Metabolomics for early pancreatic cancer detection in plasma samples from a Swedish prospective population-based biobank.

Background: Pancreatic ductal adenocarcinoma (pancreatic cancer) is often detected at late stages resulting in poor overall survival. To improve survival, more patients need to be diagnosed early when curative surgery is feasible. We aimed to identify circulating metabolites that could be used as early pancreatic cancer biomarkers. Methods: We performed metabolomics by liquid and gas chromatography-mass spectrometry in plasma samples from 82 future pancreatic cancer patients and 82 matched healthy controls within the Northern Sweden Health and Disease Study (NSHDS). Logistic regression was used to assess univariate associations between metabolites and pancreatic cancer risk. Least absolute shrinkage and selection operator (LASSO) logistic regression was used to design a metabolite-based risk score. We used receiver operating characteristic (ROC) analyses to assess the discriminative performance of the metabolite-based risk score. Results: Among twelve risk-associated metabolites with a nominal P value <0.05, we defined a risk score of three metabolites [indoleacetate, 3-hydroxydecanoate (10:0-OH), and retention index (RI): 2,745.4] using LASSO. A logistic regression model containing these three metabolites, age, sex, body mass index (BMI), smoking status, sample date, fasting status, and carbohydrate antigen 19-9 (CA 19-9) yielded an internal area under curve (AUC) of 0.784 [95% confidence interval (CI): 0.714-0.854] compared to 0.681 (95% CI: 0.597-0.764) for a model without these metabolites (P value =0.007). Seventeen metabolites were significantly associated with pancreatic cancer survival [false discovery rate (FDR) <0.1]. Conclusions: Indoleacetate, 3-hydroxydecanoate (10:0-OH), and RI: 2,745.4 were identified as the top candidate biomarkers for early detection. However, continued efforts are warranted to determine the usefulness of these metabolites as early pancreatic cancer biomarkers.

Bioinformatics analysis of miRNAs in the neuroblastoma 11q-deleted region reveals a role of miR-548l in both 11q-deleted and MYCN amplified tumour cells.

Neuroblastoma is a childhood tumour that is responsible for approximately 15% of all childhood cancer deaths. Neuroblastoma tumours with amplification of the oncogene MYCN are aggressive, however, another aggressive subgroup without MYCN amplification also exists; rather, they have a deleted region at chromosome arm 11q. Twenty-six miRNAs are located within the breakpoint region of chromosome 11q and have been checked for a possible involvement in development of neuroblastoma due to the genomic alteration. Target genes of these miRNAs are involved in pathways associated with cancer, including proliferation, apoptosis and DNA repair. We could show that miR-548l found within the 11q region is downregulated in neuroblastoma cell lines with 11q deletion or MYCN amplification. In addition, we showed that the restoration of miR-548l level in a neuroblastoma cell line led to a decreased proliferation of these cells as well as a decrease in the percentage of cells in the S phase. We also found that miR-548l overexpression suppressed cell viability and promoted apoptosis, while miR-548l knockdown promoted cell viability and inhibited apoptosis in neuroblastoma cells. Our results indicate that 11q-deleted neuroblastoma and MYCN amplified neuroblastoma coalesce by downregulating miR-548l.

Circulating Tissue Polypeptide-Specific Antigen in Pre-Diagnostic Pancreatic Cancer Samples.

Early detection of pancreatic ductal adenocarcinoma (PDAC) is challenging, and late diagnosis partly explains the low 5-year survival. Novel and sensitive biomarkers are needed to enable early PDAC detection and improve patient outcomes. Tissue polypeptide specific antigen (TPS) has been studied as a biomarker in PDAC diagnostics, and it has previously been shown to reflect clinical status better than the 'golden standard' biomarker carbohydrate antigen 19-9 (CA 19-9) that is most widely used in the clinical setting. In this cross-sectional case-control study using pre-diagnostic plasma samples, we aim to evaluate the potential of TPS as a biomarker for early PDAC detection. Furthermore, in a subset of individuals with multiple samples available at different time points before diagnosis, a longitudinal analysis was used. We assessed plasma TPS levels using enzyme-linked immunosorbent assay (ELISA) in 267 pre-diagnostic PDAC plasma samples taken up to 18.8 years before clinical PDAC diagnosis and in 320 matched healthy controls. TPS levels were also assessed in 25 samples at PDAC diagnosis. Circulating TPS levels were low both in pre-diagnostic samples of future PDAC patients and in healthy controls, whereas TPS levels at PDAC diagnosis were significantly increased (odds ratio 1.03; 95% confidence interval: 1.01-1.05) in a logistic regression model adjusted for age. In conclusion, TPS levels increase late in PDAC progression and hold no potential as a biomarker for early detection.

Comparison of Skimmed Milk and Lanthanum Flocculation for Concentration of Pathogenic Viruses in Water.

Concentration of viruses in water is necessary for detection and quantification of the viruses present, in order to evaluate microbiological barriers in water treatment plants and detect pathogenic viruses during waterborne outbreaks, but there is currently no standardised procedure. In this study, we implemented a previously described fast and simple lanthanum-based protocol for concentration of norovirus genogroup I (GI), genogroup II (GII) and hepatitis A virus (HAV) in drinking and surface water. We compared the results with those of a widely used skimmed milk flocculation method, followed by nucleic acid extraction and RT-qPCR detection. Three seeding levels, with intended concentrations 5 × 103, 5 × 104 and 5 × 105 genome copies/10 L, were added to drinking water or surface water. All seed levels were detected with both flocculation methods. Samples extracted with skimmed milk flocculation had on average 1.82, 1.86 and 1.38 times higher measured concentration of norovirus GI, GII and HAV, respectively, than those extracted with lanthanum flocculation, across all seeding levels and water types tested. Mengovirus was used as a positive process control. Mengovirus recovery was higher for skimmed milk (40.7% in drinking water, 26.0% in surface water) than for lanthanum flocculation (24.4% in drinking water, 9.7% in surface water). Together, this indicates that skimmed milk flocculation provides higher viral recovery than lanthanum flocculation. However, lanthanum-based flocculation can be performed much faster than skimmed milk flocculation (1.5 h versus 16 h flocculation time) and thus could be a good alternative for rapid monitoring of viruses in water.

miRFA: an automated pipeline for microRNA functional analysis with correlation support from TCGA and TCPA expression data in pancreatic cancer.

