Overview | November 24, 2025
FFPE Multi-Omics for Discovery Oncology
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Download NowDiscovery oncology scientists are under pressure to identify and validate novel drug targets, but several recurring barriers challenge progress – specifically limiting the ability to perform multi-omics in FFPE tissue and tumors:
- Genomics alone misses protein-level function. DNA-seq or RNA-seq fails to reveal key target expression, pathway activation, post-translational signaling, and drug response.
- Fresh-frozen tumor tissue is limited. These samples are expensive to obtain and store, and often lack associated clinical and outcomes data.
- Direct measure of proteins in FFPE tissue is traditionally challenging. Antibody-based proteomic approaches are typically low-plex and can be compromised by formalin-induced cross-linking.
The result? Programs advance targets with incomplete functional validation, leading to high failure rates in translation.
Turn archival tissue into a discovery-ready molecular resource.
Sapient’s next-generation mass spectrometry-based FFPE proteomics method delivers deep, quantitative proteomic data via the direct measure of >10,000 proteins and their isoforms in FFPE tissue. Now, using existing biorepositories, you can perform deep proteomics and PTM mapping to profile functional biology, from tumor signaling to immune activation. This allows discovery oncology teams to accelerate the time from target nomination to functional validation, saving months per program and building confidence to de-risk translation.
Through Sapient’s DynamIQ™ virtual biobank, we can offer streamlined access to thousands of annotated FFPE samples, including those linked with clinical outcomes, if you need specific tumor types to support your study.
Download the data sheet to learn more about our FFPE proteomics workflow to measure protein expression and pathway activity, and see how Sapient’s next-generation FFPE Multi-Omics platform enables comprehensive multi-omic molecular mapping by additionally integrating DNA sequencing, single-cell sequencing, and spatial profiling to create a unified map of tumor biology.