Biology subjects

Harutyunyan, N.

Publications and source records attributed to Harutyunyan, N..

3 recordsLinked to original sources

bioRxiv2026

Benchmarking of bulk transcriptomic harmonization tools in a multi-platform B-cell lymphoma cohort identifies feature-specific quantile normalization and surrogate variable analysis as top-performing methods

Cross-platform harmonization of bulk transcriptomic datasets remains a fundamental challenge for developing cancer biomarkers because of persistent unresolved batch effects. Most harmonization tools are benchmarked on datasets with large inter-group biological differences (for example TCGA tumor types), whereas actionable biomarker mining requires preserving subtle transcriptional distinctions between closely related diagnoses. Here we present ComboBatch, a benchmarking pipeline that evaluates the full cross-product of 14 batch-removal strategies, 3 imputation methods, 33 harmonization algorithms and 2 post-removal conditions across 7,174 samples from 88 germinal-center B-cell lymphoma cohorts spanning four transcriptomic platforms. Scoring 87 quality metrics across 2,234 harmonization approaches, we show that method choice (R2 0.36) and batch-removal strategy (0.26) are the principal determinants of harmonization quality, whereas imputation (0.016) and post-removal (<0.01) are secondary. Feature Specific Quantile Normalization and Surrogate Variable Analysis were the top methods, jointly resolving follicular lymphoma, diffuse large B-cell lymphoma and normal germinal-center B-cell differences in multi-platform and RNA-seq-only compositions, respectively. We provide a data-driven five-scenario decision tree for harmonization method selection, applicable to any retrospective multi-platform transcriptomic study. The ComboBatch pipeline is available on GitHub and can be used for harmonization, allowing bioinformaticians to utilize 33 harmonization and 3 imputation methods according to their needs.

cancer biology↗

bioRxiv2026

Allele-specific correction of dominant Best vitelliform macular dystrophy in patient-derived retinal pigment epithelium

Autosomal dominant Best vitelliform macular dystrophy (BVMD) caused by variants in the BEST1 gene is characterized by dysfunction of the macular retinal pigment epithelium (RPE) and secondary degeneration of the photoreceptors. There are currently no approved treatments for BVMD, and owing to its dominant nature, there remains uncertainty regarding the utility of traditional gene augmentation. Here we evaluated whether a dominant pathogenic BEST1 allele can be corrected by base editing in differentiated RPE cells. We identified a patient with a likely pathogenic BEST1 c.851A>G (p. Tyr284Cys) variant that was amenable to cytidine base editing. After establishing patient-derived induced pluripotent stem cells (iPSCs), we corrected the pathogenic variant in the iPSCs to obtain corrected iPSCs with the same genetic background. Corrected iPSC-derived RPE exhibited normalized monolayer appearance, improved barrier integrity, reduced cell death, and restored RPE-specific transcriptome. We then used a dual adeno-associated virus (AAV) split-intein system to deliver a CRISPR-associated protein 9 cytidine base editor (SpCas9-CBE) to BEST1 c.851A>G mutant RPE monolayers and achieved editing of the pathogenic allele with a maximum efficiency of 13.42 {+/-} 3.64% (mean {+/-} SD). Together, these results demonstrate progress towards allele-specific base editing in a dominantly inherited retinal disorder.

neuroscience↗

bioRxiv2022

Non-Synonymous, Synonymous, and Non-Coding Nucleotide Variants Contribute to Recurrently Altered Biological Processes During Retinoblastoma Progression

Retinoblastomas form in response to biallelic RB1 mutations or MYCN amplification and progress to more aggressive and therapy-resistant phenotypes through accumulation of secondary genomic changes. Progression-related changes include recurrent somatic copy number alterations and typically non-recurrent nucleotide variants, including synonymous and non-coding variants, whose significance has been unclear. To assess synonymous and non-coding variant contributions to recurrently altered processes, we identified altered genes and over-represented variant gene ontologies in 168 exome or whole-genome-sequenced retinoblastomas and 12 tumor-matched cell lines. In addition to initiating RB1 mutations, MYCN amplification, and established retinoblastoma SCNAs, the analyses revealed enrichment of variant genes related to diverse biological processes including histone monoubiquitination, mRNA processing (P) body assembly, and mitotic sister chromatid segregation and cytokinesis. Importantly, inclusion of non-coding and synonymous variants increased the enrichment significance of each over-represented biological process term. To assess the effects of such mutations, we performed functional tests of 3 UTR variants of PCGF3 (a BCOR-binding component of Polycomb repressive complex I) and CDC14B (a regulator of sister chromatid segregation) and a synonymous variant of DYNC1H1 (a regulator of P-body assembly). PCGF3 and CDC14B 3 UTR variants impaired gene expression whereas a base-edited DYNC1H1 synonymous variant altered protein structure and stability. Compared to tumors, retinoblastoma cell lines had a partially overlapping variant gene spectrum and enrichment for p53 pathway mutations. These findings reveal potentially important differences in retinoblastoma cell lines and antecedent tumors and implicate synonymous and non-coding variants, along with non-synonymous variants, in retinoblastoma oncogenesis.

cancer biology↗