Spagnolo, Daniel M
(2018)
Spatial statistics from hyperplexed immunofluorescence images: to elucidate tumor microenvironment, to characterize intratumor heterogeneity, and to predict metastatic potential.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
The composition of the tumor microenvironment (TME)–the malignant, immune, and stromal cells implicated in tumor biology as well as the extracellular matrix and noncellular elements–and the spatial relationships between its constituents are important diagnostic biomarkers for cancer progression, proliferation, and therapeutic response. In this thesis, we develop methods to quantify spatial intratumor heterogeneity (ITH). We apply a novel pattern recognition framework to phenotype cells, encode spatial information, and calculate pairwise association statistics between cell phenotypes in the tumor using pointwise mutual information. These association statistics are summarized in a heterogeneity map, used to compare and contrast cancer subtypes and identify interaction motifs that may underlie signaling pathways and functional heterogeneity.
Additionally, we test the prognostic power of spatial protein expression and association profiles for predicting clinical cancer staging and recurrence, using multivariate modeling techniques. By demonstrating the relationship between spatial ITH and outcome, we advocate this method as a novel source of information for cancer diagnostics. To this end, we have released an open-source analysis and visualization platform, THRIVE (Tumor Heterogeneity Research Image Visualization Environment), to segment and quantify multiplexed imaging samples, and assess underlying heterogeneity of those samples. The quantification of spatial ITH will uncover key spatial interactions, which contribute to disease proliferation and progression, and may confer metastatic potential in the primary neoplasm.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
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| Date: |
2 May 2018 |
| Date Type: |
Publication |
| Defense Date: |
2 February 2018 |
| Approval Date: |
2 May 2018 |
| Submission Date: |
25 April 2018 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
122 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Medicine > Computational and Systems Biology |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
computational pathology, computational biology, multiplexed immunofluorescence, tumor microenvironment, tumor heterogeneity, pointwise mutual information, |
| Date Deposited: |
02 May 2018 14:00 |
| Last Modified: |
02 May 2019 05:00 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/34415 |
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