Chronic inflammation: key player and biomarker-set to predict and prevent cancer development and progression based on individualized patient profiles

Abstract

A strong relationship exists between tumor and inflammation, which is the hot point in cancer research. Inflammation can promote the occurrence and development of cancer by promoting blood vessel growth, cancer cell proliferation, and tumor invasiveness, negatively regulating immune response, and changing the efficacy of certain anti-tumor drugs. It has been demonstrated that there are a large number of inflammatory factors and inflammatory cells in the tumor microenvironment, and tumor-promoting immunity and anti-tumor immunity exist simultaneously in the tumor microenvironment. The typical relationship between chronic inflammation and tumor has been presented by the relationships between Helicobacter pylori, chronic gastritis, and gastric cancer; between smoking, development of chronic pneumonia, and lung cancer; and between hepatitis virus (mainly hepatitis virus B and C), development of chronic hepatitis, and liver cancer. The prevention of chronic inflammation is a factor that can prevent cancer, so it effectively inhibits or blocks the occurrence, development, and progression of the chronic inflammation process playing important roles in the prevention of cancer. Monitoring of the causes and inflammatory factors in chronic inflammation processes is a useful way to predict cancer and assess the efficiency of cancer prevention. Chronic inflammation-based biomarkers are useful tools to predict and prevent cancer.

Keywords: Big data analysis; Biomarkers; Cancer; Chronic inflammation; Collateral pathologies; Epigenetics; Genetics; Global statistics; Individualized patient profile; Inflammatory factors; Machine learning; Modifiable and preventable; Multiomics; Patient stratification; Phenotyping; Predictive preventive personalized medicine; Risk factors.

Fig. 1

A molecular model proposed for chronic inflammation in cancer. The orange box means the potential therapeutic targets and biomarkers for cancer. The green box means potential therapeutic targets for cancer. The corresponding information on relevant syndromes is provided in the article, for example, regarding the “Flammer syndrome” phenotype, “Individualized patient profiling is instrumental for cancer prediction and prevention” section