Interleukins (Cytokines) as Biomarkers in Colorectal Cancer: Progression, Detection, and Monitoring.
Sajida MaryamKatarzyna KrukiewiczIhtisham Ul HaqAwal Ayaz KhanGalal YahyaSimona CavaluPublished in: Journal of clinical medicine (2023)
Cancer is the primary cause of death in economically developed countries and the second leading cause in developing countries. Colorectal cancer (CRC) is the third most common cause of cancer-related deaths worldwide. Risk factors for CRC include obesity, a diet low in fruits and vegetables, physical inactivity, and smoking. CRC has a poor prognosis, and there is a critical need for new diagnostic and prognostic biomarkers to reduce related deaths. Recently, studies have focused more on molecular testing to guide targeted treatments for CRC patients. The most crucial feature of activated immune cells is the production and release of growth factors and cytokines that modulate the inflammatory conditions in tumor tissues. The cytokine network is valuable for the prognosis and pathogenesis of colorectal cancer as they can aid in the cost-effective and non-invasive detection of cancer. A large number of interleukins (IL) released by the immune system at various stages of CRC can act as "biomarkers". They play diverse functions in colorectal cancer, and include IL-4, IL-6, IL-8, IL-11, IL-17A, IL-22, IL-23, IL-33, TNF, TGF-β, and vascular endothelial growth factor (VEGF), which are pro-tumorigenic genes. However, there are an inadequate number of studies in this area considering its correlation with cytokine profiles that are clinically useful in diagnosing cancer. A better understanding of cytokine levels to establish diagnostic pathways entails an understanding of cytokine interactions and the regulation of their various biochemical signaling pathways in healthy individuals. This review provides a comprehensive summary of some interleukins as immunological biomarkers of CRC.
Keyphrases
- poor prognosis
- vascular endothelial growth factor
- papillary thyroid
- physical activity
- end stage renal disease
- machine learning
- type diabetes
- metabolic syndrome
- long non coding rna
- squamous cell carcinoma
- insulin resistance
- drug delivery
- chronic kidney disease
- deep learning
- weight loss
- signaling pathway
- drinking water
- peritoneal dialysis
- dna methylation
- anti inflammatory
- transcription factor
- young adults
- ejection fraction
- oxidative stress
- sensitive detection
- patient reported