Dataset Information

Identification of postoperative prognostic microRNA predictors in hepatocellular carcinoma.

ABSTRACT: Comparison of microRNA (miRNA) expression profiles in the noncancerous liver tissues adjacent to hepatocelluar carcinomas (HCCs) was a strategy to identify postoperative prognostic predictors in this study. Expression profiles of 270 miRNAs were determined in the paraneoplastic liver tissues of 12 HCC patients with known postoperative prognosis. A panel of candidate miRNA predictors was identified. The prognostic predictive value of these candidate miRNAs was then verified in 216 postoperative HCC patients. Univariate analysis identified 8 and 3 miRNA predictors for recurrence-free (RFS) and overall (OS) survivals, respectively. Multivariate analysis revealed high expression levels of miR-155 (HR, 2.002 [1.324-3.027]; P?=?.001), miR-15a (HR, 0.478 [0.248-0.920]; P?=?.027), miR-432 (HR, 1.816 [1.203-2.740]; P?=?.015), miR-486-3p (HR, 0.543 [0.330-0.893]; P?=?.016), miR-15b (HR, 1.074 [1.002-1.152]; P?=?.043) and miR-30b (HR, 1.102 [1.025-1.185]; P?=?.009) were significantly associated with RFS. When clinicopathological predictors were included, multivariate analysis revealed that tumor number and miR-432, miR-486-3p, and miR-30b expression levels remained significant as independent predictors for RFS. Additionally, expression knockdown of miR-155 in J7 and Mahlavu hepatoma cells resulted in decreased cell growth and enhanced cell death in xenograft tumors, suggesting an oncogenic effect of miR-155. In conclusion, significant prognostic miRNA predictors were identified through examination of miRNA expression levels in paraneoplastic liver tissues. Functional analysis of a miRNA predictor, miR-155, suggested that the prognostic miRNA predictors identified under this strategy could serve as potential molecular targets for anticancer therapy.

SUBMITTER: Huang YH

PROVIDER: S-EPMC3358336 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Identification of postoperative prognostic microRNA predictors in hepatocellular carcinoma.

Huang Ya-Hui YH Lin Kwang-Huei KH Chen Hua-Chien HC Chang Ming-Ling ML Hsu Chao-Wei CW Lai Ming-Wei MW Chen Tse-Ching TC Lee Wei-Chen WC Tseng Yi-Hsin YH Yeh Chau-Ting CT

PloS one 20120522 5

Comparison of microRNA (miRNA) expression profiles in the noncancerous liver tissues adjacent to hepatocelluar carcinomas (HCCs) was a strategy to identify postoperative prognostic predictors in this study. Expression profiles of 270 miRNAs were determined in the paraneoplastic liver tissues of 12 HCC patients with known postoperative prognosis. A panel of candidate miRNA predictors was identified. The prognostic predictive value of these candidate miRNAs was then verified in 216 postoperative H ...[more]

PMID: 22629365

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Project description:BackgroundThe immunological inflammatory biomarkers for advanced hepatocellular carcinoma are unclear. We aimed to investigate the association of immunity and inflammatory status with treatment outcomes in patients with advanced hepatocellular carcinoma who received molecular-targeted agents as primary treatment.Patients and methodsWe enrolled 728 consecutive patients with advanced hepatocellular carcinoma who received sorafenib (n = 554) or lenvatinib (n = 174) as primary treatment in Japan between May 2009 and June 2020. Changes in the neutrophil-to-lymphocyte ratio before and 1 month after treatment and their impact on survival were evaluated. The cut-off values of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio for predicting overall and progression-free survival were calculated using receiver operating characteristic curves.ResultsThe neutrophil-to-lymphocyte ratio, but not the platelet-to-lymphocyte ratio, was an independent prognostic factor. Patients with decreased neutrophil-to-lymphocyte ratio survived significantly longer than patients with increased neutrophil-to-lymphocyte ratio (median overall survival: 14.7 versus 10.4 months, P = 0.0110). Among patients with a low pre-treatment neutrophil-to-lymphocyte ratio, the overall survival did not differ significantly between those with decreased and those with increased neutrophil-to-lymphocyte ratio after 1 month (median: 19.0 versus 14.8 months, P = 0.1498). However, among patients with high pre-treatment neutrophil-to-lymphocyte ratio, those whose neutrophil-to-lymphocyte ratio decreased after 1 month showed significantly longer survival than those whose neutrophil-to-lymphocyte ratio increased (median: 12.7 versus 5.5 months, P < 0.0001). The therapeutic effect was not correlated with pre-treatment neutrophil-to-lymphocyte ratio or platelet-to-lymphocyte ratio.ConclusionsThe neutrophil-to-lymphocyte ratio is a prognostic factor, along with liver function and tumor markers, in patients with advanced hepatocellular carcinoma who received molecular-targeted agents as primary treatment. Thus, the neutrophil-to-lymphocyte ratio could be a prognostic biomarker for advanced hepatocellular carcinoma primarily treated with immunotherapy.

