Evidence map›Paper›PMID 33928239›Full record

ArticleJournal of translational genetics and genomics2021

Prostate cancer in young men represents a distinct clinical phenotype: gene expression signature to predict early metastases.

Yuan C Ding, Huiqing Wu, Elai Davicioni, R Jeffrey Karnes, Eric A Klein, Robert B Den, Linda Steele, Susan L Neuhausen

Abstract read
In one paragraph

Article in Journal of translational genetics and genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Review
  2. Molecules (Basel, Switzerland) · 2021
    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

8 authors.

Yuan C DingDepartment of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, CA 91010, USA.
Huiqing WuDepartment of Pathology, City of Hope Medical Center, Duarte, California, CA 91010, USA.
Elai DavicioniGenomeDX Biosciences, Vancouver, British Columbia V6B 1B8, Canada.
R Jeffrey KarnesDepartment of Urology, Mayo Clinic, Rochester, Minnesota, MN 55905, USA.
Eric A KleinGlickman Urological and Kidney Institute, Cleveland Clinic, Ohio, OH 44195, USA.
Robert B DenDepartment of Radiation Oncology, Thomas Jefferson University, Philadelphia, Pennsylvania, PA 19044, USA.
Linda SteeleDepartment of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, CA 91010, USA.
Susan L NeuhausenDepartment of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, CA 91010, USA.

Funding

Transgenic Mouse FacilityP30CA033572 · NCI · CITY OF HOPE/BECKMAN RESEARCH INSTITUTE · PI XIWEI WU · 1985 to 2026
$86.3M
NCI NIH HHS P30 CA033572
6 · The paper itself

Abstract

aimSeveral genomic signatures are available to predict Prostate Cancer (CaP) outcomes based on gene expression in prostate tissue. However, no signature was tailored to predict aggressive CaP in younger men. We attempted to develop a gene signature to predict the development of metastatic CaP in young men.

methodsWe measured genome-wide gene expression for 119 tumor and matched benign tissues from prostatectomies of men diagnosed at ≤ 50 years and > 70 years and identified age-related differentially expressed genes (DEGs) for tissue type and Gleason score. Age-related DEGs were selected using the improved Prediction Analysis of Microarray method (iPAM) to construct and validate a classifier to predict metastasis using gene expression data from 1,232 prostatectomies. Accuracy in predicting early metastasis was quantified by the area under the curve (AUC) of receiver operating characteristic (ROC), and abundance of immune cells in the tissue microenvironment was estimated using gene expression data.

resultsThirty-six age-related DEGs were selected for the iPAM classifier. The AUC of five-year survival ROC for the iPAM classifier was 0.87 (95%CI: 0.78-0.94) in young (≤ 55 years), 0.82 (95%CI: 0.76-0.88) in middle-aged (56-70 years), and 0.69 (95%CI: 0.55-0.69) in old (> 70 years) patients. Metastasis-associated immune responses in the tumor microenvironment were more pronounced in young and middle-aged patients than in old ones, potentially explaining the difference in accuracy of prediction among the groups.

conclusionWe developed a genomic classifier with high precision to predict early metastasis for younger CaP patients and identified age-related differences in immune response to metastasis development.

Indexed as

ageclinical phenotypeDifferentially expressed geneimmune cell enrichmentmetastasispatient stratificationpredictionprostate cancertissue microenvironment

Identifiers

PMID33928239
PMCPMC8081383

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