Evidence map›Paper›PMID 36752203›Full record

ArticleJCI insight2023

Association of self-identified race and genetic ancestry with the immunogenomic landscape of primary prostate cancer.

Thiago Vidotto, Eddie L Imada, Farzana Faisal, Sanjana Murali, Adrianna A Mendes, Harsimar Kaur, Siqun Zheng, Jianfeng Xu, Edward M Schaeffer, William B Isaacs and 3 more

Open access · goldAbstract read
In one paragraph

Article in JCI insight, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  4. Review
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

13 authors at 4 institutions in 1 country.

Thiago VidottoDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Eddie L ImadaDepartment of Pathology, Weill-Cornell School of Medicine, New York, New York, USA.
Farzana FaisalDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Sanjana MuraliDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Adrianna A MendesDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Harsimar KaurDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Siqun ZhengProgram for Personalized Cancer Care, NorthShore University Health System, Evanston, Illinois, USA.
Jianfeng XuProgram for Personalized Cancer Care, NorthShore University Health System, Evanston, Illinois, USA.
Edward M SchaefferDepartment of Urology, Northwestern University School of Medicine, Chicago, Illinois, USA.
William B IsaacsDepartment of Urology and.
Karen S SfanosDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Luigi MarchionniDepartment of Pathology, Weill-Cornell School of Medicine, New York, New York, USA.
Tamara L LotanDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Johns Hopkins University · USNorthShore University HealthSystem · USCornell University · USNorthwestern University · US

Funding

Translational Research Central ServicesP30CA006973 · NCI · JOHNS HOPKINS UNIVERSITY · PI ALAN KEITH MEEKER · 1985 to 2026
$208.6M
Opportunities for Pathology Trainees in Cancer ResearchT32CA193145 · NCI · JOHNS HOPKINS UNIVERSITY · PI ANDERS, ROBERT A., EBERHART, CHARLES G · 2015 to 2025
$2.6M
Hardwiring Mechanism into Predicting Cancer Phenotypes by Computational LearningR01CA200859 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI MARCHIONNI, LUIGI · 2016 to 2020
$1.9M
NCI NIH HHS P30 CA006973NCI NIH HHS R01 CA200859NCI NIH HHS T32 CA193145
6 · The paper itself

Abstract

The genomic and immune landscapes of prostate cancer differ by self-identified race. However, few studies have examined the genome-wide copy number landscape and immune content of matched cohorts with genetic ancestry data and clinical outcomes. Here, we assessed prostate cancer somatic copy number alterations (sCNA) and tumor immune content of a grade-matched, surgically treated cohort of 145 self-identified Black (BL) and 145 self-identified White (WH) patients with genetic ancestry estimation. A generalized linear model adjusted with age, preoperative prostate-specific antigen (PSA), and Gleason Grade Group and filtered for germline copy number variations (gCNV) identified 143 loci where copy number varied significantly by percent African ancestry, clustering on chromosomes 6p, 10q, 11p, 12p, and 17p. Multivariable Cox regression models adjusted for age, preoperative PSA levels, and Gleason Grade Group revealed that chromosome 8q gains (including MYC) were significantly associated with biochemical recurrence and metastasis, independent of genetic ancestry. Finally, Treg density in BL and WH patients was significantly correlated with percent genome altered, and these findings were validated in the TCGA cohort. Taken together, our findings identify specific sCNA linked to genetic ancestry and outcome in primary prostate cancer and demonstrate that Treg infiltration varies by global sCNA burden in primary disease.

Indexed as

Prostatic NeoplasmsDNA Copy Number VariationsHumansMaleNeoplasm GradingProportional Hazards ModelsProstate-Specific AntigenRacial GroupsProstate-Specific AntigenCellular immune responseGeneticsGenetic variationProstate cancer

Identifiers

PMID36752203
PMCPMC9977441
OpenAlexW4319341215

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.