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pmid:39695705
Construction of a prognostic model based on disulfidptosis-related genes and identification of CCNA2 as a novel biomarker for hepatocellular carcinoma.
Tao Wang · Wenxuan Li · Yuelan Wu · Liping You · Chao Zheng · Jinghao Zhang · Lihong Qu · Xuehua Sun
Biology direct · 2024 doi:10.1186/s13062-024-00569-9
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Experiment
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Complete file
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In-depth analyses exploring the relationship between disulfidptosis-related genes (DRGs) and hepatocellular carcinoma (HCC) are currently limited.\nMETHODS: Transcriptomic data and clinical information were retrieved from the TCGA and GEO databases (GSE76427 and GSE54236), concentrating on the expression levels of 24 DRGs. Subsequently, multifactor and LASSO regression analyses were utilized to construct the 5-DRG prognostic signature. Immunohistochemistry (IHC) was employed to assess Cyclin A2 (CCNA2) protein expression levels. Quantitative real-time PCR (qRT-PCR) and western blot analyses were conducted to detect transcriptomic and protein expression of CCNA2-targeting short interfering RNA (siRNA). The Cell Counting Kit-8 (CCK-8) assay, EdU staining, and scratch experiments were employed to observe the proliferation and migration of hepatoma cell lines subsequent to CCNA2 inhibition.\nRESULTS: Three HCC patterns were identified, among which pattern B exhibited the the most unfavorable survival outcomes. Five DRGs (STC2, PBK, CCNA2, SERPINE1, and SLC6A1) were involved to establish the 5-DRG prognostic signature. High-risk groups (HRGs) exhibited prolonged survival durations in comparison to low-risk groups (LRGs). Both bioinformatics analyses and experimental methodologies corroborated the association of CCNA2 with poor prognosis in HCC patients. Functional studies elucidated that interference with CCNA2 significantly inhibited proliferation and migration, while simultaneously promoting apoptosis in hepatoma cells and resulting in the downregulation of epithelial-mesenchymal transition (EMT)-related protein markers.\nCONCLUSIONS: The 5-DRG prognostic signature is proficient in predicting clinical outcomes, informing therapeutic strategies, and elucidating the characteristics of the immune microenvironment in HCC patients. Furthermore, this study elucidates the potential of CCNA2 as an innovative biomarker for HCC.", "claims": [{"id": "claim-method", "statement": "Following this, 80 DEGs were selected via one-way Cox regression analysis (P < 0.001) for constructing the risk model. 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METHODS: Transcriptomic data and clinical information were retrieved", "stern blot analyses were conducted to detect transcriptomic and protein expression of CCNA2-targeting sh"], "order_basis": "paper_text_order:446", "id": "assay:1"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["to construct the 5-DRG prognostic signature. Immunohistochemistry (IHC) was employed to assess Cyclin A2 (CCNA", "prognostic signature. Immunohistochemistry (IHC) was employed to assess Cyclin A2 (CCNA2) pr"], "order_basis": "paper_text_order:729", "id": "assay:2"}, {"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["NA2) protein expression levels. Quantitative real-time PCR (qRT-PCR) and western blot analyses were con"], "order_basis": "paper_text_order:837", "id": "assay:3"}, {"role": "data_generation", "definition_id": "western_blot", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["ls. Quantitative real-time PCR (qRT-PCR) and western blot analyses were conducted to detect transcript"], "order_basis": "paper_text_order:865", "id": "assay:4"}, {"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 of CCNA2-targeting short interfering RNA (siRNA). The Cell Counting Kit-8 (CCK-8) assay, EdU", "argeting the CCNA2 gene and negative control siRNA were synthesized by Genepharma (Zhousu, Chin", "e sequences of CCNA2 siRNAs were as follows: siRNA-1: F5’- GUAGCAGAGUUUGUGUACATT, F3’-UGUACACAA", "AGAGUUUGUGUACATT, F3’-UGUACACAAACUCUGCUACTT; siRNA-2: F5’-CAGCCAGACAUCACUAACATT, F3’- UGUUAGUGA"], "order_basis": "paper_text_order:992", "id": "assay:5"}, {"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["nd migration, while simultaneously promoting apoptosis in hepatoma cells and resulting in the downr", "fering RNA (siRNA). The Cell Counting Kit-8 (CCK-8) assay, EdU staining, and scratch experiment"], "order_basis": "paper_text_order:1025", "id": "assay:6"}, {"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": ["ai, China. The MIHA, HepG2, HuH-7, and Hep3B cell lines were cultured in high fructose DMEM (Gibco), while SUN-449", "IHA, HepG2, HuH-7, and Hep3B cell lines were cultured in high fructose DMEM (Gibco), while SUN-449 wa", "igh fructose DMEM (Gibco), while SUN-449 was cultured in RPMI 1640 medium. All culture media were sup", "cyte cell line MIHA and four HCC cell lines (HepG2, SUN-449, HuH-7, Hep3B) were acquired from t"], "order_basis": "paper_text_order:2362", "id": "assay:7"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ratory Animal Co. Ltd (Shanghai, China). The mice were randomized into the control and tumor groups", "AATT. Clinical sample collection and two HCC mouse models construction HCC tumor samples with t"], "order_basis": "paper_text_order:3327", "id": "assay:8"}, {"role": "data_generation", "definition_id": "clinical_trial", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["y Animal Co. Ltd (Shanghai, China). The mice were randomized into the control and tumor groups (n = 5 per grou"], "order_basis": "paper_text_order:3719", "id": "assay:9"}, {"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": ["Following this, 80 DEGs were selected via one-way Cox regression analysis (P < 0.001) for constructing the risk model. The risk model was subsequently developed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and multivariate Cox regression analysis."], "order_basis": "consumes_earlier_output", "id": "assay:10"}]}