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| ID | Type | Description | Link |
|---|---|---|---|
| 1830/2015 | Other Identifier | ethic committee of Medical University Vienna |
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Patients with relapsed/ refractory acute leukemia and relapsed/ refractory aggressive lymphoma harboring an activating genetic alteration (gene mutation, gene fusion) or drug-able biomarker / activated signal transduction pathway and resistant to any approved treatment modality will be eligible for this study.
The investigators aim to combine DNA sequencing-based molecular profiling with an ex vivo high-throughput drug screening strategy. For the latter method, viable cells are obtained from the individual patient's lymphoma or leukemia in order to determine i)the expression of relevant therapeutic target molecules and ii)the ex vivo response of the patient's cancer cells to a panel of agents with anticancer activity. In addition, analysis of tumor stroma cells will provide information about the differential target expression and cellular sensitivity aiming at the evaluation of a therapeutic safety window. Thereby, biological material will have to be accessed within 4 weeks before onset of individualized treatment (real-time biopsy). Bioinformatic data-management based on a Bayesian statistical approach will support individualized treatment decisions in this controlled clinical approach.
Background and rationale for the trial Etiological concepts on cancer development, malignant growth and tumor propagation have led to the discovery of various molecular driver mechanisms. Based on these advances, medical oncology has started to enter an era of individualized medicine where treatment selection is becoming tailored to drug-able molecular pathways. This individualized treatment concept is mainly based on molecular and genetic characterization of the tumors including biomarker technology, which allow us to align the most appropriate treatment according to the patient's disease. Although there is a general acceptance towards such individualized approach thereby stratifying and subgrouping patients to improve the quality of clinical care in oncology, molecular profiling has just started to assist prediction of the drug's clinical benefit by identifying the most responsive patient subgroup. Recently, excellent demonstrations of the utility of prognostic and/or predictive biomarkers have emerged. Von Hoff and co-workers have recently demonstrated that molecular profiling of patients' tumors is an efficient approach to identify potential targets and select treatments for their treatment-refractory cancers(Von Hoff, Stephenson et al. 2010). Such a tailored treatment strategy revealed to be an effective approach to increase progression free survival (PFS), when compared to the patients' most recent standard treatment regimen. Another example for individualized treatment of patients is given by the recently published BATTLE trial (Biomarker-integrated Approaches of Targeted Therapy for Lung Cancer Elimination), a prospective biomarker and biopsy driven trial in pretreated non-small cell lung cancer (NSCLC) patients (Kim, Herbst et al. 2011). By this Bayesian approach, the authors demonstrated that targeting individually analyzed molecules of the patient's tumor might represent an efficient therapeutic approach in the treatment of an incurable disease. While these examples suggest a benefit for individual tumor characterization for selection of a tailored treatment concept, currently novel targeted agents in the treatment of cancer are rather approved for a certain subtype of cancer, but not for patients based on the expression or activity of respective target lesions. Therefore, the need of an extension of clinical protocols focusing on molecular profile-based treatment decisions, rather than on anatomic cancer-subtypes is mandatory. Based on this concept the current protocol was designed. The investigators hypothesize that molecular profiling of a patient's tumor might not only predict treatment response, but also leads to an individualized treatment protocol resulting in clinical benefit for the individual patient. Therefore, this project aims to assess the feasibility of an individualized treatment concept for pre-defined patient's benefit.
Design, methodology, statistical considerations and organization The Medical University of Vienna will be clinical sponsor and clinical center of this investigator-initiated open-label single center single-arm, exploratory phase II study. The individualized treatment concept is determined to be biopsy-mandated and biomarker-based. Bio-data analysis will be supported by a software, which is generated by the Center of Medical Statistics, Informatics and Intelligent Systems.
Study design and methodology Patients with relapsed/ refractory acute leukemia and relapsed/ refractory aggressive lymphoma harboring an activating genetic alteration (gene mutation, gene fusion) or drug-able biomarker / activated signal transduction pathway and resistant to any approved treatment modality will be eligible for this study.
The investigators aim to combine DNA sequencing-based molecular profiling with an ex vivo high-throughput drug screening strategy. For the latter method, viable cells are obtained from the individual patient's lymphoma or leukemia in order to determine i)the expression of relevant therapeutic target molecules and ii)the ex vivo response of the patient's cancer cells to a panel of agents with anticancer activity. In addition, analysis of tumor stroma cells will provide information about the differential target expression and cellular sensitivity aiming at the evaluation of a therapeutic safety window. Thereby, biological material will have to be accessed within 4 weeks before onset of individualized treatment (real-time biopsy). Bioinformatic data-management based on a Bayesian statistical approach will support individualized treatment decisions in this controlled clinical approach.
Number of patients. A sample size of 49 patients achieves ≥ 80% power to detect a difference of 15% between the null hypothesis proportion P0 (PFS ratio ≥ 1.3) = 10% and the alternative proportion P1(PFS ratio ≥ 1.3) = 25% using a one-sided exact binomial test at a significance level of 0.0250. The null hypothesis can be rejected, if at least 10 out of 50 patients treated show a PFS ratio ≥ 1.3. The investigators therefore aim to enroll 49 leukemia patients and 49 lymphoma patients.
