Lipidomic profiling of human serum enables detection of pancreatic cancer.
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ABSTRACT:
SUBMITTER: Wolrab D
PROVIDER: S-EPMC8748654 | biostudies-literature |
REPOSITORIES: biostudies-literature
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| S-EPMC8780681 | biostudies-literature
Project description:Aims/hypothesisThe molecular response and function of pancreatic islet cells during metabolic stress is a complex process. The anatomical location and small size of pancreatic islets coupled with current methodological limitations have prevented the achievement of a complete, coherent picture of the role that lipids and proteins play in cellular processes under normal conditions and in diseased states. Herein, we describe the development of untargeted tissue imaging mass spectrometry (IMS) technologies for the study of in situ protein and, more specifically, lipid distributions in murine and human pancreases.MethodsWe developed matrix-assisted laser desorption/ionisation (MALDI) IMS protocols to study metabolite, lipid and protein distributions in mouse (wild-type and ob/ob mouse models) and human pancreases. IMS allows for the facile discrimination of chemically similar lipid and metabolite isoforms that cannot be distinguished using standard immunohistochemical techniques. Co-registration of MS images with immunofluorescence images acquired from serial tissue sections allowed accurate cross-registration of cell types. By acquiring immunofluorescence images first, this serial section approach guides targeted high spatial resolution IMS analyses (down to 15 μm) of regions of interest and leads to reduced time requirements for data acquisition.ResultsMALDI IMS enabled the molecular identification of specific phospholipid and glycolipid isoforms in pancreatic islets with intra-islet spatial resolution. This technology shows that subtle differences in the chemical structure of phospholipids can dramatically affect their distribution patterns and, presumably, cellular function within the islet and exocrine compartments of the pancreas (e.g. 18:1 vs 18:2 fatty acyl groups in phosphatidylcholine lipids). We also observed the localisation of specific GM3 ganglioside lipids [GM3(d34:1), GM3(d36:1), GM3(d38:1) and GM3(d40:1)] within murine islet cells that were correlated with a higher level of GM3 synthase as verified by immunostaining. However, in human pancreas, GM3 gangliosides were equally distributed in both the endocrine and exocrine tissue, with only one GM3 isoform showing islet-specific localisation.Conclusions/interpretationThe development of more complete molecular profiles of pancreatic tissue will provide important insight into the molecular state of the pancreas during islet development, normal function, and diseased states. For example, this study demonstrates that these results can provide novel insight into the potential signalling mechanisms involving phospholipids and glycolipids that would be difficult to detect by targeted methods, and can help raise new hypotheses about the types of physiological control exerted on endocrine hormone-producing cells in islets. Importantly, the in situ measurements afforded by IMS do not require a priori knowledge of molecules of interest and are not susceptible to the limitations of immunohistochemistry, providing the opportunity for novel biomarker discovery. Notably, the presence of multiple GM3 isoforms in mouse islets and the differential localisation of lipids in human tissue underscore the important role these molecules play in regulating insulin modulation and suggest species, organ, and cell specificity. This approach demonstrates the importance of both high spatial resolution and high molecular specificity to accurately survey the molecular composition of complex, multi-functional tissues such as the pancreas.
