Dataset Information

Gene Expression Profiling of Gastric Cancer.

ABSTRACT: Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent's whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma.

SUBMITTER: Marimuthu A

PROVIDER: S-EPMC4809432 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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Gene Expression Profiling of Gastric Cancer.

Marimuthu Arivusudar A Jacob Harrys K C HK Jakharia Aniruddha A Subbannayya Yashwanth Y Keerthikumar Shivakumar S Kashyap Manoj Kumar MK Goel Renu R Balakrishnan Lavanya L Dwivedi Sutopa S Pathare Swapnali S Dikshit Jyoti Bajpai JB Maharudraiah Jagadeesha J Singh Sujay S Sameer Kumar Ghantasala S GS Vijayakumar M M Veerendra Kumar Kariyanakatte Veeraiah KV Premalatha Chennagiri Shrinivasamurthy CS Tata Pramila P Hariharan Ramesh R Roa Juan Carlos JC Prasad T S K TS Chaerkady Raghothama R Kumar Rekha Vijay RV Pandey Akhilesh A

Journal of proteomics & bioinformatics 20110416 4

Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent's whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tu ...[more]

PMID: 27030788

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Project description:Surgically resected gastric adenocarcinoma samples and their paired disease-free (R0) marginal nonmalignant tissue were obtained from 14 patients with gastric adenocarcinoma. RNA was isolated using the RNAeasy Kit (Qiagen Valencia, CA) from 15 mg of tissue. The quality of total RNA and its integrity was assessed using the Bioanalyzer 2100 (Agilent, Palo Alto, CA) and RIN value (RNA Integrity Number) was recorded for all the samples for intact 18S and 28S rRNA. Total RNA (800 ng) from each sample was reverse transcribed and linear amplified using the low RNA input linear amplification kit (Agilent Technologies). After synthesis of the first and second strand of cDNA, the product was used in an in vitro transcription reaction to generate cRNAs in the presence of cyanine 3-labeled UTP (Cy3) for normal and cyanine 5-labeled UTP (Cy5) for tumor. Fragmented Cy3-labeled cRNA of the control sample were mixed with equal amounts of Cy5-labeled cRNA from the gastric tumor sample, and the mixtures were hybridized onto 44K whole human genome DNA microarrays (Agilent Technologies) for 17 hrs at 65°C with constant rotation (10 rpm). Subsequently, the arrays were washed according to manufacturer’s instructions. The slides were scanned using an Agilent microarray scanner (G2565AA), and the images were processed using the Agilent feature extraction software AFE 9.5. GeneSpring GX v10.1 (Agilent Technologies) was used to analyze the expression profiles obtained after microarray hybridization. The feature extraction files from all the samples were uploaded to GeneSpring. Following intensity-dependent normalization (Lowess), the data was subjected to statistical analysis. A two tailed student’s t-test was used to determine significance of the differences observed between the normal and tumor samples. Benjamini Hochberg algorithm was used to compute false discovery rates. Genes were filtered based on P value threshold of 0.001 and false discovery rate of less than 1%.

Project description:AimTo investigate the differentiated whole genome expression profiling of gastric high- and low-grade intraepithelial neoplasia and early-stage adenocarcinoma.MethodsGastric specimens from an upper magnifying chromoendoscopic targeted biopsy were collected from March 2010 to May 2013. Whole genome expression profiling was performed on 19 low-grade intraepithelial neoplasia (LGIN), 20 high-grade intraepithelial neoplasia (HGIN), 19 early-stage adenocarcinoma (EGC), and 19 chronic gastritis tissue samples using Agilent 4 × 44K Whole Human Genome microarrays. Differentially expressed genes between different types of lesions were identified using an unpaired t-test and corrected with the Benjamini and Hochberg false discovery rate algorithm. A gene ontology (GO) enrichment analysis was performed using the GeneSpring software GX 12.6. The differentially expressed gene was verified using a real-time TaqMan® PCR assay with independent tissue samples, including 26 LGIN, 15 HGIN, 14 EGC, and 20 chronic gastritis. The expression of G0S2 were further validated by immunohistochemical staining (IHC) in 24 LGIN, 40 HGIN, 30 EGC and 61 chronic gastritis specimens.ResultsThe gene expression patterns of LGIN and HGIN tissues were distinct. There were 2521 significantly differentially expressed transcripts in HGIN, with 951 upregulated and 1570 downregulated. A GO enrichment analysis demonstrated that the most striking overexpressed transcripts in HGIN compared with LGIN were in the category of metabolism, defense response, and nuclear factor κB (NF-κB) cascade. While the vast majority of transcripts had barely altered expression in HGIN and EGC tissues, only 38 transcripts were upregulated in EGC. A GO enrichment analysis revealed that the alterations of the immune response were most prominent in the progression from HGIN to EGC. It is worth noting that, compared with LGIN, 289 transcripts were expressed at higher levels both in HGIN and EGC. A characteristic gene, G0/G1 switch 2 (G0S2) was one of the 289 transcripts and related to metabolism, the immune response, and the NF-κB cascade, and its expression was validated in independent samples through real-time TaqMan® PCR and immunohistochemical staining. In real-time PCR analysis, the expression of G0S2 was elevated both in HGIN and EGC compared with that in LGIN (P < 0.01 and P < 0.001, respectively). In IHC analysis, G0S2 immunoreactivity was detected in the cytoplasmic of neoplastic cells, but was undetectable in chronic gastritis cells. The G0S2 expression in HGIN was higher than that of LGIN (P = 0.012, χ (2) = 6.28) and EGC (P = 0.008, χ (2) = 6.94).ConclusionA clear biological distinction between gastric high- and low-grade intraepithelial neoplasia was identified, and provides molecular evidence for clinical application.

Dataset Information

Gene Expression Profiling of Gastric Cancer.

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Gene Expression Profiling of Gastric Cancer.

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