Integrated multi-omics, machine learning, network toxicology, and molecular docking reveal potential mechanisms underlying methyl 4-hydroxybenzoate-associated breast cancer.

Multi-omics, machine learning, and molecular simulation identify CD44 as a candidate target in endocrine-disrupting chemical-associated thyroid cancer progression.

A network toxicology and machine learning approach to uncover the molecular machinery of bisphenol A-induced colorectal cancer

The machine learning-derived 12-gene signature, interpreted as CRC-associated genes overlapping with predicted BPA targets and supported by in silico molecular docking, offers valuable insights into the molecular basis of BPA-associated colorectal carcinogenesis and presents candidate targets for subsequent experimenta...

Integrated multi-omics and experimental analyses reveal VIPR1 as a potential mediator linking environmental bisphenol A exposure to MASH-HCC progression.

Metabolic dysfunction-associated steatohepatitis-related liver cancer (MASH-HCC) is an increasingly important subtype of hepatocellular carcinoma, and environmental contaminants have been proposed as potential contributors to its progression. Bisphenol A (BPA), a ubiquitous endocrine-disrupting chemical, has been impli...

Integrated Transcriptomic, Network Pharmacology, and Machine-Learning Framework Identifies Candidate Phytochemical-Associated Targets in Lung Adenocarcinoma

Network toxicology-aided identification of potential toxicological mechanisms of rhodamine B in ovarian cancer: Insights from transcriptomics, molecular docking, molecular dynamics simulations, and machine learning modeling

Ovarian cancer is the most lethal gynecological malignancy, accounting for disproportionate cancer-related mortality due to late-stage diagnosis and limited therapeutic options. Despite documented cytotoxicity, genotoxicity, hepatotoxicity, and reproductive toxicity of Rhodamine B, its toxic molecular interaction lands...

An integrated network toxicology and multi-omics framework prioritizes BRCA1 as a testable candidate in benzo[a]pyrene-associated oral cancer

Environmental exposure to benzo[a]pyrene (BaP) is a recognized risk factor for oral cancer, but systematic strategies for prioritizing candidate molecular nodes and generating experimentally testable hypotheses remain limited. Here, we conducted a hypothesis-generating, methodologically oriented exploratory study using...