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Inflammatory breast cancer (IBC) is a difficult-to-treat disease with poor clinical outcomes due to high risk of metastasis and resistance to treatment. In breast cancer, CD44+CD24− cells possess stem cell-like features and contribute to disease progression, and we previously described a CD44+CD24−pSTAT3+ breast cancer cell subpopulation that is dependent on JAK2/STAT3 signaling. Here we report that CD44+CD24− cells are the most frequent cell type in IBC and are commonly pSTAT3+. Combination of JAK2/STAT3 inhibition with paclitaxel decreased IBC xenograft growth more than either agent alone. IBC cell lines resistant to paclitaxel and doxorubicin were developed and characterized to mimic therapeutic resistance in patients. Multi-omic profiling of parental and resistant cells revealed enrichment of genes associated with lineage identity and inflammation in chemotherapy-resistant derivatives. Integrated pSTAT3 chromatin immunoprecipitation sequencing and RNA sequencing (RNA-seq) analyses showed pSTAT3 regulates genes related to inflammation and epithelial-to-mesenchymal transition (EMT) in resistant cells, as well as PDE4A, a cAMP-specific phosphodiesterase. Metabolomic characterization identified elevated cAMP signaling and CREB as a candidate therapeutic target in IBC. Investigation of cellular dynamics and heterogeneity at the single cell level during chemotherapy and acquired resistance by CyTOF and single cell RNA-seq identified mechanisms of resistance including a shift from luminal to basal/mesenchymal cell states through selection for rare preexisting subpopulations or an acquired change. Finally, combination treatment with paclitaxel and JAK2/STAT3 inhibition prevented the emergence of the mesenchymal chemo-resistant subpopulation. These results provide mechanistic rational for combination of chemotherapy with inhibition of JAK2/STAT3 signaling as a more effective therapeutic strategy in IBC. Significance: Chemotherapy resistance in inflammatory breast cancer is driven by the JAK2/STAT3 pathway, in part via cAMP/PKA signaling and a cell state switch, which can be overcome using paclitaxel combined with JAK2 inhibitors.

In prostate cancer, the development of castration resistance is pivotal in progression to aggressive disease. However, understanding of the pathways involved remains incomplete. In this study, we performed a high-throughput genetic screen to identify kinases that enable tumor formation by androgen-dependent prostate epithelial (LHSR-AR) cells under androgen-deprived conditions. In addition to the identification of known mediators of castration resistance, which served to validate the screen, we identified a mitotic-related serine/threonine kinase, NEK6, as a mediator of androgen-independent tumor growth. NEK6 was overexpressed in a subset of human prostate cancers. Silencing NEK6 in castration-resistant cancer cells was sufficient to restore sensitivity to castration in a mouse xenograft model system. Tumors in which castration resistance was conferred by NEK6 were predominantly squamous in histology with no evidence of AR signaling. Gene expression profiling suggested that NEK6 overexpression stimulated cytoskeletal, differentiation, and immune signaling pathways and maintained gene expression patterns normally decreased by castration. Phosphoproteome profiling revealed the transcription factor FOXJ2 as a novel NEK6 substrate, with FOXJ2 phosphorylation associated with increased expression of newly identified NEK6 transcriptional targets. Overall, our studies establish NEK6 signaling as a central mechanism mediating castration-resistant prostate cancer. Cancer Res; 77(3); 753–65. ©2016 AACR.

Supplementary Table S4

Description of additional methods and procedures used in the study.

GO terms for NEK6 upregulated genes Day 5 after castration (filtered for >10 GeneHits).

Triple-negative breast cancer (TNBC) is a heterogeneous disease enriched for mutations in PTEN and dysregulation of innate immune signaling. Here, we demonstrate that Rab7, a recently identified substrate of PTEN phosphatase activity, is also a substrate of the innate immune signaling kinases TANK-binding kinase 1 (TBK1)/IκB kinase ϵ (IKKϵ) on the same serine-72 (S72) site. An unbiased search for novel TBK1/IKKϵ substrates using stable isotope labeling with amino acids in cell culture phosphoproteomic analysis identified Rab7-S72 as a top hit. PTEN-null TNBC cells expressing a phosphomimetic version of Rab7-S72 exhibited diffuse cytosolic Rab7 localization and enhanced innate immune signaling, in contrast to a kinase-resistant version, which localized to active puncta that promote lysosomal-mediated stimulator of interferon genes (STING) degradation. Thus, convergence of PTEN loss and TBK1/IKKϵ activation on Rab7-S72 phosphorylation limited STING turnover and increased downstream production of IRF3 targets including CXCL10, CCL5, and IFNβ. Consistent with this data, PTEN-null TNBC tumors expressed higher levels of STING, and PTEN-null TNBC cell lines were hyperresponsive to STING agonists. Together, these findings begin to uncover how innate immune signaling is dysregulated downstream of TBK1/IKKϵ in a subset of TNBCs and reveals previously unrecognized cross-talk with STING recycling that may have implications for STING agonism in the clinic.Significance:These findings identify Rab7 as a substrate for TBK1 for regulation of innate immune signaling, thereby providing important insight for strategies aimed at manipulating the immune response to enhance therapeutic efficacy in TNBC.

