Establishment and Evaluation of Immune Checkpoint Inhibitor Treatment Response Model Based on Gene Expression Value

Abstract Background: In the past 10 years, the identification of new mutant genes involved in the pathogenesis of melanoma and the discovery of key immune checkpoints have promoted the development of targeted therapy and immunotherapy. There is no doubt that an important breakthrough has been made in the treatment of advanced or metastatic melanoma. However, the treatment of melanoma also faces many challenges. In addition to resistance to existing targeted therapies or immunotherapy, most patients do not respond to immunotherapy or have serious adverse reactions. At present, the value of existing biomarkers to predict treatment response and toxicity is still limited. Therefore, there is an urgent need to establish a convenient and reliable immunotherapy response prediction model in order to preliminarily clarify the population benefiting from immunotherapy.Results: We established a predictive model based on the expression values of five genes for patients with melanoma with an anti-PD1 immunotherapy response score. This model showed better predictive ability compared with other common immunotherapy predictors. Differences were found in the number of immune cells and the expression of common immune checkpoint genes between the high- and low-score groups. The model played a pivotal role in predicting renal cell carcinoma anti-PD1 immunotherapy response. Conclusions: The anti-PD1 immunotherapy response score prediction model for patients with melanoma showed good predictive power, thus having far-reaching significance for identifying people who benefited from anti-PD1 immunotherapy and reducing the potential toxicity of insensitive patients.

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The polymorphism rs975484 in the protein arginine methyltransferase 1 gene modulates expression of immune checkpoint genes in hepatocellular carcinoma

Journal of Biological Chemistry ◽

10.1074/jbc.ra120.013401 ◽

2020 ◽

Vol 295 (20) ◽

pp. 7126-7137 ◽

Cited By ~ 2

Author(s):

Michael Schonfeld ◽

Jie Zhao ◽

Amberly Komatz ◽

Steven A. Weinman ◽

Irina Tikhanovich

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Checkpoint ◽

Immune Checkpoints ◽

Luciferase Reporter ◽

Antibody Treatment ◽

Protein Arginine Methyltransferase ◽

Arginine Methyltransferase ◽

Protein Arginine Methyltransferase 1 ◽

Checkpoint Genes ◽

Methyltransferase 1

Protein arginine methyltransferase 1 (PRMT1) is a key regulator of hepatic immune responses. Recently, we reported that PRMT1 regulates the tumor immune response in hepatocellular carcinoma (HCC). Here we found that PRMT1 expression in human HCC correlates with that of programmed cell death 1 ligand 1 (PD-L1), PD-L2, and other checkpoint genes. PRMT1 deletion in mice reduced PD-L1 and PD-L2 expression in tumors and reduced the efficiency of PD-1 antibody treatment in a diethylnitrosamine-induced HCC mouse model, suggesting that PRMT1 regulates the hepatic immune checkpoint. Mice had reduced PD-L1 and PD-L2 expression when PRMT1 was specifically deleted in tumor cells or macrophages, but PRMT1 deletion in dendritic cells did not alter PD-L1 and PD-L2 expression. rs975484 is a common polymorphism in the human PRMT1 gene promoter, and we found that it alters PRMT1 expression in blood monocytes and tumor-associated macrophages in human HCC. PRMT1 expression was higher in individuals with a GG genotype than in individuals with a CC genotype, and heterozygous carriers had intermediate expression. Luciferase reporter assays indicated that this differential expression is due to an extra C/EBPβ-binding site in the PRMT1 promoter of individuals carrying the minor G allele. The rs975484 genotype also correlated with PRMT1 target expression in HCC. Individuals with the GG genotype had significantly higher levels of the PRMT1 targets PD-L1, PD-L2, and VISTA than those with the CC genotype. We conclude that PRMT1 critically controls immune checkpoints in mice and humans and that the PRMT1 polymorphism rs975484 affects checkpoint gene expression in HCC.

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Identification of the Prognosis Value and Potential Mechanism of Immune Checkpoints in Renal Clear Cell Carcinoma Microenvironment

Frontiers in Oncology ◽

10.3389/fonc.2021.720125 ◽

2021 ◽

Vol 11 ◽

Author(s):

Guodong Liao ◽

Ping Wang ◽

Yuyong Wang

Keyword(s):

