Evidence map›Paper›PMID 25974664›Full record

ArticleCancer medicine2015

Identifying Etiologically Distinct Sub-Types of Cancer: A Demonstration Project Involving Breast Cancer.

Colin B Begg, Irene Orlow, Emily C Zabor, Arshi Arora, Ajay Sharma, Venkatraman E Seshan, Jonine L Bernstein

Abstract read
In one paragraph

Article in Cancer medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Evidence for Etiologic Subtypes of Breast Cancer in the Carolina Breast Cancer Study.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2019
    Article
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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.

Colin B BeggDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, New York.
Irene OrlowDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, New York.
Emily C ZaborDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, New York.
Arshi AroraDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, New York.
Ajay SharmaDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, New York.
Venkatraman E SeshanDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, New York.
Jonine L BernsteinDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, New York.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Statistical Strategies for Establishing Etiologic Heterogeneity of TumorsR01CA163251 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI BEGG, COLIN B · 2012 to 2015
$1.5M
Identification of Etiologically Distinct Sub-Types of Breast CancerR21CA167237 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI BEGG, COLIN B, BERNSTEIN, JONINE L. · 2013 to 2014
$417k
NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA163251NCI NIH HHS R21 CA167237
6 · The paper itself

Abstract

With the advent of increasingly detailed molecular portraits of tumor specimens, much attention has been directed toward identifying clinically distinct subtypes of cancer. Subtyping of tumors can also be accomplished with the goal of identifying distinct etiologies. We demonstrate the use of new methodologies to identify genes that distinguish etiologically heterogeneous subtypes of breast cancer using data from the case-control Cancer and Steroid Hormone Study. Tumor specimens were evaluated using a breast cancer expression panel of 196 genes. Using a statistical measure that distinguishes the degree of etiologic heterogeneity in tumor subtypes, each gene is ranked on the basis of its ability to distinguish etiologically distinct subtypes. This is accomplished independently using case-control comparisons and by examining the concordance odds ratios in double primaries. The estrogen receptor gene, and others in this pathway with expression levels that correlated strongly with estrogen receptor levels, demonstrate high degrees of etiologic heterogeneity in both methods. Our results are consistent with a growing literature that confirms the distinct etiologies of breast cancers classified on the basis of estrogen receptor expression levels. This proof-of-principle project demonstrates the viability of new strategies to identify genomic features that distinguish subtypes of cancer from an etiologic perspective.

Indexed as

AdultBreast NeoplasmsCase-Control StudiesFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMiddle AgedOdds RatioRisk FactorsSEER ProgramYoung AdultDouble primariesetiologic heterogeneityrisk predictiontumor subtypes

Identifiers

PMID25974664
PMCPMC4567028

What OpenQuestion holds

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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.