Serum biomarker-based early detection of pancreatic ductal adenocarcinomas with ensemble learning.

BACKGROUND: Earlier detection of pancreatic ductal adenocarcinoma (PDAC) is key to improving patient outcomes, as it is mostly detected at advanced stages which are associated with poor survival. Developing non-invasive blood tests for early detection would be an important breakthrough. METHODS: The primary objective of the work presented here is to use a dataset that is prospectively collected, to quantify a set of cancer-associated proteins and construct multi-marker models with the capacity to predict PDAC years before diagnosis. The data used is part of a nested case-control study within the UK Collaborative Trial of Ovarian Cancer Screening and is comprised of 218 samples, collected from a total of 143 post-menopausal women who were diagnosed with pancreatic cancer within 70 months after sample collection, and 249 matched non-cancer controls. We develop a stacked ensemble modelling technique to achieve robustness in predictions and, therefore, improve performance in newly collected datasets. RESULTS: Here we show that with ensemble learning we can predict PDAC status with an AUC of 0.91 (95% CI 0.75-1.0), sensitivity of 92% (95% CI 0.54-1.0) at 90% specificity, up to 1 year prior to diagnosis, and at an AUC of 0.85 (95% CI 0.74-0.93) up to 2 years prior to diagnosis (sensitivity of 61%, 95% CI 0.17-0.83, at 90% specificity). CONCLUSIONS: The ensemble modelling strategy explored here outperforms considerably biomarker combinations cited in the literature. Further developments in the selection of classifiers balancing performance and heterogeneity should further enhance the predictive capacity of the method.

Pancreatic cancers are most frequently detected at an advanced stage. This limits treatment options and contributes to the dismal survival rates currently recorded. The development of new tests that could improve detection of early-stage disease is fundamental to improve outcomes. Here, we use advanced data analysis techniques to devise an early detection test for pancreatic cancer. We use data on markers in the blood from people enrolled on a screening trial. Our test correctly identifies as positive for pancreatic cancer 91% of the time up to 1 year prior to diagnosis, and 78% of the time up to 2 years prior to diagnosis. These results surpass previously reported tests and should encourage further evaluation of the test in different populations, to see whether it should be adopted in the clinic.

Intracellular Chloride Channels Regulate Endothelial Metabolic Reprogramming in Pulmonary Arterial Hypertension.

Mitochondrial fission and a metabolic switch from oxidative phosphorylation to glycolysis are key features of vascular pathology in pulmonary arterial hypertension (PAH) and are associated with exuberant endothelial proliferation and apoptosis. The underlying mechanisms are poorly understood. We describe the contribution of two intracellular chloride channel proteins, CLIC1 and CLIC4, both highly expressed in PAH and cancer, to mitochondrial dysfunction and energy metabolism in PAH endothelium. Pathological overexpression of CLIC proteins induces mitochondrial fragmentation, inhibits mitochondrial cristae formation, and induces metabolic shift toward glycolysis in human pulmonary artery endothelial cells, consistent with changes observed in patient-derived cells. Interactions of CLIC proteins with structural components of the inner mitochondrial membrane offer mechanistic insights. Endothelial CLIC4 excision and mitofusin 2 supplementation have protective effects in human PAH cells and preclinical PAH. This study is the first to demonstrate the key role of endothelial intracellular chloride channels in the regulation of mitochondrial structure, biogenesis, and metabolic reprogramming in expression of the PAH phenotype.

The postprandial secretion of peptide YY1-36 and 3-36 in obesity is differentially increased after gastric bypass versus sleeve gastrectomy.

OBJECTIVES: Peptide tyrosine tyrosine (PYY) exists as two species, PYY1-36 and PYY3-36 , with distinct effects on insulin secretion and appetite regulation. The detailed effects of bariatric surgery on PYY1-36 and PYY3-36 secretion are not known as previous studies have used nonspecific immunoassays to measure total PYY. Our objective was to characterize the effect of sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB) on fasting and postprandial PYY1-36 and PYY3-36 secretion using a newly developed liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay. DESIGN AND SUBJECTS: Observational study in 10 healthy nonobese volunteers and 30 participants with obesity who underwent RYGB (n = 24) or SG (n = 6) at the Imperial Weight Centre [NCT01945840]. Participants were studied using a standardized mixed meal test (MMT) before and 1 year after surgery. The outcome measures were PYY1-36 and PYY3-36 concentrations. RESULTS: Presurgery, the fasting and postprandial levels of PYY1-36 and PYY3-36 were low, with minimal responses to the MMT, and these did not differ from healthy nonobese volunteers. The postprandial secretion of both PYY1-36 and PYY3-36 at 1 year was amplified after RYGB, but not SG, with the response being significantly higher in RYGB compared with SG. CONCLUSIONS: There appears to be no difference in PYY secretion between nonobese and obese volunteers at baseline. At 1 year after surgery, RYGB, but not SG, is associated with increased postprandial secretion of PYY1-36 and PYY3-36 , which may account for long-term differences in efficacy and adverse effects between the two types of surgery.

