A comprehensive catalog of cancer driver mutations is essential for understanding tumorigenesis and developing therapies. Exome-sequencing studies have mapped many protein-coding drivers, yet few ...non-coding drivers are known because genome-wide discovery is challenging. We developed a driver discovery method, ActiveDriverWGS, and analyzed 120,788 cis-regulatory modules (CRMs) across 1,844 whole tumor genomes from the ICGC-TCGA PCAWG project. We found 30 CRMs with enriched SNVs and indels (FDR < 0.05). These frequently mutated regulatory elements (FMREs) were ubiquitously active in human tissues, showed long-range chromatin interactions and mRNA abundance associations with target genes, and were enriched in motif-rewiring mutations and structural variants. Genomic deletion of one FMRE in human cells caused proliferative deficiencies and transcriptional deregulation of cancer genes CCNB1IP1, CDH1, and CDKN2B, validating observations in FMRE-mutated tumors. Pathway analysis revealed further sub-significant FMREs at cancer genes and processes, indicating an unexplored landscape of infrequent driver mutations in the non-coding genome.
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•Pan-cancer driver analysis highlights frequently mutated regulatory elements (FMREs)•FMREs are active in many tissues and interact with genes via chromatin loops•FMRE deletion in human cells caused alterations in pathway activity and proliferation•Additional less-frequent regulatory mutations are enriched at cancer genes and pathways
Cancer is driven by somatic mutations in critical genes, but few non-coding drivers are known. In a pan-cancer analysis, Zhu et al. identified frequently mutated, multi-tissue regulatory elements with chromatin loops to distal genes. Genomic deletion of one region caused deregulation of cancer genes, pathways, and proliferation in human cells.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Mutational signatures represent a genomic footprint of endogenous and exogenous mutational processes through tumor evolution. However, their functional impact on the proteome remains incompletely ...understood. We analyzed the protein-coding impact of single-base substitution (SBS) signatures in 12,341 cancer genomes from 18 cancer types. Stop-gain mutations (SGMs) (i.e., nonsense mutations) were strongly enriched in SBS signatures of tobacco smoking, APOBEC cytidine deaminases, and reactive oxygen species. These mutational processes alter specific trinucleotide contexts and thereby substitute serines and glutamic acids with stop codons. SGMs frequently affect cancer hallmark pathways and tumor suppressors such as
TP53
,
FAT1
, and
APC
. Tobacco-driven SGMs in lung cancer correlate with smoking history and highlight a preventable determinant of these harmful mutations. APOBEC-driven SGMs are enriched in YTCA motifs and associate with
APOBEC3A
expression. Our study exposes SGM expansion as a genetic mechanism by which endogenous and carcinogenic mutational processes directly contribute to protein loss of function, oncogenesis, and tumor heterogeneity.
Mutational processes of tobacco smoking and APOBEC disrupt gene function in cancer by adding premature stop codons.
Functional interpretation of candidate gene lists is an essential task in modern biomedical research. Here, we present the 2011 update of g:Profiler (http://biit.cs.ut.ee/gprofiler/), a popular ...collection of web tools for functional analysis. g:GOSt and g:Cocoa combine comprehensive methods for interpreting gene lists, ordered lists and list collections in the context of biomedical ontologies, pathways, transcription factor and microRNA regulatory motifs and protein-protein interactions. Additional tools, namely the biomolecule ID mapping service (g:Convert), gene expression similarity searcher (g:Sorter) and gene homology searcher (g:Orth) provide numerous ways for further analysis and interpretation. In this update, we have implemented several features of interest to the community: (i) functional analysis of single nucleotide polymorphisms and other DNA polymorphisms is supported by chromosomal queries; (ii) network analysis identifies enriched protein-protein interaction modules in gene lists; (iii) functional analysis covers human disease genes; and (iv) improved statistics and filtering provide more concise results. g:Profiler is a regularly updated resource that is available for a wide range of species, including mammals, plants, fungi and insects.
The original version of this Article omitted Suzana A. Kahn, Siddhartha S. Mitra & Samuel H. Cheshier as jointly supervising authors. This has now been corrected in both the PDF and HTML versions of ...the Article.
The current epidemic of obesity has caused a surge of interest in the study of adipose tissue formation. While major progress has been made in defining the molecular networks that control adipocyte ...terminal differentiation, the early steps of adipocyte development and the embryonic origin of this lineage remain largely unknown.
Here we performed genome-wide analysis of gene expression during adipogenesis of mouse embryonic stem cells (ESCs). We then pursued comprehensive bioinformatic analyses, including de novo functional annotation and curation of the generated data within the context of biological pathways, to uncover novel biological functions associated with the early steps of adipocyte development. By combining in-depth gene regulation studies and in silico analysis of transcription factor binding site enrichment, we also provide insights into the transcriptional networks that might govern these early steps.
This study supports several biological findings: firstly, adipocyte development in mouse ESCs is coupled to blood vessel morphogenesis and neural development, just as it is during mouse development. Secondly, the early steps of adipocyte formation involve major changes in signaling and transcriptional networks. A large proportion of the transcription factors that we uncovered in mouse ESCs are also expressed in the mouse embryonic mesenchyme and in adipose tissues, demonstrating the power of our approach to probe for genes associated with early developmental processes on a genome-wide scale. Finally, we reveal a plethora of novel candidate genes for adipocyte development and present a unique resource that can be further explored in functional assays.
