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Abstract Most prostate cancers express the androgen receptor (AR), and tumor growth and progression are facilitated by exceptionally low levels of systemic or intratumorally produced androgens. Thus, absolute inhibition of the androgen signaling axis remains the goal of current therapeutic approaches to treat prostate cancer (PCa). Paradoxically, high dose androgens also exhibit considerable efficacy as a treatment modality in patients with late-stage metastatic PCa. Here we show that low levels of androgens, functioning through an AR monomer, facilitate a non-genomic activation of the mTOR signaling pathway to drive proliferation. Conversely, high dose androgens facilitate the formation of AR dimers/oligomers to suppress c-MYC expression, inhibit proliferation and drive a transcriptional program associated with a differentiated phenotype. These findings highlight the inherent liabilities in current approaches used to inhibit AR action in PCa and are instructive as to strategies that can be used to develop new therapeutics for this disease and other androgenopathies.

Abstract Enhancer of zeste homolog 2 (EZH2) is a histone methyltransferase and emerging therapeutic target that is overexpressed in most castration-resistant prostate cancers and implicated as a driver of disease progression and resistance to hormonal therapies. Here we define the lineage-specific action and differential activity of EZH2 in both prostate adenocarcinoma and neuroendocrine prostate cancer (NEPC) subtypes of advanced prostate cancer to better understand the role of EZH2 in modulating differentiation, lineage plasticity, and to identify mediators of response and resistance to EZH2 inhibitor therapy. Mechanistically, EZH2 modulates bivalent genes that results in upregulation of NEPC-associated transcriptional drivers (e.g., ASCL1) and neuronal gene programs in NEPC, and leads to forward differentiation after targeting EZH2 in NEPC. Subtype-specific downstream effects of EZH2 inhibition on cell cycle genes support the potential rationale for co-targeting cyclin/CDK to overcome resistance to EZH2 inhibition.

Abstract Cell state atlases constructed through single-cell RNA-seq and ATAC-seq analysis are powerful tools for analyzing the effects of genetic and drug treatment-induced perturbations on complex cell systems. Comparative analysis of such atlases can yield new insights into cell state and trajectory alterations. Perturbation experiments often require that single-cell assays be carried out in multiple batches, which can introduce technical distortions that confound the comparison of biological quantities between different batches. Here we propose CODAL, a variational autoencoder-based statistical model which uses a mutual information regularization technique to explicitly disentangle factors related to technical and biological effects. We demonstrate CODAL’s capacity for batch-confounded cell type discovery when applied to simulated datasets and embryonic development atlases with gene knockouts. CODAL improves the representation of RNA-seq and ATAC-seq modalities, yields interpretable modules of biological variation, and enables the generalization of other count-based generative models to multi-batched data.

Summary: Triple-negative breast cancer (TNBC) is a heterogeneous disease with limited treatment options. To characterize TNBC heterogeneity, we defined transcriptional, epigenetic, and metabolic subtypes and subtype-driving super-enhancers and transcription factors by combining functional and molecular profiling with computational analyses. Single-cell RNA sequencing revealed relative homogeneity of the major transcriptional subtypes (luminal, basal, and mesenchymal) within samples. We found that mesenchymal TNBCs share features with mesenchymal neuroblastoma and rhabdoid tumors and that the PRRX1 transcription factor is a key driver of these tumors. PRRX1 is sufficient for inducing mesenchymal features in basal but not in luminal TNBC cells via reprogramming super-enhancer landscapes, but it is not required for mesenchymal state maintenance or for cellular viability. Our comprehensive, large-scale, multiplatform, multiomics study of both experimental and clinical TNBC is an important resource for the scientific and clinical research communities and opens venues for future investigation.

