Clinical importance of the expression of CD4+CD8+ T cells in renal cell carcinoma

Nishida, Kentaro; Kawashima, Atsunari; Kanazawa, Takayuki; Kidani, Yujiro; Yoshida, Tetsuya; Hirata, Michinari; Yamamoto, Kei; Yamamoto, Yoko; Sawada, Masaaki; Kato, Ryo; Kato, Taigo; Hatano, Koji; Ujike, Takeshi; Fujita, Kazutoshi; Uemura, Mamoru; Morimoto-Okazawa, Akiko; Iwahori, Kota; Yamasaki, Makoto; Ohkura, Naganari; Sakaguchi, Shimon; Nonomura, Norio; Doki, Yuichiro; Wada, Hisashi

doi:10.1093/intimm/dxaa004

Cited by 14 publications

(14 citation statements)

References 39 publications

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“… 47 Some previous studies also show that CD4+ T cells are upregulated and are significantly correlated with OS in RCC. 48–50 These previous results were consistent with our findings as a higher abundance ratio of Treg cells was identified in patients with worse OS. Nakanishi et al showed that mast cells played an important role in tumor growth, progression, and malignant aggressiveness of RCC tissues, 51 which was consistent with our findings that the larger quantity of mast cells resting was associated with a better prognosis.…”

Section: Discussionsupporting

confidence: 93%

A Bioinformatic Analysis of Immune-Related Prognostic Genes in Clear Cell Renal Cell Carcinoma Based on TCGA and GEO Databases

Li¹,

Cao²,

Li³

et al. 2022

IJGM

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Background Clear cell renal cell carcinoma (ccRCC) is a commonly occurring tumor. Through a deeper understanding of the immune regulatory mechanisms in the tumor microenvironment, immunotherapy may serve as a potential treatment for cancer patients. This study aimed at identifying the survival-related immune cells and hub genes, which could be potential targets for immunotherapy in ccRCC. Methods The gene expression profiles and clinical data of ccRCC patients were extracted from UCSC Xena and Gene Expression Omnibus (GEO) databases. Kaplan–Meier (KM) survival and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were utilized to select the survival-related tumor-infiltrating immune cells. Multivariate Cox regression was utilized to develop a signature based on the tumor-infiltrating immune cells (TIICs). Based on the signature, the risk score was calculated, following which the samples were divided into high-risk and low-risk groups. Differentially expressed genes (DEGs) between the two risk groups were identified. Functional enrichment analysis was performed and cytoHubba plug-in of Cytoscape was used to identify the hub genes. Multiple datasets were utilized to validate these hub genes, including the Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and the Human Protein Atlas (HPA), and the GEO datasets. Finally, a correlation analysis was performed to evaluate the relationship between the hub genes and TIICs. Results Four immune survival-related cells, including T cell CD4 memory-activated, T cell regulatory (Tregs), eosinophils, and mast cell resting were identified. Nine immune-specific hub genes were identified, which included APOE, CASR, CTLA4, CXCL8, EGF, F2, KNG1, MMP9 , and IL6 . Furthermore, these hub genes were significantly correlated with clinical traits and closely associated with some TIICs. Conclusion A total of four survival-related immune cell types and nine hub genes were found to be closely associated with ccRCC. These findings may have implications for the development of novel potential immunotherapeutic targets for ccRCC.

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Section: Discussionsupporting

confidence: 93%

A Bioinformatic Analysis of Immune-Related Prognostic Genes in Clear Cell Renal Cell Carcinoma Based on TCGA and GEO Databases

Li¹,

Cao²,

Li³

et al. 2022

IJGM

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“…Previous study revealed that CD4 + T cells could promote tumor cell proliferation in RCC [55]. Moreover, another study found that CD4 + T cells in RCC patients were associated with favorable prognosis [56]. Therefore, BIRC5 may also regulate tumor cell biological process, thus affecting the prognosis of chRCC via CD4 + T cells.…”

Section: Discussionmentioning

confidence: 97%

Exploration of immune-related genes in high and low tumor mutation burden groups of chromophobe renal cell carcinoma

