Association Between FSIP2 Mutation and an Improved Efficacy of Immune Checkpoint Inhibitors in Patients With Skin Cutaneous Melanoma

Comparison of genetic and epigenetic profiles of periodontitis according to the presence of type 2 diabetes

Type 2 diabetes mellitus (T2DM) and periodontitis (PD) have intricated connections as chronic inflammatory diseases. While the immune response is a key factor that accounts for their association, the underlying mechanisms remain unclear. To gain a deeper understanding of the connection, we conducted research using a multiomics approach. We generated whole genome and methylation profiling array data from the periodontium of PD patients with DM (PDDM) and without DM to confirm genetic and epigenetic changes. Independent bulk and single-cell RNA sequencing data were employed to verify the expression levels of hypo-methylated genes. We observed a gradual rise in C>T base substitutions and hypomethylation in PD and PDDM patients compared with healthy participants. Furthermore, specific genetic and epigenetic alterations were prominently associated with the Fc-gamma receptor-mediated phagocytosis pathway. The upregulation of these genes was confirmed in both the periodontal tissues of PD patients and the pancreatic tissues of T2DM patients. Through single-cell RNA analysis of peripheral blood mononuclear cells, substantial upregulation of Fc-gamma receptors and related genes was particularly identified in monocytes. Our findings suggest that targeting the Fc-gamma signaling pathway in monocytes holds promise as a potential treatment strategy for managing systemic complications associated with diabetes.

CACNA1C mutation as a prognosis predictor of immune checkpoint inhibitor in skin cutaneous melanoma

Aims: There is an urgent need for appropriate biomarkers that can precisely and reliably predict immunotherapy efficacy, as immunotherapy responses can differ in skin cutaneous melanoma (SKCM) patients. Methods: In this study, univariate regression models and survival analysis were used to examine the link between calcium voltage-gated channel subunit alpha 1C (CACNA1C) mutation status and immunotherapy outcome in SKCM patients receiving immunotherapy. Mutational landscape, immunogenicity, tumor microenvironment and pathway-enrichment analyses were also performed. Results: The CACNA1C mutation group had a better prognosis, higher immunogenicity, lower endothelial cell infiltration, significant enrichment of antitumor immune response pathways and significant downregulation of protumor pathways. Conclusion: CACNA1C mutation status is anticipated to be a biomarker for predicting melanoma immunotherapy effectiveness.

Predictive value and accuracy of [18F]FDG PET/CT modified response criteria for checkpoint immunotherapy in patients with advanced melanoma

PURPOSE

Immune checkpoint inhibitors (ICIs) are widely used in metastatic melanoma and dramatically alter the treatment of these patients. Given the high cost and potential toxicity, a reliable method for evaluating treatment response is needed. In this study, we assessed tumor response in patients with metastatic melanoma treated with ICIs using three modified response criteria: PET Response Evaluation Criteria for Immunotherapy (PERCIMT), PET Response Criteria in Solid Tumors for up to Five Lesions (PERCIST5), and immunotherapy-modified PET Response Criteria in Solid Tumors for up to Five Lesions (imPERCIST5).

METHODS

Ninety-one patients with non-resectable stage IV metastatic melanoma who received ICIs were retrospectively enrolled in this study. Each patient had two [18F]FDG PET/CT scans performed before and after ICI therapy. Responses at the follow-up scan were evaluated according to PERCIMT, PERCIST5, and imPERCIST5 criteria. Patients were classified into four groups: complete metabolic response (CMR), partial metabolic response (PMR), progressive metabolic disease (PMD), and stable metabolic disease (SMD). To assess the "disease control rate," two groups have been defined based on each criterion: patients with CMR, PMR, and SMD as "disease-controlled group (i.e., responders)" and PMD as the "uncontrolled-disease group (i.e., non-responders)". The correspondence between metabolic tumor response defined by these criteria and clinical outcome was assessed and compared.

RESULTS

The response and the disease control rates were 40.7% and 71.4%, 41.8% and 50.5%, and 54.9% and 74.7% based on the PERCIMT, PERCIST5, and imPERCIST5 criteria, respectively. PERCIMT and imPERCIST5 showed significantly different disease control rates from that of PERCIST5 (P < 0.001), whereas it was not significant between PERCIMT and imPERCIST5. Overall survival was significantly longer in the metabolic responder groups than in the non-responder groups based on PERCIMT and PERCIST5 criteria (PERCIMT: 2.48 versus 1.47 years, P = 0.003; PERCIST5: 2.57 versus 1.81 years. P = 0.017). However, according to imPERCIST5 criterion, this difference was not observed (P = 0.12).

CONCLUSION

Although the appearance of new lesions can be secondary to an inflammatory response to ICIs and indicative of pseudoprogression, given the higher rate of true progression, the appearance of new lesions should be interpreted deliberately. Of the three assessed modified criteria, PERCIMT appear to provide more reliable metabolic response assessment that correlates strongly with overall patient survival.

Prognostic modeling of patients with metastatic melanoma based on tumor immune microenvironment characteristics

Most of the malignant melanomas are already in the middle and advanced stages when they are diagnosed, which is often accompanied by the metastasis and spread of other organs. Besides, the prognosis of patients is bleak. The characteristics of the local immune microenvironment in metastatic melanoma have important implications for both tumor progression and tumor treatment. In this study, data on patients with metastatic melanoma from the TCGA and GEO datasets were selected for immune, stromal, and estimate scores, and overlapping differentially expressed genes were screened. A nine-IRGs prognostic model (ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22) was established by univariate COX regression, LASSO and multivariate COX regression. Receiver operating characteristic curves were used to test the predictive accuracy of the model. Immune infiltration was analyzed by using CIBERSORT and Xcell in high-risk and low-risk groups. The immune infiltration of the high-risk group was significantly lower than that of the low-risk group. Immune checkpoint analysis revealed that the expression of PDCD1, CTLA4, TIGIT, CD274, HAVR2 and LAG3 demonstrated the visible difference in groups with different levels of risk scores. WGCNA analysis found that the yellow-green module contained seven genes from the nine-IRG prognostic model, and the yellow-green module had the highest correlation with risk scores. The results of GO and KEGG suggested that the genes in the yellow-green module were mainly enriched in immune-related biological processes. Finally, the expression characteristics of ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22 were analyzed between metastatic melanoma and normal samples. Overall, a prognostic model for metastatic melanoma based on the tumor immune microenvironment characteristics was established, which left plenty of space for further studies. It could function well in helping people to understand characteristics of the immune microenvironment in metastatic melanoma.