A Patient-Derived Xenograft Model of Dedifferentiated Endometrial Carcinoma: A Proof-of-Concept Study for the Identification of New Molecularly Informed Treatment Approaches

Cancers (Basel). 2021 Nov 26;13(23):5962. doi: 10.3390/cancers13235962.

Abstract

Conventional treatment of dedifferentiated endometrial carcinoma (DEC)-an uncommon and highly aggressive uterine malignancy-is beset by high failure rates. A line of research that holds promise to overcome these limitations is tailored treatments targeted on specific molecular alterations. However, suitable preclinical platforms to allow a reliable implementation of this approach are still lacking. Here, we developed a patient-derived xenograft (PDX) model for preclinical testing of investigational drugs informed by molecular data. The model-termed PDX-mLung was established in mice implanted with lung metastatic lesions obtained from a patient with DEC. Histologic and whole-exome genetic analyses revealed a high degree of identity between PDX-mLung and the patient's parental lesions (both primary DEC and lung metastases). Interestingly, molecular analyses revealed that PDX-mLung harbored druggable alterations including a FGFR2 mutation and CCNE2 amplification. Targeted combined treatment with the FGFR inhibitor lenvatinib and the cell cycle inhibitor palbociclib was found to exert synergistic therapeutic effects against in vivo tumor growth. Based on the results of RNA sequencing, lenvatinib and palbociclib were found to exert anti-tumor effects by interfering interferon signaling and activating hormonal pathways, respectively. Collectively, these data provide proof-of-concept evidence on the value of PDX models for preclinical testing of molecularly informed drug therapy in difficult-to-treat human malignancies. Further clinical research is needed to examine more rigorously the potential usefulness of the lenvatinib and palbociclib combination in patients with DEC.

Keywords: dedifferentiated endometrial carcinoma; lenvatinib; palbociclib; patient-derived xenograft models; proof-of-concept; targeted treatment.