Gliomas are the most common primary
brain cancers. In recent years, IDH mutation and 1p/19q codeletion have been suggested as
biomarkers for the diagnosis, treatment, and prognosis of
gliomas. However, these
biomarkers are only effective for a part of
glioma patients, and thus more
biomarkers are still emergently needed. Recently, an electrochemical communication between normal neurons and
glioma cells by neuro-
glioma synapse has been reported. Moreover, it was discovered that breast-to-brain
metastasis tumor cells have pseudo synapses with neurons, and these synapses were indicated to promote
tumor progression and
metastasis. Based on the above observations, we first curated a panel of 17 synapse-related genes and then proposed a metric, synapse score to quantify the "stemness" for each sample of 12
glioma gene expression datasets from TCGA, CGGA, and GEO. Strikingly, synapse score showed excellent predictive ability for the prognosis, diagnosis, and grading of
gliomas. Moreover, being compared with the two established
biomarkers, IDH mutation and 1p/19q codeletion, synapse score demonstrated independent and better predictive performance. In conclusion, this study proposed a quantitative method, synapse score, as an efficient
biomarker for monitoring
gliomas.