies involving navitoclax.

Background: Several metabolic steps are mediated by distinct proteins or isoenzymes that catalyze the same reaction, providing redundancy of metabolic functions. Metabolic states are frequently altered in cancer to support survival and proliferation in hypoxic and otherwise hostile microenvironments, and metabolic re-wiring often involve loss of isoenzyme diversity. We hypothesize that targeting enzymes that have lost isoenzyme diversity in cancer, but not in normal cells, provides an opportunity to selectively target cancers. In this study, we assessed mRNA expression of all known human isoenzyme families in breast cancer and normal breast tissue and identified isoenzymes with loss of diversity within each breast cancer subtype. Methods: We obtained RNAseq data from cancer and patient-matched normal breast tissues from the TCGA (N=66 HR+, N=24 HER2+, and N=15 TNBC tumors). We retrieved annotated human isoenzyme families from the ENZYME nomenclature database. We compared expression in cancer and matched normal samples from the same patient to identify isoenzymes that had i) same or increased expression of the target isoenzyme in cancer vs normal and ii) reduced expression of the complementary isoenzymes in cancer. We developed five scores that capture various elements of these characteristics and prioritized candidates as targets based on clustering and their combined ranking based on the five scores. We validated overexpression of the candidate isoenzymes relative to other isoforms in breast cancer microarray data from ArrayExpress (E-GEOD-76250: 33 TNBC, and E-GEOD-70951: 30 TNBC, 108 HR+, 10 HER2+). Results: We identified 321 enzymes in the TCGA discovery cohort that correspond to 829 unique isoenzymes. Overall, 636, 483 and 429 isoenzymes were differentially expressed in HR+, HER2+ and TNBC cancers, respectively, compared to corresponding normal samples. Of these, 308 isoenzymes were differentially expressed relative to normal in all 3 subtypes. In all, 112 and 92, and 84 were selected as candidate isoenzyme therapeutic targets in HR+, HER2+ and TNBC, respectively. 23 isoenzymes prioritized in clustering step were further validated. Finally, 6 isoenzymes were validated in HR+ (ALDOA, GUSB, GYG1, MIF, P3H1, PCK2), 10 in HER2+ (ALDH1L2, ALDOA, GLYATL2, GUSB, GYG1, GYS1, MIF, P3H1, PCK2, PTGS1) and 12 in TNBC (ADSS, ALAS1, ALDH1L2, ALDOA, ART3, GLYATL2, GUSB, GYS1, HS3ST1, MIF, PCK2, SOAT1), as potential targets for breast cancer treatment. Of these, 5 potential isoenzyme targets (ALDH1L2, GUSB, GLYATL2, MIF, PCK2), which were mostly hydrolases and transferases, were further selected for ongoing experimental validation in the laboratory. Decreased expression of the complementary isoforms of these 5 targets were primarily due to DNA methylation of the genes in cancer. Conclusions: We found that loss of isoenzyme diversity is a broad phenomenon in breast cancers that may be explored therapeutically. We identified several instances of “isoenzyme addiction” in which cancers depend exclusively on a single isoenzyme while downregulating via methylation the complementary isoenzymes, providing cancer-specific targeting opportunities. We are currently validating several of these targets in cell line models. Citation Format: Marczyk M, Gunasekharan V, Wali VB, Shi W, Patwardhan G, Qing T, Pusztai L, Hatzis C. Targeting loss of isoenzyme diversity as a novel therapeutic strategy in breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P2-06-06.

