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BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) is a highly fatal cancer characterized by high intra-tumor heterogeneity (ITH). A panoramic understanding of its tumor evolution, in relation to its clinical trajectory, may provide novel prognostic and treatment strategies. METHODS: Through the Asia-Pacific Hepatocellular Carcinoma trials group (NCT03267641), we recruited one of the largest prospective cohorts of patients with HCC, with over 600 whole genome and transcriptome samples from 123 treatment-naïve patients. RESULTS: Using a multi-region sampling approach, we revealed seven convergent genetic evolutionary paths governed by the early driver mutations, late copy number variations and viral integrations, which stratify patient clinical trajectories after surgical resection. Furthermore, such evolutionary paths shaped the molecular profiles, leading to distinct transcriptomic subtypes. Most significantly, although we found the coexistence of multiple transcriptomic subtypes within certain tumors, patient prognosis was best predicted by the most aggressive cell fraction of the tumor, rather than by overall degree of transcriptomic ITH level - a phenomenon we termed the 'bad apple' effect. Finally, we found that characteristics throughout early and late tumor evolution provide significant and complementary prognostic power in predicting patient survival. CONCLUSIONS: Taken together, our study generated a comprehensive landscape of evolutionary history for HCC and provides a rich multi-omics resource for understanding tumor heterogeneity and clinical trajectories. IMPACT AND IMPLICATIONS: This prospective study, utilizing comprehensive multi-sector, multi-omics sequencing and clinical data from surgically resected hepatocellular carcinoma (HCC), reveals critical insights into the role of tumor evolution and intra-tumor heterogeneity (ITH) in determining the prognosis of HCC. These findings are invaluable for oncology researchers and clinicians, as they underscore the influence of distinct evolutionary paths and the 'bad apple' effect, where the most aggressive tumor fraction dictates disease progression. These insights not only enhance prognostic accuracy post-surgical resection but also pave the way for personalized treatment strategies tailored to specific tumor evolutionary and transcriptomic profiles. The coexistence of multiple subtypes within the same tumor prompts a re-appraisal of the utilities of depending on single samples to represent the entire tumor and suggests the need for clinical molecular imaging. This research thus marks a significant step forward in the clinical understanding and management of HCC, underscoring the importance of integrating tumor evolutionary dynamics and multi-omics biomarkers into therapeutic decision-making. CLINICAL TRIAL NUMBER: NCT03267641 (Observational cohort).
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OBJECTIVE: Gastric cancer (GC) comprises multiple molecular subtypes. Recent studies have highlighted mesenchymal-subtype GC (Mes-GC) as a clinically aggressive subtype with few treatment options. Combining multiple studies, we derived and applied a consensus Mes-GC classifier to define the Mes-GC enhancer landscape revealing disease vulnerabilities. DESIGN: Transcriptomic profiles of ~1000 primary GCs and cell lines were analysed to derive a consensus Mes-GC classifier. Clinical and genomic associations were performed across >1200 patients with GC. Genome-wide epigenomic profiles (H3K27ac, H3K4me1 and assay for transposase-accessible chromatin with sequencing (ATAC-seq)) of 49 primary GCs and GC cell lines were generated to identify Mes-GC-specific enhancer landscapes. Upstream regulators and downstream targets of Mes-GC enhancers were interrogated using chromatin immunoprecipitation followed by sequencing (ChIP-seq), RNA sequencing, CRISPR/Cas9 editing, functional assays and pharmacological inhibition. RESULTS: We identified and validated a 993-gene cancer-cell intrinsic Mes-GC classifier applicable to retrospective cohorts or prospective single samples. Multicohort analysis of Mes-GCs confirmed associations with poor patient survival, therapy resistance and few targetable genomic alterations. Analysis of enhancer profiles revealed a distinctive Mes-GC epigenomic landscape, with TEAD1 as a master regulator of Mes-GC enhancers and Mes-GCs exhibiting preferential sensitivity to TEAD1 pharmacological inhibition. Analysis of Mes-GC super-enhancers also highlighted NUAK1 kinase as a downstream target, with synergistic effects observed between NUAK1 inhibition and cisplatin treatment. CONCLUSION: Our results establish a consensus Mes-GC classifier applicable to multiple transcriptomic scenarios. Mes-GCs exhibit a distinct epigenomic landscape, and TEAD1 inhibition and combinatorial NUAK1 inhibition/cisplatin may represent potential targetable options.
