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In future mass casualty medical management scenarios involving radiation injury, medical diagnostics to both identify those who have been exposed and the level of exposure will be needed. As almost all exposures in the field are heterogeneous, determination of degree of exposure and which vital organs have been exposed will be essential for effective medical management. In the current study we sought to characterize novel proteomic biomarkers of radiation exposure and develop exposure and dose prediction algorithms for a variety of exposure paradigms to include uniform total-body exposures, and organ-specific partial-body exposures to only the brain, only the gut and only the lung. C57BL6 female mice received a single total-body irradiation (TBI) of 2, 4 or 8 Gy, 2 and 8 Gy for lung or gut exposures, and 2, 8 or 16 Gy for exposure to only the brain. Plasma was then screened using the SomaScan v4.1 assay for ∼7,000 protein analytes. A subset panel of protein biomarkers demonstrating significant (FDR<0.05 and|logFC|>0.2) changes in expression after radiation exposure was characterized. All proteins were used for feature selection to build 7 different predictive models of radiation exposure using different sample cohort combinations. These models were structured according to practical field considerations to differentiate level of exposure, in addition to identification of organ-specific exposures. Each model algorithm built using a unique sample cohort was validated with a training set of samples and tested with a separate new sample series. The overall predictive accuracy for all models was 100% at the model training level. When tested with reserved samples Model 1 which compared an exposure group inclusive of all TBI and organ-specific partial-body exposures in the study vs. control, and Model 2 which differentiated between control, TBI and partials (all organ-specific partial-body exposures) the resulting prediction accuracy was 92.3% and 95.4%, respectively. For identification of organ-specific exposures vs. control, Model 3 (only brain), Model 4 (only gut) and Model 5 (only lung) were developed with predictive accuracies of 78.3%, 88.9% and 94.4%, respectively. Finally, for Models 6 and 7, which differentiated between TBI and separate organ-specific partial-body cohorts, the testing predictive accuracy was 83.1% and 92.3%, respectively. These models represent novel predictive panels of radiation responsive proteomic biomarkers and illustrate the feasibility of development of biodosimetry algorithms with utility for simultaneous classification of total-body, partial-body and organ-specific radiation exposures. [ABSTRACT FROM AUTHOR]

Bromodomain 4 (BRD4), a key regulator with pleiotropic functions, plays crucial roles in cancers and cellular stress responses. It exhibits dual functionality: chromatin-bound BRD4 regulates remodeling through its histone acetyltransferase (HAT) activity, while promoter-associated BRD4 regulates transcription through its kinase activity. Notably, chromatin-bound BRD4 lacks kinase activity, and RNA polymerase II (RNA Pol II)-bound BRD4 exhibits no HAT activity. This study unveils one mechanism underlying BRD4's functional switch. In response to diverse stimuli, c-Jun N-terminal kinase (JNK)-mediated phosphorylation of human BRD4 at Thr1186 and Thr1212 triggers its transient release from chromatin, disrupting its HAT activity and potentiating its kinase activity. Released BRD4 directly interacts with and phosphorylates RNA Pol II, PTEFb, and c-Myc, thereby promoting transcription of target genes involved in immune and inflammatory responses. JNK-mediated BRD4 functional switching induces CD8 expression in thymocytes and epithelial-to-mesenchymal transition (EMT) in prostate cancer cells. These findings elucidate the mechanism by which BRD4 transitions from a chromatin regulator to a transcriptional activator., Competing Interests: Declaration of interests The authors declare no competing interests., (Published by Elsevier Inc.)

Immuno-oncology has transformed the treatment of cancer, with several immunotherapies becoming the standard treatment across histologies. Despite these advancements, the majority of patients do not experience durable clinical benefits, highlighting the imperative for ongoing advancement in immuno-oncology. Computational immuno-oncology emerges as a forefront discipline that draws on biomedical data science and intersects with oncology, immunology, and clinical research, with the overarching goal to accelerate the development of effective and safe immuno-oncology treatments from the laboratory to the clinic. In this review, we outline 10 critical challenges and opportunities in computational immuno-oncology, emphasizing the importance of robust computational strategies and interdisciplinary collaborations amid the constantly evolving interplay between clinical needs and technological innovation., Competing Interests: Competing interests: RB declares PCT/US15/612657 (Cancer Immunotherapy), PCT/US18/36052 (Microbiome Biomarkers for Anti-PD-1/PD-L1 Responsiveness: Diagnostic, Prognostic and Therapeutic Uses Thereof), PCT/US63/055227 (Methods and Compositions for Treating Autoimmune and Allergic Disorders). AM is an equity holder in Picture Health, Elucid Bioimaging, and Inspirata. Currently, he serves on the advisory board of Picture Health, and SimBioSys. He currently consults for Takeda; He also has sponsored research agreements with AstraZeneca and Bristol Myers-Squibb; his technology has been licensed to Picture Health and Elucid Bioimaging; he is also involved in two different R01 grants with Inspirata; he also serves as a member for the Frederick National Laboratory Advisory Committee.VDJ has performed consulting for VincerX Pharmaceuticals, Providence St. John, Los Angeles; she is a founder of Bioinformatica. JSB-S, EK, DM are full time, paid employees of NCI/NIH. EJF is on the Scientific Advisory Board of Resistance Bio, a consultant for Mestag and Merck, and receives research funding from AbbVie. SG reports current and past research funding from Regeneron Pharmaceuticals, Boehringer Ingelheim, BMS (Celgene), Genentech, EMD Serono, Pfizer, and Takeda. ER is a co-founder of MedAware, Metabomed and Pangea Biomed (divested), and an unpaid member of Pangea Biomed’s and GSK Oncology scientific advisory boards. DVV is a co-founder and chief scientist of Barrier Biosciences and holds equity in the company. NV is on the Consulting/Advisory Boards of Sanofi/Genzyme (2022), Oncocyte (2021), Eli Lilly (2021), Regeneron (2022), Amgen (2023), Xencor (2023), AstraZeneca (2023), Tempus (2023), Pfizer (2024), Summit Therapeutics (2024), OncoHost (2024); she reports travel reimbursement from Regeneron; research grants from Oncocyte (2022–), Circulogene and Mirati, funding from Circulogene, and honoraria from Nebraska Oncology Society, Scienomics Group, Grace, OncLive and OMNI-Oncology. EMVA reports personal fees from Tango Therapeutics, Genome Medical, Genomic Life, Monte Rosa Therapeutics, Manifold Bio, Enara Bio, Riva Therapeutics, Foaley & Hoag, and Serinus Bio, grants and personal fees from Novartis Institute for Biomedical Research, and grants from BMS, Janssen, and Sanofi outside the submitted work; in addition, EMVA has a patent for institutional patents filed on chromatin mutations and immunotherapy response and methods for clinical interpretation pending., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Cowpea mosaic virus (CPMV) is a plant virus that is currently being developed for intratumoral immunotherapy. CPMV relieves the immune system from tumor-induced immunosuppression; reprograms the tumor microenvironment to an activated state whereby the treated and distant tumors are recognized and eradicated. Toward translational studies, we investigated the safety of CPMV, specifically addressing whether pathogenicity would be induced in mammalian cells. We show that murine macrophage immune cells recognize CPMV; however, there is no indication of de novo viral protein synthesis or RNA replication. Furthermore, we show that CPMV does not induce hemolysis, platelet aggregation and plasma coagulation amongst other assays in human blood and immune cells. Taken together, we anticipate that these results will reinforce the development of CPMV as an immunotherapeutic platform., (© 2024. The Author(s).)