| S-EPMC6553460 | biostudies-literature
Project description:Serum-biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations.Eighty-three circulating proteins were analyzed in sera of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC, n = 333), benign pancreatic conditions (n = 144), and healthy control individuals (n = 227). Samples from each group were split randomly into training and blinded validation sets prior to analysis. A Metropolis algorithm with Monte Carlo simulation (MMC) was used to identify discriminatory biomarker panels in the training set. Identified panels were evaluated in the validation set and in patients diagnosed with colon (n = 33), lung (n = 62), and breast (n = 108) cancers.Several robust profiles of protein alterations were present in sera of PDAC patients compared to the Healthy and Benign groups. In the training set (n = 160 PDAC, 74 Benign, 107 Healthy), the panel of CA 19-9, ICAM-1, and OPG discriminated PDAC patients from Healthy controls with a sensitivity/specificity (SN/SP) of 88/90%, while the panel of CA 19-9, CEA, and TIMP-1 discriminated PDAC patients from Benign subjects with an SN/SP of 76/90%. In an independent validation set (n = 173 PDAC, 70 Benign, 120 Healthy), the panel of CA 19-9, ICAM-1 and OPG demonstrated an SN/SP of 78/94% while the panel of CA19-9, CEA, and TIMP-1 demonstrated an SN/SP of 71/89%. The CA19-9, ICAM-1, OPG panel is selective for PDAC and does not recognize breast (SP = 100%), lung (SP = 97%), or colon (SP = 97%) cancer.The PDAC-specific biomarker panels identified in this investigation warrant additional clinical validation to determine their role in screening targeted high-risk populations.
| S-EPMC3075824 | biostudies-literature
Project description:Radiation biodosimeters are required urgently for fast and accurate evaluation of absorbed dose for irradiated individuals. Lipidomics has appeared as a credible technique for identification and quantification of lipid for researching biomarker of diseases. We performed a lipidomic profile on mice serum at time points of 6, 24, and 72 hours after 0, 2, 5.5, 7, and 8 Gy irradiation to select radiation-responsive lipids and conducted Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis to recognize the pathways and network changes. Then, Pearson correlation analysis was performed to evaluate the feasibility of radiation-responsive lipids to estimate radiation dose. Seven radiation-responsive lipids including PC (18:2/18:2), PC (18:0/18:2), Lyso PC 18:1, PC (18:0/20:4), SM (D18:0/24:1), PC (16:0/18:1), and Lyso PC 18:2 were identified in which glycerophospholipid metabolism presented as the most significant pathway, and they all presented good linear correlation with the irradiated dose. This study identified 7 radiation-responsive lipids in mice serum and certificate their feasibility of dose estimation as biodosimeters.
| S-EPMC7180312 | biostudies-literature
Project description:There is a wide variety of extracellular vesicles (EVs) that differ in size and cargo composition. EVs isolated from human plasma or serum carry lipid, protein, and RNA cargo that provides insights to the regulation of normal physiological processes, and to pathological states. Specific populations of EVs have been proposed to contain protein and RNA cargo that are biomarkers for neurologic and systemic diseases. Although there is a considerable amount of evidence that circulating lipids are biomarkers for multiple disease states, it not clear if these lipid biomarkers are enriched in EVs, or if specific populations of EVs are enriched for particular classes of lipid. A highly reproducible workflow for the analysis of lipid content in EVs isolated from human plasma or serum would facilitate this area of research. Here we optimized an MS/MSALL workflow for the untargeted analysis of the lipid content in EVs isolated from human serum. A simple sequential ultracentrifugation protocol isolated three distinct types of serum EVs that were identified based on size, targeted protein, and untargeted lipidomic analyses. EVs in the upper and middle fractions were approximately 140 nm in diameter, while EVs in the pellet were approximately 110 nm in diameter. EVs in the upper most buoyant fractions contained the highest concentration of lipids, were enriched with phospholipids, and immunopositive for the cytoskeletal markers actin, α-actinin, and the mitochondrial protein mitofillin, but negative for the typical EV markers CD63, TSG101, and flotillin. A central fraction of EVs was devoid of cytoskeletal and mitochondrial markers, and positive for CD63, and TSG101, but negative for flotillin. The EV pellet contained no cytoskeletal or mitochondrial markers, but was positive for CD63, TSG101, and flotillin. The EV pellet contained the lowest concentration of most lipids, but was enriched with ceramide. These results provided new insights into the lipid composition of EVs isolated from serum using a simple ultracentrifugation isolation method suitable for lipidomic analysis by mass spectrometry.
