10 research outputs found

    Advances and Applications of Antibody Arrays - Proteomic Profiling of Pancreatic Disease

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    Recombinant antibody microarrays have advanced into indispensable tools for large-scale, high-throughput multiplexed serum proteomics. This thesis, based upon five original papers, deals with the development of an in-house designed antibody microarray platform, and its applications for serum profiling of pancreatic disease. Pancreatic cancer is the 4th deadliest cancer, with a 5-year survival rate of only 6%. In order to increase the survival of this deadly disease, novel diagnostic biomarkers for earlier detection will be essential. In paper I and II of this thesis, we identified candidate biomarker signatures for predicting pancreatic cancer among healthy controls and pancreatitis. Pancreatitis (pancreatic inflammation) is symptomatically highly similar to pancreatic cancer, and biomarkers able to discriminate pancreatic cancer from pancreatitis would be of great clinical value. Pancreatitis appears in mainly chronic, acute, and autoimmune manifestations, and like for pancreatic cancer, there is a lack of high-performing biomarkers for diagnosis and stratification. In paper III, we applied antibody microarrays for pancreatitis protein profiling, and presented tentative biomarker signatures for the three main subtypes of this disease. In parallel to performing clinical applications of the antibody microarrays, technical efforts for improving and expanding the use of the platform have also been conducted. In paper IV, we studied the impact of the antibody-surface interplay, and evaluated different solid supports for antibody microarray production. We also took the first steps towards developing a user-friendly ELISA-like multiplexed biomarker assay, by presenting the first plate-based recombinant array-in-well set-up. In paper V, we designed protocols for an increased utility of the antibody microarray platform, to comprise not only targeting of proteins, but also serum/plasma profiling of glycan and carbonyl groups. Post-translational modification of proteins, like glycosylation and carbonylation (oxidation) is often altered in disease, and biomarkers based on differentiated levels of these modifications may complement traditional protein biomarkers. Proof-of-concept was demonstrated for preeclampsia, a common pregnancy disorder, for which the results indicated that particularly the level of carbonylation could be used for diagnosis and stratification. In conclusion, the work in this thesis has contributed to an improved and increased utility of the recombinant antibody microarray technology, and demonstrated its use for serum proteomic profiling of pancreatic disease

    Is lung involvement a favorable prognostic factor for pancreatic ductal adenocarcinoma with synchronous liver metastases?—A propensity score analysis

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    BackgroundFor advanced pancreatic cancer, pulmonary metastases (PM) have been considered favorable factors compared to metastases of other sites, but it remains unknown whether the prognosis of patients with synchronous liver and lung metastases is better than that of non-PM.MethodsData was derived from a two-decade cohort and included 932 cases of pancreatic adenocarcinoma with synchronous liver metastases (PACLM). Propensity score matching (PSM) was applied to balance 360 selected cases, grouped into PM (n = 90) and non-PM (n = 270). Overall survival (OS) and survival-related factors were analyzed.ResultsIn PSM-adjusted data, the median OS was 7.3 and 5.8 months, for PM and non-PM, respectively (p = 0.16). Multivariate analysis revealed that male gender, poor performance status, higher hepatic tumor burden, ascites, elevated carbohydrate antigen 19–9, and lactate dehydrogenase were factors of poor survival (p < 0.05). Chemotherapy was the only independent significant factor of favorable prognosis (p < 0.05).ConclusionAlthough lung involvement was indicated to be a favorable prognostic factor for patients with PACLM in the whole cohort, PM were not associated with better survivals in the subset of cases subjected to PSM adjustment

    Serum proteome profiling of pancreatitis using recombinant antibody microarrays reveals disease-associated biomarker signatures