Non-Histone Protein Methylation: Biological Significance and Bioengineering Potential.

Protein methylation is a key post-translational modification whose effects on gene expression have been intensively studied over the last two decades. Recently, renewed interest in non-histone protein methylation has gained momentum for its role in regulating important cellular processes and the activity of many proteins, including transcription factors, enzymes, and structural complexes. The extensive and dynamic role that protein methylation plays within the cell also highlights its potential for bioengineering applications. Indeed, while synthetic histone protein methylation has been extensively used to engineer gene expression, engineering of non-histone protein methylation has not been fully explored yet. Here, we report the latest findings, highlighting how non-histone protein methylation is fundamental for certain cellular functions and is implicated in disease, and review recent efforts in the engineering of protein methylation.

Improved early detection of ovarian cancer using longitudinal multimarker models.

BACKGROUND: Ovarian cancer has a poor survival rate due to late diagnosis and improved methods are needed for its early detection. Our primary objective was to identify and incorporate additional biomarkers into longitudinal models to improve on the performance of CA125 as a first-line screening test for ovarian cancer. METHODS: This case-control study nested within UKCTOCS used 490 serial serum samples from 49 women later diagnosed with ovarian cancer and 31 control women who were cancer-free. Proteomics-based biomarker discovery was carried out using pooled samples and selected candidates, including those from the literature, assayed in all serial samples. Multimarker longitudinal models were derived and tested against CA125 for early detection of ovarian cancer. RESULTS: The best performing models, incorporating CA125, HE4, CHI3L1, PEBP4 and/or AGR2, provided 85.7% sensitivity at 95.4% specificity up to 1 year before diagnosis, significantly improving on CA125 alone. For Type II cases (mostly high-grade serous), models achieved 95.5% sensitivity at 95.4% specificity. Predictive values were elevated earlier than CA125, showing the potential of models to improve lead time. CONCLUSIONS: We have identified candidate biomarkers and tested longitudinal multimarker models that significantly improve on CA125 for early detection of ovarian cancer. These models now warrant independent validation.

HiLight-PTM: an online application to aid matching peptide pairs with isotopically labelled PTMs.

MOTIVATION: Database searching of isotopically labelled PTMs can be problematic and we frequently find that only one, or neither in a heavy/light pair are assigned. In such cases, having a pair of MS/MS spectra that differ due to an isotopic label can assist in identifying the relevant m/z values that support the correct peptide annotation or can be used for de novo sequencing. RESULTS: We have developed an online application that identifies matching peaks and peaks differing by the appropriate mass shift (difference between heavy and light PTM) between two MS/MS spectra. Furthermore, the application predicts, from the exact-match peaks, the mass of their complementary ions and highlights these as high confidence matches between the two spectra. The result is a tool to visually compare two spectra, and downloadable peaks lists that can be used to support de novo sequencing. AVAILABILITY AND IMPLEMENTATION: HiLight-PTM is released using shinyapps.io by RStudio, and can be accessed from any internet browser at https://harrywhitwell.shinyapps.io/hilight-ptm/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Parenclitic networks for predicting ovarian cancer.

Prediction and diagnosis of complex disease may not always be possible with a small number of biomarkers. Modern 'omics' technologies make it possible to cheaply and quantitatively assay hundreds of molecules generating large amounts of data from individual samples. In this study, we describe a parenclitic network-based approach to disease classification using a synthetic data set modelled on data from the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) and serological assay data from a nested set of samples from the same study. This approach allows us to integrate quantitative proteomic and categorical metadata into a single network, and then use network topologies to construct logistic regression models for disease classification. In this study of ovarian cancer, comprising of 30 controls and cases with samples taken <14 months to diagnosis (n = 30) and/or >34 months to diagnosis (n = 29), we were able to classify cases with a sensitivity of 80.3% within 14 months of diagnosis and 18.9% in samples exceeding 34 months to diagnosis at a specificity of 98%. Furthermore, we use the networks to make observations about proteins within the cohort and identify GZMH and FGFBP1 as changing in cases (in relation to controls) at time points most distal to diagnosis. We conclude that network-based approaches may offer a solution to the problem of complex disease classification that can be used in personalised medicine and to describe the underlying biology of cancer progression at a system level.

Identification of a serum biomarker panel for the differential diagnosis of cholangiocarcinoma and primary sclerosing cholangitis.

