Integrated Patient-Derived Models Delineate Individualized Therapeutic Vulnerabilities of Pancreatic Cancer

Abstract

Pancreatic ductal adenocarcinoma (PDAC) harbors the worst prognosis of any common solid tumor, and multiple failed clinical trials indicate therapeutic recalcitrance. Here we use exome sequencing of patient tumors and find multiple conserved genetic alterations. However, the majority of tumors exhibit no clearly defined therapeutic target. High-throughput drug screens using patient-derived cell lines found rare examples of sensitivity to monotherapy, with most requiring combination therapy. Using PDX models, we confirmed the effectiveness and selectivity of the identified treatment responses. Out of greater than 500 single and combination drug regimens tested, no single treatment was effective for the majority of PDAC tumors, and each case had unique sensitivity profiles that could not be predicted using genetic analyses. These data indicate a shortcoming of reliance on genetic analysis to predict efficacy of currently available agents against PDAC, and that sensitivity profiling of patient-derived models could inform personalized therapy design for PDAC.

Rapid identification of optimal drug combinations for personalized cancer therapy using microfluidics

“…http://dx.doi.org/10.1101/093906 doi: bioRxiv preprint first posted online Dec. 14, 2016; 3 approach for treatment of pancreatic cancer 6 . However, strategies to identify effective combinations are still in their infancy 14 .…”

“…While there have been some impressively successful examples 4,5 , cancer genomics is generally very complex and, despite the increasing knowledge on occurring mutations, there is still limited understanding on how they affect drug response 6 . Multiple efforts have been devoted to the large--scale in vitro screening of drugs across cell lines [7][8][9] that have proven useful to identify some genomic markers associated with drug response.…”

“…Due to these limitations, genomics data has to be supplemented with other information in order to optimally guide the treatment for each patient, and systems for phenotypic stratification are urgently needed 6,12 . The need for new approaches is even more acute for the application of drug combinations.…”

Patient-Derived-Tumor-Xenograft: modeling cancer for basic and translational cancer research

“…Clones evolve dynamically in space and time following principles of Darwinian evolution, generating remarkable features, such as drug resistance and metastasis. The existence of intratumoral subclone diversity elucidates the enormous flexibility of cancer cells in response to different stresses, including chemotherapy [18,40,41]. This heterogeneity is largely lost when tumor cells are propagated in vitro, a scenario that facilitates the emergence of few or a single dominant clone that most efficiently fits to the new in vitro conditions.…”

Pancreatic cancer: a mechanobiology approach

“…Very recent research suggests genetic sequencing of tumours is insufficient for determining personalised drug targets; thus patient derived models need to be empirically tested [24]. Molecular characterisation of tumours also may open new avenues for personalised treatment but naturally raises the question whether stroma-targeting strategies in PDAC are more or less effective depending on the underlying mutational spectrum and subtype of the tumour.…”