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    PURPOSE: Pancreatitis is an inflammatory state of the pancreas, for which high-performing serological biomarkers are lacking. The aim of the present study was to evaluate the use of affinity proteomics for identifying potential markers of disease and stratifying pancreatitis subtypes. EXPERIMENTAL DESIGN: High-content, recombinant antibody microarrays were applied for serum protein expression profiling of 113 serum samples from patients with chronic, acute, and autoimmune pancreatitis, as well as healthy controls. The sample groups were compared using supervised classification based on support vector machine analysis. RESULTS: This discovery study showed that pancreatitis subtypes could be discriminated with high accuracy. Using unfiltered data, the individual subtypes, as well as the combined pancreatitis cohort, were distinguished from healthy controls with high AUC values (0.96-1.00). Moreover, characteristic protein patterns and AUC values in the range of 0.69-0.95 were observed for the individual pancreatitis entities when compared to each other, and to all other samples combined. CONCLUSIONS AND CLINICAL RELEVANCE: This study demonstrated the potential of the antibody microarray approach for stratification of pancreatitis. Distinct candidate multiplex serum biomarker signatures for chronic, acute, and autoimmune pancreatitis were defined, which could enhance our fundamental knowledge of the underlying molecular mechanisms, and potentially lead to improved diagnosis

    Identification of serum biomarker signatures associated with pancreatic cancer

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    Pancreatic cancer is an aggressive disease with poor prognosis, due, in part, to the lack of disease-specific biomarkers that could afford early and accurate diagnosis. With a recombinant antibody microarray platform, targeting mainly immunoregulatory proteins, we screened sera from 148 patients with pancreatic cancer, chronic pancreatitis, autoimmune pancreatitis (AIP), and healthy controls (N). Serum biomarker signatures were derived from training cohorts and the predictive power was evaluated using independent test cohorts. The results identified serum portraits distinguishing pancreatic cancer from N [receiver operating characteristics area under the curve (AUC) of 0.95], chronic pancreatitis (0.86), and AIP (0.99). Importantly, a 25-serum biomarker signature discriminating pancreatic cancer from the combined group of N, chronic pancreatitis, and AIP was determined. This signature exhibited a high diagnostic potential (AUC of 0.88). In summary, we present the first prevalidated, multiplexed serum biomarker signature for diagnosis of pancreatic cancer that may improve diagnosis and prevention in premalignant diseases and in screening of high-risk individuals

    Design of recombinant antibody microarrays for membrane protein profiling of cell lysates and tissue extracts.

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    Generating global protein expression profiles, including also membrane proteins, will be crucial for our understanding of biological processes in health and disease. In this study, we have expanded our antibody microarray technology platform and designed the first human recombinant antibody microarray for membrane proteins targeting crude cell lysates and tissue extracts. We have optimized all key technological parameters and successfully developed a setup for extracting, labeling and analyzing non-fractionated membrane proteomes under non-denaturing conditions. Finally, the platform was also extended and shown to be compatible with simultaneous profiling of both membrane proteins and water-soluble proteins

    Large Extracellular Vesicle Characterization and Association with Circulating Tumor Cells in Metastatic Castrate Resistant Prostate Cancer

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    Liquid biopsies hold potential as minimally invasive sources of tumor biomarkers for diagnosis, prognosis, therapy prediction or disease monitoring. We present an approach for parallel single-object identification of circulating tumor cells (CTCs) and tumor-derived large extracellular vesicles (LEVs) based on automated high-resolution immunofluorescence followed by downstream multiplexed protein profiling. Identification of LEVs >6 µm in size and CTC enumeration was highly correlated, with LEVs being 1.9 times as frequent as CTCs, and additional LEVs were identified in 73% of CTC-negative liquid biopsy samples from metastatic castrate resistant prostate cancer. Imaging mass cytometry (IMC) revealed that 49% of cytokeratin (CK)-positive LEVs and CTCs were EpCAM-negative, while frequently carrying prostate cancer tumor markers including AR, PSA, and PSMA. HSPD1 was shown to be a specific biomarker for tumor derived circulating cells and LEVs. CTCs and LEVs could be discriminated based on size, morphology, DNA load and protein score but not by protein signatures. Protein profiles were overall heterogeneous, and clusters could be identified across object classes. Parallel analysis of CTCs and LEVs confers increased sensitivity for liquid biopsies and expanded specificity with downstream characterization. Combined, it raises the possibility of a more comprehensive assessment of the disease state for precise diagnosis and monitoring