How the genetic landscape governs a tumor's response to immunotherapy remains poorly understood. To assess the immune-modulatory capabilities of 573 genes associated with altered cytotoxicity in ...human cancers, here we perform CRISPR/Cas9 screens directly in mouse lung cancer models. We recover the known immune evasion factors Stat1 and Serpinb9 and identify the cancer testis antigen Adam2 as an immune modulator, whose expression is induced by Kras
and further elevated by immunotherapy. Using loss- and gain-of-function experiments, we show that ADAM2 functions as an oncogene by restraining interferon and TNF cytokine signaling causing reduced presentation of tumor-associated antigens. ADAM2 also restricts expression of the immune checkpoint inhibitors PDL1, LAG3, TIGIT and TIM3 in the tumor microenvironment, which might explain why ex vivo expanded and adoptively transferred cytotoxic T-cells show enhanced cytotoxic efficacy in ADAM2 overexpressing tumors. Together, direct in vivo CRISPR/Cas9 screens can uncover genetic alterations that control responses to immunotherapies.
g:Profiler (http://biit.cs.ut.ee/gprofiler/) is a public web server for characterising and manipulating gene lists resulting from mining high-throughput genomic data. g:Profiler has a simple, ...user-friendly web interface with powerful visualisation for capturing Gene Ontology (GO), pathway, or transcription factor binding site enrichments down to individual gene levels. Besides standard multiple testing corrections, a new improved method for estimating the true effect of multiple testing over complex structures like GO has been introduced. Interpreting ranked gene lists is supported from the same interface with very efficient algorithms. Such ordered lists may arise when studying the most significantly affected genes from high-throughput data or genes co-expressed with the query gene. Other important aspects of practical data analysis are supported by modules tightly integrated with g:Profiler. These are: g:Convert for converting between different database identifiers; g:Orth for finding orthologous genes from other species; and g:Sorter for searching a large body of public gene expression data for co-expression. g:Profiler supports 31 different species, and underlying data is updated regularly from sources like the Ensembl database. Bioinformatics communities wishing to integrate with g:Profiler can use alternative simple textual outputs.
Medulloblastoma is the most common malignant brain tumor of childhood. Group 3 medulloblastoma, the most aggressive molecular subtype, frequently disseminates through the leptomeningeal cerebral ...spinal fluid (CSF) spaces in the brain and spinal cord. The mechanism of dissemination through the CSF remains poorly understood, and the molecular pathways involved in medulloblastoma metastasis and self-renewal are largely unknown. Here we show that NOTCH1 signaling pathway regulates both the initiation of metastasis and the self-renewal of medulloblastoma. We identify a mechanism in which NOTCH1 activates BMI1 through the activation of TWIST1. NOTCH1 expression and activity are directly related to medulloblastoma metastasis and decreased survival rate of tumor-bearing mice. Finally, medulloblastoma-bearing mice intrathecally treated with anti-NRR1, a NOTCH1 blocking antibody, present lower frequency of spinal metastasis and higher survival rate. These findings identify NOTCH1 as a pivotal driver of Group 3 medulloblastoma metastasis and self-renewal, supporting the development of therapies targeting this pathway.
The specific genes and molecules that drive physiological angiogenesis differ from those involved in pathological angiogenesis, suggesting distinct mechanisms for these seemingly related processes. ...Unveiling genes and pathways preferentially associated with pathologic angiogenesis is key to understanding its mechanisms, thereby facilitating development of novel approaches to managing angiogenesis-dependent diseases. To better understand these different processes, we elucidated the transcriptome of the mouse retina in the well-accepted oxygen-induced retinopathy (OIR) model of pathological angiogenesis. We identified 153 genes changed between normal and OIR retinas, which represent a molecular signature relevant to other angiogenesis-dependent processes such as cancer. These genes robustly predict the survival of breast cancer patients, which was validated in an independent 1,000-patient test cohort (40% difference in 15-year survival; p = 2.56 x 10-21). These results suggest that the OIR model reveals key genes involved in pathological angiogenesis, and these may find important applications in stratifying tumors for treatment intensification or for angiogenesis-targeted therapies.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Cancer genomes are shaped by mutational processes with complex spatial variation at multiple scales. However, the underlying mechanisms of this mutagenesis and its functional and genetic ...determinants remain poorly understood. Somatic regional mutagenesis is known to correlate with DNA replication timing and chromatin accessibility; however, these studies have used epigenetic information from common cell lines while the epigenomes of primary human cancers remain uncharacterized in this context.
Here we model megabase-scale mutation frequencies of single nucleotide variants (SNVs) in thousands of whole cancer genomes using hundreds of genome-wide profiles of chromatin accessibility and replication timing spanning primary cancer samples, normal tissues, and cell lines. Using a machine learning framework, we show that CA profiles of primary cancers, rather than those of normal cells, predict regional mutagenesis and single base substitution (SBS) signatures in most cancer types. Thus the majority of passenger mutations follow the epigenetic landscapes of transformed cells of matching cancer sites and tissues.
Mutational signatures associated with carcinogen exposure, as well as signatures of unknown origin, show the strongest associations with epigenomes while associations with endogenous signatures are weaker. In most cases, overall mutation burden and SBS signatures inversely correlate with chromatin accessibility, however certain signatures are instead enriched in chromatin-accessible elements.
Lastly, the genomic regions with excess mutations unexplained by the epigenetic profiles in our models likely represent a combination of localized mutagenesis and positive selection of functional oncogenic mutations. Our computational models highlight an enrichment of known driver mutations, point out novel intergenic regions with putative non-coding drivers, and indicate an over-representation of developmental and lineage-specific genes in these frequently mutated genomic regions.
These results characterize the complex interplay of mutational processes, genome function, and somatic evolution in cancer and its tissues of origin, and also outline strategies for distinguishing driver and passenger mutations.
Citation Format: Jüri Reimand, Oliver Ocsenas. Chromatin accessibility of primary human cancers ties regional mutational processes with tissues of origin abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1508.
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