Colorectal Cancer Treatment and Prognostic Biomarkers

Colorectal cancer remains one of the leading causes of cancer morbidity and mortality worldwide. Multimodal treatment typically combines surgery, chemotherapy and, increasingly, targeted agents or immunotherapy. Surgical resection with complete mesocolic excision remains the cornerstone for local disease, while adjuvant and neoadjuvant regimens employ fluoropyrimidines, oxaliplatin or irinotecan, often in combination with monoclonal antibodies against epidermal growth factor receptor or vascular endothelial growth factor. In the metastatic setting, immunotherapy has shown benefit in mismatch repair–deficient tumours, and novel small-molecule inhibitors are under investigation. Prognostic biomarkers have evolved from serum markers such as carcinoembryonic antigen to complex molecular signatures derived from genomic, transcriptomic and epigenetic data. Circulating tumour DNA and microsatellite instability status now inform treatment selection and risk stratification. Gene-expression classifiers and immune-infiltration profiles help to identify patients who may derive most benefit from specific therapies, driving a precision-medicine approach that integrates tumour biology with clinical decision making.

Research from Nature Portfolio

No recent Nature Portfolio content available.

Colorectal Cancer Treatment and Prognostic Biomarkers publication trend

The graph below shows the total number of articles in colorectal cancer treatment and prognostic biomarkers across all publications each year (not limited to Nature Index journals).

Technical terms

Risk score: Composite numerical value derived from weighted expression of multiple genes to stratify patients by prognosis.

Microsatellite instability (MSI): Hypermutation phenotype caused by defects in DNA mismatch repair, predictive of immunotherapy response.

Circulating tumour DNA (ctDNA): Fragments of tumour-derived DNA in the circulation, used for non-invasive detection and monitoring.

Consensus clustering: Unsupervised statistical method for identifying robust molecular subtypes across datasets.

LASSO regression: Regularisation technique that selects a subset of predictors for model building by shrinking coefficients.

Immune infiltration: Presence and density of immune cells within the tumour microenvironment, influencing prognosis and therapy response.

References

1. Identification of Gene Signature‐Related Oxidative Stress for Predicting Prognosis of Colorectal Cancer. Oxidative Medicine and Cellular Longevity (2023).
2. A novel prognostic signatures based on metastasis- and immune-related gene pairs for colorectal cancer. Frontiers in Immunology (2023).
3. Development of an immune-related gene prognostic risk model and identification of an immune infiltration signature in the tumor microenvironment of colon cancer. BMC Gastroenterology (2023).