A census of human cancer genes

Futreal, P. Andrew; Coin, Lachlan; Marshall, Mhairi; Down, Thomas A.; Hubbard, Tim; Wooster, Richard; Rahman, Nazneen; Stratton, Michael R.

doi:10.1038/nrc1299

Cited by 2,919 publications

(2,939 citation statements)

References 37 publications

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“…Also, genes that are probably not associated with tumour development but rather represent non-neoplastic somatic hypermutation processes in the context of immune function were removed. Furthermore, genes mutated in < 2% of the cohort were included only if they had a secondary signal from either functional impact or from localized clustering bias (Intogen modules OncodriveFM and OncodriveClust v. 3.0 beta) or from being among known cancer genes 29,93 . Mutation needle plots were generated using MutationMapper 94 .…”

Section: Discussionmentioning

confidence: 99%

The landscape of genomic alterations across childhood cancers

Gröbner¹,

Worst²,

Weischenfeldt³

et al. 2018

Nature

1,231

1,156

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The landscape of genomic alterations across childhood cancers a list of authors and affiliations appears at the end of the paper. OPENPan-cancer analyses that examine commonalities and differences among various cancer types have emerged as a powerful way to obtain novel insights into cancer biology. Here we present a comprehensive analysis of genetic alterations in a pan-cancer cohort including 961 tumours from children, adolescents, and young adults, comprising 24 distinct molecular types of cancer. Using a standardized workflow, we identified marked differences in terms of mutation frequency and significantly mutated genes in comparison to previously analysed adult cancers. Genetic alterations in 149 putative cancer driver genes separate the tumours into two classes: small mutation and structural/copy-number variant (correlating with germline variants). Structural variants, hyperdiploidy, and chromothripsis are linked to TP53 mutation status and mutational signatures. Our data suggest that 7-8% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trials.Cure rates for childhood cancers have increased to about 80% in recent decades, but cancer is still the leading cause of death by disease in the developed world among children over one year of age 1,2 . Furthermore, many children who survive cancer suffer from long-term sequelae of surgery, cytotoxic chemotherapy, and radiotherapy, including mental disabilities, organ toxicities, and secondary cancers 3 . A crucial step in developing more specific and less damaging therapies is the unravelling of the complete genetic repertoire of paediatric malignancies, which differ from adult malignancies in terms of their histopathological entities and molecular subtypes 4 . Over the past few years, many entityspecific sequencing efforts have been launched, but the few paediatric pan-cancer studies thus far have focused only on mutation frequencies, germline predisposition, and alterations in epigenetic regulators [4][5][6] .We have carried out a broad exploration of cancers in children, adolescents, and young adults, by incorporating small mutations and copy-number or structural variants on somatic and germline levels, and by identifying putative cancer genes and comparing them to those previously reported in adult cancers by The Cancer Genome Atlas (TCGA) 7 . We have also examined mutational signatures and potential drug targets. The compendium of genetic alterations presented here is available to the scientific community at http://www.pedpancan.com.This integrative analysis includes 24 types of cancer and covers all major childhood cancer entities, many of which occur exclusively in children 8 (Fig. 1, Supplementary Table 1). Ninety-five per cent of the patients in this study were diagnosed during childhood or adolescence (aged 18 years or younger) and 5% as young adults (up to 25 years) (Extended Data ...

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Section: Discussionmentioning

confidence: 99%

The landscape of genomic alterations across childhood cancers

Gröbner¹,

Worst²,

Weischenfeldt³

et al. 2018

Nature

1,231

1,156

View full text Add to dashboard Cite

show abstract

“…After cumulative filtering, 21 missense mutations were identified, 19 of which were confirmed using Sequenom (Supplementary Table 1). In particular, we found mutations in TP53 and MLH1, which are both recognized cancer genes 35,36 . On the other hand, when applying the MCC filter combination, we identified 117 somatic variants, 50 of which were confirmed by Sequenom or Sanger sequencing ( Table 2).…”

Section: Somatic Mutations In Ovarian Tumor Genomesmentioning

confidence: 82%

Optimized filtering reduces the error rate in detecting genomic variants by short-read sequencing

et al. 2011

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“…This comparison indicated that nodes in DRCEs tended to be the network hubs and bottlenecks, implying important functions. Cancer‐associated lncRNA, miRNA, and genes from the Lnc2Cancer (Ning et al ., 2016), miRCancer (Xie et al ., 2013), and Cancer Gene Census (Futreal et al ., 2004) databases, which are all manually curated data resources. First, we compared the proportion of cancer‐associated lncRNA, miRNA, and genes in DRCEs and background ceRNA.…”

Section: Resultsmentioning

confidence: 99%

Inferences of individual drug responses across diverse cancer types using a novel competing endogenous RNA network

Zhang

Zhou

et al. 2018

Molecular Oncology

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Differences in individual drug responses are an obstacle to progression in cancer treatment, and predicting responses would help to plan treatment. The accumulation of cancer molecular profiling and drug response data provides opportunities and challenges to identify novel molecular signatures and mechanisms of tumor responsiveness to drugs. This study evaluated drug responses with a competing endogenous RNA (ceRNA) system that depended on competition between diverse RNA species. We identified drug response‐related ceRNA (DRCEs) by combining the sequence and expression data of long noncoding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA), and the survival data of cancer patients treated with drugs. We constructed a patient–drug two‐layer integrated network and used a linear weighting method to predict individual drug responses. DRCEs were found to be significantly enriched in known cancer and drug‐associated data resources, involved in biological processes known to mediate drug responses, and correlated to drug activity in cancer cell lines. The dysregulation of DRCE expression influenced drug response‐associated functions and pathways, suggesting DRCEs as potential therapeutic targets affecting drug responses. A further case study in breast invasive carcinoma (BRCA) found that DRCE expression was consistent with the drug response pattern and the aberrant expression of the two NEAT1‐related DRCEs may lead to poor response to tamoxifen therapy for patients with TP53 mutations. In summary, this study provides a framework for ceRNA‐based evaluation of clinical drug responses across multiple cancer types. Understanding the underlying molecular mechanisms of drug responses will allow improved response to chemotherapy and outcomes of cancer treatment.

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A census of human cancer genes

Cited by 2,919 publications

References 37 publications

The landscape of genomic alterations across childhood cancers

The landscape of genomic alterations across childhood cancers

Optimized filtering reduces the error rate in detecting genomic variants by short-read sequencing

Inferences of individual drug responses across diverse cancer types using a novel competing endogenous RNA network

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