Inflammatory breast cancer (IBC) is a difficult-to-treat disease with poor clinical outcomes due to high risk of metastasis and resistance to treatment. In breast cancer, CD44+CD24− cells possess stem cell-like features and contribute to disease progression, and we previously described a CD44+CD24−pSTAT3+ breast cancer cell subpopulation that is dependent on JAK2/STAT3 signaling. Here we report that CD44+CD24− cells are the most frequent cell type in IBC and are commonly pSTAT3+. Combination of JAK2/STAT3 inhibition with paclitaxel decreased IBC xenograft growth more than either agent alone. IBC cell lines resistant to paclitaxel and doxorubicin were developed and characterized to mimic therapeutic resistance in patients. Multi-omic profiling of parental and resistant cells revealed enrichment of genes associated with lineage identity and inflammation in chemotherapy-resistant derivatives. Integrated pSTAT3 chromatin immunoprecipitation sequencing and RNA sequencing (RNA-seq) analyses showed pSTAT3 regulates genes related to inflammation and epithelial-to-mesenchymal transition (EMT) in resistant cells, as well as PDE4A, a cAMP-specific phosphodiesterase. Metabolomic characterization identified elevated cAMP signaling and CREB as a candidate therapeutic target in IBC. Investigation of cellular dynamics and heterogeneity at the single cell level during chemotherapy and acquired resistance by CyTOF and single cell RNA-seq identified mechanisms of resistance including a shift from luminal to basal/mesenchymal cell states through selection for rare preexisting subpopulations or an acquired change. Finally, combination treatment with paclitaxel and JAK2/STAT3 inhibition prevented the emergence of the mesenchymal chemo-resistant subpopulation. These results provide mechanistic rational for combination of chemotherapy with inhibition of JAK2/STAT3 signaling as a more effective therapeutic strategy in IBC.Significance:Chemotherapy resistance in inflammatory breast cancer is driven by the JAK2/STAT3 pathway, in part via cAMP/PKA signaling and a cell state switch, which can be overcome using paclitaxel combined with JAK2 inhibitors.

SF1: Unaltered immunoblots for Fig 4E. SF2: Unaltered immunoblots for Fig 4F. SF3: Unaltered immunoblots for Fig 4G. SF4: Additional phosphopeptide analysis for cell based and in vitro SILAC screen. SF5: Lower magnification (40X) of basal expression of V5 and Rab7 in mutants, to correspond with Fig 4A. SF6: EGFR and STING localization following TBK1/IKKE inhibition. SF7: Schematic for Rab7S72 role in regulating STING/TBK1/IKKE signaling in TNBCs. STableS3: Primer sequence for qRT-PCR. STableS4: List of antibodies. STableS5: PTEN/STING Staining of a TNBC TMA.

Supplementary Figures

Phosphopeptides from cell based screen

Legend for Supplemental Figures S1-S6.

Multiple challenges remain in Data-Independent Acquisition (DIA) data analysis, like confidently identifying peptides, defining integration boundaries, removing interferences, and controlling false discovery rates. In practice, a visual inspection of the signals is still required, which is impractical with large datasets. We developed Avant-garde as a tool to refine DIA (and PRM) data. Avant-garde uses a novel data-driven scoring strategy; signals are refined by learning from the data itself, using all measurements in all samples to achieve the best optimization. We evaluated Avant-garde’s performance with benchmarking DIA datasets. We showed that it can determine the quantitative suitability of a peptide peak, and reaches the same levels of selectivity, accuracy, and reproducibility as manual validation. Avant-garde is complementary to existing DIA analysis engines and aims to establish a strong foundation for subsequent analysis of quantitative MS data., Editorial summary: A computational tool, Avant-garde, automates refinement of data-independent acquisition mass spectrometry-based quantitative proteomics data.

Interactions between chromatin-associated proteins and the histone landscape play major roles in dictating genome topology and gene expression. Cancer-specific fusion oncoproteins, which display unique chromatin localization patterns, often lack classical DNA-binding domains, presenting challenges in identifying mechanisms governing their site-specific chromatin targeting and function. Here we identify a minimal region of the human SS18-SSX fusion oncoprotein (the hallmark driver of synovial sarcoma) that mediates a direct interaction between the mSWI/SNF complex and the nucleosome acidic patch. This binding results in altered mSWI/SNF composition and nucleosome engagement, driving cancer-specific mSWI/SNF complex targeting and gene expression. Furthermore, the C-terminal region of SSX confers preferential affinity to repressed, H2AK119Ub-marked nucleosomes, underlying the selective targeting to polycomb-marked genomic regions and synovial sarcoma–specific dependency on PRC1 function. Together, our results describe a functional interplay between a key nucleosome binding hub and a histone modification that underlies the disease-specific recruitment of a major chromatin remodeling complex., A combination of cell-based and biochemical approaches reveals how oncogenic fusion protein SS18-SSX directs BAF complexes to H2AK119Ub-modified nucleosomes to remodel chromatin at cancer-specific gene targets.

