Search

Medulloblastoma (MB) comprises a group of heterogeneous paediatric embryonal neoplasms of the hindbrain with strong links to early development of the hindbrain 1–4. Mutations that activate Sonic hedgehog signalling lead to Sonic hedgehog MB in the upper rhombic lip (RL) granule cell lineage 5–8. By contrast, mutations that activate WNT signalling lead to WNT MB in the lower RL 9,10. However, little is known about the more commonly occurring group 4 (G4) MB, which is thought to arise in the unipolar brush cell lineage 3,4. Here we demonstrate that somatic mutations that cause G4 MB converge on the core binding factor alpha (CBFA) complex and mutually exclusive alterations that affect CBFA2T2, CBFA2T3, PRDM6, UTX and OTX2. CBFA2T2 is expressed early in the progenitor cells of the cerebellar RL subventricular zone in Homo sapiens, and G4 MB transcriptionally resembles these progenitors but are stalled in developmental time. Knockdown of OTX2 in model systems relieves this differentiation blockade, which allows MB cells to spontaneously proceed along normal developmental differentiation trajectories. The specific nature of the split human RL, which is destined to generate most of the neurons in the human brain, and its high level of susceptible EOMES +KI67 + unipolar brush cell progenitor cells probably predisposes our species to the development of G4 MB.

Ion channels, transporters, and other ion-permeating proteins, collectively comprising the ion permeome (IP), are common drug targets. However, their roles in cancer are understudied. Our integrative pan-cancer analysis shows that IP genes display highly-elevated expression patterns in subsets of cancer samples significantly more often than expected transcriptome-wide. To enable target identification, we identified 410 survival-associated IP genes in 29 cancer types using a machine learning approach. Notably,GJB2andSCN9Ashow prominent expression in neoplastic cells and associate with poor prognosis in glioblastoma (GBM), the most common and aggressive brain cancer.GJB2orSCN9Aknockdown in patient-derived GBM cells induces transcriptome-wide changes involving neural projection and proliferation pathways, impairs cell viability and tumor sphere formation, mitigates tunneling nanotube formation, and extends the survival of GBM-bearing mice. Thus, aberrant activation of IP genes appears as a pan-cancer feature of tumor heterogeneity that can be exploited for mechanistic insights and therapy development.

Whole-genome sequencing of primary breast tumors enabled the identification of cancer driver genes and noncoding cancer driver plexuses from somatic mutations. However, differentiating driver from passenger events among noncoding genetic variants remains a challenge. Herein, we reveal cancer-driver cis-regulatory elements linked to transcription factors previously shown to be involved in development of luminal breast cancers by defining a tumor-enriched catalogue of approximately 100,000 unique cis-regulatory elements from 26 primary luminal estrogen receptor (ER)+ progesterone receptor (PR)+ breast tumors. Integrating this catalog with somatic mutations from 350 publicly available breast tumor whole genomes, we uncovered cancer driver cistromes, defined as the sum of binding sites for a transcription factor, for ten transcription factors in luminal breast cancer such as FOXA1 and ER, nine of which are essential for growth in breast cancer with four exclusive to the luminal subtype. Collectively, we present a strategy to find cancer driver cistromes relying on quantifying the enrichment of noncoding mutations over cis-regulatory elements concatenated into a functional unit.Implications:Mapping the accessible chromatin of luminal breast cancer led to discovery of an accumulation of mutations within cistromes of transcription factors essential to luminal breast cancer. This demonstrates coopting of regulatory networks to drive cancer and provides a framework to derive insight into the noncoding space of cancer.

Supplementary Figure from Mutations in Noncoding Cis-Regulatory Elements Reveal Cancer Driver Cistromes in Luminal Breast Cancer

Supplementary Table from Mutations in Noncoding Cis-Regulatory Elements Reveal Cancer Driver Cistromes in Luminal Breast Cancer

Measurement of ID1 half-life by cycloheximide chase assays. U251 cells were pretreated with or without TMZ for 3 days, followed by treatment with cycloheximide for the indicated times. The cell lysates were then analyzed by Western blots.

