A Novel Prognostic Biomarker CENPF in Papillary Renal Cell Carcinoma

Background: The objective of this study was to examine the expression disparity, prognostic implication, and potential mechanism of centromeric protein F (CENPF) in papillary renal cell carcinoma (PRCC). A series of advanced methods were employed, including the utilisation of the R language for data analysis, the incorporation of the Human Protein Mapping (HPA) database as a resource, functional enrichment analysis, single sample gene set enrichment analysis (ssGSEA), epigenetic studies (including the EWAS and MEXPRESS platforms), survival analysis and Cox regression analysis, amongst others. The expression characteristics, prognostic associations, and potential carcinogenic pathways of CENPF in PRCC were subjected to analysis. The findings indicated that CENPF was markedly overexpressed in PRCC and was significantly correlated with poor prognosis. Results: A growing body of evidence from studies on papillary renal cell carcinoma indicates that the expression level of the CENPF gene is significantly elevated. This abnormally high expression is found to be closely related to several core clinicopathological features, including pathological stage, T stage reflecting tumour size and invasion, N stage reflecting lymph node metastasis, and M stage indicating the presence of distant metastasis. Furthermore, the age of the patient is a contributing factor. A comprehensive examination substantiated a notable correlation between elevated CENPF expression and diminished overall survival. Furthermore, high expression was linked to reduced disease-specific survival and progression-free survival. CENPF is a key biomarker for evaluating the prognosis of patients with renal papillary cell carcinoma and can provide an important reference for clinical decision-making. Furthermore, multivariate Cox regression analysis confirmed that CENPF is not only an independent predictor of poor prognosis but also independently affects the overall survival of patients, thereby highlighting its central role in prognosis assessment. There was a positive correlation between CENPF overexpression and the degree of infiltration of multiple immune cell subpopulations, including helper T cell type 2, activated dendritic cells, central memory T cells, and helper T cells. Conclusion: CENPF is a pivotal marker in the field of papillary renal cell carcinoma research, offering a scientific foundation for prognostic assessment and targeted therapy development. An analysis of CENPF expression can accurately predict the prognosis of patients and facilitate the implementation of a personalised treatment plan.

Authors

Institutions

Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1145/3718677.3718700
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Novel Prognostic Biomarker CENPF in Papillary Renal Cell Carcinoma

Hongci Chen, Youhong Hu, Huiyun Pu, Ping Yang
1 links
Ferroptosis and cancer prognosis
article

A Novel Prognostic Biomarker CENPF in Papillary Renal Cell Carcinoma

Hongci Chen, Youhong Hu, Huiyun Pu, Ping Yang
article en

Abstract

Background: The objective of this study was to examine the expression disparity, prognostic implication, and potential mechanism of centromeric protein F (CENPF) in papillary renal cell carcinoma (PRCC). A series of advanced methods were employed, including the utilisation of the R language for data analysis, the incorporation of the Human Protein Mapping (HPA) database as a resource, functional enrichment analysis, single sample gene set enrichment analysis (ssGSEA), epigenetic studies (including the EWAS and MEXPRESS platforms), survival analysis and Cox regression analysis, amongst others. The expression characteristics, prognostic associations, and potential carcinogenic pathways of CENPF in PRCC were subjected to analysis. The findings indicated that CENPF was markedly overexpressed in PRCC and was significantly correlated with poor prognosis. Results: A growing body of evidence from studies on papillary renal cell carcinoma indicates that the expression level of the CENPF gene is significantly elevated. This abnormally high expression is found to be closely related to several core clinicopathological features, including pathological stage, T stage reflecting tumour size and invasion, N stage reflecting lymph node metastasis, and M stage indicating the presence of distant metastasis. Furthermore, the age of the patient is a contributing factor. A comprehensive examination substantiated a notable correlation between elevated CENPF expression and diminished overall survival. Furthermore, high expression was linked to reduced disease-specific survival and progression-free survival. CENPF is a key biomarker for evaluating the prognosis of patients with renal papillary cell carcinoma and can provide an important reference for clinical decision-making. Furthermore, multivariate Cox regression analysis confirmed that CENPF is not only an independent predictor of poor prognosis but also independently affects the overall survival of patients, thereby highlighting its central role in prognosis assessment. There was a positive correlation between CENPF overexpression and the degree of infiltration of multiple immune cell subpopulations, including helper T cell type 2, activated dendritic cells, central memory T cells, and helper T cells. Conclusion: CENPF is a pivotal marker in the field of papillary renal cell carcinoma research, offering a scientific foundation for prognostic assessment and targeted therapy development. An analysis of CENPF expression can accurately predict the prognosis of patients and facilitate the implementation of a personalised treatment plan.

Hubei University of Chinese Medicine (CN), Hubei Provincial Hospital of Traditional Chinese Medicine (CN)
Good health and well-being
Openalex Percentile: Top 55%
Ferroptosis and cancer prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.