Dataset Information

Construction and validation of a three-microRNA signature as prognostic biomarker in patients with hepatocellular carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC), a common type of primary liver cancer, is one of the most aggressive malignant tumors worldwide. Although overall survival (OS) rates for HCC has significantly improved in recent years, however, the exact predictive value of microRNA (miRNA) for the prognosis of HCC has not yet been recognized. Here, we aimed to identify potential prognostic miRNAs involved in HCC by bioinformatics analysis and validated expression levels through quantitative polymerase chain reaction (qPCR) and GEO database. The RNA expression profiles and corresponding clinical information of HCC were available from The Cancer Genome Atlas (TCGA) datasets. Differentially expression and standardization analysis of miRNAs, Kaplan-Meier curve and time dependent ROC curve were performed by using R tools. Differentially expressed miRNAs (DEmiRNAs) and clinical parameters involved in the OS of HCC were confirmed by Cox regression models. And functional enrichment analysis was used to establish functions of the targeted genes of DEmiRNAs. A total of 300 DEmiRNAs were significantly related with HCC, of which 40 were down-regulated and 260 were up-regulated. A total of 344 patients with DEmiRNAs, status, overall survival (OS) time were randomized into training group (172) and test group (172). Multivariate Cox regression analyses revealed that 3 miRNA (hsa-miR-139-3p, hsa-miR-760, hsa-miR-7-5p) had independent prognostic significance for the OS of HCC in both training and test group. Moreover, according to Kaplan Meier analysis, the OS of HCC patients with high-risk score was shorter in validation and entire series. The time dependent ROC curve demonstrated high accuracy of the signature for OS. Besides, target genes of three miRNAs were analyzed by functional enrichment analysis and 20 genes associated with OS were verified by using Kaplan-Meier method. Compared with normal and benign group, the relative expression level of hsa-miR-139-3p was significantly decreased, while hsa-miR-7-5p and hsa-miR-760 were distinctly increased in the plasma of HCC patients. The same results were observed in the independent cohort. Collectively, our research suggested that three-miRNA signature could serve as an independent prognostic indicator for HCC patients.

SUBMITTER: Zhang X

PROVIDER: S-EPMC7807177 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Construction and validation of a three-microRNA signature as prognostic biomarker in patients with hepatocellular carcinoma.

Zhang Xi X Ma Li L Zhai Li L Chen Dong D Li Yong Y Shang Zhongjun Z Zhang Zongmei Z Gao Yanzhang Y Yang Wei W Li Yixun Y Pan Yuqing Y

International journal of medical sciences 20210101 4

Hepatocellular carcinoma (HCC), a common type of primary liver cancer, is one of the most aggressive malignant tumors worldwide. Although overall survival (OS) rates for HCC has significantly improved in recent years, however, the exact predictive value of microRNA (miRNA) for the prognosis of HCC has not yet been recognized. Here, we aimed to identify potential prognostic miRNAs involved in HCC by bioinformatics analysis and validated expression levels through quantitative polymerase chain reac ...[more]

PMID: 33456356

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Project description:Background: Ferroptosis, as a unique programmed cell death modality, has been found to be closely related to the occurrence and development of hepatocellular carcinoma (HCC). Hypoxia signaling pathway has been found to be extensively involved in the transformation and growth of HCC and to inhibit anti-tumor therapy through various approaches. However, there is no high-throughput study to explore the potential link between ferroptosis and hypoxia, as well as their combined effect on the prognosis of HCC. Methods: We included 370 patients in The Cancer Genome Atlas (TCGA) database and 231 patients in the International Cancer Genome Consortium (ICGC) database. Univariate COX regression and Least Absolute Shrinkage and Selection Operator approach were used to construct ferroptosis-related genes (FRGs) and hypoxia-related genes (HRGs) prognostic signature (FHPS). Kaplan-Meier method and Receiver Operating Characteristic curves were analyzed to evaluate the predictive capability of FHPS. CIBERSOR and single-sample Gene Set Enrichment Analysis were used to explore the connection between FHPS and tumor immune microenvironment. Immunohistochemical staining was used to compare the protein expression of prognostic FRGs and HRGs between normal liver tissue and HCC tissue. In addition, the nomogram was established to facilitate the clinical application of FHPS. Results: Ten FRGs and HRGs were used to establish the FHPS. We found consistent results in the TCGA training cohort, as well as in the independent ICGC validation cohort, that patients in the high-FHPS subgroup had advanced tumor staging, shorter survival time, and higher mortality. Moreover, patients in the high-FHPS subgroup showed ferroptosis suppressive, high hypoxia, and immunosuppression status. Finally, the nomogram showed a strong prognostic capability to predict overall survival (OS) for HCC patients. Conclusion: We developed a novel prognostic signature combining ferroptosis and hypoxia to predict OS, ferroptosis, hypoxia, and immune status, which provides a new idea for individualized treatment of HCC patients.

