Determination of genes related to gastrointestinal tract origin cancer cells using a cDNA microarray.
ABSTRACT We evaluated the genome-wide gene expression profiles of various cancer cell lines to identify the gastrointestinal tract cancer cell-related genes.
Gene expression profilings of 27 cancer cell lines and 9 tissues using 7.5K human cDNA microarrays in indirect design with Yonsei reference RNA composed of 11 cancer cell line RNAs were done. The significant genes were selected using significant analysis of microarray in various sets of data. The selected genes were validated using real-time PCR analysis.
After intensity-dependent, within-print-tip normalization by loess method, we observed that expression patterns of cell lines and tissues were substantially different, divided in two discrete clusters. Next, we selected 115 genes that discriminate gastrointestinal cancer cell lines from others using significant analysis of microarray. Among the expression profiles of five gastric cancer cell lines, 66 genes were identified as differentially expressed genes related to metastatic phenotype. YCC-16, which was established from the peripheral blood of one advanced gastric cancer patient, produced a unique gene expression pattern resembling the profiles of lymphoid cell lines. Quantitative real-time reverse transcription-PCR results of selected genes, including PXN, KRT8, and ITGB5, were correlated to microarray data and successfully discriminate the gastrointestinal tract cancer cell lines from hematologic malignant cell lines.
A gene expression database could serve as a useful source for the further investigation of cancer biology using the cell lines.
- SourceAvailable from: Swetha Raghavan[Show abstract] [Hide abstract]
ABSTRACT: Genomic aberrations are common in cancers and the long arm of chromosome 1 is known for its frequent amplifications in breast cancer. However, the key candidate genes of 1q, and their contribution in breast cancer pathogenesis remain unexplored. We have analyzed the gene expression profiles of 1635 breast tumor samples using meta-analysis based approach and identified clinically significant candidates from chromosome 1q. Seven candidate genes including exonuclease 1 (EXO1) are consistently over expressed in breast tumors, specifically in high grade and aggressive breast tumors with poor clinical outcome. We derived a EXO1 co-expression module from the mRNA profiles of breast tumors which comprises 1q candidate genes and their co-expressed genes. By integrative functional genomics investigation, we identified the involvement of EGFR, RAS, PI3K / AKT, MYC, E2F signaling in the regulation of these selected 1q genes in breast tumors and breast cancer cell lines. Expression of EXO1 module was found as indicative of elevated cell proliferation, genomic instability, activated RAS/AKT/MYC/E2F1 signaling pathways and loss of p53 activity in breast tumors. mRNA-drug connectivity analysis indicates inhibition of RAS/PI3K as a possible targeted therapeutic approach for the patients with activated EXO1 module in breast tumors. Thus, we identified seven 1q candidate genes strongly associated with the poor survival of breast cancer patients and identified the possibility of targeting them with EGFR/RAS/PI3K inhibitors.PLoS ONE 01/2013; 8(10):e77553. · 3.53 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: Activation of plasminogen on the cell surface initiates a cascade of protease activity with important implications for several physiological and pathological events. In particular, components of the plasminogen system participate in tumor growth, invasion and metastasis. Plasminogen receptors are in fact expressed on the cell surface of most tumors, and their expression frequently correlates with cancer diagnosis, survival and prognosis. Notably, they can trigger multiple specific immune responses in cancer patients, highlighting their role as tumor-associated antigens. In this review, three of the most characterized plasminogen receptors involved in tumorigenesis, namely Annexin 2 (ANX2), Cytokeratin 8 (CK8) and alpha-Enolase (ENOA), are analyzed to ascertain an overall view of their role in the most common cancers. This analysis emphasizes the possibility of delineating new personalized therapeutic strategies to counteract tumor growth and metastasis by targeting plasminogen receptors, as well as their potential application as cancer predictors.Experimental hematology & oncology. 04/2013; 2(1):12.
- [Show abstract] [Hide abstract]
ABSTRACT: Mucinous colorectal carcinoma exhibits distinct clinicopathological features compared to non-mucinous colorectal carcinoma. Previous studies have discovered several molecular genetic features in mucinous colorectal carcinomas, but have limitations as they are confined to a small number of molecules. To understand the mucinous colorectal carcinoma system, this study was designed to identify genes that are differentially expressed in mucinous colorectal carcinoma compared to non-mucinous colorectal carcinoma using cDNA microarrays. cDNA microarray experiments were performed using human cDNA 17k chips with 25 mucinous and 27 non-mucinous cancer tissues. Differentially expressed genes (DEGs) were determined by Welch's t-test and more accurate classifiers were selected from the DEGs using the prediction analysis for microarrays (PAM) software package. Array results were validated using quantitative real-time RT-PCR. The identified gene set was functionally investigated through in silico analysis. Sixty-two DEGs were identified and the 50 highest ranking genes could be used to accurately classify mucinous and non-mucinous colorectal carcinomas. The identified gene set included up-regulated TFF1 (4-fold), AGR2 (3.3-fold), FSCN1 (2.2-fold), CD44 (1.5-fold) and down-regulated SLC26A3 (0.2-fold) in MC. TFF1, AGR2 and SLC26A3 were validated by quantitative real-time RT-PCR. The functions of these DEGs were related to tumorigenesis (14 genes), cell cycle progression (6 genes), invasion (2 genes), anti-apoptosis (7 genes), cell adhesion and proliferation (5 genes) and carbohydrate metabolism (3 genes). We suggest that MC has distinct molecular characteristics from NMC and therefore, that the expression signatures of DEGs may improve the understanding of molecular pathogenesis and clinical behaviors in MC.Oncology Reports 03/2011; 25(3):717-27. · 2.30 Impact Factor