PDX Study Investigates Cetuximab for Esophageal Cancer
Esophageal cancer patients lack targeted agent treatment options, leaving them with a poor prognosis post-surgery/chemoradiotherapy. A new publication details the preclinical evaluation of cetuximab in ESCC using clinically relevant PDX models to assess response and identify candidate predictive biomarkers.
Esophageal Cancer Patients Lack Targeted Agent Treatment Options
Esophageal cancer has a poor prognosis, even with recent advances in multi-modal treatment approaches and surgical techniques. The disease is the sixth leading cause of cancer death globally and new treatment options are needed, fast.
Targeted agents which act at specific oncogenic alterations have been highly successful for many cancer types, but only a few agents (such as HER2 inhibitors) are approved for esophageal cancer. Other research has looked at targeting VEGF/VEGFR, COX-2, mTOR, and EGFR.
EGFR in Esophageal Cancer
The role of EGFR is interesting in esophageal cancer, with EGFR overexpression correlating with a poor prognosis and aggressive disease. Gene amplification is also seen at varying levels across esophageal cancer subtypes. Many research teams have hypothesized that targeting EGFR could provide an effective treatment strategy in esophageal cancer.
EGFR blocking monoclonal antibodies (cetuximab, panitumumab) and tyrosine kinase inhibitors (gefitinib) were trialed in esophageal cancer and in esophageal squamous cell carcinoma (ESCC), where EGFR overexpression is high. However, results have varied or often proved negative, potentially down to non-selected patient groups being tested.
Most studies so far have added cetuximab to chemo-/radiotherapy in ESCC, but without first defining a suitable ESCC subtype, or without using a predictive biomarker for response.
Using Patient-Derived Xenografts (PDX) to Identify Responders
Patient-derived xenografts are highly clinically-relevant preclinical models for recapitulating human disease. Using large panels of these models in Mouse Clinical Trials mimics a patient Phase II trial. Each PDX subject reflects the pathology of its original patient, behaving as a patient avatar, and the cohort of patient avatars represents a diversity of the human patient population.
As well as studying response to a drug across a population, another main use of PDX Mouse Clinical Trials is to identify predictive biomarkers. This has already been accomplished for cetuximab response and biomakers in gastric cancer, and colorectal cancer, as well as PARP inhibitor response in SCLC.
This is the approach taken by Zhu et al, where the first PDX Mouse Clinical Trial to study the effectiveness of cetuximab in esophageal cancer and identify biomarkers of response was performed.
Mouse Clinical Trials with ESCC PDX Models
A panel of 61 ESCC PDX were generated, of which 16 were enrolled into the Mouse Clinical Trial. Multiple disease stages were covered, as were varying differentiation levels.
All of the enrolled models were extensively characterized, in order to be able to link response to oncogenic features. Common PDX model characterization includes:
- Histopathology analysis.
- Transcriptome sequencing.
- Gene copy number analysis.
- Protein expression analysis.
In this case, activated oncogenic pathways commonly seen in cancer were also examined using profiling data to fully allow biomarker determination.
Mouse Clinical Trial Reveals Responder Subset
The PDX models were treated with single agent cetuximab and response was assessed. The panel of ESCC PDX models clearly fell into two distinct groups:
- 7 of 16 models were responders (ΔT/ΔC <0).
- 9 of 16 models were non responders (ΔT/ΔC >0).
Among the responder models, two showed nearly complete response, with the other five being partial responders. This Mouse Clinical Trial data clearly suggests that a subset of ESCC patients could benefit from cetuximab treatment.
EGFR Expression Positively Predicts Cetuximab Response
Combining the response and characterization data allowed the research team to start teasing out predictive biomarkers. As cetuximab binds surface-expressed EGFR, EGFR status was the first starting point.
Firstly, EGFR copy number was studied. An amplification rate of 37.5% was found, which significantly correlated with cetuximab response. Next EGFR mRNA levels were assessed, with all high expressors shown to be cetuximab responders. Finally, EGFR protein levels were also examined, with high IHC scores for EGFR and pEGFR also associated with tumor response.
Overall, these analyses showed that EGFR may function as a single predictive biomarker for cetuximab response in ESCC. Other oncogenes and their downstream effectors (e.g. MET, HGF, ERBB2, AKT) were also evaluated, but none seemed to be an alternative promising biomarker for cetuximab efficacy.
Targeted agents are vitally needed in esophageal cancer to improve poor survival rates. Using predictive preclinical models in a Mouse Clinical Trial format allows the analysis of tumor response and the identification of predictive biomarkers.
An avatar trial of this type in ESCC found a disease subtype with overexpression of EGFR copy number, mRNA, and protein levels which benefits from single agent cetuximab treatment. These data can hopefully lead on to clinical confirmation and potential new treatments in this aggressive disease.
Zhu et al. A subset of esophageal squamous cell carcinoma patient-derived xenografts respond to cetuximab, which is predicted by high EGFR expression and amplification. Journal of Thoracic Disease 2018; 10(9):5328-38.