Biology subjects

Chan, P. Y.

Publications and source records attributed to Chan, P. Y..

2 recordsLinked to original sources

bioRxiv2020

Tumorigenic epithelial clusters are less sensitive to moderate osmotic stresses due to low amounts of junctional E-cadherin

The migration of tumorigenic epithelial cells is a critical step for metastatic breast cancer progression. Although the role of the extracellular matrix in breast cancer cell migration has been extensively described, the effect of osmotic stress on the migration of tumor breast epithelial cohorts remains unclear. Most of our understanding on the effect of osmotic stresses on cell migration comes from studies at the level of the single cell in isolation and does not take into account cell-cell interactions. Here, we study the impact of moderate osmotic stress on the migration of epithelial clusters composed of either non-tumorigenic or tumorigenic epithelial cells. We observe a decrease in migration distance and speed for non-tumorigenic epithelial cells but not for tumorigenic ones. To explain these differences, we investigate how osmotic stress impacts the mechanical properties of cell clusters and affects cell volumes. After application of osmotic stress renal epithelial cells become stiffer whereas non-tumorigenic and tumorigenic breast epithelial cells do not. In addition, tumorigenic cells are shown to be less sensitive to osmotic stress than non-tumorigenic cells, and this difference is associated with lower levels of E-cadherin expression. Using EGTA treatments, we confirm that the establishment of cell-cell adhesive interactions is a key component of the behavior of epithelial clusters in response to osmotic stress. This study provides evidence on the low sensitivity of tumorigenic epithelial clusters to moderate osmotic stress and highlights the importance of cadherin-based junctions in response to osmotic stress.

biophysics↗

bioRxiv2019

High-sensitivity monitoring of ctDNA by patient-specific sequencing panels and integration of variant reads

Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Patients with small tumors have few copies of ctDNA in plasma, resulting in limited sensitivity to detect low-volume or residual disease. We show that sampling limitations can be overcome and sensitivity for ctDNA detection can be improved by massively parallel sequencing when hundreds to thousands of mutations are identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) analysis pipeline, which combines patient-specific mutation lists with both custom error-suppression methods and signal enrichment based on biological features of ctDNA. In this framework, the sensitivity can be estimated independently for each sample based on the number of informative reads, which is the product of the number of mutations analyzed and the average depth of unique sequencing reads. We applied INVAR to deep sequencing data generated by custom hybrid-capture panels, and showed that when ~106 informative reads were obtained INVAR allowed detection of tumor-derived DNA fractions to parts per million (ppm). In serial samples from patients with advanced melanoma on treatment, we detected ctDNA when imaging confirmed tumor volume of ~1cm3. In patients with resected early-stage melanoma, ctDNA was detected in 40% of patients who later relapsed, with higher rates of detection when more informative reads were obtained. We further demonstrated that INVAR can be generalized and allows improved detection of ctDNA from whole-exome and low-depth whole-genome sequencing data.

cancer biology↗