Prognostic values of a novel multi-mRNA signature for predicting relapse of cholangiocarcinoma

Guo, Han; Cai, Jie; Wang, Xuan; Wang, Bingrui; Wang, Fang; Li, Xiang; Qu, Xiaoye; Kong, Xiangdong; Gao, Yueqiu; Wu, Hailong; Sun, Xuehua; Xia, Qiang; Kong, Xiaoni

doi:10.7150/ijbs.38846

Cited by 17 publications

(18 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As expected, Oil Red O staining showed that HepG2 cells treated with OA exhibited elevated intracellular lipid storage compared to the control cells ( Figure 5A). Consistent with previous report (25), OA reduced the expression of phosphatase and tensin homolog (PTEN) ( Figure 5B), a vital tumor suppressor gene in hepatocellular carcinoma. Importantly, OA markedly stimulated HMMR expression at the transcriptional and translational levels.…”

Section: Oleate Acid Elevates the Expression Of Hmmr Via Cebpαsupporting

confidence: 92%

See 1 more Smart Citation

Oleate acid-stimulated HMMR expression by CEBPα is associated with nonalcoholic steatohepatitis and hepatocellular carcinoma

Zhang¹,

Liu²,

Xie³

et al. 2020

Int. J. Biol. Sci.

View full text Add to dashboard Cite

Non-alcoholic steatohepatitis (NASH) is a type of nonalcoholic fatty liver disease and has become a major risk factor for hepatocellular carcinoma (HCC). However, the underlying pathophysiological mechanisms are still elusive. Here, we identify hyaluronan-mediated motility receptor (HMMR) as a critical gene associated with NASH/HCC by combination of bioinformatic analysis and functional experiments. Analysis of differentially expressed genes (DEGs) between normal controls and NASH/HCC identified 5 hub genes (HMMR, UBE2T, TYMS, PTTG1 and GINS2). Based on the common DEGs, analyses of univariate and multivariate Cox regression and the area under the curve (AUC) value of the receiver operating characteristic (ROC) indicate that HMMR is the most significant gene associated with NASH/HCC among five hub genes. Oleate acid (OA), one of fatty acids that induce cellular adipogenesis, stimulates HMMR expression via CCAAT/enhancer-binding protein α (CEBPα). CEBPα increases the expression of HMMR through binding to its promoter. HMMR promotes HCC cell proliferation in vitro via activation of G1/S and G2/M checkpoint transitions, concomitant with a marked increase of the positive cell cycle regulators, including cyclin D1, cyclin E, and cyclin B1. Knockdown of HMMR suppresses HCC tumor growth in nude mice. Our study identifies an important role of HMMR in NASH/HCC, and suggests that HMMR may be a useful target for therapy and prognostic prediction of NASH/HCC patients.

show abstract

Section: Oleate Acid Elevates the Expression Of Hmmr Via Cebpαsupporting

confidence: 92%

“…Functional and pathway enrichment analyses were performed for DEGs using the clusterProfiler R package [25], including Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses [26]. GO terms and KEGG pathways with an adj.…”

Section: Functional and Pathway Enrichment Analysismentioning

confidence: 99%

Oleate acid-stimulated HMMR expression by CEBPα is associated with nonalcoholic steatohepatitis and hepatocellular carcinoma

Zhang¹,

Liu²,

Xie³

et al. 2020

Int. J. Biol. Sci.

View full text Add to dashboard Cite

show abstract

“…Considering that previous research has mainly focused on one or two types of immune cells and key genes, it may create a bias against the LUAD microenvironment. Finding multiple genes from the tumor microenvironment to build a gene signature can obtain a better accuracy of the prognostic potential ( Liu et al, 2019a ,b; Zhou et al, 2019 ; Bi et al, 2020 ; Guo et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Identification of a Novel Tumor Microenvironment–Associated Eight-Gene Signature for Prognosis Prediction in Lung Adenocarcinoma

Luo

Cao

et al. 2020

Front. Mol. Biosci.

