Browsing by Subject "Serum"

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Open Access
Development and validation of methods for the diagnosis of lung cancer via serological biomarkers
(2019-02) Akçay, Abbas Güven
Over 10% of all new cancer cases are lung cancer. Moreover, estimates till 2030 indicate that already increasing lung cancer incidences will keep increasing, especially in developing countries like Turkey. Lung cancer, the leading cause of cancer deaths, has two large divisions: Small Cell Lung Cancer (SCLC) and Non-Small Cell Lung Cancer (NSCLC). SCLC is the most aggressive subtype of lung cancer. And although, the treatment options and median survival time is more favorable in Limited Disease (LD), high tumor growth rate and metastatic tendency of SCLC even in the early stages, makes the diagnosis troublesome. Similarly, if NSCLC is diagnosed in early stages, surgery option is open and this increases the patient survival rate. However, current methods in screening and diagnosis, such as computed tomography (CT) and positron emission tomography (PET), are all limited by false positivity rates. Additionally, biopsy methods used in histological evaluations are both invasive and prone to false negativity. Therefore, new diagnostic tools which are cheap, accurate and non-invasive are in high demand. Autologous antibodies are abundantly elicited and stably exist in patient sera years before the clinical diagnosis of disease. Several such antibodies were reported by our group and other groups in lung cancer. Therefore, new diagnostic methods incorporating autologous antibodies can be a huge step forward in early diagnosis of lung cancer. Moreover, miRNAs, with their unique hormone like features such as circulation in serum and their regulatory effects in cell, are another good candidate for the early diagnosis of lung cancer. Therefore, in this study I aimed to develop a reliable, robust and automated evaluation method to re-evaluate custom Protein Array (cPA) screenings previously performed in our lab, and to determine the autologous antibodies with highest discriminatory power between SCLC patients & healthy controls. Moreover, I aimed to develop a Quartz Crystal Microbalance with Dissipation (QCM-D) based immunoassay to be incorporated later in the validation of cPA results. Lastly, in a parallel study I aimed to identify and validate novel miRNA biomarkers NSCLC. My results indicate that cPAs can have better sensitivity and specificity than ELISA and that QCM-D can be developed as an alternative to ELISA. miRNAs identified in silico, can also be validated ex vivo. Previously, Protein Arrays (PAs) and cPAs were screened using 49 SCLC patient’s and 50 healthy serums in our laboratory, incorporating visual and manual evaluations. Sensitivity and specificity values were calculated for individual autologous-antibodies and a number of autologous-antibody panels. Moreover, validations of cPA results were carried via ELISA. However, large discrepancies between cPA and ELISA results, as well as inconsistencies among ELISA results urged me to consider re-evaluation of cPA results with a more robust way, and to focus on developing a method superior to ELISA in autologous-antibody evaluations. Therefore, I incorporated AIDA to generate numeric values out of cPA screening images and filtered low quality data with optimized cut-off values. Several Receiver Operating Characteristic (ROC) curves were plotted using evaluated data. Improved results were evident by the increased Area Under Curve (AUC) values in both individual and combined ROC curves. Moreover, I developed a QCM based immunosensor for detection of anti-SOX2 antibody to be incorporated later in validation of cPA results. Binding interaction between anti-SOX2 antibody and SOX2 protein was modelled using 1:1 Langmuir Isothermal Binding and standard curves generated in QCM. In a parallel study, I also investigated miRNAs significantly upregulated in NSCLC when compared to high risk controls. For that purpose, miRNA expression datasets were gathered from GEO. Selected 2 datasets with the same sample type were analyzed for common significantly upregulated miRNAs among these two datasets. Significantly upregulated miRNAs were subjected to logistic regression analysis with LASSO regularization (error metrics: AUC and MSE) to select best panel of miRNAs that can distinguish NSCLC patients from healthy controls in given datasets. Moreover, selected miRNAs were analyzed with qRT-PCR to validate the panel. I was able to re-evaluate cPA results by eliminating low quality data from numeric values generated via AIDA software from cPA images. I identified a panel of 4 autologous antibodies (FKBP8 – P53 – SOX2 – POLB) which resulted in 60% sensitivity at 100% specificity in discrimination of SCLC from controls. ROC of this autologous antibody panel had an AUC of 95.04%. Given panel surpassed diagnostic power of the only commercially available diagnostic kit of the same kind; EarlyCDT-Lung. Moreover, proof of concept for measurements of anti-protein antibodies were carried successfully in QCM, using anti-SOX2 antibody-SOX2 protein pair in PBS buffer as an example for it. Early results of anti-SOX2 mAb QCM indicate a linear assay range comparable to ELISA. Langmuir Isothermal Binding model revealed a strong interaction between antibody and protein in our QCM anti-SOX2 measurement experiments. Lastly, I was able to select 5 miRNAs using logistic regression and LASSO regularization that can best discriminate between NSCLC patients and high risk controls. However, validation experiments using qRT-PCR needs to be repeated as low Ct values and prominent hemolysis in serum samples prevented drawing meaningful conclusions.