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is a potential cancer therapeutic that induces apoptosis in cancer cells while sparing the non-malignant cells in preclinical models. However, its efficacy in clinical trials has been limited, suggesting unknown modulatory mechanisms responsible for the lack of TRAIL activity in patients. Here, we hypothesized that TRAIL treatment elicits transcriptional changes in triple negative breast cancer (TNBC) cells that alter the immune milieu. To test this, we performed an RNAseq analysis of MDA-MB-231 cells treated with TRAIL, followed by validation in additional TNBC cell lines. TRAIL significantly induces expression of multiple cytokines such as CXCLs 1, 2, 3, 8,11 and IL-6, which are known to modify neutrophil function. Mechanistically, the induction of these cytokines was predominantly mediated by death receptor 5, caspase 8 (but not caspase 8 enzymatic activity), and the non-canonical NFKB2 pathway. The cytokines produced by the TRAIL-treated TNBC cells enhanced chemotaxis of healthy human donor isolated neutrophils. In vivo , TRAIL treated TNBC murine xenograft tumors showed activation of the NFKB2 pathway, elevated production of CXCLs and IL-6, and increased neutrophil recruitment into the tumors. Moreover, donor isolated neutrophils preincubated in supernatants from TRAIL-treated TNBC cells exhibited impaired cytotoxic effect against TNBC cells. Transcriptomic analysis of neutrophils incubated with either TRAIL alone or supernatant of TRAIL-treated TNBC cells revealed increased expression of inflammatory cytokines, immune modulatory genes, immune checkpoint genes, and genes implicated in delayed neutrophil apoptosis. Functional studies with these neutrophils confirmed their suppressive effect on T cell proliferation and an increase in Treg suppressive phenotype. Collectively, our study demonstrates a novel role of TRAIL-induced NFKB2-dependent cytokine production that promotes neutrophil chemotaxis and immune suppression.

Extracellular matrix remodeling is a hallmark of tissue development, homeostasis, and disease. The processes that mediate remodeling, and the consequences of such, are the topic of extensive focus in biomedical research. Cell culture methods represent a crucial tool utilized by those interested in matrisome function, the easiest of which are implemented with immortalized/cancer cell lines. These cell lines often form the foundations of a research proposal, or serve as vehicles of validation for other model systems. For these reasons, it is important to understand the complement of matrisome genes that are expressed when identifying appropriate cell culture models for hypothesis testing. To this end, we harvested bulk RNA sequencing data from the Cancer Cell Line Encyclopedia (CCLE) to assess matrisome gene expression in 1019 human cell lines. Our examination reveals that a large proportion of the matrisome is poorly represented in human cancer cell lines, with approximately 10% not expressed above threshold in any of the cell lines assayed. Conversely, we identify clusters of essential/common matrisome genes that are abundantly expressed in cell lines. To validate these observations against tissue data, we compared our findings with bulk RNA sequencing data from the Genotype-Tissue Expression (GTEx) portal and The Cancer Genome Atlas (TCGA) program. This comparison demonstrates general agreement between the "essential/common" and "dark/uncommon" matrisome across the three datasets, albeit with discordance observed in 59 matrisome genes between cell lines and tissues. Notably, all of the discordant genes are essential/common in tissues yet minimally expressed in cell lines, underscoring critical considerations for matrix biology researchers employing immortalized cell lines for their investigations., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

More than ever, scientific progress in cancer research hinges on our ability to combine datasets and extract meaningful interpretations to better understand diseases and ultimately inform the development of better treatments and diagnostic tools. To enable the successful sharing and use of big data, the NCI developed the Cancer Research Data Commons (CRDC), providing access to a large, comprehensive, and expanding collection of cancer data. The CRDC is a cloud-based data science infrastructure that eliminates the need for researchers to download and store large-scale datasets by allowing them to perform analysis where data reside. Over the past 10 years, the CRDC has made significant progress in providing access to data and tools along with training and outreach to support the cancer research community. In this review, we provide an overview of the history and the impact of the CRDC to date, lessons learned, and future plans to further promote data sharing, accessibility, interoperability, and reuse. See related articles by Brady et al., p. 1384, Wang et al., p. 1388, and Pot et al., p. 1396., (©2024 The Authors; Published by the American Association for Cancer Research.)

