Mapping the lung cancer methylome

Wright, C. M., Francis, S. M. S., Sriram, K. B., Quinn, K. R., Stark, M. S., Hayward, N. K., Yang, I. A., Bowman, R. V. and Fong, K. M. (2011). Mapping the lung cancer methylome. In: Supplement to Journal of Thoracic Oncology: 3rd Australian Lung Cancer Conference (ALCC). 3rd Australian Lung Cancer Conference (ALCC), Melbourne VIC, Australia, (S10-S10). 6-9 October 2010.

Author Wright, C. M.
Francis, S. M. S.
Sriram, K. B.
Quinn, K. R.
Stark, M. S.
Hayward, N. K.
Yang, I. A.
Bowman, R. V.
Fong, K. M.
Title of paper Mapping the lung cancer methylome
Conference name 3rd Australian Lung Cancer Conference (ALCC)
Conference location Melbourne VIC, Australia
Conference dates 6-9 October 2010
Proceedings title Supplement to Journal of Thoracic Oncology: 3rd Australian Lung Cancer Conference (ALCC)   Check publisher's open access policy
Journal name Journal of Thoracic Oncology   Check publisher's open access policy
Place of Publication Philadelphia PA, United States
Publisher Lippincott Williams & Wilkins
Publication Year 2011
Year available 2011
Sub-type Published abstract
Open Access Status
ISSN 1556-0864
1556-1380
Volume 6
Issue 3, Supp. 1
Start page S10
End page S10
Total pages 1
Collection year 2012
Language eng
Formatted Abstract/Summary
Epigenetic gene inactivation of tumour suppressor genes underlies several human cancers. The potential to develop targeted therapies is being driven by the recent development of high-throughput genome-wide approaches including
methylation-based microarrays. Here we report a large-scale project aiming to characterize the lung cancer methylome.

Methods: Methylation profiling by Illumina Infinium Methylation27 arrays was performed on 226 primary lung tumours and 81 normal lung samples from the TPCH lung tumour bank. Data was feature extracted using proprietary software (Genome Studio, Illumina, Hayward, CA). We used two separate approaches in gene identification: 1) we utilised stringent criteria employed by the The Cancer Genome Atlas (TCGA) project on Glioblastoma performing separate analyses for training and test sets and 2) we used in-house (TPCH) criteria (vis. (1) false discovery rate (FDR) P<1x10E-7, (2) P-value < 1x10E-7, (3) frequency of methylation across samples and (4) magnitude of difference between normal/tumour pairs (at least 2-fold)).

Results: Unsupervised cluster analyses demonstrated distinct clusters for normal and tumour lung and in primary tumours identified six distinct tumour clades which could not be explained purely by histology. Differential methylation analysis identified 171 CpG loci highly methylated in tumours exhibiting substantially higher methylation levels compared to common lung cancer methylation markers including P16, MGMT and DAPK1. Next, we demonstrate samples frequently methylated across multiple genes demonstrate a survival advantage. Finally, we report methylation signatures capable of distinguishing adenocarcinoma and squamous cell carcinoma histologies.

Discussion:
DNA methylation profiles differ between normal and tumour lung and are predictive of adenocarcinoma and squamous cell carcinoma histology. Further validation studies are required to confirm involvement of candidate genes in lung carcinogenesis.
Q-Index Code EX
Q-Index Status Provisional Code
Institutional Status UQ
Additional Notes Published under Young Investigator/Fellow Abstract Orals: 3rd Australian Lung Cancer Conference (ALCC).

Document type: Conference Paper
Collections: Temporary Review
School of Medicine Publications
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Google Scholar Search Google Scholar
Created: Sun, 20 Mar 2011, 00:11:21 EST