AIMC Topic: Carcinogenesis

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Unraveling diethyl phthalate-induced prostate carcinogenesis: core targets revealed by integrated network toxicology, machine learning, and structural validation.

Human genomics
PURPOSE: Diethyl phthalate (DEP), a widely distributed environmental contaminant, is epidemiologically linked to prostate cancer (PCa). However, its molecular mechanisms beyond endocrine disruption remain poorly defined. We aimed to investigate the c...

Learning the cellular origins across cancers using single-cell chromatin landscapes.

Nature communications
Deciphering the pre-malignant cell of origin (COO) of different cancers is critical for understanding tumor development and improving diagnostic and therapeutic strategies in oncology. Prior work demonstrates that somatic mutations preferentially acc...

Innovative organ-on-a-chip platforms for exploring tumorigenesis and therapy in head and neck cancer.

Journal of translational medicine
BACKGROUND: Head and neck cancer (HNC) presents significant research challenges due to the complexity of its tumor microenvironment (TME) and the heterogeneity across different cancer subtypes. Recent advancements in three-dimensional (3D) culture mo...

Neurodegeneration Promotes Tumorigenesis in Colorectal Cancer: Insights From Single-Cell and Spatial Multiomics.

JCO precision oncology
PURPOSE: Colorectal cancer (CRC) ranks third in global incidence and second in mortality, with rates increasing among younger populations. The enteric nervous system (ENS) is crucial for gastrointestinal function, and its dysfunction is associated wi...

Unraveling senescence in cancer: mechanistic complexities and therapeutic opportunities.

Molecular biology reports
Senescence is a pivotal cellular process, which also plays a major role in development, immune regulation, tissue repair, and aging, triggered by stressors such as telomere shortening, oncogene activation, and DNA damage. Characterized by distinct mo...

Mathematical and numerical tumour development modelling for personalised treatment planning.

Biomechanics and modeling in mechanobiology
This paper presents a mathematical and numerical framework for modelling and parametrising tumour evolution dynamics to enhance computer-aided diagnosis and personalised treatment. The model comprises six differential equations describing cancer cell...

Deep learning prioritizes cancer mutations that alter protein nucleocytoplasmic shuttling to drive tumorigenesis.

Nature communications
Genetic variants can affect protein function by driving aberrant subcellular localization. However, comprehensive analysis of how mutations promote tumor progression by influencing nuclear localization is currently lacking. Here, we systematically ch...

Radiogenomics and machine learning predict oncogenic signaling pathways in glioblastoma.

Journal of translational medicine
BACKGROUND: Glioblastoma (GBM) is a highly aggressive brain tumor associated with a poor patient prognosis. The survival rate remains low despite standard therapies, highlighting the urgent need for novel treatment strategies. Advanced imaging techni...

Cross-disease transcriptomic analysis reveals DOK3 and PAPOLA as therapeutic targets for neuroinflammatory and tumorigenic processes.

Frontiers in immunology
OBJECTIVE: Subarachnoid hemorrhage (SAH) and tumorigenesis share numerous biological complexities; nevertheless, the specific gene expression profiles and underlying mechanisms remain poorly understood. This study aims to identify differentially expr...