Nervous NDRGs: the N-myc downstream–regulated gene family in the central and peripheral nervous system

textabstractThe N-Myc downstream-regulated gene (NDRG) family consists of four members (NDRG1, NDRG2, NDRG3, NDRG4) that are differentially expressed in various organs and function in important processes, like cell proliferation and differentiation. In the last couple of decades, interest in this family has risen due to its connection with several disorders of the nervous system including Charcot-Marie-Tooth disease and dementia, as well as nervous system cancers. By combining a literature review with in silico data analysis of publicly available datasets, such as the Mouse Brain Atlas, BrainSpan, the Genotype-Tissue Expression (GTEx) project, and Gene Expression Omnibus (GEO) datasets, this review summarizes the expression and functions of the NDRG family in the healthy and diseased nervous system. We here show that the NDRGs have a differential, relatively cell type–specific, expression pattern in the nervous system. Even though NDRGs share functionalities, like a role in vesicle trafficking, stress response, and neurite outgrowth, other functionalities seem to be unique to a specific member, e.g., the role of NDRG1 in myelination. Furthermore, mutations, phosphorylation, or changes in expression of NDRGs are related to nervous system diseases, including peripheral neuropathy and different forms of dementia. Moreover, NDRG1, NDRG2, and NDRG4 are all involved in cancers of the nervous system, such as glioma, neuroblastoma, or meningioma. All in all, our review elucidates that although the NDRGs belong to the same gene family and share some functional features, they should be considered unique in their expression patterns and functional importance for nervous system development and neuronal diseases

Technical considerations in PCR-based assay design for diagnostic DNA methylation cancer biomarkers

Background: DNA methylation biomarkers for early detection, risk stratification and treatment response in cancer have been of great interest over the past decades. Nevertheless, clinical implementation of these biomarkers is limited, as only < 1% of the identified biomarkers is translated into a clinical or commercial setting. Technical factors such as a suboptimal genomic location of the assay and inefficient primer or probe design have been emphasized as important pitfalls in biomarker research. Here, we use eleven diagnostic DNA methylation biomarkers for colorectal cancer (ALX4, APC, CDKN2A, MGMT, MLH1, NDRG4, SDC2, SFRP1, SFRP2, TFPI1 and VIM), previously described in a systematic literature search, to evaluate these pitfalls. Results: To assess the genomic assay location, the optimal genomic locations according to TCGA data were extracted and compared to the genomic locations used in the published assays for all eleven biomarkers. In addition, all primers and probes were technically evaluated according to several criteria, based on literature and expert opinion. Both assay location and assay design quality varied widely among studies. Conclusions: Large variation in both assay location and design hinders the development of future DNA methylation biomarkers as well as inter-study comparability

Technical considerations in PCR-based assay design for diagnostic DNA methylation cancer biomarkers

BACKGROUND: DNA methylation biomarkers for early detection, risk stratification and treatment response in cancer have been of great interest over the past decades. Nevertheless, clinical implementation of these biomarkers is limited, as only < 1% of the identified biomarkers is translated into a clinical or commercial setting. Technical factors such as a suboptimal genomic location of the assay and inefficient primer or probe design have been emphasized as important pitfalls in biomarker research. Here, we use eleven diagnostic DNA methylation biomarkers for colorectal cancer (ALX4, APC, CDKN2A, MGMT, MLH1, NDRG4, SDC2, SFRP1, SFRP2, TFPI1 and VIM), previously described in a systematic literature search, to evaluate these pitfalls. RESULTS: To assess the genomic assay location, the optimal genomic locations according to TCGA data were extracted and compared to the genomic locations used in the published assays for all eleven biomarkers. In addition, all primers and probes were technically evaluated according to several criteria, based on literature and expert opinion. Both assay location and assay design quality varied widely among studies. CONCLUSIONS: Large variation in both assay location and design hinders the development of future DNA methylation biomarkers as well as inter-study comparability

Identification of DNA methylation markers for early detection of CRC indicates a role for nervous system-related genes in CRC

Purpose: Colonoscopy and the fecal immunochemical test (FIT) are currently the most widely used screening modalities for colorectal cancer (CRC), however, both with their own limitations. Here we aim to identify and validate stool-based DNA methylation markers for the early detection of CRC and investigate the biological pathways prone to DNA methylation. Methods: DNA methylation marker discovery was performed using The Cancer Genome Atlas (TCGA) colon adenocarcinoma data set consisting of normal and primary colon adenocarcinoma tissue. The performance of the five best candidate markers and a previously identified marker, NDRG4, was evaluated on tissues and whole stool samples of healthy subjects and CRC patients using quantitative MSP assays. The results were compared and combined with FIT data. Finally, pathway and gene ontology enrichment analyses were performed using ToppFun, GOrilla and clusterProfiler. Results: GDNF, HAND2, SLC35F3, SNAP91 and SORCS1 were ranked as the best performing markers. Gene combinations of all five markers, NDRG4 and FIT were evaluated to establish the biomarker panel with the highest diagnostic potential, resulting in the identification of GDNF/SNAP91/NDRG4/FIT as the best performing marker panel. Pathway and gene ontology enrichment analyses revealed that genes associated with the nervous system were enriched in the set of best performing CRC-specific biomarkers. Conclusion: In silico discovery analysis using TCGA-derived data yielded a novel DNA-methylation-based assay for the early detection of CRC, potentially improving current screening modalities. Additionally, nervous system-related pathways were enriched in the identified genes, indicating an epigenetic regulation of neuronal genes in CRC