Building a predictive model based on glycogene expression profiles of melanoma patients from TCGA-SKCM project”

MERLO, JP.; MAHMOUD, YD.; VEIGAS, F.; RABINOVICH, GA.; MARIÑO, KV.; GIROTTI, MR.

Buenos Aires

Congreso; Reunion Anual de Biociencias 2020; 2020

SAIC-SAI

Melanoma is the deadliest form of skin cancer and the incidence will continue to increase. Until recently, first line of treatment was a set of targeted therapies, but since the approval of immunotherapies in 2010, there has been a paradigm shift within the area. This therapeutic strategy targets Immune Checkpoints and unleashes anti-tumor immunity by impeding immune-suppressive mechanisms, considerably improving survival rates. However, and considering that around 50% of patients show intrinsic resistance, having a set of bona-fide biomarkers becomes indispensable to achieve proper diagnostic and accurate clinical decisions.We are dissecting the glycoimmunological pathways that may be involved in resistance to immunotherapies. In my PhD project, we have started by interrogating The Cancer Genome Atlas database using a set of 834 glycogenes. Results show that, when analyzing data for metastatic melanoma samples, there is a group of patients who shows worst overall survival, and this clinical trait correlates to a strong downregulation of glycol-related genes: from 483 differentially expressed genes, 353 are downregulated. Full transcriptome analysis in these samples by Gene Set Enrichment Analysis indicates that ~500 genesets are dysregulated; while top downregulated genesets were related to immune pathways, top upregulated were related to DNA methylation and cell growth. Using deconvolutional methods to infer quantity and quality of the immune infiltrate, we found that those patients with worst prognostic presented poor prognosis parameters, such as low immune Infiltrate Score, low pro-inflammatory M1 macrophages proportion, and a higher proportion of T regulatory cells. On the other hand, and with the goal of validating this glycogene signature in other neoplastic diseases, we have also analyzed data from 14 others cancer types. Our preliminary results show that this glycogene dysregulation pattern is maintained independently of the tumor type.Considering these results, we are currently searching for underlying glycobiological mechanisms that may regulate the anti-tumor immune response.