We performed a deep proteogenomic analysis of bulk tumor and laser microdissection enriched tumor cell populations from high-grade serous ovarian cancer (HGSOC) tissue specimens spanning a broad spectrum of purity. We identified patients with longer progression-free survival had increased immune-related signatures and validated proteins correlating with tumor-infiltrating lymphocytes in 65 tumors from an independent cohort of HGSOC patients, as well as with overall survival in an additional 126 HGSOC patient cohort. We identified that homologous recombination deficient (HRD) tumors are enriched in pathways associated with metabolism and oxidative phosphorylation that we validated in independent patient cohorts. We further identified that polycomb complex protein BMI-1 is elevated in HR proficient (HRP) tumors, that elevated BMI-1 correlates with poor overall survival in HRP but not HRD HGSOC patients, and that HRP HGSOC cells are uniquely sensitive to BMI-1 inhibition., (© 2024. The Author(s).)

Previous studies of the murine Ly49 and human KIR gene clusters implicated competing sense and antisense promoters in the control of variegated gene expression. In the current study, an examination of transcription factor genes defines an abundance of convergent and divergent sense/antisense promoter pairs, suggesting that competing promoters may control cell fate determination. Differentiation of CD34 + hematopoietic progenitors in vitro shows that cells with GATA1 antisense transcription have enhanced GATA2 transcription and a mast cell phenotype, whereas cells with GATA2 antisense transcription have increased GATA1 transcripts and an erythroblast phenotype. Detailed analyses of the AHR and RORC genes demonstrate the ability of competing promoters to act as binary switches and the association of antisense transcription with an immature/progenitor cell phenotype. These data indicate that alternative cell fates generated by promoter competition in lineage-determining transcription factors contribute to the programming of cell differentiation., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023. Published by Elsevier Inc.)

Background: Glioblastomas (GBM) are rapidly progressive, nearly uniformly fatal brain tumors. Proteomic analysis represents an opportunity for noninvasive GBM classification and biological understanding of treatment response., Purpose: We analyzed differential proteomic expression pre vs. post completion of concurrent chemoirradiation (CRT) in patient serum samples to explore proteomic alterations and classify GBM by integrating clinical and proteomic parameters., Materials and Methods: 82 patients with GBM were clinically annotated and serum samples obtained pre- and post-CRT. Serum samples were then screened using the aptamer-based SOMAScan® proteomic assay. Significant traits from uni- and multivariate Cox models for overall survival (OS) were designated independent prognostic factors and principal component analysis (PCA) was carried out. Differential expression of protein signals was calculated using paired t-tests, with KOBAS used to identify associated KEGG pathways. GSEA pre-ranked analysis was employed on the overall list of differentially expressed proteins (DEPs) against the MSigDB Hallmark, GO Biological Process, and Reactome databases with weighted gene correlation network analysis (WGCNA) and Enrichr used to validate pathway hits internally., Results: 3 clinical clusters of patients with differential survival were identified. 389 significantly DEPs pre vs. post-treatment were identified, including 284 upregulated and 105 downregulated, representing several pathways relevant to cancer metabolism and progression. The lowest survival group (median OS 13.2 months) was associated with DEPs affiliated with proliferative pathways and exhibiting distinct oppositional response including with respect to radiation therapy related pathways, as compared to better-performing groups (intermediate, median OS 22.4 months; highest, median OS 28.7 months). Opposite signaling patterns across multiple analyses in several pathways (notably fatty acid metabolism, NOTCH, TNFα via NF-κB, Myc target V1 signaling, UV response, unfolded protein response, peroxisome, and interferon response) were distinct between clinical survival groups and supported by WGCNA. 23 proteins were statistically signficant for OS with 5 (NETO2, CST7, SEMA6D, CBLN4, NPS) supported by KM., Conclusion: Distinct proteomic alterations with hallmarks of cancer, including progression, resistance, stemness, and invasion, were identified in serum samples obtained from GBM patients pre vs. post CRT and corresponded with clinical survival. The proteome can potentially be employed for glioma classification and biological interrogation of cancer pathways., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Krauze, Sierk, Nguyen, Chen, Yan, Hu, Jiang, Tasci, Zgela, Sproull, Mackey, Shankavaram, Meerzaman and Camphausen.)

Introduction: In the era of big data, gene-set pathway analyses derived from multi-omics are exceptionally powerful. When preparing and analyzing high-dimensional multi-omics data, the installation process and programing skills required to use existing tools can be challenging. This is especially the case for those who are not familiar with coding. In addition, implementation with high performance computing solutions is required to run these tools efficiently., Methods: We introduce an automatic multi-omics pathway workflow, a point and click graphical user interface to Multivariate Single Sample Gene Set Analysis (MOGSA), hosted on the Cancer Genomics Cloud by Seven Bridges Genomics. This workflow leverages the combination of different tools to perform data preparation for each given data types, dimensionality reduction, and MOGSA pathway analysis. The Omics data includes copy number alteration, transcriptomics data, proteomics and phosphoproteomics data. We have also provided an additional workflow to help with downloading data from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium and preprocessing these data to be used for this multi-omics pathway workflow., Results: The main outputs of this workflow are the distinct pathways for subgroups of interest provided by users, which are displayed in heatmaps if identified. In addition to this, graphs and tables are provided to users for reviewing., Conclusion: Multi-omics Pathway Workflow requires no coding experience. Users can bring their own data or download and preprocess public datasets from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium using our additional workflow based on the samples of interest. Distinct overactivated or deactivated pathways for groups of interest can be found. This useful information is important in effective therapeutic targeting., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)