View full text Add to dashboard Cite

Background: Lung cancer has become the most common cancer type and caused the most cancer deaths. Lung adenocarcinoma (LUAD) is one of the major types of lung cancer. Accumulating evidence suggests the tumor microenvironment is correlated with the tumor progress and the patient's outcome. This study aimed to establish a gene signature based on tumor microenvironment that can predict patients' outcomes for LUAD. Methods: Dataset TCGA-LUAD, downloaded from the TCGA portal, were taken as training cohort, and dataset GSE72094, obtained from the GEO database, was set as validation cohort. In the training cohort, ESTIMATE algorithm was applied to find intersection differentially expressed genes (DEGs) among tumor microenvironment. Kaplan-Meier analysis and univariate Cox regression model were performed on intersection DEGs to preliminarily screen prognostic genes. Besides, the LASSO Cox regression model was implemented to build a multi-gene signature, which was then validated in the validation cohorts through Kaplan-Meier, Cox, and receiver operating characteristic curve (ROC) analyses. In addition, the correlation between tumor mutational burden (TMB) and risk score was evaluated by Spearman test. GSEA and immune infiltrating analyses were conducted for understanding function annotation and the role of the signature in the tumor microenvironment. Results: An eight-gene signature was built, and it was examined by Kaplan-Meier analysis, revealing that a significant overall survival difference was seen. The eight-gene signature was further proven to be independent of other clinico-pathologic parameters via the Cox regression analyses. Moreover, the ROC analysis demonstrated that this signature owned a better predictive power of LUAD prognosis. The eight-gene signature was correlated with TMB. Furthermore, GSEA and immune infiltrating analyses showed

show abstract

“…Hence, IRGs expression may be an important predictor of prognosis and progression in CCA. Up to date, considerable efforts have been made to identify prognostic model based on differentially expressed genes, but the report on prognostic IRGs signature of CCA is lacking [33,34]. In our study, we identi ed a new prognostic IRGs signature by screening the differentially expressed genes, and established a dependable model to predict survival of CCA patients based on this immune signature.…”

Section: Discussionmentioning

confidence: 97%

Identification and Validation of a Predictive Immune-Related Genes Signature for the Prognosis of Cholangiocarcinoma

Zhang

Chen

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Immune-related genes (IRGs) play a crucial role in the initiation and progression of cholangiocarcinoma (CCA). However, immune signatures have rarely been used to predict prognosis of CCA. The aim of this study was to construct a novel model for CCA to predict survival based on IRGs expression data. Methods: The gene expression profiles and clinical data of CCA patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were integrated to establish and validate prognostic IRG signatures. Differentially expressed immune-related genes were screened. Univariate and multivariate Cox analysis were performed to identify prognostic IRGs, and the risk model that predicts outcomes was constructed. Furthermore, receiver operating characteristic (ROC) and Kaplan-Meier curve were plotted to examine predictive accuracy of the model, and a nomogram was constructed based on IRGs signature, combining with other clinical characteristics. Finally, CIBERSORT was used to analyze the association of immune cells infiltration with risk score. Results: We identified that 223 IRGs were signiﬁcantly dysregulated in patients with CCA, among which five IRGs (AVPR1B, CST4, TDGF1, RAET1E and IL9R) were identified as robust indicators for overall survival (OS), and a prognostic model was built based on the IRGs signature. Meanwhile, patients with high risk had worse OS in training and validation cohort, and the area under the ROC was 0.898 and 0.846, respectively. Nomogram demonstrated that immune risk score contributed much more points than other clinicopathological variables, with a C-index of 0.819 (95% CI, 0.727-0.911). Finally, we found that IRGs signature was positively correlated with the proportion of CD8+ T cells, neurophils and T gamma delta, while negatively with that of CD4+ memory resting T cells. Conclusions: We established and validated an effective five IRGs-based prediction model for CCA, which could accurately classify patients into groups with low and high risk of poor prognosis.

show abstract

Prognostic values of a novel multi-mRNA signature for predicting relapse of cholangiocarcinoma

Cited by 17 publications

References 44 publications

Oleate acid-stimulated HMMR expression by CEBPα is associated with nonalcoholic steatohepatitis and hepatocellular carcinoma

Oleate acid-stimulated HMMR expression by CEBPα is associated with nonalcoholic steatohepatitis and hepatocellular carcinoma

Identification of a Novel Tumor Microenvironment–Associated Eight-Gene Signature for Prognosis Prediction in Lung Adenocarcinoma

Identification and Validation of a Predictive Immune-Related Genes Signature for the Prognosis of Cholangiocarcinoma

Contact Info

Product

Resources

About