Abstract Recent advances in single-cell RNA sequencing have shown heterogeneous cell types and gene expression states in the non-cancerous cells in tumors. The integration of multiple scRNA-seq datasets across tumors can indicate common cell types and states in the tumor microenvironment (TME). We develop a data driven framework, MetaTiME, to overcome the limitations in resolution and consistency that result from manual labelling using known gene markers. Using millions of TME single cells, MetaTiME learns meta-components that encode independent components of gene expression observed across cancer types. The meta-components are biologically interpretable as cell types, cell states, and signaling activities. By projecting onto the MetaTiME space, we provide a tool to annotate cell states and signature continuums for TME scRNA-seq data. Leveraging epigenetics data, MetaTiME reveals critical transcriptional regulators for the cell states. Overall, MetaTiME learns data-driven meta-components that depict cellular states and gene regulators for tumor immunity and cancer immunotherapy.

The role of MYC in transcriptional reprogramming in prostate cancer remains poorly characterized. Here, MYC overexpression antagonizes the canonical AR transcriptional program leading to prostate tumor initiation and progression by disrupting transcriptional pause release at AR-regulated genes.

Neuroendocrine carcinomas (NECs) arise from different anatomic sites, but have similar histological and clinical features. Here, the authors show that the epigenetic landscape of a range of NECs converges towards a common epigenetic state, while distinct subtypes occur within neuroendocrine prostate cancer contributing to intratumor heterogeneity in clinical samples.

The molecular processes that lead to neuroendocrine prostate cancer after treating prostate adenocarcinoma (PRAD) are not well understood. Here the authors show that regulation by FOXA1 and changes in the epigenomic profile drive the transition from PRAD to a neuroendocrine phenotype.

The androgen receptor (AR) is a master transcription factor that regulates prostate cancer (PC) development and progression. Inhibition of AR signaling by androgen deprivation is the first-line therapy with initial efficacy for advanced and recurrent PC. Paradoxically, supraphysiological levels of testosterone (SPT) also inhibit PC progression. However, as with any therapy, not all patients show a therapeutic benefit, and responses differ widely in magnitude and duration. In this study, we evaluated whether differences in the AR cistrome before treatment can distinguish between SPT-responding (R) and -nonresponding (NR) tumors. We provide the first preclinical evidence to our knowledge that SPT-R tumors exhibit a distinct AR cistrome when compared with SPT-NR tumors, indicating a differential biological role of the AR. We applied an integrated analysis of ChIP-Seq and RNA-Seq to the pretreatment tumors and identified an SPT-R signature that distinguishes R and NR tumors. Because transcriptomes of SPT-treated clinical specimens are not available, we interrogated available castration-resistant PC (CRPC) transcriptomes and showed that the SPT-R signature is associated with improved survival and has the potential to identify patients who would respond to SPT. These findings provide an opportunity to identify the subset of patients with CRPC who would benefit from SPT therapy.

Summary: BAG1 is a family of polypeptides with a conserved C-terminal BAG domain that functions as a nucleotide exchange factor for the molecular chaperone HSP70. BAG1 proteins also control several signaling processes including proteostasis, apoptosis, and transcription. The largest isoform, BAG1L, controls the activity of the androgen receptor (AR) and is upregulated in prostate cancer. Here, we show that BAG1L regulates AR dynamics in the nucleus and its ablation attenuates AR target gene expression especially those involved in oxidative stress and metabolism. We show that a small molecule, A4B17, that targets the BAG domain downregulates AR target genes similar to a complete BAG1L knockout and upregulates the expression of oxidative stress-induced genes involved in cell death. Furthermore, A4B17 outperformed the clinically approved antagonist enzalutamide in inhibiting cell proliferation and prostate tumor development in a mouse xenograft model. BAG1 inhibitors therefore offer unique opportunities for antagonizing AR action and prostate cancer growth.

