Defining and Targeting Esophagogastric Cancer Genomic Subsets With Patient-Derived Xenografts.

PURPOSE

Comprehensive genomic profiling has defined key oncogenic drivers and distinct molecular subtypes in esophagogastric cancer; however, the number of clinically actionable alterations remains limited. To establish preclinical models for testing genomically driven therapeutic strategies, we generated and characterized a large collection of esophagogastric cancer patient-derived xenografts (PDXs).

MATERIALS AND METHODS

We established a biobank of 98 esophagogastric cancer PDX models derived from primary tumors and metastases. Clinicopathologic features of each PDX and the corresponding patient sample were annotated, including stage at diagnosis, treatment history, histology, and biomarker profile. To identify oncogenic DNA alterations, we analyzed and compared targeted sequencing performed on PDX and parent tumor pairs. We conducted xenotrials in genomically defined models with oncogenic drivers.

RESULTS

From April 2010 to June 2019, we implanted 276 patient tumors, of which 98 successfully engrafted (35.5%). This collection is enriched for PDXs derived from patients with human epidermal growth factor receptor 2-positive esophagogastric adenocarcinoma (62 models, 63%), the majority of which were refractory to standard therapies including trastuzumab. Factors positively correlating with engraftment included advanced stage, metastatic origin, intestinal-type histology, and human epidermal growth factor receptor 2-positivity. Mutations in and alterations in receptor tyrosine kinases ( and ), RAS/PI3K pathway genes, cell-cycle mediators ( and ), and were the predominant oncogenic drivers, recapitulating clinical tumor sequencing. We observed antitumor activity with rational combination strategies in models established from treatment-refractory disease.

CONCLUSION

The Memorial Sloan Kettering Cancer Center PDX collection recapitulates the heterogeneity of esophagogastric cancer and is a powerful resource to investigate mechanisms driving tumor progression, identify predictive biomarkers, and develop therapeutic strategies for molecularly defined subsets of esophagogastric cancer.