ReviewNature reviews. Gastroenterology & hepatology2020
Harnessing big 'omics' data and AI for drug discovery in hepatocellular carcinoma.
Review in Nature reviews. Gastroenterology & hepatology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT05543304 (Predicting Response to Systemic Therapies for Hepatocellular Carcinoma), which is not on this map. Cited by 85 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Predicting Response to Systemic Therapies for Hepatocellular Carcinoma(HCC) Based on Clinical Variables and Radiomics Data With Machine Learning Methods
Who cites it
85 citing papers in PubMed, 1 synthesis or guideline pooled it, 161 citations in OpenAlex.
- Prognostic role of artificial intelligence among patients with hepatocellular cancer: A systematic review.World journal of gastroenterology · 2020Pooled it
- Efficacy and safety of lenvatinib plus gefitinib in lenvatinib-resistant hepatocellular carcinomas: a prospective, single-arm exploratory trial.Signal transduction and targeted therapy · 2024Trial
- Artificial intelligence and oral microbiome: Reshaping the diagnostic and therapeutic paradigm of OSCC.Clinical and translational medicine · 2026Review
- Article
- Analysis of genetic mutation characteristics in 40 Chinese patients with hepatocellular carcinoma.Genes & genomics · 2026Article
- Polysaccharide-functionalized gold, silver, and iron oxide nanoparticles for siRNA delivery: The role of artificial intelligence in design and optimization.Materials today. Bio · 2026Review
- Sorafenib nanomedicine in HCC: nano-bio interactions and combination therapies.Journal of nanobiotechnology · 2026Review
- Artificial Intelligence Applications in the Diagnosis, Treatment, and Prognosis of Hepatocellular Carcinoma.Gut and liver · 2026Review
- CENPA as a Genome Stability-Associated Biomarker in Hepatocellular Carcinoma: Multiomics Analysis and Experimental Validation.Human mutation · 2026Article
- Unveiling EFNB2 as a Key Player in Sorafenib Resistance: Insights from Bioinformatics Analysis and Functional Validation in Hepatocellular Carcinoma.Biochemical genetics · 2025Article
- Genetic Insight Into Dissecting the FODMAP Diet Frame and Liver Cancer: The Mediation Role of Efferocytosis and Trogocytosis.Food science & nutrition · 2025Article
- Regulatory Functions of microRNAs in Cancer Stem Cells: Mechanism, Facts, and Perspectives.Cells · 2025Review
- Metabolic reprogramming in hepatocellular carcinoma: an integrated omics study of lipid pathways and their diagnostic potential.Journal of translational medicine · 2025Article
- Bridging Immune Evasion and Vascular Dynamics for Novel Therapeutic Frontiers in Hepatocellular Carcinoma.Cancers · 2025Review
- Cancer chemoprevention: signaling pathways and strategic approaches.Signal transduction and targeted therapy · 2025Review
- Integrative transcriptomic analysis identifies emetine as a promising candidate for overcoming acquired resistance to ALK inhibitors in lung cancer.Molecular oncology · 2025Article
- Harnessing big data for precision medicine: radiomics based application of nanomaterials in MRI enhancement and multimodal therapy of hepatocellular carcinoma.Frontiers in immunology · 2025Review
- The Synergistic Mechanisms and Prospects of Transarterial Chemoembolization Combined with Immunotherapy for Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2025Review
- The Impact of Artificial Intelligence on Cancer Diagnosis and Treatment: A Review.Cancer informatics · 2025Review
- Big Data and Artificial Intelligence in Drug Discovery for Gastric Cancer: Current Applications and Future Perspectives.Current medicinal chemistry · 2025Review
25 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
6 authors at 5 institutions in 3 countries.
Funding
Abstract
Hepatocellular carcinoma (HCC) is the most common form of primary adult liver cancer. After nearly a decade with sorafenib as the only approved treatment, multiple new agents have demonstrated efficacy in clinical trials, including the targeted therapies regorafenib, lenvatinib and cabozantinib, the anti-angiogenic antibody ramucirumab, and the immune checkpoint inhibitors nivolumab and pembrolizumab. Although these agents offer new promise to patients with HCC, the optimal choice and sequence of therapies remains unknown and without established biomarkers, and many patients do not respond to treatment. The advances and the decreasing costs of molecular measurement technologies enable profiling of HCC molecular features (such as genome, transcriptome, proteome and metabolome) at different levels, including bulk tissues, animal models and single cells. The release of such data sets to the public enhances the ability to search for information from these legacy studies and provides the opportunity to leverage them to understand HCC mechanisms, rationally develop new therapeutics and identify candidate biomarkers of treatment response. Here, we provide a comprehensive review of public data sets related to HCC and discuss how emerging artificial intelligence methods can be applied to identify new targets and drugs as well as to guide therapeutic choices for improved HCC treatment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.