Biology subjects

Akimov, Y.

Publications and source records attributed to Akimov, Y..

5 recordsLinked to original sources

bioRxiv2022

A synthetic lethal dependency on casein kinase 2 in response to replication-perturbing drugs in RB1-deficient ovarian and breast cancer cells

Treatment of patients with high-grade serous ovarian carcinoma (HGSOC) and triple-negative breast cancer (TNBC) includes platinum-based drugs, gemcitabine, and PARP inhibitors. However, resistance to these therapies develops in most cases, highlighting the need for novel therapeutic approaches and biomarkers to guide the optimal treatment choice. Using a CRISPR loss-of-function screen for carboplatin sensitizers in the HGSOC cell line OVCAR8, we identified CSNK2A2, the gene encoding for the alpha () catalytic subunit of casein kinase 2 (CK2). Expanding on this finding, we confirmed that the CK2 inhibitors silmitasertib and SGC-CK2-1 sensitized many, but not all, TNBC and HGSOC cell lines to the drugs that perturb DNA replication, including platinum drugs, gemcitabine, and PARP inhibitors. We identified RB1 tumor suppressor deficiency as a prerequisite context for the CK2 inhibition-mediated sensitization to these therapeutics. In RB1-deficient cells, CK2 inhibition resulted in accumulation of cells in S phase of the cell cycle, associated with micronuclei formation, and accelerated PARP inhibitor-induced aneuploidy and mitotic cell death. Patient HGSOC organoids that lacked RB1 expression displayed an enhanced long-term response to carboplatin and PARP inhibitor niraparib when combined with silmitasertib, suggesting RB1-stratified efficacy in patients. As RB1 deficiency affects up to 25% of HGSOC and 40% of TNBC cases, CK2 inhibition, proven safe from previous clinical exploration with silmitasertib, is a promising approach to overcome resistance to standard therapeutics in large strata of patients.

cancer biology↗

bioRxiv2022

Genome-wide CRISPRi screening reveals regulators of Alzheimee's tau pathology shared between exosomal and vesicle-free tau seeds.

Aggregation of the microtubule-associated protein tau is a defining feature of Alzheimers disease and other tauopathies. Tau pathology is believed to be driven by both free tau aggregates and tau carried within exosomes, which propagate trans-synaptically and induce tau pathology in recipient neurons by a corrupting process of seeding. Here, we performed a genome-wide CRISPRi screen in tau biosensor cells and identified cellular regulators shared by both mechanisms of tau seeding. The top validated regulators are ANKLE2, BANF1, NUSAP1, EIF1AD, and VPS18, which work as factors that restrict tau aggregation initiated by both exosomal and vesicle-free tau seeds. Interestingly, ANKLE2 and BANF1 more robustly affected exosomal tau seeding than free aggregates. Lastly, validation studies revealed that several of the identified protein hits are downregulated in the brains of Alzheimers patients, suggesting that their decreased activity may be required for the emergence or progression of tau pathology in the human brain.

neuroscience↗

bioRxiv2020

Method to identify physical, chemical and biological factors that trigger Bcl-xL-mediated apoptosis

The evidence that pan-Bcl-2 or Bcl-xL-specific inhibitors prematurely kill virus-infected or RNA/DNA-transfected cells provides rationale for investigating these apoptotic inducers further. Here, we show that Bcl-xL-specific agent A-1155463 prematurely kills cells of different origins and the small roundworms (C. elegans), when combined with DNA-damaging agent 4-nitroquinoline-1-oxide (4NQO). The synergistic effect of 4NQO-A-1155463 combination was p53-dependent, was associated with the release of Bad and Bax from Bcl-xL, which triggered mitochondrial outer membrane permeabilization (MOMP). Combinations of Bcl-xL-specific inhibitors with certain anticancer compounds or physical insults also killed cells. Collectively, our results suggest that biological, chemical and physical factors trigger evolutionary conserved Bcl-xL-mediated apoptotic pathway.

cancer biology↗

bioRxiv2019

Improved detection of differentially represented DNA barcodes for high-throughput lineage phenomics

Cellular DNA barcoding has become a popular approach to study heterogeneity of cell populations and to identify lineages with differential response to cellular stimuli. However, there is a lack of reliable methods for statistical inference of differentially responding lineages. Here, we used mixtures of DNA-barcoded cell pools to generate a realistic benchmark read count dataset for modelling a range of outcomes of lineage-tracing experiments. By accounting for the statistical properties intrinsic to the DNA barcode read count data, we implemented an improved algorithm that provides a significantly higher accuracy at detecting differentially responding lineages, compared to current RNA-seq data analysis algorithms. Building on the reliable statistical methodology, we illustrate how multidimensional phenotypic profiling (or high-throughput lineage phenomics) enables one to deconvolute phenotypically distinct cell subpopulations within a cancer cell line. The mixture control dataset and our analysis results provide a systematic foundation for benchmarking and improving algorithms for lineage-tracing experiments.

bioinformatics↗

bioRxiv2019

DNA barcode-guided lentiviral CRISPRa tool to trace and isolate individual clonal lineages in heterogeneous cancer cell populations

The genetic and functional heterogeneity of tumors imposes the challenge of understanding how a cancer progresses, evolves and adapts to treatment at the subclonal level. Therefore, there is a critical need for methods that enable profiling of individual cancer cell lineages. Here, we report a novel system that couples an established DNA barcoding technique for lineage tracing with a controlled DNA barcode-guided lineage isolation (B-GLI). B-GLI allows both high-complexity of lineage tracing and effective isolation of individual clones by CRISPRa-mediated induction of puromycin resistance, making it possible to unbiasedly trace, isolate, and study individual cancer cell lineages. We present experimental evaluation of the system performance in isolation of lineages and outline a comprehensive workflow for B-GLI applications. We believe the system has broad applications aimed at molecular and phenotypic profiling of individual lineages in heterogeneous cell populations.

cancer biology↗