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Elementos de Facilitación Genéticos , Epigénesis Genética , Regulación Neoplásica de la Expresión Génica , Neoplasias Gástricas , Humanos , Cisplatino/metabolismo , Cisplatino/uso terapéutico , Estudios Prospectivos , Proteínas Quinasas/genética , Proteínas Represoras , Estudios Retrospectivos , Neoplasias Gástricas/genéticaRESUMEN
OBJECTIVE: Gastric cancer (GC) is a leading cause of cancer mortality, with ARID1A being the second most frequently mutated driver gene in GC. We sought to decipher ARID1A-specific GC regulatory networks and examine therapeutic vulnerabilities arising from ARID1A loss. DESIGN: Genomic profiling of GC patients including a Singapore cohort (>200 patients) was performed to derive mutational signatures of ARID1A inactivation across molecular subtypes. Single-cell transcriptomic profiles of ARID1A-mutated GCs were analysed to examine tumour microenvironmental changes arising from ARID1A loss. Genome-wide ARID1A binding and chromatin profiles (H3K27ac, H3K4me3, H3K4me1, ATAC-seq) were generated to identify gastric-specific epigenetic landscapes regulated by ARID1A. Distinct cancer hallmarks of ARID1A-mutated GCs were converged at the genomic, single-cell and epigenomic level, and targeted by pharmacological inhibition. RESULTS: We observed prevalent ARID1A inactivation across GC molecular subtypes, with distinct mutational signatures and linked to a NFKB-driven proinflammatory tumour microenvironment. ARID1A-depletion caused loss of H3K27ac activation signals at ARID1A-occupied distal enhancers, but unexpectedly gain of H3K27ac at ARID1A-occupied promoters in genes such as NFKB1 and NFKB2. Promoter activation in ARID1A-mutated GCs was associated with enhanced gene expression, increased BRD4 binding, and reduced HDAC1 and CTCF occupancy. Combined targeting of promoter activation and tumour inflammation via bromodomain and NFKB inhibitors confirmed therapeutic synergy specific to ARID1A-genomic status. CONCLUSION: Our results suggest a therapeutic strategy for ARID1A-mutated GCs targeting both tumour-intrinsic (BRD4-assocatiated promoter activation) and extrinsic (NFKB immunomodulation) cancer phenotypes.
