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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 models requiring combination therapy. Using PDX models, we confirmed the effectiveness and selectivity of the identified treatment responses. Out of more 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 suggest that sensitivity profiling of patient-derived models could inform personalized therapy design for PDAC.

SUBMITTER: Witkiewicz AK

PROVIDER: S-EPMC5287055 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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

Witkiewicz Agnieszka K AK Balaji Uthra U Eslinger Cody C McMillan Elizabeth E Conway William W Posner Bruce B Mills Gordon B GB O'Reilly Eileen M EM Knudsen Erik S ES

Cell reports 20160804 7

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 models requiring combination thera ...[more]

PMID: 27498862

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Project description:Background and aimsPancreatic cancer is the seventh leading cause of cancer-related deaths worldwide. Checkpoint immunotherapy has not yet shown encouraging results in pancreatic cancer possibly because of a poor immunogenicity and/or an immune suppressive microenvironment. The aim of this study was to develop patient-derived xenograft (PDX) models, compare their genetics to the original biopsies, and assess if autologous tumor-infiltrating lymphocytes (TILs) would have antitumoral activity in pancreatic cancer.MethodsWe subcutaneously transplanted tumors from 29 patients into NOG mice to generate PDX models. We established TIL cultures and injected them into PDX mice. We analyzed histology and genetics of biopsies and PDX tumors.ResultsTumor growths were confirmed in 11 of 29 transplantations. The PDX tumors histologically resembled their original biopsies, but because stromal cells in the PDX model tumors were from mouse, their gene expression differed from the original biopsies. Immune checkpoint ligands other than programmed death ligand-1 (PD-L1) were expressed in pancreatic cancers, but PD-L1 was rarely expressed. When it was expressed, it correlated with tumor take in PDX models. One of the 3 tumors that expressed PD-L1 was an adenosquamous cancer, and another had a mismatch repair deficiency. TILs were expanded from 6 tumors and were injected into NOG or human interleukin-2 transgenic-NOG mice carrying PDX tumors. Regression of tumors could be verified in human interleukin-2 transgenic-NOG mice in 3 of the 6 PDX models treated with autologous TILs, including the adenosquamous PDX model.ConclusionPDX models of pancreatic cancer can be used to learn more about tumor characteristics and biomarkers and to evaluate responses to adoptive cell therapy and combination therapies. The major benefit of the model is that modifications of T cells can be tested in an autologous humanized mouse model to gain preclinical data to support the initiation of a clinical trial.

Project description:Simple Summary For personalized oncology, it is crucial to develop appropriate patient-derived tumor models that allow individualized validation of the most effective cancer therapy. The objective of this study was to develop and characterize a new patient-derived ovarian cancer tumor model composed of patient-derived microtumors (PDM) and autologous tumor-infiltrating lymphocytes (TIL). In contrast to other preclinical tumor models, such as patient-derived organoids, PDM are generated within 24 h from fresh ovarian tumor samples. From immunohistochemical comparison with the original primary tumor, we conclude that the histopathological features of the original tumor are essentially preserved. Importantly, we successfully identified treatment-sensitive and treatment-resistant tumor models for standard platinum-based therapy by reverse-phase protein array (RPPA) analysis of PDM. Furthermore, we were able to evaluate the efficacy of cancer immunotherapy by co-culturing PDM and autologous TILs. PDM and TILs may therefore serve as a preclinical platform to identify individualized, tailored cancer treatments in the future. Abstract In light of the frequent development of therapeutic resistance in cancer treatment, there is a strong need for personalized model systems representing patient tumor heterogeneity, while enabling parallel drug testing and identification of appropriate treatment responses in individual patients. Using ovarian cancer as a prime example of a heterogeneous tumor disease, we developed a 3D preclinical tumor model comprised of patient-derived microtumors (PDM) and autologous tumor-infiltrating lymphocytes (TILs) to identify individual treatment vulnerabilities and validate chemo-, immuno- and targeted therapy efficacies. Enzymatic digestion of primary ovarian cancer tissue and cultivation in defined serum-free media allowed rapid and efficient recovery of PDM, while preserving histopathological features of corresponding patient tumor tissue. Reverse-phase protein array (RPPA)-analyses of >110 total and phospho-proteins enabled the identification of patient-specific sensitivities to standard, platinum-based therapy and thereby the prediction of potential treatment-responders. Co-cultures of PDM and autologous TILs for individual efficacy testing of immune checkpoint inhibitor treatment demonstrated patient-specific enhancement of cytotoxic TIL activity by this therapeutic approach. Combining protein pathway analysis and drug efficacy testing of PDM enables drug mode-of-action analyses and therapeutic sensitivity prediction within a clinically relevant time frame after surgery. Follow-up studies in larger cohorts are currently under way to further evaluate the applicability of this platform to support clinical decision making.

Dataset Information

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

Publications

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

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