YaXuan Wang
1*
Ma Li
2*
Haixia Zhu
3*The final, formatted version of the article will be published soon.
ORIGINAL RESEARCH article
Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
Volume 15 - 2024 |
doi: 10.3389/fimmu.2024.1464698
This article is part of the Research Topic Advancements in Multi-Omics and Bioinformatics for the Management of Solid Malignancies View all 4 articles
Identification of cancer stem cell-related genes through single cells and machine learning for predicting prostate cancer prognosis and immunotherapy
Provisionally accepted- 1 First Affiliated Hospital of Harbin Medical University, Harbin, China
- 2 Department of Pharmacy, Wuhan Third Hospital, Wuhan, Hebei Province, China
- 3 Nantong Tumor Hospital, Nantong, Jiangsu Province, China
Background: Cancer stem cells (CSCs) are a subset of cells within tumors that possess the unique ability to self-renew and give rise to diverse tumor cells. These cells are crucial in driving tumor metastasis, recurrence, and resistance to treatment. The objective of this study was to pinpoint the essential regulatory genes associated with CSCs in prostate adenocarcinoma (PRAD) and assess their potential significance in the diagnosis, prognosis, and immunotherapy of patients with PRAD.The study utilized single-cell analysis techniques to identify stem cell-related genes and evaluate their significance in relation to patient prognosis and immunotherapy in PRAD through cluster analysis. By utilizing diverse datasets and employing various machine learning methods for clustering, diagnostic models for PRAD were developed and validated. The random forest algorithm pinpointed HSPE1 as the most crucial prognostic gene among the stem cell-related genes. Furthermore, the study delved into the association between HSPE1 and immune infiltration, and employed molecular docking to investigate the relationship between HSPE1 and its associated compounds. Immunofluorescence staining analysis of 60 PRAD tissue samples confirmed the expression of HSPE1 and its correlation with patient prognosis in PRAD.Result: This study identified 15 crucial stem cell-related genes through single-cell analysis, highlighting their importance in diagnosing, prognosticating, and potentially treating PRAD patients. HSPE1 was specifically linked to PRAD prognosis and response to immunotherapy, with experimental data supporting its upregulation in PRAD and association with poorer prognosis.Overall, our findings underscore the significant role of stem cell-related genes in PRAD and unveil HSPE1 as a novel target related to stem cell.
Keywords: Cancer stem cell, Prostate adenocarcinoma, single cell analysis, machine learning, HSPE1
Received: 14 Jul 2024; Accepted: 12 Aug 2024.
Copyright: © 2024 Wang, Li, He, Gu and Zhu. 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:
YaXuan Wang, First Affiliated Hospital of Harbin Medical University, Harbin, China
Ma Li, Department of Pharmacy, Wuhan Third Hospital, Wuhan, Hebei Province, China
Jiaxin He, First Affiliated Hospital of Harbin Medical University, Harbin, China
Haijuan Gu, Nantong Tumor Hospital, Nantong, 226000, Jiangsu Province, China
Haixia Zhu, Nantong Tumor Hospital, Nantong, 226000, Jiangsu Province, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.