Glioblastoma is the most common primary brain tumor in adults. While the introduction of temozolomide chemotherapy has increased long-term survivorship, treatment failure and rapid tumor recurrence remains universal. The transcriptional regulatory protein, inhibitor of DNA-binding-1 (ID1), is a key regulator of cell phenotype in cancer. We show that CRISPR-mediated knockout of ID1 in glioblastoma cells, breast adenocarcinoma cells, and melanoma cells dramatically reduced tumor progression in all three cancer systems through transcriptional downregulation of EGF, which resulted in decreased EGFR phosphorylation. Moreover, ID1-positive cells were enriched by chemotherapy and drove tumor recurrence in glioblastoma. Addition of the neuroleptic drug pimozide to inhibit ID1 expression enhanced the cytotoxic effects of temozolomide therapy on glioma cells and significantly prolonged time to tumor recurrence. Conclusively, these data suggest ID1 could be a promising therapeutic target in patients with glioblastoma.Significance:These findings show that the transcriptional regulator ID1 is critical for glioblastoma initiation and chemoresistance and that inhibition of ID1 enhances the effect of temozolomide, delays tumor recurrence, and prolongs survival.

Mutational signatures represent a footprint of tumor evolution and its endogenous and exogenous mutational processes. However, their functional impact on the proteome remains incompletely understood. We analysed the protein-coding impact of single base substitution signatures in 12,341 cancer genomes from 18 cancer types. Stop-gain mutations (SGMs) were strongly enriched in the signatures of tobacco smoking, APOBEC cytidine deaminases, and reactive oxygen species. These mutational processes affect specific trinucleotide contexts to substitute serine and glutamic acid residues with stop codons. SGMs are enriched in cancer hallmark pathways and tumor suppressors such asTP53, FAT1, andAPC. Tobacco-driven SGMs in lung cancer correlate with lifetime smoking history and highlight a preventable determinant of these harmful mutations. Our study exposes SGM expansion as a genetic mechanism by which endogenous and carcinogenic mutational processes contribute to protein loss-of-function, oncogenesis, and tumor heterogeneity, providing potential translational and mechanistic insights.

Whole-genome sequencing of primary breast tumors enabled the identification of cancer driver genes and noncoding cancer driver plexuses from somatic mutations. However, differentiating driver from passenger events among noncoding genetic variants remains a challenge. Herein, we reveal cancer-driver cis-regulatory elements linked to transcription factors previously shown to be involved in development of luminal breast cancers by defining a tumor-enriched catalogue of approximately 100,000 unique cis-regulatory elements from 26 primary luminal estrogen receptor (ER)+ progesterone receptor (PR)+ breast tumors. Integrating this catalog with somatic mutations from 350 publicly available breast tumor whole genomes, we uncovered cancer driver cistromes, defined as the sum of binding sites for a transcription factor, for ten transcription factors in luminal breast cancer such as FOXA1 and ER, nine of which are essential for growth in breast cancer with four exclusive to the luminal subtype. Collectively, we present a strategy to find cancer driver cistromes relying on quantifying the enrichment of noncoding mutations over cis-regulatory elements concatenated into a functional unit. Implications: Mapping the accessible chromatin of luminal breast cancer led to discovery of an accumulation of mutations within cistromes of transcription factors essential to luminal breast cancer. This demonstrates coopting of regulatory networks to drive cancer and provides a framework to derive insight into the noncoding space of cancer.

Ion channels (IC) are one of the largest families of highly druggable proteins targeted in therapies for many human diseases; however, their role in cancer remains understudied. IC drug repurposing for cancer therapies is an appealing avenue; however, prioritizing ICs for pre-clinical research, mechanistic elucidation, and target development remains a challenge. Here we performed a systematic, pan-cancer analysis to prioritize IC genes as putative targets for therapeutic and biomarker development. Using machine learning, we studied ~10,000 human transcriptomes from 32 cancer types of The Cancer Genome Atlas (TCGA) to identify ICs whose expression significantly associated with patient survival. IC genes showed dysregulation in all cancer types: elevated IC expression was characteristic of a subset of tumors often associated with poor patient prognosis. Excessive IC expression was unexpectedly frequent and high-magnitude compared to control sets of protein-coding genes and genes of major druggable families. We focused on ICs in glioblastoma (GBM), the most prevalent and lethal form of brain cancer in adults, prioritizing GJB2 (gap junction protein beta 2) and SCN9A (sodium voltage-gated channel alpha subunit 9) as potential GBM oncogenes. High expression of these ICs associated with poor GBM prognosis in TCGA and independent transcriptomics datasets. GJB2 and SCN9A expression was higher in GBMs than normal brain tissues and associated with GBM subtypes, histological features, and immune cell infiltration. At the single-cell level, GJB2 and SCN9A were predominantly expressed in malignant cell types in GBMs. We validated GJB2 and SCN9A with shRNA-mediated knockdowns (KDs) in patient-derived GBM cell lines and mouse xenograft models. First, GJB2 and SCN9A KDs significantly impaired cell viability and spheroid formation. We then validated survival associations, showing that GJB2 and SCN9A KDs prolonged survival of mice with GBM xenografts. Finally, we showed GBJ2 KD impaired tunneling nanotube length in GBM cells. Transcriptome-wide profiling of IC KD cells revealed hundreds of differentially expressed genes. Integrative pathway enrichment across IC KDs in GBM cells and IC-stratified TCGA samples identified dysregulated pathways with functional themes of neuronal development, cancer hallmarks, and regulation of glial cells, including tumor cell connectivity pathways in GBM, corroborating the phenotypes observed in our functional validations. Our pan-cancer analysis prioritized ICs for further pre-clinical development and mechanistic study. The functional validation experiments of GJB2 and SCN9A highlight their possible roles in GBM pathology and lends confidence to our analysis. This study demonstrates the utility of investigating ICs as avenues for drug repurposing and the development of novel cancer therapeutics. Citation Format: Alexander Bahcheli, Hyun Min, Xi Huang, Jüri Reimand. Pan-cancer analysis of ion channel genes reveals patterns of large-scale transcriptional dysregulation and novel oncogenes with functions in cellular connectivity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2057.