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Neoplasias Gástricas , Factores de Transcripción , Humanos , Factores de Transcripción/genética , Factores de Transcripción/metabolismo , Neoplasias Gástricas/genética , Neoplasias Gástricas/terapia , Neoplasias Gástricas/patología , Proteínas Nucleares/genética , Epigenómica , Mutación , Microambiente Tumoral/genética , Proteínas de Unión al ADN/genética , Proteínas de Ciclo Celular/genéticaRESUMEN
OBJECTIVES: Epigenomic alterations in cancer interact with the immune microenvironment to dictate tumour evolution and therapeutic response. We aimed to study the regulation of the tumour immune microenvironment through epigenetic alternate promoter use in gastric cancer and to expand our findings to other gastrointestinal tumours. DESIGN: Alternate promoter burden (APB) was quantified using a novel bioinformatic algorithm (proActiv) to infer promoter activity from short-read RNA sequencing and samples categorised into APBhigh, APBint and APBlow. Single-cell RNA sequencing was performed to analyse the intratumour immune microenvironment. A humanised mouse cancer in vivo model was used to explore dynamic temporal interactions between tumour kinetics, alternate promoter usage and the human immune system. Multiple cohorts of gastrointestinal tumours treated with immunotherapy were assessed for correlation between APB and treatment outcomes. RESULTS: APBhigh gastric cancer tumours expressed decreased levels of T-cell cytolytic activity and exhibited signatures of immune depletion. Single-cell RNAsequencing analysis confirmed distinct immunological populations and lower T-cell proportions in APBhigh tumours. Functional in vivo studies using 'humanised mice' harbouring an active human immune system revealed distinct temporal relationships between APB and tumour growth, with APBhigh tumours having almost no human T-cell infiltration. Analysis of immunotherapy-treated patients with GI cancer confirmed resistance of APBhigh tumours to immune checkpoint inhibition. APBhigh gastric cancer exhibited significantly poorer progression-free survival compared with APBlow (median 55 days vs 121 days, HR 0.40, 95% CI 0.18 to 0.93, p=0.032). CONCLUSION: These findings demonstrate an association between alternate promoter use and the tumour microenvironment, leading to immune evasion and immunotherapy resistance.
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Neoplasias Gastrointestinales , Neoplasias Gástricas , Animales , Epigénesis Genética , Epigenómica , Neoplasias Gastrointestinales/genética , Neoplasias Gastrointestinales/terapia , Humanos , Inhibidores de Puntos de Control Inmunológico/farmacología , Inhibidores de Puntos de Control Inmunológico/uso terapéutico , Inmunoterapia , Ratones , Neoplasias Gástricas/tratamiento farmacológico , Neoplasias Gástricas/terapia , Microambiente TumoralRESUMEN
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal and debilitating disease with limited therapeutic options. The aim of this clinical study was to evaluate the safety, efficacy and pharmacokinetics of a novel regimen comprised of metronomic oxaliplatin (O), chronomodulated capecitabine (X) and UGT1A1 genotype-guided dosing of irinotecan (IRI) [OXIRI] as well as its immunomodulatory effects. Thirty-six patients were enrolled into either dose-escalation or expansion cohorts. In the dose escalation phase, capecitabine doses (2000, 2650, 3500 and 4500 mg/day) were administered at midnight on days 1 to 14 while oxaliplatin and irinotecan were intravenously infused at fixed doses of 50 and 75 mg/m2 respectively on days 1, 8 in a 21-day cycle. The maximum tolerated dose of capecitabine was 2650 mg/day and the most common grade 3 adverse events were neutropenia (30.6%) and diarrhea (13.9%). No grade 4 toxicity was observed. UGT1A1-genotype directed dosing resulted in similar exposure levels of irinotecan, SN-38 and SN-38G in all patients. Objective response rate was 22.2%. Median overall survival and progression-free survival were 8.1 and 5.2 months, respectively. Exploratory immunoprofiling by flow cytometry and quantitative spatial localization analysis of infiltrated immune cells performed on biopsy and plasma samples revealed significant declines in CCL22, CCL2 and TNFα levels at end of first cycle and an active host immune response. Our study showed that OXIRI was well-tolerated and exhibited good efficacy, with immunomodulatory effects. It may be considered as an alternative to FOLFIRINOX in patients intolerant to the latter.
