MSACL 2026 Abstract

Spatial Multi Omics Reveals Modulation of the Tumor Microenvironment in Ovarian Cancer

Erin H. Seeley, Chun Wai Ng, Basant Gamal, Yadira Pacheco, Christopher Pacheco, Jared K. Burks, Samuel Mok, Sammy Ferri-Borgogno
The University of Texas MD Anderson Cancer Center, Houston, TX

Erin Seeley, PhD (Presenter) The University of Texas MD Anderson Cancer Center

Presenter Bio: Dr. Erin Seeley is the Director of the Mass Spectrometry Imaging Core at MD Anderson Cancer Center. She received her PhD in Analytical Chemistry from Purdue University where she studied phosphoproteomics. She then moved to Vanderbilt University as a postdoc in the lab of Professor Richard Caprioli where she was quickly promoted to Associate Director of the Tissue Profiling and Imaging Core, spending a total of 9 years there. Dr. Seeley then spent about 6 years in Contract Research Organizations performing MSI with a focus on the development of diagnostic tests. In 2020, she moved to the University of Texas at Austin to start up the CPRIT funded Mass Spectrometry Imaging Core. In the summer of 2025, she was recruited to MD Anderson to start a new MSI Core in support of their world-class cancer research. Throughout her career, she has been passionate about developing new sample preparation strategies for advancing the depth of coverage of MSI experiments and moving MSI to clinical applications that can be used to improve patient care.

Relevant Financial Disclosures (within past 24 months, reported on May 11, 2026) No relevant financial relationship(s) to disclose.

INTRODUCTION:
Ovarian cancer (OC) can be subdivided into different histologic types. Among them, clear cell ovarian cancer (CCOC), which constitutes 8% of ovarian cancer, differs from the other types with respect to its clinical characteristics. Most CCOC frequently presents at an early stage compared to high-grade serous ovarian cancer (HGSOC), with most cases diagnosed at Stage I or II, which offers a favorable prognosis. However, those diagnosed with advanced disease experience poorer clinical outcomes compared to those with HGSOC, since CCOC is usually more resistant to systemic chemotherapy than other types. Currently, little is known about spatial/neighborhood analyses in these cancers. Here we integrate multiple spatial omics approaches to uncover the tumor microenvironment of HGSOC and CCOC.

OBJECTIVES:
Integration of sequential mass spectrometry imaging, spatial transcriptomics, and sequential immunofluorescence to interrogate the tumor microenvironment in ovarian cancer. Use the knowledge generated to better guide patient care.

METHODS:
Serial sections of frozen CCOC (5) and HGSOC (4) were analyzed by spatial transcriptomics (ST) and mass spectrometry imaging (MSI). Additional FFPE samples (17 CCOC, 34 HGSOC) were subjected to sequential immunofluorescence (seqIF). From a single tissue section, five MSI datasets were sequentially collected at 20 µm resolution using a Bruker timsTOF flex MS; metabolites in positive and negative ion mode, lipids in positive and negative ion mode, and N-linked glycans. Sample preparation was performed using an HTX M5 Robotic Sprayer; NEDC for metabolite imaging, DAN for lipids, and PNGaseF/CHCA for glycans. Data were visualized using SCiLS Lab and putative IDs generated using MetaboScape. Data were integrated over all spatial omics platforms for a deeper evaluation of the tumor microenvironment (TME).

RESULTS:
In total, over 3,000 monoisotopic peaks were detected across the 5 MSI datasets, with numerous expression differences observed between CCOC and HGSOC. For example, several polyamines (histamine, spermine, spermidine) were found to be more abundant in HGSOC while carnitine, cis-aconitate, anserine, and valine were at higher levels in CCOC. High mannose glycans were more readily detected in HGSOC while glycogen and sialated glycans were more abundant in CCOC. PC(O) lipids and fatty acid carnitines were at higher levels in HGSOC, but sulfatides and sphingomyelins were at higher expression in CCOC.

Initial data integration focused on polyamines. Recent ST analyses demonstrated that increased AOC1 expression was found in the epithelial cell cluster of early stage CCOC than in HGSOC, validated by seqIF analysis. Increased AOC1 expression is associated with improved overall survival in HGSOC patients. Functional studies showed that despite lack of a direct effect on the growth of OC cells, syngeneic mouse cells transfected with full-length AOC1 had significantly lower tumor burden than the control mice, suggesting that the TME mediates the effect of AOC1 on tumor growth. Integrating ST and MSI revealed significantly inverse correlation between AOC1, and histamine and cell membrane VISTA expression levels in cancer cells and/or macrophages in the TME of CCOC and HGSOC, which was confirmed by seqIF, suggesting that histamine and VISTA mediate the tumor suppressive effect of AOC1. Indeed, our in vitro studies demonstrated that AOC1 abrogates the growth promoting effect of histamine in OC cells expressing high levels of histamine receptor HRH1, and AOC1 attenuates histamine induced OC proliferation and enhances T cell-mediated anti-tumor immunity via the histamine/HRH1/VISTA axis. Further studies demonstrated that in addition to VISTA, histamine can upregulate PD-L1 in both macrophages and OC cells. AOC1 may increase immune surveillance through attenuating histamine-induced VISTA and PD-L1 expression in the OC TME.

CONCLUSION:
The integration of multi spatial omics is enabling a deeper understanding of the tumor microenvironment in ovarian cancer. The knowledge gleaned from the further mining and integration of the mass spectrometry imaging data with spatial transcriptomics and sequential immunofluorescence will enable the discovery of additional potential treatment targets for aggressive ovarian cancer.