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Mining of Targeted Therapeutic Drugs for Hepatocellular Carcinoma based on Programmed Cell Death-related Features and
Juan Wang1, Xiaoli Zhao1, Chunguang Chen2
1Department of Infectious Diseases and Hepatology, Henan Provincial Infectious Disease Hospital, Zhengzhou, 450000, China.
Introduction:
The programmed cell death (PCD) is crucial in inhibiting cancer cell proliferation and enhancing anti-tumor immune responses. Mining targeted therapeutics for liver hepatocellular carcinoma (LIHC) based on PCD genes and revealing their molecular mechanisms are essential for the development of effective clinical treatments for LIHC.
Methods:
Key genes associated with PCD characteristics of LIHC were identified in cancer genome mapping by the weighted gene co-expression network analysis (WGCNA). In this study, the performance and clinical value of key genes were evaluated by the receiver operating characteristic curve (ROC). The relative expressions of genes related to PCD in LIHC cells were measured employing QRT-PCR. The practical regulation of PCD-correlated key genes on the migration and invasion levels of LIHC cells was assessed by transwell and wound healing assays. Functional and pathway characterization of gene sets was performed by Gene Set Enrichment Analysis (GSEA). CIBERSORT was used to assess immune cell infiltration in the samples. DSigDB and AutoDock tools were used for molecular docking of key genes and downstream targeted drugs. Impact omics characterization of the samples was determined by the nomogram.
Results:
Three genes, CAMK4, CD200R1, and KCNA3, were screened as key PCD-related genes in LIHC. Cellular experiments verified that CD200R1 knockdown repressed the migration and invasion in LIHC cells. GSEA showed that these three genes were enriched for cytokine release, apoptosis, and other pathways. In immune profiling, we revealed that the three genes were related to the infiltration of immune cells such as CD4+ memory T cells and CD8+ T cells. Molecular docking predicted potential drugs for the three biomarkers, among which CAMK4 was tightly bound to GSK1838705A and had the highest AUC value in the ROC curve. In addition, we constructed a nomogram to accurately assess the imaging features of LIHC.
Discussion:
This study provided a new strategy for precision treatment of LIHC by screening key genes associated with PCD in LIHC (CAMK4, CD200R1, and KCNA3), revealing their roles in the regulation of the tumor immune microenvironment and predicting potential target drugs, as well as constructing a diagnostic model based on imaging histology; however, the study did not delve deeper into the long-range drug-target interaction mechanism and lacked molecular dynamics simulation validation, which limited the comprehensiveness of the results.
Conclusion:
This study identified key genes associated with PCD in LIHC, revealed its immunoregulatory mechanism, and predicted potential target drugs, providing new ideas for precision treatment and diagnosis of LIHC.
Insights
This study identifies three key programmed cell death (PCD) genes (CAMK4, CD200R1, KCNA3) in liver hepatocellular carcinoma (LIHC), revealing their immune roles and potential drug targets for precision cancer therapy.
Area of Science:
- Oncology
- Immunology
- Genetics
Background:
- Programmed cell death (PCD) is critical for controlling cancer cell growth and boosting anti-tumor immunity.
- Targeted therapies for liver hepatocellular carcinoma (LIHC) based on PCD genes are essential for effective clinical treatment.
Purpose of the Study:
- To identify key PCD-related genes in LIHC.
- To elucidate their molecular mechanisms and roles in the tumor immune microenvironment.
- To predict potential targeted drugs for LIHC precision treatment.
Main Methods:
- Weighted gene co-expression network analysis (WGCNA) to identify key PCD genes.
- Receiver operating characteristic (ROC) curves for performance evaluation.
- Quantitative reverse transcription PCR (QRT-PCR), Transwell, and scratch healing assays for gene expression and cell function analysis.
- Gene Set Enrichment Analysis (GSEA), CIBERSORT for pathway and immune cell infiltration analysis.
- Molecular docking (DSigDB, AutoDock) for drug-target interactions.
Main Results:
- Three key PCD genes (CAMK4, CD200R1, KCNA3) were identified in LIHC.
- CD200R1 was found to promote hepatocellular carcinoma cell migration and invasion.
- Genes were enriched in apoptosis and cytokine release pathways and correlated with CD4+ and CD8+ T cell infiltration.
- CAMK4 showed strong binding with GSK1838705A, with high ROC AUC; potential drugs were predicted.
Conclusions:
- Identified CAMK4, CD200R1, and KCNA3 as key PCD genes in LIHC, offering a novel strategy for precision treatment.
- Revealed the immunoregulatory roles of these genes and predicted potential therapeutic targets.
- Highlighted the need for further research into drug-target interaction mechanisms and molecular dynamics validation.
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