Phedias Diamandis

Dr. Diamandis completed his combined MD/PhD and residency training in neuropathology at the University of Toronto. His graduate work was carried out under the mentorship of Professors Peter Dirks and Mike Tyers in the field of cancer stem cell biology. Notably, he designed high-throughput screening platforms to allow chemical profiling of neural precursors and identified novel regulators of neural and cancer stem cell function.

Following completion of his training in 2016, he joined the University Health Network and Princess Margaret Cancer Centre as a Neuropathologist and Clinician Scientist. His research team focuses on optimizing high-resolution mass spectrometry for proteomic analysis of clinical formalin fixed paraffin embedded (FFPE) samples to define novel protein-based biomarkers driving disease.

Similarly, his group is utilizing artificial intelligence to improve the efficiency and objectivity of repetitive and subjective tasks in pathology. These tools aim to augment efficiencies of physician-lead pathology workflows, quality assurance and personalized medicine initiatives. Together with proteomics, Dr. Diamandis aims to help modernize pathology, from a somewhat qualitative art, into a highly quantitative science.

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Research Synopsis

The Diamandis Lab II focuses on modernizing traditional phenotypic readouts of human disease. Specifically, they are leveraging artificial intelligence (AI) to carry out large-scale morphologic analyses of neurological disorders not practical by human observers. Similarly, they use proteomics to provide global protein-based profiles of normal developmental and disease processes not possible with traditional candidate protein-based methods (e.g. immunohistochemistry).

As a pathologist, Dr. Diamandis believes morphologic analysis remains at the cornerstone of understanding human disease. Unlike most molecular tools, it provides rich single cell-level information regarding disease while maintaining important spatial relationships of cells within complex tissue. It is however not without limitations. Currently, morphologic analysis still remains a highly qualitative and subjective tool. His team is aiming to overcome these drawbacks by utilizing artificial intelligence, and particularly deep learning, to begin to improve the efficiency and objectivity of repetitive and subjective tasks in pathology. Specifically, they train neural networks to interpret digitized pathology slides and provide annotated outputs to aid in the diagnostic process. Ultimately, the augmentation of physician-led workflows with technology aims to improve quality assurance, patient safety and care.

Dr. Diamandis’ group is also developing expertise in liquid chromatography tandem mass spectrometry (LC-MS/MS) to molecularly characterize the global protein architecture of the human brain and neurological disorders. So far, molecular studies have mainly focused on genomic readouts, leaving the proteomic landscape of the brain and its maladies largely unexplored. This is an important gap, as proteins are the functional building blocks that directly carry out biological processes.

Dr. Diamandis recently successfully applied this approach to study different sub-population of cells during human brain development and uncovered a number of novel markers of neuronal cell types and neural precursors. They are now using these proteomic approaches to resolving protein patterns in cancer to predict activated pathways in each patient’s tumor and aid with personalized medicine efforts. Dr. Diamandis’ group hopes to continue to build and leverage LC-MS/MS-based proteomics to molecularly characterize the nervous system and diverse array of disease including neurodevelopmental and neurodegenerative disorders. Development of efficient workflows to isolate and analyze the proteomes of small subpopulations of cells can revolutionize our understanding of the brain and related diseases. Their proteomics expertise offers new approaches to studying these disorders using human tissue.

Dr. Diamandis’ current research team consists of a diverse group of trainees at all levels of training including undergraduate and graduate students, post-doctoral fellows and research associates from both the biological and computer sciences. The Diamandis Lab II seeks to expand by recruiting highly motivated undergraduate and graduate students and skilled technologists with an interest in neurosciences. Their collaborative partnerships provided access to a complete array of state-of-the art machines and experienced personnel. The learning objectives for all trainees during their tenure includes acquisition of foundational knowledge of neuroanatomy, neurosciences, neuro-oncology and neuro-development as well as familiarization and novel application of contemporary molecular techniques in these fields.

Specifically, The Diamandis Lab II is currently looking to recruit highly motivated and accomplished individuals with bioinformatics and programming expertise. Talented graphic designers and medical writers are also encouraged to apply for internships.

Selected Publications

Diamandis P. De-coding group 3 medulloblastoma biology with non-coding RNA. Neuro-Oncology. 2021 Apr 12; 23(4):525-6. Available from: doi.org/10.1093/neuonc/noab010. Impact Factor 10.1. Principal Author.

