Correlation between Genes of the ceRNA Network and Tumor-Infiltrating Immune Cells and Their Biomarker Screening in Kidney Renal Clear Cell Carcinoma

Aoran Kong; Hui Dong; Guangwen Zhang; Shuang Qiu; Mengyuan Shen; Xiaohan Niu; Lixin Wang

doi:10.1155/2022/4084461

Correlation between Genes of the ceRNA Network and Tumor-Infiltrating Immune Cells and Their Biomarker Screening in Kidney Renal Clear Cell Carcinoma

J Oncol. 2022 Aug 29:2022:4084461. doi: 10.1155/2022/4084461. eCollection 2022.

Authors

Aoran Kong^{1

2}, Hui Dong³, Guangwen Zhang⁴, Shuang Qiu⁵, Mengyuan Shen⁶, Xiaohan Niu⁷, Lixin Wang¹

Affiliations

¹ Center of Laboratory Medicine, General Hospital of Ningxia Medical University, Yinchuan 750004, China.
² Clinical Laboratory, XiangYang Hospital of Traditional Chinese Medicine, Xiangyang, Hubei 441000, China.
³ Institute of Medical Sciences, General Hospital of Ningxia Medical University, Yinchuan 750004, China.
⁴ Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
⁵ Clinical Laboratory, Yichang Central Hospital, Yichang, Hubei 443000, China.
⁶ Clinical Laboratory, ShangHai Changzheng Hospital, Shanghai 200003, China.
⁷ Department of Medical Examination, The People's Hospital of West Coast, Qingdao, Shangdong 2664000, China.

Abstract

This study aimed to using bioinformatics tools, qPCR, and the immunohistochemical analysis to find out factors related to the early diagnosis and prognosis of kidney renal clear cell carcinoma (KIRC). The expression profiles of lncRNA, miRNA, and mRNA of KIRC were downloaded from The Cancer Genome Atlas database. A ceRNA regulatory network was constructed based on the interaction between these three differentially expressed genes. The CIBERSORT deconvolution algorithm was used to analyze the differential distribution of 22 types of immune cells. The Kaplan-Meier survival and Cox analyses were used to screen genes of the ceRNA network and also immune cell subtypes related to the clinical and prognostic prediction of KIRC. Co-expression regulatory relationships were found among LINC01426, LINC00894, CCNA2, L1 cell adhesion molecule (L1CAM), and T follicular helper cells, which served as potential biomarkers. The results of quantitative reverse transcriptase-polymerase chain reaction showed that LINC01426 was upregulated while L1CAM was downregulated in KIRC, but no difference was found in the expression levels of LINC00894 and CCNA2 in cancer and adjacent samples. The immunohistochemical analysis showed that T follicular helper cells were more concentrated in core tissues and metastases of KIRC. In a word, co-expression relationships were found among LINC01426, L1CAM, and T follicular helper cells, and they may serve as biomarkers for early diagnosis and prognostic evaluation of KIRC.