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  • 1
    In: Infection and Immunity, American Society for Microbiology, Vol. 83, No. 1 ( 2015-01), p. 28-38
    Abstract: Shiga toxins (Stx) are a family of cytotoxic proteins that can cause hemolytic-uremic syndrome (HUS), a thrombotic microangiopathy, following infections by Shiga toxin-producing Escherichia coli (STEC). Renal failure is a key feature of HUS and a major cause of childhood renal failure worldwide. There are currently no specific therapies for STEC-associated HUS, and the mechanism of Stx-induced renal injury is not well understood primarily due to a lack of fully representative animal models and an inability to monitor disease progression on a molecular or cellular level in humans at early stages. Three-dimensional (3D) tissue models have been shown to be more in vivo -like in their phenotype and physiology than 2D cultures for numerous disease models, including cancer and polycystic kidney disease. It is unknown whether exposure of a 3D renal tissue model to Stx will yield a more in vivo -like response than 2D cell culture. In this study, we characterized Stx2-mediated cytotoxicity in a bioengineered 3D human renal tissue model previously shown to be a predictor of drug-induced nephrotoxicity and compared its response to Stx2 exposure in 2D cell culture. Our results demonstrate that although many mechanistic aspects of cytotoxicity were similar between 3D and 2D, treatment of the 3D tissues with Stx resulted in an elevated secretion of the kidney injury marker 1 (Kim-1) and the cytokine interleukin-8 compared to the 2D cell cultures. This study represents the first application of 3D tissues for the study of Stx-mediated kidney injury.
    Type of Medium: Online Resource
    ISSN: 0019-9567 , 1098-5522
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    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2015
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  • 2
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 9, No. 1 ( 2019-08-01)
    Abstract: Although 70–80% of newly diagnosed ovarian cancer patients respond to first-line therapy, almost all relapse and five-year survival remains below 50%. One strategy to increase five-year survival is prolonging time to relapse by improving first-line therapy response. However, no biomarker today can accurately predict individual response to therapy. In this study, we present analytical and prospective clinical validation of a new test that utilizes primary patient tissue in 3D cell culture to make patient-specific response predictions prior to initiation of treatment in the clinic. Test results were generated within seven days of tissue receipt from newly diagnosed ovarian cancer patients obtained at standard surgical debulking or laparoscopic biopsy. Patients were followed for clinical response to chemotherapy. In a study population of 44, the 32 test-predicted Responders had a clinical response rate of 100% across both adjuvant and neoadjuvant treated populations with an overall prediction accuracy of 89% (39 of 44, p  〈  0.0001). The test also functioned as a prognostic readout with test-predicted Responders having a significantly increased progression-free survival compared to test-predicted Non-Responders, p = 0.01. This correlative accuracy establishes the test’s potential to benefit ovarian cancer patients through accurate prediction of patient-specific response before treatment.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
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  • 3
    In: Cells, MDPI AG, Vol. 10, No. 12 ( 2021-12-02), p. 3400-
    Abstract: Li Fraumeni syndrome (LFS) is a hereditary cancer predisposition syndrome caused by germline mutations in TP53. TP53 is the most common mutated gene in human cancer, occurring in 30–50% of glioblastomas (GBM). Here, we highlight a precision medicine platform to identify potential targets for a GBM patient with LFS. We used a comparative transcriptomics approach to identify genes that are uniquely overexpressed in the LFS GBM patient relative to a cancer compendium of 12,747 tumor RNA sequencing data sets, including 200 GBMs. STAT1 and STAT2 were identified as being significantly overexpressed in the LFS patient, indicating ruxolitinib, a Janus kinase 1 and 2 inhibitors, as a potential therapy. The LFS patient had the highest level of STAT1 and STAT2 expression in an institutional high-grade glioma cohort of 45 patients, further supporting the cancer compendium results. To empirically validate the comparative transcriptomics pipeline, we used a combination of adherent and organoid cell culture techniques, including ex vivo patient-derived organoids (PDOs) from four patient-derived cell lines, including the LFS patient. STAT1 and STAT2 expression levels in the four patient-derived cells correlated with levels identified in the respective parent tumors. In both adherent and organoid cultures, cells from the LFS patient were among the most sensitive to ruxolitinib compared to patient-derived cells with lower STAT1 and STAT2 expression levels. A spheroid-based drug screening assay (3D-PREDICT) was performed and used to identify further therapeutic targets. Two targeted therapies were selected for the patient of interest and resulted in radiographic disease stability. This manuscript supports the use of comparative transcriptomics to identify personalized therapeutic targets in a functional precision medicine platform for malignant brain tumors.
