Refractory Metastatic Colorectal Cancer: Current Challenges and Future Prospects.
Marissa LamCaroline LumSarah LathamSamuel SmithHans PrenenEva SegelovPublished in: Cancer management and research (2020)
Despite advances, patients with metastatic colorectal cancer (mCRC) still have poor long-term survival. Identification of molecular subtypes is important to guide therapy through standard treatment pathways and holds promise for the development of new treatments. Following standard first- and second-line chemotherapy plus targeted agents, many patients retain a reasonable performance status, and thus are seeking further effective treatment to extend life and maintain symptom control. The challenge lies in selecting the most appropriate therapy in the third- and fourth-line settings, from a range of options including the relatively new oral agents TAS-102 and regorafenib, or rechallenge with previous chemotherapy or anti-epidermal growth factor receptor (anti-EGFR) monoclonal antibodies (mAB). Beyond this, therapy consists of trials involving novel agents and new combinations of treatments with theoretical synergy and/or non-overlapping toxicity. There is a great focus on enhancing immunogenicity in mCRC, to reflect the impressive results of immunotherapy drugs in the small cohort with mismatch repair deficient (dMMR) mCRC. Rare molecular subtypes of mCRC are increasingly being identified, including Her2-positive disease, NTRK fusions and others. Clinical trials exploring the efficacy of immunomodulatory and precision agents are plentiful and will hopefully yield clinically meaningful results that can be rapidly translated into routine care.
Keyphrases
- metastatic colorectal cancer
- epidermal growth factor receptor
- clinical trial
- tyrosine kinase
- healthcare
- small cell lung cancer
- end stage renal disease
- ejection fraction
- current status
- oxidative stress
- locally advanced
- palliative care
- prognostic factors
- randomized controlled trial
- stem cells
- combination therapy
- mesenchymal stem cells
- machine learning
- pain management
- rectal cancer
- chronic pain
- cell therapy
- deep learning
- monoclonal antibody
- big data