GCRIS

Melanoma is the deadliest form of skin cancer and develops from the melanocytes that are responsible for the pigmentation of the skin. The skin is also a highly regenerative organ, harboring a pool of undifferentiated melanocyte stem cells that proliferate and differentiate into mature melanocytes during regenerative processes in the adult. Melanoma and melanocyte regeneration share remarkable cellular features, including activation of cell proliferation and migration. Yet, melanoma considerably differs from the regenerating melanocytes with respect to abnormal proliferation, invasive growth, and metastasis. Thus, it is likely that at the cellular level, melanoma resembles early stages of melanocyte regeneration with increased proliferation but separates from the later melanocyte regeneration stages due to 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 opposite regulation of a substantial number of genes related to Wnt signaling and transforming growth factor beta (TGF-beta)/(bone morphogenetic protein) BMP signaling pathways between regeneration and cancer. Functional activation of canonical Wnt or TGF-beta/BMP pathways during melanocyte regeneration promoted melanocyte regeneration but potently suppressed the invasiveness, migration, and proliferation of human melanoma cells in vitro and in vivo. Therefore, the opposite regulation of signaling mechanisms between melanocyte regeneration and melanoma can be exploited to stop tumor growth and develop new anti-cancer therapies.

Collective cell analysis from microscopy image series is important for wound healing research. Computer-based automation of such analyses may help in rapid acquisition of reliable and reproducible results. In this study phase -contrast optical microscopy image series of an in-vitro wound healing essay is manually delineated by two experts and its analysis is realized, traditional image processing and deep learning based approaches for automated segmentation of wound area are developed and their perlOrmance comparisons are carried out.

Molecular Biology and Genetics / Moleküler Biyoloji ve Genetik

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