Compartment-specific spatial transcriptomics to reveal microenvironmental programs driving omental metastasis in high-grade serous ovarian cancer.

A Alayne Morrel (Texas A&M University School of Engineering Medicine, Houston, TX) C Cailin OConnell (University of Pennsylvania Department of Radiology, Philadelphia, PA) B Biana Godin (Houston Methodist Research Institute, Houston, Texas, United States)

Abstract

e17601 Background: High-grade serous ovarian cancer (HGSOC) frequently metastasizes to the omentum, yet spatially distinct transcriptional programs within tumor and stromal compartments remain incompletely characterized. Methods: To generate a high-resolution map of these microenvironments, we applied NanoString GeoMx Digital Spatial Profiling to matched primary–omental metastatic HGSOC samples from 15 patients. A nuclear marker and pan-cytokeratin positivity differentiated epithelial tumor regions from surrounding stroma. Digital segmentation enabled compartmentalized whole-transcriptome sequencing, allowing direct comparison of gene expression between matched primary and metastatic disease with specificity for stromal versus tumor compartments. We identified the top 25 differentially expressed mRNA signals from tumor and stroma compartments (p<0.05). These biomarkers were correlated with the Kaplan-Meier Plotter dataset (including GEO, EGA, TCGA, Metabric, Impact, and PubMed) to assess expression–overall survival associations (p<0.05) and generate a candidate gene set driving omental carcinomatosis. Results: Six primary pathways associated with decreased overall survival were identified (Table 1): (1) increased tumor migration and extracellular matrix remodeling; (2) tumor stress hormone upregulation with immune suppression; (3) stromal fibroblast activation; (4) increased stromal GABA transporter; (5) downregulation of hypoxia-driven tumoral pathways; and (6) loss of epigenetic surveillance in stroma. Conclusions: The resulting transcriptional map supports biomarker discovery and identification of actionable pathways in HGSOC. Pathway Genes mRNA Fold Change (Omental Mets vs. Primary) P value (Omental Mets vs. Primary) Survival Difference in Months (High vs. Low Expressors) P Value (High vs. Low Expressors) Tumor migration and remodeling of ECM ENPP2; FN1; TAGLN; CRTAC1 1.44; 2,11; 1.61; 1.55 0.009479; 0.020053; 0.006779; 0.005031 15 vs 17; 14 vs 17; 14 vs 18; 13 vs 16 0.0399; 0.0489; 0.0003; 0.0063 Tumor stress and immune regulation TSC22D3; FKBP5 1.51; 1.53 0.023870; 0.021592 14 vs 18; 13 vs 16 0.0132; 0.0104 Stromal fibroblast activation CD109; ZDHHC7; SMAP2 1.55; 1.61; 1.59 0.001646; 0.000366; 0.000625 13 vs 16; 15 vs 18; 11 vs 15 0.0307; 0.0210; 0.0041 Stromal GABA transporter SLC6A11/GAT3 1.73 0.000256 16 vs 18 0.0029 Downregulation of HIF EGLN3 0.58 0.008467 18 vs 15 0.0170 Loss of replication surveillance MCM6; HELLS; TTC28 0.57; 0.62; 0.71 0.000032; 0.000102; 0.001598 18 vs 16; 17 vs 16; 17 vs 15 0.0116; 0.0075; 0.0198

Article Details

Volume / Issue Vol. 44, Issue 16_suppl
Published June 01, 2026
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (3)

A

Alayne Morrel

Texas A&M University School of Engineering Medicine, Houston, TX

C

Cailin OConnell

University of Pennsylvania Department of Radiology, Philadelphia, PA

B

Biana Godin

Houston Methodist Research Institute, Houston, Texas, United States