Background: High throughput experiments in cancer and other areas of genomic research identify large numbers of sequence variants that need to be evaluated for phenotypic impact. While many tools exist to score the likely impact of single nucleotide polymorphisms (SNPs) based on sequence alone, the three-dimensional structural environment is essential for understanding the biological impact of a nonsynonymous mutation., Results: We present a program, 3DVizSNP, that enables the rapid visualization of nonsynonymous missense mutations extracted from a variant caller format file using the web-based iCn3D visualization platform. The program, written in Python, leverages REST APIs and can be run locally without installing any other software or databases, or from a webserver hosted by the National Cancer Institute. It automatically selects the appropriate experimental structure from the Protein Data Bank, if available, or the predicted structure from the AlphaFold database, enabling users to rapidly screen SNPs based on their local structural environment. 3DVizSNP leverages iCn3D annotations and its structural analysis functions to assess changes in structural contacts associated with mutations., Conclusions: This tool enables researchers to efficiently make use of 3D structural information to prioritize mutations for further computational and experimental impact assessment. The program is available as a webserver at https://analysistools.cancer.gov/3dvizsnp or as a standalone python program at https://github.com/CBIIT-CGBB/3DVizSNP ., (© 2023. The Author(s).)

Tissue inhibitor of metalloproteinases (TIMPs/Timps) are an endogenous family of widely expressed matrisome-associated proteins that were initially identified as inhibitors of matrix metalloproteinase activity (Metzincin family proteases). Consequently, TIMPs are often considered simply as protease inhibitors by many investigators. However, an evolving list of new metalloproteinase-independent functions for TIMP family members suggests that this concept is outdated. These novel TIMP functions include direct agonism/antagonism of multiple transmembrane receptors, as well as functional interactions with matrisome targets. While the family was fully identified over two decades ago, there has yet to be an in-depth study describing the expression of TIMPs in normal tissues of adult mammals. An understanding of the tissues and cell-types that express TIMPs 1 through 4, in both normal and disease states are important to contextualize the growing functional capabilities of TIMP proteins, which are often dismissed as non-canonical. Using publicly available single cell RNA sequencing data from the Tabula Muris Consortium, we analyzed approximately 100,000 murine cells across eighteen tissues from non-diseased organs, representing seventy-three annotated cell types, to define the diversity in Timp gene expression across healthy tissues. We describe the unique expression profiles across tissues and organ-specific cell types that all four Timp genes display. Within annotated cell-types, we identify clear and discrete cluster-specific patterns of Timp expression, particularly in cells of stromal and endothelial origins. RNA in-situ hybridization across four organs expands on the scRNA sequencing analysis, revealing novel compartments associated with individual Timp expression. These analyses emphasize a need for specific studies investigating the functional significance of Timp expression in the identified tissues and cell sub-types. This understanding of the tissues, specific cell types and microenvironment conditions in which Timp genes are expressed adds important physiological context to the growing array of novel functions for TIMP proteins., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 Published by Elsevier B.V.)

Cohesin, a trimeric complex that establishes sister chromatid cohesion, has additional roles in chromatin organization and transcription. We report that among those roles is the regulation of alternative splicing through direct interactions and in situ colocalization with splicing factors. Degradation of cohesin results in marked changes in splicing, independent of its effects on transcription. Introduction of a single cohesin point mutation in embryonic stem cells alters splicing patterns, demonstrating causality. In primary human acute myeloid leukemia, mutations in cohesin are highly correlated with distinct patterns of alternative splicing. Cohesin also directly interacts with BRD4, another splicing regulator, to generate a pattern of splicing that is distinct from either factor alone, documenting their functional interaction. These findings identify a role for cohesin in regulating alternative splicing in both normal and leukemic cells and provide insights into the role of cohesin mutations in human disease.

Epidermal growth factor receptor (EGFR) signaling is frequently dysregulated in various cancers. The ubiquitin ligase Casitas B-lineage lymphoma proto-oncogene (Cbl) regulates degradation of activated EGFR through ubiquitination and acts as an adaptor to recruit proteins required for trafficking. Here, we used stable isotope labeling with amino acids in cell culture mass spectrometry to compare Cbl complexes with or without epidermal growth factor (EGF) stimulation. We identified over a hundred novel Cbl interactors, and a secondary siRNA screen found that knockdown of Flotillin-2 (FLOT2) led to increased phosphorylation and degradation of EGFR upon EGF stimulation in HeLa cells. In PC9 and H441 cells, FLOT2 knockdown increased EGF-stimulated EGFR phosphorylation, ubiquitination, and downstream signaling, reversible by EGFR inhibitor erlotinib. CRISPR knockout (KO) of FLOT2 in HeLa cells confirmed EGFR downregulation, increased signaling, and increased dimerization and endosomal trafficking. Furthermore, we determined that FLOT2 interacted with both Cbl and EGFR. EGFR downregulation upon FLOT2 loss was Cbl dependent, as coknockdown of Cbl and Cbl-b restored EGFR levels. In addition, FLOT2 overexpression decreased EGFR signaling and growth. Overexpression of wildtype (WT) FLOT2, but not the soluble G2A FLOT2 mutant, inhibited EGFR phosphorylation upon EGF stimulation in HEK293T cells. FLOT2 loss induced EGFR-dependent proliferation and anchorage-independent growth. Lastly, FLOT2 KO increased tumor formation and tumor volume in nude mice and NSG mice, respectively. Together, these data demonstrated that FLOT2 negatively regulated EGFR activation and dimerization, as well as its subsequent ubiquitination, endosomal trafficking, and degradation, leading to reduced proliferation in vitro and in vivo., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Published by Elsevier Inc.)

Background: The cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples., Results: We systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy., Conclusions: A high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods., (© 2022. The Author(s).)

