Detergent fractionation with subsequent subtractive suppression hybridization as a tool for identifying genes coding for plasma membrane proteins

Biological Role of Nodal Modulator: A Comprehensive Review of the Last Two Decades

Nodal modulator (NOMO) is a type I transmembrane protein that is conserved in various human tissues. Humans have three highly similar NOMO proteins, namely NOMO1, NOMO2, and NOMO3. These three proteins are closely related and may have similar functions. NOMO has been identified as a part of a protein complex that mediates a wide range of biological processes such as tumor formation, bone and cartilage formation, embryo formation, facial asymmetry, and development of congenital heart disease. To date, a few studies have focused on the role of NOMO; however, the mechanism underlying its effects remains unknown. To improve our understanding regarding NOMO, we reviewed the role of NOMO in different diseases and investigated the mechanism underlying its effects.

Genotype-based gene signature of glioma risk

Background

Glioma accounts for 80% of malignant brain tumors, but its etiologic determinants remain elusive. Despite genetic susceptibility loci identified by genome-wide association study (GWAS), the agnostic approach leaves open the possibility that other susceptibility genes remain to be discovered. Here we conduct a gene-centric integrative GWAS (iGWAS) of glioma risk that combines transcriptomics and genetics.

Methods

We synthesized a brain transcriptomics dataset (n = 354), a GWAS dataset (n = 4203), and an advanced glioma tumor transcriptomic dataset (n = 483) to conduct an iGWAS. Using the expression quantitative trait loci (eQTL) dataset, we built models to predict gene expression for the GWAS data, based on eQTL genotypes. With the predicted gene expression, iGWAS analyses were performed using a novel statistical method. Gene signature risk score was constructed using a penalized logistic regression model.

Results

A total of 30527 transcripts were analyzed using the iGWAS approach. Four novel glioma susceptibility genes were identified with internal and external validation, including DRD5 (P = 3.0 × 10-79), WDR1 (P = 8.4 × 10-77), NOMO1 (P = 1.3 × 10-25), and PDXDC1 (P = 8.3 × 10-24). The genotype-predicted transcription pattern between cases and controls is consistent with that between tumor and its matched normal tissue. The genotype-based 4-gene signature improved the classification between glioma cases and controls based on age, gender, and population stratification, with area under the receiver operating characteristic curve increasing from 0.77 to 0.85 (P = 8.1 × 10-23).

Conclusion

A new genotype-based gene signature of glioma was identified using a novel iGWAS approach, which integrates multiplatform genomic data as well as different genetic association studies.