Inflammation-related signature for prognostic prediction, tumor immune, genomic heterogeneity, and drug choices in prostate cancer: Integrated analysis of bulk and single-cell RNA-sequencing

Background: Prostate cancer (PCa) ranks as the second most prevalent malignancy among males on a global scale. Accumulating evidence suggests that inflammation has an intricate relationship with tumorigenesis, tumor progression and tumor immune microenvironment. However, the overall impact of inflam...

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Main Authors: Weian Zhu, Jiongduan Huang, Jianjie Wu, Chenglun Wu, Fengxi Ye, Xiang Li, Wenjie Lai
Format: Article
Language:English
Published: Elsevier 2023-11-01
Series:Heliyon
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844023083822
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author Weian Zhu
Jiongduan Huang
Jianjie Wu
Chenglun Wu
Fengxi Ye
Xiang Li
Wenjie Lai
author_facet Weian Zhu
Jiongduan Huang
Jianjie Wu
Chenglun Wu
Fengxi Ye
Xiang Li
Wenjie Lai
author_sort Weian Zhu
collection DOAJ
description Background: Prostate cancer (PCa) ranks as the second most prevalent malignancy among males on a global scale. Accumulating evidence suggests that inflammation has an intricate relationship with tumorigenesis, tumor progression and tumor immune microenvironment. However, the overall impact of inflammation-related genes on the clinical prognosis and tumor immunity in PCa remains unclear. Methods: Machine learning methods were utilized to construct and validate a signature using The Cancer Genome Atlas (TCGA) for training, while the Memorial Sloan Kettering Cancer Center (MSKCC) and GSE70769 cohorts for independent validation. The efficacy of the signature in predicting outcomes and its clinical utility were assessed through a series of investigations encompassing in vitro experiments, survival analysis, and nomogram development. The association between the signature and precision medicine was explored via tumor immunity, genomic heterogeneity, therapeutic response, and molecular docking analyses, using bulk and single-cell RNA-sequencing data. Results: We identified 7 inflammation-related genes with prognostic significance and developed an inflammation-related prognostic signature (IRPS) with 6 genes. Furthermore, we demonstrated that both the IRPS and a nomogram integrating risk score and pathologic T stage exhibited excellent predictive ability for the survival outcomes in PCa patients. Moreover, the IRPS was found to be significantly associated with the tumor immune, genomic heterogeneity, therapeutic response, and drug selection. Conclusion: IRPS can serve as a reliable predictor for PCa patients. The signature may provide clinicians with valuable information on the efficacy of therapy and help personalize treatment for PCa patients.
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spelling doaj.art-2c8d44d202d4491993d9adb9dcf7b2542023-12-02T07:01:22ZengElsevierHeliyon2405-84402023-11-01911e21174Inflammation-related signature for prognostic prediction, tumor immune, genomic heterogeneity, and drug choices in prostate cancer: Integrated analysis of bulk and single-cell RNA-sequencingWeian Zhu0Jiongduan Huang1Jianjie Wu2Chenglun Wu3Fengxi Ye4Xiang Li5Wenjie Lai6Department of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510630, ChinaDepartment of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510630, ChinaDepartment of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510630, ChinaDepartment of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510630, ChinaZhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, ChinaDepartment of Emergency Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China; Corresponding author. Department of Emergency Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.Laboratory of Biomaterials and Translational Medicine, Center for Nanomedicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510630, China; Department of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510630, China; Corresponding author. Department of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510630, China.Background: Prostate cancer (PCa) ranks as the second most prevalent malignancy among males on a global scale. Accumulating evidence suggests that inflammation has an intricate relationship with tumorigenesis, tumor progression and tumor immune microenvironment. However, the overall impact of inflammation-related genes on the clinical prognosis and tumor immunity in PCa remains unclear. Methods: Machine learning methods were utilized to construct and validate a signature using The Cancer Genome Atlas (TCGA) for training, while the Memorial Sloan Kettering Cancer Center (MSKCC) and GSE70769 cohorts for independent validation. The efficacy of the signature in predicting outcomes and its clinical utility were assessed through a series of investigations encompassing in vitro experiments, survival analysis, and nomogram development. The association between the signature and precision medicine was explored via tumor immunity, genomic heterogeneity, therapeutic response, and molecular docking analyses, using bulk and single-cell RNA-sequencing data. Results: We identified 7 inflammation-related genes with prognostic significance and developed an inflammation-related prognostic signature (IRPS) with 6 genes. Furthermore, we demonstrated that both the IRPS and a nomogram integrating risk score and pathologic T stage exhibited excellent predictive ability for the survival outcomes in PCa patients. Moreover, the IRPS was found to be significantly associated with the tumor immune, genomic heterogeneity, therapeutic response, and drug selection. Conclusion: IRPS can serve as a reliable predictor for PCa patients. The signature may provide clinicians with valuable information on the efficacy of therapy and help personalize treatment for PCa patients.http://www.sciencedirect.com/science/article/pii/S2405844023083822Prostate cancerInflammationPrognostic signatureSingle-cell RNA-SequencingTumor immuneGenomic heterogeneity
spellingShingle Weian Zhu
Jiongduan Huang
Jianjie Wu
Chenglun Wu
Fengxi Ye
Xiang Li
Wenjie Lai
Inflammation-related signature for prognostic prediction, tumor immune, genomic heterogeneity, and drug choices in prostate cancer: Integrated analysis of bulk and single-cell RNA-sequencing
Heliyon
Prostate cancer
Inflammation
Prognostic signature
Single-cell RNA-Sequencing
Tumor immune
Genomic heterogeneity
title Inflammation-related signature for prognostic prediction, tumor immune, genomic heterogeneity, and drug choices in prostate cancer: Integrated analysis of bulk and single-cell RNA-sequencing
title_full Inflammation-related signature for prognostic prediction, tumor immune, genomic heterogeneity, and drug choices in prostate cancer: Integrated analysis of bulk and single-cell RNA-sequencing
title_fullStr Inflammation-related signature for prognostic prediction, tumor immune, genomic heterogeneity, and drug choices in prostate cancer: Integrated analysis of bulk and single-cell RNA-sequencing
title_full_unstemmed Inflammation-related signature for prognostic prediction, tumor immune, genomic heterogeneity, and drug choices in prostate cancer: Integrated analysis of bulk and single-cell RNA-sequencing
title_short Inflammation-related signature for prognostic prediction, tumor immune, genomic heterogeneity, and drug choices in prostate cancer: Integrated analysis of bulk and single-cell RNA-sequencing
title_sort inflammation related signature for prognostic prediction tumor immune genomic heterogeneity and drug choices in prostate cancer integrated analysis of bulk and single cell rna sequencing
topic Prostate cancer
Inflammation
Prognostic signature
Single-cell RNA-Sequencing
Tumor immune
Genomic heterogeneity
url http://www.sciencedirect.com/science/article/pii/S2405844023083822
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