Colon Cancer

Targeting m6A-SCG2-TAMs axis overcomes 5-FU resistance in colorectal cancer via a multi-omics model.

Chemoresistance to 5-fluorouracil (5-FU) remains a critical barrier in colorectal cancer (CRC) management. This study integrates multi-omics data from 26,192 human samples to elucidate the RNA methylation-mediated crosstalk between tumor-associated macrophages (TAMs) and tumor cells. Machine learning models were able to effectively stratify patients by risk and identified a core signature of six g...

Multi-omics and metabolic flux modeling reveal that macrophage CYP27A1-derived 26-hydroxycholesterol drives immunosuppression and cancer malignancy.

Emerging evidence indicates that aberrant cholesterol metabolism in macrophages plays a role in tumorigenesis, however, how specific metabolites released by macrophages influence immunosurveillance and along with their potential as therapeutic targets and prognostic biomarkers, remain unclear. We integrated 465 single-cell multi-omics and 1,318 bulk RNA-seq samples of colorectal cancer (CRC) using...

Improving pancreatic adenocarcinoma prognosis models through ligand receptor interactions and histopathological integration.

BACKGROUND: Pancreatic adenocarcinoma (PAAD) has an extremely poor prognosis, and existing prognostic markers fail to fully capture the complex hetero...

A predictive model for pathological complete response in neoadjuvant-treated breast cancer: integrating pretreatment clinicopathologic and contrast-enhanced ultrasound characteristics via interpretable machine learning.

BACKGROUND: The ability to predict pathological complete response (pCR) prior to neoadjuvant therapy (NAT) would inform and facilitate tailored therap...

Technical and clinical feasibility of single-use gastroscopy with real-time AI-based quality monitoring and single-use colonoscopy: a prospective two-center study.

BACKGROUND: Single-use gastrointestinal endoscopes eliminate the need for post-procedure reprocessing and have become an area of interest in endoscopi...

Comment on "MRI and PET-Based Machine Learning Radiomics for Metastasis Prediction in Pancreatic Ductal Adenocarcinoma: A Systematic Review".

Single-cell and machine learning-based neural regulation signature for prognosis prediction and immunotherapy response in lung adenocarcinoma.

OBJECTIVE: Lung adenocarcinoma (LUAD) molecular heterogeneity limits traditional prognostic models. Given the emerging role of neural regulation (NR) ...

Deep Learning for Differentiating Pulmonary Metastasis from Primary Lung Cancer Constructed on Frozen Sections for Intraoperative Diagnosis.

The surgical procedures for primary lung cancer and metastatic lung tumors differ. An intraoperative diagnosis is important for surgical procedure dec...

Detection of cancer recurrence from Thai-English electronic medical records using sentence embeddings.

OBJECTIVE: This study developed and validated monolingual and bilingual sentence-bidirectional encoder representations from transformers (SBERT) model...

Dihydroberberine regulates the ferroptosis-autophagy positive feedback loop in colorectal cancer by targeting PANX2.

BACKGROUND: Colorectal cancer (CRC) is one of the most common malignancies worldwide and remains a major clinical challenge, underscoring the urgent n...

From heterogeneity to mechanism: a systems-level analysis pinpoints the S100A8/A9 axis in colorectal cancer.

BACKGROUND: The functional roles of the S100 protein family in colorectal cancer (CRC) are enigmatic, marked by widespread dysregulation but limited p...

ADC Target Profiling in NSCLC: Generalizable AI Separates TROP-2 and cMET Phenotypes.

PURPOSE: Antibody-drug conjugates (ADC) targeting trophoblast cell surface antigen 2 (TROP-2) and cMET are entering clinical trials in non-small cell ...

AI-Powered Deep Visual Proteomics Reveals Critical Molecular Transitions in Pancreatic Cancer Precursors.

UNLABELLED: Pancreatic ductal adenocarcinoma (PDAC) evolves through precursors, yet the protein programs governing early progression remain poorly def...

Explanation-Guided Reconstruction of Missing Clinical Features for Survival Prediction in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal cancers, with survival rates influenced by a variety of factors, including earl...

Integrative Genomic and Clinical Profiling of Colorectal Cancer Liver Metastases to Guide Personalized Surgery and Liver Transplantation.

BACKGROUND/AIM: Colorectal cancer liver metastases (CRLM) remain a leading cause of cancer-related mortality. Although hepatic resection is the only e...

Effectiveness of CADe in Colonoscopy for Improved Adenoma and Polyp Detection Under Diverse Clinical Conditions.

BACKGROUND/AIM: Colonoscopy is the gold standard for colorectal cancer prevention, but its effectiveness is limited by missed lesions and operator-dep...

AI-powered real-time detection and classification of peritoneal nodules in colorectal cancer using multi-center laparoscopic data: A feasibility study.

OBJECTIVE: To explore the feasibility of developing an intraoperative real-time detection model for peritoneal nodules in laparoscopic colorectal canc...

In vitro development of the Autonomous Colonoscope Robot System (ACRS) for fully automated colonoscope insertion.

BACKGROUND: In the field of colonoscopy, robotic systems have been developed to support or replace human operators due to a shortage of trained endosc...

Retinal Vascular Features and Risk of Colorectal Cancer Incidence and Mortality: A Population-Based Cohort Study.

INTRODUCTION: Colorectal cancer (CRC) screening remains limited by invasiveness and suboptimal sensitivity of current methods. Retinal microvasculatur...

Emerging Role of AI in Gastroenterology and Hepatology: Revolutionizing Medical Device-Assisted Diagnosis.

Recent advancements in AI have emerged in the diagnosis of different diseases by enhancing the analysis of various medical imaging. Similarly, the eng...