Raster · study · 2026
An Integrated Spatial Multi-Omics Workflow for Sequential RNA and Protein Profiling in FFPE Tumor Tissue
Listed in NCBI GEO
Understanding complex cellular niches, such as tertiary lymphoid structures (TLS), requires spatially resolved, multi-omic approaches that link transcriptional states and protein expression levels within individual cells.
Description
Here, we present an integrated spatial multi-omics workflow that enables sequential mapping of hundreds of genes via the In Situ platform (Xenium) and over 40 protein markers via Imaging Mass Cytometry™ (IMC™) technology on a single formalin-fixed, paraffin-embedded (FFPE) tissue section.
We applied this multi-modal approach to colorectal liver metastases (CRLM) and matched adjacent normal liver tissues. Our results demonstrate that the sequential application of these technologies maintains tissue morphology and the assay’s technical sensitivity. Further, high-dimensional data integration was performed through optimised computational co-registration at a single-cell level.
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Through this approach, we observed a correlation between β-catenin proteomic levels and malignant cell states, characterised immune cell phenotypes in TLS, and identified biological discrepancies between RNA and protein levels for key checkpoint molecules (PD-L1, TIM-3, and IDO). Overall, this technical framework enables robust profiling of functional cellular states, mapping chemokines, and more sensitive detection of clinically relevant targets missing in single-modality methods.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE335nnn/GSE335552 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE335552 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1478863 ncbi.nlm.nih.gov/bioproject/PRJNA1478863 ↗
project · from NCBI GEO
Topics
- Stated by source
- Homo sapiens · Other
- From keywords
- Life Sciences
- Inferred from text
- Bioinformatics and computational biology 75% · Cancer 65% · Imaging 75%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE335552 | 14 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[field].anzsrc:group:3102 | enrichment · NCBI GEO | taxonomy-embedding@1.1.0 | title+keywords+description (75%) |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:other | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[modality].local:modality:imaging | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[organism].NCBITaxon:9606 | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /taxon |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |