The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously. Analysing 261 EACs from the OCCAMS Consortium, we discover helper genes that, alongside well-known drivers, promote cancer. We confirm the robustness of our approach in 107 additional EACs. Unlike recurrent alterations of known drivers, these cancer helper genes are rare or patient-specific. However, they converge towards perturbations of well-known cancer processes. Recurrence of the same process perturbations, rather than individual genes, divides EACs into six clusters differing in their molecular and clinical features. Experimentally mimicking the alterations of predicted helper genes in cancer and pre-cancer cells validates their contribution to disease progression, while reverting their alterations reveals EAC acquired dependencies that can be exploited in therapy.
The Network of Cancer Genes (NCG) is a manually curated repository of 2372 genes whose somatic modifications have known or predicted cancer driver roles. These genes were collected from 275 publications, including two sources of known cancer genes and 273 cancer sequencing screens of more than 100 cancer types from 34,905 cancer donors and multiple primary sites. This represents a more than 1.5-fold content increase compared to the previous version. NCG also annotates properties of cancer genes,...
The Catalogue of Somatic Mutations in Cancer (COSMIC) Cancer Gene Census (CGC) is an expert-curated description of the genes driving human cancer that is used as a standard in cancer genetics across basic research, medical reporting and pharmaceutical development. After a major expansion and complete re-evaluation, the 2018 CGC describes in detail the effect of 719 cancer-driving genes. The recent expansion includes functional and mechanistic descriptions of how each gene contributes to disease ...
Summary Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical si...
We conducted the largest investigation of predisposition variants in cancer to date, discovering 853 pathogenic or likely pathogenic variants in 8% of 10,389 cases from 33 cancer types. Twenty-one genes showed single or cross-cancer associations, including novel associations of SDHA in melanoma and PALB2 in stomach adenocarcinoma. The 659 predisposition variants and 18 additional large deletions in tumor suppressors, including ATM, BRCA1, and NF1, showed low gene expression and frequent (43%) lo...
#2Kenji M. Oman(Fred Hutchinson Cancer Research Center)H-Index: 6
Last. Xiaohong Li(Fred Hutchinson Cancer Research Center)H-Index: 21
view all 11 authors...
Background Use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been shown to protect against tetraploidy, aneuploidy, and chromosomal alterations in the metaplastic condition Barrett’s esophagus (BE) and to lower the incidence and mortality of esophageal adenocarcinoma (EA). The esophagus is exposed to both intrinsic and extrinsic mutagens resulting from gastric reflux, chronic inflammation, and exposure to environmental carcinogens such as those found in cigarettes. Here...
Summary Cancer develops as a result of somatic mutation and clonal selection, but quantitative measures of selection in cancer evolution are lacking. We adapted methods from molecular evolution and applied them to 7,664 tumors across 29 cancer types. Unlike species evolution, positive selection outweighs negative selection during cancer development. On average, 10/tumor in endometrial and colorectal cancers. Half of driver substitutions occur in yet-to-be-discovered cancer genes. With increasing...
We have recently gained unprecedented insight into genetic factors that determine risk for Barrett's esophagus (BE) and progression to esophageal adenocarcinoma (EA). Next-generation sequencing technologies have allowed us to identify somatic mutations that initiate BE and track genetic changes during development of tumors and invasive cancer. These technologies led to identification of mechanisms of tumorigenesis that challenge the current multistep model of progression to EA. Newer, cost-effec...
Esophageal adenocarcinoma (EAC) develops in an inflammatory microenvironment with reduced microbial diversity, but mechanisms for these influences remain poorly characterized. We hypothesized that mutations targeting the Toll-like receptor (TLR) pathway could disrupt innate immune signaling and promote a microenvironment that favors tumorigenesis. Through interrogating whole genome sequencing data from 171 EAC patients, we showed that non-synonymous mutations collectively affect the TLR pathway ...
// Lorena Benedetti 1, 2 , Matteo Cereda 1, 2 , LeeAnn Monteverde 1, 2 , Nikita Desai 1, 2 and Francesca D. Ciccarelli 1, 2 1 Division of Cancer Studies, King’s College London, London SE1 1UL, UK 2 Cancer Systems Biology Laboratory, The Francis Crick Institute, London NW1 1AT, UK Correspondence to: Francesca D. Ciccarelli, email: francesca.ciccarelli@kcl.ac.uk Keywords: synthetic lethality, cohesin complex, paralog dependency, cancer vulnerability, precision medicine Received: September 20, 2016...