We present a deep proteogenomic profiling study of 87 lung adenocarcinoma (LUAD) tumors from the United States, integrating whole-genome sequencing, transcriptome sequencing, proteomics and phosphoproteomics by mass spectrometry, and reverse-phase protein arrays. We identify three subtypes from somatic genome signature analysis, including a transition-high subtype enriched with never smokers, a transversion-high subtype enriched with current smokers, and a structurally altered subtype enriched with former smokers, TP53 alterations, and genome-wide structural alterations. We show that within-tumor correlations of RNA and protein expression associate with tumor purity and immune cell profiles. We detect and independently validate expression signatures of RNA and protein that predict patient survival. Additionally, among co-measured genes, we found that protein expression is more often associated with patient survival than RNA. Finally, integrative analysis characterizes three expression subtypes with divergent mutations, proteomic regulatory networks, and therapeutic vulnerabilities. This proteogenomic characterization provides a foundation for molecularly informed medicine in LUAD., Competing Interests: Declaration of interests M.D.W., R.F.B., and C.D.S. are inventors for a provisional patent application related to findings reported in this manuscript. J.S.H.L. serves as Chief Science and Innovation Officer for Ellison Institute, LLC (paid); board of trustee for Health and Environmental Institute, Inc. (unpaid, travel support); and scientific advisory board for AtlasXomics, Inc., and ATOM, Inc. (unpaid, travel support)., (Published by Elsevier Inc.)

Background: Adoptive transfer of tumor-infiltrating lymphocytes (TIL) fails to consistently elicit tumor rejection. Manipulation of intrinsic factors that inhibit T cell effector function and neoantigen recognition may therefore improve TIL therapy outcomes. We previously identified the cytokine-induced SH2 protein (CISH) as a key regulator of T cell functional avidity in mice. Here, we investigate the mechanistic role of CISH in regulating human T cell effector function in solid tumors and demonstrate that CRISPR/Cas9 disruption of CISH enhances TIL neoantigen recognition and response to checkpoint blockade., Methods: Single-cell gene expression profiling was used to identify a negative correlation between high CISH expression and TIL activation in patient-derived TIL. A GMP-compliant CRISPR/Cas9 gene editing process was developed to assess the impact of CISH disruption on the molecular and functional phenotype of human peripheral blood T cells and TIL. Tumor-specific T cells with disrupted Cish function were adoptively transferred into tumor-bearing mice and evaluated for efficacy with or without checkpoint blockade., Findings: CISH expression was associated with T cell dysfunction. CISH deletion using CRISPR/Cas9 resulted in hyper-activation and improved functional avidity against tumor-derived neoantigens without perturbing T cell maturation. Cish knockout resulted in increased susceptibility to checkpoint blockade in vivo., Conclusions: CISH negatively regulates human T cell effector function, and its genetic disruption offers a novel avenue to improve the therapeutic efficacy of adoptive TIL therapy., Funding: This study was funded by Intima Bioscience, U.S. and in part through the Intramural program CCR at the National Cancer Institute., Competing Interests: Declaration of interests M.C. is a co-founder of Intima Bioscience. B.R.W., S.A.R., and B.S.M. have received sponsored research support from Intima Bioscience. D.C.P., B.R.W., M.C., S.A.R., B.S.M., and N.P.R. have patents filed based on the findings described here., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Mitochondria are multifaceted organelles which are important for bioenergetics, biosynthesis and signaling in metazoans. Mitochondrial functions are frequently altered in cancer to promote both the energy and the necessary metabolic intermediates for biosynthesis required for tumor growth. Cancer stem cells (CSCs) contribute to chemotherapy resistance, relapse, and metastasis. Recent studies have shown that while non-stem, bulk cancer cells utilize glycolysis, breast CSCs are more dependent on oxidative phosphorylation (OxPhos) and therefore targeting mitochondria may inhibit CSC function. We previously reported that small molecule ONC201, which is an agonist for the mitochondrial caseinolytic protease (ClpP), induces mitochondrial dysfunction in breast cancer cells. In this study, we report that ClpP agonists inhibit breast cancer cell proliferation and CSC function in vitro and in vivo . Mechanistically, we found that OxPhos inhibition downregulates multiple pathways required for CSC function, such as the mevalonate pathway, YAP, Myc, and the HIF pathway. ClpP agonists showed significantly greater inhibitory effect on CSC functions compared with other mitochondria-targeting drugs. Further studies showed that ClpP agonists deplete NAD(P)+ and NAD(P)H, induce redox imbalance, dysregulate one-carbon metabolism and proline biosynthesis. Downregulation of these pathways by ClpP agonists further contribute to the inhibition of CSC function. In conclusion, ClpP agonists inhibit breast CSC functions by disrupting mitochondrial homeostasis in breast cancer cells and inhibiting multiple pathways critical to CSC function., Significance: ClpP agonists disrupt mitochondrial homeostasis by activating mitochondrial matrix protease ClpP. We report that ClpP agonists inhibit cell growth and cancer stem cell functions in breast cancer models by modulating multiple metabolic pathways essential to cancer stem cell function., Competing Interests: Conflict of interest disclosure EJI has a financial interest in Madera Therapeutics. The other authors declare no potential conflicts of interest.

Background: Next-generation sequencing platforms allow us to sequence millions of small fragments of DNA simultaneously, revolutionizing cancer research. Sequence analysis has revealed that cancer driver genes operate across multiple intricate pathways and networks with mutations often occurring in a mutually exclusive pattern. Currently, low-frequency mutations are understudied as cancer-relevant genes, especially in the context of networks., Results: Here we describe a tool, gcMECM, that enables us to visualize the functionality of mutually exclusive genes in the subnetworks derived from mutation associations, gene-gene interactions, and graph clustering. These subnetworks have revealed crucial biological components in the canonical pathway, especially those mutated at low frequency. Examining the subnetwork, and not just the impact of a single gene, significantly increases the statistical power of clinical analysis and enables us to build models to better predict how and why cancer develops., Conclusions: gcMECM uses a computationally efficient and scalable algorithm to identify subnetworks in a canonical pathway with mutually exclusive mutation patterns and distinct biological functions., (© 2021. The Author(s).)

