Overview
The project creates a multimodal atlas by integrating several layers of data from patient samples (untreated HGSOC) to map the tumor-immune ecosystem.
Study dataset
MSK SPECTRUM
High-Grade Serous Ovarian Cancer Multimodal Atlas
Genomic, single-cell, spatial and tissue imaging data from untreated HGSOC.
Memorial Sloan Kettering Cancer Center · Listed May 5, 2026
- Genomic
- Single-cell
- Spatial
- Tissue imaging
- Clinical
- Ovarian
Inside the dataset
Single-cell RNA sequencing (scRNA-seq)
To understand the transcriptomic landscape of malignant and immune cells.
Whole-genome sequencing (WGS) & MSK-IMPACT
To identify somatic mutations, copy-number alterations, and structural variants.
Multiplexed Immunofluorescence (mIF)
To visualize the spatial arrangement of immune cells (CD4+, CD8+, NK cells) within the tumor microenvironment.
Histopathology (H&E)
Whole-slide imaging for morphological context.
Research focus
Site-Specific Immune Evasion
The studies show that HGSOC develops distinct tumor microenvironments (TMEs) based on the site of metastasis, with specific mutational processes driving immune evasion, such as HLA loss.
Spatial Mapping
Researchers constructed a cell type map identifying nine broad cellular lineages (including epithelial, lymphoid, myeloid, and stromal cells) to understand tumor-stroma interactions.
Evolutionary Model
The project proposes that HGSOC develops from an early differentiated state to a late proliferative spectrum, characterized by increasing genomic instability and subclonal expansion.
Treatment Resistance
The study aims to stratify patients for standard-of-care and investigational therapies by analyzing their genomic and transcriptomic signatures.
Publications
Contributors
- Investigators
- Sohrab Shah, PhD, Memorial Sloan Kettering Cancer Center ORCID
- Institutions
- Memorial Sloan Kettering Cancer Center