Purwar, R. | bioRxiv Science

bioRxiv2022

MAP Kinase and mammalian target of rapamycin are main pathways of gallbladder carcinogenesis: Results from bioinformatic analysis of Next Generation Sequencing data from a hospital-based cohort.

BackgroundGallbladder Cancer (GBC) is one of the most common cancers of the biliary tract and the third commonest gastrointestinal (GI) malignancy worldwide. The disease is characterized by the late presentation and poor outcome despite treatment, and hence, newer therapies and targets need to be identified. MethodsThe current study investigated various functionally enriched pathways in GBC pathogenesis involving the genes identified through Next Generation Sequencing (NGS). The Pathway enrichment analysis and Gene Ontology (GO) were carried out after NGS, followed by the construction of the protein-protein interaction (PPI) network to discover associations among the genes. ResultsOf the thirty-three patients with GBC who were screened through next-generation sequencing (NGS), 27somatic mutations were identified. These mutations involved a total of 14 genes. The p53 and KRAS were commonly found to be mutated, while mutations in other genes were seen in one case each, the mean number of mutations were 1.2, and maximum mutation in a single case (eight) was seen in one case. The bioinformatics analysis identified MAP kinase, PI3K-AKT, EGF/EGFR, and Focal Adhesion PI3K-AKT-mTOR signaling pathways and cross-talk between these. ConclusionThe results suggest that the complex crosstalk between the mTOR, MAPK, and multiple interacting cell signaling cascades can promote GBC progression, and hence, mTOR - MAPK targeted treatment will be an attractive option.

cancer biology↗

bioRxiv2022

Transcriptional fluctuations govern the serum dependent cell cycle duration heterogeneities in Mammalian cells

Mammalian cells exhibit a high degree of intercellular variability in cell cycle period and phase durations. However, the factors orchestrating the cell cycle duration heterogeneities remain unclear. Herein, by combining cell cycle network-based mathematical models with live single-cell imaging studies under varied serum conditions, we demonstrate that fluctuating transcription rates of cell cycle regulatory genes across cell lineages and during cell cycle progression in mammalian cells majorly govern the robust correlation patterns of cell cycle period and phase durations among sister, cousin, and mother-daughter lineage pairs. However, for the overall cellular population, alteration in serum level modulates the fluctuation and correlation patterns of cell cycle period and phase durations in a correlated manner. These heterogeneities at the population level can be finetuned under limited serum conditions by perturbing the cell cycle network using a p38-signaling inhibitor without affecting the robust lineage level correlations. Overall, our approach identifies transcriptional fluctuations as the key controlling factor for the cell cycle duration heterogeneities, and predicts ways to reduce cell-to-cell variabilities by perturbing the cell cycle network regulations. Significance statementIn malignant tumors, cells display a diverse pattern in cell division time. This cell-to-cell variability in cell cycle duration had been observed even under culture conditions for various mammalian cells. Here we used live-cell imaging studies to monitor FUCCI-HeLa cells and quantified the cell cycle period and time spent in different phases under varied serum conditions. We proposed a set of stochastic cell cycle network-based mathematical models to investigate the live-cell imaging data and unraveled that the transcription rate variation across cell lineages and during cell cycle phases explains every aspect of the cell cycle duration variabilities. Our models identified how different deterministic effects and stochastic fluctuations control these variabilities and predicted ways to alter these cell cycle duration variabilities.

systems biology↗