Biology subjects

Demirci, Y.

Publications and source records attributed to Demirci, Y..

3 recordsLinked to original sources

bioRxiv2022

Comparative membrane lipidomics of hepatocellular carcinoma cells reveals diacylglycerol and ceramide as key regulators of Wnt/β-catenin signaling and tumor growth

Hepatocellular carcinoma (HCC) is largely associated with aberrant activation of Wnt/{beta}-catenin signaling. Nevertheless, how membrane lipid composition is altered in HCC cells with abnormal Wnt signaling remains elusive. Here, by exploiting comprehensive lipidome profiling, we unravel membrane lipid composition of six different HCC cell lines with mutations in components of Wnt/{beta}-catenin signaling, leading to differences in their endogenous signaling activity. Among the differentially regulated lipids are diacylglycerol (DAG) and ceramide, which were downregulated at the membrane of HCC cells after Wnt3a stimulation. DAG and ceramide enhanced Wnt/{beta}-catenin signaling in SNU475 and HepG2 cells. In contrast, depletion of DAG and ceramide suppressed Wnt/{beta}-catenin signaling and significantly impeded the proliferation, tumor growth and in vivo migration capacity of SNU475 and HepG2 cells. This study, by pioneering plasma membrane lipidome profiling in HCC cells, exhibits the remarkable potential of lipids to correct dysregulated signaling pathways in cancer and stop abnormal tumor growth.

cancer biology↗

bioRxiv2022

Wnt and BMP signaling enhance melanocyte regeneration and suppress melanoma cell migration

Tissue regeneration and cancer share remarkable features including activation of cell proliferation and migration. Yet, tumors considerably differ from the regenerating tissue with respect to abnormal proliferation, invasive growth, and metastasis. Thus, it is likely that cancer resembles early stages of regeneration with increased proliferation, but separates from the later stages with reduced proliferation and enhanced differentiation. Here, by exploiting the zebrafish melanocytes that can efficiently regenerate and be induced to undergo malignant melanoma, we unravel the transcriptome profiles of the regenerating melanocytes during early and late regeneration, and the melanocytic nevi and malignant melanoma. Our global comparison of the gene expression profiles of melanocyte regeneration and nevi/melanoma uncovers the differential regulation of a substantial number of genes related to Wnt signaling and TGF-{beta}/BMP signaling pathways between regeneration and cancer. Functional activation of canonical Wnt or TGF-{beta}/BMP pathways during melanocyte regeneration promoted melanocyte regeneration and potently suppressed the invasiveness, migration, and proliferation of human melanoma cells in vitro and in vivo. Therefore, differential regulation of signaling mechanisms between regeneration and cancer can be exploited to stop tumor growth and develop new anticancer therapies.

developmental biology↗

bioRxiv2019

A Generalized Similarity Metric for Peptide Binding Affinity Prediction

The ability to capture the relationship between similarity and functionality would enable the predictive design of peptide sequences for a wide range of implementations from developing new drugs to molecular scaffolds in tissue engineering and biomolecular building blocks in nanobiotechnology. Similarity matrices are widely used for detecting sequence homology but depend on the assumption that amino acid mutational frequencies reflected by each matrix are relevant to the system in which they are applied. Increasingly, neural networks and other statistical learning models solve problems related to functional prediction but avoid using known features to circumvent unconscious bias. We demonstrated an iterative alignment method that enhances predictive power of similarity matrices based on a similarity metric, the Total Similarity Score. A generalized method is provided for application to amino acid sequences from inorganic and organic systems by benchmarking it on the debut quartz-binder set and 3 peptide-protein sets from the Immune Epitope Database. Pearson and Spearman Rank Correlations show that by treating the gapless Total Similarity Score as a predictor of relative binding affinity, prediction of test data has a 0.5-0.7 Pearson and Spearman Rank correlation. with respect to size of the dataset. Since the benchmarks used herein are from a solid-binding peptide and a protein-peptide system, our proposed method could prove to be a highly effective general approach for establishing the predictive sequence-function relationships of among the peptides with different sequences and lengths in a wide range of biotechnology, nanomedicine and bioinformatics applications.\n\nAuthor SummaryThe significance of this work is to expand the applicability of a known metric for describing the function of tiny proteins also called peptides. The Total Similarity Score (TSS) can describe how similar a peptide, or a group of peptides are to another group of sequences with a known or suspected function. A peptide/group of peptides will always have a high TSS if it contains the same or similar amino acids in the same positions. This metric can therefore be used to select peptides for useful functions based purely on conserved amino acids in unknown positions. The greedy search algorithm used to learn how similar amino acids are to each other has been shown to be marginally effective in this larger dataset. Therefore, we argue that the TSS metric is a highly useful one for predicting peptide affinity but a different machine learning algorithm should be applied to make full use of it.

bioinformatics↗