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Biochem Biophys Res Commun ; 585: 103-110, 2021 12 31.
Artigo em Inglês | MEDLINE | ID: mdl-34800881

RESUMO

OBJECTIVE: This study aimed to screen pyroptosis-related genes influencing the therapeutic effect of dehydroabietic acid in liver cancer and to construct an effective survival prognostic nomogram model. METHODS: Differentially expressed genes (DEGs) between liver cancer tissues and normal tissues were analyzed with The Cancer Genome Atlas database, weighted gene coexpression network analysis and a genetic expression compilation database. The targets of dehydroabietic acid were screened with databases such as TCMSP and pharmacy. Spearman correlation analysis was analyzed. The prognosis model was built through one-factor Cox analysis and LASSO regression. The final core targets were screened by prognosis-related genes combined with a protein-protein interaction (PPI) network. On this basis, the survival nomogram was constructed. The effects of different concentrations of dehydroabietic acid on the growth of HepG2 liver cancer cells were detected by CCK8. Moreover, the expression of related genes was further verified through real-time fluorescence quantitative PCR and Western blot. RESULTS: Venn diagram analysis of DEGs of liver cancer in three databases was performed, through which 890 genes related to the genesis and development of liver cancer were acquired. According to Venn diagram analysis of targets of dehydroabietic acid and related genes of liver cancer, 44 intersecting targets for liver cancer treatment with dehydroabietic acid were acquired. Then, 7 prognosis-related genes were identified through one-factor Cox analysis and LASSO regression of 25 related genes. Next, 10 targets were screened through the PPI network, and the intersection was processed, thus obtaining 3 ultimate core targets of KIF11, CCNA2 and CDC25A. The IC50 of dehydroabietic acid is 23.22 ± 0.98 µg/mL. According to further verification of related genes, the mRNA and protein levels of KIF11, CCNA2 and CDC25A decrease significantly after treatment with dehydroabietic acid. The nomogram shows that T stage is an independent risk factor, and the postoperative survival C-index of the model group was 0.709. CONCLUSIONS: Three pyroptosis-related genes that influence the therapeutic effect of dehydroabietic acid in liver cancer were screened through bioinformatics methods. The survival prognostic nomogram model, which is built based on independent risk factors that influence the postoperative survival of patients in the T stage, has good accuracy and can provide references for clinical and fundamental studies in the future.


Assuntos
Abietanos/uso terapêutico , Carcinoma Hepatocelular/tratamento farmacológico , Detecção Precoce de Câncer , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Neoplasias Hepáticas/tratamento farmacológico , Piroptose/efeitos dos fármacos , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/metabolismo , Carcinoma Hepatocelular/diagnóstico , Carcinoma Hepatocelular/genética , Ciclina A2/genética , Ciclina A2/metabolismo , Feminino , Perfilação da Expressão Gênica/métodos , Células Hep G2 , Humanos , Estimativa de Kaplan-Meier , Cinesinas/genética , Cinesinas/metabolismo , Neoplasias Hepáticas/diagnóstico , Neoplasias Hepáticas/genética , Masculino , Nomogramas , Piroptose/genética , Fosfatases cdc25/genética , Fosfatases cdc25/metabolismo
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