System analysis based on the lysosome-related genes identifies HPS4 as a novel therapy target for liver hepatocellular carcinoma
Background Liver cancer is a leading cause of cancer-related deaths worldwide. Lysosomal dysfunction is implicated in cancer progression; however, prognostic prediction models based on lysosome-related genes (LRGs) are lacking in liver cancer. This study aimed to establish an LRG-based model to impr...
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Published in | Frontiers in oncology Vol. 13; p. 1221498 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Frontiers Media S.A
13.09.2023
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Subjects | |
Online Access | Get full text |
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Summary: | Background
Liver cancer is a leading cause of cancer-related deaths worldwide. Lysosomal dysfunction is implicated in cancer progression; however, prognostic prediction models based on lysosome-related genes (LRGs) are lacking in liver cancer. This study aimed to establish an LRG-based model to improve prognosis prediction and explore potential therapeutic targets in liver cancer.
Methods
Expression profiles of 61 LRGs were analyzed in The Cancer Genome Atlas liver cancer cohorts. There were 14 LRGs identified, and their association with clinical outcomes was evaluated. Unsupervised clustering, Cox regression, and functional assays were performed.
Results
Patients were classified into high-risk and low-risk subgroups based on the 14 LRGs. The high-risk group had significantly worse overall survival. Aberrant immune infiltration and checkpoint expression were observed in the high-risk group. Furthermore, HPS4 was identified as an independent prognostic indicator. Knockdown of HPS4 suppressed liver cancer cell proliferation and induced apoptosis.
Conclusion
This study developed an LRG-based prognostic model to improve risk stratification in liver cancer. The potential value of HPS4 as a therapeutic target and biomarker was demonstrated. Regulation of HPS4 may offer novel strategies for precision treatment in liver cancer patients. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Edited by: Zongli Zhang, Qilu Hospital of Shandong University, China These authors share first authorship Reviewed by: Xiaoting Huang, Guangzhou Medical University Cancer Hospital, China; Surendra Kumar Shukla, University of Oklahoma, United States; Sudhir Varma, Hithru Analytics LLC, United States |
ISSN: | 2234-943X 2234-943X |
DOI: | 10.3389/fonc.2023.1221498 |