Evidence map›Paper›PMID 34137435›Full record

ArticleBriefings in bioinformatics2021

COSMIC Cancer Gene Census 3D database: understanding the impacts of mutations on cancer targets.

Ali F Alsulami, Pedro H M Torres, Ismail Moghul, Sheikh Mohammed Arif, Amanda K Chaplin, Sundeep Chaitanya Vedithi, Tom L Blundell

Open access · hybridAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Genomic characterization of peritoneal lavage cytology-positive gastric cancer.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2024
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Ali F AlsulamiDepartment of Biochemistry at the University of Cambridge, Cambridge CB2 1GA, UK.
Pedro H M TorresLaboratório de Modelagem e Dinâmica Molecular, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brasil.
Ismail MoghulUCL Cancer Institute, University College London, UK.
Sheikh Mohammed ArifDepartment of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK.
Amanda K ChaplinDepartment of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK.
Sundeep Chaitanya VedithiDepartment of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK.
Tom L BlundellDepartment of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK.
University of Cambridge · GBUniversidade Federal do Rio de Janeiro · BRUniversity College London · GB

Funding

Wellcome Trust 200814/Z/16/Z
6 · The paper itself

Abstract

Mutations in hallmark genes are believed to be the main drivers of cancer progression. These mutations are reported in the Catalogue of Somatic Mutations in Cancer (COSMIC). Structural appreciation of where these mutations appear, in protein-protein interfaces, active sites or deoxyribonucleic acid (DNA) interfaces, and predicting the impacts of these mutations using a variety of computational tools are crucial for successful drug discovery and development. Currently, there are 723 genes presented in the COSMIC Cancer Gene Census. Due to the complexity of the gene products, structures of only 87 genes have been solved experimentally with structural coverage between 90% and 100%. Here, we present a comprehensive, user-friendly, web interface (https://cancer-3d.com/) of 714 modelled cancer-related genes, including homo-oligomers, hetero-oligomers, transmembrane proteins and complexes with DNA, ribonucleic acid, ligands and co-factors. Using SDM and mCSM software, we have predicted the impacts of reported mutations on protein stability, protein-protein interfaces affinity and protein-nucleic acid complexes affinity. Furthermore, we also predicted intrinsically disordered regions using DISOPRED3.

Indexed as

Biomarkers, TumorDatabases, GeneticMutationOncogenesSoftwareComputational BiologyData AnalysisHumansModels, MolecularNeoplasmsStructure-Activity RelationshipUser-Computer InterfaceWorkflowBiomarkers, TumorCancer Gene Census 3Dhallmark mutationsmodelling cancer genes censusmutational analyses of cancer drug targets

Identifiers

PMID34137435
PMCPMC8574963
OpenAlexW3166546774

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.