Abstract Background Immune checkpoint blockade (ICB) therapy has improved patient survival in a variety of cancers, but only a minority of cancer patients respond. Multiple studies have sought to identify general biomarkers of ICB response, but elucidating the molecular and cellular drivers of resistance for individual tumors remains challenging. We sought to determine whether a tumor with defined genetic background exhibits a stereotypic or heterogeneous response to ICB treatment. Results We establish a unique mouse system that utilizes clonal tracing and mathematical modeling to monitor the growth of each cancer clone, as well as the bulk tumor, in response to ICB. We find that tumors derived from the same clonal populations showed heterogeneous ICB response and diverse response patterns. Primary response is associated with higher immune infiltration and leads to enrichment of pre-existing ICB-resistant cancer clones. We further identify several cancer cell-intrinsic gene expression signatures associated with ICB resistance, including increased interferon response genes and glucocorticoid response genes. These findings are supported by clinical data from ICB treatment cohorts. Conclusions Our study demonstrates diverse response patterns from the same ancestor cancer cells in response to ICB. This suggests the value of monitoring clonal constitution and tumor microenvironment over time to optimize ICB response and to design new combination therapies. Furthermore, as ICB response may enrich for cancer cell-intrinsic resistance signatures, this can affect interpretations of tumor RNA-seq data for response-signature association studies.

Abstract We present Model-based AnalysEs of Transcriptome and RegulOme (MAESTRO), a comprehensive open-source computational workflow ( http://github.com/liulab-dfci/MAESTRO ) for the integrative analyses of single-cell RNA-seq (scRNA-seq) and ATAC-seq (scATAC-seq) data from multiple platforms. MAESTRO provides functions for pre-processing, alignment, quality control, expression and chromatin accessibility quantification, clustering, differential analysis, and annotation. By modeling gene regulatory potential from chromatin accessibilities at the single-cell level, MAESTRO outperforms the existing methods for integrating the cell clusters between scRNA-seq and scATAC-seq. Furthermore, MAESTRO supports automatic cell-type annotation using predefined cell type marker genes and identifies driver regulators from differential scRNA-seq genes and scATAC-seq peaks.

Characterization of the distance over which TF binding influences gene expression is important for inferring target genes. Here the authors study this relationship using thousands of genomic data sets, finding two classes of TFs with distinct ranges of regulatory influence modulated by chromatin states of topologically associated domains.

Effective combination therapies to improve the efficacy of BET inhibitors are currently under investigation. Here, the authors examine palbociclib and paclitaxel as two promising candidates for combination therapies with BET inhibition in breast cancer and investigate the dynamics of resistance to these combinations through DNA barcoding and mathematical modelling.

Abstract We developed Lisa ( http://lisa.cistrome.org/ ) to predict the transcriptional regulators (TRs) of differentially expressed or co-expressed gene sets. Based on the input gene sets, Lisa first uses histone mark ChIP-seq and chromatin accessibility profiles to construct a chromatin model related to the regulation of these genes. Using TR ChIP-seq peaks or imputed TR binding sites, Lisa probes the chromatin models using in silico deletion to find the most relevant TRs. Applied to gene sets derived from targeted TF perturbation experiments, Lisa boosted the performance of imputed TR cistromes and outperformed alternative methods in identifying the perturbed TRs.

BRAF is a serine/threonine kinase that harbors activating mutations in ∼7% of human malignancies and ∼60% of melanomas. Despite initial clinical responses to BRAF inhibitors, patients frequently develop drug resistance. To identify candidate therapeutic targets for BRAF inhibitor resistant melanoma, we conduct CRISPR screens in melanoma cells harboring an activating BRAF mutation that had also acquired resistance to BRAF inhibitors. To investigate the mechanisms and pathways enabling resistance to BRAF inhibitors in melanomas, we integrate expression, ATAC-seq, and CRISPR screen data. We identify the JUN family transcription factors and the ETS family transcription factor ETV5 as key regulators of CDK6, which together enable resistance to BRAF inhibitors in melanoma cells. Our findings reveal genes contributing to resistance to a selective BRAF inhibitor PLX4720, providing new insights into gene regulation in BRAF inhibitor resistant melanoma cells.