Vascular stiffness increases with age and independently predicts cardiovascular disease risk. Epigenetic changes, including histone modifications, accumulate with age but the global pattern has not been elucidated nor are the regulators known. Smooth muscle cell-mineralocorticoid receptor (SMC-MR) contributes to vascular stiffness in aging mice. Thus, we investigated the regulatory role of SMC-MR in vascular epigenetics and stiffness.Mass spectrometry-based proteomic profiling of all histone modifications completely distinguished 3 from 12-month-old mouse aortas. Histone-H3 lysine-27(H3K27) methylation(me) significantly decreased in aging vessels and this was attenuated in SMC-MR-KO littermates. Immunoblotting revealed less H3K27-specific methyltransferase EZH2 with age in MR-intact but not SMC-MR-KO vessels. These aging changes were examined in primary human aortic (HA)SMC from adult versus aged donors. MR, H3K27 acetylation(ac), and stiffness gene (CTGF, Integrin-α5) expression significantly increased, while H3K27me and EZH2 decreased, with age. MR inhibition reversed these aging changes in HASMC and the decline in stiffness genes was prevented by EZH2 blockade. Atomic force microscopy revealed that MR antagonism decreased intrinsic stiffness and the probability of fibronectin adhesion of aged HASMC. Conversely, aging induction in young HASMC with H2O2; increased MR, decreased EZH2, enriched H3K27ac and MR at stiffness gene promoters by ChIP, and increased stiffness gene expression. In 12-month-old mice, MR antagonism increased aortic EZH2 and H3K27 methylation, increased EZH2 recruitment and decreased H3K27ac at stiffness genes promoters, and prevented aging-induced vascular stiffness and fibrosis. Finally, in human aortic tissue, age positively correlated with MR and stiffness gene expression and negatively correlated with H3K27me3 while MR and EZH2 are negatively correlated.These data support a novel vascular aging model with rising MR in human SMC suppressing EZH2 expression thereby decreasing H3K27me, promoting MR recruitment and H3K27ac at stiffness gene promoters to induce vascular stiffness and suggests new targets for ameliorating aging-associated vascular disease.These findings provide a new epigenetic mechanism whereby rising MR in aging human SMC promotes vascular stiffness. Vascular stiffness contributes to common disorders of aging including hypertension, heart and kidney failure, and stroke, yet no therapies successfully target vascular stiffness. Drugs that inhibit MR are already approved and used in the elderly. In addition, drugs targeting histone-modifying enzymes, including EZH2, are being developed to treat cancer. Thus, these results provide preclinical support for drugs that could be immediately tested to treat aging-associated vascular stiffness and raise the potential for some cancer therapies to promote vascular stiffness.

Down syndrome (DS) is a genetic disorder driven by the triplication of chromosome 21 (T21) that is characterized by a wide-range of neurodevelopmental and physical disabilities. Transcriptomic analysis of tissue samples from individuals with DS has revealed that T21 induces a genome-wide transcriptional disruption. However, the consequences of T21 on the nuclear-architecture and its interplay with the transcriptome remain unknown. In this study, we find that unlike human induced pluripotent stem cells (iPSCs), iPSC-derived neural progenitor cells (NPCs) exhibit genome-wide “chromosomal introversion”, disruption of lamina-associated domains, and global chromatin-accessibility changes in response to T21, consistent with the transcriptional and nuclear-architecture changes characteristic of senescent cells. Treatment of T21-harboring NPCs with senolytic drugs alleviates the transcriptional, molecular and cellular dysfunctions associated with DS. Our findings provide a mechanistic link between T21 and global transcriptional disruption, and indicate that senescence-associated phenotypes may play a key role in the neurodevelopmental pathogenesis of DS.

Introduction: Vascular stiffness increases with age and independently predicts cardiovascular events but vascular fibrosis mechanisms are unclear. Epigenetic changes accumulate with age and contribute to aging pathology. We showed that aging-associated increase in vascular stiffness/fibrosis are mitigated by treating old mice with mineralocorticoid receptor (MR) antagonist (MRA) or by genetic deletion of MR in smooth muscle cells (SMC-MR-KO). Hypothesis: We hypothesized that SMC-MR regulates vascular fibrosis genes by modulating epigenetic histone modifications in the aging vasculature. Methods and Results: Global histone proteomic profiling revealed increased acetylation (ac) and decreased methylation (me) of histone H3 lysine 27 (H3K27) in old vs young mouse aorta that is attenuated by SMC-MR-KO. Similarly, RNA profiling shows downregulation of fibrotic genes (CTGF, MMP2 and Integrin-α5) with aging in mouse aortas from SMC-MR-KO mice. Mechanism was explored in primary low passage human aortic SMC (HASMC). Comparison of protein levels in HASMCs from old vs young people shows increased MR, decreased H3K27-specific methyltransferase EZH2, increased H3K27ac and increased fibrosis gene expression in aged HASMC. Treatment of young HASMC with H 2 O 2 (aging inductor) increased MR and decreased EZH2 in association with decreased H3K27me. These epigenetic changes were associated with increased H3K27ac and MR enrichment at the promoter of fibrosis genes by ChIP along with increased fibrosis gene expression. Conversely, treatment of aged HASMC with MRA increased EZH2 and H3K27me with decreased fibrosis gene expression. Finally, treatment of 12 month old mice with MR antagonist for 4 months or deletion of MR from SMC prevented aging induction of vascular stiffness by pulse wave velocity in association with decreased H3K27ac at promoters and decreased expression of fibrosis genes in aging aortas. Conclusion: These data support a model in which rising SMC-MR with aging contributes to vascular fibrosis via EZH2 reduction leading to decreased H3K27me and increased H3K27ac and MR recruitment to promote transcription of fibrotic genes. These findings suggest the therapeutic potential for MRAs for aging-associated vascular stiffening/fibrosis.

