Report

Teaser, summary, work performed and final results

Periodic Reporting for period 2 - AVATAR (Integrating Genomics and Avatar Mouse Models to Personalize Pancreatic Cancer Treatment)

Teaser

Pancreatic cancer adenocarcinoma (PDAC) remains one of the most lethal cancers in humans. In contracts to other tumor types such as lung cancer and melanoma, for example, in which significant progress has been made, very few advances have occurred in PDAC. Indeed, so far...

Summary

Pancreatic cancer adenocarcinoma (PDAC) remains one of the most lethal cancers in humans. In contracts to other tumor types such as lung cancer and melanoma, for example, in which significant progress has been made, very few advances have occurred in PDAC. Indeed, so far, neither precision medicine nor immune-oncology have resulted in meaningful improvement in patient’s outcome. This project aims to implement a comprehensive approach to precision medicine in PDAC by incorporating genomic and bio-informatic analysis of tumor biopsies and circulating cell free DNA as well as modeling the disease in Avatar mouse models and, more recently, in patient derived organoids. The specific research questions include assessment of the impact of this action in patient outcome, the further characterization of the PDAC genome and the development of methods to monitor the evolution of the disease. The project is based on an ongoing randomized clinical trial which is currently open for recruitment in seven Hospitals in Spain and the US. We expect the results of this trial will provide unbiassed information as well as a path for implementing precision medicine in PDAC that, if successful, will contribute to the control of this disease with its corresponding positive impact in society.
The long-term goal of our research group is to improve the outcome of patients with PDAC. The principal objective of this research application is to develop a system for individualized treatment of patients with this disease. The central hypothesis of the proposed research, which is substantiated by our preliminary data, is that the response of tumors to specific drugs is related to specific molecular and biological features in cancer cells and that this information can be used for individualized patient treatment. To achieve these goals, we will perform a randomized clinical trial in patients with metastatic PDAC to compare the outcome of patients treated with conventional treatment with those treated with a personalize treatment approach. The personalized approach arm will include generation of an Avatar mouse model, from each patient as well as a full genome analysis for target discovery with subsequent therapeutic validation in the mouse model and will develop personalize monitoring approaches.
This proposal is innovative because it integrates two powerful approaches for personalize medicine, next generation sequencing (NGS) with Avatar mouse modelling to address a significant question, which is the development of individualized treatment strategies for patients with PDAC. In addition, we will take advantage of the tumor samples collected and models generate to perform an in depth genomic analysis and functional validation of newly discovered targets in metastatic PDAC. We expect this approach will yield several important outcomes including the validation of the integrated approach for PDAC treatment, the generation of advanced genetic knowledge of metastatic PDAC as well as the generation of new mouse models of metastatic PDAC for future research.

Work performed

1. STATE OF THE ART

1A. Pancreatic Cancer
Pancreatic cancer (PDAC) is a frequent and deadly disease. In 2018, it is estimated that 55,440 patients will be diagnosed (13.2% of all new cancer cases) and that 44,330 patients will succumb (7.3% of all cancer related deaths) in the US. In addition, PDAC is expected to become the second most common cause of cancer related death by 2020 (1, 2). At the time of diagnoses, only 20-30% of patients with PDAC are candidates for surgical resection, the only curative option. Seventy percent of these patients, however, will develop disease progression shortly after resection. For those patients, as well as those who are diagnosed with more advanced disease, there is no effective treatment and invariably die of disease progression with a median survival of less than 1 year (3). The current management of advanced PDAC consist of systemic chemotherapy. The two regimens more commonly used are FOLFIRINOX and gemcitabine + nab-paclitaxel (4,5). In a randomized trial, the former regimen was superior to single agent gemcitabine resulting in a median survival close to one year. This improvement, however, came with a higher rate of grade 3-4 toxicities. Our group was involved in the development of the combination regimen of nab-paclitaxel and gemcitabine. In a series of studies ranging from phase 1 to phase 3 we showed that patients treated with the combined regimen have a better survival (5,6). These studies led to the approval of nab-paclitaxel for the treatment of patients with advanced PDAC. Initial studies suggested that SPARC expression in the stroma of tumor tissues was associated with better outcome. However, analysis of samples collected from the phase 3 studies as well as additional preclinical data does not support the role of SPARC expression as a marker of efficacy for nab-paclitaxel (7). Therefore, at present time, no biomarker to predict treatment response has reached the clinic and patients are treated in a one size fits all approach. Once patients developed disease progression, they are either enrolled in clinical studies with new agents or treated with additional standard chemotherapy regimens. The outcome of patients treated with second line chemotherapy is poor, with less than 20 % one year survival (8).

1B. Genomic Understanding of PDAC
The genomic landscape of PDAC is starting to be elucidated. A study conducted at Johns Hopkins University in which the applicant participated, performed the first systematic analyses of PDAC genetics in 24 PDAC samples (9). The results of this study showed that PDAC is a genetically complex disease. While most patients had alterations in the TP53, KRAS, p16/CDKN2A and SMAD4 genes, there were a large number of additional mutations in other genes averaging 63 mutations per patient. In general, these mutations alter the functioning of 12 main signaling pathways believe to be critical in PDAC genesis and progression. In addition, it became obvious that PDAC is a heterogeneous disease. Indeed, there were no two identical patients and a significant fraction of important genes were mutated in only one or very few patients. A more recent study in 142 primary PDAC tumors further supports the genetic complexity of the disease (10). Subsequent work has shown that this heterogeneity is also present between the primary and metastatic tumors indicating that there is a genetic evolution process from the primary tumor to the fully developed metastatic disease (11,12). It should be noted however that a) these studies have been performed in primary lesions and, as there are data supporting a genetic drift in metastatic lesions, a more comprehensive analysis of metastasis would be important; b) the current data is mostly descriptive with no information regarding the implications of genomic alterations with prognosis and response to treatment and c) because most of the studies have been performed in store tissues, there is little functional validat

Final results

This work is still ongoing and we cannot gauge at the present time if this approach will lead to changes in the management of patients with PDAC beyond the current state of the art. We have learnt, however, that genetic analysis does not appear to be very useful in therapy selection in PDAC as most of the mutations we find are not actionable. In addition, we have learn that Avatar models, because the time it takes to be generated and tested, cannot be used in many patients for therapy selection. Thus, we are incorporating new approaches such as more extensive and deep sequencing to explore rate but targetable mutations as well as phenotypic screening using organoid models. We expect that these interventions will permit a truly personalize medicine approach that will change the management of PDAC.