Development and characterization of a patient-derived orthotopic xenograft of therapy-resistant breast cancer

Numerous years of cell line-based studies have enhanced the current understanding of cancer and its treatment. However, limited success has been achieved in treating hormone receptor-positive, HER2-negative metastatic breast cancers that are refractory to treatment. The majority of cancer cell lines are unsuitable for use as pre-clinical models that mimic this critical and often fatal clinical type, since they are derived from treatment-naive or non-metastatic breast cancer cases. The aim of the present study was to develop and characterize patient-derived orthotopic xenografts (PDOXs) from patients with endocrine hormone receptor-positive, HER2-negative metastatic breast cancer who had relapsed on therapy. A patient who progressed on endocrine hormone therapy provided her tumor via a biobank. This tumor was implanted in mice. It was then serially passaged by implanting PDOX tumor fragments into another set of mice to develop further generations of PDOXs. These tissues were characterized using various histological and biochemical techniques. Histological, immunofluorescence and western blot analyses indicated that the PDOX tumors retained a similar morphology, histology and subtype-specific molecular features to that of the patient's tumor. The present study successfully established PDOXs of hormone-resistant breast cancer and characterized them in comparison with those derived from the original breast cancer tissue of the patient. The data highlight the reliability and usefulness of PDOX models for studies of biomarker discovery and preclinical drug screening. The present study was registered with the clinical trial registry of India (CTRI; registration no. CTRI/2017/11/010553; registered on 17/11/2017).

Automated summary

By establishing and characterizing patient-derived orthotopic xenografts (PDOXs), researchers successfully identified hormone-resistant breast cancer and demonstrated the reliability and usefulness of these models for biomarker discovery and preclinical drug screening.