Triple-negative breast cancer (TNBC) is a subtype accounting for 20-30% all breast cancer cases and is a highly aggressive disease with inferior prognosis. The acquired resistance is a major obstacle for efficient therapy and discovery of novel clinically-actionable targets has become an urgent need. In this study, we carried out an in-depth functional characterization of histone demethylase KDM4C in TNBC and uncovered a novel mechanism underlying KDM4C-driven tumorigenesis. KDM4C is the second most frequently amplified histone demethylase in TNBC. Genetic knockdown or pharmacological inhibition of KDM4C in two amplified basal breast cancer cell lines, SUM149 and HCC1954, drastically suppressed primary tumor growth in vitro and in vivo. Transcriptomic analysis underlined oxidative phosphorylation impairment as functional consequences of KDM4C blockade. Surprisingly, integrating series of histone ChIP-seq and ATAC-seq showed that KDM4C suppression caused accessible chromatin remodeling without substantial changes of its canonical substrates H3K9me3 and H3K36me3. Rather KDM4C loss caused proteolytic cleavage at histone 3 N-terminus (Ala21 site) identified by histone mass spectrometry. Protease inhibitor array pointed out cathepsin L (CTSL) as the endopeptidase mediating this procedure. KDM4C blockade induced CTSL activation and promoted H3 tail clipping at around 30% CTSL binding sites, which was associated with restricted chromatin accessibility and transcriptomic reprogramming. Proteomic interactome profiling revealed that grainyhead like transcription factor 2 (GRHL2) tightly binds to CTSL. In addition, GRHL2 knockout induced nearly complete loss of CTSL chromatin binding, demonstrating its role as a recruiter of CTSL to the chromatin. KDM4C serves as either a direct or indirect suppressor for CTSL-mediated H3 cleavage. The latter one was largely mediated by redox imbalance. Metabolomic profiling showed that KDM4C inhibition strongly dampened intracellular glutathione (GSH) levels and hence produced more reactive oxygen species (ROS) and alleviated mitochondrial respiration. This procedure was grounded on the mechanism that KDM4C blockade decreased expression of GSH synthesis rate-limiting enzyme glutamate-cysteine ligase catalytic subunit (GCLC) via CTSL-mediated H3 tail clipping. Knockout of CTSL rescued KDM4C blockade-associated metabolic dysfunction, confirming KDM4C links redox homeostasis and chromatin remodeling. Finally, we found KDM4C-CTSL-GSH axis was associated with cisplatin resistance in TNBC patients. Co-targeting KDM4C and GSH production efficiently improved cisplatin response in TNBC cells. Our study provided detailed and unbiased evidence supporting a novel non-canonical role of KDM4C in preventing CTSL-mediated histone clipping and maintaining redox balance, opening up possibilities to improve chemotherapy through targeting this circus. Citation Format: Zheqi Li, Guillermo Peluffo, Laura E. Stevens, Xintao Qiu, Shawn B. Egri, Malvina Papanastasiou, Natalie Kingston, Clive S. D'Santos, Eva Papachristou, Kyle Evans, Ji-Heui Seo, Kendell Clement, Daniel Temko, Muhammad Ekram, Anton Simeonov, Stephen C. Kales, Ganesha Rai, Madhu Lal-Nag, David J. Maloney, Ajit Jadhav, Franziska Michor, Alex Meissner, Jason S. Carroll, Matthew L. Freedman, Henry W. Long, Jacob D. Jaffe, Kornelia Polyak. KDM4C histone demethylase connects redox balance to chromatin remodeling via histone H3 tail clipping. [abstract]. In: Proceedings of the AACR Special Conference: Cancer Epigenomics; 2022 Oct 6-8; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2022;82(23 Suppl_2):Abstract nr A018.

Triple-negative breast cancer (TNBC) is a heterogeneous disease enriched for mutations in PTEN and dysregulation of innate immune signaling. Here, we demonstrate that Rab7, a recently identified substrate of PTEN phosphatase activity, is also a substrate of the innate immune signaling kinases TANK-binding kinase 1 (TBK1)/IκB kinase ϵ (IKKϵ) on the same serine-72 (S72) site. An unbiased search for novel TBK1/IKKϵ substrates using stable isotope labeling with amino acids in cell culture phosphoproteomic analysis identified Rab7-S72 as a top hit. PTEN-null TNBC cells expressing a phosphomimetic version of Rab7-S72 exhibited diffuse cytosolic Rab7 localization and enhanced innate immune signaling, in contrast to a kinase-resistant version, which localized to active puncta that promote lysosomal-mediated stimulator of interferon genes (STING) degradation. Thus, convergence of PTEN loss and TBK1/IKKϵ activation on Rab7-S72 phosphorylation limited STING turnover and increased downstream production of IRF3 targets including CXCL10, CCL5, and IFNβ. Consistent with this data, PTEN-null TNBC tumors expressed higher levels of STING, and PTEN-null TNBC cell lines were hyperresponsive to STING agonists. Together, these findings begin to uncover how innate immune signaling is dysregulated downstream of TBK1/IKKϵ in a subset of TNBCs and reveals previously unrecognized cross-talk with STING recycling that may have implications for STING agonism in the clinic. Significance: These findings identify Rab7 as a substrate for TBK1 for regulation of innate immune signaling, thereby providing important insight for strategies aimed at manipulating the immune response to enhance therapeutic efficacy in TNBC.

Data-independent acquisition (DIA) is a powerful mass spectrometry method that promises higher coverage, reproducibility, and throughput than traditional quantitative proteomics approaches. However, the complexity of DIA data caused by fragmentation of co-isolating peptides presents significant challenges for confident assignment of identity and quantity, information that is essential for deriving meaningful biological insight from the data. To overcome this problem, we previously developed Avant-garde, a tool for automated signal refinement of DIA and other targeted mass spectrometry data. AvG is designed to work alongside existing tools for peptide detection to address the reliability and quantitative suitability of signals extracted for the identified peptides. While its use is straightforward and offers efficient refinement for small datasets, the execution of AvG for large DIA datasets is time-consuming, especially if run with limited computational resources. To overcome these limitations, we present here an improved, cloud-based implementation of the AvG algorithm deployed on Terra, a user-friendly cloud-based platform for large-scale data analysis and sharing, as an accessible and standardized resource to the wider community.

