Cancer is one of the most persistent and hardy diseases. Cancers often develop the ability to suppress the immune system. A tumor can interact with its immediate environment, and “turn off” certain immune cells. These immune cells, which usually survey the body for problems, become blind to the tumor and cannot target it for destruction.
Melanoma is a deadly form of cancer with a poor five-year prognosis. It has several biomarkers useful for its general diagnosis, but a team from Central South University in China found them to have poor prognostic abilities. Melanoma has a strong link to the immune system, so they hypothesized that immune-related genes could be biomarker candidates for melanoma.
The study would utilize two databases: the Gene Expression Omnibus, and The Cancer Genome Atlas. Both are public genetic databases that contain expression data from patients with and without cancer. Using these data, they identified genes that had different expression levels in melanoma versus healthy skin tissue. They then cross-referenced the hits with known immune-related genes to identify 81 biomarker candidates. Most of these candidates turned out to be involved in cytokine and chemokine pathways, which are critical signaling pathways involved in the immune response.
Further analysis of the 81 candidates showed that two, in particular, CCL8 and DEFB1, had real potential as biomarkers. They developed a basic formula to generate an immune-related gene (IRG) score that could separate patients into either a high or a low-risk group. The high-risk group was characterized by decreased CCL8 levels and increased DEFB1 levels. With the IRG score, alongside age and stage of cancer, the team could reasonably predict the 3 and 5-year overall survival rates using data from the databases.
This study represents an attempt to identify immune-related biomarkers for the prognosis of melanoma. The accuracy of the overall test was reasonable and may present a useful tool for doctors should it be validated. The team made an interesting observation that the high-risk group seemed to respond better to anti-PD-1 therapy, a common chemotherapy for many cancers, than the low-risk group. They noted the group for that test was small, so it may not be a real finding.
Biomarkers are a challenge to study, considering the incredibly diverse cancer expression profiles out there. The team concludes, “we have constructed a predictive model which combined immune-related genes with clinical characteristics for the first time, to estimate melanoma patient survivals and therefore help with decision making in the treatment.”