Dataset Information

9-Gene Signature Correlated With CD8⁺ T Cell Infiltration Activated by IFN-γ: A Biomarker of Immune Checkpoint Therapy Response in Melanoma.

ABSTRACT:

Purpose

To identify CD8⁺ T cell-related factors and the co-expression network in melanoma and illustrate the interactions among CD8⁺ T cell-related genes in the melanoma tumor microenvironment.

Method

We obtained melanoma and paracancerous tissue mRNA matrices from TCGA-SKCM and GSE65904. The CIBERSORT algorithm was used to assess CD8⁺ T cell proportions, and the "estimate" package was used to assess melanoma tumor microenvironment purity. Weighted gene co-expression network analysis was used to identify the most related co-expression modules in TCGA-SKCM and GSE65904. Subsequently, a co-expression network was built based on the joint results in the two cohorts. Subsequently, we identified the core genes of the two most relevant modules of CD8⁺T lymphocytes according to the module correlation, and constructed the signature using ssGSEA. Later, we compared the signature with the existing classical pathways and gene sets, and confirmed the important prognostic significance of the signature in this paper.

Results

Nine co-expressed genes were identified as CD8⁺ T cell-related genes enriched in the cellular response to interferon-gamma process and antigen processing and presentation of peptide antigen. In the low expression level group, inflammation and immune responses were weaker. Single-cell sequencing and immunohistochemistry indicated that these nine genes were highly expressed in CD8⁺ T cells group.

Conclusion

We identified nine-gene signature, and the signature is considered as the biomarker for T lymphocyte response and clinical response to immune checkpoint inhibitors for melanoma.

SUBMITTER: Yan K

PROVIDER: S-EPMC8248551 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundStratification of patients who could benefit from immune checkpoint inhibitor (ICI) therapy is of much importance. PD-1hiCD8+ T cells represent a newly identified and effective biomarker for ICI therapy response biomarker in lung cancer. Accurately quantifying these T cells using commonly available RNA sequencing (RNA-seq) data may extend their applications to more cancer types.MethodWe built a transcriptome signature of PD-1hiCD8+ T cells from bulk RNA-seq and single-cell RNA-seq (scRNA-seq) data of tumor-infiltrating immune cells. The signature was validated by flow cytometry and in independent datasets. The clinical applications of the signature were explored in non-small-cell lung cancer, melanoma, gastric cancer, urothelial cancer, and a mouse model of breast cancer samples treated with ICI, and systematically evaluated across 21 cancer types in The Cancer Genome Atlas (TCGA). Its associations with other biomarkers were also determined.ResultsSignature scores could be used to identify the PD-1hiCD8+ T subset and were correlated with the fraction of PD-1hiCD8+ T cells in tumor tissue (Pearson correlation, R=0.76, p=0.0004). Furthermore, in the scRNA-seq dataset, we confirmed the capability of PD-1hiCD8+ T cells to secrete CXCL13, as well as their interactions with other immune cells. In 581 clinical samples and 204 mouse models treated with ICIs, high signature scores were associated with increased survival, and the signature achieved area under the receiver operating characteristic curve scores of 0.755 (ranging from 0.61 to 0.91) in predicting therapy response. In TCGA pan-cancer datasets, our signature scores were consistently correlated with therapy response (R=0.78, p<0.0001) and partially explained the diverse response rates among different cancer types. Finally, our signature generally outperformed other mRNA-based predictors and showed improved predictive performance when used in combination with tumor mutational burden (TMB). The signature score is available in the R package "PD1highCD8Tscore" (https://github.com/Liulab/PD1highCD8Tscore).ConclusionThrough estimating the fraction of the PD-1hiCD8+ T cell, our signature could predict response to ICI therapy across multiple cancers and could serve as a complementary biomarker to TMB.