Alsafwani N, Alrjoub M, Djuric U, Gao A, Diamandis P. Tumor infiltrating lymphocytes are enriched in non-hypoxic glioblastoma niches. Journal of Neuropathology and Experimental Neurology. 2021 Jan 20; 80(2): 202-204. Available from: doi.org/ 10.1093/jnen/nlaa108. Impact Factor 3.8. Senior Responsible Author.

Samuel N, So E, Djuric U, Diamandis P. Consumer-grade electroencephalography devices as potential tools for early detection of brain tumors. BMC Medicine. 2021; Jan 22; 19(1) 16. Available from: doi.org/ 10.1186/s12916-020-01889-z. Impact Factor 6.8. Senior Responsible Author.

Papaioannou MR, Sangster K, Sajid RS, Djuric U, Diamandis P. (2020). Cerebral organoids: emerging ex vivo humanoid models of glioblastoma. Acta Neuropathologica Communication. 2020 Dec 1;8(1):209. Available from: doi.org/ 10.1186/s40478-020-01077-3. Impact Factor 5.9. Senior Responsible Author.

Lam KHB, Valkanas K, Djuric U, Diamandis P. Unifying models of glioblastoma's intratumoral heterogeneity. Neuro-Oncology Advances. 2020 Aug 11;2(1). Available from: doi.org/10.1093/noajnl/vdaa096. Impact Factor Not Assigned. Senior Responsible Author.

Faust K, Roohi A, Leon AJ, Leroux E, Dent A, Evans AJ, Pugh TJ, Kalimuthu SN, Djuric U, Diamandis P. Unsupervised Resolution of Histomorphologic Heterogeneity in Renal Cell Carcinoma Using a Brain Tumor-Educated Neural Network. JCO Clinical Cancer Informatics. 2020 Sep;4:811-821. Available from: doi.org/ 10.1200/CCI.20.00035. Impact Factor Not Assigned. Senior Responsible Author.

Malcolm J, Fiala C, Djuric U, Diamandis P. Can gliomas provide insights into promoting synaptogenesis? Molecular Psychiatry. 2020 Sept; 25(9): 1920-5. Available from: doi.org/ 10.1038/s41380-020-0795-4. Impact Factor 12.4 Senior Responsible Author.

Roohi A, Faust K, Djuric U, Diamandis P. Unsupervised machine learning in pathology: the next frontier. Surgical Pathology Clinics. 2020 Jun;13(2):349-358. Available from: doi.org/ 10.1016/j.path.2020.01.002. Impact Factor 1.0 Senior Responsible Author.

Diamandis P, Prassas I, Diamandis EP. Antibody tests for COVID-19: drawing attention to the importance of analytical specificity. Clinical Chemistry and Laboratory Medicine. 2020 Jun 25;58(7):1144-5. Available from: doi.org/ 10.1515/cclm-2020-0554. Impact Factor 3.6 Principal Author.

Djuric U, Kao J, Papaioannou M, Jevtic S, Batruch I, Diamandis P. Proteomic profiling of diffuse gliomas defines genomically and histopathologically relevant disease subtypes. Molecular and Cellular Proteomics, 2019 Oct;18(10):2029-43. Available from: 10.1074/mcp.RA119.001521. Impact Factor 4.8. Senior Responsible Author.

Grenier K, Kao J, Diamandis P. Three-dimensional modeling of human neurodegeneration: Brain organoids coming of age. Molecular Psychiatry, 2020 Feb; 25(2):254-74. Available from: doi.org.10.1038/s41380-019-0500-7. Impact Factor 12.3. Senior Responsible Author.

Faust K, Bala S, Ommeren RV, Portante A, Qawahmed RA, Djuric U, Diamandis P. Intelligent feature engineering and ontological mapping of brain tumour histomorphologies by deep learning. Nature Machine Intelligence. 2019; 1: 316–32. Available from: doi.org/10.1038/s42256-019-0068-6. Impact Factor Not Assigned. Senior Responsible Author.

Sarwar S, Dent A, Faust K, Richer M, Djuric U, Ommeren RV, Diamandis P. International Perspectives on the Advent of Artificial Intelligence in Diagnostic Pathology. npj Digital Medicine. 2019 Apr 26: 2:28. Available from: doi.org/10.1038/s41746-019-0106-0. Impact Factor 2.3. Senior Responsible Author.

