| Literature DB >> 29721060 |
Jun Cheng1, Xuekun Song2, Lu Ao1, Rou Chen1, Meirong Chi1, You Guo1, Jiahui Zhang1, Hongdong Li1, Wenyuan Zhao2, Zheng Guo1,2,3, Xianlong Wang1.
Abstract
Background & Aims: Primary tumors of colorectal carcinoma (CRC) with liver metastasis might gain some liver-specific characteristics to adapt the liver micro-environment. This study aims to reveal potential liver-like transcriptional characteristics associated with the liver metastasis in primary colorectal carcinoma.Entities:
Keywords: colorectal cancer; liver metastasis; micro-environment; microdissection; transcriptional characteristics
Year: 2018 PMID: 29721060 PMCID: PMC5929095 DOI: 10.7150/jca.23017
Source DB: PubMed Journal: J Cancer ISSN: 1837-9664 Impact factor: 4.207
Datasets analyzed in the study
| Dataset | Microarray Platform | Tissue Type* | Sample Size |
|---|---|---|---|
| GSE40367 | GPL570 | pCRC# | 7 |
| mCRC# | 7 | ||
| pHCC# | 10 | ||
| normal liver | 5 | ||
| GSE28702 | GPL570 | mCRC | 23 |
| pCRC | 56 | ||
| GSE41258 | GPL96 | normal liver | 13 |
| normal colon | 54 | ||
| GSE21510 | GPL570 | mCRC# | 66 |
| GSE17536 | pCRC | 103 | |
| GSE8671 | normal colon | 32 | |
| GSE9254 | 19 | ||
| GSE21510 | 25 | ||
| GSE37364 | 38 | ||
| GSE45267 | GPL570 | normal liver | 39 |
| pHCC | 48 |
*pCRC, primary colorectal tumor samples; mCRC, colorectal-liver metastasis; and pHCC,
primary hepatocellular carcinoma samples. #represented that the samples were microdissected.
Figure 1The ranks of expression levels of 12 liver-specific genes in four types of tissues: Colorectal tissues included 114 normal colorectal tissues (red) and 103 Primary CRCs without metastasis (blue); 48 HCCs (green); 39 normal liver tissues (black).
Figure 2The ranks of expression levels of ANGPTL3 and CFHR5 in 7 paired microdissected primary colorectal tumors and liver metastases.
KEGG pathways enriched with the genes significantly co-expressed with ANGPTL3 and CFHR5, respectively.
| KEGG pathway | |
|---|---|
| Complement and coagulation cascades | 2.20E-16 |
| Retinol metabolism | 1.11E-16 |
| Drug metabolism-cytochrome P450 | 1.61E-11 |
| Bile secretion | 9.07E-10 |
| Metabolism of xenobiotics by cytochrome P450 | 1.03E-08 |
| Fatty acid degradation | 5.67E-07 |
| Tyrosine metabolism | 3.72E-05 |
| Drug metabolism - other enzymes | 1.06E-04 |
| Glycine, serine and threonine metabolism | 2.46E-04 |
| Steroid hormone biosynthesis | 5.03E-04 |
| Glycolysis / Gluconeogenesis | 9.90E-04 |
| PPAR signaling pathway | 1.19E-03 |
| Starch and sucrose metabolism | 2.46E-03 |
| Fat digestion and absorption | 2.46E-03 |
| Linoleic acid metabolism | 2.54E-03 |
| Complement and coagulation cascades | 2.20E-16 |
| Retinol metabolism | 3.42E-12 |
| Drug metabolism-cytochrome P450 | 6.21E-10 |
| Metabolism of xenobiotics by cytochrome P450 | 2.30E-08 |
| Bile secretion | 3.09E-08 |
| Steroid hormone biosynthesis | 5.42E-06 |
| Fatty acid degradation | 4.56E-05 |
| Drug metabolism - other enzymes | 4.62E-04 |
| Tyrosine metabolism | 1.38E-03 |
Figure 3Protein-protein interaction (PPI) links between the DEGs (ellipses) and the target genes of anti-liver cancer drugs (triangles): pink for down-regulated genes and cyan for up-regulated genes.