TNF, produced largely by T and innate immune cells, is potently proinflammatory, as are cytokines such as IFN-γ and IL-17 produced by Th1 and Th17 cells, respectively. Here, we asked if TNF is upstream of Th skewing toward inflammatory phenotypes. Exposure of mouse CD4 + T cells to TNF and TGF-β generated Th17 cells that express low levels of IL-17 (ROR-γt + IL-17 lo ) and high levels of inflammatory markers independently of IL-6 and STAT3. This was mediated by the nondeath TNF receptor TNFR2, which also contributed to the generation of inflammatory Th1 cells. Single-cell RNA sequencing of central nervous system-infiltrating CD4 + T cells in mouse experimental autoimmune encephalomyelitis (EAE) found an inflammatory gene expression profile similar to cerebrospinal fluid-infiltrating CD4 + T cells from patients with multiple sclerosis. Notably, TNFR2-deficient CD4 + T cells produced fewer inflammatory mediators and were less pathogenic in EAE and colitis. IL-1β, a Th17-skewing cytokine, induced TNF and proinflammatory granulocyte-macrophage colony-stimulating factor (GM-CSF) in T cells, which was inhibited by disruption of TNFR2 signaling, demonstrating IL-1β can function indirectly via the production of TNF. Thus, TNF is not just an effector but also an initiator of inflammatory Th differentiation., Competing Interests: The authors declare no competing interest.

The TFIID component, TAF7, has been extensively characterized as essential for transcription and is critical for cell proliferation and differentiation. Here, we report that TAF7 is a previously unknown RNA chaperone that contributes to the regulation of protein synthesis. Mechanistically, TAF7 binds RNAs in the nucleus and delivers them to cytoplasmic polysomes. A broad spectrum of target RNA species, including the HIV-1 transactivation response element, binds TAF7 through consensus CUG motifs within the 3′ untranslated region. Export to the cytoplasm depends on a TAF7 nuclear export signal and occurs by an exportin 1–dependent pathway. Notably, disrupting either TAF7’s RNA binding or its export from the nucleus results in retention of target messenger RNAs in the nucleus and reduced levels of the protein products of TAF7-target RNAs. Thus, TAF7, an essential transcription factor, plays a key role in the regulation of RNA translation, thereby potentially connecting these processes.

With the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies., (© 2021. The Author(s).)

Background: Acute myeloid leukemia (AML) is a clinically heterogeneous group of cancers. While some patients respond well to chemotherapy, we describe here a subgroup with distinct molecular features that has very poor prognosis under chemotherapy. The classification of AML relies substantially on cytogenetics, but most cytogenetic abnormalities do not offer targets for development of targeted therapeutics. Therefore, it is important to create a detailed molecular characterization of the subgroup most in need of new targeted therapeutics. Methods: We used a multi-omics approach to identify a molecular subgroup with the worst response to chemotherapy, and to identify promising drug targets specifically for this AML subgroup. Results: Multi-omics clustering analysis resulted in three primary clusters among 166 AML adult cancer cases in TCGA data. One of these clusters, which we label as the high-risk molecular subgroup (HRMS), consisted of cases that responded very poorly to standard chemotherapy, with only about 10% survival to 2 years. The gene TP53 was mutated in most cases in this subgroup but not in all of them. The top six genes over-expressed in the HRMS subgroup included E2F4, CD34, CD109, MN1, MMLT3, and CD200 . Multi-omics pathway analysis using RNA and CNA expression data identified in the HRMS subgroup over-activated pathways related to immune function, cell proliferation, and DNA damage. Conclusion: A distinct subgroup of AML patients are not successfully treated with chemotherapy, and urgently need targeted therapeutics based on the molecular features of this subgroup. Potential drug targets include over-expressed genes E2F4 , and MN1 , as well as mutations in TP53, and several over-activated molecular pathways., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Nguyen, Pepper, Nguyen, Fan, Hu, Chen, Yan and Meerzaman.)

Deciphering the post-transcriptional mechanisms (PTM) regulating gene expression is critical to understand the dynamics underlying transcriptomic regulation in cancer. Alternative polyadenylation (APA)-regulation of mRNA 3'UTR length by alternating poly(A) site usage-is a key PTM mechanism whose comprehensive analysis in cancer remains an important open challenge. Here we use a method and analysis pipeline that sequences 3'end-enriched RNA directly to overcome the saturation limitation of traditional 5'-3' based sequencing. We comprehensively map the APA landscape in lung cancer in a cohort of 98 tumor/non-involved tissues derived from European American and African American patients. We identify a global shortening of 3'UTR transcripts in lung cancer, with notable functional implications on the expression of both coding and noncoding genes. We find that APA of non-coding RNA transcripts (long non-coding RNAs and microRNAs) is a recurrent event in lung cancer and discover that the selection of alternative polyA sites is a form of non-coding RNA expression control. Our results indicate that mRNA transcripts from EAs are two times more likely than AAs to undergo APA in lung cancer. Taken together, our findings comprehensively map and identify the important functional role of alternative polyadenylation in determining transcriptomic heterogeneity in lung cancer., (© 2021. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Purpose: Whole-exome (WES) and RNA sequencing (RNA-seq) are key components of cancer immunogenomic analyses. To evaluate the consistency of tumor WES and RNA-seq profiling platforms across different centers, the Cancer Immune Monitoring and Analysis Centers (CIMAC) and the Cancer Immunologic Data Commons (CIDC) conducted a systematic harmonization study., Experimental Design: DNA and RNA were centrally extracted from fresh frozen and formalin-fixed paraffin-embedded non-small cell lung carcinoma tumors and distributed to three centers for WES and RNA-seq profiling. In addition, two 10-plex HapMap cell line pools with known mutations were used to evaluate the accuracy of the WES platforms., Results: The WES platforms achieved high precision (> 0.98) and recall (> 0.87) on the HapMap pools when evaluated on loci using > 50× common coverage. Nonsynonymous mutations clustered by tumor sample, achieving an index of specific agreement above 0.67 among replicates, centers, and sample processing. A DV200 > 24% for RNA, as a putative presequencing RNA quality control (QC) metric, was found to be a reliable threshold for generating consistent expression readouts in RNA-seq and NanoString data. MedTIN > 30 was likewise assessed as a reliable RNA-seq QC metric, above which samples from the same tumor across replicates, centers, and sample processing runs could be robustly clustered and HLA typing, immune infiltration, and immune repertoire inference could be performed., Conclusions: The CIMAC collaborating laboratory platforms effectively generated consistent WES and RNA-seq data and enable robust cross-trial comparisons and meta-analyses of highly complex immuno-oncology biomarker data across the NCI CIMAC-CIDC Network., (©2020 American Association for Cancer Research.)