Summary: Sustained treatment of estrogen receptor (ER)-positive breast cancer with ER-targeting drugs results in ER mutations and refractory unresponsive cancers. Androgen receptor (AR), which is expressed in 80%–95% of ER-positive breast cancers, could serve as an alternate therapeutic target. Although AR agonists were used in the past to treat breast cancer, their use is currently infrequent due to virilizing side effects. Discovery of tissue-selective AR modulators (SARMs) has renewed interest in using AR agonists to treat breast cancer. Using translational models, we show that AR agonist and SARM, but not antagonist, inhibit the proliferation and growth of ER-positive breast cancer cells, patient-derived tissues, and patient-derived xenografts (PDX). Ligand-activated AR inhibits wild-type and mutant ER activity by reprogramming the ER and FOXA1 cistrome and rendering tumor growth inhibition. These findings suggest that ligand-activated AR may function as a non-canonical inhibitor of ER and that AR agonists may offer a safe and effective treatment for ER-positive breast cancer. : Molecular Biology; Molecular Mechanism of Gene Regulation; Cancer Subject Areas: Molecular Biology, Molecular Mechanism of Gene Regulation, Cancer

Prostate cancer progression may be enhanced by a high-fat diet. Here the authors show that a diet high in saturated fats enhance the MYC-driven transcriptional program, a feature that independently predicts prostate cancer progression and death.

Abstract Background The androgen receptor (AR) is an emerging prognostic marker and therapeutic target in breast cancer. AR is expressed in 60–80% of breast cancers, with higher prevalence among estrogen receptor-positive (ER+) tumors. Androgen treatment inhibits ER signaling in ER+/AR+ breast cancer cell lines, and AR expression is associated with improved survival for this subtype in epidemiologic studies. However, whether AR expression modifies the efficacy of selective ER modulators or aromatase inhibitors for ER+ cancers remains unclear. Methods We evaluated the prognostic and predictive value of AR expression among 3021 postmenopausal ER+ breast cancer patients in the Breast International Group (BIG) trial 1–98. The BIG 1–98 study was a four-armed, double-blind, phase III randomized clinical trial that compared 5 years of tamoxifen or letrozole monotherapy, or sequences of 2 years and 3 years treatment with one drug and then the other. AR expression was measured by immunohistochemistry and the percentage of AR-positive nuclei was quantified. The association between AR expression and prognosis was evaluated using Cox proportional hazards models. Continuous AR-by-treatment interactions were assessed using Subpopulation Treatment Effect Pattern Plots (STEPP). Results Eighty-two percent of patients had AR+ (≥ 1%) tumors. Patients with AR+ cancers were more likely to have smaller, lower-grade tumors, with higher expression of ER and PR. AR expression was not associated with breast cancer-free interval (BCFI) (415 events) over a median 8.0 years of follow-up (p = 0.12, log-rank test). In multivariable-adjusted models, AR expression was not associated with BCFI (HR = 1.07, 95% CI 0.83–1.36, p = 0.60). The letrozole versus tamoxifen monotherapy treatment effect did not significantly differ for AR+ tumors (HR = 0.63, 95% CI 0.44–0.75, p = 0.003) and AR− tumors (HR = 0.39, 95% CI 0.21–0.72, p = 0.002) (p-heterogeneity = 0.16). STEPP analysis also suggested no heterogeneity of the treatment effect across the continuum of AR expression. Conclusions AR expression was not associated with prognosis, nor was there heterogeneity of the letrozole versus tamoxifen treatment effect by AR expression. These findings suggest that AR expression may not be an informative biomarker for the selection of adjuvant endocrine therapy for postmenopausal women with ER+ breast cancers. Trial registration ClinicalTrials.gov, NCT00004205, Registered 27 January 2003—Retrospectively registered, https://clinicaltrials.gov/ct2/show/study/NCT00004205.