Background Little is known about how the immune microenvironment of breast cancer evolves during disease progression. Patients and methods We compared tumor infiltrating lymphocyte (TIL) count, programmed death-ligand 1 (PD-L1) protein expression by immunohistochemistry and mRNA levels of 730 immune-related genes using Nanostring technology in primary and metastatic cancer samples. Results TIL counts and PD-L1 positivity were significantly lower in metastases. Immune cell metagenes corresponding to CD8, T-helper, T-reg, Cytotoxic T, Dendritic and Mastoid cells, and expression of 13 of 29 immuno-oncology therapeutic targets in clinical development including PD1, PD-L1, and CTLA4 were significantly lower in metastases. There was also coordinated down regulation of chemoattractant ligand/receptor pairs (CCL19/CCR7, CXCL9/CXCR3, IL15/IL15R), interferon regulated genes (STAT1, IRF-1,-4,-7, IFI-27,-35), granzyme/granulysin, MHC class I and immune proteasome (PSMB-8,-9,-10) expression in metastases. Immunotherapy response predictive signatures were also lower. The expression of macrophage markers (CD163, CCL2/CCR2, CSF1/CSFR1, CXCR4/CXCL12), protumorigenic toll-like receptor pathway genes (CD14/TLR-1,-2,-4,-5,-6/MyD88), HLA-E, ecto-nuclease CD73/NT5E and inhibitory complement receptors (CD-59,-55,-46) remained high in metastases and represent potential therapeutic targets. Conclusions Metastatic breast cancers are immunologically more inert than the corresponding primary tumors but some immune-oncology targets and macrophage and angiogenesis signatures show preserved expression and suggest therapeutic combinations for clinical testing.

The goal of this study was to identify a novel target for antibody-drug conjugate (ADC) development in triple negative breast cancer (TNBC), which has limited treatment options, using gene expression datasets and in vitro siRNA/CRISPR and in vivo functional assays. We analyzed 4467 breast cancers and identified GABRP as top expressed gene in TNBC with low expression in most normal tissues. GABRP protein was localized to cell membrane with broad range of receptors/cell (815–53,714) and expressed by nearly half of breast cancers tissues. GABRP gene knockdown inhibited TNBC cell growth and colony formation in vitro and growth of MDA-MB-468 xenografts in nude mice. Commercially available anti-GABRP antibody (5–100 μg/ml) or de novo generated Fabs (20 μg/ml) inhibited TNBC cell growth in vitro. The same antibody conjugated to mertansine (DM1) also showed significant anticancer activity at nanomolar concentrations. Our results indicate that GABRP is a potential novel therapeutic target for ADC development.

Purpose: We performed whole-exome sequencing (WES) of pre- and posttreatment cancer tissues to assess the somatic mutation landscape of tumors before and after neoadjuvant taxane and anthracycline chemotherapy with or without bevacizumab. Experimental Design: Twenty-nine pretreatment biopsies from the SWOG S0800 trial were subjected to WES to identify mutational patterns associated with response to neoadjuvant chemotherapy. Nine matching samples with residual cancer after therapy were also analyzed to assess changes in mutational patterns in response to therapy. Results: In pretreatment samples, a higher proportion of mutation signature 3, a BRCA-mediated DNA repair deficiency mutational signature, was associated with higher rate of pathologic complete response (pCR; median signature weight 24%, range 0%–38% in pCR vs. median weight 0%, range 0%–19% in residual disease, Wilcoxon rank sum, Bonferroni P = 0.007). We found no biological pathway level mutations associated with pCR or enriched in posttreatment samples. We observed statistically significant enrichment of high functional impact mutations in the “E2F targets” and “G2–M checkpoint” pathways in residual cancer samples implicating these pathways in resistance to therapy and a significant depletion of mutations in the “myogenesis pathway” suggesting the cells harboring these variants were effectively eradicated by therapy. Conclusions: These results suggest that genomic disturbances in BRCA-related DNA repair mechanisms, reflected by a dominant mutational signature 3, confer increased chemotherapy sensitivity. Cancers that survive neoadjuvant chemotherapy frequently have alterations in cell-cycle–regulating genes but different genes of the same pathways are affected in different patients.

