Colon Cancer

GIN-CRC-Pareto: A graph-based pareto-optimized multi-task learning framework to identify miRNA-target interactions in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) ranks as the third highest incidence among malignancies for human and the second most common cause of cancer-related mortality in the United States. Accumulating evidence has established microRNAs (miRNAs) as critical regulators of cancer development and therapeutic response. Understanding miRNA-mRNA interactions is critical for elucidating the molecular mechani...

AI-Driven Rational Design of Nanotherapeutics for Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) remains a formidable malignancy characterized by late diagnosis, high recurrence rates, and pronounced chemoresistance. While nanoparticle-based drug delivery systems (NDDS) offer theoretical advantages over conventional therapies, their clinical translation in PDAC has been severely limited. The dense desmoplastic stroma, elevated interstitial fluid pressur...

MOF-regulated aggregation-induced electrochemiluminescence for machine learning-assisted aptasensing of cancer marker.

Electrochemiluminescence (ECL) biosensing requires luminophores with high emission efficiency and favorable interfacial reaction kinetics. Herein, a n...

Oral and gut microbiota profiles in patients with locally advanced rectal cancer with varying responses to neoadjuvant chemoradiotherapy.

Recent research has focused on gut bacteria in colorectal cancer, but the influence of other microbiota, including oral and nonbacterial gut microbiot...

CLDN18 as a novel junctional biomarker enhancing multi-gene classification of pancreatic cancer.

Pancreatic adenocarcinoma (PAAD) remains one of the most lethal cancers, largely due to the lack of reliable diagnostic biomarkers. Through integrativ...

Machine learning identifies ac4C-related prognostic signature and TUBA1C as therapeutic target in COAD.

To explore the role of N4-acetylcytidine (ac4C)-related genes (acRGs) in colon adenocarcinoma (COAD) and identify reliable prognostic biomarkers and p...

Colorectal Lesion diagnosis using transformer and deep learning with multiscale feature interface.

Colorectal cancer is the third most common malignancy worldwide. Manual screening requires expertise and resources. However, advancements in AI (artif...

An Exosomal Signature for Preoperative Detection of Occult Liver Metastasis in Pancreatic Cancer.

IMPORTANCE: Early liver metastasis (early-LiM) after pancreatectomy represents an aggressive biological phenotype of pancreatic ductal adenocarcinoma ...

From dysbiosis to precision oncology: translational role of the microbiome in gastrointestinal cancer.

Gastrointestinal (GI) cancers, including colorectal, gastric, pancreatic, hepatocellular, and esophageal malignancies, remain a leading cause of cance...

DNAmBERT: a transformer-based model for non-invasive cancer diagnosis using DNA sequence and methylation data.

DNA methylation alterations are early and stable hallmarks of cancer and represent promising biomarkers for non-invasive detection using circulating c...

Feasibility of a Stool State Check App Using AI During Bowel Preparation Before Colonoscopy: Multicenter Prospective Study (SCAN Study).

BACKGROUND: Optimal bowel preparation (BP) is crucial for a successful colonoscopy. Although multiple factors influence BP quality, including patient ...

Assessment of atypical glandular cell interpretation in Pap tests using the Hologic Genius Digital Diagnostics System.

Atypical glandular cells (AGC) are a diagnostic challenge. The aim of this study was to evaluate the efficacy and diagnostic performance of AGC detect...

Artificial intelligence-assisted histopathological diagnosis of endocervical gastric-type adenocarcinoma: a multicenter model development and validation study.

Endocervical gastric-type adenocarcinoma (GAS) is one of the most aggressive subtypes of cervical cancer and is frequently underdiagnosed due to morph...

Machine learning-based classification model to distinguish tumor and tumor-free samples using synthetic plasma proteomic dataset.

BACKGROUND: Tumor-Specific Peptides (TSPs) and Tumor-associated Overexpressed Proteins (TOPs) are promising biomarkers for cancer diagnosis and monito...

Multi-level Transcriptomic and Machine-learning Analyses Identify MZT1 as a Proliferation-associated Prognostic Marker in Lung Adenocarcinoma.

BACKGROUND/AIM: Lung adenocarcinoma (LUAD) exhibits substantial molecular heterogeneity and variable clinical outcomes, highlighting the need for biom...

Mechanistic and Clinical Perspectives on Traditional Chinese Medicine in Thyroid Cancer Management.

Thyroid cancer is one of the most prevalent malignancies of the endocrine system, comprising various subtypes such as papillary thyroid carcinoma (PTC...

Patient-Derived Organoid and Single-Cell Multiomics Reveal Evolution Driven by CEACAM6/KRT19-Mediated Heterogeneity.

Colorectal cancer (CRC) remains a leading cause of cancer mortality globally, with therapeutic efficacy hindered by tumor heterogeneity and drug resis...

Prognostic Models and Predictors of Recurrence in Resectable Colorectal Liver Metastases: A Systematic Review and Meta-analysis.

We systematically reviewed prognostic models for recurrence after curative-intent locoregional treatment of colorectal liver metastases (CRLM) and qua...

Integrative single-cell and spatial transcriptomic analysis reveals 4-HNE-related stromal remodeling in lung adenocarcinoma.

BACKGROUND: 4-HNE is a lipid peroxidation product involved in oxidative stress, tumor microenvironment remodeling, and tumor progression. This study a...

Application of Artificial Intelligence in Diagnosis and Management of Thyroid Disease.

Artificial intelligence (AI) is transforming thyroid care, with applications spanning ultrasound risk stratification, cytopathology, histopathology, r...