Biomarker discovery for cervical cancer

Proteomics of human boy fluids is still in its early stage of development with major methodological challenges ahead. This implies that much attention is given to improving the methods and strategies. One major challenge is that many samples that have been acquired in the past may not fulfill the stringent requirements of storage and sample preparation to allow comparable proteomics analyses. It is therefore important to assess the factors that may affect the final proteomics result through systematic and reproducible analyses. Therefore accuracy and sensitivity of the analytical instrumentation is not the only critical factor in this research. Blood (plasma or serum) and urine can be easily sampled from patients or healthy volunteers and are therefore often the first choice when trying to discover novel biomarkers or biomarker patterns to diagnose cancer and other diseases. There are, however, drawbacks such as the masking of low-abundance by high abundance proteins and the possible effect of sampling and sample handling procedures (e.g. different times for blood clotting). A number of different approaches to deplete highly abundant proteins from human serum were studied throughout this thesis. Further, different analytical techniques were applied, such as a miniaturized, microfluidics-based LC-MS system (chip-LC-MS) to enhance overall sensitivity. It is shown that chip-LC-MS has at least twice the resolution of the previously used standard capillary LC-MS method. Since blood composition will change under the influence of external factors, the influence of clotting time on proteome of serum was studied. It was found that most proteins were not affected by clotting time except for those directly involved in this process, such as the fibrinopeptides. Next, we describe a more comprehensive approach for evaluating the influence of various pre-analytical parameters on the serum proteome. A factorial design strategy was applied to assess the importance of seven factors considered to be of relevance, including the level of hemolysis, the digestion conditions, and the storage conditions. Finally, we analyzed serum samples from cervical cancer patients at various stages of disease before and after treatment followed by data processing and statistical data analysis. While we did not discover major changes in the serum proteome using this method, subtle changes in the protein composition were observed in relation to treatment, the significance of which are being further investigated. It is thus demonstrated that the described methods are applicable to highly complex body fluids such as serum and that further studies into the relevance of the discovered changes of the serum proteome are warranted.

New Approaches for Isolation and Characterization of Extracellular Vesicles

Extracellular vesicles (EVs) are membrane vesicles secreted by cells and distributed widely in all biofluids. Extracellular vesicles can modulate the biological activities of the recipient cells. Due to their role in intercellular communication, they are receiving attention for therapeutic and diagnostic applications. The first step to better understand EVs and to utilize them as therapeutic and diagnostic tools is to purify them from a variety of biofluids. Membranes have been extensively used for purification of different biological species from biological fluids. As the first aim, a novel microfluidic system, termed as tangential flow for analyte capture (TFAC) was developed to isolate nanoparticles and EVs using ultrathin nanomembranes. Ultrathin nanomembranes were found well-suited for TFAC system when compared with conventional thickness membranes. TFAC also proved feasible for capturing of EVs from undiluted plasma. Fluorescent labeling of EVs has been employed for studying uptake and biodistribution of EVs. However, far too little attention has been paid to the effect of the fluorescent labeling on the size of EVs. In the second aim, the effect of PKH labeling, the most commonly used dye, on the size of EVs was systematically evaluated by nanoparticle tracking analysis (NTA). PKH labeling did not preserve the size of EVs and caused a size increase in all the PKH labeling conditions tested. The observed size shift may alter the uptake and biodistribution of EVs, suggesting that PKH labeling is not a reliable technique. Precise quantification and characterization of EVs is an important step towards utilizing them as therapeutic and diagnostic tools. EVs have been analyzed using bulk techniques such as western blot which is challenging due to the heterogeneity of EVs. Therefore, a robust and well-established technique for quantification and characterization of individual EVs is required. As the third aim, the efficacy of a virus detection technology for EVs was evaluated. Virus Counter 3100 (VC3100) is a fluorescence-based technique with similar principles as flow cytometry and was purpose-built for detection of small nanoparticles such as viruses. Due to the similarity in size and density of viruses and EVs in many biofluids, it was hypothesized that the VC3100 could detect EVs similarly to flow cytometry characterization of cells. Fluorescently labeled EVs from different sources were successfully quantified by the VC3100. Furthermore, VC3100 was also used to determine the expression level of target protein markers. Therefore, VC3100 is a powerful technique for precise quantification and protein profiling of EVs

