Dataset Information

Ratio of the interferon-? signature to the immunosuppression signature predicts anti-PD-1 therapy response in melanoma.

ABSTRACT: Immune checkpoint inhibitor (ICI) treatments produce clinical benefit in many patients. However, better pretreatment predictive biomarkers for ICI are still needed to help match individual patients to the treatment most likely to be of benefit. Existing gene expression profiling (GEP)-based biomarkers for ICI are primarily focused on measuring a T cell-inflamed tumor microenvironment that contributes positively to the response to ICI. Here, we identified an immunosuppression signature (IMS) through analyzing RNA sequencing data from a combined discovery cohort (n?=?120) consisting of three publicly available melanoma datasets. Using the ratio of an established IFN-? signature and IMS led to consistently better prediction of the ICI therapy outcome compared to a collection of nine published GEP signatures from the literature on a newly generated internal validation cohort (n?=?55) and three published datasets of metastatic melanoma treated with anti-PD-1 (n?=?54) and anti-CTLA-4 (n?=?42), as well as in patients with gastric cancer treated with anti-PD-1 (n?=?45), demonstrating the potential utility of IMS as a predictive biomarker that complements existing GEP signatures for immunotherapy.

SUBMITTER: Cui C

PROVIDER: S-EPMC7862369 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Ratio of the interferon-γ signature to the immunosuppression signature predicts anti-PD-1 therapy response in melanoma.

Cui Chuanliang C Xu Canqiang C Yang Wenxian W Chi Zhihong Z Sheng Xinan X Si Lu L Xie Yihong Y Yu Jinyu J Wang Shun S Yu Rongshan R Guo Jun J Kong Yan Y

NPJ genomic medicine 20210204 1

Immune checkpoint inhibitor (ICI) treatments produce clinical benefit in many patients. However, better pretreatment predictive biomarkers for ICI are still needed to help match individual patients to the treatment most likely to be of benefit. Existing gene expression profiling (GEP)-based biomarkers for ICI are primarily focused on measuring a T cell-inflamed tumor microenvironment that contributes positively to the response to ICI. Here, we identified an immunosuppression signature (IMS) thro ...[more]

PMID: 33542239

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Project description:Background: Glioma is the most common primary tumor of the central nervous system. The conventional glioma treatment strategies include surgical excision and chemo- and radiation-therapy. Interferon Gamma (IFN-γ) is a soluble dimer cytokine involved in immune escape of gliomas. In this study, we sought to identify IFN-γ-related genes to construct a glioma prognostic model to guide its clinical treatment. Methods: RNA sequences and clinicopathological data were downloaded from The Cancer Genome Atlas (TCGA) and the China Glioma Genome Atlas (CGGA). Using univariate Cox analysis and the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm, IFN-γ-related prognostic genes were selected to construct a risk scoring model, and analyze its correlation with the clinical features. A high-precision nomogram was drawn to predict prognosis, and its performance was evaluated using calibration curve. Finally, immune cell infiltration and immune checkpoint molecule expression were analyzed to explore the tumor microenvironment characteristics associated with the risk scoring model. Results: Four out of 198 IFN-γ-related genes were selected to construct a risk score model with good predictive performance. The expression of four IFN-γ-related genes in glioma tissues was significantly increased compared to normal brain tissue (p < 0.001). Based on ROC analysis, the risk score model accurately predicted the overall survival rate of glioma patients at 1 year (AUC: The Cancer Genome Atlas 0.89, CGGA 0.59), 3 years (AUC: TCGA 0.89, CGGA 0.68), and 5 years (AUC: TCGA 0.88, CGGA 0.70). Kaplan-Meier analysis showed that the overall survival rate of the high-risk group was significantly lower than that of the low-risk group (p < 0.0001). Moreover, high-risk scores were associated with wild-type IDH1, wild-type ATRX, and 1P/19Q non-co-deletion. The nomogram predicted the survival rate of glioma patients based on the risk score and multiple clinicopathological factors such as age, sex, pathological grade, and IDH Status, among others. Risk score and infiltrating immune cells including CD8 T-cell, resting CD4 memory T-cell, regulatory T-cell (Tregs), M2 macrophages, resting NK cells, activated mast cells, and neutrophils were positively correlated (p < 0.05). In addition, risk scores closely associated with expression of immune checkpoint molecules such as PD-1, PD-L1, CTLA-4, LAG-3, TIM-3, TIGIT, CD48, CD226, and CD96. Conclusion: Our risk score model reveals that IFN-γ -associated genes are an independent prognostic factor for predicting overall survival in glioma, which is closely associated with immune cell infiltration and immune checkpoint molecule expression. This model will be helpful in predicting the effectiveness of immunotherapy and survival rate in patients with glioma.

Project description:BACKGROUND:The sepsis-induced immunodepression contributes to impaired clinical outcomes of various stress conditions. This syndrome is well documented and characterized by attenuated function of innate and adaptive immune cells. Several pharmacological interventions aimed to restore the immune response are emerging of which interferon-gamma (IFN?) is one. It is of paramount relevance to obtain clinical information on optimal timing of the IFN?-treatment, -tolerance, -effectiveness and outcome before performing a RCT. We describe the effects of IFN? in a cohort of 18 adult and 2 pediatric sepsis patients. METHODS:In this open-label prospective multi-center case-series, IFN? treatment was initiated in patients selected on clinical and immunological criteria early (<?4?days) or late (>?7?days) following the onset of sepsis. The data collected in 18 adults and 2 liver transplanted pediatric patients were: clinical scores, monocyte expression of HLA-DR (flow cytometry), lymphocyte immune-phenotyping (flow cytometry), IL-6 and IL-10 plasma levels (ELISA), bacterial cultures, disease severity, and mortality. RESULTS:In 15 out of 18 patients IFN? treatment was associated with an increase of median HLA-DR expression from 2666 [IQ 1547; 4991] to 12,451 [IQ 4166; 19,707], while the absolute number of lymphocyte subpopulations were not affected, except for the decrease number of NK cells 94.5 [23; 136] to 32.5 [13; 90.8] (0.0625)]. Plasma levels of IL-6 464 [201-770] to 108 (89-140) ng/mL (p?=?0.04) and IL-10 from IL-10 from 29 [12-59] to 9 [1-15] pg/mL decreased significantly. Three patients who received IFN? early after ICU admission (<4?days) died. The other patients had a rapid clinical improvement assessed by the SOFA score and bacterial cultures that were repeatedly positive became negative. The 2 pediatric cases improved rapidly, but 1 died for hemorrhagic complication. CONCLUSION:Guided by clinical and immunological monitoring, adjunctive immunotherapy with IFN? appears well-tolerated in our cases and improves immune host defense in sepsis induced immuno suppression. Randomized clinical studies to assess its potential clinical benefit are warranted.

Dataset Information

Ratio of the interferon-? signature to the immunosuppression signature predicts anti-PD-1 therapy response in melanoma.

Publications

Ratio of the interferon-γ signature to the immunosuppression signature predicts anti-PD-1 therapy response in melanoma.

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