Biology subjects

Kuznetsov, V. A.

Publications and source records attributed to Kuznetsov, V. A..

3 recordsLinked to original sources

bioRxiv2023

ABI1 regulates transcriptional activity of Androgen Receptor by novel DNA and AR binding mechanism

Transcription regulates key functions of living organisms in normal and disease states, including cell growth and development, embryonic and adult tissue organization, and tumor progression. Here we identify a novel mechanism of transcriptional regulation by an actin regulatory and signaling protein, Abelson Interactor 1 (ABI1). Using prostate cancer models, we uncover a reciprocal regulation between ABI1 and the Androgen Receptor (AR). ABI1 is a direct, androgen-regulated target; in turn, ABI1 interacts with AR and its splice variant ARv7, and co-regulates a subset of specific transcriptional targets. ABI1 directs transcription through transient yet well-defined interaction of its intrinsically disordered region with DNA. Clinical evaluation shows that the ABI1-DNA binding (through Exon 4 splicing) and ABI1-AR interaction are regulated during androgen deprivation therapy and prostate cancer progression, thus controlling tumor plasticity through connecting actin cytoskeleton and cellular signaling to transcriptional regulation. We propose ABI1 as epigenetic regulator of transcriptional homeostasis in AR-driven cancers. Statement of importanceThis study describes fundamental discovery in prostate cancer identifying novel mechanism of transcription by unique DNA binding mechanism involving actin cytoskeleton regulatory protein ABI1. ABI1-DNA binding activity predicts survival of prostate cancer patients. Moreover, we discover ABI1-AR reciprocal regulation that has far reaching implications for tumor plasticity and androgen-sensitive pathogenesis.

cancer biology↗

bioRxiv2022

Generalized Hypergeometric Distributions Generated by Birth-Death Process in Bioinformatics

Modern high-throughput biological systems detection methods generate empirical frequency distributions (EFD) which exhibit complex forms and have long right-side tails. Such EFD are often observed in normal and pathological processes, of which the probabilistic properties are essential, but the underlying probability mechanisms are poorly understood. To better understand the probability mechanisms driving biological complexity and the pathological role of extreme values, we propose that the observed skewed discrete distributions are generated by non-linear transition rates of birth and death processes (BDPs). We introduce a (3d+1)-parameter Generalized Gaussian Hypergeometric Probability ((3d+1)-GHP) model with the probabilities defined by a stationary solution of generalized BDP (g-BDP) and represented by generalized hypergeometric series with regularly varying function properties. We study the Regularly Varying 3d-Parameter Generalized Gaussian Hypergeometric Probability (3d-RGHP) functions regular variation properties, asymptotically constant slow varying component, unimodality and upward/ downward convexity which allows us to specify a family of 3d-RGHP models and study their analytical and numerical characteristics. The frequency distribution of unique muta-tions occurring in the human genome of patients with melanoma have been analyzed as an example application of our theory in bioinformatics. The results show that the parameterized model not only fits the heavy tail well, but also the entire EFD taken on the complete experimental outcome space. Our model provides a rigorous and flexible mathematical framework for analysis and application of skewed distributions generated by BDPs which often occur in bioinformatics and big data science.

bioinformatics↗

bioRxiv2021

Immunity Depletion, Telomere Imbalance, and Cancer-associated Metabolism Pathway Aberrations in Intestinal Mucosa upon Caloric Restriction

Systematic analysis of calorie restriction (CR) mechanisms and pathways in cancer biology has not been carried out, leaving therapeutic benefits unclear. Using a systems biology approach and metadata analysis, we studied gene expression changes in the response of normal mouse duodenum mucosa (DM) to short-term (2-weeks) 25% CR as a biological model. We found a high similarity of gene expression profiles in human and mouse DM tissues. Surprisingly, 26% of the 467 CR responding differential expressed genes (DEGs) in mice consist of cancer-associated genes--most never studied in CR contexts. The DEGs were enriched with over-expressed cell cycle, oncogenes, and metabolic reprogramming pathways (MRP) that determine tissue-specific tumorigenesis, cancer, and stem cell activation; tumor suppressors and apoptosis genes were under-expressed. DEG enrichments suggest a misbalance in telomere maintenance and activation of metabolic pathways playing dual (anti-cancer and pro-oncogenic) roles. Immune system genes (ISGs) consist of 37% of the total DEGs; the majority of ISGs are suppressed, including cell-autonomous immunity and tumor immune evasion controls. Thus, CR induces MRP suppressing multiple immune mechanics and activating oncogenic pathways, potentially driving pre-malignant and cancer states. These findings change the paradigm regarding the anti-cancer role of CR and may initiate specific treatment target development.

cancer biology↗