Chen

Hao³

et al. 2020

Bioscience Reports

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Renal cell carcinoma (RCC) is one of most common cancer with gradually increasing incidence and high mortality. chromogenic RCC (chRCC) is the third most common histological subtype of RCC, accounting for about 5-7% of RCC. In our study, the transcriptome expression profile data (n=89) of chRCC, corresponding clinical data (n=113) and the somatic mutation data (n=66) was obtained from the TCGA database. We first analyzed the mutation data of chRCC patients and divided chRCC patients into high and low tumor mutation burden (TMB) groups based on the median TMB. We found that high TMB was significantly associated with worse prognosis and could promote tumor metastasis and development. Moreover, four different immune-related genes (BIRC5, PDGFRL, INHBE, IL20RB) were also identified. We found that BIRC5 was significantly overexpressed in the high TMB group and correlated with worse prognosis. The result of univariate and multivariate COX analysis demonstrated that BIRC5 (HR=2.094) may serve as a prognostic indicator for patients with chRCC with high TMB. In addition, we identified the possible functional pathways of BIRC5 through GSEA enrichment. A positive correlation was obtained between BIRC5 and the abundance of CD4 + T cells. The result of our study revealed their correlation between the immune-related genes and clinicopathologic features as well as potential functional pathways as well as immune infiltrating cells, which may provide more data about the development of chRCC immunotherapy.

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“…Depletion or decrease of peripheral and intratumoral CD4+ T cells is more prone to inactivate the anti-tumor response and lead to deterioration and progression of the disease. Actually, various previous studies have already elucidated and verified that CD4+/CD8+ ratio can serve as independent prognostic predictors in multiple cancers, including laryngeal squamous cell carcinoma, 45 renal cell cancer, 72 nasopharyngeal carcinoma, 46 gastric cancer, 73 cervical cancer, 74 etc. Similarly, our study also demonstrated that CD4+/CD8+ ratio is a reliable and accurate prognostic predictor for patients with advanced osteosarcoma.…”

Section: Figurementioning

confidence: 99%

<p>CONUT Score or/and Peripheral Blood CD4+/CD8+ Ratio-Based Web Dynamic Nomograms to Predict the Individualized Survival of Patients with Advanced Osteosarcoma</p>

Yang

Wang

et al. 2020

CMAR

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Background: Nutritional and immune status is paramount for the overall survival (OS) of patients with advanced osteosarcoma. Comprehensive prognostic predictors based on the two indices are scarce. This study aimed to construct and validate individualized web dynamic nomograms based on CONUT score or/and peripheral blood CD4+/CD8+ ratio for OS in patients with advanced osteosarcoma. Materials and Methods: The clinical data of 376 advanced osteosarcoma patients from January 2000 to December 2019 were retrospectively collected. Data from the 301 patients (diagnosed in the first 15 years) were used as the development set and data from the remaining 75 patients were assigned as the validation set. Multivariate Cox regression analyses were conducted and three prediction models were constructed, namely, CD4 +/CD8+ ratio univariate model (model 1), CONUT score univariate model (model 2), and CD4+/CD8+ ratio plus CONUT score (model 3). These models were visualized by conventional nomograms and individualized web dynamic nomograms, and their performances were further evaluated by C-index, calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA), respectively. Results: In multivariate Cox analysis, age, metastasis, ALP, CD4+/CD8+ ratio, chemotherapy, and CONUT score were identified as independent prognostic factors for OS. The calibration curves of the three models all showed good agreement between the actual observation and nomogram prediction for 1-year overall survival. In the development set, the C-index and area under the curve (AUC) of model 3 (0.837, 0.848) were higher than that of model 1 (0.765, 0.773) and model 2 (0.712, 0.749). Similar trends were observed in the validation set. The net benefits of model 3 were better than the other two models within the threshold probability of 36-80% in DCA. Conclusion: CONUT score and peripheral CD4+/CD8+ ratio are easily available, reliable, and economical prognostic predictors for survival prediction and stratification in patients with advanced osteosarcoma, but the two predictors combined can establish a better prognosis prediction model.

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Clinical importance of the expression of CD4+CD8+ T cells in renal cell carcinoma

Cited by 14 publications

References 39 publications

A Bioinformatic Analysis of Immune-Related Prognostic Genes in Clear Cell Renal Cell Carcinoma Based on TCGA and GEO Databases

A Bioinformatic Analysis of Immune-Related Prognostic Genes in Clear Cell Renal Cell Carcinoma Based on TCGA and GEO Databases

Exploration of immune-related genes in high and low tumor mutation burden groups of chromophobe renal cell carcinoma

<p>CONUT Score or/and Peripheral Blood CD4+/CD8+ Ratio-Based Web Dynamic Nomograms to Predict the Individualized Survival of Patients with Advanced Osteosarcoma</p>

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