Dipeptidyl peptidase 10, a novel prognostic marker in colorectal cancer

Genomic Assessment of Cancer Susceptibility in the Threatened Catalina Island Fox (Urocyon littoralis catalinae)

Small effective population sizes raise the probability of extinction by increasing the frequency of potentially deleterious alleles and reducing fitness. However, the extent to which cancers play a role in the fitness reduction of genetically depauperate wildlife populations is unknown. Santa Catalina island foxes (Urocyon littoralis catalinae) sampled in 2007-2008 have a high prevalence of ceruminous gland tumors, which was not detected in the population prior to a recent bottleneck caused by a canine distemper epidemic. The disease appears to be associated with inflammation from chronic ear mite (Otodectes) infections and secondary elevated levels of Staphyloccus pseudointermedius bacterial infections. However, no other environmental factors to date have been found to be associated with elevated cancer risk in this population. Here, we used whole genome sequencing of the case and control individuals from two islands to identify candidate loci associated with cancer based on genetic divergence, nucleotide diversity, allele frequency spectrum, and runs of homozygosity. We identified several candidate loci based on genomic signatures and putative gene functions, suggesting that cancer susceptibility in this population may be polygenic. Due to the efforts of a recovery program and weak fitness effects of late-onset disease, the population size has increased, which may allow selection to be more effective in removing these presumably slightly deleterious alleles. Long-term monitoring of the disease alleles, as well as overall genetic diversity, will provide crucial information for the long-term persistence of this threatened population.

Integrative computational approach identifies immune-relevant biomarkers in ulcerative colitis

Ulcerative colitis is a common inflammatory bowel disease with a complex genetic and immune etiology. Immune infiltration plays a vital role in the development of ulcerative colitis. To explore potential biomarkers for ulcerative colitis and analyze characteristics of immune cell infiltration, we used bioinformatic analyses, including machine learning algorithms, cell type deconvolution methods, and pathway enrichment methods. In this study, we identified 216 differentially expressed mRNAs (DEMs), of which 153 were upregulated, and 63 were downregulated genes. DEMs were mainly enriched in infiltrating neutrophils and regulation of leukocyte migration. Moreover, eight candidate biomarkers, DPP10, MST1L, DPP10‐AS1, CEP55, ACSL1, MGP, OLFM4, and SGK1, were identified. Of these candidate biomarkers, MST1L, OLFM4, and DPP10 were then validated in the GSE48958 dataset and were predicted to be strongly correlated with infiltrating immune cells of ulcerative colitis. The underlying mechanism of these key genes in the development of colitis was also predicted by gene set variation analysis. To further validate these biomarkers' expression in ulcerative colitis, we determined mRNA levels of SGK1, CEP55, ACSL1, OLFM4, and DPP10 in lipopolysaccharides (LPS)‐stimulated Raw264.7 cells by quantitative reverse transcription‐polymerase chain reaction. We also examined SGK1, CEP55, ACSL1, OLFM4, DPP10, and MGP expression in the colon tissues of dextran sodium sulfate‐induced colitis mice. Consistent with the predicted computational results, the mRNA levels of these candidate genes were markedly changed in LPS‐stimulated Raw264.7 cells and inflamed colon tissues. Hence, our findings indicated that these critical genes may act as diagnostic biomarkers for ulcerative colitis and that differential immune infiltration cells may help illustrate the progression of ulcerative colitis.

Research Progress on Dipeptidyl Peptidase Family: Structure, Function and Xenobiotic Metabolism

Prolyl-specific peptidases or proteases, including Dipeptidyl Peptidase 2, 4, 6, 8, 9, 10, Fibroblast Activation Protein, prolyl endopeptidase and prolyl carboxypeptidase, belong to the dipeptidyl peptidase family. In human physiology and anatomy, they have homology amino acid sequences, similarities in structure, but play distinct functions and roles. Some of them also play important roles in the metabolism of drugs containing endogenous peptides, xenobiotics containing peptides, and exogenous peptides. The major functions of these peptidases in both the metabolism of human health and bioactive peptides are of significant importance in the development of effective inhibitors to control the metabolism of endogenous bioactive peptides. The structural characteristics, distribution of tissue, endogenous substrates, and biological functions were summarized in this review. Furthermore, the xenobiotics metabolism of the dipeptidyl peptidase family is illustrated. All the evidence and information summarized in this review would be very useful for researchers to extend the understanding of the proteins of these families and offer advice and assistance in physiology and pathology studies.

LncRNA DPP10-AS1 promotes malignant processes through epigenetically activating its cognate gene DPP10 and predicts poor prognosis in lung cancer patients

OBJECTIVE

The purpose of this study was to explore the function and gene expression regulation of the newly identified lncRNA DPP10-AS1 in lung cancer, and its potential value as a prognostic biomarker.

