BUILDING A PREDICTIVE MODEL BASED ON GLYCOGENE EXPRESSION PROFILES OF MELANOMA PATIENTS FROM TCGA-SKCM PROJECT

VEIGAS, FLORENCIA; GIROTTI, MARÍA ROMINA; MAHMOUD, YAMIL; MARIÑO, KARINA V.; MERLO, JOAQUÍN; RABINOVICH, GABRIEL A.

CABA

Congreso; Reuníon Biociencias SAI-SAIC-SAFIS 2020; 2020

SAIC/SAI/SAFIS

Objectives. We aim to study glycoimmune pathways involved in resistance to immune checkpoint blockade (ICB) therapies for melanoma to establish a signature for patient classification.Materials & Methods. Analysis were run using R software v3.6. Deconvolution was performed using MIXTURE tool and the glycoimmune pathways analysis was based on GlycoV4 chip (834 genes).Signature score was calculated as the geometric mean of the expression of genes in each signature. Cluster1 and Cluster2 comparisons was performed using Wilcoxon test.Results. Metastatic tumor biopsies (n=357) were clustered using 78 high-variable glycogenes resulting in a Cluster2 of low Overall Survival (OS), and a Cluster1 of high OS (p