Synchronous global assessment of gene and protein expression in colorectal cancer progression
Section snippets
Results
Sixty samples, 10 from each of the six clinical stages of colorectal cancer (normal mucosa, adenoma, Duke B1, Duke C2, Duke D, and liver metastasis), were selected from those archived in the H. Lee Moffitt Cancer Center Sample Registry. Following microdissection, RNA and protein were extracted from the same frozen tissue block for cDNA microarray and proteomic analysis. RNA samples were fluorescently labeled and cohybridized with a labeled common reference RNA to a 32,488-element cDNA
Discussion
Cancer is a complex disease arising from the interplay of genetic and environmental factors. Traditionally, cancer research has been conducted using a candidate gene/factor approach, examining a single factor at a time. The success of genome sequencing projects and technological advances in functional genomics and proteomics has facilitated the transition to large-scale systemic approaches to studying disease. mRNA expression profiling by cDNA or oligonucleotide microarrays has been employed in
Sample selection
Sixty anonymous samples, 10 from each of the six clinical stages of colorectal cancer (normal mucosa, adenoma, Duke B1, Duke C2, Duke D, and liver metastasis), were selected from those archived in the H. Lee Moffitt Cancer Center Sample Registry under IRB-approved protocols. Duke’s postresectional pathologic staging segregates tumors by the depth of penetration of the cancer through the bowel wall and by the presence or absence of lymph node or distant metastases. Staging is performed according
Acknowledgments
We thank the TIGR TM4 microarray software development team for their support and advice in data analysis, Jennifer Tsai and Joseph White for bioinformatics support, and Emily Chen, Jeremy Hasseman, and Ivana Yang for technical assistance. Analyses were performed using TIGR TM4 tools developed by Dr. John Quackenbush and the TIGR microarray software development team and using BRB Arraytools developed by Dr. Richard Simon and Amy Peng, This project was supported by grants from the U.S. National
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2013, Biochimica et Biophysica Acta - Reviews on CancerSVM-T-RFE: A novel gene selection algorithm for identifying metastasis-related genes in colorectal cancer using gene expression profiles
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2011, Journal of ProteomicsCitation Excerpt :However, the liver metastases specific cluster was not reproduced by another 2-DE study performed on reported microdissected CRC [21]. There are only two proteomic reports available that identified liver metastasis-associated proteins, yet the vast majority of the identified metastasis-associated proteins turned out to be known liver tissue specific proteins such as apolipoprotein and beta-globin, suggesting a high rate of false discovery due to contamination from the normal liver tissues [21,25]. At mRNA level, while Yamasaki et al. [26] and Ki et al. [27] were able to identify a group of genes that are specifically altered in metastases, such metastasis gene signatures were not found in the other two studies which used either laser microdissected [28] or manually microdissected tumour tissues [29].
Proteomic changes in the gills of wild-type and transgenic radiosensitive medaka following exposure to direct irradiation and to X-ray induced bystander signals
2011, Biochimica et Biophysica Acta - Proteins and ProteomicsCitation Excerpt :Indeed the 2D gel location of annexin max 3, in the present investigation, is similar to that of annexin II in rainbow trout [13]. Additionally both increased and decreased annexin A4 expressions have been associated with cancer; annexin A4 is increased in colorectal cancer [27] and renal cell carcinoma (reviewed in [28]) but reduced (as was the case in the present investigation) in hormone refractory prostate cancer (reviewed in [29]). Significantly reduced expression of annexin A4 [30] and increased expression of CK (reviewed in [31]) and LDH [32] are all associated with increased apoptosis.
Gene expression profiling in colorectal cancer using microarray technologies: Results and perspectives
2009, Cancer Treatment ReviewsCitation Excerpt :Notterman et al. detected 4000 genes with a 4–10 fold difference in expression intensity between tumour and normal tissue (p < 0.001), discovering three main clusters of genes that seem to differentiate adenomas, carcinomas and their matched normal samples.20 Subsequent studies reported other sets of genes ranging from 50 to 2632 with a different cut-off of expression intensity value that were differentially expressed between cancer and normal tissue and therefore potentially involved in the development of colorectal carcinogenesis.21–34 Whereas Frederiksen et al. were not able to separate stage I and IV CRC into distinct clusters and Kwong et al. failed to discriminate stages II, III and IV CRC at the molecular level, other authors reported stage-specific gene expression patterns.26,31,35,36