Reglero, C. | bioRxiv Science

bioRxiv2023

A Novel Aberrantly Spliced Gain-of-Function NT5C2 Isoform Contributes to Thiopurine Resistance in Acute Lymphoblastic Leukemia

Relapsed or refractory B-cell acute lymphoblastic leukemia (B-ALL) is a major cause of pediatric cancer-related deaths. Relapse-specific mutations do not account for all chemotherapy failures in B- ALL patients, suggesting additional mechanisms of resistance. By mining RNA-seq datasets of paired diagnostic/relapse pediatric B-ALL samples, we discovered pervasive alternative splicing (AS) patterns linked to relapse and affecting drivers of resistance to glucocorticoids, anti-folates, and thiopurines. Most splicing variations represented cassette exon skipping, "poison" exon inclusion, and intron retention, phenocopying well-documented loss-of-function mutations. In contrast, relapse-associated AS of NT5C2 mRNA yielded an isoform with the functionally uncharacterized in-frame exon 6a. Incorporation of the 8-amino acid sequence SQVAVQKR into this enzyme created a putative phosphorylation site and resulted in elevated nucleosidase activity, which is a known consequence of gain-of-function mutations in NT5C2 and a common determinant of 6-mercaptopurine (6-MP) resistance. Consistent with this finding, NT5C2ex6a and the R238W hotspot variant conferred comparable levels of resistance to 6-MP in B-ALL cells both in vitro and in vivo. Furthermore, both the NT5C2ex6a and R238W variants induced collateral sensitivity to the inosine monophosphate dehydrogenase (IMPDH) inhibitor mizoribine. These results ascribe an important role for splicing perturbations in chemotherapy resistance in relapsed B-ALL and suggest that IMPDH inhibitors, including the commonly used immunosuppressive agent mycophenolate mofetil, could be a valuable therapeutic option for treating thiopurine-resistant leukemias.

cancer biology↗

bioRxiv2022

Computational structure prediction methods enable the systematic identification of oncogenic mutations

Oncogenic mutations are associated with the activation of key pathways necessary for the initiation, progression and treatment-evasion of tumors. While large genomic studies provide the opportunity of identifying these mutations, the vast majority of variants have unclear functional roles presenting a challenge for the use of genomic studies in the clinical/therapeutic setting. Recent developments in predicting protein structures enable the systematic large-scale characterization of structures providing a link from genomic data to functional impact. Here, we observed that most oncogenic mutations tend to occur in protein regions that undergo conformation changes in the presence of the activating mutation or when interacting with a protein partner. By combining evolutionary information and protein structure prediction, we introduce the Evolutionary and Structure (ES) score, a computational approach that enables the systematic identification of hotspot somatic mutations in cancer. The predicted sites tend to occur in Short Linear Motifs and protein-protein interfaces. We test the use of ES-scores in genomic studies in pediatric leukemias that easily recapitulates the main mechanisms of resistance to targeted and chemotherapy drugs. To experimentally test the functional role of the predictions, we performed saturated mutagenesis in NT5C2, a protein commonly mutated in relapsed pediatric lymphocytic leukemias. The approach was able to capture both commonly mutated sites and identify previously uncharacterized functionally relevant regions that are not frequently mutated in these cancers. This work shows that the characterization of protein structures provides a link between large genomic studies, with mostly variants of unknown significance, to functional systematic characterization, prioritizing variants of interest in the therapeutic setting and informing on their possible mechanisms of action.

cancer biology↗