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Adenocarcinoma , Neoplasias Pancreáticas , Adenocarcinoma/patología , Protocolos de Quimioterapia Combinada Antineoplásica/efectos adversos , Camptotecina , Capecitabina/uso terapéutico , Fluorouracilo/uso terapéutico , Humanos , Inmunidad , Irinotecán , Oxaliplatino , Neoplasias Pancreáticas/patología , Resultado del Tratamiento , Neoplasias PancreáticasRESUMEN
BACKGROUND: The identification of cancer driver genes from sequencing data has been crucial in deepening our understanding of tumor biology and expanding targeted therapy options. However, apart from the most commonly altered genes, the mechanisms underlying the contribution of other mutations to cancer acquisition remain understudied. Leveraging on our whole-exome sequencing of the largest Asian lung adenocarcinoma (LUAD) cohort (n = 302), we now functionally assess the mechanistic role of a novel driver, PARP4. METHODS: In vitro and in vivo tumorigenicity assays were used to study the functional effects of PARP4 loss and mutation in multiple lung cancer cell lines. Interactomics analysis by quantitative mass spectrometry was conducted to identify PARP4's interaction partners. Transcriptomic data from cell lines and patient tumors were used to investigate splicing alterations. RESULTS: PARP4 depletion or mutation (I1039T) promotes the tumorigenicity of KRAS- or EGFR-driven lung cancer cells. Disruption of the vault complex, with which PARP4 is commonly associated, did not alter tumorigenicity, indicating that PARP4's tumor suppressive activity is mediated independently. The splicing regulator hnRNPM is a potentially novel PARP4 interaction partner, the loss of which likewise promotes tumor formation. hnRNPM loss results in splicing perturbations, with a propensity for dysregulated intronic splicing that was similarly observed in PARP4 knockdown cells and in LUAD cohort patients with PARP4 copy number loss. CONCLUSIONS: PARP4 is a novel modulator of lung adenocarcinoma, where its tumor suppressive activity is mediated not through the vault complex-unlike conventionally thought, but in association with its novel interaction partner hnRNPM, thus suggesting a role for splicing dysregulation in LUAD tumorigenesis.
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Ribonucleoproteína Heterogénea-Nuclear Grupo M , Neoplasias Pulmonares , Proteínas Nucleares , Animales , Humanos , Ratones , Adenocarcinoma del Pulmón/genética , Adenocarcinoma del Pulmón/metabolismo , Línea Celular Tumoral , Progresión de la Enfermedad , Regulación Neoplásica de la Expresión Génica , Ribonucleoproteína Heterogénea-Nuclear Grupo M/metabolismo , Ribonucleoproteína Heterogénea-Nuclear Grupo M/genética , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/metabolismo , Mutación , Unión Proteica , Empalme del ARN , Proteínas Nucleares/genética , Proteínas Nucleares/metabolismoRESUMEN
Tumors are complex masses composed of malignant and non-malignant cells. Variation in tumor purity (proportion of cancer cells in a sample) can both confound integrative analysis and enable studies of tumor heterogeneity. Here we developed PUREE, which uses a weakly supervised learning approach to infer tumor purity from a tumor gene expression profile. PUREE was trained on gene expression data and genomic consensus purity estimates from 7864 solid tumor samples. PUREE predicted purity with high accuracy across distinct solid tumor types and generalized to tumor samples from unseen tumor types and cohorts. Gene features of PUREE were further validated using single-cell RNA-seq data from distinct tumor types. In a comprehensive benchmark, PUREE outperformed existing transcriptome-based purity estimation approaches. Overall, PUREE is a highly accurate and versatile method for estimating tumor purity and interrogating tumor heterogeneity from bulk tumor gene expression data, which can complement genomics-based approaches or be used in settings where genomic data is unavailable.
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Perfilación de la Expresión Génica , Neoplasias , Humanos , Perfilación de la Expresión Génica/métodos , Neoplasias/genética , Transcriptoma , GenómicaRESUMEN
Tumors are heterogeneous cellular environments with entwined metabolic dependencies. Here, we use a tumor transcriptome deconvolution approach to profile the metabolic states of cancer and non-cancer (stromal) cells in bulk tumors of 20 solid tumor types. We identify metabolic genes and processes recurrently altered in cancer cells across tumor types, highlighting pan-cancer upregulation of deoxythymidine triphosphate (dTTP) production. In contrast, the tryptophan catabolism rate-limiting enzymes IDO1 and TDO2 are highly overexpressed in stroma, raising the hypothesis that kynurenine-mediated suppression of antitumor immunity may be predominantly constrained by the stroma. Oxidative phosphorylation is the most upregulated metabolic process in cancer cells compared to both stromal cells and a large atlas of cancer cell lines, suggesting that the Warburg effect may be less pronounced in cancer cells in vivo. Overall, our analysis highlights fundamental differences in metabolic states of cancer and stromal cells inside tumors and establishes a pan-cancer resource to interrogate tumor metabolism.