The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor-normal genomic DNA (gDNA) samples derived from a breast cancer cell line-which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations-and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking 'tumor-only' or 'matched tumor-normal' analyses., (© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection., (© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

Astrocytoma is the most common type of primary brain tumor. The risk factors for astrocytoma are poorly understood; however, germline genetic variants account for 25% of the risk of developing gliomas. In this study, we assessed the risk of astrocytoma associated with variants in AGT, known by its role in angiogenesis, TP53, a well-known tumor suppressor and the DNA repair gene MGMT in a Mexican population. A case-control study was performed in 49 adult Mexican patients with grade II-IV astrocytoma. Sequencing of exons and untranslated regions of AGT, MGMT, and TP53 from was carried in an Ion Torrent platform. Individuals with Mexican Ancestry from the 1000 Genomes Project were used as controls. Variants found in our cohort were then assessed in a The Cancer Genome Atlas astrocytoma pan-ethnic validation cohort. Variants rs1926723 located in AGT (OR 2.74, 1.40-5.36 95% CI), rs7896488 in MGMT (OR 3.43, 1.17-10.10 95% CI), and rs4968187 in TP53 (OR 2.48, 1.26-4.88 95% CI) were significantly associated with the risk of astrocytoma after multiple-testing correction. This is the first study where the AGT rs1926723 variant, TP53 rs4968187, and MGMT rs7896488 were found to be associated with the risk of developing an astrocytoma.

Background: The vast majority of metastatic cancers cannot be cured. Palliative treatment may relieve disease symptoms by stopping or slowing cancer growth and may prolong patients' lives, but almost all patients will inevitably develop disease progression after initial response. However, for reasons that are not fully understood, a very few patients will have extraordinary durable responses to standard anticancer treatments., Materials and Methods: We analyzed exceptional responders treated at Fox Chase Cancer Center between September 2009 and November 2017. An exceptional response was defined as a complete response lasting more than 1 year or a partial response or stable disease for more than 2 years. Tumor samples were analyzed using an Ambry Genetics test kit with a 142-gene panel. Messenger RNA expression was evaluated using NanoString's nCounter PanCancer Pathways Panel and Immune Profiling Panel and compared with matched controls for gender, age, and cancer type., Results: Twenty-six exceptional responders with metastatic bladder, kidney, breast, lung, ovarian, uterine, and colon cancers were enrolled. Mutations were identified in 45 genes. The most common mutation was an EPHA5 nonsynonymous mutation detected in 87.5% of patients. Mutations in DNA damage repair pathway genes were also frequent, suggesting increased genome instability. We also found varying expression of 73 genes in the Pathways panel and 85 genes in the Immune Profiling panel, many of them responsible for improvement in tumor recognition and antitumor immune response., Conclusions: The genomic instability detected in our exceptional responders, plus treatment with DNA damage compounds combined with favorable anticancer immunity, may have contributed to exceptional responses to standard anticancer therapies in the patients studied., Implications for Practice: With recent advances in the treatment of cancer, there is increased emphasis on the importance of identifying molecular markers to predict treatment outcomes, thereby allowing precision oncology. In this study, it was hypothesized that there is a "specific biologic signature" in the biology of the cancer in long-term survivors that allows sensitivity to systemic therapy and durability of response. Results showed that DNA damage repair pathway alterations, combined with favorable anticancer immunity, may have contributed to exceptional responses. It is very likely that an in-depth examination of outlier responses will become a standard component of drug development in the future., (© 2020 AlphaMed Press.)

The term "big data" refers broadly to large volumes of data, often gathered from several sources, that are then analyzed, for example, for predictive analytics. Combining and mining genetic data from varied sources including clinical genetic testing, for example, electronic health records, what might be termed as "recreational" genetic testing such as ancestry testing, as well as research studies, provide one type of "big data." Challenges and cautions in analyzing big data include recognizing the lack of systematic collection of the source data, the variety of assay technologies used, the potential variation in classification and interpretation of genetic variants. While advanced technologies such as microarrays and, more recently, next-generation sequencing, that enable testing an individual's DNA for thousands of genes and variants simultaneously are briefly discussed, attention is focused more closely on challenges to analysis of the massive data generated by these genomic technologies. The main theme of this review is to evaluate challenges associated with big data in general and specifically to bring the sophisticated technology of genetic/genomic testing down to the individual level, keeping in mind the human aspect of the data source and considering where the impact of the data will be translated and applied. Considerations in this "humanizing" process include providing adequate counseling and consent for genetic testing in all settings, as well as understanding the strengths and limitations of assays and their interpretation., (Copyright © 2020 Helzlsouer, Meerzaman, Taplin and Dunn.)

