How High-Dimensional Multi-Tensor Machine Learning Is Being Used to Improve the Prognosis, Diagno...
Channel: Alter Lab
Date: 2021-12-14

Orly Alter, 26th Society for Neuro-Oncology (SNO) Annual Meeting (Boston, MA, November 18–21, 2021).

Speaker: Orly Alter is a Utah Science, Technology, and Research (USTAR) associate professor of bioengineering and human genetics at the Scientific Computing and Imaging Institute and the Huntsman Cancer Institute at the University of Utah, the principal investigator of a National Cancer Institute (NCI) Physical Sciences in Oncology project, and the chief technology officer (CTO) and a co-founder of Eigengene, Inc. Inventor of the "eigengene," she pioneered the matrix and tensor modeling of molecular biological data, which, as she demonstrated, can (i) compare and integrate different, e.g., multi-omic, data types; (ii) scale with data sizes; (iii) be interpreted in terms of the known biology and batch effects underlying the data; and (iv) correctly predict previously unknown and experimentally verifiable physical, cellular, and evolutionary mechanisms. Her successful retrospective clinical trial provided a proof of principle that her recently formulated and developed physics-inspired multi-tensor generalizations of the singular value decomposition additionally can (v) discover accurate, precise, and actionable genotype-phenotype relationships; (vi) prove relevant to populations based upon whole genomes of small cohorts; and (vii) be validated in clinical trials.

Alter's trial experimentally validated a genome-wide pattern of DNA copy-number alterations found in glioblastoma brain tumors as a predictor of life expectancy statistically more accurate than and independent of age, which has been the best indicator for 70 years. She discovered this pattern, and patterns similarly predicting survival and response to treatment of patients with neuroblastoma nerve cancer and lung, ovarian, and uterine adenocarcinoma cancers, by modeling data from NCI databases. Researchers have recognized copy-number alterations as a hallmark of cancer for more than a century and have observed them in these tumors for decades. However, previous attempts to associate the tumors' copy numbers with the patients' outcome failed, including studies of the same data that used other artificial intelligence and machine learning methods. This demonstrates that Alter's multi-tensor decompositions are uniquely suited for personalized medicine.

Alter received her Ph.D. in applied physics at Stanford University, and her B.Sc. magna cum laude in physics at Tel Aviv University. Her Ph.D. thesis on "Quantum Measurement of a Single System," which was published by Wiley-Interscience as a book, is recognized today as crucial to the field of gravitational wave detection.

https://doi.org/10.1063/1.5142559
https://eurekalert.org/pub_releases/2020-05/uouh-gpf051320.php
https://alterlab.org/GBM_retrospective_clinical_trial/