Why Cell Therapy Target Selection Is So Difficult
Antibody-drug conjugates (ADCs) and CAR-T therapies have reshaped modern oncology, but their success still depends on one deceptively simple question: are we targeting the right protein?
In practice, answering this is anything but simple. A clinically viable target must be present on tumor cells at sufficient levels, absent or minimal in healthy tissues, accessible on the cell surface, and in many cases capable of internalization or immune activation.
The challenge is that most of these properties are not directly observable from genomic or transcriptomic data. Gene expression can suggest potential targets, but it does not reliably indicate whether a protein reaches the cell surface, how much of it is present, or whether it behaves consistently across patient populations.
This disconnect is one of the key reasons why promising therapies fail late in development.
RNA alone cannot guide target selection
For years, drug discovery programs have relied heavily on RNA expression data as a proxy for protein abundance. While useful as a starting point, multiple studies have shown that mRNA levels only partially reflect protein abundance and often fail to capture localization or post-translational regulation.
In the context of cell therapies, this limitation becomes even more critical. A target may appear highly expressed at the transcript level while being minimally present on the actual cell surface or not present at all in the relevant disease context.
This is where surface proteomics provides a fundamentally different perspective. Instead of inferring biology from gene expression, it directly measures the proteins that are physically present and accessible on the cell membrane, which is the actual interface for ADCs and CAR-T therapies.
How surface proteomics changes the view of drug target
Surface proteomics directly measures proteins exposed on the cell membrane using enrichment strategies (e.g., biotinylation, glycoprotein capture) combined with high-resolution mass spectrometry.
Rather than focusing on a single hypothesis-driven target, this approach enables:
- unbiased identification of surface proteins
- quantitative comparison of tumor vs normal tissues
- discovery of novel, non-genomic targets
- assessment of target accessibility in real biological systems
Unlike genomic approaches, this is a functional measurement of the actual therapeutic interface.
Designing Better ADC Targets Through Biology
ADC development places particularly strict demands on target biology. A suitable antigen must be sufficiently abundant on tumor cells to ensure payload delivery, internalize efficiently after antibody binding, and show minimal expression in critical healthy tissues such as liver, heart, or bone marrow. Surface proteomics helps resolve this complexity by providing quantitative, tissue-wide measurements of target expression. Instead of relying on incomplete proxy data, researchers can directly assess whether a candidate antigen has the expression profile needed to support a viable therapeutic window.
This type of early biological validation can dramatically reduce downstream risk. Many late-stage failures in ADC programs are ultimately linked to unexpected expression in normal tissues or insufficient tumor specificity, issues that surface proteomics is uniquely positioned to detect early in development.
CAR-T therapy raises the bar
On-target, off-tissue toxicity is a well-known limitation of targeted therapies, especially While ADCs require careful target selection, CAR-T therapies impose even more stringent requirements. Because CAR-T cells actively recognize and kill target-expressing cells, even low levels of antigen expression in healthy tissue can lead to severe toxicity. At the same time, tumors are rarely uniform. Expression of a given antigen can vary widely between patients and even within different regions of the same tumor.
Surface proteomics helps address this complexity by mapping antigen distribution across both tumor and normal tissues, revealing heterogeneity patterns that are invisible in transcriptomic datasets. It also enables identification of tumor-specific surface signatures that may arise from protein modifications rather than gene-level differences.
Antigen escape and therapy resistance
One of the most significant challenges in CAR-T therapy is antigen escape, where tumor cells lose or downregulate the targeted antigen under therapeutic pressure. This is a major cause of relapses in patients who initially respond to treatment. By comparing surface protein profiles of treatment-sensitive and resistant cells, surface proteomics can reveal how tumors adapt. In many cases, alternative surface proteins become upregulated as compensatory survival mechanisms, offering new potential targets for combination or sequential therapies.
These patterns also support the design of multi-target CAR strategies, where multiple antigens are selected based on real co-expression data rather than theoretical assumptions.
CAR-T therapies require:
- very high specificity
- homogeneous tumor expression
- minimal normal tissue overlaps
- stable antigen presentation
Surface proteomics help uncover:
- tumor-specific surface signatures
- heterogeneity across patient populations
- antigen escape risk before clinical deployment
- identify alternative antigens that emerge under therapeutic pressure
- map co-expression patterns for multi-target CAR designs
- guide combination or dual-target strategies
Biomarkers and Patient Stratification
Beyond target discovery, surface proteomics also plays an important role in patient stratification. Because surface proteins are directly accessible, they can serve as clinically actionable biomarkers for imaging, liquid biopsy, or companion diagnostic development. By profiling patient-derived samples, researchers can identify expression signatures associated with response or resistance. This enables more precise clinical trial design, helping enrich for patients most likely to benefit from a given therapy and improving the clarity of efficacy signals.
A more complete view of cell therapy design
Taken together, surface proteomics shifts cell therapy development from a model-based approach to a measurement-based approach. By directly measuring the cell surface interface, surface proteomics improves:
- ADC target selection
- CAR-T safety and efficacy design
- resistance prediction
- biomarker development
- clinical stratification strategies
This leads to better target selection, improved safety profiles, more rational combination strategies, and ultimately higher clinical success rates for both ADCs and CAR-T therapies.
Supporting Research and Development
Panome Bio provides Surface Proteomics & Membrane Lipidomics, Discovery Proteomics, Next-Generation Metabolomics®, and Integrated Multi-Omics services to support therapeutic development. Using advanced mass spectrometry and bioinformatics workflows, Panome Bio enables:
- unbiased target discovery
- tumor vs normal tissue comparison
- biomarker identification
- resistance mechanism analysis
- integrated multi-omics interpretation