Summary We present a computational method to infer causal mechanisms in cell biology by analyzing changes in high-throughput proteomic profiles on the background of prior knowledge captured in biochemical reaction knowledge bases. The method mimics a biologist's traditional approach of explaining changes in data using prior knowledge but does this at the scale of hundreds of thousands of reactions. This is a specific example of how to automate scientific reasoning processes and illustrates the power of mapping from experimental data to prior knowledge via logic programming. The identified mechanisms can explain how experimental and physiological perturbations, propagating in a network of reactions, affect cellular responses and their phenotypic consequences. Causal pathway analysis is a powerful and flexible discovery tool for a wide range of cellular profiling data types and biological questions. The automated causation inference tool, as well as the source code, are freely available at http://causalpath.org., Graphical abstract, Highlights • CausalPath builds mechanistic models from proteomic profiles • It integrates biological pathway models with molecular measurements • It supports logical reasoning with post-translational modifications • A web server, free software, and a source code are available, The bigger picture Molecular profiling of biological organisms provides us with a great amount of information on cellular differences, but converting it to mechanistic insights is still a very challenging task. A prominent approach is to integrate new measurements with the mechanistic knowledge described in the scientific literature and build a model that is supported by both. Although this can be done in many ways, an adept approach will use the literature knowledge in detail and follow high standards of logical reasoning while integrating the known and the new. This article describes an approach that utilizes the details in human biological pathways to identify pairs of changes with a likely cause-effect relation within. The approach automatically converts comparative proteomic and other molecular profiles into hypotheses of differentially active mechanistic relations that explain how the profiles came to be., CausalPath integrates detailed biological pathways with proteomic and other molecular profiles to generate mechanistic models explaining how the observed changes are related. It is applicable to a wide range of contexts and a variety of experiment types. The method can be accessed at causalpath.org.

Epigenetic dysregulation is a defining feature of tumorigenesis that is implicated in immune escape1,2. Here, to identify factors that modulate the immune sensitivity of cancer cells, we performed in vivo CRISPR-Cas9 screens targeting 936 chromatin regulators in mouse tumour models treated with immune checkpoint blockade. We identified the H3K9 methyltransferase SETDB1 and other members of the HUSH and KAP1 complexes as mediators of immune escape3-5. We also found that amplification of SETDB1 (1q21.3) in human tumours is associated with immune exclusion and resistance to immune checkpoint blockade. SETDB1 represses broad domains, primarily within the open genome compartment. These domains are enriched for transposable elements (TEs) and immune clusters associated with segmental duplication events, a central mechanism of genome evolution6. SETDB1 loss derepresses latent TE-derived regulatory elements, immunostimulatory genes, and TE-encoded retroviral antigens in these regions, and triggers TE-specific cytotoxic T cell responses in vivo. Our study establishes SETDB1 as an epigenetic checkpoint that suppresses tumour-intrinsic immunogenicity, and thus represents a candidate target for immunotherapy.

A key question in genome research is whether biologically active proteins are restricted to the ∼20,000 canonical, well-annotated genes, or rather extend to the many non-canonical open reading frames (ORFs) predicted by genomic analyses. To address this, we experimentally interrogated 553 ORFs nominated in ribosome profiling datasets. Of these 553 ORFs, 57 (10%) induced a viability defect when the endogenous ORF was knocked out using CRISPR/Cas9 in 8 human cancer cell lines, 257 (46%) showed evidence of protein translation when ectopically expressed in HEK293T cells, and 401 (73%) induced gene expression changes measured by transcriptional profiling following ectopic expression across 4 cell types. CRISPR tiling and start codon mutagenesis indicated that the biological effects of these non-canonical ORFs required their translation as opposed to RNA-mediated effects. We selected one of these ORFs,G029442--renamedGREP1(Glycine-Rich Extracellular Protein-1)--for further characterization. We found thatGREP1encodes a secreted protein highly expressed in breast cancer, and its knock-out in 263 cancer cell lines showed preferential essentiality in breast cancer derived lines. Analysis of the secretome of GREP1-expressing cells showed increased abundance of the oncogenic cytokine GDF15, and GDF15 supplementation mitigated the growth inhibitory effect ofGREP1knock-out. Taken together, these experiments suggest that the non-canonical ORFeome is surprisingly rich in biologically active proteins and potential cancer therapeutic targets deserving of further study.

Mass spectrometry with data-independent acquisition (DIA) has emerged as a promising method to greatly improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory systematically measuring all peptide precursors within a biological sample. Despite the technical maturity of DIA, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms and alternative site localizations in phosphoproteomics data. We have developed Specter, an open-source software tool that uses linear algebra to deconvolute DIA mixture spectra directly in terms of a spectral library, circumventing the problems associated with typical fragment correlation-based approaches. We validate the sensitivity of Specter and its performance relative to other methods by means of several complex datasets, and show that Specter is able to successfully analyze cases involving highly similar peptides that are typically challenging for DIA analysis methods.

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.

We present a computational method to infer causal mechanisms in cell biology by analyzing changes in high-throughput proteomic profiles on the background of prior knowledge captured in biochemical reaction knowledge bases. The method mimics a biologist's approach of explaining changes in data using prior knowledge in their memory and in the literature, but at the scale of hundreds of thousands of reactions. The identified mechanisms can explain how experimental and physiological perturbations, propagating in a network of reactions, affect cellular responses and their phenotypic consequences. We first demonstrate the validity of the method on cell line perturbation experiments. In discovery mode we then identify 1) differential signaling within breast cancer and ovarian cancer, 2) subtype-specific signaling in these cancers, and 3) recurrent signaling relations across 32 cancer types. Causal pathway analysis is a powerful and flexible discovery tool for a wide range of cellular profiling data types and biological questions. The automated causation inference tool, as well as the source code, are freely available at causalpath.org.

