Single-cell Data Science Applied for Cancer Treatment and Prognosis Prediction
Lana Garmire
March 8, 2023, Wednesday, 3:00 PM - 4:00 PM EST
Recently years we have seen a wealthy collection of computational methods developed to address challenges in single cell data analysis. However, an essential remaining question is how clinical domains (eg. oncology) can benefit from it? In this talk, I will debrief some recent relevant endeavors in my research group. First, I will describe a new drug recommendation method called ASGARD, which uses the patient scRNA-Seq data to repurpose drugs at the personalized level, exemplified by breast cancer, leukemia and COVID cases. Next, I will go over new discoveries on a large population cohort of single-cell imaging mass cytometry data from breast cancer patients. We computed hundreds of tumor and tumor microenvironment level features, applied them to a deep-learning framework (Cox-nnet) developed by my group, and revealed novel breast cancer survival subtypes with atypic prognosis outcomes. Together these research projects highlight the promise of using single cell data and bioinformatics to guide personalized therapeutic treatment and to predict patient prognosis more precisely.
Dr. Garmire is an awardee of US Presidential Early Career Scientists and Engineers in 2019, and a fellow of Americian Institute of Medical and Biological Engineering (AIMBE). She is a nationally and internationally recognized expert in translational bioinformatics.

Dr. Garmire obtained the MA degree in Statistics (2005) and PhD degree in Comparative Biochemistry (Computational Biology focus, 2007), both from UC-Berkeley. She started the first tenure-track faculty position in University of Hawaii Cancer Center later 2012 and was promoted to Associate Professor with tenure in 2017. She moved to University of Michigan in 2018 to expand the research to multi-modal research (genomics, EMR and pathological imaging analysis). She has published over 90 papers in top quality journals including Cell, Nature Communications, Genome Biology, Genome Medicine, Clinical Cancer Research. She contributed as the senior corresponding author in the majority of them. She delivered over 70 invited talks to institutes including National Library of Medicine (NLM) and National Academy of Sciences (NAS). She has mentored over 50 Assistant Professors, MD fellows, postdocs, graduate students and undergraduates of various academic backgrounds, in Biology, Mathematics, Physics, (bio)Statistics, Bioengineering, Computer Science and Electrical Engineering. Most PhD and postdoc trainees became faculty or senior scientists in private sectors. She has served on various NIH study sections and currently a standing member of BDMA study section. She is on the editorial advisory board for Genome Biology and Journal of Proteome Research.

As an academic mom of 2 young kids, she tweets about science, gender and racial disparity. She is a strong advocate for women in STEM, minority and under represented groups.