Project description:BackgroundExisting research has identified correlations between numerous microRNAs (miRNAs) and the prognosis of hepatocellular carcinoma (HCC). However, the role of a combination of miRNAs in predicting HCC survival requires further elucidation.MethodsmiRNA expression profiles and clinical data from HCC patients were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed (DE) miRNAs in tumor versus normal samples were identified. All HCC patients were randomly assigned to a training cohort or a validation cohort at a ratio of 1 to 1. A least absolute shrinkage and selection operator (LASSO) Cox regression model was subsequently employed to establish the miRNA signature. The constructed miRNA signature was then developed and validated.ResultsIn total, 127 DE miRNAs were detected between HCC and paracancerous tissue using HCC RNA sequencing (RNA-Seq) data extracted from TCGA database. LASSO Cox regression generated a five-miRNA signature consisting of has-mir-105-2, has-mir-9-3, has-mir-137, has-mir-548f-1, and has-mir-561 in the training cohort. This risk model was significantly related to survival (P=5.682e-6). Log-rank tests and multivariate Cox regression analyses revealed the five-miRNA signature as an independent prognostic indicator [HR =3.285, 95% confidence interval (CI): 1.737-6.213], with the area under curve (AUC) of the miRNA signature being 0.728. The effects of the miRNA signature were further confirmed in the validation cohort and in the OncomiR Cancer Database and Gene Expression Omnibus (GEO) dataset. Functional enrichment analysis revealed the potential effects of the five-miRNA signature in tumor-related biological pathways and processes. Cell Counting Kit-8, Transwell, and wound healing assays, were used to evaluate the role of has-mir-137 in HCC cell proliferation and migration in vitro.ConclusionsWe established a novel five-miRNA signature which reliably predicted prognosis in HCC patients and which could be used to assist in both strategic counseling and personalized management in HCC.

Project description:BackgroundNecroptosis is a necrotic programmed cell death with potent immunogenicity. Due to the dual effects of necroptosis on tumor growth, metastasis and immunosuppression, we evaluated the prognostic value of necroptosis-related genes (NRGs) in hepatocellular carcinoma (HCC).MethodsWe first analyzed RNA sequencing and clinical HCC patient data obtained to develop an NRG prognostic signature based on the TCGA dataset. Differentially expressed NRGs were further evaluated by GO and KEGG pathway analyses. Next, we conducted univariate and multivariate Cox regression analyses to build a prognostic model. We also used the dataset obtained from the International Cancer Genome Consortium (ICGC) database to verify the signature. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to investigate the immunotherapy response. Furthermore, we investigated the relationship between the prediction signature and chemotherapy treatment response in HCC.ResultsWe first identified 36 differentially expressed genes out of 159 NRGs in hepatocellular carcinoma. Enrichment analysis showed that they were mainly enriched in the necroptosis pathway. Four NRGs were screened by Cox regression analysis to establish a prognostic model. The survival analysis revealed that the overall survival of patients with high-risk scores was significantly shorter than that of patients with low-risk scores. The nomogram demonstrated satisfactory discrimination and calibration. The calibration curves validated a fine concordance between the nomogram prediction and actual observation. The efficacy of the necroptosis-related signature was also validated by an independent dataset and immunohistochemistry experiments. TIDE analysis revealed that patients in the high-risk group were possibly more susceptible to immunotherapy. Furthermore, high-risk patients were found to be more sensitive to conventional chemotherapeutic medicines such as bleomycin, bortezomib, and imatinib.ConclusionWe identified 4 necroptosis-related genes and established a prognostic risk model that could potentially predict prognosis and response to chemotherapy and immunotherapy in HCC patients in the future.

Project description:BackgroundPrevious studies have shown that the hypoxia microenvironment significantly impacted tumor progression. However, the clinical prognostic value of hypoxia-related risk signatures and their effects on the tumor microenvironment (TME) in hepatocellular carcinoma (HCC) remains hazy. This study aimed to conduct novel hypoxia-related prognostic signatures and improve HCC prognosis and treatment.MethodsDifferentially expressed hypoxia-related genes (HGs) were identified with the gene set enrichment analysis (GSEA). Univariate Cox regression was utilized to generate the tumor hypoxia-related prognostic signature, which consists of 3 HGs, based on the least absolute shrinkage and selection operator (LASSO) algorithm. Then the risk score for each patient was performed. The prognostic signature's independent prognostic usefulness was confirmed, and systematic analyses were done on the relationships between the prognostic signature and immune cell infiltration, somatic cell mutation, medication sensitivity, and putative immunological checkpoints.ResultsA prognostic risk model of four HGs (FDPS, SRM, and NDRG1) was constructed and validated in the training, testing, and validation datasets. To determine the model's performance in patients with HCC, Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curves analysis was implemented. According to immune infiltration analysis, the high-risk group had a significant infiltration of CD4+ T cells, M0 macrophages, and dendritic cells (DCs) than those of the low-risk subtype. In addition, the presence of TP53 mutations in the high-risk group was higher, in which LY317615, PF-562271, Pyrimethamine, and Sunitinib were more sensitive. The CD86, LAIR1, and LGALS9 expression were upregulated in the high-risk subtype.ConclusionsThe hypoxia-related risk signature is a reliable predictive model for better clinical management of HCC patients and offers clinicians a holistic viewpoint when determining the diagnosis and course of HCC treatment.

Dataset Information

Construction and validation of a three-microRNA signature as prognostic biomarker in patients with hepatocellular carcinoma.

Publications

Construction and validation of a three-microRNA signature as prognostic biomarker in patients with hepatocellular carcinoma.

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