The N-terminal regions of histone proteins (tails) are dynamic elements that protrude from the nucleosome and are involved in many aspects of chromatin organization. Their epigenetic role is well-established, and post-translational modifications (PTMs) present on these regions contribute to transcriptional regulation. While hydrogen/deuterium exchange mass spectrometry (HX-MS) is well-suited for the analysis of dynamic structures, it has seldom been employed to analyze histones due to the poor N-terminal coverage obtained using pepsin. Here, we test the applicability of a dual protease type XIII/pepsin digestion column to this class of proteins. We optimize online digestion conditions using the H4 monomer, and extend the method to the analysis of histones in monomeric states and nucleosome core particles (NCPs). We show that the dual protease column generates many short and overlapping N-terminal peptides. We evaluate our method by performing hydrogen exchange experiments of NCPs for different time points and present full coverage of the tails at excellent resolution. We further employ electron transfer dissociation (ETD) and showcase an unprecedented degree of overlap across multiple peptides that is several fold higher than previously reported methods. The method we report here may be readily applied to the HX-MS investigation of histone dynamics and to the footprints of histone binding proteins on nucleosomes.

Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR-Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines.

Oxygen sensing revisited The cellular response to hypoxia (oxygen deficiency) is a contributing factor in many human diseases. Previous studies examining the way in which hypoxia alters gene expression have focused on oxygen-sensing enzymes that regulate the activity of a transcription factor called hypoxia-inducible factor (see the Perspective by Gallipoli and Huntly). Chakraborty et al. and Batie et al. now show that hypoxia can also affect gene expression through direct effects on chromatin regulators. Certain histone demethylases, such as KDM6A and KDM5A, were found to be direct sensors of oxygen. In cell-culture models, hypoxia diminished the activity of these enzymes and caused changes in the expression of genes that govern cell fate. Science , this issue p. 1217 , p. 1222 ; see also p. 1148

Data-Independent Acquisition (DIA) is a technique that promises to comprehensively detect and quantify all peptides above an instrument’s limit of detection. Several software tools to analyze DIA data have been developed in recent years. However, several challenges still remain, like confidently identifying peptides, defining integration boundaries, dealing with interference for selected transitions, and scoring and filtering of peptide signals in order to control false discovery rates. In practice, a visual inspection of the signals is still required, which is impractical with large datasets. Avant-garde is a new tool to refine DIA (and PRM) by removing interfered transitions, adjusting integration boundaries and scoring peaks to control the FDR. Unlike other tools where MS runs are scored independently from each other, Avant-garde uses a novel data-driven scoring strategy. DIA signals are refined by learning from the data itself, using all measurements in all samples together to achieve the best optimization. We evaluated the performances of Avant-garde with a calibrated sample using spiked-in standards in a complex background, a phospho-enriched dataset (Abelin et al, 2016), and two complex hybrid proteome samples for benchmarking DIA software tools. The results clearly showed that Avant-garde is capable of improving the selectivity, accuracy, and reproducibility of the quantification results in very complex biological matrices. We have further shown that it can evaluate the suitability of a peak to be used for quantification reaching the same levels of selectivity, accuracy, and reproducibility obtained with manual validation.

Summary Members of the KDM5 histone H3 lysine 4 demethylase family are associated with therapeutic resistance, including endocrine resistance in breast cancer, but the underlying mechanism is poorly defined. Here we show that genetic deletion of KDM5A/B or inhibition of KDM5 activity increases sensitivity to anti-estrogens by modulating estrogen receptor (ER) signaling and by decreasing cellular transcriptomic heterogeneity. Higher KDM5B expression levels are associated with higher transcriptomic heterogeneity and poor prognosis in ER+ breast tumors. Single-cell RNA sequencing, cellular barcoding, and mathematical modeling demonstrate that endocrine resistance is due to selection for pre-existing genetically distinct cells, while KDM5 inhibitor resistance is acquired. Our findings highlight the importance of cellular phenotypic heterogeneity in therapeutic resistance and identify KDM5A/B as key regulators of this process.

Epigenetic alterations are defining features of many tumor types and have recently been implicated in tumor immunity. However, the epigenetic mechanisms that mediate immune sensitivity or resistance in cancer cells are poorly characterized. To systematically identify epigenetic regulators of immune evasion in cancer, we performed in vivo loss of function CRISPR screens against 936 chromatin regulator genes in syngeneic murine tumor models treated with immune checkpoint blockade. These screens identified SETDB1, an H3K9-methyltransferase, and associated members of the HUSH and KAP1 complexes as intrinsic mediators of immune evasion in cancer cells. We also found that amplification of SETDB1 (1q21) in certain human tumors is associated with immune exclusion and resistance to immune checkpoint blockade. Mechanistically, we find that SETDB1 targets broad domains, hundreds of kilobases in size, that are predominantly located within the open genome compartment “A” (i.e., euchromatin). These SETDB1 domains show strong enrichment for transposable elements (TEs) of the LTR family, and gene loci that arose through segmental duplication events, a key driver of mammalian genome evolution. Setdb1 KO derepresses latent regulatory elements at TEs within these regions and leads to the transcriptional up-regulation of nearby immune genes, including canonical stimulatory ligands of the NKG2D receptor. SETDB1 loss also triggers the activation of hundreds of TEs with the potential to encode retroviral proteins (Gag, Pol, Env), and promotes immune responses dependent on CD8+ T cells and tumor expression of MHC Class I. Our study establishes SETDB1 as an epigenetic checkpoint that represses intrinsic immunogenicity in cancer cells, and thus represents a novel target to enhance the efficacy and scope of immunotherapy. Citation Format: Jingyi Wu, Arvin Iracheta-Vellve, James Patti, Jeffrey Hsu, Thomas Davis, Deborah Dele-Oni, Peter Du, Jeffrey Ishizuka, Sarah Kim, Susan Klaeger, Nelson Knudsen, Brian Miller, Tung Nguyen, Emily Robitschek, Emily Schneider, Margaret Zimmer, Jacob Jaffe, John Doench, W. Nicholas Haining, Kathleen Yates, Robert Manguso, Bradley Bernstein, Gabriel K. Griffin. Epigenetic silencing by SETDB1 represses tumor-cell intrinsic immunogenicity [abstract]. In: Abstracts: AACR Virtual Special Conference: Tumor Immunology and Immunotherapy; 2020 Oct 19-20. Philadelphia (PA): AACR; Cancer Immunol Res 2021;9(2 Suppl):Abstract nr PO009.