METHODS

qRT-PCR and Western blot were conducted to detect the expression of DDP10-AS1 and DPP10 in lung cancer cell lines and tissues. The effects of DDP10-AS1 on DPP10 expression, cell growth, invasion, apoptosis, and in vivo tumor growth were investigated in lung cancer cells by Western blot, rescue experiments, colony formation, flow cytometry, and xenograft animal experiments.

RESULTS

The novel antisense lncRNA DPP10-AS1 was found to be highly expressed in cancer tissues (P < 0.0001), and its upregulation predicted poor prognosis in patients with lung cancer (P = 0.0025). Notably, DPP10-AS1 promoted lung cancer cell growth, colony formation, and cell cycle progression, and repressed apoptosis in lung cancer cells by upregulating DPP10 expression. Additionally, DPP10-AS1 facilitated lung tumor growth via upregulation of DPP10 protein in a xenograft mouse model. Importantly, DPP10-AS1 positively regulated DPP10 gene expression, and both were coordinately upregulated in lung cancer tissues. Mechanically, DPP10-AS1 was found to associate with DPP10 mRNA but did not enhance DPP10 mRNA stability. Hypomethylation of DPP10-AS1 and DPP10 contributed to their coordinate upregulation in lung cancer.

CONCLUSIONS

These findings indicated that the upregulation of the antisense lncRNA DPP10-AS1 promotes lung cancer malignant processes and facilitates tumorigenesis by epigenetically regulating its cognate sense gene DPP10. DPP10-AS1 may serve as a candidate prognostic biomarker and a potential therapeutic target in lung cancer.

Identification of large rearrangements in cancer genomes with barcode linked reads

Large genomic rearrangements involve inversions, deletions and other structural changes that span Megabase segments of the human genome. This category of genetic aberration is the cause of many hereditary genetic disorders and contributes to pathogenesis of diseases like cancer. We developed a new algorithm called ZoomX for analysing barcode-linked sequence reads—these sequences can be traced to individual high molecular weight DNA molecules (>50 kb). To generate barcode linked sequence reads, we employ a library preparation technology (10X Genomics) that uses droplets to partition and barcode DNA molecules. Using linked read data from whole genome sequencing, we identify large genomic rearrangements, typically greater than 200kb, even when they are only present in low allelic fractions. Our algorithm uses a Poisson scan statistic to identify genomic rearrangement junctions, determine counts of junction-spanning molecules and calculate a Fisher's exact test for determining statistical significance for somatic aberrations. Utilizing a well-characterized human genome, we benchmarked this approach to accurately identify large rearrangement. Subsequently, we demonstrated that our algorithm identifies somatic rearrangements when present in lower allelic fractions as occurs in tumors. We characterized a set of complex cancer rearrangements with multiple classes of structural aberrations and with possible roles in oncogenesis.

Genome-wide meta-analysis identifies novel loci associated with parathyroid hormone level

Background

Parathyroid hormone (PTH) is one of the principal regulators of calcium homeostasis. Although serum PTH level is mostly accounted by genetic factors, genetic background underlying PTH level is insufficiently known. Therefore, the aim of this study was to identify novel genetic variants associated with PTH levels.

Methods

We performed GWAS meta-analysis within two genetically isolated Croatian populations followed by replication analysis in a Croatian mainland population and we also combined results across all three analyzed populations. The analyses included 2596 individuals. A total of 7,411,206 variants, imputed using the 1000 Genomes reference panel, were analysed for the association. In addition, a sex-specific GWAS meta-analyses were performed.

Results

Polymorphisms with the lowest P-values were located on chromosome 4 approximately 84 kb of the 5′ of RASGEF1B gene. The most significant SNP was rs11099476 (P = 1.15 × 10⁻⁸). Sex-specific analysis identified genome-wide significant association of the variant rs77178854, located within DPP10 gene in females only (P = 2.21 × 10^− 9). There were no genome-wide significant findings in the meta-analysis of males.

Conclusions

We identified two biologically plausible novel loci associated with PTH levels, providing us with further insights into the genetics of this complex trait.

Electronic supplementary material

The online version of this article (10.1186/s10020-018-0018-5) contains supplementary material, which is available to authorized users.

Identification of novel therapeutic target genes and pathway in pancreatic cancer by integrative analysis

BACKGROUND

Gene alterations are crucial to the molecular pathogenesis of pancreatic cancer. The present study was designed to identify the potential candidate genes in the pancreatic carcinogenesis.

METHODS

Gene Expression Omnibus database (GEO) datasets of pancreatic cancer tissue were retrieval and the differentially expressed genes (DEGs) from individual microarray data were merged. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, protein-protein interaction (PPI) networks, and gene coexpression analysis were performed.

