The Necroptotic Process-Related Signature Predicts Immune Infiltration and Drug Sensitivity in Kidney Renal Papillary Cell Carcinoma.

Necroptosis drug sensitivity gene signature immune infiltration kidney renal papillary cell carcinoma. prognosis

Journal

Current cancer drug targets
ISSN: 1873-5576
Titre abrégé: Curr Cancer Drug Targets
Pays: Netherlands
ID NLM: 101094211

Informations de publication

Date de publication:
08 Apr 2024
Historique:
received: 10 11 2023
revised: 03 03 2024
accepted: 12 03 2024
medline: 15 4 2024
pubmed: 15 4 2024
entrez: 15 4 2024
Statut: aheadofprint

Résumé

It remains controversial whether the current subtypes of kidney renal papillary cell carcinoma (KIRP) can be used to predict the prognosis independently. This observational study aimed to identify a risk signature based on necroptotic pro-cess-related genes (NPRGs) in KIRP. In the training cohort, LASSO regression was applied to construct the risk signature from 158 NPRGs, followed by the analysis of Overall Survival (OS) using the Kaplan-Meier method. The signature accuracy was evaluated by the Receiver Operating Characteristic (ROC) curve, which was further validated by the test cohort. Wilcoxon test was used to compare the expressions of immune-related genes, neoantigen genes, and immune infiltration between differ-ent risk groups, while the correlation test was performed between NPRGs expressions and drug sensitivity. Gene set enrichment analysis was used to investigate the NPRGs' signature's biologi-cal functions. We finally screened out 4-NPRGs (BIRC3, CAMK2B, PYGM, and TRADD) for con-structing the risk signature with the area under the ROC curve (AUC) reaching about 0.8. The risk score could be used as an independent OS predictor. Consistent with the enriched signaling, the NPRGs signature was found to be closely associated with neoantigen, immune cell infiltration, and immune-related functions. Based on NPRGs expressions, we also predicted multiple drugs potentially sensitive or resistant to treatment. The novel 4-NPRGs risk signature can predict the prognosis, immune infiltration, and therapeutic sensitivity of KIRP.

Sections du résumé

BACKGROUND BACKGROUND
It remains controversial whether the current subtypes of kidney renal papillary cell carcinoma (KIRP) can be used to predict the prognosis independently.
OBJECTIVE OBJECTIVE
This observational study aimed to identify a risk signature based on necroptotic pro-cess-related genes (NPRGs) in KIRP.
METHODS METHODS
In the training cohort, LASSO regression was applied to construct the risk signature from 158 NPRGs, followed by the analysis of Overall Survival (OS) using the Kaplan-Meier method. The signature accuracy was evaluated by the Receiver Operating Characteristic (ROC) curve, which was further validated by the test cohort. Wilcoxon test was used to compare the expressions of immune-related genes, neoantigen genes, and immune infiltration between differ-ent risk groups, while the correlation test was performed between NPRGs expressions and drug sensitivity. Gene set enrichment analysis was used to investigate the NPRGs' signature's biologi-cal functions.
RESULTS RESULTS
We finally screened out 4-NPRGs (BIRC3, CAMK2B, PYGM, and TRADD) for con-structing the risk signature with the area under the ROC curve (AUC) reaching about 0.8. The risk score could be used as an independent OS predictor. Consistent with the enriched signaling, the NPRGs signature was found to be closely associated with neoantigen, immune cell infiltration, and immune-related functions. Based on NPRGs expressions, we also predicted multiple drugs potentially sensitive or resistant to treatment.
CONCLUSION CONCLUSIONS
The novel 4-NPRGs risk signature can predict the prognosis, immune infiltration, and therapeutic sensitivity of KIRP.

Identifiants

pubmed: 38616744
pii: CCDT-EPUB-139660
doi: 10.2174/0115680096286503240321040556
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Auteurs

Wenfeng Lin (W)

Department of Urology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.
Department of Urology, Affiliated Qingyuan Hospital, Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, China.

Ruizhi Xue (R)

Department of Urology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.
Department of Urology, Xiangya Hospital, Central South University, Changsha, China.

Hideo Ueki (H)

Department of Urology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.

Peng Huang (P)

Department of Urology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.
Neutron Therapy Research Center (NTCR), Okayama University, Okayama, Japan.

Classifications MeSH