Immunoaffinity enrichment of peptides coupled with analysis by stable isotope dilution multiple reaction mass spectrometry has been shown to have analytical performance and detection limits suitable for many biomarker verification studies and biological applications. Prior studies have shown that antipeptide antibodies can be multiplexed up to 50 in a single assay without significant loss of performance. Achieving higher multiplex levels is relevant to all studies involving precious biological material as this minimizes the amount of sample that must be consumed to measure a given set of analytes and reduces the assay cost per analyte. Here we developed automated methods employing the Agilent AssayMAP Bravo microchromatography platform and used these methods to characterize the performance of immunoaffinity enrichment of peptides up to multiplex levels of 172. Median capture efficiency for the target peptides remained high (88%) even at levels of 150-plex and declined to 70% at 172-plex compared to antibody performance observed at standard lower multiplex levels (n = 25). Subsequently, we developed and analytically characterized a multiplexed immuno-multiple reaction monitoring-mass spectrometry (immuno-MRM-MS) assay (n = 110) and applied it to measure candidate protein biomarkers of cardiovascular disease in plasma of patients undergoing planned myocardial infarction. The median lower limit of detection of all peptides was 71.5 amol/μL (nM), and the coefficient of variation (CV) was less than 15% at the lower limit of quantification. The results demonstrate that high multiplexed immuno-MRM-MS assays are readily achievable using the optimized sample processing and peptide capture methods described here.

Profiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical perturbagens. To develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 samples. The performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). The high-throughput, reduced-representation phosphoproteomics assay provides a platform for the comparison of perturbations across a range of biological conditions, suitable for profiling thousands of samples. We believe the assay will prove highly useful for classification of known and novel drug and genetic mechanisms through comparison of phosphoproteomic signatures.

Proteogenomics is a rapidly evolving field at the intersection of genomics, transcriptomics, and proteomics. Whole genome, exome, and RNA sequencing are well-established techniques that can provide information at the DNA and RNA level with excellent sequencing coverage and depth. Although tens of thousands of clinical samples have been sequenced thus far, data integration and interpretation still remain largely incomplete. Recent advances in proteomic technologies have enabled the accurate and almost complete characterization of the proteomes of many tissues and biological fluids. Integration of multiomics data for the accurate annotation and reciprocal refinement of genomic and proteomic models is essentially the goal of proteogenomics. This integrative approach has the potential to provide solid evidence for the translation of previously unknown transcripts. Those transcripts and the respective encoded proteins might be implicated in physiological or pathophysiological processes. Novel reported peptides can represent single amino acid variants, splice variants, gene fusions, RNA editing events, novel open reading frames, translated noncoding RNAs, and pseudogenes, among many others. Proteogenomic platforms can now be used to investigate which of these novel “events” gets translated at the protein level, thereby implicating them as candidate new druggable targets or as new diagnostic or prognostic biomarkers for a wide spectrum of diseases. The potential for such identifications is maximized when both sequencing and raw proteomic data originate from the very same sample under investigation. It is becoming clear that this “sample-specific” approach, and the use of matched customized search databases, is associated with lower false-positive and false-negative identification rates. However, like all areas of active research, proteogenomics in its current state is not free of drawbacks. Major limitations in the field are the sensitivity of the mass spectrometers, the increased false discovery rate for the novel peptide hits, and the inherent biophysical properties that render some peptides undetectable. In …

A Correction to this paper has been published: https://doi.org/10.1038/s41594-020-00540-y.

The brain is the foremost non-gonadal tissue for expression of non-coding RNAs of unclear function. Yet, whether such transcripts are truly non-coding or rather the source of non-canonical protein translation is unknown. Here, we used functional genomic screens to establish the cellular bioactivity of non-canonical proteins located in putative non-coding RNAs or untranslated regions of protein-coding genes. We experimentally interrogated 553 open reading frames (ORFs) identified by ribosome profiling for three major phenotypes: 257 (46%) demonstrated protein translation when ectopically expressed in HEK293T cells, 401 (73%) induced gene expression changes following ectopic expression across 4 cancer cell types, and 57 (10%) induced a viability defect when the endogenous ORF was knocked out using CRISPR/Cas9 in 8 human cancer cell lines. CRISPR tiling and start codon mutagenesis indicated that the biological impact of these non-canonical ORFs required their translation as opposed to RNA-mediated effects. We functionally characterized one of these ORFs, G029442—renamed GREP1 (Glycine-Rich Extracellular Protein-1)—as a cancer-implicated gene with high expression in multiple cancer types, such as gliomas. GREP1 knockout in >200 cancer cell lines reduced cell viability in multiple cancer types, including glioblastoma, in a cell-autonomous manner and produced cell cycle arrest via single-cell RNA sequencing. Analysis of the secretome of GREP1-expressing cells showed increased abundance of the oncogenic cytokine GDF15, and GDF15 supplementation mitigated the growth inhibitory effect of GREP1 knock-out. Taken together, these experiments suggest that the non-canonical ORFeome is surprisingly rich in biologically active proteins and potential cancer therapeutic targets deserving of further study.

