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An immunotherapy response prediction model derived from proliferative CD4⁺ T cells and antigen-presenting monocytes in ccRCC.

ABSTRACT: Most patients with clear cell renal cell carcinoma (ccRCC) have an impaired response to immune checkpoint blockade (ICB) therapy. Few biomarkers can predict responsiveness, and there is insufficient evidence to extend them to ccRCC clinical use. To explore subtypes and signatures of immunocytes with good predictive performance for ICB outcomes in the ccRCC context, we reanalyzed two ccRCC single-cell RNA sequencing (scRNA-seq) datasets from patients receiving ICB treatment. A subtype of proliferative CD4⁺ T cells and regulatory T cells and a subtype of antigen-presenting monocytes that have good predictive capability and are correlated with ICB outcomes were identified. These findings were corroborated in independent ccRCC ICB pretreatment bulk RNA-seq datasets. By incorporating the cluster-specific marker genes of these three immunocyte subtypes, we developed a prediction model, which reached an AUC of 93% for the CheckMate cohort (172 samples). Our study shows that the ICB response prediction model can serve as a valuable clinical decision-making tool for guiding ICB treatment of ccRCC patients.

SUBMITTER: Zheng K

PROVIDER: S-EPMC9452905 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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An immunotherapy response prediction model derived from proliferative CD4<sup>+</sup> T cells and antigen-presenting monocytes in ccRCC.

Zheng Kun K Gao Lianchong L Hao Jie J Zou Xin X Hu Xiaoyong X

Frontiers in immunology 20220825

Most patients with clear cell renal cell carcinoma (ccRCC) have an impaired response to immune checkpoint blockade (ICB) therapy. Few biomarkers can predict responsiveness, and there is insufficient evidence to extend them to ccRCC clinical use. To explore subtypes and signatures of immunocytes with good predictive performance for ICB outcomes in the ccRCC context, we reanalyzed two ccRCC single-cell RNA sequencing (scRNA-seq) datasets from patients receiving ICB treatment. A subtype of prolifer ...[more]

PMID: 36091022

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Project description:In leishmaniasis, the protective immunity is largely mediated by proinflammatory cytokine producing abilities of T cells and an efficient parasite killing by phagocytic cells. Notwithstanding a substantial progress that has been made during last decades, the mechanisms or factors involved in establishing protective immunity against Leishmania are not identified. In ancient Indian literature, metallic "bhasma," particularly that of "swarna" or gold (fine gold particles), is indicated as one of the most prominent metal-based therapeutic medicine, which is known to impart protective and curative properties in various health issues. In this work, we elucidated the potential of swarna bhasma (SB) on the effector properties of phagocytes and antigen-activated CD4+ T cells in augmenting the immunogenicity of L. donovani antigens. The characterization of SB revealing its shape, size, composition, and measurement of cytotoxicity established the physiochemical potential for its utilization as an immunomodulator. The activation of macrophages with SB enhanced their capacity to produce nitric oxide and proinflammatory cytokines, which eventually resulted in reduced uptake of parasites and their proliferation in infected cells. Further, in Leishmania-infected animals, SB administration reduced the generation of IL-10, an anti-inflammatory cytokine, and enhanced pro-inflammatory cytokine generation by antigen activated CD4+ T cells with increased frequency of double (IFNγ+/TNFα+) and triple (IFNγ+TNFα+IL-2+) positive cells and abrogated disease pathogeneses at the early days of infection. Our results also suggested that cow-ghee (A2) emulsified preparation of SB, either alone or with yashtimadhu, a known natural immune modulator which enhances the SB's potential in enhancing the immunogenicity of parasitic antigens. These findings suggested a definite potential of SB in enhancing the effector functions of phagocytes and CD4+ T cells against L. donovani antigens. Therefore, more studies are needed to elucidate the mechanistic details of SB and its potential in enhancing vaccine-induced immunity.

Dataset Information

An immunotherapy response prediction model derived from proliferative CD4⁺ T cells and antigen-presenting monocytes in ccRCC.

Publications

An immunotherapy response prediction model derived from proliferative CD4<sup>+</sup> T cells and antigen-presenting monocytes in ccRCC.

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Dataset Information

An immunotherapy response prediction model derived from proliferative CD4+ T cells and antigen-presenting monocytes in ccRCC.

Publications

An immunotherapy response prediction model derived from proliferative CD4<sup>+</sup> T cells and antigen-presenting monocytes in ccRCC.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

An immunotherapy response prediction model derived from proliferative CD4⁺ T cells and antigen-presenting monocytes in ccRCC.