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=12

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=<sec><title>Background</title><p>Kidney cancer (KC) is one of the most challenging cancers due to its delayed diagnosis and high metastasis rate. The 5-year survival rate of KC patients is less than 11.2%. Therefore, identifying suitable biomarkers to accurately predict KC outcomes is important and urgent.</p></sec><sec><title>Methods</title><p>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.</p></sec><sec><title>Results</title><p>We found two ferroptosis- and immune-related differentially expressed genes (FI-DEGs) (<italic>Klotho</italic> (<italic>KL</italic>) and <italic>Sortilin 1</italic> (<italic>SORT1</italic>)) independently correlated with the overall survival of KC patients. The 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 1-year receiver operating characteristic (ROC) curve reached 0.70 in all the groups.</p></sec><sec><title>Conclusions</title><p>Our present study indicated that <italic>KL</italic> and <italic>SORT1</italic> could be prognostic biomarkers for KC patients. Whether this model can be used in clinical settings requires further validation.</p></sec>