BET bromodomain inhibitors (BBDIs) are candidate therapeutic agents for triple-negative breast cancer (TNBC) and other cancer types, but inherent and acquired resistance to BBDIs limits their potential clinical use. Using CRISPR and small-molecule inhibitor screens combined with comprehensive molecular profiling of BBDI response and resistance, we identified synthetic lethal interactions with BBDIs and genes that, when deleted, confer resistance. We observed synergy with regulators of cell cycle progression, YAP, AXL, and SRC signaling, and chemotherapeutic agents. We also uncovered functional similarities and differences among BRD2, BRD4, and BRD7. Although deletion of BRD2 enhances sensitivity to BBDIs, BRD7 loss leads to gain of TEAD-YAP chromatin binding and luminal features associated with BBDI resistance. Single-cell RNA-seq, ATAC-seq, and cellular barcoding analysis of BBDI responses in sensitive and resistant cell lines highlight significant heterogeneity among samples and demonstrate that BBDI resistance can be pre-existing or acquired.

The N-terminal regions (tails) of histone proteins are dynamic elements that protrude from the nucleosome and are involved in many aspects of chromatin organization. Their epigenetic role is well-established, and post-translational modifications present on these regions contribute to transcriptional regulation. Considering their biological significance, relatively few structural details have been established for histone tails, mainly because of their inherently disordered nature. Although hydrogen/deuterium exchange mass spectrometry (HX-MS) is well-suited for the analysis of dynamic structures, it has seldom been employed in this context, presumably because of the poor N-terminal coverage provided by pepsin. Inspired from histone-clipping events, we profiled the activity of cathepsin-L under HX-MS quench conditions and characterized its specificity employing the four core histones (H2A, H2B, H3 and H4). Cathepsin-L demonstrated cleavage patterns that were substrate- and pH-dependent. Cathepsin-L generated overlapping N-terminal peptides about 20 amino acids long for H2A, H3, and H4 proving its suitability for the analysis of histone tails dynamics. We developed a comprehensive HX-MS method in combination with pepsin and obtained full sequence coverage for all histones. We employed our method to analyze histones H3 and H4. We observe rapid deuterium exchange of the N-terminal tails and cooperative unfolding (EX1 kinetics) in the histone-fold domains of histone monomers in-solution. Overall, this novel strategy opens new avenues for investigating the dynamic properties of histones that are not apparent from the crystal structures, providing insights into the structural basis of the histone code.

Mammalian cells express multiple 2-oxoglutarate (OG)-dependent dioxygenases, including many chromatin regulators. The oxygen affinities, and hence oxygen sensing capabilities, of the 2-oxoglutarate (OG)-dependent dioxygenases reported to date vary widely. Hypoxia can affect chromatin, but whether this reflects a direct effect on chromatin-modifying dioxygenases, or indirect effects caused by the hypoxic-induction of the HIF transcription factor or the endogenous 2-OG competitor 2-hydroxyglutarate (2-HG), is unclear. Here we report that hypoxia induces a HIF- and 2-HG-independent histone modification signature consistent with KDM inactivation. We also show that the H3K27 histone demethylase KDM6A (also called UTX), but not its paralog KDM6B, is oxygen-sensitive. KDM6A loss, like hypoxia, prevented H3K27me3 erasure and blocked differentiation. Conversely, restoring H3K27me3 homeostasis in hypoxic cells reversed these effects. Therefore, oxygen directly affects chromatin regulators to control cell fate.One Sentence SummaryKDM6A demethylase activity is diminished under hypoxic conditions and causes changes in gene expression programs that govern cell fate.

Signaling pathways are orchestrated by post-translational modifications (PTMs) such as phosphorylation. However, pathway analysis of PTM data sets generated by mass spectrometry (MS)-based proteomics is typically performed at a gene-centric level because of the lack of appropriately curated PTM signature databases and bioinformatic tools that leverage PTM site-specific information. Here we present the first version of PTMsigDB, a database of modification site-specific signatures of perturbations, kinase activities and signaling pathways curated from more than 2,500 publications. We adapted the widely used single sample Gene Set Enrichment Analysis approach to utilize PTMsigDB, enabling PTM Signature Enrichment Analysis (PTM-SEA) of quantitative MS data. We used a well-characterized data set of epidermal growth factor (EGF)-perturbed cancer cells to evaluate our approach and demonstrated better representation of signaling events compared with gene-centric methods. We then applied PTM-SEA to analyze the phosphoproteomes of cancer cells treated with cell-cycle inhibitors and detected mechanism-of-action specific signatures of cell cycle kinases. We also applied our methods to analyze the phosphoproteomes of PI3K-inhibited human breast cancer cells and detected signatures of compounds inhibiting PI3K as well as targets downstream of PI3K (AKT, MAPK/ERK) covering a substantial fraction of the PI3K pathway. PTMsigDB and PTM-SEA can be freely accessed at https://github.com/broadinstitute/ssGSEA2.0.

Systemic metabolic alterations associated with increased consumption of saturated fat and obesity are linked with increased risk of prostate cancer progression and mortality, but the molecular underpinnings of this association are poorly understood. Here, we demonstrate in a murine prostate cancer model, that high-fat diet (HFD) enhances the MYC transcriptional program through metabolic alterations that favour histone H4K20 hypomethylation at the promoter regions of MYC regulated genes, leading to increased cellular proliferation and tumour burden. Saturated fat intake (SFI) is also associated with an enhanced MYC transcriptional signature in prostate cancer patients. The SFI-induced MYC signature independently predicts prostate cancer progression and death. Finally, switching from a high-fat to a low-fat diet, attenuates the MYC transcriptional program in mice. Our findings suggest that in primary prostate cancer, dietary SFI contributes to tumour progression by mimicking MYC over expression, setting the stage for therapeutic approaches involving changes to the diet.

Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to compare the signal-to-noise ratios of different networks and to identify the optimal network with which to interpret a particular genetic dataset. We present GeNets, a platform in which users can train a machine-learning model (Quack) to carry out these comparisons and execute, store, and share analyses of genetic and RNA-sequencing datasets.