    Type of Medium: Online Resource
    ISSN: 2073-4409
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
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  • 4
    In: Cancer Immunology, Immunotherapy, Springer Science and Business Media LLC, Vol. 70, No. 3 ( 2021-03), p. 843-856
    Type of Medium: Online Resource
    ISSN: 0340-7004 , 1432-0851
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
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  • 5
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2020
    In:  Cancer Research Vol. 80, No. 16_Supplement ( 2020-08-15), p. 6018-6018
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 16_Supplement ( 2020-08-15), p. 6018-6018
    Abstract: Models that accurately reflect patient drug response are essential for the clinical design of personalized treatment plans and necessary for preclinical drug development. The advancement of predictive models for rare tumor types is impeded in part, by the relative scarcity of fresh tumor tissue available for study. To address the problem of tissue availability we have developed a label-free, combined functional and chemical selection method for the isolation of rare tumor cancer stem cells (CSC) and circulating tumor cells (CTC) from primary patient tissue and blood. Enriched cells were expanded as 3D microtumors under optimized conditions, validated as CSC through in vivo tumorigenesis studies, and characterized by correlative genomic, proteomic/phosphoproteomic, and phenomic analysis. We found isolation and expansion by this method yielded a source of primary cells suitable for live, cell-based predictive drug screening in multiple rare tumor derived models of neuroendocrine and mesenchymal origin, including locally or regionally advanced and metastatic SCLC, recurrent Merkel Cell Carcinoma, recurrent osteosarcoma and dermatofibrosarcoma protuberans. The 3DKUBE™ rare tumor assay was performed using validated CSCs cultured as perfused 3D microtumors (pMTs). Drug studies using the perfused, 3DKUBE™ rare tumor assay modeled individual patient response better than CSC-based or 3D static microtumor-based drug screens and thus demonstrate the effectiveness of this platform for predictive modeling of individual patient drug response. Taken together, this system provides a means of performing ex vivo drug response experiments on very small tissue samples, including core biopsies, with relevant results for patients. Citation Format: Melissa Millard, Kathryn M. Appleton, Ashley Elrod, Nicholas W. Bateman, Tamara Abulez, Kelly Conrads, Brian Hood, Thomas P. Conrads, Lillia M. Holmes, Teresa M. DesRochers. The perfused 3DKUBE™ rare tumor assay models in vivo drug response [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6018.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 6
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2020
    In:  Cancer Research Vol. 80, No. 16_Supplement ( 2020-08-15), p. 2244-2244
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 16_Supplement ( 2020-08-15), p. 2244-2244
    Abstract: Poly(ADP-ribose) polymerase (PARP) inhibitors have shown impressive clinical activities for ovarian cancer patients with BRCA mutations and have altered the paradigm for ovarian cancer treatment. Despite the utility that PARP inhibitors provide, intrinsic and acquired resistance often limit their effectiveness as a monotherapy, and therefore combination treatment is an attractive alternative for more durable responses. Checkpoint inhibitors have shown impressive efficacy in numerous solid tumor types, but have failed to show meaningful response in ovarian cancer. The role PARP inhibitors play as immune modulators to enhance checkpoint blockade efficacy has just recently emerged indicating that their combination with checkpoint inhibitors may be beneficial over either single agent. A recent phase I/II clinical trial by researchers at the Dana-Farber Cancer Institute demonstrated niraparib in combination with pembrolizumab produced complete or partial responses in 18% of patients with recurrent platinum-resistant ovarian cancer compared to less than a 5% response rate with PARP inhibitors alone (JAMA Oncol. 