{"title":"Comprehensive assessment of the association between tumor-infiltrating immune cells and the prognosis of renal cell carcinoma.","authors":"Guo-Hao Wei, Xi-Yi Wei, Ling-Yao Fan, Wen-Zheng Zhou, Ming Sun, Chuan-Dong Zhu","doi":"10.5306/wjco.v15.i10.1280","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Aim: </strong>To investigate the effects of 22 TIICs on the prognosis of RCC patients and identify potential therapeutic targets for RCC immunotherapy.</p><p><strong>Methods: </strong>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 <i>P</i> < 0.05 was regarded as statistically significant.</p><p><strong>Results: </strong>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 (<i>P</i> = 1<sup>E-05</sup>). The immunological risk score model was demonstrated to be a dependable predictor of survival risk (area under the curve = 0.747) <i>via</i> 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; <i>P</i> < 0.001). Finally, we established a nomogram that accurately and comprehensively forecast the survival of patients with RCC.</p><p><strong>Conclusion: </strong>TIICs play various roles in RCC prognosis. The immunological risk score is an independent predictor of poor survival in kidney cancer cases.</p>","PeriodicalId":23802,"journal":{"name":"World journal of clinical oncology","volume":"15 10","pages":"1280-1292"},"PeriodicalIF":2.6000,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11514508/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"World journal of clinical oncology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5306/wjco.v15.i10.1280","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍：
The WJCO is a high-quality, peer reviewed, open-access journal. The primary task of WJCO is to rapidly publish high-quality original articles, reviews, editorials, and case reports in the field of oncology. In order to promote productive academic communication, the peer review process for the WJCO is transparent; to this end, all published manuscripts are accompanied by the anonymized reviewers’ comments as well as the authors’ responses. The primary aims of the WJCO are to improve diagnostic, therapeutic and preventive modalities and the skills of clinicians and to guide clinical practice in oncology. Scope: Art of Oncology, Biology of Neoplasia, Breast Cancer, Cancer Prevention and Control, Cancer-Related Complications, Diagnosis in Oncology, Gastrointestinal Cancer, Genetic Testing For Cancer, Gynecologic Cancer, Head and Neck Cancer, Hematologic Malignancy, Lung Cancer, Melanoma, Molecular Oncology, Neurooncology, Palliative and Supportive Care, Pediatric Oncology, Surgical Oncology, Translational Oncology, and Urologic Oncology.
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