The goal of this clinical trial was to prospectively generate fresh PDA xenografts with annotated clinical information and significant biological data. The main results of the study indicate that patients whose tumors engrafted have a poor outcome, which is likely related to loss of Smad4 and increased metastatic potential. Due to the inherent nature of complex adjuvant protocols, we were not able to correlate response to gemcitabine in the xenograft model and time to progression given that few patients received gemcitabine alone adjuvantly. Nonetheless, the data confirm that response to gemcitabine in the xenograft model did correlate with response to gemcitabine in the advanced metastatic setting. However, an important limitation of this study was that only seven patients received single agent gemcitabine, abrogating definitive statistical correlations.
We demonstrate that tumor engraftment is an independent predictor of survival in resected PDA. Patients whose tumors failed to engraft had an 81% reduced risk of death. To further investigate this issue we tested two complementary hypotheses. One is that engrafting tumor contains higher proportion of tumor initiating cells (TICs) as these cells have been linked to treatment resistance and development of metastasis.(20
) No differences were observed in the number of TICs as assessed by IHC for ALDH.(16
) However, other markers that have been associated with TICs in pancreatic cancer were not tested in this study.(21
) The second hypothesis was that engrafting tumors lack Smad4 based on previous work from our group, which showed that Smad4-defective tumors have a worse prognosis and a higher metastatic potential.(18
) Indeed, engrafted tumors more frequently had Smad4 loss (67% vs. 36%, p=0.024). Development of metastatic disease is the ultimate determinant of survival in cancer patients. This is further supported by the finding that the gene expression of xenografted tumors is similar to metastatic adenocarcinomas, suggesting that passage of the tumor in mice selects a clonal population of cells with a predilection to colonize new microenvironments. Altogether, the higher prevalence of Smad4 loss and the presence of a metastatic signature of adenocarcinoma in engrafted patients suggest that patients whose tumors engraft are more likely to have metastatic disease. This is consistent with evidence from different disease types showing that engraftment is a marker of poor prognosis.(24
Several lines of evidence suggest that the stroma plays an important role in the pathophysiology of cancer. Enrichment of stroma-related genes was observed in the progression from preinvasive disease to invasive gastrointestinal cancers.(26
) This mechanism is not disease specific as mesenchymal stem cells within the stroma promote breast cancer growth and metastases.(27
) Moreover, shifting towards a stromal phenotype is an intrinsic property of chemotherapy-resistant tumors.(28
) An additional finding in our work was that stromal pathways were enriched in gemcitabine-resistant patients. We acknowledge that the number of samples included in the gene expression analysis was low to draw definitive conclusions (supplementary Table 1
), however, this finding needs to be examined in the context of earlier works showing that stromal depletion may increase tumor permeability to gemcitabine and result in increased drug activity.(6
) A phase III trial is testing this “stromal collapse” strategy based on promising activity in the phase I setting.(29
The work presented here also augments information from previous preclinical models by developing tumors from clinically well-annotated cases. For many of these tumors, there is significant information available from “omics” technologies, including global exonic sequencing.(10
) This is a unique platform for performing additional research in PDA, although the development of these platforms has not been limited to PDA. Recently, several papers have reported similar efforts in other diseases such as lung cancer, melanoma and breast cancer.(24
) It is anticipated that these models will progressively become more utilized in early drug development discovery.
A fundamental question that must be answered to justify using freshly generated xenograft platforms for drug development is whether findings in the model correlate with clinical findings. Our first attempt to see if such a correlation existed was analyzing the results of adjuvant treatment. However, most patients included in this series had been treated with complex multimodality treatments that were impossible to replicate in a murine model (supplementary Table 1
). In retrospect, it became apparent that the ability to appropriately assess correlations between the model and clinical responses in patients rested upon protocol-guided treatments. In the group of patients who received gemcitabine in a setting of advanced cancer, the time to treatment failure was longer in patients whose xenografts responded better to gemcitabine. A difficulty we also encountered was the lack of efficacy of gemcitabine in these xenografts and, indeed, as borne out by applying RECIST criteria to the T/C data and finding that not a single case reached the 30% partial response mark. This lack of response highlights the major issue in PDA treatment, which is the lack of minimally effective treatments. While overall these data are encouraging, additional work is needed to properly determine the predictive capabilities of these models. This point is illustrated by the potentially better predictive power of orthotopic implantation versus subcutaneous implantation.
In summary, we have developed and characterized a set of 42 PDA engrafted xenografts with annotated clinical information. Interestingly, successfully engrafted tumors are more likely to lack Smad4 and show a gene expression profile similar to cancer metastasis, which might explain the finding that these patients have a poorer prognosis. The stromal compartment has a putative role in resistance to gemcitabine. Despite the limitations in the number of patients and the overall lack of efficacy of gemcitabine treatment, the model seems to be predictive of response to gemcitabine in the metastatic setting. Given the complexities of generating these models and testing drugs in real time, it is unlikely that this approach will be broadly applicable to personalized cancer treatment, at least in PDA with its rapid clinical course and very few effective agents to address this refractory tumor. Moreover, our findings suggest that host microenviroments are better mimicked by orthotopic models. Although our data is limited to one patient, it suggest that orthotopic xenografts may be better predictors of response. Additional work is needed to continue developing and exploring the role of freshly generated xenografts in cancer research.