000042771 001__ 42771
000042771 005__ 20240323123741.0
000042771 037__ $$aETD
000042771 041__ $$aeng
000042771 245__ $$aQuantifying the single-cell spatial landscape of cancer
000042771 260__ $$bOregon Health and Science University
000042771 269__ $$a2024-03-22
000042771 336__ $$aDissertation
000042771 502__ $$bPh.D.
000042771 502__ $$gBiomedical Engineering
000042771 520__ $$aThis dissertation quantitatively assesses the single-cell spatial landscape of the tumor microenvironment for three cancer types. Statistical and machine learning approaches were used to identify candidate biomarkers of various clinical parameters, which can be leveraged to improve treatment strategies for future cancer patients. Importantly, the computational methods used here are widely applicable regardless of tissue type, and they provide a framework for future quantitative assessments of biological datasets resulting from any multiplex tissue imaging assay.
000042771 540__ $$fCC BY
000042771 542__ $$fIn copyright - single owner
000042771 650__ $$aTumor Microenvironment$$039473
000042771 650__ $$aMachine Learning$$011449
000042771 650__ $$aSingle-Cell Analysis$$039468
000042771 650__ $$aSpatial Analysis$$040030
000042771 650__ $$aBreast Neoplasms$$015809
000042771 650__ $$aSquamous Cell Carcinoma of Head and Neck$$012663
000042771 6531_ $$aspatial proteomics
000042771 6531_ $$amultiplex immunohistochemistry
000042771 6531_ $$abreast cancer
000042771 6531_ $$apancreatic ductal adenocarcinoma
000042771 691__ $$aSchool of Medicine$$041369
000042771 692__ $$aDepartment of Biomedical Engineering$$041397
000042771 7001_ $$aBlise, Katie$$uOregon Health and Science University$$041354$$10000-0002-6433-9455
000042771 8564_ $$9ef89cfcc-3218-4a4d-bfcb-7804237a577f$$s68816879$$uhttps://digitalcollections.ohsu.edu/record/42771/files/Blise.Katie.2024.pdf
000042771 909CO $$ooai:digitalcollections.ohsu.edu:42771$$pstudent-work
000042771 980__ $$aTheses and Dissertations
000042771 981__ $$aPublished$$b2024-03-22