Biomarker research in thromboembolic stroke

Introduction Stroke is a leading cause of death and disability worldwide. Approximately one quarter of all strokes are secondary to carotid atherosclerosis. There is a clinical need to improve risk stratification of carotid atherosclerosis, to better target surgical or interventional therapy and prevent stroke. This study aimed to determine diagnostic biomarkers of high-risk carotid atherosclerosis, and ensure the validity of such markers in the presence of alternative phenotypes of atherosclerotic disease. Methods 150 patients were recruited according to the following criteria: Group 1: Symptomatic >50% carotid stenosis Group 2: Non-carotid stroke/TIA Group 3: Asymptomatic >50% carotid stenosis Group 4: Asymptomatic controls with <50% carotid stenosis Group 5: Abdominal aortic aneurysm Group 6: Intermittent claudication Disease groups were matched for age, gender, cardiovascular risk factors, haematological parameters, renal function and lipid status. Blood and urine was collected from all patients and analysed through global metabolic profiling (1H-NMR Spectroscopy, HILIC-Mass Spectrometry and Lipid Profiling-Mass Spectrometry). Acquired spectra were compared across groups using computational multivariate data analysis to determine markers of high-risk carotid atherosclerosis. Results Statistical models derived from urinary spectra proved stronger than serum datasets, in particular with HILIC-Mass Spectrometry (positive ionisation mode). Application of computational OPLS DA resulted in discrimination of symptomatic carotid atherosclerosis from asymptomatic disease, aneurysmal disease, and intermittent claudication. Differentiating metabolites span a vast array of compounds including lipid derivatives, amino acid derivatives and nucleotide derivatives. Conclusion This is the first study to identify urinary metabolic biomarkers of high-risk carotid atherosclerosis, differentiating symptomatic carotid atherosclerosis from asymptomatic disease, and aneurysmal and peripheral arterial disease. Targeted temporal studies are now required for clinical validation and to determine the variation of acute biomarkers with time.Open Acces

The immune microenvironment in mantle cell lymphoma : Targeted liquid and spatial proteomic analyses