Papaioannou MD, Djuric U, Kao J, Karimi S, Zadeh G, Aldape K, Diamandis P. Proteomic analysis of meningiomas reveals clinically-distinct molecular patterns. Neuro-Oncology. 2019 Aug 5;21(8): 1028-38. Available from: doi.org/10.1093/neuonc/noz084. Impact Factor 10.1. Senior Responsible Author.

Diamandis P, Aldape K. World Health Organization 2016 Classification of Central Nervous System Tumors. Neurologic Clinics. 2018 Aug;36(3):439-47. Impact Factor 2.9. Principal Author.

Faust K, Xie Q, Han D, Goyle K, Volynskaya Z, Djuric U, Diamandis P. Visualizing histopathologic learning and classification by deep neural networks using nonlinear feature space dimensionality reduction. BMC Bioinformatics. 2018 May 16;19(1):173. Available from: doi.org/ 10.1186/s12859-018-2184-4. Impact Factor 3.2. Senior Responsible Author.

Djuric U, Rodrigues DC, Batruch I, Ellis J, Shannon P, Diamandis P. Spatiotemporal proteomic profiling of human cerebral development. Molecular and Cellular Proteomics. 2017 Sep;16(9):1548-62. Available from: doi.org/ 10.1074/mcp.M116.066274. Impact Factor 4.8. Senior Responsible Author.

Diamandis P, Aldape KD. Insights from molecular profiling of adult glioma. Journal of Clinical Oncology. 2017 Jul 20; 35(21):2386-93. Available from: doi.org/10.1200/JCO.2017.73.9516. Impact Factor 33.0. Principal Author.

Djuric U, Zadeh G, Aldape K, Diamandis P. Precision Histology: How deep learning is poised to revitalize the H&E slide for personalized cancer care. NPJ Precision Oncology. 2017 June 19; 1:22. Available from: 10.1038/s41698-017-0022-1. Impact Factor 7.7. Senior Responsible Author.

Diamandis P, Chitayat D, Toi A, Blaser S, Shannon P. The pathology of incipient polymicrogyria. Brain Development. 2017 Jan; 39(1):23-39. Available from: doi.org/ 10.1016/j.braindev.2016.06.005. Impact Factor 1.5. Principal Author.

Diamandis P, Ferrer-Luna R, Huang RY, Folkerth RD, Ligon AH, Wen PY, Beroukhim R, Ligon KL, Ramkissoon SH. Case Report: Next-generation sequencing identifies a NAB2-STAT6 fusion in Glioblastoma. Diagnostic Pathology. 2016 Jan 27;11(1):13. Available from: doi.org/ 10.1186/s13000-016-0455-9. Impact Factor 2.6. Principal Author.

Diamandis P, Amato D, Finkelstein J, Keith J. 79-year old man with Parkinsonism and acute spinal cord compression. Brain Pathology. 2014 Jan;24:101-2. Available from: doi.org/10.1111/bpa.12106. Impact Factor 6.6. Principal Author.

Diamandis P. On the origins of physicians: Darwin or Lamarckian evolution? Clinical Chemistry and Laboratory Medicine. 2010 Oct; 48:1389-92. Available from: doi.org/ 10.1515/CCLM.2010.297. Impact Factor 3.6. Principal Author.

Diamandis P. The cost of autonomy: Estimates from recent advances in living donor kidney transplantation. Journal of Medical Ethics. 2010 Mar; 36:155-9. Available from: doi.org/10.1136/jme.2009.034306. Impact Factor 2.0. Principal Author.

Diamandis P, Sacher AG, Tyers M & Dirks PB. New drugs for brain tumors? Insights from chemical probing of neural stem cells. Medical Hypotheses. 2009 Jun; 72:683-7. Available from: doi.org/ 10.1016/j.mehy.2008.10.034. Impact Factor 1.3. Principal Author.

Diamandis P, Wildenhain J, Clarke ID, Sacher AG, Graham J, Bellows DS, Ling EK, Ward RJ, Jamieson LG, Tyers M & Dirks PB. Chemical genetics reveals a complex functional ground state of neural stem cells. Nature Chemical Biology. 2007 May; 3:268-73. Available from: doi.org/10.1038/nchembio873. Impact Factor 12.6. Principal Author.