RESULTS

Three GEO datasets, including 74 pancreatic cancer samples and 55 controls samples were selected. A total of 2325 DEGs were identified, including 1383 upregulated and 942 downregulated genes. The GO terms for molecular functions, biological processes, and cellular component were protein binding, small molecule metabolic process, and integral to membrane, respectively. The most significant pathway in KEGG analysis was metabolic pathways. PPI network analysis indicated that the significant hub genes including cytochrome P450, family 2, subfamily E, polypeptide 1 (CYP2E1), mitogen-activated protein kinase 3 (MAPK3), and phospholipase C, gamma 1 (PLCG1). Gene coexpression network analysis identified 4 major modules, and the potassium channel tetramerization domain containing 10 (KCTD10), kin of IRRE like (KIRREL), dipeptidyl-peptidase 10 (DPP10), and unc-80 homolog (UNC80) were the hub gene of each modules, respectively.

CONCLUSION

Our integrative analysis provides a comprehensive view of gene expression patterns associated with the pancreatic carcinogenesis.

Long Noncoding RNA BC032913 as a Novel Therapeutic Target for Colorectal Cancer that Suppresses Metastasis by Upregulating TIMP3

Long noncoding RNAs (lncRNAs) have been shown to play critical roles in the biology of various cancers. However, their expression patterns and biological functions in human colorectal cancer (CRC) remain largely unknown. The aim of this study was to explore lncRNA profiles in CRC and investigate key lncRNAs involved in CRC tumorigenesis and progression. The microarray data of six CRC and matched non-cancerous tissues revealed distinct lncRNA profiles, including 899 upregulated and 1,646 downregulated lncRNAs (p < 0.05, fold change > 2.0). Furthermore, we found that the lncRNA BC032913 was generally underexpressed in 115 CRC samples compared with normal tissues. Reduced BC032913 levels were significantly associated with an advanced tumor, lymph nodes, distant metastasis (TNM) stage and a higher risk of lymph node and distant metastases. BC032913 downregulation indicated poor overall survival in CRC patients. Moreover, BC032913 enhanced the mRNA and protein expression of TIMP3 and inhibited Wnt/β-catenin pathway activity, thus suppressing CRC metastasis in vitro and in vivo. Collectively, the obtained data show that BC032913 plays an inhibitory role in CRC aggression by upregulating TIMP3, followed by inactivation of the Wnt/β-catenin pathway. Our findings indicate that the novel lncRNA BC032913 could serve as a novel prognostic marker and effective therapeutic target for CRC.

Optimization of gold nanoparticle-based real-time colorimetric assay of dipeptidyl peptidase IV activity

Dipeptidyl peptidase IV (DPP-IV also referred to as CD-26) is a serine protease enzyme with remarkable diagnostic and prognostic value in a variety of health and disease conditions. Herein, we describe a simple and real-time colorimetric assay for DPP-IV/CD-26 activity based on the aggregation of gold nanoparticles (AuNPs) functionalized with the peptide substrates: Gly-Pro-Asp-Cys (GPDC) or Val-Pro-ethylene diamine-Asp-Cys (VP-ED-DC). Cleavage of the substrates by DPP-IV resulted in aggregation of the AuNPs with accompanying color change in the solution from red to blue that was monitored using either a UV-visible spectrophotometer or by the naked eye. Factors, such as time course of the reaction, stability of the functionalized AuNPs and the structure of the substrate that influence the cleavage reaction in solution were investigated. The effects of potential interference from serum proteins (lysozyme, thrombin and trypsin) on the analytical response were negligible. The detection limits when GPDC or VP-EN-DC functionalized AuNPs were used for DPP-IV assay were 1.2U/L and 1.5U/L, respectively. The VP-EN-DC method was preferred for the quantitative determination of DPP-IV activity in serum because of its wide linear range 0-30U/L compared to 0-12U/L for the GPDC assay. Recoveries from serum samples spiked with DPP-IV activity, between 5 and 25U/L, and using the VP-EN-DC modified AuNPs method ranged between 83.6% and 114.9%. The two colorimetric biosensors described here are superior to other conventional methods because of their simplicity, stability, selectivity and reliability.

Structure of human dipeptidyl peptidase 10 (DPPY): a modulator of neuronal Kv4 channels

The voltage-gated potassium channel family (Kv) constitutes the most diverse class of ion channels in the nervous system. Dipeptidyl peptidase 10 (DPP10) is an inactive peptidase that modulates the electrophysiological properties, cell-surface expression and subcellular localization of voltage-gated potassium channels. As a consequence, DPP10 malfunctioning is associated with neurodegenerative conditions like Alzheimer and fronto-temporal dementia, making this protein an attractive drug target. In this work, we report the crystal structure of DPP10 and compare it to that of DPP6 and DPP4. DPP10 belongs to the S9B serine protease subfamily and contains two domains with two distinct folds: a β-propeller and a classical α/β-hydrolase fold. The catalytic serine, however, is replaced by a glycine, rendering the protein enzymatically inactive. Difference in the entrance channels to the active sites between DPP10 and DPP4 provide an additional rationale for the lack of activity. We also characterize the DPP10 dimer interface focusing on the alternative approach for designing drugs able to target protein-protein interactions.