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Neoplasias , Microambiente Tumoral , Línea Celular Tumoral , Humanos , Quinurenina/metabolismo , Neoplasias/genética , Células del Estroma/metabolismo , Triptófano Oxigenasa/genética , Triptófano Oxigenasa/metabolismoRESUMEN
Identification of somatic mutations in tumor samples is commonly based on statistical methods in combination with heuristic filters. Here we develop VarNet, an end-to-end deep learning approach for identification of somatic variants from aligned tumor and matched normal DNA reads. VarNet is trained using image representations of 4.6 million high-confidence somatic variants annotated in 356 tumor whole genomes. We benchmark VarNet across a range of publicly available datasets, demonstrating performance often exceeding current state-of-the-art methods. Overall, our results demonstrate how a scalable deep learning approach could augment and potentially supplant human engineered features and heuristic filters in somatic variant calling.
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Aprendizaje Profundo , Neoplasias , Algoritmos , Benchmarking , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Humanos , Neoplasias/genéticaRESUMEN
Tumor purity is the percentage of cancer cells within a tissue section. Pathologists estimate tumor purity to select samples for genomic analysis by manually reading hematoxylin-eosin (H&E)-stained slides, which is tedious, time consuming, and prone to inter-observer variability. Besides, pathologists' estimates do not correlate well with genomic tumor purity values, which are inferred from genomic data and accepted as accurate for downstream analysis. We developed a deep multiple instance learning model predicting tumor purity from H&E-stained digital histopathology slides. Our model successfully predicted tumor purity in eight The Cancer Genome Atlas (TCGA) cohorts and a local Singapore cohort. The predictions were highly consistent with genomic tumor purity values. Thus, our model can be utilized to select samples for genomic analysis, which will help reduce pathologists' workload and decrease inter-observer variability. Furthermore, our model provided tumor purity maps showing the spatial variation within sections. They can help better understand the tumor microenvironment.
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The consensus molecular subtype (CMS) classification of colorectal cancer is based on bulk transcriptomics. The underlying epithelial cell diversity remains unclear. We analyzed 373,058 single-cell transcriptomes from 63 patients, focusing on 49,155 epithelial cells. We identified a pervasive genetic and transcriptomic dichotomy of malignant cells, based on distinct gene expression, DNA copy number and gene regulatory network. We recapitulated these subtypes in bulk transcriptomes from 3,614 patients. The two intrinsic subtypes, iCMS2 and iCMS3, refine CMS. iCMS3 comprises microsatellite unstable (MSI-H) cancers and one-third of microsatellite-stable (MSS) tumors. iCMS3 MSS cancers are transcriptomically more similar to MSI-H cancers than to other MSS cancers. CMS4 cancers had either iCMS2 or iCMS3 epithelium; the latter had the worst prognosis. We defined the intrinsic epithelial axis of colorectal cancer and propose a refined 'IMF' classification with five subtypes, combining intrinsic epithelial subtype (I), microsatellite instability status (M) and fibrosis (F).
