Comprehensive analyses of nuclear mitochondria‐related genes in the molecular features, immune infiltration, and drug sensitivity of clear cell renal cell carcinoma

Abstract Background Clear cell renal cell carcinoma (ccRCC) is one of the most common urological diseases and the most common subtype of renal cell carcinoma. Nuclear mitochondria‐related genes (MTRGs) play an essential role in cancer, but their effect on ccRCC has not been clarified. This work aimed to investigate the role of nuclear MTRGs in ccRCC. Methods We collected nuclear MTRGs from the MITOMAP database and obtained the ccRCC profile from the TCGA database. Gene expression validation came from the GEO database. The ccRCC subtypes were determined by unsupervised clustering analysis based on the nuclear MTRGs. Immune scores were computed using the EPIC algorithm. The drug sensitivity scores were calculated using GDSC resources. A nomogram explored the diagnostic value of the nuclear MTRGs. Results In total, 11 nuclear MTRGs were identified as both related to prognosis and differentially expressed in ccRCC, showing a significant positive correlation with CD274 expression. We determined two subtypes of ccRCC based on these genes and found remarkable differences in survival status, immune infiltration, mutation landscape, and drug sensitivity between the two subtypes. The high‐MTRG group had a better prognosis and a lower tumor stage than the low‐MTRG group. Immune checkpoint blockade therapy was more effective for the high‐MTRG group. A nomogram based on the nuclear MTRGs concluded that patients with a higher score had poorer survival. SUCLA2 (succinate‐CoA ligase ADP‐forming subunit beta) was identified as the hub gene linked to ccRCC. High SUCLA2 expression showed a correlation with better survival and a negative correlation with the tumor mutation burden in ccRCC. Pan‐cancer analysis revealed wide‐ranging roles for SUCLA2 across human tumors. Conclusions Nuclear MTRGs play vital roles in determining the molecular features, immune infiltration, and drug sensitivity of ccRCC. High levels of nuclear MTRGs may indicate a better prognosis for patients with ccRCC. SUCLA2 is a representative nuclear MTRG and may serve as a protective biomarker in ccRCC. Our study provides therapeutic guidance and potential biomarkers for ccRCC patients, and contributes to the advancement of precision medicine.

Authors

Institutions

Publication Details

Journal
Medicine Advances
Published
2024-09-01
DOI
https://doi.org/10.1002/med4.72
Citations
10
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
4.19

Funders

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

Comprehensive analyses of nuclear mitochondria‐related genes in the molecular features, immune infiltration, and drug sensitivity of clear cell renal cell carcinoma

Yuchen Zhang, Feixiang Yang, Miao Cheng, Huake Cao et al.
10 citations
Medicine Advances
Ferroptosis and cancer prognosis
4.19
article

Comprehensive analyses of nuclear mitochondria‐related genes in the molecular features, immune infiltration, and drug sensitivity of clear cell renal cell carcinoma

Yuchen Zhang, Feixiang Yang, Miao Cheng, Huake Cao, Zhihao Xu, Ning Zhang, Yinyin Xie, Shuqi Yang, Xuefeng Tian, Xiaofeng Wang
article en
10 citations

Abstract

Abstract Background Clear cell renal cell carcinoma (ccRCC) is one of the most common urological diseases and the most common subtype of renal cell carcinoma. Nuclear mitochondria‐related genes (MTRGs) play an essential role in cancer, but their effect on ccRCC has not been clarified. This work aimed to investigate the role of nuclear MTRGs in ccRCC. Methods We collected nuclear MTRGs from the MITOMAP database and obtained the ccRCC profile from the TCGA database. Gene expression validation came from the GEO database. The ccRCC subtypes were determined by unsupervised clustering analysis based on the nuclear MTRGs. Immune scores were computed using the EPIC algorithm. The drug sensitivity scores were calculated using GDSC resources. A nomogram explored the diagnostic value of the nuclear MTRGs. Results In total, 11 nuclear MTRGs were identified as both related to prognosis and differentially expressed in ccRCC, showing a significant positive correlation with CD274 expression. We determined two subtypes of ccRCC based on these genes and found remarkable differences in survival status, immune infiltration, mutation landscape, and drug sensitivity between the two subtypes. The high‐MTRG group had a better prognosis and a lower tumor stage than the low‐MTRG group. Immune checkpoint blockade therapy was more effective for the high‐MTRG group. A nomogram based on the nuclear MTRGs concluded that patients with a higher score had poorer survival. SUCLA2 (succinate‐CoA ligase ADP‐forming subunit beta) was identified as the hub gene linked to ccRCC. High SUCLA2 expression showed a correlation with better survival and a negative correlation with the tumor mutation burden in ccRCC. Pan‐cancer analysis revealed wide‐ranging roles for SUCLA2 across human tumors. Conclusions Nuclear MTRGs play vital roles in determining the molecular features, immune infiltration, and drug sensitivity of ccRCC. High levels of nuclear MTRGs may indicate a better prognosis for patients with ccRCC. SUCLA2 is a representative nuclear MTRG and may serve as a protective biomarker in ccRCC. Our study provides therapeutic guidance and potential biomarkers for ccRCC patients, and contributes to the advancement of precision medicine.

Medicine AdvancesVol. 2(3)
Anhui Medical University (CN), First Affiliated Hospital of Anhui Medical University (CN)
Anhui Medical University, National College Students Innovation and Entrepreneurship Training Program
No poverty
Openalex Percentile: Top 5%
Ferroptosis and cancer prognosis
4.19
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.