Evidence map›Paper›PMID 37209182›Full record

ArticleBreast cancer research and treatment2023

Quantification of subtype purity in Luminal A breast cancer predicts clinical characteristics and survival.

Neeraj Kumar, Peter H Gann, Stephanie M McGregor, Amit Sethi

Open access · hybridAbstract read
In one paragraph

Article in Breast cancer research and treatment, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

9 citing papers in PubMed, 9 citations in OpenAlex.

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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

4 authors at 3 institutions in 2 countries.

Neeraj KumarAlberta Machine Intelligence Institute, Edmonton, AB, Canada.
Peter H GannDepartment of Pathology, College of Medicine, University of Illinois Cancer Center, University of Illinois at Chicago, Chicago, IL, USA. pgann@uic.edu.ORCID http://orcid.org/0000-0002-9439-2900
Stephanie M McGregorDepartment of Pathology and Laboratory Medicine, University of Wisconsin Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI, USA.
Amit SethiDepartment of Pathology, College of Medicine, University of Illinois Cancer Center, University of Illinois at Chicago, Chicago, IL, USA.
Illinois College · USIndian Institute of Technology Bombay · INUniversity of Wisconsin–Madison · US

Funding

Breast Cancer Alliance Exceptional Project AwardNational Institutes of Health (US) NCI R25-CA057699
6 · The paper itself

Abstract

purposePAM50 profiling assigns each breast cancer to a single intrinsic subtype based on a bulk tissue sample. However, individual cancers may show evidence of admixture with an alternate subtype that could affect prognosis and treatment response. We developed a method to model subtype admixture using whole transcriptome data and associated it with tumor, molecular, and survival characteristics for Luminal A (LumA) samples.

methodsWe combined TCGA and METABRIC cohorts and obtained transcriptome, molecular, and clinical data, which yielded 11,379 gene transcripts in common and 1,178 cases assigned to LumA. We used semi-supervised non-negative matrix factorization (ssNMF) to compute the subtype admixture proportions of the four major subtypes-pLumA, pLumB, pHER2, and pBasal-for each case and measured associations with tumor characteristics, molecular features, and survival.

resultsLuminal A cases in the lowest versus highest quartile for pLumA transcriptomic proportion had a 27% higher prevalence of stage > 1, nearly a threefold higher prevalence of TP53 mutation, and a hazard ratio of 2.08 for overall mortality. We found positive associations between pHER2 and HER2 positivity by IHC or FISH; between pLumB and PR negativity; and between pBasal and younger age, node positivity, TP53 mutation, and EGFR expression. Predominant basal admixture, in contrast to predominant LumB or HER2 admixture, was not associated with shorter survival.

conclusionBulk sampling for genomic analyses provides an opportunity to expose intratumor heterogeneity, as reflected by subtype admixture. Our results elucidate the striking extent of diversity among LumA cancers and suggest that determining the extent and type of admixture holds promise for refining individualized therapy. LumA cancers with a high degree of basal admixture appear to have distinct biological characteristics that warrant further study.

Indexed as

Breast NeoplasmsBiomarkers, TumorErb-b2 Receptor Tyrosine KinasesFemaleGene Expression ProfilingHumansPrognosisBiomarkers, TumorErb-b2 Receptor Tyrosine KinasesBreast cancerIntratumor heterogeneityMatrix factorizationSubtype admixture

Identifiers

PMID37209182
PMCPMC10241706
OpenAlexW4377197117

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.