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pmid:37229243
Identification of afatinib-associated ADH1B and potential small-molecule drugs targeting ADH1B for hepatocellular carcinoma.
Yongxu Zhou · Liang Yu · Peng Huang · Xudong Zhao · Risheng He · Yunfu Cui · Bo Pan · Chang Liu
Frontiers in pharmacology · 2023 doi:10.3389/fphar.2023.1166454
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Experiment
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Data
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Analysis
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Complete file
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This study aimed to screen a key gene associated with afatinib and identify its potential candidate drugs. Methods: We screened afatinib-associated differential expressed genes based on transcriptomic data of LIHC patients from The Cancer Genome Atlas, Gene Expression Omnibus, and the Hepatocellular Carcinoma Database (HCCDB). By using the Genomics of Drug Sensitivity in Cancer 2 database, we determined candidate genes using analysis of the correlation between differential genes and half-maximal inhibitory concentration. Survival analysis of candidate genes was performed in the TCGA dataset and validated in HCCDB18 and GSE14520 datasets. Immune characteristic analysis identified a key gene, and we found potential candidate drugs using CellMiner. We also evaluated the correlation between the expression of ADH1B and its methylation level. Furthermore, Western blot analysis was performed to validate the expression of ADH1B in normal hepatocytes LO2 and LIHC cell line HepG2. Results: We screened eight potential candidate genes (ASPM, CDK4, PTMA, TAT, ADH1B, ANXA10, OGDHL, and PON1) associated with afatinib. Patients with higher ASPM, CDK4, PTMA, and TAT exhibited poor prognosis, while those with lower ADH1B, ANXA10, OGDHL, and PON1 had unfavorable prognosis. Next, ADH1B was identified as a key gene negatively correlated with the immune score. The expression of ADH1B was distinctly downregulated in tumor tissues of pan-cancer. The expression of ADH1B was negatively correlated with ADH1B methylation. Small-molecule drugs panobinostat, oxaliplatin, ixabepilone, and seliciclib were significantly associated with ADH1B. The protein level of ADH1B was significantly downregulated in HepG2 cells compared with LO2 cells. Conclusion: Our study provides ADH1B as a key afatinib-related gene, which is associated with the immune microenvironment and can be used to predict the prognosis of LIHC. It is also a potential target of candidate drugs, sharing a promising approach to the development of novel drugs for the treatment of LIHC.", "claims": [{"id": "claim-method", "statement": "The immune score was predicted using the ESTIMATE algorithm (Yoshihara et al., 2013) in the TCGA dataset, and Spearmen correlation analysis was conducted to evaluate the correlation between candidate genes and immune score.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37229243", "locator": "sections[6] \"Identification of the key gene based on immune abnormalities\" paragraph 2", "quote": "The immune score was predicted using the ESTIMATE algorithm (Yoshihara et al., 2013) in the TCGA dataset, and Spearmen correlation analysis was conducted to evaluate the correlation between candidate genes and immune score."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37229243", "locator": "sections[25] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "ADH1B was significantly negatively correlated with the immune score (R = −0.14, p = 0.009).", "kind": "quantitative", "target": {"value": 0.009, "unit": "p-value", "tolerance": null, "source": "Furthermore, we analyzed the relationship between candidate genes and immune score and found that ADH1B was significantly negatively correlated with the immune score (R = −0.14, p = 0.009) (Figures 4A, B)."}, "evidence": [{"asset": "source:pmid:37229243", "locator": "sections[16] \"Identification of key genes based on immune abnormalities\" paragraph 2", "quote": "Furthermore, we analyzed the relationship between candidate genes and immune score and found that ADH1B was significantly negatively correlated with the immune score (R = −0.14, p = 0.009) (Figures 4A, B)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "ADH1B was significantly negatively correlated with the immune score (R = −0.14, p = 0.009).", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:37229243"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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