BACKGROUND: MicroRNAs (miRNAs) are small RNAs that regulate gene expression at a post-transcriptional level and are emerging as potentially important biomarkers for various disease states, including pancreatic cancer. In silico-based functional analysis of miRNAs usually consists of miRNA target prediction and functional enrichment analysis of miRNA targets. Since miRNA target prediction methods generate a large number of false positive target genes, further validation to narrow down interesting candidate miRNA targets is needed. One commonly used method correlates miRNA and mRNA expression to assess the regulatory effect of a particular miRNA. The aim of this study was to build a bioinformatics pipeline in R for miRNA functional analysis including correlation analyses between miRNA expression levels and its targets on mRNA and protein expression levels available from the cancer genome atlas (TCGA) and the cancer proteome atlas (TCPA). TCGA-derived expression data of specific mature miRNA isoforms from pancreatic cancer tissue was used. RESULTS: Fifteen circulating miRNAs with significantly altered expression levels detected in pancreatic cancer patients were queried separately in the pipeline. The pipeline generated predicted miRNA target genes, enriched gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes (KEGG) pathways. Predicted miRNA targets were evaluated by correlation analyses between each miRNA and its predicted targets. MiRNA functional analysis in combination with Kaplan-Meier survival analysis suggest that hsa-miR-885-5p could act as a tumor suppressor and should be validated as a potential prognostic biomarker in pancreatic cancer. CONCLUSIONS: Our miRNA functional analysis (miRFA) pipeline can serve as a valuable tool in biomarker discovery involving mature miRNAs associated with pancreatic cancer and could be developed to cover additional cancer types. Results for all mature miRNAs in TCGA pancreatic adenocarcinoma dataset can be studied and downloaded through a shiny web application at https://emmbor.shinyapps.io/mirfa/ .

Accounting for Bacterial Overlap Between Raw Water Communities and Contaminating Sources Improves the Accuracy of Signature-Based Microbial Source Tracking.

Microbial source tracking (MST) analysis is essential to identifying and mitigating the fecal pollution of water resources. The signature-based MST method uses a library of sequences to identify contaminants based on operational taxonomic units (OTUs) that are unique to a certain source. However, no clear guidelines for how to incorporate OTU overlap or natural variation in the raw water bacterial community into MST analyses exist. We investigated how the inclusion of bacterial overlap between sources in the library affects source prediction accuracy. To achieve this, large-scale sampling - including feces from seven species, raw sewage, and raw water samples from water treatment plants - was followed by 16S rRNA amplicon sequencing. The MST library was defined using three settings: (i) no raw water communities represented; (ii) raw water communities selected through clustering analysis; and (iii) local water communities collected across consecutive years. The results suggest that incorporating either the local background or representative bacterial composition improves MST analyses, as the results were positively correlated to measured levels of fecal indicator bacteria and the accuracy at which OTUs were assigned to the correct contamination source increased fourfold. Using the proportion of OTUs with high source origin probability, underpinning a contaminating signal, is a solid foundation in a framework for further deciphering and comparing contaminating signals derived in signature-based MST approaches. In conclusion, incorporating background bacterial composition of water in MST can improve mitigation efforts for minimizing the spread of pathogenic and antibiotic resistant bacteria into essential freshwater resources.

Improved Detection of Norovirus and Hepatitis A Virus in Surface Water by Applying Pre-PCR Processing.

Quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) detection of waterborne RNA viruses generally requires concentration of large water volumes due to low virus levels. A common approach is to use dead-end ultrafiltration followed by precipitation with polyethylene glycol. However, this procedure often leads to the co-concentration of PCR inhibitors that impairs the limit of detection and causes false-negative results. Here, we applied the concept of pre-PCR processing to optimize RT-qPCR detection of norovirus genogroup I (GI), genogroup II (GII), and hepatitis A virus (HAV) in challenging water matrices. The RT-qPCR assay was improved by screening for an inhibitor-tolerant master mix and modifying the primers with twisted intercalating nucleic acid molecules. Additionally, a modified protocol based on chaotropic lysis buffer and magnetic silica bead nucleic acid extraction was developed for complex water matrices. A validation of the modified extraction protocol on surface and drinking waters was performed. At least a 26-fold improvement was seen in the most complex surface water studied. The modified protocol resulted in average recoveries of 33, 13, 8, and 4% for mengovirus, norovirus GI, GII, and HAV, respectively. The modified protocol also improved the limit of detection for norovirus GI and HAV. RT-qPCR inhibition with C q shifts of 1.6, 2.8, and 3.5 for norovirus GI, GII, and HAV, respectively, obtained for the standard nucleic acid extraction were completely eliminated by the modified protocol. The standard nucleic acid extraction method worked well on drinking water with no RT-qPCR inhibition observed and average recoveries of 80, 124, 89, and 32% for mengovirus, norovirus GI, GII, and HAV, respectively.