Analysis on tumor immune microenvironment and construction of a prognosis model for immune-related skin cutaneous melanoma / 中南大学学报(医学版)

OBJECTIVES@#Malignant melanoma is a highly malignant and heterogeneous skin cancer. Although immunotherapy has improved survival rates, the inhibitory effect of tumor microenvironment has weakened its efficacy. To improve survival and treatment strategies, we need to develop immune-related prognostic models. Based on the analysis of the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Sequence Read Archive (SRA) database, this study aims to establish an immune-related prognosis prediction model, and to evaluate the tumor immune microenvironment by risk score to guide immunotherapy.@*METHODS@#Skin cutaneous melanoma (SKCM) transcriptome sequencing data and corresponding clinical information were obtained from the TCGA database, differentially expressed genes were analyzed, and prognostic models were developed using univariate Cox regression, the LASSO method, and stepwise regression. Differentially expressed genes in prognostic models confirmed by real-time reverse transcription PCR (real-time RT-PCR) and Western blotting. Survival analysis was performed by using the Kaplan-Meier method, and the effect of the model was evaluated by time-dependent receiver operating characteristic curve as well as multivariate Cox regression, and the prognostic model was validated by 2 GEO melanoma datasets. Furthermore, correlations between risk score and immune cell infiltration, Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) score, immune checkpoint mRNA expression levels, tumor immune cycle, or tumor immune micro-environmental pathways were analyzed. Finally, we performed association analysis for risk score and the efficacy of immunotherapy.@*RESULTS@#We identified 4 genes that were differentially expressed in TCGA-SKCM datasets, which were mainly associated with the tumor immune microenvironment. A prognostic model was also established based on 4 genes. Among 4 genes, the mRNA and protein levels of killer cell lectin like receptor D1 (KLRD1), leukemia inhibitory factor (LIF), and cellular retinoic acid binding protein 2 (CRABP2) genes in melanoma tissues differed significantly from those in normal skin (all P<0.01). The prognostic model was a good predictor of prognosis for patients with SKCM. The patients with high-risk scores had significantly shorter overall survival than those with low-risk scores, and consistent results were achieved in the training cohort and multiple validation cohorts (P<0.001). The risk score was strongly associated with immune cell infiltration, ESTIMATE score, immune checkpoint mRNA expression levels, tumor immune cycle, and tumor immune microenvironmental pathways (P<0.001). The correlation analysis showed that patients with the high-risk scores were in an inhibitory immune microenvironment based on the prognostic model (P<0.01).@*CONCLUSIONS@#The immune-related SKCM prognostic model constructed in this study can effectively predict the prognosis of SKCM patients. Considering its close correlation to the tumor immune microenvironment, the model has some reference value for clinical immunotherapy of SKCM.

Interactome of vertebrate GAF/ThPOK reveals its diverse functions in gene regulation and DNA repair

GAGA associated factor (GAF) is a sequence-specific DNA binding transcription factor that is evolutionarilyconserved from flies to humans. Emerging evidence shows a context-dependent function of vertebrate GAF(vGAF, a.k.a. ThPOK) in multiple processes like gene activation, repression, and enhancer-blocking. Wehypothesize that context-dependent interaction of vGAF with a diverse set of proteins forms the basis for themultifunctional nature of vGAF. To this end, we deciphered the protein–protein interactome of vGAF andshow that vGAF interacts with chromatin remodelers, RNA metabolic machinery, transcriptional activators/repressors, and components of DNA repair machinery. We further validated the biological significance of ourprotein–protein interaction data with functional studies and established a novel role of vGAF in DNA repairand cell-survival after UV-induced DNA damage. One of the major risk factors for skin cutaneous melanoma isprolonged exposure of UV and subsequent DNA damage. vGAF is highly expressed in normal skin tissue.Interestingly, our analysis of high-throughput RNA-sequencing data shows that vGAF is heavily downregulated across all major stages of skin cutaneous melanoma suggesting its potential as a diagnostic biomarker.Taken together, our study provides a plausible explanation for the diverse gene regulatory functions of vGAFand unravels its novel role in DNA repair.