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Neoplasias Colorrectales , Neoplasias Glandulares y Epiteliales , Neoplasias Colorrectales/genética , Neoplasias Colorrectales/patología , Células Epiteliales/patología , Humanos , Inestabilidad de Microsatélites , Repeticiones de Microsatélite/genética , Neoplasias Glandulares y Epiteliales/genética , Transcriptoma/genéticaRESUMEN
Intra-tumor heterogeneity (ITH) is a key challenge in cancer treatment, but previous studies have focused mainly on the genomic alterations without exploring phenotypic (transcriptomic and immune) heterogeneity. Using one of the largest prospective surgical cohorts for hepatocellular carcinoma (HCC) with multi-region sampling, we sequenced whole genomes and paired transcriptomes from 67 HCC patients (331 samples). We found that while genomic ITH was rather constant across stages, phenotypic ITH had a very different trajectory and quickly diversified in stage II patients. Most strikingly, 30% of patients were found to contain more than one transcriptomic subtype within a single tumor. Such phenotypic ITH was found to be much more informative in predicting patient survival than genomic ITH and explains the poor efficacy of single-target systemic therapies in HCC. Taken together, we not only revealed an unprecedentedly dynamic landscape of phenotypic heterogeneity in HCC, but also highlighted the importance of studying phenotypic evolution across cancer types.
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PURPOSE: Precision oncology has transformed the management of advanced cancers through implementation of advanced molecular profiling technologies to identify increasingly defined subsets of patients and match them to appropriate therapy. We report outcomes of a prospective molecular profiling study in a high-volume Asian tertiary cancer center. PATIENTS AND METHODS: Patients with advanced cancer were enrolled onto a prospective protocol for genomic profiling, the Individualized Molecular Profiling for Allocation to Clinical Trials Singapore study, at the National Cancer Center Singapore. Primary objective was to identify molecular biomarkers in patient's tumors for allocation to clinical trials. The study commenced in February 2012 and is ongoing, with the results of all patients who underwent multiplex next-generation sequencing (NGS) testing until December 2018 presented here. The results were discussed at a molecular tumor board where recommendations for allocation to biomarker-directed trials or targeted therapies were made. RESULTS: One thousand fifteen patients were enrolled with a median age of 58 years (range 20-83 years). Most common tumor types were lung adenocarcinoma (26%), colorectal cancer (15%), and breast cancer (12%). A total of 1,064 NGS assays were performed, on fresh tumor tissue for 369 (35%) and archival tumor tissue for 687 (65%) assays. TP53 (39%) alterations were most common, followed by EGFR (21%), KRAS (14%), and PIK3CA (10%). Of 405 NGS assays with potentially actionable alterations, 111 (27%) were allocated to a clinical trial after molecular tumor board and 20 (4.9%) were enrolled on a molecularly matched clinical trial. Gene fusions were detected in 23 of 311 (7%) patients tested, including rare fusions in new tumor types and known fusions in rare tumors. CONCLUSION: Individualized Molecular Profiling for Allocation to Clinical Trials Singapore demonstrates the feasibility of a prospective broad molecular profiling program in an Asian tertiary cancer center, with the ability to develop and adapt to a dynamic landscape of precision oncology.
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Ensayos Clínicos como Asunto , Perfilación de la Expresión Génica , Neoplasias/genética , Neoplasias/terapia , Medicina de Precisión , Adulto , Anciano , Anciano de 80 o más Años , Instituciones Oncológicas , Femenino , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Masculino , Persona de Mediana Edad , Estudios Prospectivos , Singapur , Centros de Atención Terciaria , Adulto JovenRESUMEN
BACKGROUND: Enhancers are distal cis-regulatory elements required for cell-specific gene expression and cell fate determination. In cancer, enhancer variation has been proposed as a major cause of inter-patient heterogeneity-however, most predicted enhancer regions remain to be functionally tested. METHODS: We analyzed 132 epigenomic histone modification profiles of 18 primary gastric cancer (GC) samples, 18 normal gastric tissues, and 28 GC cell lines using Nano-ChIP-seq technology. We applied Capture-based Self-Transcribing Active Regulatory Region sequencing (CapSTARR-seq) to assess functional enhancer activity. An Activity-by-contact (ABC) model was employed to explore the effects of histone acetylation and CapSTARR-seq levels on enhancer-promoter interactions. RESULTS: We report a comprehensive catalog of 75,730 recurrent predicted enhancers, the majority of which are GC-associated in vivo (> 50,000) and associated with lower somatic mutation rates inferred by whole-genome sequencing. Applying CapSTARR-seq to the enhancer catalog, we observed significant correlations between CapSTARR-seq functional activity and H3K27ac/H3K4me1 levels. Super-enhancer regions exhibited increased CapSTARR-seq signals compared to regular enhancers, even when decoupled from native chromatin contexture. We show that combining histone modification and CapSTARR-seq functional enhancer data improves the prediction of enhancer-promoter interactions and pinpointing of germline single nucleotide polymorphisms (SNPs), somatic copy number alterations (SCNAs), and trans-acting TFs involved in GC expression. We identified cancer-relevant genes (ING1, ARL4C) whose expression between patients is influenced by enhancer differences in genomic copy number and germline SNPs, and HNF4α as a master trans-acting factor associated with GC enhancer heterogeneity. CONCLUSIONS: Our results indicate that combining histone modification and functional assay data may provide a more accurate metric to assess enhancer activity than either platform individually, providing insights into the relative contribution of genetic (cis) and regulatory (trans) mechanisms to GC enhancer functional heterogeneity.
