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ORIGINAL RESEARCH article

Front. Cell Dev. Biol.
Sec. Cellular Biochemistry
Volume 12 - 2024 | doi: 10.3389/fcell.2024.1475980
This article is part of the Research Topic Protein lactylation in disease progression: biological function and therapeutic targets View all articles

Characterizing adipocytokine-related signatures for prognosis prediction in prostate cancer

Provisionally accepted
Shicheng Fan Shicheng Fan 1Haolin Liu Haolin Liu 2*Hou Jian Hou Jian 1Guiying Zheng Guiying Zheng 1*Peng Gu Peng Gu 1*Xiaodong Liu Xiaodong Liu 1*
  • 1 Department of Urology, First Affiliated Hospital of Kunming Medical University, Kunming, China
  • 2 Department of Urology, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China

The final, formatted version of the article will be published soon.

    Prostate cancer (PCa) is a prevalent malignant tumor in males, with a significant incidence of biochemical recurrence (BCR) despite advancements in treatment. Adipose tissue surrounding the prostate, known as periprostatic adipose tissue (PPAT), contributes to PCa invasion through adipocytokine production. However, the relationship between adipocytokine-related genes and PCa prognosis remains understudied. This study was conducted to provide a theoretical basis and serve as a reference for the use of adipocytokine-related genes as prognostic markers in PCa. Transcriptome and survival data of PCa patients from The Cancer Genome Atlas (TCGA) database were analyzed. Differential gene expression analysis was conducted using the DESeq2 and limma packages. Prognostic genes were identified through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. A prognostic model was developed and validated utilizing receiver operating characteristic (ROC) and Kaplan-Meier (K-M) curves. Assessments of immune cell infiltration and drug sensitivity were also carried out. Subsequently, the function of BNIP3L gene in PCa was verified. A total of 47 adipocytokine-related differentially expressed genes (DEGs) were identified. Five genes (PPARGC1A, APOE, BNIP3L, STEAP4, and C1QTNF3) were selected as prognostic markers. The prognostic model demonstrated significant predictive accuracy in both training and validation cohorts. Patients with higher risk scores exhibited poorer survival outcomes. Immune cell infiltration analysis revealed that the high-risk group had increased immune and ESTIMATE scores, while the low-risk group had higher tumor purity. In vitro experiments confirmed the suppressive effects of BNIP3L on PCa cell proliferation, migration, and invasion.The prognostic model independently predicts the survival of patients with PCa, aiding in prognostic prediction and therapeutic efficacy. It expands the study of adipocytokine-related genes in PCa, presenting novel targets for treatment.

    Keywords: prostate cancer, adipocytokine-related gene, prognosis, Bnip3L, Immune infiltration

    Received: 04 Aug 2024; Accepted: 16 Oct 2024.

    Copyright: © 2024 Fan, Liu, Jian, Zheng, Gu and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Haolin Liu, Department of Urology, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
    Guiying Zheng, Department of Urology, First Affiliated Hospital of Kunming Medical University, Kunming, China
    Peng Gu, Department of Urology, First Affiliated Hospital of Kunming Medical University, Kunming, China
    Xiaodong Liu, Department of Urology, First Affiliated Hospital of Kunming Medical University, Kunming, China

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