Immune Checkpoint ◽

Prognostic Value ◽

Immune Cell ◽

Clear Cell ◽

Clear Cell Carcinoma ◽

Renal Clear Cell Carcinoma ◽

Immune Checkpoints ◽

Immune Cell Infiltration ◽

Free Survival ◽

Checkpoint Genes

BackgroundKidney Renal Clear Cell Carcinoma (KIRC) is one of the most prevalent types of cancer worldwide. KIRC has a poor prognosis and, to date, immunotherapy based on immune checkpoints is the most promising treatment. However, the role of immune checkpoints in KIRC remains ambiguous.MethodsBioinformatics analyses and qRT-PCR were performed to explore and further confirm the prognostic value of immune checkpoint genes and their correlation with immune infiltration in KIRC samples.ResultsThe expression of the immune checkpoint genes CD274, PDCD1LG2, HAVCR2, CTLA4, TIGFT, LAG3, and PDCD1 was upregulated in KIRC tissues. These genes were involved in the activation of the apoptosis pathway in KIRC. Low expression of CD274 and HAVCR2 and high expression of CTLA4 were associated with poor overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of KIRC patients. The univariate and multivariate analyses revealed that CTLA4, HAVCR2, age, pTNM stage, and tumor grade were independent factors affecting the prognosis of KIRC patients. A predictive nomogram demonstrated that the calibration plots for the 3‐year and 5‐year OS probabilities showed good agreement compared to the actual OS of KIRC patients. The expression of CTLA4 and HAVCR2 were positively associated with immune cell infiltration, immune biomarkers, chemokines, and chemokine receptors. Moreover, miR-20b-5p was identified as a potential miRNA target of CTLA4 in KIRC.ConclusionOur study clarified the prognostic value of several immune checkpoint regulators in KIRC, revealing a CTLA4/miR-20b-5p axis in the control of immune cell infiltration in the tumor microenvironment.

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Modulation of SRSF2 expression reverses the exhaustion of TILs via the epigenetic regulation of immune checkpoint molecules

Cellular and Molecular Life Sciences ◽

10.1007/s00018-019-03362-4 ◽

2019 ◽

Vol 77 (17) ◽

pp. 3441-3452 ◽

Cited By ~ 3

Author(s):

Ziqiang Wang ◽

Kun Li ◽

Wei Chen ◽

Xiaoxia Wang ◽

Yikun Huang ◽

...

Keyword(s):

T Cells ◽

Tumor Microenvironment ◽

Immune Checkpoint ◽

Tumor Infiltrating Lymphocytes ◽

Immune Checkpoints ◽

Gene Promoters ◽

Immune Checkpoint Molecules ◽

Elevated Expression ◽

Infiltrating Lymphocytes ◽

Checkpoint Genes

AbstractThe elevated expression of immune checkpoints by the tumor microenvironment is associated with poor prognosis in several cancers due to the exhaustion of tumor-infiltrating lymphocytes (TILs), and the effective suppression of the expression of these genes is key to reversing the exhaustion of TILs. Herein, we determined that serine/arginine-rich splicing factor 2 (SRSF2) is a target for blocking the tumor microenvironment-associated immunosuppressive effects. We found that the expression of SRSF2 was increased in exhausted T cells and that SRSF2 was involved in multiple immune checkpoint molecules mediating TILs’ exhaustion. Furthermore, SRSF2 was revealed to regulate the transcription of these immune checkpoint genes by associating with an acyl-transferases P300/CBP complex and altering the H3K27Ac level near these genes, thereafter influencing the recruitment of signal transducer and activator of transcription 3 (STAT3) to these gene promoters. Collectively, our data indicated that SRSF2 functions as a modulator of the anti-tumor response of T cells and may be a therapeutic target for reversing the exhaustion of TILs.

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Research on Drug Response Prediction Model Based on Big Data

Advances in Artificial Intelligence and Security - Communications in Computer and Information Science ◽

10.1007/978-3-030-78615-1_46 ◽

2021 ◽

pp. 524-537

Author(s):

Guijin Li ◽

Minzhu Xie

Keyword(s):

Big Data ◽

Prediction Model ◽

Drug Response ◽

Response Prediction ◽

Model Based

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A review on the role of gut microbiota in immune checkpoint blockade therapy for cancer

Mammalian Genome ◽

10.1007/s00335-021-09867-3 ◽

2021 ◽

Author(s):

Esther Kim ◽

Hyeok Ahn ◽

Hansoo Park

Keyword(s):

Gut Microbiota ◽

Immune Checkpoint ◽

Molecular Mechanisms ◽

Cytotoxic T Lymphocyte ◽

Response Prediction ◽

Immune Checkpoint Blockade ◽

Immune Checkpoints ◽

Bacterial Strains ◽

Programmed Cell Death 1 ◽

Health And Disease

AbstractGut microbiota has been studied in relation to human health and disease prediction for decades. Also, immune checkpoints (ICPs) are enthusiastically investigated for anti-tumor immunotherapy. Recent studies show potential of gut microbiome and gut cytokines as biomarkers for carcinogenesis and response prediction of immune checkpoint inhibitor (ICI) response. Evidence has revealed that intestinal microorganisms play a major role in the effectiveness of programmed cell death 1 (PD-1) and cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) blockade. In this review, we have focused on how microbiome and microbiome-generated cytokines affect immune checkpoints. We have also described the molecular mechanisms behind this interplay and the bacterial strains that have a potential role in immunotherapy.

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