Target population. Patients with relapsed/ refractory acute leukemia and relapsed/ refractory aggressive lymphoma after standard treatment. Standard treatment is defined according to actual National Comprehensive Cancer Network (NCCN) (http://www.nccn.org/professionals/physician\_gls/f\_guidelines.asp) and/or local guidelines. 49 acute leukemia subjects and 49 lymphoma subjects will be screened for enrolment in the trial. Deviations from inclusion criteria are not allowed because they can potentially jeopardize the scientific integrity of the study, regulatory acceptability or subject safety. Therefore, adherence to the criteria as specified in the protocol is essential. Inclusion criteria as well as exclusion criteria must be respected.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| ngFDS selected treatment | Treatment with commercially available treatments (per package insert instructions) chosen via next-generation functional drug screening (ngFDS). |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| ngFDS selected treatment | Drug | Treatment based on next-generation functional drug screening (ngFDS). Treatment with commercially available treatments (per package insert instructions) selected by functional drug screening. For drug screening tumor cells from bone marrow aspirates, peripheral blood, pleural effusion, or excised lymph node samples are purified over Ficoll gradient (bone marrow, peripheral blood, pleural effusion) (GE healthcare) or homogenized and filtered (lymph tissue). |
| Measure | Description | Time Frame |
|---|---|---|
| progression-free survival | To compare progression-free survival using a treatment regimen selected by molecular profiling with progression-free survival for the most recent regimen the patient has progressed on. The treatment concept is deemed for clinical benefit for the individual patient who has a PSF ratio (PSF on molecular profiling-based therapy/PSF on prior therapy) of ≥ 1.3. For this purpose we will reject the null hypothesis, which is defined as follows: ≤ 15% of patients would have a PFS ratio of ≥ 1.3. Thus, the individual patient is his own control. For tumor types with high numbers of patients per cohort, the overall response rate (ORR) will be evaluated. | From date of randomization until the date of first documented progression or date of death from any cause, whichever came first, assessed up to 100 months |
| Measure | Description | Time Frame |
|---|---|---|
| overall response rate | overall response rate (ORR: achieving either CR or PR). For lymphoma patients' responses were classified as complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD) according to the criteria proposed by the International Workshop for malignant lymphoma. For leukemia patients, responses were assessed following the response criteria defined by the recommendations of the European Leukemia net. |
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Inclusion Criteria:
Exclusion Criteria:
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Patients with relapsed or refractory aggressive hematological malignancy lacking further standard treatment.
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| Name | Affiliation | Role |
|---|---|---|
| Philipp B Staber, MD, PhD | Medical University of Vienna, Department of Medicine I, Division of Hematology and Hemostaseology | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Medical University Vienna | Vienna | 1090 | Austria |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 37783805 | Derived | Liebers N, Bruch PM, Terzer T, Hernandez-Hernandez M, Paramasivam N, Fitzgerald D, Altmann H, Roider T, Kolb C, Knoll M, Lenze A, Platzbecker U, Rollig C, Baldus C, Serve H, Bornhauser M, Hubschmann D, Muller-Tidow C, Stolzel F, Huber W, Benner A, Zenz T, Lu J, Dietrich S. Ex vivo drug response profiling for response and outcome prediction in hematologic malignancies: the prospective non-interventional SMARTrial. Nat Cancer. 2023 Dec;4(12):1648-1659. doi: 10.1038/s43018-023-00645-5. Epub 2023 Oct 2. | |
| 29153976 |
| Label | URL |
|---|---|
| Publication of Interimsanalysis | View source |
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| ID | Term |
|---|---|
| D019337 | Hematologic Neoplasms |
| ID | Term |
|---|---|
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D006402 | Hematologic Diseases |
| D006425 | Hemic and Lymphatic Diseases |
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| 4 months |
| Derived |
| Snijder B, Vladimer GI, Krall N, Miura K, Schmolke AS, Kornauth C, Lopez de la Fuente O, Choi HS, van der Kouwe E, Gultekin S, Kazianka L, Bigenzahn JW, Hoermann G, Prutsch N, Merkel O, Ringler A, Sabler M, Jeryczynski G, Mayerhoefer ME, Simonitsch-Klupp I, Ocko K, Felberbauer F, Mullauer L, Prager GW, Korkmaz B, Kenner L, Sperr WR, Kralovics R, Gisslinger H, Valent P, Kubicek S, Jager U, Staber PB, Superti-Furga G. Image-based ex-vivo drug screening for patients with aggressive haematological malignancies: interim results from a single-arm, open-label, pilot study. Lancet Haematol. 2017 Dec;4(12):e595-e606. doi: 10.1016/S2352-3026(17)30208-9. Epub 2017 Nov 15. |