Tumor-infiltrating TNFRSF9
            <sup>+</sup>
            CD8
            <sup>+</sup>
            T cells define different subsets of clear cell renal cell carcinoma with prognosis and immunotherapeutic response

Li, Yaohui; Wang, Zewei; Jiang, Wenbin; Zeng, Han; Liu, Zhaopei; Lin, Zhiyuan; Qu, Yang; Xiong, Ying; Wang, Jiajun; Chang, Yuan; Bai, Qi; Wang, Yiwei; Liu, Li; Zhu, Yu; Xu, Liang; Yu, Xinbing; Guo, Jianming

doi:10.1080/2162402x.2020.1838141

Cited by 30 publications

(32 citation statements)

References 52 publications

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“…A large-scale analysis targeting ccRCC tumors confirmed T cells are the main TIICs within the TME. 45 Overall, higher CD8+ T cell infiltration in ccRCC is associated with worse outcomes, implying that the infiltrating CD8+ T cells might play a critical role in TME. Multiple ccRCC studies have confirmed that these infiltrating CD8+ T cells can be suppressed to become dysfunctional.…”

Section: Discussionmentioning

confidence: 90%

Prognostic Value of Metabolism-Related Genes and Immune Infiltration in Clear Cell Renal Cell Carcinoma

Li¹,

Mo²

2021

IJGM

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Background: Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent cancers. Thus, it is warranted to detect the status of metabolism-related genes (MRGs) and infiltrating immune cells in ccRCC progression for the prognosis of ccRCC. This research was designed to establish and verify the prognostic signature of ccRCC using MRGs. In addition, we investigated the potential link between the relative proportion of tumor infiltrated immune cells (TIICs) and ccRCC prognosis. Methods: Sequencing data of metabolism-related gene sets in ccRCC cases were obtained from The Cancer Genome Atlas database (TCGA) and Gene Expression Omnibus Database (GEO). The R Programming Language software packages were applied for differential analysis of MRGs. First, a univariate Cox regression model was applied to determine the MRGs linked with overall survival (OS). Then, the multivariate Cox regression model was applied to establish the prognostic signature. Finally, the CIBERSORT algorithm was used to determine the proportion of TIICs. Results: Overall, 286 differentially expressed MRGs were identified in the TCGA dataset. Univariate and multivariate Cox regression models were applied to develop a prognostic signature with six MRGs. The predictive capability of the prognostic signature was further verified by TCGA and GEO database. In addition, RS positively correlated with memory B cells, plasma cells, activated memory CD4+ T cells, follicular helper T cells, regulatory T cells, CD8+ T cells, and M0 macrophages, and were negatively associated with resting memory CD4+ T cells, resting dendritic cells, activated dendritic cells, M2 macrophages, monocytes, resting mast cells, and eosinophils. Conclusion: Herein, a prognostic signature was developed using MRGs for ccRCC prognosis. The proportion of 22 TIICs in ccRCC and the association between TIICs and clinical outcomes were also determined. The identified genes and cells could guide future targeted therapy and immunotherapy.

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Section: Discussionmentioning

confidence: 90%

Prognostic Value of Metabolism-Related Genes and Immune Infiltration in Clear Cell Renal Cell Carcinoma

Li¹,

Mo²

2021

IJGM

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“…Specifically, according to the data published by Gedye et al ( 2016 ), the total number of RCC tumor cells per mm 3 has a minimum value of 2.5 × 10 4 . The median number of CD8+ T cells varies among studies; we used as reference the value obtained by Li et al ( 2020 ) of 84 cells per mm 2 . To obtain the density of the other immune cells, we used the immune cell type absolute fraction data for ccRCC from the Cancer Immunome Atlas (TCIA) database (data available at https://tcia.at/cellTypeFractions ).…”

Section: Methodsmentioning

confidence: 99%

Agent-Based Learning Model for the Obesity Paradox in RCC

Belenchia

Rocchetti

Maestri

et al. 2021

Front. Bioeng. Biotechnol.

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A recent study on the immunotherapy treatment of renal cell carcinoma reveals better outcomes in obese patients compared to lean subjects. This enigmatic contradiction has been explained, in the context of the debated obesity paradox, as the effect produced by the cell-cell interaction network on the tumor microenvironment during the immune response. To better understand this hypothesis, we provide a computational framework for the in silico study of the tumor behavior. The starting model of the tumor, based on the cell-cell interaction network, has been described as a multiagent system, whose simulation generates the hypothesized effects on the tumor microenvironment. The medical needs in the immunotherapy design meet the capabilities of a multiagent simulator to reproduce the dynamics of the cell-cell interaction network, meaning a reaction to environmental changes introduced through the experimental data.

