Wei GH, Wei XY, Fan LY, Zhou WZ, Sun M, Zhu CD. Comprehensive assessment of the association between tumor-infiltrating immune cells and the prognosis of renal cell carcinoma. World J Clin Oncol 2024; 15(10): 1280-1292 [DOI: 10.5306/wjco.v15.i10.1280]
Corresponding Author of This Article
Chuan-Dong Zhu, MD, PhD, Assistant Professor, Chief Doctor, Department of Oncology, The Second Hospital of Nanjing, Affiliated to Nanjing University of Chinese Medicine, No. 1-1 Zhongfu District, Nanjing 210003, Jiangsu Province, China. zhucd@njucm.edu.cn
Research Domain of This Article
Computer Science, Interdisciplinary Applications
Article-Type of This Article
Clinical and Translational Research
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Guo-Hao Wei, Ling-Yao Fan, Wen-Zheng Zhou, Ming Sun, Chuan-Dong Zhu, Department of Oncology, The Second Hospital of Nanjing, Affiliated to Nanjing University of Chinese Medicine, Nanjing 210003, Jiangsu Province, China
Xi-Yi Wei, The State Key Laboratory of Reproductive, Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210003, Jiangsu Province, China
Author contributions: Wei GH wrote the article; Wei GH, Fan LY and Wei XY designed the experiments; Wei GH, Wei XY, Sun M and Zhou WZ analyzed data and contributed to the resources; Zhu CD supervised the study; All authors have read and approved the final manuscript.
Supported byThe Medical Scientific Research Project of the Jiangsu Health Commission, China, No. M2020055; The Nanjing Medical Science and Technology Development Project, China, No. YKK22130; and The Postgraduate Research and Practice Innovation Program of Jiangsu Province, China, No. KYCX23_2105.
Conflict-of-interest statement: The authors declare no conflicts of interest.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Chuan-Dong Zhu, MD, PhD, Assistant Professor, Chief Doctor, Department of Oncology, The Second Hospital of Nanjing, Affiliated to Nanjing University of Chinese Medicine, No. 1-1 Zhongfu District, Nanjing 210003, Jiangsu Province, China. zhucd@njucm.edu.cn
Received: July 4, 2024 Revised: August 7, 2024 Accepted: August 13, 2024 Published online: October 24, 2024 Processing time: 86 Days and 15.1 Hours
Abstract
BACKGROUND
According to current statistics, renal cancer accounts for 3% of all cancers worldwide. Renal cell carcinoma (RCC) is the most common solid lesion in the kidney and accounts for approximately 90% of all renal malignancies. Increasing evidence has shown an association between immune infiltration in RCC and clinical outcomes. To discover possible targets for the immune system, we investigated the link between tumor-infiltrating immune cells (TIICs) and the prognosis of RCC.
AIM
To investigate the effects of 22 TIICs on the prognosis of RCC patients and identify potential therapeutic targets for RCC immunotherapy.
METHODS
The CIBERSORT algorithm partitioned the 22 TIICs from the Cancer Genome Atlas cohort into proportions. Cox regression analysis was employed to evaluate the impact of 22 TIICs on the probability of developing RCC. A predictive model for immunological risk was developed by analyzing the statistical relationship between the subpopulations of TIICs and survival outcomes. Furthermore, multivariate Cox regression analysis was used to investigate independent factors for the prognostic prediction of RCC. A value of P < 0.05 was regarded as statistically significant.
RESULTS
Compared to normal tissues, RCC tissues exhibited a distinct infiltration of immune cells. An immune risk score model was established and univariate Cox regression analysis revealed a significant association between four immune cell types and the survival risk connected to RCC. High-risk individuals were correlated to poorer outcomes according to the Kaplan-Meier survival curve (P = 1E−05). The immunological risk score model was demonstrated to be a dependable predictor of survival risk (area under the curve = 0.747) via the receiver operating characteristic curve. According to multivariate Cox regression analysis, the immune risk score model independently predicted RCC patients' prognosis (hazard ratio = 1.550, 95%CI: 1.342–1.791; P < 0.001). Finally, we established a nomogram that accurately and comprehensively forecast the survival of patients with RCC.
CONCLUSION
TIICs play various roles in RCC prognosis. The immunological risk score is an independent predictor of poor survival in kidney cancer cases.
Core Tip: Renal cell carcinoma (RCC) is a prevalent form of renal cancer that typically arises subtly and is distinguished by its propensity for easy metastasis and poor prognosis. Patients with advanced RCC frequently exhibit low overall survival rates owing to the extensive spread of cancer. However, the recent advent of immunotherapy has resulted in an improvement in the median overall survival for all risk groups of patients, making it imperative to identify potential immune targets. Our research has led to the development of an immune risk assessment model that underscores the critical role of tumor-infiltrating immune cells-based immune models in the prognostic prediction and clinical management of RCC.