The complex interplay of the tumour and immune cells affects tumour growth, progression, and response to treatment. Restorationof effective immune response forms the basis of onco-immunology, which further enabled the development of immunotherapy. Inthe era of precision medicine, pin-pointing patient biological heterogeneity especially in relation to patient-specific immunemicroenvironment is a necessity for the discovery of novel biomarkers and for development of patient stratification tools for targetedtherapeutics. Mantle cell lymphoma (MCL) is a rare and aggressive subtype of B-cell lymphoma with poor survival and high relapserates. Previous investigations of MCL have largely focused on the tumour itself and explorations of the immune microenvironmenthave been limited. This thesis and the included five papers, investigates multiple aspects of the immune microenvironment withrespect to proteomic analysis performed on tissue and liquid biopsies of diagnostic and relapsed/refractory (R/R) MCL cohorts.Analyses based on liquid biopsies (serum) in particular are relevant for aggressive cases such as in relapse, where invasiveprocedures for extracting tissues is not recommended. Thus, paper I-II probes the possibility of using serum for treatment andoutcome-associated biomarker discovery in R/R MCL, using a targeted affinity-based protein microarray platform quantifyingimmune-regulatory and tumor-secretory proteins in sera. Analysis performed in paper I using pre-treatment samples, identifies 11-plex biomarker signature (RIS – relapsed immune signature) associated with overall survival. Further integration of RIS with mantlecell lymphoma international prognostic index (MIPI) led to the development of MIPIris index for the stratification of R/R MCL intothree risk groups. Moreover, longitudinal analysis can be important in understanding how patient respond to treatment and thiscan further guide therapeutic interventions. Thus, paper II is a follow-up study wherein longitudinal analyses was performed onpaired samples collected at pre-treatment (baseline) and after three months of chemo-immunotherapy (on-treatment). We showhow genetic aberrations can influence systemic profiles and thus integrating genetic information can be crucial for treatmentselection. Furthermore, we observe that the inter-patient heterogeneity associated with absolute values can be circumvented byusing velocity of change to capture general changes over time in groups of patients. Thus, using velocity of change in serumproteins between pre- and on-treatment samples identified response biomarkers associated with minimal residual disease andprogression. While exploratory analysis using high dimensional omics-based data can be important for accelerating discovery,translating such information for clinical utility is a necessity. Thus, in paper III, we show how serum quantification can be usedcomplementary tissue-identified prognostic biomarkers and this can enable faster clinical implementation. Presence of CD163+M2-like macrophages has shown to be associated with poor outcome in MCL tissues. We show that higher expression of sCD163levels in sera quantified using ELISA, is also associated with poor outcome in diagnostic and relapsed MCL. Furthermore, wesuggest a cut-off for sCD163 levels that can be used for clinical utility. Further exploration of the dynamic interplay of tumourimmunemicroenvironment is now possible using spatial resolved omics for tissue-based analysis. Thus, in paper IV and V, weanalyse cell-type specific proteomic data collected from tumour and immune cells using GeoMx™ digital spatial profiler. In paperIV, we show that presence as well as spatial localization of CD163+ macrophage with respect to tumour regions impactsmacrophage phenotypic profiles. Further modulation in the profile of surrounding tumour and T-cells is observed whenmacrophages are present in the vicinity. Based on this analysis, we suggest MAPK pathway as a potential therapeutic target intumours with CD163+ macrophages. Immune composition can be defined not just by the type of cells, but also with respect tofrequency and spatial localization and this is explored in paper V with respect to T-cell subtypes. Thus, in paper V, we optimizeda workflow of multiplexed immunofluorescence image segmentation that allowed us to extract cell metrics for four subtypes ofCD3+ T-cells. Using this data, we show that higher infiltration of T-cells is associated with a positive outcome in MCL. Moreover,by combining image derived metrics to cell specific spatial omics data, we were able to identify immunosuppressivemicroenvironment associated with highly infiltrated tumours and suggests new potential targets of immunotherapy with respect toIDO1, GITR and STING. In conclusion, this thesis explores systemic and tumor-associated immune microenvironment in MCL, fordefining patient heterogeneity, developing methods of patient stratification and for identifying novel and actionable biomarkers

Incorporating standardised drift-tube ion mobility to enhance non-targeted assessment of the wine metabolome (LC×IM-MS)

Liquid chromatography with drift-tube ion mobility spectrometry-mass spectrometry (LCxIM-MS) is emerging as a powerful addition to existing LC-MS workflows for addressing a diverse range of metabolomics-related questions [1,2]. Importantly, excellent precision under repeatability and reproducibility conditions of drift-tube IM separations [3] supports the development of non-targeted approaches for complex metabolome assessment such as wine characterisation [4]. In this work, fundamentals of this new analytical metabolomics approach are introduced and application to the analysis of 90 authentic red and white wine samples originating from Macedonia is presented. Following measurements, intersample alignment of metabolites using non-targeted extraction and three-dimensional alignment of molecular features (retention time, collision cross section, and high-resolution mass spectra) provides confidence for metabolite identity confirmation. Applying a fingerprinting metabolomics workflow allows statistical assessment of the influence of geographic region, variety, and age. This approach is a state-of-the-art tool to assess wine chemodiversity and is particularly beneficial for the discovery of wine biomarkers and establishing product authenticity based on development of fingerprint libraries

Correlation analysis of two-dimensional gel electrophoretic protein patterns and biological variables

BACKGROUND: Two-dimensional gel electrophoresis (2DE) is a powerful technique to examine post-translational modifications of complexly modulated proteins. Currently, spot detection is a necessary step to assess relations between spots and biological variables. This often proves time consuming and difficult when working with non-perfect gels. We developed an analysis technique to measure correlation between 2DE images and biological variables on a pixel by pixel basis. After image alignment and normalization, the biological parameters and pixel values are replaced by their specific rank. These rank adjusted images and parameters are then put into a standard linear Pearson correlation and further tested for significance and variance. RESULTS: We validated this technique on a set of simulated 2DE images, which revealed also correct working under the presence of normalization factors. This was followed by an analysis of p53 2DE immunoblots from cancer cells, known to have unique signaling networks. Since p53 is altered through these signaling networks, we expected to find correlations between the cancer type (acute lymphoblastic leukemia and acute myeloid leukemia) and the p53 profiles. A second correlation analysis revealed a more complex relation between the differentiation stage in acute myeloid leukemia and p53 protein isoforms. CONCLUSION: The presented analysis method measures relations between 2DE images and external variables without requiring spot detection, thereby enabling the exploration of biosignatures of complex signaling networks in biological systems