    Systemic chemotherapy with or without hepatic arterial infusion chemotherapy for liver metastases from pancreatic cancer: a propensity score matching analysis

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    The significance of systemic chemotherapy (SCT) combined with hepatic arterial infusion (HAI) chemotherapy in the treatment of pancreatic ductal adenocarcinoma with liver metastases (PACLM) remains unclear. Based on previous studies, this single-center propensity score matching (PSM) study aimed to explore the efficacy of SCT with or without HAI for PACLM

    Plasma protein profiling in a stage defined pancreatic cancer cohort – Implications for early diagnosis

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    Pancreatic ductal adenocarcinoma (PDAC) is a disease where detection preceding clinical symptoms significantly increases the life expectancy of patients. In this study, a recombinant antibody microarray platform was used to analyze 213 Chinese plasma samples from PDAC patients and normal control (NC) individuals. The cohort was stratified according to disease stage, i.e. resectable disease (stage I/II), locally advanced (stage III) and metastatic disease (stage IV). Support vector machine analysis showed that all PDAC stages could be discriminated from controls and that the accuracy increased with disease progression, from stage I to IV. Patients with stage I/II PDAC could be discriminated from NC with high accuracy based on a plasma protein signature, indicating a possibility for early diagnosis and increased detection rate of surgically resectable tumors

    Overexpression of the key metabolic protein CPT1A defines mantle cell lymphoma patients with poor response to standard high dose chemotherapy independent of MIPI and complement established high-risk factors

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    The variable outcome to standard immunochemotherapy for mantle cell lymphoma (MCL) patients is a clinical challenge. Established risk factors, including high MCL international prognostic index (MIPI), high proliferation (Ki-67), non-classic (blastoid/pleomorphic) morphology, and mutated TP53, only partly identify patients in need of alternative treatment. Deepened understanding of biological factors that influence time to progression and relapse would allow for an improved stratification, and identification of novel targets for high-risk patients. We performed gene expression analyses to identify pathways and genes associated with outcome in a cohort of homogeneously treated patients. In addition to deregulated proliferation, we show that thermogenesis, fatty acid degradation and oxidative phosphorylation are altered in patients with poor survival, and that high expression of carnitine palmitoyltransferase 1A (CPT1A), an enzyme involved in fatty acid degradation, can specifically identify high-risk patients independent of the established high-risk factors. We suggest that complementary investigations of metabolism may increase the accuracy of patient stratification and that immunohistochemistry-based assessment of CPT1A can contribute to defining high-risk MCL

    Circulating Tumor Cell Kinetics and Morphology from the Liquid Biopsy Predict Disease Progression in Patients with Metastatic Colorectal Cancer Following Resection

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    The liquid biopsy has the potential to improve current clinical practice in oncology byproviding real-time personalized information about a patient’s disease status and response to treatment. In this study, we evaluated 161 peripheral blood (PB) samples that were collected aroundsurgical resection from 47 metastatic colorectal cancer (mCRC) patients using the High-DefinitionSingle Cell Assay (HDSCA) workflow. In conjunction with the standard circulating tumor cell (CTC)enumeration, cellular morphology and kinetics between time-points of collection were considered inthe survival analysis. CTCs, CTC-Apoptotic, and CTC clusters were found to indicate poor survivalwith an increase in cell count from pre-resection to post-resection. This study demonstrates thatCTC subcategorization based on morphological differences leads to nuanced results between thesubtypes, emphasizing the heterogeneity within the CTC classification. Furthermore, we show thatfactoring in the time-point of each blood collection is critical, both for its static enumeration and forthe change in cell populations between draws. By integrating morphology and time-based analysisalongside standard CTC enumeration, liquid biopsy platforms can provide greater insight into thepathophysiology of mCRC by highlighting the complexity of the disease across a patient’s treatment
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