Biology subjects

Armenia, J.

Publications and source records attributed to Armenia, J..

4 recordsLinked to original sources

bioRxiv2022

Drug-gene interaction screens coupled to tumour data analyses identify the most clinically-relevant cancer vulnerabilities driving sensitivity to PARP inhibition

Poly(ADP-ribose) polymerase (PARP) inhibitors (PARPi) are currently indicated for the treatment of ovarian, breast, pancreatic and prostate cancers harbouring mutations in the tumour suppressor genes BRCA1 or BRCA2. In the case of ovarian and prostate cancers, their classification as homologous recombination repair (HRR) deficient (HRD) or mutated (HRRm) also makes PARPi an available treatment option beyond BRCA1 or BRCA2 mutational status. However, identification of the most relevant genetic alterations driving the HRD phenotype has proven difficult and recent data have shown that other genetic alterations not affecting HRR are also capable of driving PARPi responses. To gain insight into the genetics driving PARPi sensitivity, we performed CRISPR-Cas9 loss-of-function screens in 6 PARPi-insensitive cell lines and combined the output with published PARPi datasets from 8 additional cell lines. Ensuing exploration of the data identified 110 genes whose inactivation is strongly linked to sensitivity to PARPi. Parallel cell line generation of isogenic gene knockouts in ovarian and prostate cancer cell lines identified that inactivation of core HRR factors is required for driving in vitro PARPi responses comparable to the ones observed for BRCA1 or BRCA2 mutations. Moreover, pan-cancer genetic, transcriptomic and epigenetic data analyses of these 110 genes highlight the ones most frequently inactivated in tumours, making this study a valuable resource for prospective identification of potential PARPi-responsive patient populations. Importantly, our investigations uncover XRCC3 gene silencing as a potential new prognostic biomarker of PARPi sensitivity in prostate cancer. Statement of significanceThis study identifies tumour genetic backgrounds where to expand the use of PARP inhibitors beyond mutations in BRCA1 or BRCA2. This is achieved by combining the output of unbiased genome-wide loss-of-function CRISPR-Cas9 genetic screens with bioinformatics analysis of biallelic losses of the identified genes in public tumour datasets, unveiling loss of the DNA repair gene XRCC3 as a potential biomarker of PARP inhibitor sensitivity in prostate cancer.

cancer biology↗

bioRxiv2022

Cancer-driving mutations are enriched in genic regions intolerant to germline variation

Large reference datasets of protein-coding variation in human populations have allowed us to determine which genes and genic sub-regions are intolerant to germline genetic variation. There is also a growing number of genes implicated in severe Mendelian diseases that overlap with genes implicated in cancer. Here, we hypothesized that mitotically mutable genic sub-regions that are intolerant to germline variation are enriched for cancer-driving mutations. We introduce a new metric, OncMTR, which uses 125,748 exomes in the gnomAD database to identify genic sub-regions intolerant to germline variation but enriched for hematologic somatic variants. We demonstrate that OncMTR can significantly predict driver mutations implicated in hematologic malignancies. Divergent OncMTR regions were enriched for cancer-relevant protein domains, and overlaying OncMTR scores on protein structures identified functionally important protein residues. Finally, we performed a rare variant, gene-based collapsing analysis on an independent set of 394,694 exomes from the UK Biobank and find that OncMTR dramatically improves genetic signals for hematologic malignancies. Our web app enables easy visualization of OncMTR scores for each protein-coding gene (https://astrazeneca-cgr-publications.github.io/OncMTR-Viewer/).

genomics↗

bioRxiv2020

A meta-analysis of clinical cases of reversion mutations in BRCA genes identifies signatures of DNA end-joining repair mechanisms driving therapy resistance

Germline mutations in the BRCA1 or BRCA2 genes predispose to hereditary breast and ovarian cancer and, mostly in the case of BRCA2, are also prevalent in cases of pancreatic and prostate malignancies. Tumours from these patients tend to lose both copies of the wild type BRCA gene, which makes them exquisitely sensitive to platinum drugs and PARP inhibitors (PARPi), treatments of choice in these disease settings. Reversion secondary mutations with the capacity of restoring BRCA protein expression have been documented in the literature as bona fide mechanisms of resistance to these treatments. Here, we perform a detailed analysis of clinical cases of reversion mutations described in BRCA1 and BRCA2, which underlines the different importance of BRCA protein domains in contributing to resistance and the potential key role of mutagenic end-joining DNA repair pathways in generating reversions. Our analyses suggest that pharmacological inhibition of these repair pathways could improve durability of drug treatments and highlights potential interventions to both prevent the appearance of reversions and provide new therapeutic opportunities after their acquisition. HighlightsO_LIComprehensive analysis of reversion mutations in BRCA genes identified in clinical cases of resistance to platinum or PARPi C_LIO_LIRevertant proteins devoid of parts of the original sequence, identifying key protein functions involved in resistance C_LIO_LIHypomorph revertant BRCA proteins suggest potential new therapeutic opportunities to overcome resistance C_LIO_LIPrevalence of mutational end-joining DNA repair mechanisms leading to reversions, especially in those affecting BRCA2 C_LIO_LIPharmacological inhibition of mutational end-joining DNA repair could improve durability of drug treatments C_LI

cancer biology↗

bioRxiv2017

Enabling cross-study analysis of RNA-Sequencing data

Driven by the recent advances of next generation sequencing (NGS) technologies and an urgent need to decode complex human diseases, a multitude of large-scale studies were conducted recently that have resulted in an unprecedented volume of whole transcriptome sequencing (RNA-seq) data. While these data offer new opportunities to identify the mechanisms underlying disease, the comparison of data from different sources poses a great challenge, due to differences in sample and data processing. Here, we present a pipeline that processes and unifies RNA-seq data from different studies, which includes uniform realignment and gene expression quantification as well as batch effect removal. We find that uniform alignment and quantification is not sufficient when combining RNA-seq data from different sources and that the removal of other batch effects is essential to facilitate data comparison. We have processed data from the Genotype Tissue Expression project (GTEx) and The Cancer Genome Atlas (TCGA) and have successfully corrected for study-specific biases, enabling comparative analysis across studies. The normalized data are available for download via GitHub (at https://github.com/mskcc/RNAseqDB).

bioinformatics↗