2019;5(8):1141-1149). Further understanding of the immune modulatory capacity of PARP inhibitors alone and in combination with checkpoint blockade will aid in the prediction of patient response or resistance to therapy. To address this lack in knowledge, we evaluated therapeutic responses to PARP inhibitors, checkpoint inhibitors, and combinations using ovarian cancer patient-derived 3D tumor spheroids. Primary tumor samples were evaluated for PD-L1 and EpCAM expression, and tumor infiltrating lymphocyte (TILs) populations were assessed for T-cell activation and CD8+:Treg ratios. Immune-mediated antitumor activity was investigated by monitoring changes in PD-L1 and MHC class-I expression in the tumor cell populations following PARP inhibition, pembrolizumab treatment, and in combination. The effects of pembrolizumab alone and in combination for enhanced T-cell mediated tumor cell killing were also tested. PD-L1 expression was associated with response to pembrolizumab, and pembrolizumab induced tumor cell killing was T-cell dependent. Despite detection of cytotoxic activity by olaparib and pembrolizumab as single agents, increased tumor cell killing was detected when olaparib and pembrolizumab were used in combination. In summary, we detected therapy related modulation of tumor cells as well as the immune composition which results in decreased tumor spheroid viability in the presence of PARP inhibition in combination with checkpoint blockade. These results highlight the potential benefit of PARP/checkpoint inhibitor combination therapy and of patient-derived 3D spheroids as a platform to help identify subsets of cancer patients who would likely respond to immunotherapies as single agents or in combination with other approved agents. Citation Format: Kathryn M. Appleton, Ashley Elrod, Stephen Shuford, Teresa M. DesRochers. PARP inhibition in combination with pembrolizumab enhances cytotoxicity in ovarian cancer patient-derived 3D spheroids [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2244.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 7
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 1121-1121
    Abstract: Glioblastoma (GBM) has a median survival of less than 2 years due to intra-tumoral heterogeneity, diffuse infiltrations of adjacent brain tissue, and a lack of effective therapies. Development of more efficacious therapies will require better GBM models for the testing and identification of novel agents. Towards this end, we have successfully developed a GBM 3D tissue model that can provide in vitro, patient-specific compound screening. Stable populations of glioma stem cells (GSC) from 24 of 41 patient samples have been successfully established and cultured long-term with minimal changes. To confirm stemness of the GSC population, we have successfully established a limiting-dilution series within SCID/Bg mice and characterized the resultant tumors. 4 of these lines have been used to establish patient-derived xenograft (PDX) models in mice. The original, primary patient tissue established GSC populations, and the resultant PDX tissues have been characterized by flow cytometry, IHC, RNA expression, NGS, and MGMT methylation status. With the goal of better modeling the patient tumor tissue in vitro, our GSC populations have also been used to establish complex microtumors within the KIYATEC 3DKUBE™ perfusion system, consisting of monoculture GSCs, GSCs co-cultured with human brain endothelial cells (HBECs), and GSCs co-cultured with HBECs and CD14+ peripheral blood mononuclear cells. Our monoculture microtumors consisting of only GSCs show a maintenance of GSC markers Nestin and Sox2 by both IHC and mRNA. Interestingly, when these cells are used to produce PDX, they up-regulate GFAP as a marker of differentiation that is not observed in the neurosphere or monoculture microtumor cultures. We have shown these 3D models to be viable for more than 1 month in perfusion and to be effective models for drug compound screening by dosing the microtumors on a weekly basis with temozolomide (TMZ). We have correlated TMZ response to MGMT methylation as reported both clinically and measured in vitro. Finally, In vitro drug response has been compared to both matched PDX in vivo drug response and the patient's clinical response to TMZ and MGMT methylation. Our data supports that this complex, 3D, patient-derived GBM model can be used to effectively screen, identify and characterize novel treatments of GBM. Citation Format: Ashley M. Smith, Melissa Millard, Lillia Holmes, Michael T. Lewis, Lacey E. Dobrolecki, Charles Kanos, Stephen Gardner, Philip Hodge, Fred Nelson, Michael Lynn, Jeff Edenfield, Christopher Corless, David Schammel, Howland E. Crosswell, Teresa M. DesRochers. Profiling patient-specific glioblastoma drug response in vitro using complex 3D microtumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1121.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
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  • 8
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2023
    In:  Cancer Research Vol. 83, No. 7_Supplement ( 2023-04-04), p. 2275-2275
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 7_Supplement ( 2023-04-04), p. 2275-2275
