Colon Cancer

Pathomic model to predict the expression of UQCRH and overall survival of lung adenocarcinoma patients.

Multimodal brain-gut-sleep phenotypes predict delirium, long-term cognitive decline, and survival after colorectal cancer surgery.

BACKGROUND: Neuroimmune, circadian, autonomic, and gut-brain processes jointly shape vulnerability to postoperative delirium and long-term cognitive decline, yet their integrated contribution remains unclear. METHODS: In this prospective cohort (n = 300), preoperative assessments included circadian actigraphy, gut microbial diversity and short-chain fatty acids, inflammatory cytokines (IL-6, CRP),...

Prediction model for ctDNA detectability in liquid comprehensive genomic profiling of advanced pancreatic cancer based on Japanese real-world data.

BACKGROUND: Circulating tumor DNA (ctDNA) is sometimes undetectable in liquid comprehensive genomic profiling (CGP) of advanced-stage pancreatic cance...

[The Digital Lab: Practical digital workflow and integration of AI for routine in pathology, through the example of prostate cancer].

Digital pathology is a major technological revolution for pathology. It modernizes routine practices and paves the way for the integration of artifici...

Intelligent Stain-Free Histology on Structural Colorimetric Nanocavities.

Optical microscopic imaging and analysis are indispensable in modern pathology for providing conclusive evidence in disease diagnosis. However, the cu...

Applicability of mitotic figure counting by deep learning: a development and pan-cancer validation study.

Mitotic figure counting is an established measure of cell proliferation that is included in grading systems. We developed a deep learning method for m...

Outcomes of Artificial Intelligence Enhanced Colonoscopy in a Tertiary Clinical Setting.

BACKGROUND AND AIMS: Colonoscopies reduce colorectal cancer incidence and mortality, but challenges remain in detecting all precancerous lesions. Oper...

Ancestry-Associated Performance Variability of Open-Source AI Models for EGFR Prediction in Lung Cancer.

IMPORTANCE: Artificial intelligence (AI) models are emerging as rapid, low-cost tools for predicting targetable genomic alterations directly from rout...

Large-Scale Histological Image Dataset with Metadata for Colorectal Cancer Microenvironment.

The pronounced heterogeneity of the tumor microenvironment (TME) in colorectal cancer (CRC) presents major obstacles in accurately predicting patient ...

Multimodal activity-affinity assay of ADAM-10 extracellular vesicles in untreated plasma reveals metastatic stage of colorectal cancer.

Metalloproteinases (MPs) such as a-disintegrin and metalloproteinase-10 (ADAM-10) are key drivers of extracellular matrix remodeling during tumor prog...

Machine learning-based prediction of long-term prognosis in cervical adenocarcinoma: a retrospective cohort study.

TCF21-WNT5A axis drives metastasis of colorectal cancer via stromal-tumor cell communication.

INTRODUCTION: The third most prevalent form of cancer, colorectal cancer (CRC), is associated with a high mortality rate due to colorectal liver metas...

Development and Validation of a Computational Histology Artificial Intelligence-Powered Predictive Biomarker for Selection of Chemotherapy in Advanced Pancreatic Cancer.

PURPOSE: Predictive biomarkers to guide selection of first-line chemotherapy for advanced pancreatic ductal adenocarcinoma (PDAC) are an unmet clinica...

Exploring the toxicological mechanisms of Benzo[a]anthracene (BaA) exposure in lung adenocarcinoma (LUAD) via network toxicology, machine learning, and multi-dimensional bioinformatics analysis.

BACKGROUND: Lung adenocarcinoma (LUAD) is a major lung cancer subtype influenced by environmental factors. Benzo[a]anthracene (BaA), a common Group 2B...

Artificial intelligence performance in generating colorectal surgery board questions.

BACKGROUND: Large language models (LLM) can pass medical licensing and specialty board exams, but their ability to generate high-quality board-style e...

Identifying Post-Surgical Recurrence Subtype of T1 Stage Colorectal Cancer by Machine Learning.

INTRODUCTION: Traditional risk stratification heavily relies on expert judgment and manually established thresholds. This study aims to automatically ...

Attention-guided enhanced deconvolution enables reference-free cell type estimation in spatial transcriptomics.

Spatial transcriptomics technologies profile gene expression across tissue sections while retaining spatial information, yet most platforms capture si...

Mitochondrial DNA methylation predicts immunotherapy response and prognosis in lung adenocarcinoma: evidence from scRNA-Seq and machine learning.

Multi-structure CT radiomics-based consensus model for the diagnosis of pancreatic ductal adenocarcinoma and vascular involvement.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy, with accurate preoperative assessment of vascular involvement criti...

Integrative analysis of immune and microbial subtypes predicts immunotherapy response in stomach adenocarcinoma.

The tumor immune microenvironment and intratumoral microbiota play critical roles in cancer progression and immunotherapy response, yet their integrat...