Unveiling the link between inflammasomes and skin cutaneous melanoma: Insights into expression patterns and immunotherapy response prediction

Machine learning-based identification of an immunotherapy-related signature to enhance outcomes and immunotherapy responses in melanoma

Background

Immunotherapy has revolutionized skin cutaneous melanoma treatment, but response variability due to tumor heterogeneity necessitates robust biomarkers for predicting immunotherapy response.

Methods

We used weighted gene co-expression network analysis (WGCNA), consensus clustering, and 10 machine learning algorithms to develop the immunotherapy-related gene model (ITRGM) signature. Multi-omics analyses included bulk and single-cell RNA sequencing of melanoma patients, mouse bulk RNA sequencing, and pathology sections of melanoma patients.

Results

We identified 66 consensus immunotherapy prognostic genes (CITPGs) using WGCNA and differentially expressed genes (DEGs) from two melanoma cohorts. The CITPG-high group showed better prognosis and enriched immune activities. DEGs between CITPG-high and CITPG-low groups in the TCGA-SKCM cohort were analyzed in three additional melanoma cohorts using univariate Cox regression, resulting in 44 consensus genes. Using 101 machine learning algorithm combinations, we constructed the ITRGM signature based on seven model genes. The ITRGM outperformed 37 published signatures in predicting immunotherapy prognosis across the training cohort, three testing cohorts, and a meta-cohort. It effectively stratified patients into high-risk or low-risk groups for immunotherapy response. The low-risk group, with high levels of model genes, correlated with increased immune characteristics such as tumor mutation burden and immune cell infiltration, indicating immune-hot tumors with a better prognosis. The ITRGM's relationship with the tumor immune microenvironment was further validated in our experiments using pathology sections with GBP5, an important model gene, and CD8 IHC analysis. The ITRGM also predicted better immunotherapy response in eight cohorts, including urothelial carcinoma and stomach adenocarcinoma, indicating broad applicability.

Conclusions

The ITRGM signature is a stable and robust predictor for stratifying melanoma patients into 'immune-hot' and 'immune-cold' tumors, enhancing prognosis and response to immunotherapy.

The Keratinocyte in the Picture Cutaneous Melanoma Microenvironment

Melanoma progression is a multistep evolution from a common melanocytic nevus through a radial superficial growth phase, the invasive vertical growth phase finally leading to metastatic dissemination into distant organs. Melanoma aggressiveness largely depends on the propensity to metastasize, which means the capacity to escape from the physiological microenvironment since tissue damage due to primary melanoma lesions is generally modest. Physiologically, epidermal melanocytes are attached to the basement membrane, and their adhesion/migration is under the control of surrounding keratinocytes. Thus, the epidermal compartment represents the first microenvironment responsible for melanoma spread. This complex process involves cell-cell contact and a broad range of secreted bioactive molecules. Invasion, or at the beginning of the microinvasion, implies the breakdown of the dermo-epidermal basement membrane followed by the migration of neoplastic melanocytic cells in the superficial papillary dermis. Correspondingly, several experimental evidences documented the structural and functional rearrangement of the entire tissue surrounding neoplasm that in some way reflects the atypia of tumor cells. Lastly, the microenvironment must support the proliferation and survival of melanocytes outside the normal epidermal-melanin units. This task presumably is mostly delegated to fibroblasts and ultimately to the self-autonomous capacity of melanoma cells. This review will discuss remodeling that occurs in the epidermis during melanoma formation as well as skin changes that occur independently of melanocytic hyperproliferation having possible pro-tumoral features.