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| Status |
Public on Apr 03, 2012 |
| Title |
AMPKα Modulation in Cancer Progression: Multilayer Integrative Analysis of the Whole Transcriptome in Asian Gastric Cancer |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
Non-coding RNA profiling by high throughput sequencing
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| Summary |
Gastric cancer is the most common cancer in Asia and most developing countries. To identify the molecular underpinnings of gastric cancer in the Asian population, we applied an RNA-sequencing approach to gastric tumor and noncancerous specimens to quantitatively characterize the entire transcriptome of gastric cancer (including mRNAs and microRNAs). A multi-layer analysis was then developed to identify multiple types of transcriptional aberrations associated with different stages of gastric cancer, including differentially expressed mRNAs, recurrent somatic mutations and key differentially expressed microRNAs. Through this approach, we identified the central metabolic regulator AMPK-α as a potential functional target in Asian gastric cancer. Further, we experimentally demonstrated the translational relevance of this gene as a potential therapeutic target for early-stage gastric cancer in Asian patients. Together, our findings not only provide a valuable information resource for identifying and elucidating the molecular mechanisms of Asian gastric cancer, but also represent a general integrative framework to develop more effective therapeutic targets.
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| Overall design |
Using Life Technologies SOLiD™ sequencing platform, we performed transcriptome-wide profiling of gastric cancer samples from 30 anonymous, unrelated Asians of both sexes. Included were six noncancerous gastric tissue samples and 24 gastric tumor samples that represented stages I through IV of tumor development. From the WT-seq protocol we generated a WT-seq dataset of 2.1 billion 50-nt short reads from the 30 samples; Applying the second small RNA-seq protocol to 19 gastric tumor samples (5 of the original 24 yielded insufficient sample amounts) and 6 noncancerous gastric tissue samples resulted in a small RNA-seq dataset.
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| Contributor(s) |
Kim YH, Liang H, Liu X, Lee J, Cho JY, Cheong J, Kim H, Li M, Downey TJ, Dyer MD, Sun Y, Sun J, Beasley EM, Chung HC, Noh SH, Weinstein JN, Liu C, Powis G |
| Citation(s) |
22434430, 25410163 |
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| Submission date |
Mar 30, 2012 |
| Last update date |
May 15, 2019 |
| Contact name |
Han Liang |
| E-mail(s) |
hliang1@mdanderson.org
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| Phone |
1-713-745-9815
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| Fax |
1-713-563-4242
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| Organization name |
University of Texas MD Anderson Cancer Center
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| Department |
Bioinformatics and Computational Biology
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| Lab |
Dr. Han Liang
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| Street address |
1400 Pressler Street
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| City |
Houston |
| State/province |
TX |
| ZIP/Postal code |
77030 |
| Country |
USA |
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| Platforms (1) |
| GPL9442 |
AB SOLiD System 3.0 (Homo sapiens) |
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| Samples (55)
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| Relations |
| SRA |
SRP012016 |
| BioProject |
PRJNA157511 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE36968_GeneExpressionRPKM_30Sample_WT.xls.gz |
5.4 Mb |
(ftp)(http) |
XLS |
| GSE36968_miRNAExpressionRPM_25Sample_smRNA.xls.gz |
97.6 Kb |
(ftp)(http) |
XLS |
SRA Run Selector |
| Processed data are available on Series record |
| Raw data are available in SRA |
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