| Title |
Meta-analysis of gene expression profiles identifies differential biomarkers for hepatocellular carcinoma and cholangiocarcinoma
|
|---|---|
| Published in |
Tumor Biology, July 2016
|
| DOI | 10.1007/s13277-016-5186-8 |
| Pubmed ID | |
| Authors |
Somsak Likhitrattanapisal, Jaitip Tipanee, Tavan Janvilisri |
| Abstract |
Hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA) are the members of hepatobiliary diseases. Both types of cancer often exert high levels of similarity in terms of phenotypic characteristics, thus leading to difficulties in HCC and CCA differential diagnoses. In this study, a transcriptome meta-analysis was performed on HCC and CCA microarray data to identify differential transcriptome networks and potential biomarkers for HCC and CCA. Raw data from nine gene expression profiling datasets, consisting of 1,185 samples in total, were methodologically compiled and analyzed. To evaluate differentially expressed (DE) genes in HCC and CCA, the levels of gene expression were compared between cancer and its normal counterparts (i.e., HCC versus normal liver and CCA versus normal bile duct) using t test (P < 0.05) and k-fold validation. A total of 226 DE genes were specific to HCC, 249 DE genes specific to CCA, and 41 DE genes in both HCC and CCA. Gene ontology and pathway enrichment analyses revealed different patterns between functional transcriptome networks of HCC and CCA. Cell cycle and glycolysis/gluconeogenesis pathways were exclusively dysregulated in HCC whereas complement and coagulation cascades as well as glycine, serine, and threonine metabolism were prodominantly differentially expressed in CCA. Our meta-analysis revealed distinct dysregulation in transcriptome networks between HCC and CCA. Certain genes in these networks were discussed in the context of HCC and CCA transition, unique characteristics of HCC and CCA, and their potentials as HCC and CCA differential biomarkers. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 4% |
| Unknown | 22 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Postgraduate | 3 | 13% |
| Lecturer | 3 | 13% |
| Student > Master | 3 | 13% |
| Student > Bachelor | 2 | 9% |
| Professor | 2 | 9% |
| Other | 5 | 22% |
| Unknown | 5 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 22% |
| Medicine and Dentistry | 5 | 22% |
| Nursing and Health Professions | 2 | 9% |
| Agricultural and Biological Sciences | 2 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 4% |
| Other | 3 | 13% |
| Unknown | 5 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 October 2016.
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#20,336,685
of 22,881,964 outputs
Outputs from Tumor Biology
#1,835
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Outputs of similar age
#318,268
of 364,027 outputs
Outputs of similar age from Tumor Biology
#59
of 92 outputs
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