Biomarkers for Evaluating the Inflammation Status in Patients with Cancer
- Author:
Ali GUNER
1
;
Hyoung Il KIM
Author Information
- Publication Type:Review
- Keywords: Inflammation; Cancer; Biomarkers; Immune system; Outcome assessment
- MeSH: Biomarkers; C-Reactive Protein; Carcinogenesis; Checklist; Enzyme-Linked Immunosorbent Assay; Flow Cytometry; Gene Expression Profiling; Humans; Immune System; Inflammation; Lymphocytes
- From:Journal of Gastric Cancer 2019;19(3):254-277
- CountryRepublic of Korea
- Language:English
- Abstract: Inflammation can be a causative factor for carcinogenesis or can result from a consequence of cancer progression. Moreover, cancer therapeutic interventions can also induce an inflammatory response. Various inflammatory parameters are used to assess the inflammatory status during cancer treatment. It is important to select the most optimal biomarker among these parameters. Additionally, suitable biomarkers must be examined if there are no known parameters. We briefly reviewed the published literature for the use of inflammatory parameters in the treatment of patients with cancer. Most studies on inflammation evaluated the correlation between host characteristics, effect of interventions, and clinical outcomes. Additionally, the levels of C-reactive protein, albumin, lymphocytes, and platelets were the most commonly used laboratory parameters, either independently or in combination with other laboratory parameters and clinical characteristics. Furthermore, the immune parameters are classically examined using flow cytometry, immunohistochemical staining, and enzyme-linked immunosorbent assay techniques. However, gene expression profiling can aid in assessing the overall peri-interventional immune status. The checklists of guidelines, such as STAndards for Reporting of Diagnostic accuracy and REporting recommendations for tumor MARKer prognostic studies should be considered when designing studies to investigate the inflammatory parameters. Finally, the data should be interpreted after adjusting for clinically important variables, such as age and cancer stage.