Abstract Background RNA sequencing has become a ubiquitous technology used throughout life sciences as an effective method of measuring RNA abundance quantitatively in tissues and cells. The increase in use of RNA-seq technology has led to the continuous development of new tools for every step of analysis from alignment to downstream pathway analysis. However, effectively using these analysis tools in a scalable and reproducible way can be challenging, especially for non-experts. Results Using the workflow management system Snakemake we have developed a user friendly, fast, efficient, and comprehensive pipeline for RNA-seq analysis. VIPER (Visualization Pipeline for RNA-seq analysis) is an analysis workflow that combines some of the most popular tools to take RNA-seq analysis from raw sequencing data, through alignment and quality control, into downstream differential expression and pathway analysis. VIPER has been created in a modular fashion to allow for the rapid incorporation of new tools to expand the capabilities. This capacity has already been exploited to include very recently developed tools that explore immune infiltrate and T-cell CDR (Complementarity-Determining Regions) reconstruction abilities. The pipeline has been conveniently packaged such that minimal computational skills are required to download and install the dozens of software packages that VIPER uses. Conclusions VIPER is a comprehensive solution that performs most standard RNA-seq analyses quickly and effectively with a built-in capacity for customization and expansion.

While the multiple endocrine neoplasia type 1 (MEN1) gene functions as a tumor suppressor in a variety of cancer types, we explored its oncogenic role in breast tumorigenesis. The MEN1 gene product menin is involved in H3K4 trimethylation and co-activates transcription. We integrated ChIP-seq and RNA-seq data to identify menin target genes. Our analysis revealed that menin-dependent target gene promoters display looping to distal enhancers that are bound by menin, FOXA1 and GATA3. In this fashion, MEN1 co-regulates a proliferative breast cancer-specific gene expression program in ER+ cells. In primary mammary cells, MEN1 exerts an anti-proliferative function by regulating a distinct expression signature. Our findings clarify the cell-type-specific functions of MEN1 and inform the development of menin-directed treatments for breast cancer.

Summary: Notwithstanding the positive clinical impact of endocrine therapies in estrogen receptor-alpha (ERα)-positive breast cancer, de novo and acquired resistance limits the therapeutic lifespan of existing drugs. Taking the position that resistance is nearly inevitable, we undertook a study to identify and exploit targetable vulnerabilities that were manifest in endocrine therapy-resistant disease. Using cellular and mouse models of endocrine therapy-sensitive and endocrine therapy-resistant breast cancer, together with contemporary discovery platforms, we identified a targetable pathway that is composed of the transcription factors FOXA1 and GRHL2, a coregulated target gene, the membrane receptor LYPD3, and the LYPD3 ligand, AGR2. Inhibition of the activity of this pathway using blocking antibodies directed against LYPD3 or AGR2 inhibits the growth of endocrine therapy-resistant tumors in mice, providing the rationale for near-term clinical development of humanized antibodies directed against these proteins. : Cocce et al. show that FOXA1 contributes to disease pathogenesis by cooperating with GRHL2 in endocrine therapy-resistant breast cancer. LYPD3 is identified as an actionable downstream target of FOXA1/GRHL2, and humanized antibodies against LYDP3, or its ligand AGR2, demonstrate anti-tumor efficacy in animal models of endocrine therapy-resistant breast tumors. Keywords: FOXA1, tamoxifen, breast cancer, GRHL2, cistrome, enhancer, histone, chromatin, LYPD3

Post-translational histone H3 modifications regulate transcriptional competence. The mechanisms by which the epigenome is regulated in response to oncogenic signaling remain unclear. Here we show that H3K4me3 is increased in breast tumors driven by an activated PIK3CA allele and that inhibition of PI3K/AKT signaling reduces promoter-associated H3K4me3 in human breast cancer cells. We show that the H3K4 demethylase KDM5A is an AKT target and that phosphorylation of KDM5A regulates its nuclear localization and promoter occupancy. Supporting a role for KDM5A in mediating PI3K/AKT transcriptional effects, the decreased expression in response to AKT inhibition of a subset of cell-cycle genes associated with poor clinical outcome is blunted by KDM5A silencing. Our data identify a mechanism by which PI3K/AKT signaling modulates the cancer epigenome through controlling H3K4 methylation and suggest that KDM5A subcellular localization and genome occupancy may be pharmacodynamic markers of the activity of PI3K/AKT inhibitors currently in clinical development.

