SIO: A Spatioimageomics Pipeline to Identify Prognostic Biomarkers Associated with the Ovarian Tumor Microenvironment

Stromal and immune cells in the tumor microenvironment (TME) have been shown to directly affect high-grade serous ovarian cancer (HGSC) malignant phenotypes, however, how these cells interact to influence HGSC patients' survival remains largely unknown. To investigate the cell-cell communicatio...

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Bibliographic Details
Published in:Cancers 2021-04, Vol.13 (8), p.1777
Main Authors: Zhu, Ying, Ferri-Borgogno, Sammy, Sheng, Jianting, Yeung, Tsz-Lun, Burks, Jared K, Cappello, Paola, Jazaeri, Amir A, Kim, Jae-Hoon, Han, Gwan Hee, Birrer, Michael J, Mok, Samuel C, Wong, Stephen T C
Format: Article
Language:English
Subjects:
Ablation
Biomarkers
Cell interactions
Cell signaling
Chemotherapy
Cytometry
Deep learning
Gene expression
Medical research
Nearest-neighbor
Neural networks
Ovarian cancer
Patients
Phenotypes
Stromal cells
Surgery
Transcriptomes
Tumor microenvironment
Tumors
Watersheds
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Summary:Stromal and immune cells in the tumor microenvironment (TME) have been shown to directly affect high-grade serous ovarian cancer (HGSC) malignant phenotypes, however, how these cells interact to influence HGSC patients' survival remains largely unknown. To investigate the cell-cell communication in such a complex TME, we developed a SpatioImageOmics (SIO) pipeline that combines imaging mass cytometry (IMC), location-specific transcriptomics, and deep learning to identify the distribution of various stromal, tumor and immune cells as well as their spatial relationship in TME. The SIO pipeline automatically and accurately segments cells and extracts salient cellular features to identify biomarkers, and multiple nearest-neighbor interactions among tumor, immune, and stromal cells that coordinate to influence overall survival rates in HGSC patients. In addition, SIO integrates IMC data with microdissected tumor and stromal transcriptomes from the same patients to identify novel signaling networks, which would lead to the discovery of novel survival rate-modulating mechanisms in HGSC patients.
ISSN:2072-6694
2072-6694
DOI:10.3390/cancers13081777