Systematic and Mechanism-based Approach to Rational Treatment Trials of Blood Cancer

German Cancer Research Center80 enrolled

Overview

This observational study evaluates if drug response testing can be performed within 7 days and analyzes the value of ex-vivo drug screening for hematological malignancies as a biomarker to predict outcome, clinical course and response to treatment.

Targeted treatments have revolutionized care of individual diseases. While a new generation of targeted drugs is emerging in leukemia and lymphoma it remains clinical reality that most genetic information is not used for therapeutic stratification. This is in part based on the shortcomings of traditional biomarker discovery within clinical trials, where throughput is limited in both, drug number and sample size. If it were possible to map the variable pathway dependencies and drug sensitivity patterns in individual patients it is likely to become an asset to identify genotype-phenotype associations, understand the underlying complexities of molecular networks and further precision medicine stratification. To link clinical outcome and ex-vivo drug response assays, the investigators systematically measure pathway sensitivity and resistance of primary tumor cells ex-vivo using a diverse compound library for individual patients in need of treatment. By systematically analyzing ex-vivo drug response patterns, tumors should be functionally grouped, by response phenotype. While for the purpose of this study selection of a specific treatment will not be based on ex-vivo drug response assays, clinical response- and follow-up data of patients will be prospectively collected in parallel.

Study Type

OBSERVATIONAL

Enrollment

Conditions

Hematologic Diseases Treatment

Interventions

ex-vivo drug response assayDIAGNOSTIC_TEST

drug sensitivity testing of primary patient derived cancer cells

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: 1. Diagnosis of a hematological malignancy: patients with leukemia, myeloma or lymphoma (e.g. ALL, AML, CLL, T-PLL, MCL, MM) who are in need of treatment and are willing to donate sufficient tumor material for ex-vivo drug sensitivity testing. 2. The treating physician needs to indicate treatment. 3. Measurable disease burden according to criteria as mention in section 3. 4. Treatment must be scheduled and the patient must be eligible for the planed treatment as judged by the treating physician. 5. Availability of 5x10e7 cells from peripheral blood draws, bone marrow aspirations or lymph node biopsies. 6. Patient's written informed consent present. 7. Ability to understand the nature of the trial and the trial related procedures and to comply with them. Exclusion Criteria: 1. Any condition, which precludes initiation of treatment (e.g. breast feeding, pregnancy, infections, etc.) as judged by the treating physician. 2. Any coexisting medical or psychological condition that would preclude participation in the required study procedures, as judged by the treating physician. 3. No systemic cancer treatment except for cytoreductive pretreatment within 1 week of enrollment.

Locations (1)

University Hospital Heidelberg

Heidelberg, Germany

Outcomes

Primary Outcomes

Rate of completed drug sensitivity testing

Patients' sample (blood, bonemarrow aspirate, tissue of lymphnode) will collected on day 0. Ex-vivo drug sensitivity testing will be performed.

Time frame: 7 days

Secondary Outcomes

Accuracy of patients' drug response prediction by ex-vivo drug profiling

Ex-vivo drug sensitivity categorizes drugs as sensitive/not sensitive. Results will be compared with clinical outcome of patient (response vs. stable disease as defined in the clinical response definition by protocol

Time frame: from date of inclusion until date of best treatment response (latest 12 months)

Prediction of time to next treatment

prediction of time to next treatment by a mathematical model based on ex-vivo drug response testing

Time frame: from date of inclusion until change of treatment (latest 12 months)

Data from ClinicalTrials.gov

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