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Biology subjects

Chung, C. Y.-L.

Publications and source records attributed to Chung, C. Y.-L..

2 recordsLinked to original sources

Chemo-senolytic therapeutic potential against angiosarcoma

Angiosarcoma is an aggressive soft-tissue sarcoma with a poor prognosis. Chemotherapy for this cancer typically employs paclitaxel, one of the taxanes (genotoxic drugs), although it has a limited effect due to chemoresistance for prolonged treatment. Here we examine a new angiosarcoma treatment approach that combines chemotherapeutic and senolytic agents. We first find that the chemotherapeutic drugs, cisplatin and paclitaxel, efficiently induce cellular senescence of angiosarcoma cells. Subsequent treatment with a senolytic agent, ABT-263, eliminates senescent cells through the activation of the apoptotic pathway. In addition, expression analysis indicates that senescence-associated secretory phenotype (SASP) genes are activated in senescent angiosarcoma cells and that ABT-263 treatment eliminates senescent cells expressing genes in the type-I interferon (IFN-I) pathway. Moreover, we show that cisplatin treatment alone requires a high dose to remove angiosarcoma cells, whereas a lower dose of cisplatin is sufficient to induce senescence, followed by the elimination of senescent cells by senolytic treatment. This study sheds light on a potential therapeutic strategy against angiosarcoma by combining a relatively low dose of cisplatin with the ABT-263 senolytic agent, which can help ease the deleterious side effects of chemotherapy.

cancer biology↗

Accurate identification of structural variations from cancer samples

Structural variations (SVs) are commonly found in cancer genomes. They can cause gene amplification, deletion, and fusion, among other functional consequences. With an average read length of hundreds of kilobases, nano-channel-based optical DNA mapping is powerful in detecting large SVs. However, existing SV calling methods are not tailored for cancer samples, which have special properties such as mixed cell types and sub-clones. Here we propose the COMSV method that is specifically designed for cancer samples. It shows high sensitivity and specificity in benchmark comparisons. Applying to cancer cell lines and patient samples, COMSV identifies hundreds of novel SVs per sample.

genomics↗