Analyses of data from high-throughput genomic technologies are challenging given large data dimensionality. Here, Liu and colleagues describe a method called MANCIE (Matrix Analysis and Normalization by Concordant Information Enhancement) that can conduct genomic data normalization and bias correction to detect biologically relevant information.

Long non-coding RNAs (lncRNA; >200 base pair nucleic acids with little protein-coding capacity) are emerging as potentially important regulators of oncogenesis. Here the authors show tumour suppressive lncRNA sponge function for the protein products of prostate cancer driver genes.

Acquired resistance to endocrine therapy remains a significant clinical burden for breast cancer patients. Somatic mutations in the ESR1 (estrogen receptor alpha (ERα)) gene ligand-binding domain (LBD) represent a recognized mechanism of acquired resistance. Antiestrogens with improved efficacy versus tamoxifen might overcome the resistant phenotype in ER +breast cancers. Bazedoxifene (BZA) is a potent antiestrogen that is clinically approved for use in hormone replacement therapies. We found that BZA possesses improved inhibitory potency against the Y537S and D538G ERα mutants compared to tamoxifen and has additional inhibitory activity in combination with the CDK4/6 inhibitor palbociclib. In addition, comprehensive biophysical and structural biology studies show BZA’s selective estrogen receptor degrading (SERD) properties that override the stabilizing effects of the Y537S and D538G ERα mutations.

Summary: Lysine-Specific Demethylase 1 (LSD1, KDM1A) functions as a transcriptional corepressor through demethylation of histone 3 lysine 4 (H3K4) but has a coactivator function on some genes through mechanisms that are unclear. We show that LSD1, interacting with CoREST, associates with and coactivates androgen receptor (AR) on a large fraction of androgen-stimulated genes. A subset of these AR/LSD1-associated enhancer sites have histone 3 threonine 6 phosphorylation (H3T6ph), and these sites are further enriched for androgen-stimulated genes. Significantly, despite its coactivator activity, LSD1 still mediates H3K4me2 demethylation at these androgen-stimulated enhancers. FOXA1 is also associated with LSD1 at AR-regulated enhancer sites, and a FOXA1 interaction with LSD1 enhances binding of both proteins at these sites. These findings show that LSD1 functions broadly as a regulator of AR function, that it maintains a transcriptional repression function at AR-regulated enhancers through H3K4 demethylation, and that it has a distinct AR-linked coactivator function mediated by demethylation of other substrates. : Cai et al. show that lysine-specific demethylase 1 (LSD1), although generally a transcriptional corepressor through H3K4 demethylation, functions broadly as a coactivator for androgen receptor and interacts with FOXA1 on androgen-stimulated genes. LSD1-mediated H3K4 demethylation persists at these sites, indicating a distinct coactivator function mediated by demethylation of other substrates.

Merkel cell carcinoma (MCC) frequently contains integrated copies of Merkel cell polyomavirus DNA that express a truncated form of Large T antigen (LT) and an intact Small T antigen (ST). While LT binds RB and inactivates its tumor suppressor function, it is less clear how ST contributes to MCC tumorigenesis. Here we show that ST binds specifically to the MYC homolog MYCL (L-MYC) and recruits it to the 15-component EP400 histone acetyltransferase and chromatin remodeling complex. We performed a large-scale immunoprecipitation for ST and identified co-precipitating proteins by mass spectrometry. In addition to protein phosphatase 2A (PP2A) subunits, we identified MYCL and its heterodimeric partner MAX plus the EP400 complex. Immunoprecipitation for MAX and EP400 complex components confirmed their association with ST. We determined that the ST-MYCL-EP400 complex binds together to specific gene promoters and activates their expression by integrating chromatin immunoprecipitation with sequencing (ChIP-seq) and RNA-seq. MYCL and EP400 were required for maintenance of cell viability and cooperated with ST to promote gene expression in MCC cell lines. A genome-wide CRISPR-Cas9 screen confirmed the requirement for MYCL and EP400 in MCPyV-positive MCC cell lines. We demonstrate that ST can activate gene expression in a EP400 and MYCL dependent manner and this activity contributes to cellular transformation and generation of induced pluripotent stem cells.

