March 27, 2019 | Molecular diagnostics is a field overdue for disruptive technologies. Recent developments in mass spectrometry (MS) provide opportunities to more effectively and systematically gain insight on protein levels in biological fluids, argues to Anthony Whetton, the director for the Stoller Biomarker Discovery Centre at the University of Manchester.
Whetton believes the use of the latest innovations in MS-based technologies reduce the time for biomarker discovery, validation, verification, and adoption for clinical usage for the patient’s benefit, which is the ultimate goal.
On behalf of Diagnostics World, Kaitlyn Barago spoke with Whetton about how the Stoller Biomarker Discovery Centre is using game changing technology, the barriers in implementing molecular diagnostics in clinical care, and lessons that can be learned from other infectious disease researchers.
Editor’s note: Kaitlyn Barago, a conference producer at Cambridge Healthtech Institute, is planning a track dedicated to Advanced Diagnostics for Infectious Diseases at the upcoming Molecular Diagnostics Europe Conference in Lisbon, Portugal, May 6-9. Whetton will be a keynote speaker on the program, discussing the development of integrated platforms for biomarker and drug target discovery using proteomics. Their conversation has been edited for length and clarity.
Diagnostics World: Mass spectrometry is proving to be a game changer in diagnostics. How is your work focusing on applying proteomics and mass spectrometry in a systems biology approach to diagnostics, and what are some challenges in applying these precision medicine type approaches to diagnostics?
Anthony Whetton: Relative quantification between many samples in a clinical cohort using mass spectrometry has been a major difficulty in biomarker discovery proteomics. The game changing advent of a new approach in mass spectrometry has altered our perspective on this. Within our Stoller Biomarker Discovery Centre and elsewhere, the disruptive technology known as SWATH-MS (Sequential Window Acquisition of all Theoretical fragment ion Mass Spectrometry) enables a digitized proteomic profile of plasma to be generated with about three hours of machine time. SWATH-MS allows a recording of all fragment ion traces of detectable peptide precursors present in a biological sample. This approach to plasma proteomics (with improved sensitivity, specificity, reproducibility, and coverage) permits rapid generation of proteomic maps that can be checked against reference libraries of proteins, enabling relative quantities of such proteins across large cohorts to be determined. This information can then be subjected to correlation with clinical data to identify biomarker signatures. To do this we use machine learning approaches that extract optimal information and discriminatory power from the proteomics datasets.
Molecular diagnostics for infectious disease is a rapidly growing subsection of the field. What are some of the barriers that remain in implementing molecular diagnostics platforms into clinical care?
The big issue with molecular diagnostics implementation into clinical care is not necessarily going to be the discovery of signatures or algorithms that have the degree of clinical sensitivity and specificity required but the development of an appropriately validated and verified test. This requires a sufficient number and size of cohorts plus adherence to laboratory standards throughout the process that can satisfy the regulatory authorities. In other words, the identification of the critical clinical question, the development and execution of study designs needs to be rigorous from the earliest point. The new ‘omics approaches and technologies offer big data. Informatics can turn that data into information but adherence to processes will more rapidly yield tests and algorithms that can be used to take clinical decisions.
What are some ways that infectious disease researchers can apply lessons learned from other fields including oncology to pathogen diagnostics?
In looking for signatures of infection we can apply the same plasma proteomic profiling as seen in oncology and inflammatory diseases in our laboratory. We can assess the blood proteins (or proteins from other sources) using SWATH MS and using different protein reference libraries to look for human or pathogen proteins. Then we can apply the same machine learning approaches to the data acquired to seek out signatures of proteins to answer specific clinical questions on prognosis, diagnosis, response to therapy and so on. Mass spectrometry is already being used to identify bacterial species in clinical specimens so the above research can complement and extend ongoing proteomic/pathogen analytical approaches.