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pmid:35516457

Characterization of a Pyroptosis-Related Signature for Prognosis Prediction and Immune Microenvironment Infiltration in Prostate Cancer.

Guian Zhang · Yong Luo · Weimin Dong · Weide Zhong

Computational and mathematical methods in medicine · 2022 doi:10.1155/2022/8233840

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Experiment

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Data

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title
Characterization of a Pyroptosis-Related Signature for Prognosis Prediction and Immune Microenvironment Infiltration in Prostate Cancer.
doi
10.1155/2022/8233840
pmid
35516457
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Guian Zhang
[1]
Yong Luo
[2]
Weimin Dong
[3]
Weide Zhong
journal
Computational and mathematical methods in medicine
year
2022
abstract
This study was aimed at constructing a pyroptosis-related signature for prostate cancer (PCa) and elucidating the prognosis and immune landscape and the sensitivity of immune checkpoint blockade (ICB) therapy in signature-define subgroups of PCa. We identified 22 differentially expressed pyroptosis-related genes in PCa from The Cancer Genome Atlas (TCGA) database. The pyroptosis-related genes could divide PCa patients into two clusters with differences in survival. Seven genes were determined to construct a signature that was confirmed by qRT-PCR to be closely associated with the biological characteristics of malignant PCa. The signature could effectively and independently predict the biochemical recurrence (BCR) of PCa, which was validated in the GSE116918 and GSE21034. We found that patients in the high-risk group were more prone to BCR and closely associated with high-grade and advanced-stage disease progression. Outperforming clinical characteristics and nine published articles, our signature demonstrated excellent predictive performance. The patients in the low-risk group were strongly related to the high infiltration of various immune cells including CD8+ T cells and plasma B cells. Furthermore, the high-risk group with higher TMB levels and expression of immune checkpoints was more likely to benefit from immune checkpoint therapy such as PD-1 and CTLA-4 inhibitors. The sensitivity to chemotherapy, endocrine, and targeted therapy showed significant differences in the two risk groups. Our signature was a novel therapeutic strategy to distinguish the prognosis and guide treatment strategies.
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Then, we performed univariate Cox regression and Lasso regression analysis, in which the best values of the penalty parameter were determined by 10-fold cross-validation (Figures 4(a) and 4(b)).
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sections[16] "3.3. Construction and Evaluation of Prognostic Signature for PCa" paragraph 2
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Then, we performed univariate Cox regression and Lasso regression analysis, in which the best values of the penalty parameter were determined by 10-fold cross-validation (Figures 4(a) and 4(b)).
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All data generated or analyzed during this study are included in this article or are available from the corresponding author on reasonable request.
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The study constructed a seven-gene pyroptosis-related prognostic signature that independently predicted biochemical recurrence in prostate cancer and was validated in GSE116918 and GSE21034.
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Seven genes were determined to construct a signature that was confirmed by qRT-PCR to be closely associated with the biological characteristics of malignant PCa.
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The signature could effectively and independently predict the biochemical recurrence (BCR) of PCa, which was validated in the GSE116918 and GSE21034.
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The study constructed a seven-gene pyroptosis-related prognostic signature that independently predicted biochemical recurrence in prostate cancer and was validated in GSE116918 and GSE21034.
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sample_count
370
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5188;10264
taxon
Homo sapiens
title
Whole-transcript and exon-level expression data for human primary and metastatic prostate cancer samples and control normal adjacent benign prostate
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2026-11-01T15:39:54Z
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Then, we performed univariate Cox regression and Lasso regression analysis, in which the best values of the penalty parameter were determined by 10-fold cross-validation (Figures 4(a) and 4(b)).
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All data generated or analyzed during this study are included in this article or are available from the corresponding author on reasonable request.
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The paper names GSE116918, GSE21034 in Gene Expression Omnibus (GEO) dataset and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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Then, we performed univariate Cox regression and Lasso regression analysis, in which the best values of the penalty parameter were determined by 10-fold cross-validation (Figures 4(a) and 4(b)).
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35516457", "kind": "science-record", "revision": 3, "content_hash": "sha256:016f3f3ba2953d59911370fdafa73d2a3394d5c4c5eb4bc366b80a7e708dd2f4", "created_at": "2026-11-01T18:14:24Z", "updated_at": "2026-11-01T21:27:48Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Characterization of a Pyroptosis-Related Signature for Prognosis Prediction and Immune Microenvironment Infiltration in Prostate Cancer.", "doi": "10.1155/2022/8233840", "pmid": "35516457", "authors": ["Guian Zhang", "Yong Luo", "Weimin Dong", "Weide Zhong"], "journal": "Computational and mathematical methods in medicine", "year": 2022, "abstract": "This study was aimed at constructing a pyroptosis-related signature for prostate cancer (PCa) and elucidating the prognosis and immune landscape and the sensitivity of immune checkpoint blockade (ICB) therapy in signature-define subgroups of PCa. We identified 22 differentially expressed pyroptosis-related genes in PCa from The Cancer Genome Atlas (TCGA) database. The pyroptosis-related genes could divide PCa patients into two clusters with differences in survival. Seven genes were determined to construct a signature that was confirmed by qRT-PCR to be closely associated with the biological characteristics of malignant PCa. The signature could effectively and independently predict the biochemical recurrence (BCR) of PCa, which was validated in the GSE116918 and GSE21034. We found that patients in the high-risk group were more prone to BCR and closely associated with high-grade and advanced-stage disease progression. Outperforming clinical characteristics and nine published articles, our signature demonstrated excellent predictive performance. The patients in the low-risk group were strongly related to the high infiltration of various immune cells including CD8+ T cells and plasma B cells. Furthermore, the high-risk group with higher TMB levels and expression of immune checkpoints was more likely to benefit from immune checkpoint therapy such as PD-1 and CTLA-4 inhibitors. The sensitivity to chemotherapy, endocrine, and targeted therapy showed significant differences in the two risk groups. Our signature was a novel therapeutic strategy to distinguish the prognosis and guide treatment strategies.", "claims": [{"id": "claim-method", "statement": "Then, we performed univariate Cox regression and Lasso regression analysis, in which the best values of the penalty parameter were determined by 10-fold cross-validation (Figures 4(a) and 4(b)).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35516457", "locator": "sections[16] \"3.3. 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