AIMC Topic: Colorectal Neoplasms

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Preoperative radiomics models using CT and MRI for microsatellite instability in colorectal cancer: a systematic review and meta-analysis.

Abdominal radiology (New York)
OBJECTIVE: Microsatellite instability (MSI) is a novel predictive biomarker for chemotherapy and immunotherapy response, as well as prognostic indicator in colorectal cancer (CRC). The current standard for MSI identification is polymerase chain react...

Genetic Control of tRNA-Derived Fragments Contributes to Cancer Risk.

Cancer research
UNLABELLED: tRNA-derived fragments (tRF) are a class of small noncoding RNAs that have exhibited several functions in cancer. Recent studies have shown that mutations in tRNA genes can lead to global changes in tRF expression levels and may affect tR...

Associations between Calcium Intake and T-cell Infiltration in Colorectal Tumors.

Cancer prevention research (Philadelphia, Pa.)
UNLABELLED: Higher T-cell infiltration in colorectal tumors has been associated with better prognosis. Evidence indicates that calcium signaling is essential for T-cell functioning. However, as it is unknown whether calcium intake influences T-cell i...

Machine learning models for predicting chemotherapy-induced adverse drug reactions in colorectal cancer patients.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: Chemotherapy-induced adverse drug reactions (ADRs) are common in patients with colorectal cancer. We developed four machine learning models to predict chemotherapy-induced ADRs and assessed the performance. These models leverage high-dime...

Fecal volatile organic compounds for colorectal cancer detection: A systematic review and meta-analysis.

Computers in biology and medicine
BACKGROUND: Background: Fecal volatile organic compound (VOC) analysis has emerged as a promising non-invasive tool for detecting colorectal cancer (CRC). Despite its reported high diagnostic accuracy, clinical adoption is hindered due to issues like...

CRCpred: An AI-ML tool for colorectal cancer prediction using gut microbiome.

Computers in biology and medicine
Colorectal cancer (CRC) is a leading cause of death worldwide. A plethora of research shows the alteration of the gut microbiome and the association of bacterial taxa with CRC. Gaining insights into the health status through microbiome-based diagnosi...

Interpretable machine learning models based on body composition and inflammatory nutritional index (BCINI) to predict early postoperative recurrence of colorectal cancer: Multi-center study.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Colorectal cancer (CRC) ranks among the most prevalent cancers worldwide, with early postoperative recurrence remaining a major cause of mortality. Body composition and inflammatory-nutritional indices (BCINI) have demonstra...

Development and interpretation of a pathomics-based model for the prediction of immune therapy response in colorectal cancer.

Methods (San Diego, Calif.)
Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related deaths worldwide, with a 5-year survival rate below 20 %. Immunotherapy, particularly immune checkpoint blockade (ICB)-based therapies, has bec...

Unraveling the Role of Gut Microbiota in Colorectal Cancer: A Global Perspectives and Biomarkers as Early Screening Tool for Colorectal Cancer.

Studies in health technology and informatics
Colorectal cancer (CRC), the second deadliest cancer globally, is closely tied to gut microbiota, opening doors for early detection and treatment. This review of 45 studies (2018-2024) highlights microbial biomarkers like Fusobacterium nucleatum, Bac...