Evidence map›Paper›PMID 38173042›Full record

ArticleClinical epigenetics2024

Tumor microenvironment deconvolution identifies cell-type-independent aberrant DNA methylation and gene expression in prostate cancer.

Samuel R Reynolds, Ze Zhang, Lucas A Salas, Brock C Christensen

Open access · goldAbstract read
In one paragraph

Article in Clinical epigenetics, 2024. 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
1.2field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 1 institution in 1 country.

Samuel R ReynoldsDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. reynolds.samuel.r@gmail.com.ORCID 0009-0008-1480-7581
Ze ZhangDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.ORCID 0000-0001-9854-5823
Lucas A SalasDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.ORCID 0000-0002-2279-4097
Brock C ChristensenDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.ORCID 0000-0003-3022-426X
Dartmouth College · US

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Fred W Kolling IV · 1985 to 2026
$91.3M
Pilot Project ProgramP30GM149408 · NIGMS · DARTMOUTH COLLEGE · PI MARGARET Rita KARAGAS · 2023 to 2026
$6.3M
DNA-based Immune Phenotyping in HNSCC for Biomarkers of Response to ImmunotherapyR01CA253976 · NCI · BROWN UNIVERSITY · PI CHRISTENSEN, BROCK C, KELSEY, KARL TIMOTHY · 2021 to 2025
$3.3M
(PQ3) Immune epigenetic biomarkers of bladder cancer outcomesR01CA216265 · NCI · DARTMOUTH COLLEGE · PI CHRISTENSEN, BROCK CLARKE · 2017 to 2021
$2.9M
NCI NIH HHS P30 CA023108NCI NIH HHS R01 CA216265NCI NIH HHS R01 CA253976NIGMS NIH HHS P30 GM149408
6 · The paper itself

Abstract

backgroundAmong men, prostate cancer (PCa) is the second most common cancer and the second leading cause of cancer death. Etiologic factors associated with both prostate carcinogenesis and somatic alterations in tumors are incompletely understood. While genetic variants associated with PCa have been identified, epigenetic alterations in PCa are relatively understudied. To date, DNA methylation (DNAm) and gene expression (GE) in PCa have been investigated; however, these studies did not correct for cell-type proportions of the tumor microenvironment (TME), which could confound results.

methodsThe data (GSE183040) consisted of DNAm and GE data from both tumor and adjacent non-tumor prostate tissue of 56 patients who underwent radical prostatectomies prior to any treatment. This study builds upon previous studies that examined methylation patterns and GE in PCa patients by using a novel tumor deconvolution approach to identify and correct for cell-type proportions of the TME in its epigenome-wide association study (EWAS) and differential expression analysis (DEA).

resultsThe inclusion of cell-type proportions in EWASs and DEAs reduced the scope of significant alterations associated with PCa. We identified 2,093 significantly differentially methylated CpGs (DMC), and 51 genes associated with PCa, including PCA3, SPINK1, and AMACR.

conclusionsThis work illustrates the importance of correcting for cell types of the TME when performing EWASs and DEAs on PCa samples, and establishes a more confounding-adverse methodology. We identified a more tumor-cell-specific set of altered genes and epigenetic marks that can be further investigated as potential biomarkers of disease or potential therapeutic targets.

Indexed as

DNA MethylationProstatic NeoplasmsCpG IslandsEpigenesis, GeneticGene ExpressionHumansMaleTrypsin Inhibitor, Kazal PancreaticTumor MicroenvironmentSPINK1 protein, humanTrypsin Inhibitor, Kazal PancreaticDeconvolutionDifferential expression analysisDNA methylationEpigenome-wide association studyProstate cancerTumor microenvironment

Identifiers

PMID38173042
PMCPMC10765773
OpenAlexW4390571209

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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.