Background How the immune microenvironment changes during neoadjuvant chemotherapy of primary breast cancer is not well understood. Methods We analyzed pre- and post-treatment samples from 60 patients using the NanoString PanCancer IO360™ assay to measure the expression of 750 immune-related genes corresponding to 14 immune cell types and various immune functions, and assessed TIL counts and PD-L1 protein expression by immunohistochemistry. Treatment associated changes in gene expression levels were compared using t-test with Bonferroni correction. TIL count, PD-L1 protein and immune metagenes were compared using Wilcoxon test. Baseline immune markers were correlated with pathologic complete response (pCR) using estrogen receptor and treatment arm adjusted logistic regression. Results At baseline, high TIL counts and high expression of chemoattractant cytokines (CCL21, CCL19) and cytotoxic T cell markers were associated with higher pCR rate. High expression of stromal genes (VEGFB, TGFB3, PDGFB, FGFR1, IGFR1), mast and myeloid inflammatory cell metagenes, stem cell related genes (CD90, WNT11, CTNNB1) and CX3CR1, and IL11RA were associated with residual disease (RD). After treatment, in cases with pCR, TIL counts and most immune genes decreased significantly. Among RD cases, TIL counts and PD-L1 expression did not change but cellular stress and hypoxia associated genes (DUSP1, EGR1), and IL6, CD36, CXCL2, CD69 and the IL8/VEGF metagene increased. Conclusions Activated T cells in the tumor microenvironment are associated with pCR whereas stromal functions are associated with residual disease. Most immune functions decrease during neoadjuvant chemotherapy but several immunotherapy targets (PD-L1, IL6, IL8) remain expressed in RD suggesting potential therapeutic strategies. Electronic supplementary material The online version of this article (10.1186/s40425-019-0563-7) contains supplementary material, which is available to authorized users.

Triple-negative breast cancer (TNBC) remains an aggressive disease without effective targeted therapies. In this study, we addressed this challenge by testing 128 FDA-approved or investigational drugs as either single agents or in 768 pairwise drug combinations in TNBC cell lines to identify synergistic combinations tractable to clinical translation. Medium-throughput results were scrutinized and extensively analyzed for sensitivity patterns, synergy, anticancer activity, and were validated in low-throughput experiments. Principal component analysis revealed that a fraction of all upregulated or downregulated genes of a particular targeted pathway could partly explain cell sensitivity toward agents targeting that pathway. Combination therapies deemed immediately tractable to translation included ABT-263/crizotinib, ABT-263/paclitaxel, paclitaxel/JQ1, ABT-263/XL-184, and paclitaxel/nutlin-3, all of which exhibited synergistic antiproliferative and apoptotic activity in multiple TNBC backgrounds. Mechanistic investigations of the ABT-263/crizotinib combination offering a potentially rapid path to clinic demonstrated RTK blockade, inhibition of mitogenic signaling, and proapoptotic signal induction in basal and mesenchymal stem–like TNBC. Our findings provide preclinical proof of concept for several combination treatments of TNBC, which offer near-term prospects for clinical translation. Cancer Res; 77(2); 566–78. ©2016 AACR.

Cancer cells possess various anti-apoptotic defense mechanisms that can protect them from drug induced cell death. We investigated the effects of treatment with the bcl-2/bcl-XL inhibitor Navitoclax on transcriptome, methylome, and genome of MDA-MB-231 cells. Two biological replicates were treated simultaneously and profiled using 10x Genomics single-cell RNA sequencing (scRNAseq; gene expression), bulk RNA sequencing (bRNAseq; gene expression), ATAC sequencing (ATAC; chromatin accessibility), bisulphite targeted sequencing (DNAm; DNA methylation) and shallow whole-genome sequencing (WGS; copy number variants) at baseline before treatment, after 3 days of 10µM navitoclax treatment, and after 10 days of cell recovery from treatment. Variance between biological replicates on transcriptome level was minimal before the treatment (R>0.99), but we noticed divergence in gene expression after recovery from the treatment (both on bulk and single-cell level), mostly driven by cell cycle genes. On other platforms, biological replicates were similar in all 3 phases. After treatment, we observed more genes with decreased expression (n=151) in comparison to baseline, but after 10 days of recovery there were more up-regulated genes (n=655) in comparison to samples after treatment. Chromatin accessibility for most genomic regions increased after treatment in comparison to baseline, suggesting an acute response to the stress caused by drug treatment, and then returned to baseline level after recovery period. DNA methylation patterns showed more regions with decreased methylation after treatment (n=529) in comparison to baseline which remained detectable even after the recovery period. In WGS data, we found 752 genes with deletions and amplifications only in baseline samples representing genomic background of drug sensitive cells, mostly enriched in epithelial mesenchymal transition pathway. On single-cell level, we identified a subset of cells that were resistant to treatment and discovered 2,324 genes significantly up-regulated in these cells, that could be potential markers of resistance. In gene set analysis, these markers were enriched in MYC and E2F target gene sets, and were involved in angiogenesis and JAK-STAT pathway. We measured the expression of 16 top up-regulated markers of resistance in 4 different TNBC cell lines using qPCR and found that 5 were significantly enriched after treatment in 3 cell lines, 5 in 2 cell lines and 5 in a single cell line. Summarizing, we thoroughly described molecular effects of Navitoclax treatment and showed that most cells return to the basal transcriptional state after the drug recovery period, but bulk genome and methylome are permanently changed. Finally, we provided a list of new markers of resistance that may be useful in the studies of combinational therapies with other drugs. This work was funded by Breast Cancer Research Foundation. Citation Format: Michal Marczyk, Vignesh Gunasekharan, Jun Zhao, Rihao Qu, Xiaotong Li, Gauri A. Patwardhan, Vikram B. Wali, Abhishek K. Gupta, Manoj M. Pillai, Yuval Kluger, Christos Hatzis, Lajos Pusztai. Genomic, transcriptomic, and epigenetic profiling of triple-negative breast cancer cells after Navitoclax treatment [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6333.