| S-EPMC6769212 | biostudies-literature
Project description:While the link between serum proteins and cancer has been studied in an effort to enable early-stage cancer detection, factors that might perturb this link has been poorly understood. To ask this question, we performed serum protein profiling on a prospective cohort of 601 individuals with or without lung, pancreatic, or colorectal cancers and identified ten distinct serum protein signatures with distinct link to the patient metadata. Importantly, we discovered that a positive history of alcohol consumption is a major factor that diminishes the sensitivity of serum protein-mediated liquid biopsy in early-stage malignancies, resulting in a 44% decline in the sensitivity of detecting American Joint Committee on Cancer (AJCC) stage I malignancies. Our data provide evidence that patient lifestyle can affect the sensitivity of liquid biopsy and suggest the potential need for abstinence from alcohol before measurement during serum protein-based cancer screening.
| S-EPMC9794896 | biostudies-literature
Project description:BackgroundThe aim of this study was to investigate the use of podocalyxin (PODXL) and secretoglobin family 1D, member 2 (SCGB1D2) expressions in whole blood as diagnostic biomarkers to distinguish between patients with pancreatic cancer and control participants, in comparison with serum cancer antigen 19-9 (CA19-9), which is the current clinical standard.Patients and methodsFlow cytometric analysis was performed to determine the expressions of PODXL and SCGB1D2 on the surface of cultured pancreatic cancer cells. Immunoblotting was performed to determine whether PODXL and SCGB1D2 were detectable in the media of cultured pancreatic cancer cells. A discovery-stage clinical study was performed in a cohort of 23 patients with pancreatic cancer and 51 control individuals without pancreatic disease who had been treated in the Department of Gastroenterology and Hepatology at Kochi Medical School Hospital from April 2014 to January 2016. Serum PODXL and SCGB1D2 levels were measured by enzyme-linked immunosorbent assay (ELISA).ResultsPODXL and SCGB1D2 accumulated in the protrusions of cultured pancreatic cancer cells, and they were detectable both on the cell surface and in the cultured media from these cells. The discovery-stage clinical study showed that the area under the receiver-operating characteristic curve (AUC) was 0.96 (95% confidence interval [CI] 0.91-1.000) for PODXL, 0.80 (95% CI 0.67-0.94) for SCGB1D2, and 0.78 (95% CI 0.66-0.90) for CA19-9. The AUC for PODXL was thus significantly higher than that for CA19-9 (P = 0.006). The combination of SCGB1D2 with CA19-9 did not significantly increase the AUC (0.83; 95% CI 0.70-0.96) compared with the AUC for either SCGB1D2 or CA19-9 alone (P = 0.563).ConclusionPODXL may be a novel, non-invasive diagnostic biomarker for the detection of pancreatic cancer.
| S-EPMC5858829 | biostudies-literature
Project description:This study evaluated the clinical use of serum metabolomics to discriminate malignant cancers including pancreatic cancer (PC) from malignant diseases, such as biliary tract cancer (BTC), intraductal papillary mucinous carcinoma (IPMC), and various benign pancreaticobiliary diseases. Capillary electrophoresismass spectrometry was used to analyze charged metabolites. We repeatedly analyzed serum samples (n = 41) of different storage durations to identify metabolites showing high quantitative reproducibility, and subsequently analyzed all samples (n = 140). Overall, 189 metabolites were quantified and 66 metabolites had a 20% coefficient of variation and, of these, 24 metabolites showed significant differences among control, benign, and malignant groups (p < 0.05; Steel-Dwass test). Four multiple logistic regression models (MLR) were developed and one MLR model clearly discriminated all disease patients from healthy controls with an area under receiver operating characteristic curve (AUC) of 0.970 (95% confidential interval (CI), 0.946-0.994, p < 0.0001). Another model to discriminate PC from BTC and IPMC yielded AUC = 0.831 (95% CI, 0.650-1.01, p = 0.0020) with higher accuracy compared with tumor markers including carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), pancreatic cancer-associated antigen (DUPAN2) and s-pancreas-1 antigen (SPAN1). Changes in metabolomic profiles might be used to screen for malignant cancers as well as to differentiate between PC and other malignant diseases.
