Tumor Microenvironment in Metastatic Colorectal Cancer: The Arbitrator in Patients' Outcome.
Cristina Galindo-PumariñoManuel ColladoMercedes HerreraCristina PeñaPublished in: Cancers (2021)
Colorectal cancer (CRC) is one of the most common cancers in western countries. Its mortality rate varies greatly, depending on the stage of the disease. The main cause of CRC mortality is metastasis, which most commonly affects the liver. The role of tumor microenvironment in tumor initiation, progression and metastasis development has been widely studied. In this review we summarize the role of the tumor microenvironment in the liver pre-metastatic niche formation, paying attention to the distant cellular crosstalk mediated by exosomes. Moreover, and based on the prognostic and predictive capacity of alterations in the stromal compartment of tumors, we describe the role of tumor microenvironment cells and related liquid biopsy biomarkers in the delivery of precise medication for metastatic CRC. Finally, we evaluate the different clinical strategies to prevent and treat liver metastatic disease, based on the targeting of the tumor microenvironment. Specifically, targeting angiogenesis pathways and regulating immune response are two important research pipelines that are being widely developed and promise great benefits.
Keyphrases
- squamous cell carcinoma
- small cell lung cancer
- metastatic colorectal cancer
- immune response
- end stage renal disease
- cardiovascular events
- chronic kidney disease
- ejection fraction
- cancer therapy
- newly diagnosed
- induced apoptosis
- bone marrow
- mesenchymal stem cells
- lymph node
- stem cells
- prognostic factors
- peritoneal dialysis
- risk factors
- endothelial cells
- healthcare
- cell cycle arrest
- young adults
- cell death
- south africa
- coronary artery disease
- vascular endothelial growth factor
- machine learning
- cardiovascular disease
- patient reported outcomes
- inflammatory response
- ionic liquid
- drug delivery
- ultrasound guided
- working memory
- adverse drug
- deep learning
- signaling pathway