Project description:ObjectivesLimited research on the role of membrane-bound O-acyltransferase domain-containing 2 (MBOAT2) in cancer biology exists. In particular, the underlying role of MBOAT2 and its potential mechanisms in pancreatic cancer have not yet been explored. Further study of MBOAT2 could provide new ideas about the carcinogenesis and treatment of pancreatic cancer (PC).MethodsIn the current study, the potential biological and clinical significances of MBOAT2 were explored by bioinformatics analysis. Real-time quantitative polymerase chain reaction and western blot analysis were performed to determine the level of MBOAT2 in pancreatic ductal adenocarcinoma (PDAC) cell lines. MTT, colony formation, and Transwell assays and flow cytometry of cell cycle were performed to analyze PDAC cell proliferation, migration, and cycle progression. The potential relationship between MBOAT2 level and tumor immunity was analyzed using the ESTIMATE algorithm, CIBERSORT algorithm, and single-sample gene set enrichment analysis.ResultsThe level of MBOAT2 was remarkably upregulated in most tumors, especially pancreatic tumors, and was positively correlated with a greater rate of tumor recurrence, higher histologic grade, and worse overall survival. MBOAT2 overexpression was also closely correlated with the mutation status and expression level of driver genes, especially KRAS. Meanwhile, functional enrichment analysis demonstrated that MBOAT2 might be involved in cell-cell communication; cell cycling; the Ras signaling pathway; and immune-related biological functions such as the leukocyte activation involved in T-cell-receptor signaling pathway, the inflammatory response, and antigen processing and presentation. Furthermore, in vitro experiments demonstrated that MBOAT2 overexpression accelerated PC cell proliferation and migration. MBOAT2 overexpression also enhanced CDK2 and CCNA2 expression, leading to cell cycle progression from the G1 phase to the G2 phase. Lastly, MBOAT2 overexpression reduced the infiltration level of CD8+ T-cells, plasmacytoid dendritic cells, and activated dendritic cells but triggered a high type-2 T helper/type-1 T helper cell ration (Th2/Th1 ration) in PC.ConclusionOur findings suggest that MBOAT2 is a potential protooncogene in PDAC that predicts a poor prognosis and is related to KRAS activation and inferior infiltration of CD8+ T-cells in PC.

Project description:Rationale: Novel immune-activating therapeutics for the treatment of glioblastoma multiforme (GBM) have shown potential for tumor regression and increased survival over standard therapies. However, immunotherapy efficacy remains inconsistent with response assessment being complicated by early treatment-induced apparent radiological tumor progression and slow downstream effects. This inability to determine early immunotherapeutic benefit results in a drastically decreased window for alternative, and potentially more effective, treatment options. The objective of this study is to evaluate the effects of combination immunotherapy on early CD8+ cell infiltration and its association with long term response in orthotopic syngeneic glioblastoma models. Methods: Luciferase positive GBM orthotopic mouse models (GSC005-luc) were imaged via [89Zr]-CD8 positron emission tomography (PET) one week following treatment with saline, anti-PD1, M002 oncolytic herpes simplex virus (oHSV) or combination immunotherapy. Subsequently, brains were excised, imaged via [89Zr]-CD8 ImmunoPET and evaluated though autoradiography and histology for H&E and CD8 immunohistochemistry. Longitudinal immunotherapeutic effects were evaluated through [89Zr]-CD8 PET imaging one- and three-weeks following treatment, with changes in tumor volume monitored on a three-day basis via bioluminescence imaging (BLI). Response classification was then performed based on long-term BLI signal changes. Statistical analysis was performed between groups using one-way ANOVA and two-sided unpaired T-test, with p < 0.05 considered significant. Correlations between imaging and biological validation were assessed via Pearson's correlation test. Results: [89Zr]-CD8 PET standardized uptake value (SUV) quantification was correlated with ex vivo SUV quantification (r = 0.61, p < 0.01), autoradiography (r = 0.46, p < 0.01), and IHC tumor CD8+ cell density (r = 0.55, p < 0.01). Classification of therapeutic responders, via bioluminescence signal, revealed a more homogeneous CD8+ immune cell distribution in responders (p < 0.05) one-week following immunotherapy. Conclusions: Assessment of early CD8+ cell infiltration and distribution in the tumor microenvironment provides potential imaging metrics for the characterization of oHSV and checkpoint blockade immunotherapy response in GBM. The combination therapies showed enhanced efficacy compared to single agent immunotherapies. Further development of immune-focused imaging methods can provide clinically relevant metrics associated with immune cell localization that can inform immunotherapeutic efficacy and subsequent treatment response in GBM patients.

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9-Gene Signature Correlated With CD8⁺ T Cell Infiltration Activated by IFN-γ: A Biomarker of Immune Checkpoint Therapy Response in Melanoma.

Purpose

Method

Results

Conclusion

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Dataset Information

9-Gene Signature Correlated With CD8+ T Cell Infiltration Activated by IFN-γ: A Biomarker of Immune Checkpoint Therapy Response in Melanoma.

Purpose

Method

Results

Conclusion

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

9-Gene Signature Correlated With CD8⁺ T Cell Infiltration Activated by IFN-γ: A Biomarker of Immune Checkpoint Therapy Response in Melanoma.