AUTHOR=Han Zhijun , Wang Hao , Long Jing , Qiu Yanning , Xing Xiao-Liang 

TITLE=Establishing a prognostic model of ferroptosis- and immune-related signatures in kidney cancer: A study based on TCGA and ICGC databases

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.931383

DOI=10.3389/fonc.2022.931383

ISSN=2234-943X

ABSTRACT=Background: Kidney cancer (KC) is one of the most challenging cancers due to its delayed diagnosis and high metastasis rate. The five-year survival rate of KC patients is less than 11.2%. Therefore, identifying suitable biomarkers to accurately predict KC outcomes is important and urgent. Methods: Corresponding data for KC patients were obtained from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases. Systems biology/bioinformatics/computational approaches were used to identify suitable biomarkers for predicting the outcome and immune landscapes of KC patients. Results: We found two ferroptosis- and immune-related differentially expressed genes (FI-DEGs) (Klotho (KL) and Sortilin 1 (SORT1)) independently correlated with the overall survival of KC patients. Area under the curve (AUC) values of the prognosis model using these two FI-DEGs exceeded 0.60 in the training, validation, and entire groups. The AUC value of the one-year receiver operating characteristic (ROC) curve reached 0.70 in all the groups. Conclusions: Our present study indicated that KL and SORT1 could be prognostic biomarkers for KC patients. Whether this model can be used in clinical settings requires further validation.