Background Age is one of the most important risk factors for developing breast cancer. However, age-related changes in normal breast tissue that potentially lead to breast cancer are incompletely understood. Quantifying tissue-level DNA methylation can contribute to understanding these processes. We hypothesized that occurrence of breast cancer should be associated with an acceleration of epigenetic aging in normal breast tissue. Results Ninety-six normal breast tissue samples were obtained from 88 subjects (breast cancer = 35 subjects/40 samples, unaffected = 53 subjects/53 samples). Normal tissue samples from breast cancer patients were obtained from distant non-tumor sites of primary mastectomy specimens, while samples from unaffected women were obtained from the Komen Tissue Bank (n = 25) and from non-cancer-related breast surgery specimens (n = 28). Patients were further stratified into four cohorts: age

Background: Mutations or epigenetic silencing of BRCA1/2 genes result in DNA repair deficiency in a large proportion of TNBC cases. Yet it is unclear whether this deficiency is associated with increased chemosensitivity and improved benefit from standard-of-care chemotherapy. We systematically evaluated BRCA deficiency in TNBC using integrated DNA and RNA sequencing data and its association clinical outcome, exploring the potential role of tumor immune response. Patients and Methods: Whole-exome, DNA methylation, copy number variation, and RNA sequencing data from 102 stage I-III TNBCs were retrieved from The Cancer Genome Atlas (TCGA). Almost all patients received adjuvant taxane-anthracycline-cyclophosphamide (T-AC) chemotherapy and had >30 days of follow-up. The number of predicted neoantigens and an estimate of the level of immune cell activity for 77 of these tumors were previously published. Deleterious germline or somatic BRCA1/2 mutations were identified by majority voting on predictions of 5 variant scoring algorithms. Definition of BRCA1/2 deficiency (BRCA-D) included carrier of deleterious BRCA1/2 mutations or BRACA1/2 normal (BRCA-N) with wild type BRCA1/2 expression less than the maximum observed in mutation carriers. Normalized genomic mutation rate and mutant allele tumor heterogeneity (MATH) were computed as broad measures of genomic instability. Characteristics of BRCA-D vs N tumors were compared using the Wilcoxon rank test. Results: Twenty tumors (19.6%) had mutations in BRCA1, 6 (5.8%) in BRCA2, and 2 (1.9%) in both. Based on the expanded definition, 39 cases (38%) were characterized as BRCA1 deficient, 5 (4.9%) as BRCA2 deficient and 4 (3.9%) as deficient in both. BRCA-D tumors (47%) were associated with a significantly higher mutation rate (P=8x10-4) but had similar clonal heterogeneity (P=0.55) as BRCA-N tumors. BRCA-D tumors had excellent 4-year overall survival (100%) compared to 79.5% (95%CI: 66.6- 94.9) for BRCA-N tumors (log-rank P=0.02). BRCA-D tumors also presented a significantly higher number of predicted neoantigents (P=0.003), which resulted in increased level of immune cell activity. In contrast, low immunogenic TNBC tumors were underrepresented in BRCA-D (p=0.05) and showed potential signs of immunoediting (observed/expected number of predicted neoantigens < 1; p=0.07). Conclusions: Deleterious mutations in BRCA1/2 genes occur in 25% of TNBC tumors, but parallel quantification of wild-type BRCA1/2 expression identifies 47% of TNBC samples with double strand break DNA repair deficiency. These BRCA-D TNBC tumors are characterized by a significantly higher mutation rate and present a significantly greater number of neoantigens that result in increased immune cell activity. Our analysis suggested that enhanced immune activation could explain to a large extent the excellent clinical outcome in patients with BRCA-D tumors treated with standard-of-care T-AC chemotherapy. Citation Format: Jiang T, Safonov A, Bianchini G, Shi W, Wali VB, Pusztai L, Hatzis C. DNA repair deficiency enhances immune response and correlates with excellent clinical outcome in triple negative breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-07-01.