Targeting the activation function-1 (AF-1) domain located in the N-terminus of the androgen receptor (AR) is an attractive therapeutic alternative to the current approaches to inhibit AR action in prostate cancer (PCa). Here we show that the AR AF-1 is bound by the cochaperone Bag-1L. Mutations in the AR interaction domain or loss of Bag-1L abrogate AR signaling and reduce PCa growth. Clinically, Bag-1L protein levels increase with progression to castration-resistant PCa (CRPC) and high levels of Bag-1L in primary PCa associate with a reduced clinical benefit from abiraterone when these tumors progress. Intriguingly, residues in Bag-1L important for its interaction with the AR AF-1 are within a potentially druggable pocket, implicating Bag-1L as a potential therapeutic target in PCa.

The TMPRSS2:ERG gene fusion is common in androgen receptor (AR) positive prostate cancers, yet its function remains poorly understood. From a screen for functionally relevant ERG interactors, we identify the arginine methyltransferase PRMT5. ERG recruits PRMT5 to AR-target genes, where PRMT5 methylates AR on arginine 761. This attenuates AR recruitment and transcription of genes expressed in differentiated prostate epithelium. The AR-inhibitory function of PRMT5 is restricted to TMPRSS2:ERG-positive prostate cancer cells. Mutation of this methylation site on AR results in a transcriptionally hyperactive AR, suggesting that the proliferative effects of ERG and PRMT5 are mediated through attenuating AR’s ability to induce genes normally involved in lineage differentiation. This provides a rationale for targeting PRMT5 in TMPRSS2:ERG positive prostate cancers. Moreover, methylation of AR at arginine 761 highlights a mechanism for how the ERG oncogene may coax AR towards inducing proliferation versus differentiation.

Mutations in a hormone receptor can lead to therapeutic resistance by making it less able to bind and respond to hormone blocking drugs and by making it active, even when the hormome is not present.

Advancements in molecular biology have unveiled multiple breast cancer promoting pathways and potential therapeutic targets. Large randomized clinical trials remain the ultimate means of validating therapeutic efficacy, but they require large cohorts of patients and are lengthy and costly. A useful approach is to conduct a window of opportunity study in which patients are exposed to a drug pre-surgically during the interval between the core needle biopsy and the definitive surgery. These are non-therapeutic studies and the end point is not clinical or pathological response but rather evaluation of molecular changes in the tumor specimens that can predict response. However, since the end points of the non-therapeutic studies are biologic, it is critical to first define the biologic changes that occur in the absence of treatment. In this study, we compared the molecular profiles of breast cancer tumors at the time of the diagnostic biopsy versus the definitive surgery in the absence of any intervention using the Nanostring nCounter platform. We found that while the majority of the transcripts did not vary between the two biopsies, there was evidence of activation of immune related genes in response to the first biopsy and further investigations of the immune changes after a biopsy in early breast cancer seem warranted.

Motivation: The chromatin profile measured by ATAC-seq, ChIP-seq, or DNase-seq experiments can identify genomic regions critical in regulating gene expression and provide insights on biological processes such as diseases and development. However, quality control and processing chromatin profiling data involves many steps, and different bioinformatics tools are used at each step. It can be challenging to manage the analysis. Results: We developed a Snakemake pipeline called CHIPS (CHromatin enrIchment ProcesSor) to streamline the processing of ChIP-seq, ATAC-seq, and DNase-seq data. The pipeline supports single- and paired-end data and is flexible to start with FASTQ or BAM files. It includes basic steps such as read trimming, mapping, and peak calling. In addition, it calculates quality control metrics such as contamination profiles, polymerase chain reaction bottleneck coefficient, the fraction of reads in peaks, percentage of peaks overlapping with the union of public DNaseI hypersensitivity sites, and conservation profile of the peaks. For downstream analysis, it carries out peak annotations, motif finding, and regulatory potential calculation for all genes. The pipeline ensures that the processing is robust and reproducible. Availability: CHIPS is available at https://github.com/liulab-dfci/CHIPS.