The Recurrent-Specific Regulation Network of Prognostic Stemness-Related Signatures in Low-Grade Glioma.
Jin LiMeng ZhouDan HuangRuoyi LinXiaomei CuiShaofeng ChenYing YaoShuyuan XianSiqiao WangQing FuJiwen ZhuXi YueRunzhi HuangEnbo QiZongqaing HuangPublished in: Disease markers (2023)
Gliomas including astrocytomas, oligodendrogliomas, mixed oligoastrocytic, and mixed glioneuronal tumors are an important group of brain tumors. Based on the 2016 WHO classification for tumors in the central nervous system, gliomas were classified into four grades, from I to IV, and brain lower grade glioma (LGG) consists of grade II and grade III. Patients with LGG may undergo recurrence, which makes clinical treatment tough. Stem cell-like features of cancer cells play a key role in tumor's biological behaviors, including tumorigenesis, development, and clinical prognosis. In this article, we quantified the stemness feature of cancer cells using the mRNA stemness index (mRNAsi) and identified stemness-related key genes based on correlation with mRNAsi. Besides, hallmark gene sets and translate factors (TFs) which were highly related to stemness-related key genes were identified. Therefore, a recurrency-specific network was constructed and a potential regulation pathway was identified. Several online databases, assay for transposase-accessible chromatin using sequencing (ATAC-seq), single-cell sequencing analysis, and immunohistochemistry were utilized to validate the scientific hypothesis. Finally, we proposed that aurora kinase A (AURKA), positively regulated by Non-SMC Condensin I Complex Subunit G (NCAPG), promoted E2F target pathway in LGG, which played an important role in LGG recurrence.
Keyphrases
- stem cells
- single cell
- genome wide
- low grade
- epithelial mesenchymal transition
- high grade
- machine learning
- rna seq
- deep learning
- high throughput
- gene expression
- dna methylation
- cancer stem cells
- dna damage
- multiple sclerosis
- genome wide identification
- copy number
- bone marrow
- protein kinase
- binding protein
- blood brain barrier
- artificial intelligence
- drug induced
- bioinformatics analysis