Biology subjects

Grande, B.

Publications and source records attributed to Grande, B..

3 recordsLinked to original sources

bioRxiv2021

Shared and distinct genetic features in human and canine B-cell lymphomas

Animal models of human cancers are an important tool for the development and preclinical evaluation of therapeutics. Canine B-cell lymphoma (cBCL) is an appealing model for human mature B-cell neoplasms due to the high sequence similarity in cancer genes to humans and inactive telomerase in adult tissues. We performed targeted sequencing on 86 canine patients from the Canine Comparative Oncology Genomic Consortium, with 61 confirmed as B-cell lymphomas. We confirmed a high frequency of mutations in TRAF3 (45%) and FBXW7 (20%) as has been reported by our group and others. We also note a higher frequency of DDX3X (20%) and MYC (13%) mutations in our canine cohort. We compared the pattern and incidence of mutations in cBCL to human diffuse large B-cell lymphoma (hDLBCL) and human Burkitt lymphoma (hBL). Canine MYC mutations displayed a focal pattern with 80% of mutations affecting the conserved phosphodegron sequence in MYC box 1, which are known to stabilize MYC protein. We also note that MYC and FBXW7 mutations do not co-occur in our cBCL cohort, leading to the hypothesis that these mutations represent alternative approaches to stabilize MYC in canine lymphoma. We observed striking differences in the pattern of DDX3X mutations in canine lymphoma as compared to hBL and uncovered a sex-specific pattern of DDX3X mutations in hBL that is not consistent with those identified in canine lymphomas. In sum, we describe key differences between cBCL and human mature B-cell lymphomas which may indicate differences in the biology of these cancers. This should be considered in future studies of cBCL as a model of human lymphomas.

cancer biology↗

bioRxiv2019

SUBSTRA: Supervised Bayesian Patient Stratification

Patient stratification methods are key to the vision of precision medicine. Here, we consider transcriptional data to segment the patient population into subsets relevant to a given phenotype. Whereas most existing patient stratification methods focus either on predictive performance or interpretable features, we developed a method striking a balance between these two important goals. We introduce a Bayesian method called SUBSTRA that uses regularized biclustering to identify patient subtypes and interpretable subtype-specific transcript clusters. The method iteratively re-weights feature importance to optimize phenotype prediction performance by producing more phenotype-relevant patient subtypes. We investigate the performance of SUBSTRA in finding relevant features using simulated data and successfully benchmark it against state-of-the-art unsupervised stratification methods and supervised alternatives. Moreover, SUBSTRA achieves predictive performance competitive with supervised benchmark methods and provides interpretable transcriptional features in diverse biological settings, such as drug response prediction, cancer diagnosis, or kidney transplant rejection.

bioinformatics↗

bioRxiv2017

Genome-wide discovery of somatic coding and regulatory variants in Diffuse Large B-cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is an aggressive cancer originating from mature B-cells. Many known driver mutations are over-represented in one of its two molecular subgroups, knowledge of which has aided in the development of therapeutics that target these features. The heterogeneity of DLBCL determined through prior genomic analysis suggests an incomplete understanding of its molecular aetiology, with a limited diversity of genetic events having thus far been attributed to the activated B-cell (ABC) subgroup. Through an integrative genomic analysis we uncovered genes and non-coding loci that are commonly mutated in DLBCL including putative regulatory sequences. We implicate recurrent mutations in the 3UTR of NFKBIZ as a novel mechanism of oncogene deregulation and found small amplifications associated with over-expression of FC-{gamma} receptor genes. These results inform on mechanisms of NF-{kappa}B pathway activation in ABC DLBCL and may reveal a high-risk population of patients that might not benefit from standard therapeutics.

genomics↗