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“…Many receptors in the immunoglobulin superfamily (such as CD28, and inducible T cell co-stimulator) and TNF receptor superfamily (TNFSF) exert costimulatory actions [78]. TNFSRF9 is thought to be an antigen stimulation-inducible co-stimulatory receptor, which is transiently expressed on activated CD8 + T, activated CD4 + T, and NK cells [64,79,80]. Co-stimulatory signaling mediated by TNFRSF9 promotes T cell proliferation, secretion of cytokines, resistance to activation-induced cell death, and development of memory T cells [80].…”

Section: Icis Based On T Cell Exhaustion In Rcc-bmmentioning

confidence: 99%

“…Co-stimulatory signaling mediated by TNFRSF9 promotes T cell proliferation, secretion of cytokines, resistance to activation-induced cell death, and development of memory T cells [80]. TNFRSF9 + CD8 + T cells possess both exhaustion (PD-1, TIM-3, CTLA-4, and TIGIT) and effector phenotype (IFN-γ, granzyme B, and Ki-67) [79]. This dual phenotype of TNFRSF9 + CD8 + T cells indicates that these cells may not be terminally exhausted; however, they could respond to ICB [79].…”

Section: Icis Based On T Cell Exhaustion In Rcc-bmmentioning

confidence: 99%

“…TNFRSF9 + CD8 + T cells possess both exhaustion (PD-1, TIM-3, CTLA-4, and TIGIT) and effector phenotype (IFN-γ, granzyme B, and Ki-67) [79]. This dual phenotype of TNFRSF9 + CD8 + T cells indicates that these cells may not be terminally exhausted; however, they could respond to ICB [79]. The functional status of TNFRSF9 + CD8 + T cells might partly result from the complicated interactions among immune cells (helper T cells, CD8 + T cells, and myeloid cells) within the tumor, and high enrichment of TNFRSF9 + CD8 + T cells could be a predictor of immunotherapy and a novel therapeutic target in mRCC [79].…”

Section: Icis Based On T Cell Exhaustion In Rcc-bmmentioning

confidence: 99%

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Multidiscipline Immunotherapy-Based Rational Combinations for Robust and Durable Efficacy in Brain Metastases from Renal Cell Carcinoma

Lee

2021

IJMS

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Advanced imaging techniques for diagnosis have increased awareness on the benefits of brain screening, facilitated effective control of extracranial disease, and prolonged life expectancy of metastatic renal cell carcinoma (mRCC) patients. Brain metastasis (BM) in patients with mRCC (RCC-BM) is associated with grave prognoses, a high degree of morbidity, dedicated assessment, and unresponsiveness to conventional systemic therapeutics. The therapeutic landscape of RCC-BM is rapidly changing; however, survival outcomes remain poor despite standard surgery and radiation, highlighting the unmet medical needs and the requisite for advancement in systemic therapies. Immune checkpoint inhibitors (ICIs) are one of the most promising strategies to treat RCC-BM. Understanding the role of brain-specific tumor immune microenvironment (TIME) is important for developing rationale-driven ICI-based combination strategies that circumvent tumor intrinsic and extrinsic factors and complex positive feedback loops associated with resistance to ICIs in RCC-BM via combination with ICIs involving other immunological pathways, anti-antiangiogenic multiple tyrosine kinase inhibitors, and radiotherapy; therefore, novel combination approaches are being developed for synergistic potential against RCC-BM; however, further prospective investigations with longer follow-up periods are required to improve the efficacy and safety of combination treatments and to elucidate dynamic predictive biomarkers depending on the interactions in the brain TIME.

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Tumor-infiltrating TNFRSF9 ⁺ CD8 ⁺ T cells define different subsets of clear cell renal cell carcinoma with prognosis and immunotherapeutic response

Abstract: Xu (2020) Tumor-infiltrating TNFRSF9 + CD8 + T cells define different subsets of clear cell renal cell carcinoma with prognosis and immunotherapeutic response,

Cited by 30 publications

References 52 publications

Prognostic Value of Metabolism-Related Genes and Immune Infiltration in Clear Cell Renal Cell Carcinoma

Prognostic Value of Metabolism-Related Genes and Immune Infiltration in Clear Cell Renal Cell Carcinoma

Agent-Based Learning Model for the Obesity Paradox in RCC

Multidiscipline Immunotherapy-Based Rational Combinations for Robust and Durable Efficacy in Brain Metastases from Renal Cell Carcinoma

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