Pediatric medulloblastoma (MB) is the most common solid malignant brain neoplasm, with Group 3 (G3) MB representing the most aggressive subgroup. MYC amplification is an independent poor prognostic factor in G3 MB, however, therapeutic targeting of the MYC pathway remains limited and alternative therapies for G3 MB are urgently needed. Here we show that the RNA-binding protein, Musashi-1 (MSI1) is an essential mediator of G3 MB in both MYC-overexpressing mouse models and patient-derived xenografts. MSI1 inhibition abrogates tumor initiation and significantly prolongs survival in both models. We identified binding targets of MSI1 in normal neural and G3 MB stem cells and then cross referenced these data with unbiased large-scale screens at the transcriptomic, translatomic and proteomic levels to systematically dissect its functional role. Comparative integrative multi-omic analyses of these large datasets reveal cancer-selective MSI1-bound targets sharing multiple MYC associated pathways, providing a valuable resource for context-specific therapeutic targeting of G3 MB.

SARS-CoV-2 infection hijacks signaling pathways and induces protein-protein interactions between human and viral proteins. Human genetic variation may impact SARS-CoV-2 infection and COVID-19 pathology; however, the genetic variation in these signaling networks remains uncharacterized. Here, we studied human missense single nucleotide variants (SNVs) altering phosphorylation sites modulated by SARS-CoV-2 infection, using machine learning to identify amino acid substitutions altering kinase-bound sequence motifs. We found 2,033 infrequent phosphorylation-associated SNVs (pSNVs) that are enriched in sequence motif alterations, potentially reflecting the evolution of signaling networks regulating host defenses. Proteins with pSNVs are involved in viral life cycle and host responses, including RNA splicing, interferon response (TRIM28), and glucose homeostasis (TBC1D4) with potential associations with COVID-19 comorbidities. pSNVs disrupt CDK and MAPK substrate motifs and replace these with motifs of Tank Binding Kinase 1 (TBK1) involved in innate immune responses, indicating consistent rewiring of signaling networks. Several pSNVs associate with severe COVID-19 and hospitalization (STARD13, ARFGEF2). Our analysis highlights potential genetic factors contributing to inter-individual variation of SARS-CoV-2 infection and COVID-19 and suggests leads for mechanistic and translational studies.

BACKGROUND: Germline variants explain more than a third of prostate cancer (PrCa) risk, but very few associations have been identified between heritable factors and clinical progression.OBJECTIVE: To find rare germline variants that predict time to biochemical recurrence (BCR) after radical treatment in men with PrCa and understand the genetic factors associated with such progression.DESIGN, SETTING, AND PARTICIPANTS: Whole-genome sequencing data from blood DNA were analysed for 850 PrCa patients with radical treatment from the Pan Prostate Cancer Group (PPCG) consortium from the UK, Canada, Germany, Australia, and France. Findings were validated using 383 patients from The Cancer Genome Atlas (TCGA) dataset.OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: A total of 15,822 rare (MAF RESULTS AND LIMITATIONS: Optimal Cox regression multifactor models showed that rare predicted-deleterious germline variants in "Hallmark" gene sets were consistently associated with altered time to BCR. Three gene sets had a statistically significant association with risk-elevated outcome when modelling all samples: PI3K/AKT/mTOR, Inflammatory response, and KRAS signalling (up). PI3K/AKT/mTOR and KRAS signalling (up) were also associated among patients with higher-grade cancer, as were Pancreas-beta cells, TNFA signalling via NKFB, and Hypoxia, the latter of which was validated in the independent TCGA dataset.CONCLUSIONS: We demonstrate for the first time that rare deleterious coding germline variants robustly associate with time to BCR after radical treatment, including cohort-independent validation. Our findings suggest that germline testing at diagnosis could aid clinical decisions by stratifying patients for differential clinical management.PATIENT SUMMARY: Prostate cancer patients with particular genetic mutations have a higher chance of relapsing after initial radical treatment, potentially providing opportunities to identify patients who might need additional treatments earlier.