    Abstract: Biological therapies for the treatment of cancer are utilized for the same ultimate purpose as chemically derived cancer drugs, to induce tumor cell death. However, the differing mechanisms of action often make the evaluation of biologic drug efficacy more complex, requiring the support and/or recapitulation of functional immune components. Biologics also have different limitations that can govern their efficacy such as their large size potentially impeding sufficient penetration to target sites and in the case of live biotherapeutic products, the need to maintain sustained function, or persistence, by resisting immunosuppression by the tumor microenvironment. Preclinical testing of biologics is often confined to cell lines which lack an immune system and mouse models which are expensive, time consuming, and poor proxies for the human immune system. To address these issues, we have developed ex vivo 3D spheroid platforms to measure the efficacy of three types of biologics: antibody-drug conjugates (ADCs), bispecific antibodies, and chimeric antigen receptor (CAR) T-cells. Primary cells from cancer patients or from patient-derived xenografts were evaluated for the expression of the biologic target molecule then cultured to form 3D spheroids. Spheroid models were validated for the evaluation of antibody-based therapies by determining sufficient diffusion of antibodies to target sites. For ADC testing, cell death was measured in a plate-based read-out following treatment with the ADC trastuzumab deruxtecan, and the cytotoxic efficacy of the ADC was compared to trastuzumab alone or free exatecan. Differences in killing kinetics and the maximum efficacy of the ADC were determined compared to the other tested agents. HER2 inhibition was evaluated through changes in constitutive downstream signaling. Two biologics with the same molecular target, a bispecific antibody targeting carcinoembryonic antigen (CEA) on tumor cells and CD3 on T-cells, as well as a CAR T-cell product targeting CEA were also evaluated. Following treatment with the bispecific, tumor cell viability was detected using flow cytometry and changes in T-cell activation were measured via cytokine secretion using primary colorectal cancer models. Importantly, bispecific antibody efficacy was dependent upon the presence of T-cells. Finally, CAR T-cell mediated tumor cell killing was detected using a fluorescent image-based approach. Collectively, this work establishes a model for testing multiple classes of drugs in a 3D ex vivo model that can be used to advance preclinical drug development and evaluate mechanisms of action of diverse drug classes in a physiologically relevant model. Citation Format: Katy A. Lassahn, Ashley K. Elrod, Aaron L. Carlson, Natalie A. Dance, Melissa Millard, Michael J. Wick, Teresa M. DesRochers, Kathryn M. Appleton. Preclinical testing of therapeutic biologics using patient-derived 3D spheroids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2275.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
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  • 9
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2019
    In:  Cancer Research Vol. 79, No. 13_Supplement ( 2019-07-01), p. 2240-2240
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 2240-2240
    Abstract: Personalized medicine in cancer typically refers to the use of genetics and/or biomarkers to direct the use of targeted therapy or predict overall prognosis based on statistical probability. Therapy selection and predictions are not based on any physical interaction between a patient’s tumor cells to clinically relevant therapies based on their disease indication. We have developed an assay using 3D cell culture that exposes a patient’s tumor cells to standard of care chemotherapies for the purpose of predicting their clinical response to potential treatment options prior to treatment. We have analytically validated this assay enabling its performance under CLIA regulations as a Laboratory Developed Test (LDT) and prospectively validated it against clinical patient outcome in ovarian cancer. The test utilizes excess fresh patient tissue acquired during standard of care surgical debulking or biopsy and returns results within 7 business days of tissue receipt, typically well before the start of chemotherapy. Previously, we have shown in newly diagnosed ovarian cancer, the test has an accuracy of 87% with a specificity of 100% and a sensitivity of 84% in the prediction of standard first-line carboplatin/taxol combination therapy using the biomarker CA-125 and CT imaging as clinical readouts. We have similar results for the prediction of response to neoadjuvant therapy following laparoscopic biopsy using RECIST criteria. We have now analytically validated the assay in glioblastoma (GBM) and rare tumors. Preliminary clinical validation in GBM has shown the ability of the