Purpose: A cryptic inv(16)(p13.3q24.3) encoding the CBFA2T3-GLIS2 fusion is associated with poor outcome in infants with acute megakaryocytic leukemia. We aimed to broaden our understanding of the pathogenesis of this fusion through transcriptome profiling., Experimental Design: Available RNA from children and young adults with de novo acute myeloid leukemia (AML; N = 1,049) underwent transcriptome sequencing (mRNA and miRNA). Transcriptome profiles for those with the CBFA2T3-GLIS2 fusion ( N = 24) and without ( N = 1,025) were contrasted to define fusion-specific miRNAs, genes, and pathways. Clinical annotations defined distinct fusion-associated disease characteristics and outcomes., Results: The CBFA2T3-GLIS2 fusion was restricted to infants <3 years old ( P < 0.001), and the presence of this fusion was highly associated with adverse outcome ( P < 0.001) across all morphologic classifications. Further, there was a striking paucity of recurrent cooperating mutations, and transduction of cord blood stem cells with this fusion was sufficient for malignant transformation. CBFA2T3-GLIS2 positive cases displayed marked upregulation of genes with cell membrane/extracellular matrix localization potential, including NCAM1 and GABRE . Additionally, miRNA profiling revealed significant overexpression of mature miR-224 and miR-452 , which are intronic miRNAs transcribed from the GABRE locus. Gene-set enrichment identified dysregulated Hippo, TGFβ, and hedgehog signaling, as well as NCAM1 (CD56) interaction pathways. Therapeutic targeting of fusion-positive leukemic cells with CD56-directed antibody-drug conjugate caused significant cytotoxicity in leukemic blasts., Conclusions: The CBFA2T3-GLIS2 fusion defines a highly refractory entity limited to infants that appears to be sufficient for malignant transformation. Transcriptome profiling elucidated several highly targetable genes and pathways, including the identification of CD56, providing a highly plausible target for therapeutic intervention., (©2019 American Association for Cancer Research.)

Background: Adrenocortical carcinoma is an aggressive malignancy with a low but variable overall survival rate. The role of in adrenocortical carcinoma is poorly understood. Thus, in this study we performed long noncoding RNA expression profiling in adrenocortical carcinomas, adrenocortical adenomas, and normal adrenal cortex., Methods: Long noncoding RNA expression profile using Human LncRNA/mRNA Expression Microarray V3.0 (Arraystar, Inc, Rockville, MD) was analyzed in samples from 11 adrenocortical adenomas, 9 adrenocortical carcinomas, and 5 normal adrenal cortex. Differentially expressed long noncoding RNAs were validated using TaqMan, real-time quantitative polymerase chain reaction with additional samples. The dataset from the adrenocortical carcinoma Cancer Genome Atlas Programproject was used to evaluate the prognostic utility of long noncoding RNAs., Results: Unsupervised hierarchical clustering showed distinct clustering of adrenocortical carcinoma samples compared with normal adrenal cortex and adrenocortical adenoma samples by long noncoding RNA expression profiles. A total of 874 long noncoding RNAs were differentially expressed between adrenocortical carcinoma and normal adrenal cortex. LINC00271 expression level was associated with prognosis, patients with low LINC00271 expression survived a shorter time than patients with high LINC00271 expression. Low LINC00271 expression was positively associated with WNT signaling, cell cycle, and chromosome segregation pathways., Conclusion: Adrenocortical carcinoma has a distinct long noncoding RNA expression profile. LINC00271 is downregulated in adrenocortical carcinoma and appears to be involved in biologic pathways commonly dysregulated in adrenocortical carcinoma., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Remodeling of the extracellular matrix (ECM) to facilitate invasion and metastasis is a universal hallmark of cancer progression. However, a definitive therapeutic target remains to be identified in this tissue compartment. As major modulators of ECM structure and function, matrix metalloproteinases (MMPs) are highly expressed in cancer and have been shown to support tumor progression. MMP enzymatic activity is inhibited by the tissue inhibitor of metalloproteinase (TIMP1-4) family of proteins, suggesting that TIMPs may possess anti-tumor activity. TIMP2 is a promiscuous MMP inhibitor that is ubiquitously expressed in normal tissues. In this study, we address inconsistencies in the literature regarding the role of TIMP2 in tumor progression by analyzing co-expressed genes in tumor vs. normal tissue. Utilizing data from The Cancer Genome Atlas and Genotype-Tissue expression studies, focusing on breast and lung carcinomas, we analyzed the correlation between TIMP2 expression and the transcriptome to identify a list of genes whose expression is highly correlated with TIMP2 in tumor tissues. Bioinformatic analysis of the identified gene list highlights a core of matrix and matrix-associated genes that are of interest as potential modulators of TIMP2 function, thus ECM structure, identifying potential tumor microenvironment biomarkers and/or therapeutic targets for further study.

The bromodomain protein 4 (BRD4) is an atypical kinase and histone acetyl transferase (HAT) that binds to acetylated histones and contributes to chromatin remodeling and early transcriptional elongation. During transcription, BRD4 travels with the elongation complex. Since most alternative splicing events take place co-transcriptionally, we asked if BRD4 plays a role in regulating alternative splicing. We report that distinct patterns of alternative splicing are associated with a conditional deletion of BRD4 during thymocyte differentiation in vivo. Similarly, the depletion of BRD4 in T cell acute lymphoblastic leukemia (T-ALL) cells alters patterns of splicing. Most alternatively spliced events affected by BRD4 are exon skipping. Importantly, BRD4 interacts with components of the splicing machinery, as assessed by both immunoprecipitation (IP) and proximity ligation assays (PLAs), and co-localizes on chromatin with the splicing regulator, FUS. We propose that BRD4 contributes to patterns of alternative splicing through its interaction with the splicing machinery during transcription elongation., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)