AUTHOR=Zhang Fan , Liang Jiayu , Feng Dechao , Liu Shengzhuo , Wu Jiapei , Tang Yongquan , Liu Zhihong , Lu Yiping , Wang Xianding , Wei Xin 

TITLE=Integrated Analysis of Energy Metabolism Signature-Identified Distinct Subtypes of Bladder Urothelial Carcinoma

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2022.814735

DOI=10.3389/fcell.2022.814735

ISSN=2296-634X

ABSTRACT=Background
Bladder Urothelial Carcinoma (BLCA) is the most common type of bladder cancer. In this study the correlation between metabolic status and outcome of BLCA patients was evaluated using data from The Cancer Genome atlas and Gene Expression Omnibus datasets.
Methods
The clinical and transcriptomic data of BLCA patients were downloaded from The Cancer Genome Atlas and GSE13507 datasets, and energy metabolic-related gene sets were contained from Molecular Signature Database. Then, consensus clustering algorithm was conducted to identify patients into two clusters. The tumor prognosis, clinicopathological feathers, mutations, functional analysis, ferroptosis status analysis, immune infiltration, immune checkpoint related gene expression level, chemotherapy resistance and tumor stem cells were analyzed between clusters. An energy metabolic-related signature was further developed and verified by data from GSE13507 dataset.
Results
Two clusters (C1 and C2) were identified by consensus clustering algorithm based on energy metabolic-related signature. The patients in subtype C1 had more metabolism-related pathways, more active ferroptosis status, higher cancer stem cells scores, higher chemotherapy resistance, and a better prognosis. Subtype C2 was characterized by increased advance BLCA cases and immune-related pathways. A higher immune score, stromal score was also observed in C2 subtype. A signature containing four energy metabolic-related genes was then identified and can accurately predict prognosis of BLCA patients.
Conclusion
We have found the energy metabolic associated subtypes of BLCA are closely related to the immune microenvironment, immune checkpoint related gene expression, ferroptosis status, CSCs, chemotherapy resistance, prognosis and progression of BLCA patients. The established energy metabolic-related gene signature was able to predict survival among BLCA patients.