Genome-wide identification of possible methylation markers chemosensitive to targeted regimens in colorectal cancers

Autor: Seon Ye Kim, Yoon Kyung Cho, Eun Y. Choi, Ye J. Ha, Pyong W. Choi, Han C. Lee, Seon Ae Roh, Yong Sung Kim, Dong H. Cho, Jin C. Kim
Rok vydání: 2011
Předmět:
Zdroj: Journal of cancer research and clinical oncology. 137(10)
ISSN: 1432-1335
Popis: Few efficient methylation markers of chemosensitivity have been discovered. The genome-wide analysis of methylation markers is needed to identify chemosensitive candidates to targeted therapy. This study describes a two-step process to select chemosensitive candidates of methylation genes. A genome-wide screening of methylation genes was performed using a Beadarray and an in vitro chemosensitivity assay of 119 colorectal cancers (CRCs). Ten candidate genes identified during the initial screening were verified by biological utility assessment using cell viability assays of transfected CRC cells. Five methylation genes related to sensitivity to bevacizumab regimens (RASSF1, MMP25, KCNQ1, ESR1, and GALR2) or cetuximab regimens (SCL18A2, GPX7, NID2, IGFBP3, and ALX4) were chosen during the first step. A viability assay revealed that GALR2-overexpressing HCT116 cells were significantly more chemosensitive to bevacizumab regimens than control cells (P = 0.022 and 0.019 for bevacizumab with FOLFIRI and FOLFOX, respectively), concurrently verified on a caspase-3 activity assay. GPX7- or ALX4-overexpressed RKO cells were significantly less viable to cetuximab regimens compared to control cells (GPX7: P = 0.027 each for cetuximab with FOLFIRI and FOLFOX; ALX4: P = 0.049 and 0.003 for cetuximab with FOLFIRI and FOLFOX, respectively), but caspase-3 activity was not prominent in GPX7-overexpressed RKO cells. Two novel genes, GALR2 and ALX4, have been identified as chemosensitive methylation candidates to bevacizumab and cetuximab regimens, respectively. As our study did not include a clinical association study, the two candidates should be validated in large clinical cohorts, hopefully predicting responsive patients to targeted regimens.
Databáze: OpenAIRE