Evidence map›Paper›PMID 33731882›Full record

ArticleThe pharmacogenomics journal2021

A survey of cancer genome signatures identifies genes connected to distinct chromosomal instability phenotypes.

Manar S Shafat, Eamaan S Rufaie, Johnathan Watkins

Abstract read
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In one paragraph

Article in The pharmacogenomics journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 45% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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  4. Review
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

3 authors at 3 institutions in 2 countries.

Manar S ShafatResearch Department of Haematology, UCL Cancer Institute, University College London, London, UK.
Eamaan S RufaiePILAR Research Network, London, UK.
Johnathan WatkinsPILAR Research Network, London, UK. jwatkins@pilar.org.uk.ORCID http://orcid.org/0000-0001-8370-6022
Middlesex University · GBUniversidad Nacional de Pilar · PYUniversity College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Certain breast and ovarian cancers are characterised by high levels of chromosomal instability. We established a suite of eleven SNP array-based signatures of various forms of chromosomal instability. To understand what biological mechanisms might underpin these signatures, we generated and assembled genetic-feature data including allele-specific expression, fusion genes, gene expression, methylation, somatic coding mutations and protein expression. For each signature, we extracted a compendium of significantly associated genetic features using machine learning. We established an association between subchromosomal allelic imbalance-based measures and DNA repair genes. Numerical chromosomal instability and chromothripsis were found to have distinct genetic associations but shared a relationship to mitotic processes, while whole-genome doubling was characterised by TP53 mutation, and high AURKA and GINS1 expression. Furthermore, we identified two genetically distinct forms of tandem duplicator phenotypes. These findings identify potentially novel genomic targets for validation and drug development for specific subsets of breast and ovarian cancer.

Indexed as

AllelesBiomarkers, TumorBreast NeoplasmsChromosomal InstabilityDNA MethylationDNA RepairFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGenes, NeoplasmGenetic Predisposition to DiseaseGenomicsHumansMachine LearningMitosisMutationBiomarkers, Tumor

Identifiers

PMID33731882
OpenAlexW3136556524

What OpenQuestion holds

Textmetadata
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.