Antibody-based cancer therapies have expanded treatment options across multiple tumor types. Among these, antibody-drug conjugates (ADCs) and bispecific antibodies have attracted considerable attention for their ability to target cancer cells through distinct mechanisms. However, identifying patients most likely to benefit from these treatments remains a challenge.
Biomarkers, which are measurable biological characteristics that provide information about a disease or its response to treatment, are central to precision oncology. For antibody-based therapies, biomarkers can help guide patient selection, predict treatment response, and identify potential resistance mechanisms.
Recent research suggests that biomarker development should be used for more than identifying whether a tumor expresses a particular antigen. Understanding how antibody therapeutics interact with cancer cells, deliver their effects, and influence surrounding tissues are equally important.
ADCs combine the targeting specificity of monoclonal antibodies with the cytotoxic activity of small-molecule drugs. Each ADC consists of an antibody linked to a therapeutic payload through a chemical linker. The antibody recognizes a target antigen on cancer cells, enabling preferential delivery of the payload to antigen-expressing tissues.
One of the most important considerations in ADC development is tumor antigen expression. Immunohistochemistry (IHC), a technique that uses antibodies to detect proteins in tissue samples, is commonly used to assess whether a tumor expresses the intended target.
However, antigen expression does not always correlate directly with clinical response.
A 2024 review by Katrini et al. examined the clinical activity of approved ADCs in relation to tumor antigen expression. The authors highlighted that some ADCs demonstrate activity in tumors with low or heterogeneous antigen expression, challenging the assumption that high target expression is always necessary for treatment benefit.
Several biological factors may contribute to these observations. For example, certain ADC payloads can diffuse into neighboring cells after release, producing a bystander effect that may extend cytotoxic activity beyond antigen-expressing cells.
Meanwhile, a 2026 review proposed a broader approach to biomarker development. Instead of relying primarily on antigen expression, the authors recommend evaluating multiple biological processes that influence ADC activity.
These include:
Antigen abundance and accessibility: How much target antigen is present, how it is distributed within the tumor, and whether the ADC can effectively reach it.
Intracellular trafficking and linker processing: How the ADC enters target cells, moves through intracellular compartments, and releases its cytotoxic payload.
Payload susceptibility: Whether cancer cells are sensitive to the drug carried by the ADC, including mechanisms that may contribute to resistance.
Tumor microenvironment: How surrounding cells, tissue structures, and local biological conditions affect treatment activity.
Toxicity-related biomarkers: Biological characteristics that may help predict adverse effects and guide treatment selection or dosing.
They also discuss emerging analytical approaches, including quantitative, spatial, and functional assays, that could provide more detailed information than conventional semi-quantitative IHC.
For example, spatial analysis can help characterize how target expression varies across different regions of a tumor, while functional assays may help to assess whether cancer cells are susceptible to a particular payload.
As more ADCs enter clinical practice, determining which treatment to administer and in what order has become increasingly important.
Some ADCs target different antigens but carry payloads with similar mechanisms of action. For example, several ADCs use topoisomerase I inhibitors, which interfere with DNA replication and can induce cancer cell death.
Resistance to one ADC may therefore affect sensitivity to another, even when the two therapies recognize different antigens.
Payload susceptibility and cross-resistance as emerging considerations for ADC sequencing. Biomarkers that capture these characteristics could help researchers understand why patients respond differently to successive treatments. In addition, toxicity biomarkers can help in predicting adverse effects alongside antitumor activity could improve dose selection and help balance therapeutic benefit against treatment-related risks.
Despite growing interest in biomarker-guided treatment, its incorporation into clinical development is inconsistent. Another recent study examined biomarker testing in clinical trials involving both ADCs and bispecifics. Among the trials evaluated, only 47.8% incorporated biomarker testing, primarily through next-generation sequencing (NGS) and IHC.
The analysis included ADCs targeting antigens such as TROP2 and HER2, alongside bispecific antibodies directed against target combinations including EGFR × c-MET and PD-1 × CTLA-4. The authors also highlight that integrating prospective biomarker strategies in future trials is essential for advancing personalized lung cancer treatments.
Together, these studies illustrate how biomarker research is evolving alongside antibody-based cancer treatments.
For ADCs, besides measuring target expression, treatment response also depends on measuring intracellular processing, payload sensitivity, tumor biology, and toxicity. Developing biomarkers that account for these factors could improve patient selection and support more informed therapeutic sequencing.
Progress will depend on integrating biomarker assessment into clinical trials, standardizing analytical methods, and validating their ability to predict meaningful clinical outcomes.
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