# 3D Spatial Multi-Omics Profiling of Ovarian Cancer

> **NIH NIH U01** · UNIVERSITY OF TX MD ANDERSON CAN CTR · 2024 · $1,004,570

## Abstract

Research Summary:
High-grade serous ovarian cancer (HGSOC) is the most common histologic subtype of ovarian cancer.
Despite ongoing efforts to develop effective surgical and treatment regimens for advanced HGSOC, the overall
survival rate is only 30%, in part due to late diagnosis. HGSOC is among the most chemo-sensitive of all
epithelial malignancies at diagnosis. However, a subset of advanced stage patients fails to respond to initial
therapy and has a dismal prognosis. Therefore, understanding the mechanisms through which HGSOC
metastasizes, and develops intrinsic chemoresistance is crucial to improve the efficacy of treatments and
survival of patients. The proposed Ovarian Cancer Atlas Research Center (OCARC) will use and integrate
multiple state-of-the-art molecular and cellular profiling platforms to construct a three-dimensional (3D) ovarian
cancer atlas characterizing HGSOC metastasis, and the development of intrinsic therapeutic resistance using
a diverse patient cohort diagnosed with advanced HGSOC. The Center is composed of an Administrative Core
and three connected units: a Biospecimen Unit, a Characterization Unit, and a Data Processing Unit. The
multi-PI team from MD Anderson Cancer Center, and the University of Arkansas, brings together
internationally recognized experts in ovarian cancer biology and treatment, mass spectrometry, bioinformatics,
and imaging. This team will have the complementary multidisciplinary scientific expertise required for the
integration of the multidimensional, multiparametric data needed to construct a 3D ovarian cancer atlas and
address the key research problems proposed. The Administrative Core will provide the support necessary for
the proposed OCARC infrastructure. The Biospecimen Unit will acquire specimens, collect clinicopathologic
information, and prepare tissue sections. The Characterization Unit will perform spatially resolved subcellular
transcriptome profiling on FFPE tissue sections using the novel STOmics platform; 3D metabolomic and
peptidomic and glycomic profiling using high-resolution mass spectrometry imaging; and 3D stromal and tumor
cell profiling using the COMET multiplex immunofluorecence platform. The Data Processing Unit will build a
data warehouse hosting all the data generated by the Characterization Unit and the Biospecimen Unit. It will be
responsible for integrating all available data to identify the key signaling circuits that underlie the 3D spatial
changes of phenotypic profiles. The final atlas will identify differences in the cellular and molecular content, and
cell-cell crosstalk signaling networks in HGSOCs from (1) primary and metastatic sites; and (2) intrinsic
chemosensitive and chemoresistant HGSOCs. It will bring deeper insight into the multidimensional HGSOC
tumor ecosystems associated with intrinsic chemoresistance. We expect that our results will be used by
academic researchers, clinical researchers, and industry partners to improve our understanding of the
mol...

## Key facts

- **NIH application ID:** 10994265
- **Project number:** 1U01CA294459-01
- **Recipient organization:** UNIVERSITY OF TX MD ANDERSON CAN CTR
- **Principal Investigator:** Michael Birrer
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,004,570
- **Award type:** 1
- **Project period:** 2024-09-01 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10994265

## Citation

> US National Institutes of Health, RePORTER application 10994265, 3D Spatial Multi-Omics Profiling of Ovarian Cancer (1U01CA294459-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10994265. Licensed CC0.

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