The use of proteomics techniques to identify potential markers of early stage colorectal cancer

Colorectal cancer (CRC) is the third most common cancer and the second most common cause of cancer related deaths in the UK. Research has shown that the five year survival rate for patients if diagnosed at an early stage is 83% however, only 11% of cases are diagnosed at this stage. The aim of this study was to use proteomic approaches to investigate secreted proteins from colorectal cancer cell lines to identify candidate biomarkers for early stage diagnosis. Microvesicles (MVs) are a mixed population of vesicles that are released by a wide range of cells and are thought to play a role in tumour development and progression. Stable Isotope Labeling of Amino Acids in Culture (SILAC) was used to investigate the relative abundance of proteins secreted in MVs released by two cell lines that are used as a model of early tumour progression. This study identified 86 potential candidates that demonstrated increased release and six of these proteins (AGR2, OLFM4, SBP1, HSP90α, HSP90β and CEACAM5) were selected for further investigation by Western blot analysis. These proteins show potential as markers of early stage CRC and would be suitable for further validation in patient serum samples

PEDOT:PSS thin films: Applications in Bioelectronics

Owing to their capability of merging the properties of metals and conventional polymers, Conducting Polymers (CPs) are a unique class of carbon-based materials capable of conducting electrical current. A conjugated backbone is the hallmark of CPs, which can readily undergo reversible doping to different extents, thus achieving a wide range of electrical conductivities, while maintaining mechanical flexibility, transparency and high thermal stability. Thanks to these inherent versatility and attracting properties, from their discovery CPs have experienced incessant widespread in a great plethora of research fields, ranging from energy storage to healthcare, also encouraging the spring and growth of new scientific areas with highly innovative content. Nowadays, Bioelectronics stands out as one of the most promising research fields, dealing with the mutual interplay between biology and electronics. Among CPs, the polyelectrolyte complex poly (3,4-ethylenedioxythiophene): poly (styrenesulfonate) (PEDOT:PSS), especially in the form of thin films, has been emphasized as ideal platform for bioelectronic applications. Indeed, in the last two decades PEDOT:PSS has played a key role in the sensing of bioanalytes and living cells interfacing and monitoring. In the present work, development and characterization of two kinds of PEDOT:PSS-based devices for applications in Bioelectronics are discussed in detail. In particular, a low-cost amperometric sensor for the selective detection of Dopamine in a ternary mixture was optimized, taking advantage of the electrocatalytic and antifouling properties that render PEDOT:PSS thin films appealing tools for electrochemical sensing of bioanalytes. Moreover, the potentialities of this material to interact with live cells were explored through the fabrication of a microfluidic trapping device for electrical monitoring of 3D spheroids using an impedance-based approach

Chemometric methods for microarray data analysis and their application to leukemia subtype identification

Verschiedene chemometrische Methoden wurden entwickelt, die die komplette Datenverarbeitungskette bei der Analyse von Affymetrix U133 DNA Biosensoren umfassen. Ziel war es die Qualität der Daten zu erhöhen. Dafür wurden Indikatoren erstellt, mit deren Hilfe es möglich ist, Signale mangelnder Qualität zu detektieren, sowie Hintergrund und Artefakte zu entfernen. Diese Methoden können mit einem ebenfalls neu entwickeltes Datenbank-System verwendet werden, um bei der gesamten Datenverarbeitung die Qualität der Daten zu gewährleisten. Angewandt wurde dieses System bei der Diskriminierung von verschiedenen pädiatrischen Leukämie-Typen. Es wurden Indikator-Gene gefunden, mit deren Hilfe unbekannte Leukämie-Proben klassifiziert werden können