A concise review of inflammatory biomarkers targeted cancer therapy.
Ashish P ShahChhagan PatelPublished in: Folia medica (2022)
Inflammation is considered a general protective reaction of localized tissue against injury, irritation, or swelling. Inflammation may be acute, which is part of the defensive response; or chronic, which may lead to the development of various diseases including cancer. Several pro-inflammatory genes play important role in the various cellular processes like cell proliferation, angiogenesis, metastasis, and suppression of apoptosis. These pro-inflammatory genes include TNF-α, interleukins, chemokines, MMPs, cyclooxygenase, lipoxygenase, iNOS, Jak/STAT pathway, etc. All these genes are mainly regulated by the transcription factor NF-κB, which is found active in many types of neoplastic cells. Therefore, developing molecules that target pro-inflammatory genes or transcription factor is believed to be one of the good strategies for development of anti-cancer agents. Literature data suggest that many anti-inflammatory agents, including non-steroidal anti-inflammatory drugs, corticosteroids, statins, metformin, embelin, and some natural products, can interfere with the tumor microenvironment by inhibiting pro-inflammatory genes or transcription factors and increasing cell apoptosis. This review describes the link between inflammation and cancer, the role of pro-inflammatory genes and transcription factors in the development of tumor cells, and the use of anti-inflammatory agents in cancer.
Keyphrases
- transcription factor
- genome wide identification
- oxidative stress
- genome wide
- cell proliferation
- papillary thyroid
- bioinformatics analysis
- cancer therapy
- anti inflammatory
- anti inflammatory drugs
- systematic review
- signaling pathway
- induced apoptosis
- dna binding
- endothelial cells
- genome wide analysis
- liver failure
- drug delivery
- lps induced
- drug induced
- respiratory failure
- extracorporeal membrane oxygenation
- vascular endothelial growth factor
- toll like receptor
- pi k akt
- wound healing
- data analysis