Comprehensive bioinformatics and immunohistochemical analyses identify phosphoinositide metabolism and PNPLA7 as potential biomarkers in urological cancers

Phosphoinositides (PI) and their metabolic enzymes are known to be involved in cellular processes associated with the hallmarks of cancer. The impact of PI metabolism-related components on urinary tract (or urological) cancers, however, remains unexplored. Considering this, herein, we performed a comprehensive bioinformatic analysis on clear cell renal carcinoma, bladder cancer, and adenocarcinoma of the prostate using public databases to investigate the relative contribution of PI metabolism in these clinical phenotypes. Primarily, we computed phosphoinositide metabolism scores to assess the associated biological processes and further enriched the analysis by predicting drug sensitivity, immune profiling, and risk stratification. Besides, we utilized single-cell RNA sequencing datasets to identify intercellular communication networks associated with PI metabolism in these cancer subtypes. Of interest, our analysis identified the PNPLA7 gene as a potential biomarker in urological cancers, which we validated using immunohistochemical evaluation of clinical samples. In conclusion, our study reveals that PI metabolism is a critical prognostic biomarker for urological cancers and may guide drug therapies, including immunosuppressants. Therefore, PNPLA7 could serve as a potential target and requires further attention.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-04-12
DOI
https://doi.org/10.1038/s41598-025-97118-9
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comprehensive bioinformatics and immunohistochemical analyses identify phosphoinositide metabolism and PNPLA7 as potential biomarkers in urological cancers

Yinhao Chen, Maria Angeles Gonzalez-Carmona, Maria F. Setiawan, Mingde Gao et al.
Scientific Reports
Ferroptosis and cancer prognosis
article

Comprehensive bioinformatics and immunohistochemical analyses identify phosphoinositide metabolism and PNPLA7 as potential biomarkers in urological cancers

Yinhao Chen, Maria Angeles Gonzalez-Carmona, Maria F. Setiawan, Mingde Gao, Peng Chen, Xiaolin Wang, Amit Sharma, Ingo G. H. Schmidt-Wolf
article en

Abstract

Phosphoinositides (PI) and their metabolic enzymes are known to be involved in cellular processes associated with the hallmarks of cancer. The impact of PI metabolism-related components on urinary tract (or urological) cancers, however, remains unexplored. Considering this, herein, we performed a comprehensive bioinformatic analysis on clear cell renal carcinoma, bladder cancer, and adenocarcinoma of the prostate using public databases to investigate the relative contribution of PI metabolism in these clinical phenotypes. Primarily, we computed phosphoinositide metabolism scores to assess the associated biological processes and further enriched the analysis by predicting drug sensitivity, immune profiling, and risk stratification. Besides, we utilized single-cell RNA sequencing datasets to identify intercellular communication networks associated with PI metabolism in these cancer subtypes. Of interest, our analysis identified the PNPLA7 gene as a potential biomarker in urological cancers, which we validated using immunohistochemical evaluation of clinical samples. In conclusion, our study reveals that PI metabolism is a critical prognostic biomarker for urological cancers and may guide drug therapies, including immunosuppressants. Therefore, PNPLA7 could serve as a potential target and requires further attention.

Scientific ReportsVol. 15(1)
University Hospital Bonn (DE), Integrated Oncology (United States) (US)
China Scholarship Council
Openalex Percentile: Top 88%
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.