| S-EPMC5412351 | biostudies-literature
Project description:Background:Detection of circulating tumor DNA can be limited due to their relative scarcity in circulation, particularly while patients are actively undergoing therapy. Exosomes provide a vehicle through which cancer-specific material can be enriched from the compendium of circulating non-neoplastic tissue-derived nucleic acids. We carried out a comprehensive profiling of the pancreatic ductal adenocarcinoma (PDAC) exosomal 'surfaceome' in order to identify surface proteins that will render liquid biopsies amenable to cancer-derived exosome enrichment for downstream molecular profiling. Patients and methods:Surface exosomal proteins were profiled in 13 human PDAC and 2 non-neoplastic cell lines by liquid chromatography-mass spectrometry. A total of 173 prospectively collected blood samples from 103 PDAC patients underwent exosome isolation. Droplet digital PCR was used on 74 patients (136 total exosome samples) to determine baseline KRAS mutation call rates while patients were on therapy. PDAC-specific exosome capture was then carried out on additional 29 patients (37 samples) using an antibody cocktail directed against selected proteins, followed by droplet digital PCR analysis. Exosomal DNA in a PDAC patient resistant to therapy were profiled using a molecular barcoded, targeted sequencing panel to determine the utility of enriched nucleic acid material for comprehensive molecular analysis. Results:Proteomic analysis of the exosome 'surfaceome' revealed multiple PDAC-specific biomarker candidates: CLDN4, EPCAM, CD151, LGALS3BP, HIST2H2BE, and HIST2H2BF. KRAS mutations in total exosomes were detected in 44.1% of patients undergoing active therapy compared with 73.0% following exosome capture using the selected biomarkers. Enrichment of exosomal cargo was amenable to molecular profiling, elucidating a putative mechanism of resistance to PARP inhibitor therapy in a patient harboring a BRCA2 mutation. Conclusion:Exosomes provide unique opportunities in the context of liquid biopsies for enrichment of tumor-specific material in circulation. We present a comprehensive surfaceome characterization of PDAC exosomes which allows for capture and molecular profiling of tumor-derived DNA.
| S-EPMC6248757 | biostudies-literature
Project description:This study conducted comprehensive and comparative metabolic and lipidomic profiling of a human epithelial breast cell line (MCF-10A), a slightly metastatic (MCF-7), and a highly metastatic (MDA-MB-231) breast cancer cell line using gas chromatography mass spectrometry (GC-MS) and direct infusion mass spectrometry (DI-MS). Among 39 metabolites identified by GC-MS analysis, xanthine, glucose-6-phosphate, mannose-6-phosphate, guanine, and adenine were selected as prognostic markers of breast cancer metastasis. Major metabolic pathways involved in differentiation of the cell lines were alanine, aspartate, and glutamate metabolism, purine metabolism and glycine, serine, and threonine metabolism. Among 44 intact lipid species identified by DI-MS analysis, the levels of most phospholipids were higher in both metastatic groups than in normal cells. Specifically, the levels of phosphatidylserine (PS) 18:0/20:4, phosphatidylinositol (PI) 18:0/20:4, and phosphatidylcholine (PC) 18:0/20:4 were markedly higher while those of phosphatidylethanolamine (PE) 18:1/18:1 and PI 18:0/18:1 were lower in MDA-MB-231 cells than in MCF-7 cells. A partial-least-squares regression model was developed and validated for predicting the metastatic potential of breast cancer cells. The information obtained in this study will be useful when developing diagnostic tools and for identifying potential therapeutic targets for metastatic breast cancer.
| S-EPMC5341861 | biostudies-literature