Biology subjects

Massa, A.

Publications and source records attributed to Massa, A..

2 recordsLinked to original sources

bioRxiv2025

TASC: A transcriptome-driven machine learning classifier to explore molecular heterogeneity and relapse-associated programs in T-cell Acute Lymphoblastic Leukemia

T-cell acute lymphoblastic leukemia is a biologically heterogeneous malignancy characterized by diverse transcriptional and genomic alterations. Recent studies have defined a set of recurrent molecular subtypes associated with distinct differentiation stages and clinical outcomes. However, no unified framework currently exists for assigning these subtypes in a standardized and accessible manner. Existing approaches often rely on mutation or fusion detection and may overlook broader transcriptional programs. The lack of a comprehensive, transcriptome-based classification tool has hampered the use of subtype-specific insights in both research and clinical settings. Here, we present a machine learning-based classifier trained on transcriptomic data to predict previously defined multi-omic subtypes of T-cell acute lymphoblastic leukemia. The model accurately assigns subtype identity across patient samples and cell lines, and provides a practical tool for standardized molecular stratification, supporting future integration into diagnostic and translational workflows, as demonstrated by its ability to reveal subtype-specific patterns of relapse.

bioinformatics↗

bioRxiv2023

Leucine zipper-based sorting system enables generation of multi-functional CAR T cells

Resistance to chimeric antigen receptor (CAR) T cell therapy develops through multiple mechanisms including antigen-loss escape and tumor-induced immune suppression. Expression of multiple CARs may overcome multi-antigen-loss escape. Similarly, expression of switch receptors that convert inhibitory immune checkpoint signals into positive costimulatory signals may enhance CAR T cell activity in the tumor microenvironment. Engineering multiple features into one cell product, however, is limited by transgene packaging constraints of current vector systems. Here, we describe a leucine zipper-based cell sorting methodology that enables selective single-step immunomagnetic purification of cells co-transduced with two vectors, designed to potentially double the number of incorporated transgenes. This "Zip-sorting" system facilitated generation of T cells simultaneously expressing up to four CARs and co-expressing up to three switch receptors. These multi-CAR multi-Switch receptor arrays enabled T cells to eliminate antigenically heterogeneous syngeneic leukemia populations co-expressing multiple inhibitory ligands. Zip-sorted multi-CAR multi-Switch receptor T cells represent a potent therapeutic strategy to overcome multiple mechanisms of CAR T cell resistance.

synthetic biology↗