P28. Prediction of prognosis for small cell lung cancer based on genome-wide methylation analyses
CELCC 2014 Abstracts

P28. Prediction of prognosis for small cell lung cancer based on genome-wide methylation analyses

Yuichi Saito, Genta Nagae, Noriko Motoi, Makoto Nishio, Sakae Okumura, Hiroyuki Aburatani, Yuichi Ishikawa

1The Cancer Institute, Japanese Foundation for Cancer Research, Tokyo, Japan; 2Research Center for Advanced Science and Technology, University of Tokyo, Tokyo, Japan; 3The Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan

Background: The CpG island methylate phenotype (CIMP) displays characteristic alterations of promoter DNA methylation in colorectal cancers, glioblastoma and breast cancers, although there has been no report about any CIMP of small cell lung cancer (SCLC). We investigated whether DNA methylation profiles can provide useful molecular subtyping of SCLC in terms of etiology and prognosis of SCLC.

Methods: We analyzed 28 fresh frozen samples from pure SCLC patients and 13 noncancerous lung tissues. All patients underwent surgical lung resection at the Cancer Institute Hospital, nine patients among them were treated with chemotherapy before surgery. After genomic DNA was treated with sodium bisulfite, bisulfite-converted genomic DNA was analyzed using Illumina’s Infinium HumanMethylation27 BeadChip. And, total RNA was extracted from 25 SCLC tumor samples and mRNA expression of these samples were analyzed by Agilent’s SurePrint G3 Human CGH Microarray. Next, we matched these two data sets by Gene Symbol, and identified fifty-five most differentially methylated CpG sites. Gene ontology analysis was performed using DAVID Bioinformatics Resources.

Results: We selected a total of 1,741 most differentially methylated CpG sites (SD >0.20) across the 28 SCLC tumor tissues in each DNA methylation platform, after an elimination of the probes related with the X- and Y- chromosome. Unsupervised hierarchical clustering of methylation data from SCLC samples reveals two major subgroups with different prognosis: the 5 years disease-free survival (DFS) rate of patients in cluster 1 (11.1%) was lower than that of patients in cluster 2 (61.57%) (P=0.001). By multivariate analysis for DFS, both postoperative chemotherapy and cluster 1 were a significant prognostic factor (P=0.002 and 0.002; respectively).

Conclusions: By comprehensive DNA methylation profiling, two distinct subgroups with different molecular and clinical phenotype were identified to evoke a CIMP of SCLC. We hope that our data can contribute to provide a useful resource for the construction of therapeutic strategy and the development of a new chemotherapeutic agent.

Keywords: Small cell lung cancer (SCLC); methylation

doi: 10.3978/j.issn.2218-6751.2014.AB040

Cite this article as: Saito Y, Nagae G, Motoi N, Nishio M, Okumura S, Aburatani H, Ishikawa Y. Prediction of prognosis for small cell lung cancer based on genome-wide methylation analyses. Transl Lung Cancer Res 2014;3(5):AB040. doi: 10.3978/j.issn.2218-6751.2014.AB040

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