Integrative analysis and risk model construction for super‑enhancer‑related immune genes in clear cell renal cell carcinoma

Bi,Zhenyu; Zhou,Jinghao; Ma,Yan; Guo,Qingxin; Ju,Boyang; Zou,Haoran; Zhan,Zuhao; Yang,Feihong; Du,Han; Gan,Xiuguo; Song,Erlin

doi:10.3892/ol.2024.14323

Integrative analysis and risk model construction for super‑enhancer‑related immune genes in clear cell renal cell carcinoma

Authors:
- Zhenyu Bi
- Jinghao Zhou
- Yan Ma
- Qingxin Guo
- Boyang Ju
- Haoran Zou
- Zuhao Zhan
- Feihong Yang
- Han Du
- Xiuguo Gan
- Erlin Song
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Affiliations: Department of Urology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150000, P.R. China, Department of Oncology, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong 271000, P.R. China, Department of Urology, Hongqi Hospital Affiliated to Mudanjiang Medical College, Mudanjiang, Heilongjiang 157009, P.R. China, Department of Urology, Zhumadian Central Hospital, Zhumadian, Henan 463000, P.R. China, Department of Urology, The First Hospital of Zibo, Zibo, Shandong 255200, P.R. China, Department of Urology, Affiliated Hospital of Guilin Medical University, Guilin, Guangxi Zhuang Autonomous Region 541001, P.R. China
Published online on: March 1, 2024 https://doi.org/10.3892/ol.2024.14323
Article Number: 190
Copyright: © Bi et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer associated with poor prognosis, and accounts for the majority of RCC‑related deaths. The lack of comprehensive diagnostic and prognostic biomarkers has limited further understanding of the pathophysiology of ccRCC. Super‑enhancers (SEs) are congregated enhancer clusters that have a key role in tumor processes such as epithelial‑mesenchymal transition, metabolic reprogramming, immune escape and resistance to apoptosis. RCC may also be immunogenic and sensitive to immunotherapy. In the present study, an Arraystar human SE‑long non‑coding RNA (lncRNA) microarray was first employed to profile the differentially expressed SE‑lncRNAs and mRNAs in 5 paired ccRCC and peritumoral tissues and to identify SE‑related genes. The overlap of these genes with immune genes was then determined to identify SE‑related immune genes. A model for predicting clinical prognosis and response to immunotherapy was built following the comprehensive analysis of a ccRCC gene expression dataset from The Cancer Genome Atlas (TCGA) database. The patients from TCGA were divided into high‑ and low‑risk groups based on the median score derived from the risk model, and the Kaplan‑Meier survival analysis showed that the low‑risk group had a higher survival probability. In addition, according to the receiver operating characteristic curve analysis, the risk model had more advantages than other clinical factors in predicting the overall survival (OS) rate of patients with ccRCC. Using this model, it was demonstrated that the high‑risk group had a more robust immune response. Furthermore, 61 potential drugs with half‑maximal inhibitory concentration values that differed significantly between the two patient groups were screened to investigate potential drug treatment of ccRCC. In summary, the present study provided a novel index for predicting the survival probability of patients with ccRCC and may provide some insights into the mechanisms through which SE‑related immune genes influence the diagnosis, prognosis and potential treatment drugs of ccRCC.

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