Triple-negative breast cancer (TNBC) is an aggressive subtype with no clinically proven biologically targeted treatment options. The molecular heterogeneity of TNBC and lack of high frequency driver mutations other than TP53 have hindered the development of new and effective therapies that significantly improve patient outcomes. miRNAs, global regulators of survival and proliferation pathways important in tumor development and maintenance, are becoming promising therapeutic agents. We performed miRNA-profiling studies in different TNBC subtypes to identify miRNAs that significantly contribute to disease progression. We found that miR-34a was lost in TNBC, specifically within mesenchymal and mesenchymal stem cell–like subtypes, whereas expression of miR-34a targets was significantly enriched. Furthermore, restoration of miR-34a in cell lines representing these subtypes inhibited proliferation and invasion, activated senescence, and promoted sensitivity to dasatinib by targeting the proto-oncogene c-SRC. Notably, SRC depletion in TNBC cell lines phenocopied the effects of miR-34a reintroduction, whereas SRC overexpression rescued the antitumorigenic properties mediated by miR-34a. miR-34a levels also increased when cells were treated with c-SRC inhibitors, suggesting a negative feedback exists between miR-34a and c-SRC. Moreover, miR-34a administration significantly delayed tumor growth of subcutaneously and orthotopically implanted tumors in nude mice, and was accompanied by c-SRC downregulation. Finally, we found that miR-34a and SRC levels were inversely correlated in human tumor specimens. Together, our results demonstrate that miR-34a exerts potent antitumorigenic effects in vitro and in vivo and suggests that miR-34a replacement therapy, which is currently being tested in human clinical trials, represents a promising therapeutic strategy for TNBC. Cancer Res; 76(4); 927–39. ©2015 AACR.

SUMMARY Multi-region sequencing is used to detect intratumor genetic heterogeneity (ITGH) in tumors. To assess whether genuine ITGH can be distinguished from sequencing artifacts, we performed whole-exome sequencing (WES) on three anatomically distinct regions of the same tumor with technical replicates to estimate technical noise. Somatic variants were detected with three different WES pipelines and subsequently validated by high-depth amplicon sequencing. The cancer-only pipeline was unreliable, with about 69% of the identified somatic variants being false positive. Even with matched normal DNA for which 82% of the somatic variants were detected reliably, only 36%–78% were found consistently in technical replicate pairs. Overall, 34%–80% of the discordant somatic variants, which could be interpreted as ITGH, were found to constitute technical noise. Excluding mutations affecting low-mappability regions or occurring in certain mutational contexts was found to reduce artifacts, yet detection of sub-clonal mutations by WES in the absence of orthogonal validation remains unreliable., Graphical Abstract, In Brief Shi et al. report that standard coverage whole-exome sequencing and bioinformatics pipelines cannot discriminate between genuine intratumor genetic heterogeneity and sequencing artifacts. Although aggressive minimum depth filtering would not improve the false detection rate of subclonal mutations, excluding mutations in low-mappability regions or in certain mutational contexts could help.