The non-invasive differentiation of malignant and benign biliary disease is a clinical challenge. Carbohydrate antigen 19-9 (CA19-9), leucine-rich α2-glycoprotein (LRG1), interleukin 6 (IL6), pyruvate kinase M2 (PKM2), cytokeratin 19 fragment (CYFRA21.1) and mucin 5AC (MUC5AC) have reported utility for differentiating cholangiocarcinoma (CCA) from benign biliary disease. Herein, serum levels of these markers were tested in 66 cases of CCA and 62 cases of primary sclerosing cholangitis (PSC) and compared with markers of liver function and inflammation. Markers panels were assessed for their ability to discriminate malignant and benign disease. Several of the markers were also assessed in pre-diagnosis biliary tract cancer (BTC) samples with performances evaluated at different times prior to diagnosis. We show that LRG1 and IL6 were unable to accurately distinguish CCA from PSC, whereas CA19-9, PKM2, CYFRA21.1 and MUC5AC were significantly elevated in malignancy. Area under the receiver operating characteristic curves for these individual markers ranged from 0.73-0.84, with the best single marker (PKM2) providing 61% sensitivity at 90% specificity. A panel combining PKM2, CYFRA21.1 and MUC5AC gave 76% sensitivity at 90% specificity, which increased to 82% sensitivity by adding gamma-glutamyltransferase (GGT). In the pre-diagnosis setting, LRG1, IL6 and PKM2 were poor predictors of BTC, whilst CA19-9 and C-reactive protein were elevated up to 2 years before diagnosis. In conclusion, LRG1, IL6 and PKM2 were not useful for early detection of BTC, whilst a model combining PKM2, CYFRA21.1, MUC5AC and GGT was beneficial in differentiating malignant from benign biliary disease, warranting validation in a prospective trial.

Evidence against Stable Protein S-Nitrosylation as a Widespread Mechanism of Post-translational Regulation.

S-nitrosation, commonly referred to as S-nitrosylation, is widely regarded as a ubiquitous, stable post-translational modification that directly regulates many proteins. Such a widespread role would appear to be incompatible with the inherent lability of the S-nitroso bond, especially its propensity to rapidly react with thiols to generate disulfide bonds. As anticipated, we observed robust and widespread protein S-nitrosation after exposing cells to nitrosocysteine or lipopolysaccharide. Proteins detected using the ascorbate-dependent biotin switch method are typically interpreted to be directly regulated by S-nitrosation. However, these S-nitrosated proteins are shown to predominantly comprise transient intermediates leading to disulfide bond formation. These disulfides are likely to be the dominant end effectors resulting from elevations in nitrosating cellular nitric oxide species. We propose that S-nitrosation primarily serves as a transient intermediate leading to disulfide formation. Overall, we conclude that the current widely held perception that stable S-nitrosation directly regulates the function of many proteins is significantly incorrect.

Evidence of Altered Glycosylation of Serum Proteins Prior to Pancreatic Cancer Diagnosis.

Biomarkers for the early detection of pancreatic cancer are urgently needed. The aim of this pilot study was to evaluate changes in serum N-glycoproteins and their glycosylation status prior to clinical presentation of pancreatic cancer that may be potential biomarkers. Prediagnosis serum samples pooled according to five time-to-diagnosis groups and a non-cancer control pool were digested with trypsin, labelled with mass tags, and subjected to titanium dioxide capture, deglycosylation, and 2D-LC-MS/MS profiling. Unbound peptides were profiled in parallel. Across the sample groups, 703 proteins were quantified and 426 putative sites of N-glycosylation were identified with evidence of several novel sites. Altered proteins with biomarker potential were predominantly abundant inflammatory response, coagulation, and immune-related proteins. Whilst glycopeptide profiles largely paralleled those of their parent proteins, there was evidence of altered N-glycosylation site occupancy or sialic acid content prior to diagnosis for some proteins, most notably of immunoglobulin gamma chains. α-1-Antitrypsin was tested as a biomarker, but found not to complement carbohydrate antigen 19-9 (CA19-9) in early detection of cancer. In conclusion, we provide preliminary evidence of altered glycosylation of several serum proteins prior to pancreatic cancer diagnosis, warranting further investigation of these proteins as early biomarkers. These changes may be largely driven by inflammatory processes that occur in response to tumour formation and progression.

Surfactant Protein-D Is Essential for Immunity to Helminth Infection.

Pulmonary epithelial cell responses can enhance type 2 immunity and contribute to control of nematode infections. An important epithelial product is the collectin Surfactant Protein D (SP-D). We found that SP-D concentrations increased in the lung following Nippostrongylus brasiliensis infection; this increase was dependent on key components of the type 2 immune response. We carried out loss and gain of function studies of SP-D to establish if SP-D was required for optimal immunity to the parasite. N. brasiliensis infection of SP-D-/- mice resulted in profound impairment of host innate immunity and ability to resolve infection. Raising pulmonary SP-D levels prior to infection enhanced parasite expulsion and type 2 immune responses, including increased numbers of IL-13 producing type 2 innate lymphoid cells (ILC2), elevated expression of markers of alternative activation by alveolar macrophages (alvM) and increased production of the type 2 cytokines IL-4 and IL-13. Adoptive transfer of alvM from SP-D-treated parasite infected mice into naïve recipients enhanced immunity to N. brasiliensis. Protection was associated with selective binding by the SP-D carbohydrate recognition domain (CRD) to L4 parasites to enhance their killing by alvM. These findings are the first demonstration that the collectin SP-D is an essential component of host innate immunity to helminths.