Alternative Biomarkers to Predict Tumor Biology in Hepatocellular Carcinoma

Abreu, Phillipe; Ferreira, Raphaella; Mineli, Victor; Ribeiro, Mauricio Alves; Ferreira, Fábio Gonçalves; Vianna, Rodrigo; Tomasich, Flávio Daniel Saavedra; Szutan, Luiz Arnaldo

doi:10.21873/anticanres.14682

Cited by 8 publications

(5 citation statements)

References 71 publications

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“…Despite their conceptual similarity, imaging omics and deep learning involve completely different technical processes [ 15 ]. Imaging omics analysis is based on classical machine learning models in which experts predefine the following: features to be extracted, methods for feature selection, and methods for building classification models.…”

Section: Related Workmentioning

confidence: 99%

Preliminary Evaluation of Artificial Intelligence-Based Anti-Hepatocellular Carcinoma Molecular Target Study in Hepatocellular Carcinoma Diagnosis Research

Wang

Wei

Deng³

et al. 2022

BioMed Research International

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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.

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Section: Related Workmentioning

confidence: 99%

Preliminary Evaluation of Artificial Intelligence-Based Anti-Hepatocellular Carcinoma Molecular Target Study in Hepatocellular Carcinoma Diagnosis Research

Wang

Wei

Deng³

et al. 2022

BioMed Research International

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“…There is abundant literature on serological biomarkers for the early detection of HCC [ 38 , 39 , 40 , 41 ], but relatively few of these biomarkers are used for nano-mediated detection. This may lead to the development of systems that will significantly improve the diagnosis of HCC [ 7 ].…”

Section: Nanoparticles Used For Diagnosticsmentioning

confidence: 99%

Nanotechnology in the Diagnostic and Therapy of Hepatocellular Carcinoma

et al. 2022

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Hepatocellular carcinoma is the most common liver malignancy and is among the top five most common cancers. Despite the progress of surgery and chemotherapy, the results are often disappointing, in part due to chemoresistance. This type of tumor has special characteristics that allow the improvement of diagnostic and treatment techniques used in clinical practice, by combining nanotechnology. This article presents a brief review of the literature focused on nano-conditioned diagnostic methods, targeted therapy, and therapeutic implications for the pathology of hepatocellular carcinoma. Within each subdomain, several modern technologies with significant impact were highlighted: serological, imaging, or histopathological diagnosis; intraoperative detection; carrier-type nano-conditioned therapy, thermal ablation, and gene therapy. The prospects offered by nanomedicine will strengthen the hope of more efficient diagnoses and therapies in the future.

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“…Hepatocellular carcinoma (HCC) is frequently diagnosed and the fourth‐leading cause of cancer‐related mortality worldwide. More than 800,000 new HCC cases are diagnosed each year (Abreu et al, 2020; Grandhi et al, 2016; Kim & Viatour, 2020). Hepatitis B and C virus infections, metabolic liver disease (nonalcoholic fatty liver diseases), chronic ethanol consumption, and aflatoxin B1 and aristolochic acid‐contaminated food are considered important risk factors for HCC (Ezhilarasan, 2020; Kubota et al, 2020; Wallace et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Coleus vettiveroides ethanolic root extract induces cytotoxicity by intrinsic apoptosis in HepG2 cells

Mohamed Azar,

Ezhilarasan,

Shree Harini

2023

J of Applied Toxicology

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Hepatocellular carcinoma (HCC) contributes to more than 80% of all primary cancers globally and ranks fourth in cancer‐related deaths, due to the lack of an effective, definite therapeutic drug. Coleus vettiveroides (CV) has been used in Indian traditional medicine to treat diabetes, liver ailments, skin diseases, leukoderma, and leprosy. This study investigates the anticancer effect of CV ethanolic root extract in HepG2 cells. HepG2 cells were treated with CV extract, and its cytotoxicity was analyzed by MTT assay. AO/EB staining, propidium iodide staining, DCFH‐DA assay, phalloidine staining, flow cytometry, and qPCR studies were performed for ROS expression, apoptosis and cell cycle analysis. The phytochemical analysis confirmed the presence of quercetin and galangin in CV root extract. The results showed that CV inhibited the proliferation of HepG2 cells, with altered cellular and nuclear morphology. CV was also found to increase intracellular ROS levels and oxidative stress markers in HepG2 cells. CV significantly altered the actin microfilament distribution in HepG2 cells and caused cell cycle arrest at the sub G0‐G1 phase. CV also induced mitochondria‐mediated apoptosis, as evidenced by increased expression of p53, Bax, cytochrome C, Apaf‐1, PARP, caspase‐3 and caspase‐9, and downregulated Bcl‐2 expression. Therefore, CV exerts its anticancer effect by inducing mitochondrial dysfunction, oxidative stress, cytoskeletal disorganization, cell cycle arrest, and mitochondria‐mediated apoptosis, and it could be a potent therapeutic option for HCC.

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Alternative Biomarkers to Predict Tumor Biology in Hepatocellular Carcinoma

Cited by 8 publications

References 71 publications

Preliminary Evaluation of Artificial Intelligence-Based Anti-Hepatocellular Carcinoma Molecular Target Study in Hepatocellular Carcinoma Diagnosis Research

Preliminary Evaluation of Artificial Intelligence-Based Anti-Hepatocellular Carcinoma Molecular Target Study in Hepatocellular Carcinoma Diagnosis Research

Nanotechnology in the Diagnostic and Therapy of Hepatocellular Carcinoma

Coleus vettiveroides ethanolic root extract induces cytotoxicity by intrinsic apoptosis in HepG2 cells

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