SummaryHundreds of different protein complexes that perform important functions across all cellular processes, collectively comprising the “complexome” of an organism, have been identified1. However, less is known about the fraction of the interactome that exists outside the complexome, in the “outer-complexome”. To investigate features of “inner”- versus outer-complexome organisation in yeast, we generated a high-quality atlas of binary protein-protein interactions (PPIs), combining three previous maps2–4 and a new reference all-by-all binary interactome map. A greater proportion of interactions in our map are in the outer-complexome, in comparison to those found by affinity purification followed by mass spectrometry5–7 or in literature curated datasets8–11. In addition, recent advances in deep learning predictions of PPI structures12 mirror the existing experimentally resolved structures in being largely focused on the inner complexome and missing most interactions in the outer-complexome. Our new PPI network suggests that the outer-complexome contains considerably more PPIs than the inner-complexome, and integration with functional similarity networks13–15 reveals that interactions in the inner-complexome are highly detectable and correspond to pairs of proteins with high functional similarity, while proteins connected by more transient, harder-to-detect interactions in the outer-complexome, exhibit higher functional heterogeneity.

The most common events in breast cancer (BC) involve chromosome arm losses and gains. Here we describe identification of 1089 gene-centric common insertion sites (gCIS) from transposon-based screens in 8 mouse models of BC. Some gCIS are driver-specific, others driver non-specific, and still others associated with tumor histology. Processes affected by driver-specific and histology-specific mutations include well-known cancer pathways. Driver non-specific gCIS target the Mediator complex, Ca++ signaling, Cyclin D turnover, RNA-metabolism among other processes. Most gCIS show single allele disruption and many map to genomic regions showing high-frequency hemizygous loss in human BC. Two gCIS, Nf1 and Trps1, show synthetic haploinsufficient tumor suppressor activity. Many gCIS act on the same pathway responsible for tumor initiation, thereby selecting and sculpting just enough and just right signaling. These data highlight ~1000 genes with predicted conditional haploinsufficient tumor suppressor function and the potential to promote chromosome arm loss in BC., Transposon based screens carried out in mice can identify genes critical for tumourigensis. Here, the authors describe transposon screens in mouse models of breast cancer and highlight a large group of tumour suppressors that could underlie selection for common chromosome arm losses in cancer.

Whole-genome sequencing of primary breast tumors enabled the identification of cancer driver genes and noncoding cancer driver plexuses from somatic mutations. However, differentiating driver from passenger events among noncoding genetic variants remains a challenge. Herein, we reveal cancer-driver

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.

BackgroundRegional distribution of somatic mutations in cancer genomes associates with DNA replication timing (RT) and chromatin accessibility (CA), however normal tissues and cell lines have contributed these insights while associations with the epigenomes of primary cancers remain uncharacterized.ResultsHere we model megabase-scale mutation burden in whole cancer genomes using ∼900 CA and RT profiles of primary cancers, normal tissues, and cell lines. CA profiles of primary cancers, rather than normal tissues, predict regional mutagenesis in most cancer types. Regional mutation burden associates with the CA profiles of matching cancer types, indicating tissue-specific determinants of mutagenesis. However, mutagenesis in squamous cell and lymphoid cancers instead associates with RT profiles. Mutational signatures also show tissue-specific associations with cancer epigenomes, especially for carcinogen-induced and unannotated signatures. Lastly, while each cancer type includes certain frequently-mutated genomic regions exceeding epigenome-informed predictions of mutation burden, these regions show a pan-cancer convergence to biological processes involved in development and cancer. Thus, modelling excess mutations using epigenomes highlights known cancer driver genes as well as frequently mutated non-coding regions.ConclusionsThe dominant association of regional mutation burden with cancer epigenomes suggests that many passenger mutations are determined by the epigenetic landscapes of transformed cells and may occur later in tumor evolution. CA-informed models help find cancer genes and pathways with positive selection and highlight regions where additional mutation burden is contributed by local mutational processes. This study underlines the complex interplay of mutational processes, genome function and evolution in cancer and tissues of origin.