Project description:Liver hepatocellular carcinoma (LIHC) is the most prevalent primary cancer of the liver, and immune-related genes (IRGs) regulate its development. So far, there is still no precise biomarker that predicts response to immunotherapy in LIHC. Therefore, this research seeks to identify immunogenic prognostic biomarkers and explore potential predictors for the efficacy of anti-PD-1/PD-L1 therapies in LIHC. The clinical data and gene expression profiles of patients diagnosed with LIHC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Moreover, IRGs were obtained from the ImmPort database. We discovered 35 IRGs that were differentially expressed between LIHC tissues and corresponding normal tissues. Through univariate Cox regression analysis, eight prognostic differentially expressed IRGs (PDEIRGs) were identified. Further, three optimal PDEIRGs (BIRC5, LPA, and ROBO1) were identified and used to construct a prognostic risk signature of LIHC patients via multivariate Cox regression analysis. The signature was validated by ROC curves. Subsequently, based on gene set enrichment analysis (GSEA) analysis, two out of the three optimal PDEIRGs (BIRC5 and LPA) were significantly enriched in the mismatch repair (MMR) pathway. Moreover, the two PDEIRGs (BIRC5 and LPA) were significantly correlated with the expression of genes related to mismatch repair (MLH1, MSH2, MSH6, and PMS2). Furthermore, correlations between the two PDEIRGs (BIRC5 and LPA) and immune checkpoints of cancer treatment (such as CTLA4, PD-1, and PD-L1) were demonstrated. Hyperprogressive disease (HPD) is a novel pattern of tumor progression which has a close relationship with immune checkpoint inhibitors (ICIs) utilization. MDM2 family amplification might promote the HPD phenomenon. Finally, we found a positive regulatory relationship between HPD related gene (MDM2) and BIRC5. Notably, MDM2 can either interact directly with BIRC5 or indirectly via downstream transcription factors of BIRC5. Overall, our study uncovered a novel 3-immune-related prognostic genes in LIHC.

Project description:Background: An accumulating body of evidence suggests that long non-coding RNAs (lncRNAs) can serve as potential cancer prognostic factors. However, the utility of lncRNA combinations in estimating overall survival (OS) for hepatocellular carcinoma (HCC) remains to be elucidated. This study aimed to construct a powerful lncRNA signature related to the OS for HCC to enhance prognostic accuracy. Methods: The expression patterns of lncRNAs and related clinical data of 371 HCC patients were obtained based on The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs (DElncRNAs) were acquired by comparing tumors with adjacent normal samples. lncRNAs displaying significant association with OS were screened through univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. All cases were classified into the validation or training group at the ratio of 3:7 to validate the constructed lncRNA signature. Data from the Gene Expression Omnibus (GEO) were used for external validation. We conducted real-time polymerase chain reaction (PCR) and assays for Transwell invasion, migration, CCK-8, and colony formation to determine the biological roles of lncRNA. Gene set enrichment analysis (GSEA) of the lncRNA model risk score was also conducted. Results: We identified 1292 DElncRNAs, among which 172 were significant in univariate Cox regression analysis. In the training group (n = 263), LASSO regression analysis confirmed 11 DElncRNAs including AC010547.1, AC010280.2, AC015712.7, GACAT3 (gastric cancer associated transcript 3), AC079466.1, AC089983.1, AC051618.1, AL121721.1, LINC01747, LINC01517, and AC008750.3. The prognostic risk score was calculated, and the constructed risk model showed significant correlation with HCC OS (log-rank P-value of 8.489e-9, hazard ratio of 3.648, 95% confidence interval: 2.238-5.945). The area under the curve (AUC) for this lncRNA model was up to 0.846. This risk model was confirmed in the validation group (n = 108), the entire cohort, and the external GEO dataset (n = 203). GACAT3 was highly expressed in HCC tissues and cell lines. Based on online databases, GACAT3 expression independently affects both OS and disease-free survival in HCC patients. Silencing GACAT3 in vitro significantly suppressed HCC cell proliferation, invasion, and migration. Moreover, pathways related to the lncRNA model risk score were confirmed by GSEA. Conclusion: The lncRNA signature established in this study can be used to predict HCC prognosis, which could provide novel clinical evidence to guide targeted HCC treatment.

Project description:Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The efficacy of immunotherapy usually depends on the interaction of immunomodulation in the tumor microenvironment (TME). This study aimed to explore the potential stromal-immune score-based prognostic genes related to immunotherapy in HCC through bioinformatics analysis. Methods: ESTIMATE algorithm was applied to calculate the immune/stromal/Estimate scores and tumor purity of HCC using the Cancer Genome Atlas (TCGA) transcriptome data. Functional enrichment analysis of differentially expressed genes (DEGs) was analyzed by the Database for Annotation, Visualization, and Integrated Discovery database (DAVID). Univariate and multivariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed for prognostic gene screening. The expression and prognostic value of these genes were further verified by KM-plotter database and the Human Protein Atlas (HPA) database. The correlation of the selected genes and the immune cell infiltration were analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm and Tumor Immune Estimation Resource (TIMER). Results: Data analysis revealed that higher immune/stromal/Estimate scores were significantly associated with better survival benefits in HCC within 7 years, while the tumor purity showed a reverse trend. DEGs based on both immune and stromal scores primarily affected the cytokine-cytokine receptor interaction signaling pathway. Among the DEGs, three genes (CASKIN1, EMR3, and GBP5) were found most significantly associated with survival. Moreover, the expression levels of CASKIN1, EMR3, and GBP5 genes were significantly correlated with immune/stromal/Estimate scores or tumor purity and multiple immune cell infiltration. Among them, GBP5 genes were highly related to immune infiltration. Conclusion: This study identified three key genes which were related to the TME and had prognostic significance in HCC, which may be promising markers for predicting immunotherapy outcomes.

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Identification of postoperative prognostic microRNA predictors in hepatocellular carcinoma.

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Identification of postoperative prognostic microRNA predictors in hepatocellular carcinoma.

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