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Arasi, B.

Publications and source records attributed to Arasi, B..

2 recordsLinked to original sources

A Method to sort heterogenous cell populations based on migration in 2D and 3D environments

Whereas phenotypic assays such as Boyden chambers and wound healing assays can easily be employed to characterize the migratory potential of cells at the population level, few methods exist that can sort subpopulations of cells based on their migratory behaviour from an initial heterogeneous pool. In this paper, we present an approach to sort migratory cancer and immune cells based on their spontaneous migration in 2D and 3D microenvironments. Using this method, which is easy to implement and readily scalable, millions of live cells can be sorted based on their migratory characteristics and then subjected to downstream genomic, molecular and functional tests. We reveal that enrichment of the most migratory cytotoxic T lymphocytes yields a pool of cells with enhanced cytotoxicity against cancer cells. This new functional sorting method opens new avenues for the precise characterization of the mechanisms underlying hitherto unexplained heterogeneities in migratory phenotypes within a cell population, and for the targeted enrichment of the most potent migratory leukocytes in immunotherapies.

cell biology↗

Single-cell analysis of EphA clustering phenotypes to probe cancer cell heterogeneity

Eph receptors, a family of receptor tyrosine kinases, play a crutial role in the assembly and maintenance of healthy tissues. Dysfunction in Eph signaling are causally and correlatively associated with cancer progression. In breast cancer cells, dysregulated Eph signaling has been largely linked to alterations in receptor clustering abilities. In the present study, we implemented a single-cell assay and a scoring scheme to systematically probe the spatial organization of activated EphA receptor in carcinoma cells of different origin. Using this assay, we found that cancer cells retained EphA clustering phenotype upon cell division for several generations and degree of clustering reported for population as well as single-cell migration potential. Finally, using patient-derived cancer cell lines, we probed the evolution of EphA signalling in cancer cell populations that underwent metastatic transformation and acquisition of drug resistance. Taken together, our simple and scalable approach provides a reliable quantitation of EphA associated gene expression and phenotypes in multiple carcinomas and can assay the heterogeneity of cancer cell populations in a cost- and time-effective manner.

cancer biology↗