Background Cancer genomes are shaped by mutational processes with complex spatial variation at multiple scales. Entire classes of regulatory elements are affected by local variations in mutation frequency. However, the underlying mechanisms with functional and genetic determinants remain poorly understood. Results We characterise the mutational landscape of 1.3 million gene-regulatory and chromatin architectural elements in 2419 whole cancer genomes with transcriptional and pathway activity, functional conservation and recurrent driver events. We develop RM2, a statistical model that quantifies mutational enrichment or depletion in classes of genomic elements through genetic, trinucleotide and megabase-scale effects. We report a map of localised mutational processes affecting CTCF binding sites, transcription start sites (TSS) and tissue-specific open-chromatin regions. Increased mutation frequency in TSSs associates with mRNA abundance in most cancer types, while open-chromatin regions are generally enriched in mutations. We identify ~ 10,000 CTCF binding sites with core DNA motifs and constitutive binding in 66 cell types that represent focal points of mutagenesis. We detect site-specific mutational signature enrichments, such as SBS40 in open-chromatin regions in prostate cancer and SBS17b in CTCF binding sites in gastrointestinal cancers. Candidate drivers of localised mutagenesis are also apparent: BRAF mutations associate with mutational enrichments at CTCF binding sites in melanoma, and ARID1A mutations with TSS-specific mutagenesis in pancreatic cancer. Conclusions Our method and catalogue of localised mutational processes provide novel perspectives to cancer genome evolution, mutagenesis, DNA repair and driver gene discovery. The functional and genetic correlates of mutational processes suggest mechanistic hypotheses for future studies.

Sonic hedgehog medulloblastoma encompasses a clinically and molecularly diverse group of cancers of the developing central nervous system. Here, we use unbiased sequencing of the transcriptome across a large cohort of 250 tumors to reveal differences among molecular subtypes of the disease, and demonstrate the previously unappreciated importance of non-coding RNA transcripts. We identify alterations within the cAMP dependent pathway (GNAS, PRKAR1A) which converge on GLI2 activity and show that 18% of tumors have a genetic event that directly targets the abundance and/or stability of MYCN. Furthermore, we discover an extensive network of fusions in focally amplified regions encompassing GLI2, and several loss-of-function fusions in tumor suppressor genes PTCH1, SUFU and NCOR1. Molecular convergence on a subset of genes by nucleotide variants, copy number aberrations, and gene fusions highlight the key roles of specific pathways in the pathogenesis of Sonic hedgehog medulloblastoma and open up opportunities for therapeutic intervention., Sonic Hedgehog medulloblastoma (Shh-MB) comprises four subtypes each with distinct clinical traits. Here the authors characterize the genome, transcriptome, and methylome of Shh-MB subtypes, revealing a complex fusion landscape and the molecular convergence of MYCN and cAMP signaling pathways.

BackgroundCancer genomes are shaped by mutational processes with complex spatial variation at multiple scales. Entire classes of regulatory elements are affected by local variations in mutation frequency. However, the underlying mutational mechanisms with functional and genetic determinants remain poorly understood.ResultsWe characterised the mutational landscape of 1.3 million gene regulatory and chromatin architectural elements in 2,419 whole cancer genomes with transcriptional and pathway activity, functional conservation and recurrent driver events. We developed RM2, a statistical model that quantifies mutational enrichment or depletion in classes of genomic elements through genetic, trinucleotide and megabase-scale effects. We report a map of localised mutational processes affecting CTCF binding sites, transcription start sites (TSS) and tissue-specific open-chromatin regions. We show that increased mutational frequency in TSSs correlates with mRNA abundance in most cancer types, while open-chromatin regions are generally enriched in mutations. We identified ∼10,000 CTCF binding sites with core DNA motifs and constitutive binding in 66 cell types that represent focal points of local mutagenesis. We detected site-specific mutational signatures, such as SBS40 in open-chromatin regions in prostate cancer and SBS17b in CTCF binding sites in gastrointestinal cancers. We also proposed candidate drivers of localised mutagenesis: BRAF mutations associate with mutational enrichments at CTCF binding sites in melanoma, and ARID1A mutations with TSS-specific mutations in pancreatic cancer.ConclusionsOur method and catalogue of localised mutational processes provide novel perspectives to cancer genome evolution, mutagenesis, DNA repair and driver discovery. Functional and genetic correlates of localised mutagenesis provide mechanistic hypotheses for future studies.