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Nuclei Isolation from Fresh Frozen Brain Tumors for Single-Nucleus RNA-seq and ATAC-seq
Published on: August 25, 2020
Mendelian randomization and single-cell analysis reveal novel genetic risk factors and cellular heterogeneity in
Jun Li1, Jing Xu1, Lianshu Ding1
1Department of Neurosurgery, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, No. 1 Huanghe Road West, Huaian, 223300, Jiangsu Province, China.
Background:
Glioblastoma is the most aggressive primary brain tumor with limited therapeutic options and poor prognosis. Understanding the genetic determinants and cellular complexity of glioblastoma is crucial for developing novel therapeutic strategies.
Methods:
We conducted a comprehensive Mendelian randomization (MR) analysis to investigate causal relationships between genetic exposures and glioblastoma risk, employing multiple MR methods including MR Egger, weighted median, inverse variance weighted, simple mode, and weighted mode approaches. Single-cell RNA sequencing was performed to characterize cellular heterogeneity within the glioblastoma microenvironment. Extensive sensitivity analyses including funnel plots and leave-one-out analyses were conducted to ensure robust causal inference. RT-PCR validation was conducted using BV2 glioma cell line compared to normal brain tissue controls. Integration analysis linked genetic risk factors to cellular expression patterns and biological pathways.
Results:
The Mendelian randomization analysis identified several genes with robust causal relationships to glioblastoma risk. Protective associations were observed for TIMP3 (OR = 0.675, 95% CI: 0.473-0.965, p = 0.031), TREM1 (OR = 0.631, 95% CI: 0.411-0.968, p = 0.035), FLRT3 (OR = 0.661, 95% CI: 0.512-0.853, p = 0.001), and IL12B (OR = 0.644, 95% CI: 0.448-0.925, p = 0.017). Conversely, risk-increasing associations were identified for TALDO1 (OR = 12.433, 95% CI: 1.808-85.507, p = 0.010) and PDCD6 (OR = 4.532, 95% CI: 1.429-14.368, p = 0.010). RT-PCR validation confirmed significant downregulation of protective genes in BV2 glioma cells: TIMP3 (2.48-fold decrease, p = 0.031), TREM1 (2.74-fold decrease, p = 0.035), FLRT3 (2.91-fold decrease, p = 0.001), and IL12B (2.33-fold decrease, p = 0.017). Single-cell analysis revealed distinct cellular populations with cell-type-specific expression patterns of identified risk genes.
Conclusions:
This study provides robust evidence for novel genetic risk factors in glioblastoma development and reveals the complex cellular landscape of the tumor microenvironment. The identified protective and risk genes offer potential targets for therapeutic intervention and biomarker development.
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