Skin cutaneous melanoma (SKCM) is a common malignant skin cancer. Early diagnosis could effectively reduce SKCM patient’s mortality to a large extent. We managed to construct a model to examine the prognosis of SKCM patients. The methylation-related data and clinical data of The Cancer Gene Atlas- (TCGA-) SKCM were downloaded from TCGA database. After preprocessing the methylation data, 21,861 prognosis-related methylated sites potentially associated with prognosis were obtained using the univariate Cox regression analysis and multivariate Cox regression analysis. Afterward, unsupervised clustering was used to divide the patients into 4 clusters, and weighted correlation network analysis (WGCNA) was applied to construct coexpression modules. By overlapping the CpG sites between the clusters and turquoise model, a prognostic model was established by LASSO Cox regression and multivariate Cox regression. It was found that 9 methylated sites included cg01447831, cg14845689, cg20895058, cg06506470, cg09558315, cg06373660, cg17737409, cg21577036, and cg22337438. After constructing the prognostic model, the performance of the model was validated by survival analysis and receiver operating characteristic (ROC) curve, and the independence of the model was verified by univariate and multivariate regression. It was represented that the prognostic model was reliable, and riskscore could be used as an independent prognostic factor in SKCM patients. At last, we combined clinical data and patient’s riskscore to establish and testify the nomogram that could determine patient’s prognosis. The results found that the reliability of the nomogram was relatively good. All in all, we constructed a prognostic model that could determine the prognosis of SKCM patients and screened 9 key methylated sites through analyzing data in TCGA-SKCM dataset. Finally, a prognostic nomogram was established combined with clinical diagnosed information and riskscore. The results are significant for improving the prognosis of SKCM patients in the future.

Primary spinal cord glioblastoma (PSC GBM) is a rare disease with limited treatment options. Here, we describe a case of PSC GBM treated with anlotinib in this report. Molecular characterization confirmed the presence of the MGMT promoter unmethylated, IDH wild type, FGFR3 p.S249C and p53 p.V73fs mutations in the patient. Anlotinib is a multitarget tyrosine kinase inhibitor that target VEGFR2/3, FGFR1-4, PDGFRα/β, and c-kit. After a partial resection of the tumor at the extramedullary invasion site, the patient was administered anlotinib 12 mg p.o. once every day (days 1-14, 21-day cycle) in combination with irinotecan chemotherapy (days 1 and 8, 21-day cycle). The patient exhibited significant symptom remission and partial response and was maintained for more than 10 months of follow-up. This case study showed that FGFR3 S249C may be a new marker for the treatment of PSC GBM with anlotinib. This case is also another strong support for molecular diagnosis and precision medicine.