Preliminary Evaluation of Artificial Intelligence-Based Anti-Hepatocellular Carcinoma Molecular Target Study in
Yuan Wang1, Chao Wei2, Xiangui Deng3
1Infectious Disease Department, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610072, China.
Abstract:
In this paper, in-depth research analysis of anti-hepatocellular carcinoma molecular targets for hepatocellular carcinoma diagnosis was conducted using artificial intelligence. Because BRD4 plays an important role in gene transcription for cell cycle regulation and apoptosis, tumor-targeted therapy by inhibiting the expression or function of BRD4 has received increasing attention in the field of antitumor research. Study subjects in small samples were used as the validation set for validating each diagnostic model constructed based on the training set. The diagnostic effect of each model in the validation set is evaluated by calculating the sensitivity, specificity, and compliance rate, and the model with the best and most stable diagnostic value is selected by combining the results of model construction, validation, and evaluation. The total sample was divided into a training set and test set by using a stratified sampling method in the ratio of 7 : 3. Logistic regression, weighted k-nearest neighbor, decision tree, and BP artificial neural network were used in the training set to construct diagnostic models for early-stage liver cancer, respectively, and the optimal parameters of the corresponding models were obtained, and then, the constructed models were validated in the test set. To evaluate the diagnostic efficacy, stability, and generalization ability of the four classification methods more robustly, a 10-fold crossover test was performed for each classification method. BRD4 is an epigenetic regulator that is associated with the upregulation of expression of various oncogenic drivers in tumors. Targeting BRD4 with pharmacological inhibitors has emerged as a novel approach for tumor treatment. However, before we implemented this topic, there were no detailed studies on whether BRD4 could be used for the treatment of HCC, the role of BRD4 in HCC cell proliferation and apoptosis, and the ability of small molecule BRD4 inhibitors to induce apoptosis in hepatocellular carcinoma cells.
Insights
Artificial intelligence models were developed to identify early-stage hepatocellular carcinoma (HCC) using BRD4 as a molecular target. These models demonstrate potential for accurate HCC diagnosis and targeted therapy development.
Area of Science:
- Oncology
- Artificial Intelligence
- Molecular Biology
Background:
- Hepatocellular carcinoma (HCC) diagnosis and treatment remain significant challenges in oncology.
- Bromodomain-containing protein 4 (BRD4) is implicated in gene transcription, cell cycle regulation, and apoptosis, making it a potential therapeutic target.
- The role of BRD4 in HCC proliferation and apoptosis, and its potential as a therapeutic target, requires further investigation.
Purpose of the Study:
- To develop and validate artificial intelligence (AI)-based diagnostic models for early-stage hepatocellular carcinoma (HCC).
- To investigate the potential of BRD4 as a molecular target for HCC diagnosis and therapy.
- To evaluate the diagnostic efficacy, stability, and generalization ability of various AI classification methods.
Main Methods:
- AI models including logistic regression, k-nearest neighbor, decision tree, and BP neural network were constructed using a training dataset.
- Models were validated on a separate test set using stratified sampling (7:3 ratio).
- Diagnostic performance was assessed using sensitivity, specificity, compliance rate, and a 10-fold cross-validation test.
Main Results:
- AI models were successfully constructed and validated for early-stage HCC diagnosis.
- The study identified BRD4 as a promising molecular target for HCC, with potential for targeted therapy.
- The best performing diagnostic model was selected based on combined construction, validation, and evaluation results.
Conclusions:
- AI-driven diagnostic models show promise for early detection of hepatocellular carcinoma.
- Targeting BRD4 presents a novel therapeutic strategy for HCC, potentially inhibiting cancer cell proliferation and inducing apoptosis.
- Further research is warranted to fully elucidate BRD4's role in HCC and its therapeutic potential.
More Related Videos
12:24A Three-Dimensional Spheroid Model to Investigate the Tumor-Stromal Interaction in Hepatocellular Carcinoma
Published on: September 30, 2021
06:38An Oncogenic Hepatocyte-Induced Orthotopic Mouse Model of Hepatocellular Cancer Arising in the Setting of Hepatic Inflammation and Fibrosis
Published on: September 12, 2019
