Evidence map›Paper›PMID 34455425›Full record

ArticleBritish journal of cancer2021

Identification of putative actionable alterations in clinically relevant genes in breast cancer.

Pushpinder Kaur, Tania B Porras, Anthony Colombo, Alexander Ring, Janice Lu, Irene Kang, Julie E Lang

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PubMed Full text at PMC Publisher
In one paragraph

Article in British journal of cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

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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.

Pushpinder KaurDepartment of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Tania B PorrasCancer and Blood Disease Institute, Children Hospital Los Angeles, University of Southern California, Los Angeles, CA, USA.
Anthony ColomboDepartment of Preventive Medicine, University of Southern California, Los Angeles, CA, USA.
Alexander RingDepartment of Medical Oncology and Hematology, University Hospital Zürich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-0092-1323
Janice LuNorris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA.
Irene KangNorris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA.
Julie E LangDepartment of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA. LANGJ2@ccf.org.ORCID http://orcid.org/0000-0002-7534-6124

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIndividualising treatment in breast cancer requires effective predictive biomarkers. While relatively few genomic aberrations are clinically relevant, there is a need for characterising patients across different subtypes to identify actionable alterations.

methodsWe identified genomic alterations in 49 potentially actionable genes for which drugs are available either clinically or via clinical trials. We explored the landscape of mutations and copy number alterations (CNAs) in actionable genes in seven breast cancer subtypes utilising The Cancer Genome Atlas. To dissect the genomic complexity, we analysed the patterns of co-occurrence and mutual exclusivity in actionable genes.

resultsWe found that >30% of tumours harboured putative actionable events that are targetable by currently available drugs. We identified genes that had multiple targetable alterations, representing candidate targets for combination therapy. Genes predicted to be drivers in primary breast tumours fell into five categories: mTOR pathway, immune checkpoints, oestrogen signalling, tumour suppression and DNA damage repair. Our analysis also revealed that CNAs in 34/49 (69%) and mutations in 13/49 (26%) genes were significantly associated with gene expression, validating copy number events as a dominant oncogenic mechanism in breast cancer.

conclusionThese results may enable the acceleration of personalised therapy and improve clinical outcomes in breast cancer.

Indexed as

DNA Copy Number VariationsGene Regulatory NetworksMutationAdultAgedAged, 80 and overBreast NeoplasmsDatabases, GeneticExome SequencingFemaleGene Expression Regulation, NeoplasticHumansMiddle AgedPrecision MedicineSequence Analysis, RNA

Identifiers

PMID34455425
PMCPMC8548334

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Registered trials

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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.