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Elementos de Facilitación Genéticos , Epigenómica , Neoplasias Gástricas/genética , Factores de Ribosilacion-ADP/genética , Factores de Ribosilacion-ADP/metabolismo , Acetilación , Línea Celular Tumoral , Proliferación Celular , Cromatina , Regulación Neoplásica de la Expresión Génica , Genómica , Histonas/metabolismo , Humanos , Proteína Inhibidora del Crecimiento 1/genética , Proteína Inhibidora del Crecimiento 1/metabolismo , Oncogenes , Regiones Promotoras Genéticas , RNA-Seq , Transcriptoma , Secuenciación Completa del GenomaRESUMEN
Recurrence and clustering of somatic mutations (hotspots) in cancer genomes may indicate positive selection and involvement in tumorigenesis. MutSpot performs genome-wide inference of mutation hotspots in non-coding and regulatory DNA of cancer genomes. MutSpot performs feature selection across hundreds of epigenetic and sequence features followed by estimation of position- and patient-specific background somatic mutation probabilities. MutSpot is user-friendly, works on a standard workstation, and scales to thousands of cancer genomes.
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Identification of somatic mutations in tumor tissue is challenged by both technical artifacts, diverse somatic mutational processes, and genetic heterogeneity in the tumors. Indeed, recent independent benchmark studies have revealed low concordance between different somatic mutation callers. Here, we describe Somatic Mutation calling method using a Random Forest (SMuRF), a portable ensemble method that combines the predictions and auxiliary features from individual mutation callers using supervised machine learning. SMuRF has improved prediction accuracy for both somatic point mutations (single nucleotide variants; SNVs) and small insertions/deletions (indels) in cancer genomes and exomes. Here, we describe the method and provide a tutorial on the installation and application of SMuRF.
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Genómica/métodos , Mutación , Neoplasias/genética , Programas Informáticos , Aprendizaje Automático Supervisado , Genoma Humano , Humanos , Mutación INDEL , Mutación Puntual , Polimorfismo de Nucleótido SimpleRESUMEN
Transcriptional reactivation of telomerase catalytic subunit (TERT) is a frequent hallmark of cancer, occurring in 90% of human malignancies. However, specific mechanisms driving TERT reactivation remain obscure for many tumor types and in particular gastric cancer (GC), a leading cause of global cancer mortality. Here, through comprehensive genomic and epigenomic analysis of primary GCs and GC cell lines, we identified the transcription factor early B cell factor 1 (EBF1) as a TERT transcriptional repressor and inactivation of EBF1 function as a major cause of TERT upregulation. Abolishment of EBF1 function occurs through 3 distinct (epi)genomic mechanisms. First, EBF1 is epigenetically silenced via DNA methyltransferase, polycomb-repressive complex 2 (PRC2), and histone deacetylase activity in GCs. Second, recurrent, somatic, and heterozygous EBF1 DNA-binding domain mutations result in the production of dominant-negative EBF1 isoforms. Third, more rarely, genomic deletions and rearrangements proximal to the TERT promoter remobilize or abolish EBF1-binding sites, derepressing TERT and leading to high TERT expression. EBF1 is also functionally required for various malignant phenotypes in vitro and in vivo, highlighting its importance for GC development. These results indicate that multimodal genomic and epigenomic alterations underpin TERT reactivation in GC, converging on transcriptional repressors such as EBF1.
