Mutationmapper: A Tool to Aid the Mapping of Protein Mutation Data

Vohra, Shabana; Biggin, Philip C.

doi:10.1371/journal.pone.0071711

Cited by 33 publications

(26 citation statements)

References 26 publications

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“…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 . Biological processes were assigned to the significantly mutated genes mostly exclusively, except for a few genes with high relevance for multiple processes, as specified in Supplementary Table 9.…”

Section: Discussionmentioning

confidence: 99%

The landscape of genomic alterations across childhood cancers

Gröbner¹,

Worst²,

Weischenfeldt³

et al. 2018

Nature

1,167

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

1,167

1,156

View full text Add to dashboard Cite

show abstract

“…39 The figures were generated using MutationMapper. 62 MTase, methyltransferase. Contact Javeed Iqbal (jiqbal@unmc.edu) for original data, which will be deposited into the National Center for Biotechnology Information Gene Expression Omnibus database following publication.…”

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confidence: 99%

Genetic drivers of oncogenic pathways in molecular subgroups of peripheral T-cell lymphoma

Heavican

Bouska

et al. 2019

Blood

205

243

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Peripheral T-cell lymphoma (PTCL) is a group of complex clinicopathological entities, often associated with an aggressive clinical course. Angioimmunoblastic T-cell lymphoma (AITL) and PTCL-not otherwise specified (PTCL-NOS) are the 2 most frequent categories, accounting for >50% of PTCLs. Gene expression profiling (GEP) defined molecular signatures for AITL and delineated biological and prognostic subgroups within PTCL-NOS (PTCL-GATA3 and PTCL-TBX21). Genomic copy number (CN) analysis and targeted sequencing of these molecular subgroups revealed unique CN abnormalities (CNAs) and oncogenic pathways, indicating distinct oncogenic evolution. PTCL-GATA3 exhibited greater genomic complexity that was characterized by frequent loss or mutation of tumor suppressor genes targeting the CDKN2A/B-TP53 axis and PTEN-PI3K pathways. Co-occurring gains/amplifications of STAT3 and MYC occurred in PTCL-GATA3. Several CNAs, in particular loss of CDKN2A, exhibited prognostic significance in PTCL-NOS as a single entity and in the PTCL-GATA3 subgroup. The PTCL-TBX21 subgroup had fewer CNAs, primarily targeting cytotoxic effector genes, and was enriched in mutations of genes regulating DNA methylation. CNAs affecting metabolic processes regulating RNA/protein degradation and T-cell receptor signaling were common in both subgroups. AITL showed lower genomic complexity compared with other PTCL entities, with frequent co-occurring gains of chromosome 5 (chr5) and chr21 that were significantly associated with IDH2R172 mutation. CN losses were enriched in genes regulating PI3K–AKT–mTOR signaling in cases without IDH2 mutation. Overall, we demonstrated that novel GEP-defined PTCL subgroups likely evolve by distinct genetic pathways and provided biological rationale for therapies that may be investigated in future clinical trials.

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“…To visualize the somatic mutations on the gene structure we used MutationMapper 61 . We input our list of nonsilent mutations for individual genes from the Pancan12 dataset.…”

Section: Methodsmentioning

confidence: 99%

Signatures of positive selection reveal a universal role of chromatin modifiers as cancer driver genes

Zapata

Sušak

Drechsel

et al. 2017

Sci Rep

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Tumors are composed of an evolving population of cells subjected to tissue-specific selection, which fuels tumor heterogeneity and ultimately complicates cancer driver gene identification. Here, we integrate cancer cell fraction, population recurrence, and functional impact of somatic mutations as signatures of selection into a Bayesian model for driver prediction. We demonstrate that our model, cDriver, outperforms competing methods when analyzing solid tumors, hematological malignancies, and pan-cancer datasets. Applying cDriver to exome sequencing data of 21 cancer types from 6,870 individuals revealed 98 unreported tumor type-driver gene connections. These novel connections are highly enriched for chromatin-modifying proteins, hinting at a universal role of chromatin regulation in cancer etiology. Although infrequently mutated as single genes, we show that chromatin modifiers are altered in a large fraction of cancer patients. In summary, we demonstrate that integration of evolutionary signatures is key for identifying mutational driver genes, thereby facilitating the discovery of novel therapeutic targets for cancer treatment.

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Mutationmapper: A Tool to Aid the Mapping of Protein Mutation Data

Cited by 33 publications

References 26 publications

The landscape of genomic alterations across childhood cancers

The landscape of genomic alterations across childhood cancers

Genetic drivers of oncogenic pathways in molecular subgroups of peripheral T-cell lymphoma

Signatures of positive selection reveal a universal role of chromatin modifiers as cancer driver genes

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