2012年11月
TMEM158 and FBLP1 as novel marker genes of cisplatin sensitivity in non-small cell lung cancer cells
EXPERIMENTAL LUNG RESEARCH
- 巻
- 38
- 号
- 9-10
- 開始ページ
- 463
- 終了ページ
- 474
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.3109/01902148.2012.731625
- 出版者・発行元
- INFORMA HEALTHCARE
Even after development of molecular targeting therapies, platinum-based chemotherapy is still a standard care for treatment of locally advanced non-small cell lung cancer (NSCLC). So far, critical molecular markers capable to predict the therapeutic response in NSCLC patients remain undetermined. We here attempted to identify novel biomarker genes for cisplatin (CDDP) for a tailored therapy. Initial screening to explorer association of IC50 values of CDDP obtained by MTT assay and gene expression levels measured with oligonucleotide microarray and real-time RT-PCR provided 6 candidate genes, namely, NUBPL, C9orf30, ZNF12, TMEM158, GSK3B, and FBLP1 using 9 lung cancer cells consisting of 3 small and 6 NSCLC cells. These 6 genes together with 5 reported biomarkers, i.e., GSTP1, ERCC1, BRCA1, FRAP1, and RRM1, were subjected to a linear regression analysis using 12 NSCLC cell lines including 6 additional NSCLC cells: only FBLP1 and TMEM158 genes showed positive associations with statistical significances (P = .016 and .026, respectively). The biological significance of these genes was explored by in vitro experiments: Knockdown experiments in PC-9/CDDP cells revealed that the reduced expression of TMEM158 significantly decreased the chemo-resistance against CDDP (P < .0001), while 2 transformants of PC-6 cells stably over-expressing FBLP1 resulted in an enhanced resistance to CDDP (P = .004 and P = .001). Furthermore, a stepwise multiple regression analysis demonstrated the best prediction formula could be fixed when we used expression data of TMEM158 and FBLP1 (R-2 = 0.755, P = .0018). TMEM158 and FBLP1 may be powerful predictive biomarkers for CDDP therapy in NSCLC.
- リンク情報
- ID情報
-
- DOI : 10.3109/01902148.2012.731625
- ISSN : 0190-2148
- eISSN : 1521-0499
- Web of Science ID : WOS:000310347900004