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Query: UMLS:C0019204 (
hepatocellular carcinoma
)
71,386
document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)
This study systematically evaluates the TCGA whole-transcriptome sequencing data of
hepatocellular carcinoma
(
HCC
) by comparing the global gene expression profiles between tumors and their corresponding nontumorous liver tissue. Based on the differential gene expression analysis, we identified a number of novel dysregulated genes, in addition to those previously reported. Top-listing upregulated (CENPF and FOXM1) and downregulated (CLEC4G, CRHBP, and
CLEC1B
) genes were successfully validated using qPCR on our cohort of 65 pairs of human HCCs. Further examination for the mechanistic overview by subjecting significantly upregulated and downregulated genes to gene set enrichment analysis showed that different cellular pathways were involved. This study provides useful information on the transcriptomic landscape and molecular mechanism of hepatocarcinogenesis for development of new biomarkers and further in-depth characterization.
...
PMID:TCGA whole-transcriptome sequencing data reveals significantly dysregulated genes and signaling pathways in hepatocellular carcinoma. 2627 37
Spontaneous tumor hemorrhage (TH) is frequently observed in solid tumors including human
hepatocellular carcinoma
(
HCC
). TH implies fast-growing and worse tumor immunological microenvironment; however, the underlying mechanism remains largely unknown.
CLEC1B
is a signature gene highly associated with tumor progression. PD-L1 expression is a key biomarker predictive of immune checkpoint therapies, which showed astonishing effect on various types of tumor. We assume that, in
HCC
, TH may closely associate with the expression of these two molecules. In this study, 136 patients with
HCC
were enrolled. qRT-PCR showed that
CLEC1B
expression is significantly lower in
HCC
tumor tissue. Immunohistochemistry of
HCC
tissue microarrays demonstrated that PD-L1
high
and
CLEC1B
low
expressions were significantly correlated with TH and clinicopathological features indicating worse
HCC
progression. According to univariate/multivariate analysis, a combination of PD-L1
high
and
CLEC1B
low
expression was an independent prognostic factor indicating the poor outcome. The prognostic value of PD-L1
high
and
CLEC1B
low
was validated by Cox proportional-hazard analyses. Collectively, tumor with TH is closely associated with
CLEC1B
low
& PD-L1
high
expression, which may imply high response of PD-L1/PD-1 immune checkpoint therapies.
CLEC1B
may be a potential therapeutic target for PD-L1/PD-1 immunotherapy. PD-L1
high
and
CLEC1B
low
can be a valuable prognosis factor implying worse clinical outcomes.
...
PMID:CLEC1B Expression and PD-L1 Expression Predict Clinical Outcome in Hepatocellular Carcinoma with Tumor Hemorrhage. 2952 32
The high mortality rate of
hepatocellular carcinoma
(
HCC
) is primarily due to its late diagnosis. In the past, numerous attempts have been made to design genetic biomarkers for the identification of
HCC
; unfortunately, most of the studies are based on small datasets obtained from a specific platform or lack reasonable validation performance on the external datasets. In order to identify a universal expression-based diagnostic biomarker panel for
HCC
that can be applicable across multiple platforms, we have employed large-scale transcriptomic profiling datasets containing a total of 2,316
HCC
and 1,665 non-tumorous tissue samples. These samples were obtained from 30 studies generated by mainly four types of profiling techniques (Affymetrix, Illumina, Agilent, and High-throughput sequencing), which are implemented in a wide range of platforms. Firstly, we scrutinized overlapping 26 genes that are differentially expressed in numerous datasets. Subsequently, we identified a panel of three genes (
FCN3,
CLEC1B
, and
PRC1)
as
HCC
biomarker using different feature selection techniques. Three-genes-based
HCC
biomarker identified
HCC
samples in training/validation datasets with an accuracy between 93 and 98%, Area Under Receiver Operating Characteristic curve (AUROC) in a range of 0.97 to 1.0. A reasonable performance, i.e., AUROC 0.91-0.96 achieved on validation dataset containing peripheral blood mononuclear cells, concurred their non-invasive utility. Furthermore, the prognostic potential of these genes was evaluated on TCGA-LIHC and GSE14520 cohorts using univariate survival analysis. This analysis revealed that these genes are prognostic indicators for various types of the survivals of
HCC
patients (e.g., Overall Survival, Progression-Free Survival, Disease-Free Survival). These genes significantly stratified high-risk and low-risk
HCC
patients (p-value <0.05). In conclusion, we identified a universal platform-independent three-genes-based biomarker that can predict
HCC
patients with high precision and also possess significant prognostic potential. Eventually, we developed a web server HCCpred based on the above study to facilitate scientific community (http://webs.iiitd.edu.in/raghava/hccpred/).
...
PMID:Identification of Platform-Independent Diagnostic Biomarker Panel for Hepatocellular Carcinoma Using Large-Scale Transcriptomics Data. 3199 66