Open Access
Microcantilever based disposable viscosity sensor for serum and blood plasma measurements
(2013) Cakmak O.; Elbuken, C.; Ermek, E.; Mostafazadeh, A.; Baris I.; Erdem Alaca, B.; Kavakli I.H.; Urey H.
This paper proposes a novel method for measuring blood plasma and serum viscosity with a microcantilever-based MEMS sensor. MEMS cantilevers are made of electroplated nickel and actuated remotely with magnetic field using an electro-coil. Real-time monitoring of cantilever resonant frequency is performed remotely using diffraction gratings fabricated at the tip of the dynamic cantilevers. Only few nanometer cantilever deflection is sufficient due to interferometric sensitivity of the readout. The resonant frequency of the cantilever is tracked with a phase lock loop (PLL) control circuit. The viscosities of liquid samples are obtained through the measurement of the cantilever's frequency change with respect to a reference measurement taken within a liquid of known viscosity. We performed measurements with glycerol solutions at different temperatures and validated the repeatability of the system by comparing with a reference commercial viscometer. Experimental results are compared with the theoretical predictions based on Sader's theory and agreed reasonably well. Afterwards viscosities of different Fetal Bovine Serum and Bovine Serum Albumin mixtures are measured both at 23. °C and 37. °C, body temperature. Finally the viscosities of human blood plasma samples taken from healthy donors are measured. The proposed method is capable of measuring viscosities from 0.86. cP to 3.02. cP, which covers human blood plasma viscosity range, with a resolution better than 0.04. cP. The sample volume requirement is less than 150. μl and can be reduced significantly with optimized cartridge design. Both the actuation and sensing are carried out remotely, which allows for disposable sensor cartridges. © 2013 .
Open Access
RNA based biomarkers for prediction of the endometrial window of implantation
(2020-12) Dedeoğlu, Ege
Early reproductive failure is the most common issue related to successful pregnancies, as around 30% of all conceptions reach live birth. The path to a successful pregnancy is reliant on the successful implantation of the embryo to the endometrium. This event requires three major components; a viable embryo ready for implantation, a receptive endometrium in which the implantation will occur, and healthy crosstalk between the embryo and receptive endometrium. It is estimated that two out of all three implantation failures are related to endometrial origin. This has led many researchers to attempt to elucidate the mechanism behind endometrial receptivity and generate a prediction of successful implantation of endometrial origin. Although there have been plenty of articles on this subject, there is still no consensus regarding standard endometrial receptivity biomarkers. Additionally, most of these articles’ findings cannot find their way into clinics. This is highlighted by the fact that the success rate of embryo implantation in ART applied in clinics is only around 10%. This study aimed to identify novel methods and biomarkers to predict the endometrium's receptivity, which could be applied in clinics easier and faster than the current kits in the market. We took several different approaches to achieve this aim. The first was to identify and validate particular miRNAs that showed a change in expression levels of the different days of the endometrial cycle in a healthy women’s serum. Our bioinformatical analysis has yielded ten miRNAs that show statistical differences in the human endometrium and being expressed in the serum. Downstream RNA-Seq and qPCR experiments have validated specific miRNAs previously predicted and identified novel miRNAs used for this purpose. The second was using in silico methods, identifying novel genes present in the endometrium that can predict the optimal point of receptivity. If considered and validated in vitro, this novel gene-list will be a cheaper but still as powerful alternative to the current endometrial test kit used in clinics today. Further validation RNA-Seq experiments on healthy and infertile females will elucidate our novel biomarkers' strength, designed to be used in ART clinics worldwide. Furthermore, upon building on these findings, it is possible to uncover previously overlooked mechanisms leading to women's implantation success.