The functional redundancy of metabolic enzyme expression may present a new strategy for developing targeted therapies in cancer. To satisfy the increased metabolic demand required during neoplastic transformations and proliferation, cancer cells may rely on additional isoforms of a metabolic enzyme to satisfy the increased demand for metabolic precursors, which could subsequently render cancer cells more vulnerable to isoform-specific inhibitors. In this review, we provide a survey of common isoenzyme shifts that have been reported to be important in cancer metabolism and link those to metabolic pathways that currently have drugs in various stages of development. This phenomenon suggests a potentially new therapeutic strategy for the treatment of cancer by identifying shifts in the expression of metabolic isoenzymes between cancer and normal cells. We also delineate other putative metabolic isoenzymes that could be targets for novel targeted therapies for cancer. Changes in isoenzyme expression that occur during neoplastic transformations or in response to environmental pressure in cancer cells may result in isoenzyme diversity that may subsequently render cancer cells more vulnerable to isoform-specific inhibitors due to reliance on a single isoform to perform a vital enzymatic function.

Tissue handling can alter global gene expression potentially affecting the analytical performance of genomic signatures, but such effects have not been systematically evaluated.Tissue samples from 11 previously untreated breast tumors were minced and aliquots were either snap frozen or placed in RNAlater immediately or after 20, 40, 60, 120 or 180 min at room temperature. RNA was profiled on Affymetrix HG-U133A arrays. We used probe-set-wise hierarchical models to evaluate the effect of preservation method on transcript expression and linear mixed effects models to assess the effect of cold ischemic delay on the expression of individual probe sets. Gene set enrichment analysis identified pathways overrepresented in the affected transcripts. We combined the levels of 41 most sensitive transcripts to develop an index of ischemic stress.Concordance in global gene expression between the baseline and 40 min delay was higher for samples preserved in RNAlater (average concordance correlation coefficient CCC = 0.92 compared to 0.88 for snap frozen). Overall, 481 transcripts (3%) were significantly affected by the preservation method, most of them involved in processes important in cancer. Prolonged cold ischemic delay of up to 3 h induced marginal global gene expression changes (average CCC = 0.90 between baseline and 3 h delay). However 41 transcripts were significantly affected by cold ischemic delay. Among the induced transcripts were stress response genes, apoptotic response genes; among the downregulated were genes involved in metabolism, protein processing and cell cycle regulation. An index combining the expression levels of these genes was proportional to the cold ischemic delay.Prolonged cold ischemia induces significant transcriptional changes in a small subset of transcripts in the tissue. Furthermore, the expression level of about 3% of the transcripts is affected by the preservation method. These sensitive transcripts should not be included in genomic signatures for more reliable analytical performance.

Luminal breast tumors have been classified into A and B subgroups, with the luminal A being associated with a more favorable clinical outcome. Unfortunately, luminal A tumors do not have a universally good prognosis. We used transcriptomic analyses using public datasets to evaluate the differential expression between normal breast tissue and breast cancer, focusing on upregulated genes included in cell cycle function. Association of selected genes with relapse free survival (RFS) and overall survival (OS) was performed using the KM Plotter Online Tool (http://www.kmplot.com). Seventyseven genes were differentially expressed between normal and malignant breast tissue. Only five genes were associated with poor RFS and OS. The mitosis-related genes GTSE1, CDCA3, FAM83D and SMC4 were associated with poor outcome specifically in Luminal A tumors. The combination of FAM83D and CDCA3 for RFS and GTSE1 alone for OS showed the better prediction for clinical outcome. CDCA3 was amplified in 3.4% of the tumors, and FAM83D and SMC4 in 2.3% and 2.2%, respectively. In conclusion, we describe a set of genes that predict detrimental outcome in Luminal A tumors. These genes may have utility for stratification in trials of antimitotic agents or cytotoxic chemotherapy, or as candidates for direct target inhibition., Instituto de Salud Carlos III (PI16/01121), ACEPAIN; Diputación de Albacete and CRIS Cancer Foundation (to AO). BAE (Beca Ampliación de Estudios) to AO for his stay at Yale University. Ministry of Economy and Competitiveness of Spain (BFU2012–39151 and BFU2015-71371-R), the Instituto de Salud Carlos III through the Spanish Cancer Centers Network Program (RD12/0036/0003) and the CIBERONC, the scientific foundation of the AECC and the CRIS Foundation (to AP). The work carried out in the Spanish laboratories receives support from the European Community through the regional development funding program (FEDER).

