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Ectoderm-neural cortex protein 1 (ENC-1) (Kelch-like protein 37) (Nuclear matrix protein NRP/B) (p53-induced gene 10 protein) [KLHL37] [NRPB] [PIG10]


Selective molecular biomarkers to predict biologic behavior in pituitary tumors.

To date, several cell proliferation markers, apoptosis, vascular markers, oncogenes, tumor suppressor genes, cell cycle mediators, microRNA (miRNAs), and long noncoding RNAs (lncRNAs) have been identified to be involved in the tumorigenesis, migration, proliferation and invasiveness of pituitary adenomas. There are still no reliable morphologic markers predictive of pituitary adenoma recurrence. Recent scientific research introduced new techniques to enable us to attain new information on the genesis and biologic behavior of pituitary adenomas. Areas covered: This review covers selected, compelling and cumulative information in regards to TACSTD family (EpCAM, TROP2), neuropilin (NRP-1), oncogene-induced senescence (OIS), fascins (FSCN1), invasion-associated genes (CLDN7, CNTNAP2, ITGA6, JAM3, PTPRC and CTNNA1) EZH2, and ENC1 genes and endocan. Expert commentary: Ongoing research provides clinicians, surgeons and researchers with new information not only on diverse pathways in tumorigenesis but also on the clinical aggressive behavior of pituitary adenomas. Newly developed molecular techniques, bioinformatics and new pharmaceutical drug options are helpful tools to widen the perspectives in our understanding of the complex nature of pituitary tumorigenesis. The discovery of new molecular biomarkers can only be accomplished by continuing to investigate pituitary embryogenesis, histogenesis and tumorigenesis.


  • ENC1 gene
  • EZH2
  • FSCN1
  • TACSTD family (EpCAM
  • TROP2)
  • endocan
  • invasion-associated genes
  • molecular biomarkers
  • neuropilin (NRP-1)
  • oncogene-induced senescence
  • pituitary adenoma

Identification of genes associated with dissociation of cognitive performance and neuropathological burden: Multistep analysis of genetic, epigenetic, and transcriptional data.

The molecular underpinnings of the dissociation of cognitive performance and neuropathological burden are poorly understood, and there are currently no known genetic or epigenetic determinants of the dissociation. "Residual cognition" was quantified by regressing out the effects of cerebral pathologies and demographic characteristics on global cognitive performance proximate to death. To identify genes influencing residual cognition, we leveraged neuropathological, genetic, epigenetic, and transcriptional data available for deceased participants of the Religious Orders Study (n = 492) and the Rush Memory and Aging Project (n = 487). Given that our sample size was underpowered to detect genome-wide significance, we applied a multistep approach to identify genes influencing residual cognition, based on our prior observation that independent genetic and epigenetic risk factors can converge on the same locus. In the first step (n = 979), we performed a genome-wide association study with a predefined suggestive p < 10-5, and nine independent loci met this threshold in eight distinct chromosomal regions. Three of the six genes within 100 kb of the lead SNP are expressed in the dorsolateral prefrontal cortex (DLPFC): UNC5C, ENC1, and TMEM106B. In the second step, in the subset of participants with DLPFC DNA methylation data (n = 648), we found that residual cognition was related to differential DNA methylation of UNC5C and ENC1 (false discovery rate < 0.05). In the third step, in the subset of participants with DLPFC RNA sequencing data (n = 469), brain transcription levels of UNC5C and ENC1 were evaluated for their association with residual cognition: RNA levels of both UNC5C (estimated effect = -0.40, 95% CI -0.69 to -0.10, p = 0.0089) and ENC1 (estimated effect = 0.0064, 95% CI 0.0033 to 0.0096, p = 5.7 × 10-5) were associated with residual cognition. In secondary analyses, we explored the mechanism of these associations and found that ENC1 may be related to the previously documented effect of depression on cognitive decline, while UNC5C may alter the composition of presynaptic terminals. Of note, the TMEM106B allele identified in the first step as being associated with better residual cognition is in strong linkage disequilibrium with rs1990622A (r2 = 0.66), a previously identified protective allele for TDP-43 proteinopathy. Limitations include the small sample size for the genetic analysis, which was underpowered to detect genome-wide significance, the evaluation being limited to a single cortical region for epigenetic and transcriptomic data, and the use of categorical measures for certain non-amyloid-plaque, non-neurofibrillary-tangle neuropathologies. Through a multistep analysis of cognitive, neuropathological, genomic, epigenomic, and transcriptomic data, we identified ENC1 and UNC5C as genes with convergent genetic, epigenetic, and transcriptomic evidence supporting a potential role in the dissociation of cognition and neuropathology in an aging population, and we expanded our understanding of the TMEM106B haplotype that is protective against TDP-43 proteinopathy.

MeSH Terms

  • Aged
  • Aged, 80 and over
  • Aging
  • Alleles
  • Alzheimer Disease
  • Brain
  • Cognition
  • Cognition Disorders
  • DNA Methylation
  • Depression
  • Epigenesis, Genetic
  • Female
  • Genome-Wide Association Study
  • Genotype
  • Humans
  • Linkage Disequilibrium
  • Male
  • Membrane Proteins
  • Memory
  • Microfilament Proteins
  • Nerve Tissue Proteins
  • Netrin Receptors
  • Neuropeptides
  • Nuclear Proteins
  • Polymorphism, Single Nucleotide
  • RNA
  • Receptors, Cell Surface
  • TDP-43 Proteinopathies