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Goncearenco, A.

Publications and source records attributed to Goncearenco, A..

2 recordsLinked to original sources

Nucleotide and codon background mutability shape cancer mutational spectrum and advance driver mutation identification

Identifying driver mutations in cancer is notoriously difficult. To date, recurrence of a mutation in patients remains one of the most reliable markers of mutation driver status. However, some mutations are more likely to occur than others due to differences in background mutation rates arising from various forms of infidelity of DNA replication and repair machinery, endogenous, and exogenous mutagens.\n\nWe used cancer-type and mutagen-specific mutability to study the contribution of background processes of mutagenesis and DNA repair in shaping the observed mutational spectrum in cancer. We developed and tested probabilistic model that adjusts the number of mutation recurrences in patients by background mutability in order to find mutations which may be under selection in cancer.\n\nWe showed that observed recurrence frequency of cancer mutations scaled with the background mutability, especially for tumor suppressor genes. In oncogenes, however, highly recurring mutations were characterized by relatively low mutability, resulting in a U-shaped trend. Mutations not yet observed in any tumor had relatively low mutability values, indicating that background mutability might limit the mutation occurrence.\n\nWe compiled a dataset of missense mutations from 58 genes with experimentally validated functional and transforming impacts from different studies. We found that mutability of driver mutations was lower than the mutability of passengers and consequently adjusting mutation recurrence frequency by mutability significantly improved ranking of mutations and driver prediction. Even though no training on existing data was involved, our approach performed similar or better to the existing state-of-the-art methods.\n\nAvailabilityhttps://www.ncbi.nlm.nih.gov/research/mutagene/gene

cancer biology

Integrated proteogenomic analysis of metastatic thoracic tumors identifies APOBEC mutagenesis and copy number alterations as drivers of proteogenomic tumor evolution and heterogeneity

Elucidation of the proteogenomic evolution of metastatic tumors may offer insight into the poor prognosis of patients harboring metastatic disease. We performed whole-exome and transcriptome sequencing, copy number alterations (CNA) and mass spectrometry-based quantitative proteomics of 37 lung adenocarcinoma (LUAD) and thymic carcinoma (TC) metastases obtained by rapid autopsy and found evidence of patient-specific, multi-dimensional heterogeneity. Extreme mutational heterogeneity was evident in a subset of patients whose tumors showed increased APOBEC-signature mutations and expression of APOBEC3 region transcripts compared to patients with lesser mutational heterogeneity. TP53 mutation status was associated with APOBEC hypermutators in our cohort and in three independent LUAD datasets. In a thymic carcinoma patient, extreme heterogeneity and increased APOBEC3AB expression was associated with a high-risk germline APOBEC3AB variant allele. Patients with CNA occurring late in tumor evolution had corresponding changes in gene expression and protein abundance indicating genomic instability as a mechanism of downstream transcriptomic and proteomic heterogeneity between metastases. Across all tumors, proteomic heterogeneity was greater than copy number and transcriptomic heterogeneity. Enrichment of interferon pathways was evident both in the transcriptome and proteome of the tumors enriched for APOBEC mutagenesis despite a heterogeneous immune microenvironment across metastases suggesting a role for the immune microenvironment in the expression of APOBEC transcripts and generation of mutational heterogeneity. The evolving, heterogeneous nature of LUAD and TC, through APOBEC-mutagenesis and CNA illustrate the challenges facing treatment outcomes.

cancer biology