Last. Joel Nulsen('KCL': King's College London)H-Index: 3
view all 16 authors...
Genetic alterations of somatic cells can drive non-malignant clone formation and promote cancer initiation. However, the link between these processes remains unclear hampering our understanding of tissue homeostasis and cancer development. Here we collect a literature-based repertoire of 3355 well-known or predicted drivers of cancer and noncancer somatic evolution in 122 cancer types and 12 noncancer tissues. Mapping the alterations of these genes in 7953 pancancer samples reveals that, despite...
Esophageal adenocarcinoma (EAC) is a deadly disease with limited options for targeted therapy. With the help of next-generation sequencing studies over the last decade, we gained an understanding of the genomic architecture of EAC. The tumor suppressor gene TP53 is mutated in 70 to 80% of tumors followed by genomic alterations in CDKN2A, KRAS, ERBB2, ARID1A, SMAD4 and a long tail of less frequently mutated genes. EAC is characterized by a high burden of point mutations and genomic rearrangements...
In jungster Vergangenheit konnten die Tumoren des oberen Gastrointestinaltraktes (osophageales Plattenepithelkarzinom [ESCC], osophageales Adenokarzinom [EAC], gastrales Adenokarzinom) zunehmend molekulargenetisch charakterisiert werden. Die resultierenden Subtypen bieten hierbei gemas ihren biologischen Eigenschaften mogliche Angriffspunkte fur zielgerichtete Therapien. Es wird eine Ubersicht uber den aktuellen Stand der molekularen Subtypen aller drei Tumorentitaten vermittelt und hiervon abge...
Neoadjuvant therapy followed by surgery is the standard of care for locally advanced esophageal adenocarcinoma (EAC). Unfortunately, response to neoadjuvant chemotherapy (NAC) is poor (20–37%), as is the overall survival benefit at five years (9%). The EAC genome is complex and heterogeneous between patients, and it is not yet understood whether specific mutational patterns may result in chemotherapy sensitivity or resistance. To identify associations between genomic events and response to NAC i...
ABSTRACT null BACKGROUND & AIMS null Colorectal cancer (CRC) shows variable response to immune checkpoint blockade, which can only partially be explained by high tumour mutational burden (TMB). We conducted an integrated study of the cancer tissue and associated tumour microenvironment (TME) from patients treated with Pembrolizumab (KEYNOTE 177 clinical trial) or Nivolumab to dissect the cellular and molecular determinants of response to anti-PD1 immunotherapy. null METHODS null We selected mult...
The increase in available high-throughput molecular data creates computational challenges for the identification of cancer genes. Genetic as well as non-genetic causes contribute to tumorigenesis, and this necessitates the development of predictive models to effectively integrate different data modalities while being interpretable. We introduce EMOGI, an explainable machine learning method based on graph convolutional networks to predict cancer genes by combining multiomics pan-cancer data—such ...
Artificial intelligence, or the discipline of developing computational algorithms able to perform tasks that requires human intelligence, offers the opportunity to improve our idea and delivery of precision medicine. Here, we provide an overview of artificial intelligence approaches for the analysis of large-scale RNA-sequencing datasets in cancer. We present the major solutions to disentangle inter- and intra-tumor heterogeneity of transcriptome profiles for an effective improvement of patient ...
Driver mutations are typically absent in esophageal adenocarcinoma (EAC). Mostly, oncogenes are amplified as driving molecular events (including GATA6-amplification in 14% of cases). However, only little is known about its biological function and clinical relevance. We examined a large number of EAC (n = 496) for their GATA6 amplification by fluorescence in situ hybridization (FISH) analyzing both primary resected (n = 219) and neoadjuvant treated EAC (n = 277). Results were correlated to clinic...
BACKGROUND The incidence of esophageal adenocarcinoma (EAC) is rapidly rising and has a 5-year survival rate <20%. Beyond TNM staging, no reliable risk stratification tools exist and no large-scale studies have profiled ctDNA at relapse in EAC. Here we analyze the prognostic potential of ctDNA dynamics in EAC, taking into account clonal hematopoiesis with indeterminate potential (CHIP). PATIENTS AND METHODS 245 samples from 97 patients treated with neoadjuvant chemotherapy and surgery were ident...