Purpose: The 3-biomarker homologous recombination deficiency (HRD) assay measures the number of telomeric allelic imbalances, loss of heterozygosity, and large-scale state transitions in tumor DNA and combines these metrics into a single score that reflects DNA repair deficiency. The goal of this study is to assess the consistency of these HRD measures in different biopsies from distinct areas of the same cancer. Experimental Design: HRD scores, BRCA mutation status, and BRCA1 promoter methylation were assessed in 99 samples from 33 surgically resected, stage I–III breast cancers; each cancer was biopsied in three distinct areas. Homologous recombination repair (HR) deficiency was defined as either high HRD score (≥42) or tumor BRCA mutation. Results: Eighty-one biopsies from 32 cancers were analyzed. Tumor BRCA status was available for all samples, HRD scores for 70, and BRCA1 methylation values for 76 samples. The BRCA1/2 mutation and promoter methylation status and HR category showed perfect concordance across all biopsies from the same cancer. All tumors with BRCA1/2 mutations or promoter methylation had high HRD scores, as did 17% (4/24) of the BRCA1/2 wild-type and nonmethylated tumors. The HRD scores were also highly consistent between different biopsies from the same tumor with an intraclass correlation coefficient of 0.977, indicating that only 2.3% of the variance is attributed to within-tumor biopsy-to-biopsy variation. Conclusions: These results indicate that within-tumor spatial heterogeneity for HRD metrics and the technical noise in the assay are small and do not influence HRD scores and HR status. Clin Cancer Res; 23(5); 1193–9. ©2016 AACR.

Background: Progression from a normal cell state to cancer requires multiple genomic hits in key regulatory pathways. In the case of hereditary cancer syndromes, some of these hits occur in the germline, but additional somatic mutations are required for malignant transformation. We hypothesize that this paradigm could be extended to sporadic cancers as well. What somatic mutation function as a cancer driver event may be determined by the constellation of germline variants a person is born with. We propose that even rare, non-recurrent, high functional impact germline variants in genes involved in cancer-related pathways could influence the biological impact of somatic mutations in other cancer-related genes. The goal of the current analysis was to examine associations between pathway alterations caused by high functional impact germline variants or somatic mutations in the “hallmarks of cancer” pathways in breast cancer. Methods: We obtained germline DNA sequencing and copy number variation (CNV) data from the breast cancer TCGA cohort. After population clustering with the HapMap cohort, we selected a homogeneous group of 796 patients of Western European ancestry and downloaded the matching somatic mutations (SNVs and INDELs) that were available for 750 cases, that comprise the current study population. Germline CNVs were classified as recurrent or rare losses or gains. Potentially pathogenic germline variants (SNPs) were obtained from the PanCancer Altas project. All germline or somatic mutations were mapped at the gene level to the 50 Cancer Hallmarks pathway collection. We designated a pathway mutated if at least 1 gene had a germline or a somatic mutation. Complementarity between pathway alterations by germline and somatic events were evaluated using the Fisher exact test adjusted for multiple comparisons. Results: At the germline level, 2,057 genes were affected by CNVs (mean 30, range 3-151 genes/patient), and a total of 43 genes carried germline pathogenic SNPs that affected 13.8% of the patients. At the somatic level, we detected 40,881 high functional impact mutations (mean 54.3, range 1-3889 mutations/patient) in 13,080 genes (mean 50.8, range 1-3166 genes/patient). The 50 Cancer Hallmark pathways contained 4386 genes (mean 146.5, range 32-200 genes/pathway), and were mutated in the majority of the patients (85% germline, 93% somatic). Several pathways, such as HEME_METABOLISM, INTERFERON_ALPHA_RESPONSE, and KRAS_SIGNALING, were frequently affected by germline alterations, while the somatic mutations were most frequently involved in the COMPLEMENT, E2F_TARGET, and UV_RESPONSE_UP. Interaction analysis revealed co-occurrence between MYC_TARGETS_V1 (germline) and UV_RESPONSE_DN (somatic) or MTORC1_SINGALING (somatic) (p Conclusions: Our results highlight the importance of pathway-level analysis of germline alterations in breast cancer, which might help to understand the interrelationship between germline and somatic alterations in breast cancer. Citation Format: Qing T, Marczyk M, Wali V, Gunasekharan V, Patwardhan G, Pusztai L, Hatzis C. Pathway level complementarity of germline and somatic events in breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-03-01.