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Biology subjects

Silvers, T. R.

Publications and source records attributed to Silvers, T. R..

2 recordsLinked to original sources

A stress response that allows highly mutated eukaryotic cells to survive and proliferate

Rapid mutation fuels the evolution of many cancers and pathogens. Much of the ensuing genetic variation is detrimental, but cells can survive by limiting the cost of accumulating mutation burden. We investigated this behavior by propagating hypermutating yeast lineages to create independent populations harboring thousands of distinct genetic variants. Mutation rate and spectrum remained unchanged throughout the experiment, yet lesions that arose early were more deleterious than those that arose later. Although the lineages shared no mutations in common, each mounted a similar transcriptional response to mutation burden. The proteins involved in this response formed a highly connected network that has not previously been identified. Inhibiting this response increased the cost of accumulated mutations, selectively killing highly mutated cells. A similar gene expression program exists in hypermutating human cancers and is linked to survival. Our data thus define a conserved stress response that buffers the cost of accumulating genetic lesions and further suggest that this network could be targeted therapeutically.

genetics↗

Multiparameter cell characterization using nanofluidic technology facilitates real-time phenotypic and genotypic elucidation of intratumor heterogeneity

Genetic and functional complexity of bulk tumor has become evident through rapid advances in sequencing technologies. As a unique integrated approach to characterizing tumor heterogeneity, we demonstrate the multifaceted capabilities of a novel nanofluidic platform to enable single-cell phenotypic and genetic profiling of ovarian cancer patient-derived tumor cells. This approach has enabled increased resolution of tumor cell phenotypic and genetic heterogeneity, providing a better understanding of underlying biological drivers of the disease. A range of CA-125 expression levels is observed within cells from individuals, demonstrating clonal diversity consistent with other phenotypic data. Further, TP53 mutation analysis demonstrates a sub-population of cells exhibiting high mutation frequency that likely drives downstream growth kinetics and protein expression. Finally, genomic data is orthogonally used to address clonal heterogeneity across ovarian tumors when compared to bulk sequencing, illustrating the potential for single-cell sequencing data integrated with cellular functional and growth data toward future therapeutic intervention.

genomics↗