Browsing by Author "Farshidfar, Farshad"

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    A quantitative multimodal metabolomic assay for colorectal cancer
    (2018-01-04) Farshidfar, Farshad; Kopciuk, Karen A; Hilsden, Robert; McGregor, S. E; Mazurak, Vera C; Buie, W. D; MacLean, Anthony; Vogel, Hans J; Bathe, Oliver F
    Abstract Background Early diagnosis of colorectal cancer (CRC) simplifies treatment and improves treatment outcomes. We previously described a diagnostic metabolomic biomarker derived from semi-quantitative gas chromatography-mass spectrometry. Our objective was to determine whether a quantitative assay of additional metabolomic features, including parts of the lipidome could enhance diagnostic power; and whether there was an advantage to deriving a combined diagnostic signature with a broader metabolomic representation. Methods The well-characterized Biocrates P150 kit was used to quantify 163 metabolites in patients with CRC (N = 62), adenoma (N = 31), and age- and gender-matched disease-free controls (N = 81). Metabolites included in the analysis included phosphatidylcholines, sphingomyelins, acylcarnitines, and amino acids. Using a training set of 32 CRC and 21 disease-free controls, a multivariate metabolomic orthogonal partial least squares (OPLS) classifier was developed. An independent set of 28 CRC and 20 matched healthy controls was used for validation. Features characterizing 31 colorectal adenomas from their healthy matched controls were also explored, and a multivariate OPLS classifier for colorectal adenoma could be proposed. Results The metabolomic profile that distinguished CRC from controls consisted of 48 metabolites (R2Y = 0.83, Q2Y = 0.75, CV-ANOVA p-value < 0.00001). In this quantitative assay, the coefficient of variance for each metabolite was <10%, and this dramatically enhanced the separation of these groups. Independent validation resulted in AUROC of 0.98 (95% CI, 0.93–1.00) and sensitivity and specificity of 93% and 95%. Similarly, we were able to distinguish adenoma from controls (R2Y = 0.30, Q2Y = 0.20, CV-ANOVA p-value = 0.01; internal AUROC = 0.82 (95% CI, 0.72–0.93)). When combined with the previously generated GC-MS signatures for CRC and adenoma, the candidate biomarker performance improved slightly. Conclusion The diagnostic power for metabolomic tests for colorectal neoplasia can be improved by utilizing a multimodal approach and combining metabolites from diverse chemical classes. In addition, quantification of metabolites enhances separation of disease-specific metabolomic profiles. Our future efforts will be focused on developing a quantitative assay for the metabolites comprising the optimal diagnostic biomarker.
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    Cell Vibrational Profiling (CVP) Using Optical Tweezers to Improve Tumour Diagnosis: A Novel Methodological Approach
    (2021-06-29) Topham, Jared James; Amrein, Matthias; Green, Francis; Farshidfar, Farshad
    Cellular oscillations have long been recognized and previously suggested as a powerful real-time diagnostics tool for identifying and differentiating biological specimens. The oscillatory signals emitted by various biological samples are thought to be due to metabolic processes inherent to the measured sample. Various methods to measure oscillatory signals have used atomic force and dark-field microscopy accompanied by traditional interpretative methods such as Root Mean Square, Fast Fourier transform, time-domain analysis, and power spectral density. While these approaches were fundamental to the recognition of the field of cellular oscillations, the instrumentation lacked sensitivity and resolution, leading to difficulties in (1) analyzing complete frequency spectra of more than a few Hz, (2) providing empirically tested methodological approaches, and (3) statistically differentiating and/or determining distinct frequency regions for a cell-type of interest. This thesis sought to build and test a novel methodological approach to measuring and determining cellular vibrational frequency profiles. We hypothesized, each cell line (NMSCs, HEKa, and A549) exhibited unique and measurable vibrational frequency profiles reflective of their intrinsic cellular processes, measured via optical tweezers. We disclosed our efforts to improve the methodology by (1) optimizing experimental set-ups, looking specifically at sample preparation (implementation of microfluidic chambers, synchronization of cell cycles, and changes to media viscosity), and (2) analyzing data through the implementation of multivariate statistical analysis achieved through our newly developed software: VibrationScanner. Our results capitalized on our discoveries to establish a new method, cell vibrational profiling, in hopes that it may become a high-throughput, cost-effective, and sensitive technique to reliably identify biological functions and frequency components of cells.
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    Metabolomic Biomarkers for Colorectal Cancer
    (2016) Farshidfar, Farshad; Bathe, Oliver F.; Vogel, Hans J; Kopciuk, Karen A; Hilsden, Robert; Buie, W. Donald
    Colorectal cancer (CRC) is the second most common cancer in the North America. It is also a huge burden for society. Remarkable efforts have been and are being made to improve CRC diagnosis, to enhance the effectiveness of treatments, and to eventually improve the outcome of these patients. Metabolomic profiling, as a method for describing metabolic state and alterations in the molecular constituents and capable of yielding unique and invaluable information about tumor biology, has been employed. Using a range of spectroscopy and mass spectrometry techniques, we have sought to characterize the changes in the serum metabolome that appear as a result of malignant and pre-malignant lesions in the colon and rectum. In Chapter 2, Application of gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance (NMR) spectroscopy for staging CRC is described. Chapter 3 describes a larger study of 320 CRC and 31 colorectal adenoma cases as well as their matching controls by GC-MS, which led to the identification of validated metabolomic signature for identification of CRC and a proposed signature for identification of colorectal adenoma. In chapter 4, an effort for quantitative profiling of 62 CRC cases and 31 colorectal adenomas and their matching controls by tandem mass spectrometry is illustrated, and a validated quantitative signature for diagnosis of CRC is reported. Chapter 5 is dedicated to studying the prognostic value of metabolomic profiling in colorectal liver metastatic patients, and a novel workflow for estimation of recurrence risk using high-dimensional data is proposed. Challenges and pitfalls confronted in different steps of the project were addressed when possible by the use of available methods. Where no reliable method was available, we made an effort to develop one. This thesis, therefore, is focused on the metabolomic characterization of CRC and the adaptation of this knowledge for the development of clinically valuable biomarkers.
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    Serum metabolomic profile as a means to distinguish stage of colorectal cancer
    (BioMed Central, 2012-05-14) Bathe, Oliver F.; Farshidfar, Farshad; Weljie, Aalim M.; Kopciuk, Karen; Buie, W Don; MacLean, Anthony; Dixon, Elijah; Sutherland, Francis R; Molckovsky, Andrea; Vogel, Hans J