Colon Cancer

Comprehensive Multi-Omics Profiling of Tertiary Lymphoid Structures Reveals Immunogenetic Landscapes and Prognostic Subtypes in Lung Adenocarcinoma.

Tertiary lymphoid structures (TLSs) are key components of the tumor immune microenvironment and show prognostic relevance in many cancers. However, their genetic association with lung adenocarcinoma (LUAD) is still lacking. This study aims to construct a TLS-related prognostic model through an integrated multi-omics strategy and to elucidate relevant immunogenetic mechanisms. TLS-related genes (TR...

Artificial intelligence: Catalyzing a new era in pancreatic cancer cure.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal human cancers, mostly due to its insidious onset that consequently leads to diagnosis at advanced stages. The complex biology of PDAC limits effective therapeutic options, yet over 90% of cases harbor KRAS mutations, making it a compelling therapeutic target. KRAS had a notorious history of being "undruggable." Emerging novel i...

Development and external validation of an interpretable multimodal deep learning model for 5-year mortality in high-risk stage ii colorectal cancer.

PURPOSE: High-risk stage II colorectal cancer (CRC) shows heterogeneous outcomes despite adjuvant chemotherapy. We developed and validated an interpre...

Synthetic inducible bacteria normalize the microenvironment of refractory tumors, potentiating checkpoint inhibitor responses.

Immunotherapy has transformed cancer treatment but remains ineffective in many solid tumors, largely due to the immunosuppressive tumor microenvironme...

The role of artificial intelligence in colonoscopy performance and quality among gastroenterology fellows.

Deep Learning-Based Prediction System for Surgical Difficulty in Rectal Cancer Patients Using MRI Pelvimetry.

PURPOSE: This study presents a system that automatically predicts the difficulty of laparoscopic total mesorectal excision (TME) using magnetic resona...

Cross-attention multimodal fusion for EGFR mutation prediction: A predictive model using CT and whole-slide images.

BACKGROUND: The prediction of Epidermal Growth Factor Receptor (EGFR) mutation status in advanced lung adenocarcinoma is crucial for targeted therapy....

CBFI: A multi-layer gene network key node identification algorithm integrating structural-biological features and dynamic regulatory weights.

OBJECTIVE: Identifying key nodes within multi-layer GRNs is crucial for uncovering potential biomarkers and therapeutic targets. Key nodes exhibit bot...

Machine learning-enhanced plasma proteomics discriminates pancreatic cancer-associated diabetes from type 2 diabetes mellitus.

Pancreatic ductal adenocarcinoma (PDAC) is frequently preceded by new-onset diabetes mellitus (NODM), yet differentiating PDAC-associated DM from type...

Peripheral blood mononuclear cell DNA methylation signatures guide surgical decision-making in indeterminate pulmonary nodules.

BACKGROUND: Distinguishing malignant from benign pulmonary nodules remained a significant clinical challenge. Given the involvement of DNA methylation...

Integration of 117 machine learning algorithms and single-cell transcriptomics identifies macrophage polarization and ER stress signatures for cancer prognosis and precision therapy.

BACKGROUND: Macrophage polarization and endoplasmic reticulum (ER) stress play critical yet incompletely understood roles in cancer progression and th...

Integration of Single-Cell RNA Sequencing and Machine Learning to Identify and Validate Prognostic Genes With Lymph Node Metastasis and Immune Cell Signatures in Lung Adenocarcinoma.

The poor prognosis of lung adenocarcinoma (LUAD) remains unimproved. This study aimed to identify lymph node metastasis (LNM)-related and cellular imm...

Radiomics for predicting microsatellite instability-high status in colorectal cancer: a systematic review and meta-analysis.

OBJECTIVE: Microsatellite instability (MSI) has emerged as a key predictive biomarker for chemotherapy and immunotherapy response, and as a prognostic...

Data-driven design of deterministic lateral displacement microfluidic devices for CTC separation.

Circulating tumor cells (CTCs) are established biomarkers for cancer diagnosis and therapeutic monitoring, yet their extreme rarity in peripheral bloo...

The Negative Impact of a Non-Therapeutic Laparotomy in Patients With Inoperable Colorectal Peritoneal Metastases.

BACKGROUND: The peritoneum is the third most prevalent location for metastases of colorectal cancer. In patients with resectable disease, cytoreductiv...

Radiomics-based outcome prediction for irinotecan-TACE in colorectal liver metastases: advanced analysis from the prospective CIREL trial.

OBJECTIVES: Transarterial chemoembolization (TACE) is a promising locoregional therapy for unresectable colorectal liver metastases, but patient selec...

Multimodal AI approach combining deep learning imaging and clinical machine learning for pancreatic cancer detection.

Pancreatic ductal adenocarcinoma (PDAC) has poor prognosis due to late diagnosis, limitations of computed tomography (CT) imaging, and low accuracy of...

Clinical validation and implementation of mSTOP, a machine learning-based, longitudinal prediction model for the early identification of non-small cell lung cancer patients who not benefit from immune checkpoint inhibitor treatment.

OBJECTIVES: There has been a lot of interest in the field of laboratory medicine regarding the use of machine learning (ML)-based prediction models. T...

An agentic framework for autonomous scientific discovery in cancer pathology.

Artificial intelligence has advanced cancer pathology, but many systems still depend on hand-crafted features, are hard to explain and rely on fragmen...

Performance of artificial intelligence software: EndoAngel, EndoAID, CAD-EYE, GI Genius, and EndoScreener in adenoma detection: an extended network meta-analysis.

BACKGROUND: Colorectal cancer is a major global health burden, with most cases arising from adenomatous polyps. Although colonoscopy is the gold stand...