Xenograft Models of Breast Cancer and Their Predictive Power
Xenograft Models of Breast Cancer and Their Predictive Power
The most relevant data on the power of PDXs will ultimately derive from direct comparison of a patient's clinical response with that of the corresponding PDX to the same drug (Figure 3). Although limited in number, similarities between patient outcome and PDX responses have been reported. High concordance was observed between the clinical response and the corresponding xenograft model in 12 out of 13 cases, although these represented resistance to therapy. In another study, five of seven xenografts predominantly from high-grade, triple-negative tumors demonstrated a concordant response. Similar observations have been made for other solid malignancies including high-grade serous ovarian cancer for platinum sensitivity.
(Enlarge Image)
Figure 3.
Idealized personalized medicine strategy integrating data from mouse patient-derived xenograft models with patient treatment. Rather than directly assigning breast cancer patients to standard therapy, patients are treated on the basis of genomic and gene expression analyses. Blood from the patient is used as a reference for copy number alteration (CNA) analysis. In parallel, tumor fragments are xenografted into mice to establish a patient-derived xenograft (PDX) model. The patient tumor and their corresponding PDX tumor at transplant 3 (T3) undergo comparative genomic and gene expression analyses. Mice are treated with inhibitors (chemotherapy, antibodies or small molecules) based on initial genetic analysis of the patient tumor, in order to identify/validate the agents to be used for clinical treatment and to identify refractory tumors. If relapse occurs, re-biopsy and analysis of the metastatic/recurrent tumor together with the refractory PDX model could be used to reveal pathway activation. A database of mutations, expression profiles, and tumor response from multiple patients can be created to guide therapy for future patients. Rx, treatment of patient.
Clinical Correlates and Patient-derived Xenograft Models
The most relevant data on the power of PDXs will ultimately derive from direct comparison of a patient's clinical response with that of the corresponding PDX to the same drug (Figure 3). Although limited in number, similarities between patient outcome and PDX responses have been reported. High concordance was observed between the clinical response and the corresponding xenograft model in 12 out of 13 cases, although these represented resistance to therapy. In another study, five of seven xenografts predominantly from high-grade, triple-negative tumors demonstrated a concordant response. Similar observations have been made for other solid malignancies including high-grade serous ovarian cancer for platinum sensitivity.
(Enlarge Image)
Figure 3.
Idealized personalized medicine strategy integrating data from mouse patient-derived xenograft models with patient treatment. Rather than directly assigning breast cancer patients to standard therapy, patients are treated on the basis of genomic and gene expression analyses. Blood from the patient is used as a reference for copy number alteration (CNA) analysis. In parallel, tumor fragments are xenografted into mice to establish a patient-derived xenograft (PDX) model. The patient tumor and their corresponding PDX tumor at transplant 3 (T3) undergo comparative genomic and gene expression analyses. Mice are treated with inhibitors (chemotherapy, antibodies or small molecules) based on initial genetic analysis of the patient tumor, in order to identify/validate the agents to be used for clinical treatment and to identify refractory tumors. If relapse occurs, re-biopsy and analysis of the metastatic/recurrent tumor together with the refractory PDX model could be used to reveal pathway activation. A database of mutations, expression profiles, and tumor response from multiple patients can be created to guide therapy for future patients. Rx, treatment of patient.