test to accurately predict response to standard first-line temozolomide using RANO criteria as the clinical readout. Rare tumor validation has included a panel of 12 drugs covering those used as standard of care for most rare tumors. Aspects of validation have included examining inter- and intra-assay variability and drug panel response in a defined number of rare tumors including sarcomas, neuroendocrine, and other tumors such as Sertoli-Leydig. In breast cancer, we have validated the assay for the use of a single diagnostic biopsy core as the tissue source and established preliminary clinical validation against standard of care such as doxorubicin and paclitaxel with pathologic complete response (pCR) as the clinical readout. We are further validating the predictive ability of the test in newly diagnosed and relapsed ovarian cancer and GBM patients (clinical trial NCT03561207). With demonstrated accurate prediction of patient specific response, the transition to cancer therapy selection based on physical evidence vs statistical probability would significantly improve patient outcomes and benefit economic stakeholders. Citation Format: Stephen Shuford, Christine Wilhelm, Ashley M. Smith, Melissa Rayner, Jeremy Stuart, Lillia Holmes, Matt Gevaert, Howland E. Crosswell, Teresa M. DesRochers. Redefining personalized medicine by drug response profiling of patient-derived spheroids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2240.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
    detail.hit.zdb_id: 2036785-5
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  • 10
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 53-53
    Abstract: Standard first-line treatment of newly diagnosed Glioblastoma (GBM) is primarily radiotherapy and Temozolomide (TMZ) with a strong NCCN recommendation of enrollment in clinical trials. The only biomarker that can currently provide a stratification of strong and poor responders to standard of care is methylation of MGMT which indicates a median PFS of 10.3 months for methylated patients and 5.3 months for unmethylated patients. Development of patient-specific in vitro models of GBM for rapid testing of therapeutic options may yield more efficacious therapies and faster, more accurate assignation of therapies to each patient. To that end, we have developed a multi-faceted, patient-based 3D GBM model with modularity that facilitates increasing levels of model complexity such as the inclusion of immune cell components. Stable populations of glioma stem cells (GSC) from 24 of 41 patient samples have been successfully established, verified for stemness through limited dilution in in vitro and in vivo studies, and cultured long-term with minimal molecular changes, as determined from genetic analyses including RT-PCR arrays and MGMT methylation status, flow cytometry, and IHC. These cell populations have been used to establish and validate our 3D model system as well as generate comparable patient-derived xenografts (PDX). KIYATEC’s 3D microtumor in our 3DKUBE™ perfusion system provides a moderate throughput, dynamic system that is easily controlled to establish complex microtumors. GSC cell populations were cultured in monoculture only, co-cultured with human brain endothelial cells (HBEC), and tri-cultured with HBEC and CD14+ peripheral blood mononuclear cells (PBMC). Three microtumors were characterized by drug response to TMZ and axitinib, IHC, and molecular profiling including RNA expression and MGMT methylation status. Interestingly, increasing the complexity of the microtumor was capable of reestablishing the primary tumor MGMT methylation status if it were lost during culturing. We also generated PDX models from the same 3 patient tumor tissues as the above 3D models. PDX are a low throughput, time consuming, and expensive model that are still utilized for many systemic drug response studies and therefore a good comparator to the 3D tissue models we established. In vitro drug response in the 3D tissue models has been compared to both the matched PDX in vivo drug response and the patient’s clinical response to TMZ and MGMT methylation. Our data supports that KIYATEC’s complex patient-derived GBM model can be successfully used to identify, screen, and characterize novel treatments of GBM. Citation Format: Ashley M. Smith, Lillia Holmes, Lacey E. Dobrolecki, Charles Kanos, Stephen Gardner, Philip Hodge, Michael Lynn, Jeff Edenfield, Michael T. Lewis, Howland E. Crosswell, Teresa M. DesRochers. Ex vivo models of glioblastoma: a comparison of 3D tissues and patient-derived xenografts to clinical response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 53.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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