bioRxivCancer BiologyPreprint
Alisertib exerts KRAS allele specific anticancer effects in colorectal cancer
B. Ren, Z. Gao, K. Zheng, Y. Yang, P. Su, Q. Luo, J. Feng, Z. Luo, Y. Geng, Y. Ju, Z. Huang
Abstract
Colorectal cancer (CRC) is a common cancer causing substantial mortality and morbidity worldwide. Oncogene RAS mutations occur notably in [~]45% of CRCs, associated with a poor prognosis. KRAS is subject to multiple tiers of regulation, including kinase. Aurora kinases has been implicated in many types of tumor onsets and progression, making them as a promising therapeutic targets. Alisertib (ALS), selectively inhibits Aurora kinase A (AURKA) and exerts potent anticancer activities in vitro and in vivo studies, but the latent anticancer effect of ALS on CRC remains unclear in the context of different KRAS mutations. This study aimed to assess the effects of ALS on RAS signaling pathway in a panel of CRC lines expressing different KRAS alleles, including Caco-2 (KRAS WT), Colo-678 (KRAS G12D), SK-CO-1 (KRAS G12V), HCT116 (KRAS G13D), CCCL-18 (KRAS A146T), and HT29 (BRAF V600E). The results showed that ALS modulated the active form of KRAS in a RAS allele specific manner across the panel of CRC lines; ALS differentially regulated RAS signal via PI3K/Akt and MAPK pathways; and ALS induced apoptosis and autophagy in a RAS allele specific manner. Of note, in combination of ALS and MEK inhibitor, selumetinib, enhanced ALS regulatory effects in CRC lines in a RAS allele specific manner on apoptosis, autophagy, and cell growth. Taken together, this study suggests that ALS differentially regulates RAS signaling pathway and manipulates cell apoptosis and autophagy in RAS allele specific manner. The combinatorial approach of ALS and MEK inhibitor may represent a new therapeutic strategy for precision therapy of CRC in a RAS allele manner.
- organism: human
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: drug response / drug discovery
- research focus: gene regulatory network inference
- approach: experimental assay
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