Video | June 10, 2026
Mapping Tumor Biology at the Protein Level: Your Questions, Answered
Sapient Founder & CSO Dr. Mo Jain addresses the most critical questions in tumor protein profiling — from filling the genomics gap to de-risking oncology drug development.
See why direct tumor protein profiling changes everything for oncology R&D
Oncology programs have long characterized tumors through the lens of genomics, via DNA sequencing and RNA expression. But for the majority of human cancers, there is no single driver mutation that can be identified from sequencing alone. That gap is where protein measurement comes in.
Sapient’s Tumor Protein Mapping Platform is a suite of mass spectrometry-based proteomics workflows designed to directly quantify the functional biology of tumors – not infer it. Across the cell surface proteome, signaling pathways, immune microenvironment, and resistance mechanisms, the platform delivers the protein-level data that genomics cannot provide.
In this video series, Dr. Jain explains what the platform measures, how it complements existing genomic and transcriptomic data, and how oncology teams are using it to make earlier, better-supported decisions throughout drug development.
60-70%
of tumors have no single identifiable driver mutation from genomic sequencing
10,000+
proteins can now be directly measured in human tumor tissue, including FFPE samples
THE SERIES
5 Questions on Tumor Protein Profiling with Dr. Mo Jain
PART 1
What's Fundamentally Missing from How Oncology Programs Characterize Tumors Today?
Dr. Jain opens by making the case that genomics – while transformative – leaves a critical gap for the majority of human cancers. For roughly 60–70% of tumors, no single activating oncogenic mutation can be identified, making it unclear which targets to pursue and how to develop precision-based therapeutics.
This is where tumor protein profiling becomes essential: moving from inferred protein levels to direct quantitative measurement of the actual molecules driving tumor biology.
PART 2
Walking Through the Workflows – and the Tumor Biology Each One Measures
Dr. Jain steps through the specialized workflows which comprise our Tumor Protein Mapping Platform, each optimized for different biological questions and therapeutic modalities: from SurfaceSeek™ for deep characterization of the cell surface proteome, to SignalingSeek™ phosphoproteomics, to ImmuneSeek™ and ResistanceSeek™ quantifying immune and resistance biology.
He explains how the workflows can be used singularly or in combination to align with the specific objectives of a given study and maximize the likelihood of generating meaningful, interpretable results.
PART 3
How Is Tumor Protein Profiling Complementary to – or Different from – Genomics?
Genomics and transcriptomics have transformed oncology, but they reveal what a cell could do, not what it is actually doing. Dr. Jain explains that for most therapeutics – ADCs, T-cell engagers, kinase inhibitors – what ultimately matters is the protein: whether it is expressed, accessible, and present at the right level.
For the vast majority of proteins in the proteome, RNA levels are a poor proxy for protein abundance. Dr. Jain addresses why pairing proteomics with genomic data produces a far more complete picture of tumor biology than either approach alone.
PART 4
On SurfaceSeek™: What Does It Actually Measure – and Why Does It Matter for ADC and T-Cell Engager Programs?
ADCs, T-cell engagers, radioligand pharmaceuticals, and CAR-T therapies all depend on a protein being functionally deployed at the tumor cell surface – not just expressed somewhere in the cell. SurfaceSeek is built specifically for this need. Dr. Jain explains the technical approach and why RNA-based inference cannot substitute for direct measurement in this context.
By enriching for N-linked glycoproteins and using mass spectrometry to quantify their abundance in both tumor and normal tissues, SurfaceSeek can identify new targets, validate differential surface expression, and provide the target density data needed to design effective precision therapeutics.
PART 5
How Does Direct Tumor Protein Profiling Support Decision-Making and De-Risk Oncology Drug Development?
This final answer addresses what oncology teams ultimately need: a way to make better, earlier decisions about which programs to advance and how to design trials. Dr. Jain describes how the Tumor Protein Mapping Platform contributes across the full development arc – from identifying and validating targets early, through translating preclinical findings, to stratifying patients in clinical studies by their actual protein-level biology.
Interested in applying Sapient’s Tumor Protein Mapping Platform in your programs? Connect with our scientists to discuss your study design, sample types, and which platform workflows are the right fit.
THE SUMMARY
Common questions on tumor protein profiling in oncology drug development, answered.
What causes high failure rates in oncology clinical trials and how can biomarkers discovered through protein-level tumor profiling help?
High failure rates are driven primarily by target selection based on genomic inference, poor patient stratification, and incomplete understanding of resistance before enrollment begins. When trial design relies on genomic proxies for protein biology, patients who lack functional expression of the intended target are routinely enrolled – and fail to respond.
Protein-level biomarkers address this by confirming that a target is surface-accessible, verifying pathway activation, characterizing immune state, and stratifying patients by the biology that actually predicts response. Sapient’s Tumor Protein Mapping Platform is specifically designed to generate this evidence early in development and support protein-validated enrollment criteria.
How is FFPE tissue proteomics being used in modern oncology R&D in regards to tumor profiling?
FFPE tissue proteomics has emerged as a transformational capability because it enables direct, quantitative tumor protein profiling from archival samples — the most widely available form of clinical tissue. Advances in protein handling, mass spectrometry hardware, and computational software now enable reliable measurement of >10,000 protein groups from a single 5-micron FFPE section.
Oncology programs are using it to generate protein-level biomarker data from existing sample banks without new sample collection, validate targets retrospectively in clinical trial biopsies, and characterize tumor surface, signaling, immune, and resistance biology from the same archived tissue.
How can multi-omics approaches improve target identification in oncology drug development?
Multi-omics closes the gap between what genomics reveals and what proteins are actually doing in a tumor. For 60–70% of tumors, no single driver mutation is identifiable from DNA or RNA alone – meaning those approaches cannot reliably guide target selection. By layering direct proteomic measurement onto genomic and transcriptomic data, teams gain a functional view of which proteins are expressed, surface-accessible, activated in pathways, or abnormally regulated.
Sapient’s integrated multi-omics studies combine DiscoverySeek, SurfaceSeek, SignalingSeek, ImmuneSeek, and ResistanceSeek with existing genomic data to identify and validate tractable drug targets directly in human tumors.
We want to identify predictive biomarkers for an immunotherapy. Which CROs specialize in this?
Sapient specializes in identifying predictive biomarkers for immunotherapy through direct protein measurement in human tumor tissue. Our ImmuneSeek workflow profiles the functional immune biology of tumors – quantifying immune cell states, activation pathways, and immunosuppressive mechanisms – from FFPE or fresh-frozen samples via mass spectrometry.
Unlike gene expression signatures, this delivers a mechanistic view of which patients are functionally primed for response to checkpoint inhibitors, cell therapies, or other IO agents, enabling protein-validated patient stratification.
