LncRNA SNHG17 Contributes to Proliferation, Migration, and Poor Prognosis of Hepatocellular Carcinoma.

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However, the expression pattern and biological function of SNHG17 in hepatocellular carcinoma (HCC) remain unclear. Bioinformatics analysis and qRT-PCR were performed to detect the expression pattern of SNHG17 in HCC tissues, adjacent nontumorous tissues, and cell lines. The effect of SNHG17 on proliferation, migration, and apoptosis of HCC was investigated by knockdown and overexpressing SNHG17 in HCC cell lines. RNA sequencing was utilized to explore the underlying mechanism. Utilizing publicly available TCGA-LIHC, GSE102079 HCC datasets, and qRT-PCR, we found SNHG17 was significantly upregulated in HCC tissues and cell lines and was notably associated with larger tumor size, poorly differentiation, presence of vascular invasion, and advanced TNM stage. Furthermore, gain- and loss-of-function studies demonstrated that SNHG17 promoted cell proliferation and migration and inhibited apoptosis of HCC. By employing RNA sequencing, we found knockdown of SNHG17 caused 1037 differentially expressed genes, highly enriched in several pathways, including metabolic, PI3K-Akt, cell adhesion, regulation of cell proliferation, and apoptotic pathway; among them, 92 were overlapped with SNHG17-related genes in the TCGA-LIHC dataset. Furthermore, ERH, TBCA, TDO2, and PDK4 were successfully validated and found significantly dysregulated in HCC tissues. Moreover, HCC patients with higher SNHG17 expression had a relatively poor overall survival and disease-free survival, and ERH and PDK4 also played a marked role in the prognosis of HCC. Broadly, our findings illustrate that SNHG17 acts as a noncoding oncogene in HCC progression, suggesting its potential value as a novel target for HCC therapy.", "claims": [{"id": "claim-method", "statement": "The Kaplan–Meier plot was determined online for survival analysis to show the correlation between gene expression and overall survival (OS) or disease-free survival (DFS) of HCC patients (https://gepia.cancer-pku.cn/index.html). Univariate and multivariate Cox regression analyses were employed to explore the association between gene expression and overall survival. The log-rank test was employed to compare survival rates. The gene expression profile and clinical characteristics for HCC patients were downloaded from the TCGA database (https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga, TCGA-LIHC). 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By employing RNA sequencing, we foun"], "order_basis": "paper_text_order:515", "id": "assay:1"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["on, and apoptosis of HCC was investigated by knockdown and overexpressing SNHG17 in HCC cell lines.", "f HCC. By employing RNA sequencing, we found knockdown of SNHG17 caused 1037 differentially express", "nes altered (≥2-fold change, P < 0.05) after knockdown of SNHG17 in Hep3B cells. Figure S4. Distrib", "nes altered (≥2-fold change, P < 0.05) after knockdown of SNHG17 in Hep3B cells. Figure S5. The exp"], "order_basis": "paper_text_order:552", "id": "assay:2"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["and overexpressing SNHG17 in HCC cell lines. RNA sequencing was utilized to explore the underlying mecha", "and inhibited apoptosis of HCC. By employing RNA sequencing, we found knockdown of SNHG17 caused 1037 di", "e S4. The overlap of SNHG17-related genes in RNA-sequencing results and HCC tissues (TCGA-LIHC).Click he", "SNHG17 in Hep3B cells, with three repeats by RNA sequencing. Table S2. The list of KEGG terms for 1037 g"], "order_basis": "paper_text_order:607", "id": "assay:3"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["O2) and human HCC cell line (SMMC-7721) were cultured in RPMI 1640 medium (Gibco, USA) containing 10%", "ing HuH-7, Hep3B, HepG2, and PLC/PRF/5, were cultured in DMEM medium containing FBS, penicillin, and", "Xin Zhou Biotechnology (Shanghai, China) and cultured in cell culture dishes (Jet Bio-Filtration, Gua", "Xin Zhou Biotechnology (Shanghai, China) and cultured in cell culture dishes (Jet Bio-Filtration,"], "order_basis": "paper_text_order:2396", "id": "assay:4"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The Kaplan–Meier plot was determined online for survival analysis to show the correlation between gene expression and overall survival (OS) or disease-free survival (DFS) of HCC patients (https://gepia.cancer-pku.cn/index.html). Univariate and multivariate Cox regression analyses were employed to explore the association between gene expression and overall survival. The log-rank test was employed to compare survival rates. The gene expression profile and clinical characteristics for HCC patients were downloaded from the TCGA database (https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga, TCGA-LIHC). The GSE102079 dataset containing 152 tumorous and 91 adjacent liver tissues from HCC patients was downloaded from GEO (https://www.ncbi.nlm.nih.gov/geo)."], "order_basis": "consumes_earlier_output", "id": "assay:5"}]}