Background: Tumors are the second most common cause of death in humans worldwide, second only to cardiovascular and cerebrovascular diseases. Although methods and techniques for the treatment of tumors continue to improve, the effect is not satisfactory. These may lack effective therapeutic targets. This study aimed to evaluate the value of SNHG12 as a biomarker in the prognosis and clinical characteristics of various cancer patients. Methods: We analyzed SNHG12 expression and plotted the survival curves of all cancer samples in the TCGA database using the GEPIA tool. Then, we searched for eligible papers up to April 1, 2019, in databases. Next, the data were extracted from studies examining SNHG12 expression, overall survival and clinicopathological features in patients with malignant tumors. We used Review Manager 5.3 and Stata 15 software to analyze the statistical data. Results: In the TCGA database, abnormally high expression of SNHG12 in tumor samples indicates that the patient has a poor prognosis. Results of meta-analysis is that SNHG12 high expression is related to low overall survival (HR = 2.72, 95% CI = 1.95–3.8, P < 0.00001), high tumor stage (OR = 3.94, 95% CI = 2.80–5.53, P < 0.00001), high grade (OR = 2.04, 95% CI = 1.18–3.51, P = 0.01), distant metastasis (OR = 2.20, 95% CI = 1.40–3.46, P = 0.0006), tumor size (OR = 2.79, 95% CI = 1.89–4.14, P < 0.00001), and lymph node metastasis (OR = 2.66, 95% CI = 1.65–4.29, P < 0.0001). Conclusions: Our study confirmed that the high expression level of SNHG12 is closely related to the clinicopathological characteristics and prognosis of patients and is a new predictive biomarker for various cancer patients.

Genome instability is a hallmark of tumors and is involved in proliferation, invasion, migration, and treatment resistance of many tumors. However, the relationship of genome instability with gliomas remains unclear. Here, we constructed genome instability-derived long non-coding RNA (lncRNA)-based gene signatures (GILncSig) using genome instability-related lncRNAs derived from somatic mutations. Multiple platforms were used to confirm that the GILncSig were closely related to patient prognosis and clinical characteristics. We found that GILncSig, the glioma microenvironment, and glioma cell DNA methylation-based stemness index (mDNAsi) interacted with each other to form a complex regulatory network. In summary, this study confirmed that GILncSig was an independent prognostic indicator for patients, distinguished high-risk and low-risk groups, and affected immune-cell infiltration and tumor-cell stemness indicators (mDNAsi) in the tumor microenvironment, resulting in tumor heterogeneity and immunotherapy resistance. GILncSig are expected to provide new molecular targets for the clinical treatment of patients with gliomas.