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Epigenómica , Regulación Enzimológica de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , Proteínas de Neoplasias/metabolismo , Neoplasias Gástricas/metabolismo , Telomerasa/biosíntesis , Transactivadores/metabolismo , Línea Celular Tumoral , Humanos , Mutación , Proteínas de Neoplasias/genética , Elementos de Respuesta , Neoplasias Gástricas/genética , Telomerasa/genética , Transactivadores/genéticaRESUMEN
Lung cancer is the world's leading cause of cancer death and shows strong ancestry disparities. By sequencing and assembling a large genomic and transcriptomic dataset of lung adenocarcinoma (LUAD) in individuals of East Asian ancestry (EAS; n = 305), we found that East Asian LUADs had more stable genomes characterized by fewer mutations and fewer copy number alterations than LUADs from individuals of European ancestry. This difference is much stronger in smokers as compared to nonsmokers. Transcriptomic clustering identified a new EAS-specific LUAD subgroup with a less complex genomic profile and upregulated immune-related genes, allowing the possibility of immunotherapy-based approaches. Integrative analysis across clinical and molecular features showed the importance of molecular phenotypes in patient prognostic stratification. EAS LUADs had better prediction accuracy than those of European ancestry, potentially due to their less complex genomic architecture. This study elucidated a comprehensive genomic landscape of EAS LUADs and highlighted important ancestry differences between the two cohorts.
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Adenocarcinoma del Pulmón/genética , Neoplasias Pulmonares/genética , Mutación , Adenocarcinoma del Pulmón/etiología , Adenocarcinoma del Pulmón/mortalidad , Adenocarcinoma del Pulmón/terapia , Anciano , Pueblo Asiatico/genética , Estudios de Cohortes , Variaciones en el Número de Copia de ADN , Receptores ErbB/genética , Exoma , Femenino , Perfilación de la Expresión Génica , Humanos , Neoplasias Pulmonares/etiología , Neoplasias Pulmonares/mortalidad , Neoplasias Pulmonares/terapia , Masculino , Persona de Mediana Edad , Proteínas Proto-Oncogénicas p21(ras)/genética , Singapur , Proteína p53 Supresora de Tumor/genéticaRESUMEN
Somatic mutations in the RNase IIIb domain of DICER1 arise in cancer and disrupt the cleavage of 5' pre-miRNA arms. Here, we characterize an unstudied, recurrent, mutation (S1344L) in the DICER1 RNase IIIa domain in tumors from The Cancer Genome Atlas (TCGA) project and MSK-IMPACT profiling. RNase IIIa/b hotspots are absent from most cancers, but are notably enriched in uterine cancers. Systematic analysis of TCGA small RNA datasets show that DICER1 RNase IIIa-S1344L tumors deplete 5p-miRNAs, analogous to RNase IIIb hotspot samples. Structural and evolutionary coupling analyses reveal constrained proximity of RNase IIIa-S1344 to the RNase IIIb catalytic site, rationalizing why mutation of this site phenocopies known hotspot alterations. Finally, examination of DICER1 hotspot endometrial tumors reveals derepression of specific miRNA target signatures. In summary, comprehensive analyses of DICER1 somatic mutations and small RNA data reveal a mechanistic aspect of pre-miRNA processing that manifests in specific cancer settings.