Evidence map›Paper›PMID 42053424›Full record

ArticleThe Prostate2026

A Gene Expression Tumor Signature Optimizing Partial Area-Under-the-Curve (pAUC) to Improve Specificity for Indolent Prostate Cancer.

Travis A Gerke, Svitlana Tyekucheva, Konrad H Stopsack, Christopher J Sweeney, Rosina T Lis, Elizabeth N Westling, Massimo Loda, Meir J Stampfer, Kathryn L Penney, Giovanni Parmigiani and 1 more

Abstract read
In one paragraph

Article in The Prostate, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Travis A GerkeProstate Cancer Clinical Trials Consortium, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Svitlana TyekuchevaDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
Konrad H StopsackDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Christopher J SweeneySouth Australian Immunogenomics Cancer Center, University of Adelaide, Adelaide, Australia.ORCID 0000-0002-0398-6018
Rosina T LisDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
Elizabeth N WestlingDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.ORCID 0000-0002-9917-9981
Massimo LodaDepartment of Pathology, Weill Cornell Medical Center, New York, New York, USA.
Meir J StampferDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Kathryn L PenneyDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Giovanni ParmigianiDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
Lorelei A MucciDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Validity of Diet and Activity Measures in WomenP01CA055075 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI WILLETT, WALTER C. · 1991 to 2009
$41.8M
Training Program in Cancer EpidemiologyT32CA009001 · NCI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI A. Heather Eliassen, Meir Stampfer · 1985 to 2026
$17.3M
Cancer Epidemiology Cohort in Male Health ProfessionalsU01CA167552 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Lorelei Mucci, Walter C. Willett · 2017 to 2026
$17.0M
Growth Factors and Lethal Prostate Cancer SignatureR01CA141298 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI STAMPFER, MEIR · 2010 to 2013
$2.2M
DF/HCC Specialized Programs in Research Excellence (SPORE) in Prostate Cancer 2P50CA090381NCI NIH HHS P01 CA055075NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA141298NCI NIH HHS T32 CA009001NCI NIH HHS U01 CA167552
6 · The paper itself

Abstract

purposeA key clinical challenge in prostate cancer is the identification and validation of biomarkers with high specificity for indolent long-term outcomes. We applied a novel statistical method to identify tumor transcriptomic biomarkers that optimally predicted patients with low metastatic potential.

methodsUsing tumor whole-transcriptome data from the Health Professionals Follow-up Study (HPFS, discovery set) and Physicians' Health Study (PHS, validation set), we compared patients who died of prostate cancer or developed metastases ("lethal," n = 113) and patients with > 8 years of metastasis-free survival ("indolent," n = 291). Whole transcriptome tumor gene expression data were generated using an Affymetrix array. We applied a novel method for optimizing a partial area under the curve (pAUC) that up-weighted indolent cases with a predefined 80%-100% specificity. This method leverages weighted logistic lasso regression, with weights chosen via cross-validation to reduce overfitting.

resultsMedian age at cancer diagnosis was 66 years; median follow-up for outcomes was 14 years. We identified a 40-gene transcriptome signature of indolent prostate cancer, which, compared to Gleason grade groups, improved the pAUC over the predefined 80%-100% specificity range by 1.72-fold (p < 0.001) and improved overall AUC from 0.85 to 0.93 (p < 0.001). The signature improved positive predictive value for indolent tumors > 2-fold with minimal decrease in negative predictive value. Importantly, the 40-gene signature showed high discrimination among intermediate Gleason 7 tumors (Grade groups 2 and 3, AUC 0.88, 95% CI: 0.79-0.95).

conclusionIncorporating pAUC into prognostic signature development improved identification of prostate tumors with low risk of metastatic potential. Its clinical application may help reduce overtreatment and overdiagnosis of indolent prostate cancers, and the pAUC may be relevant beyond prostate cancer.

Indexed as

Biomarkers, TumorProstatic NeoplasmsTranscriptomeAgedArea Under CurveFollow-Up StudiesGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleBiomarkers, Tumorgene expressionindolent prostate cancerpartial area‐under‐the‐curveprognostic biomarkers

Identifiers

PMID42053424
PMCPMC13172939

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.