Abstract
Background Patients diagnosed with schizophrenia were found having lower risks to develop cancers, including glioma. Based on this epidemiology, we hypothesized that there were gene profiles playing opposite roles in pathogenesis of schizophrenia and glioma. Methods Based on GEO datasets and TCGA, key genes of schizophrenia genes on the opposite development of glioma were screened by different expressed genes (DEGs) screening, weighted gene coexpression network analysis (WGCNA), disease-specific survival (DSS), and glioma grading and verified by gene set enrichment analysis (GSEA). Results First, 612 DEGs were screened from schizophrenia and control brain samples. Second, 134 key genes more specific to schizophrenia were left by WGCNA, with 93 key genes having annotations in TCGA. Third, DSS of glioma helped to find 42 key gene expressions of schizophrenia oppositely associated with survival of glioma. Finally, 24 key genes showed opposite expression trends in schizophrenia and different glioma grading, i.e., the upregulated key genes in schizophrenia expressed increasingly in higher grade glioma, and vice versa. CAMK2D and MPC2 were taken as the examples and evaluated by GSEA, which indeed showed opposite trends in the same pathways of schizophrenia and glioma. Conclusion This workflow of selecting novel targeted genes which may have opposite roles in pathogenesis of two diseases was firstly and innovatively generated by our team. Some filtered key genes were indeed found by their potential effects in several mechanism studies, indicating our process could be effective to generate novel targeted genes. These 24 key genes may provide potential directions for future biochemical and pharmacotherapeutic research studies.
Highlights
Patients diagnosed with schizophrenia were found having lower risks to develop cancers, including glioma
By examining functions of different expressed genes (DEGs), we had a better view about disease progression of schizophrenia. e gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were employed to sort out DEGs
42 key genes were selected by weighted gene coexpression network analysis (WGCNA) and diseasespecific survival (DSS), the range of potential targeted genes for future biochemical and pharmacological research studies would be better to be compressed. erefore, we considered that gliomas could be divided into low-grade gliomas and highgrade gliomas according to the World Health Organization classification criteria
Summary
Patients diagnosed with schizophrenia were found having lower risks to develop cancers, including glioma. Based on this epidemiology, we hypothesized that there were gene profiles playing opposite roles in pathogenesis of schizophrenia and glioma. Based on GEO datasets and TCGA, key genes of schizophrenia genes on the opposite development of glioma were screened by different expressed genes (DEGs) screening, weighted gene coexpression network analysis (WGCNA), diseasespecific survival (DSS), and glioma grading and verified by gene set enrichment analysis (GSEA). Ird, DSS of glioma helped to find 42 key gene expressions of schizophrenia oppositely associated with survival of glioma. Some filtered key genes were found by their potential effects in several mechanism studies, indicating our process could be effective to generate novel targeted genes. Some filtered key genes were found by their potential effects in several mechanism studies, indicating our process could be effective to generate novel targeted genes. ese 24 key genes may provide potential directions for future biochemical and pharmacotherapeutic research studies
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