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string(346) "NCT01855750 - A Randomized, Double-blind, Placebo-controlled Phase 3 Study of the Bruton's Tyrosine Kinase (BTK) Inhibitor, PCI-32765 (Ibrutinib), in Combination With Rituximab, Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone (R-CHOP) in Subjects With Newly Diagnosed Non-Germinal Center B-Cell Subtype of Diffuse Large B-Cell Lymphoma"
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["project_title"]=>
string(78) "Outcome-comparison between different DLBCL first-line data sets with RCHOP + X"
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string(651) "Treating patients with diffuse-large B-cell lymphoma (DLBCL) is a very difficult task since the disease is very heterogeneous and undergoes a series of biological changes under treatment. We ran a phase I/II clinical trial, ImbruVeRCHOP, between 2017 and 2024, and treated DLBCL patients with RCHOP + Ibrutinib + Bortezomib and perfromed intensive molecular characterizations and re-biopsies under treatment to determine which subset of patients benefits from this combination. We would like to validate our findings on a molecular level and therefore apply for data access of the PHOENIX trial (DLBCL with RCHOP +/- Ibrutinib, NCT01855750).
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string(215) "S.D. has no financial relationships with Janssen-Cilag. C.S. receives honoraria for medical advice from Janssen-Cilag and coordinates clinical research (namely the ImbruVeRCHOP trial) partly funded by Janssen-Cilag."
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string(1614) "Background: ImbruVeRCHOP trial [1] treated DLBCL patients with RCHOP + Ibrutinib + Bortezomib, and performed re-biopsies under treatment with molecular profiling.
Objective: To validate our findings, we aim to compare our clinical and molecular data in a larger data set of DLBCL patients with RCHOP +/- Ibrutinib treatment.
Study Design: Cohort study.
Participants: 36 patients from our phase I/II trial were included for molecular characterization; the preferred validation cohort would be the 838 study patients of the PHOENIX trial.
Primary and Secondary Outcome Measures: 1)clinical outcome, 2)clinical risk stratifications using clinical parameters, IHC, mutational and gene expression profiles, 3) signatures for treatment response (pre-described) and new ones from our own data set, 4) prediction markers from IHC, DNA/WES and RNA-Seq, 5) multi-Omics profiling/markers pre-treatment vs. under treatment.
Statistical Analysis: The clinical and genetic characteristics are dichotomized and analyzed using descriptive statistics. The characteristics between the groups 1) RCHOP, 2) RCHOP + ibrutinib, 3) RCHOP + ibrutinib + bortezomib are compared using the chi-square or the Fisher exact test. Survival will be depicted using Kaplan-Meier plots (PFS, DFS, OS). Statistical analysis to identify differences between relevant subgroups will be performed using the Log-Rank/Mantle-Cox test. Further biostatistical algorithms, new deep learning-based and off-the-shelf methods (Random Forests, Support Vector Machines) will be performed accordingly for every molecular analysis."
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string(1560) "To date, we clinicians still find it difficult to select the right therapy for DLBCL patients at increased risk. We conducted an all-comer, investigator-initiated phase I/II trial at Charité and 11 centers in Germany and Austria, to identify signatures and markers for DLBCL patients with targeted treatment additions (ImbruVeRCHOP, ClinicalTrials.gov identifier: NCT03129828). Using an all-comers approach, but subjecting patients to another lymphoma biopsy acutely under first-cycle immune-chemo drug exposure, ImbruVeRCHOP seeks to identify an unbiased molecular responder signature that marks diffuse large B-cell lymphoma patients at risk and likely to benefit from this regimen as a double, proximal and distal B-cell receptor/NF-κB-co-targeting extension of the current R-CHOP standard of care. First-in human treatment with RCHOP+Ibrutinib as well as Bortezomib was well tolerated and the patients showed good response. For these signals to be more relevant for other patients in the future, validation in larger cohorts is needed; in addition to further clinical studies. In general, study results should be used as much as possible to get the most out of the money and effort spent so far for the patients of tomorrow. In addition to a unique combination of therapies, our study also has longitudinal multi-Omics data (WES, Bulk- and small RNA seq) prior to treatment and from up to two re-biopsies under therapy and plasma samples as liquid biopsy. No prior study has this and we can therefore deliver a great benefit to the scientific community. "
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string(1295) "• compare clinical outcome and clinical risk stratifications in patients with RCHOP, RCHOP-Ibrutinib and RCHOP-Ibrutinib-Bortezomib
• test and compare mutational profiles in patients with RCHOP, RCHOP-Ibrutinib and RCHOP-Ibrutinib-Bortezomib
• test and compare different gene expression signatures for treatment response in patients with RCHOP, RCHOP-Ibrutinib and RCHOP-Ibrutinib-Bortezomib (pre-described signatures like the CD5-signature for BTKi sensitiviy3 and new ones from our own data set)
• evaluate prediction markers in patients with RCHOP +/- Ibrutinib +/- Bortezomib
Lymphoma biopsies were collected and analyzed with whole exome sequencing and Bulk-RNA-Seq in order to determine which subset of patients benefits from this combination i.e. the treatment additions of Ibrutinib and Bortezomib. In search of a molecular comparator cohort, we were able to get access to the data of a clinical trial using RCHOP + Bortezomib (REMoDL-B[2]) but this data set does not contain such good and sophisticated molecular characterization of the patients and their lymphomas at PHOENIX[3]. Therefore, we would like to apply for data access in order to validate our findings of a molecular subtype and biomarker study of our clinical trial.
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[1]=>
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["project_research_methods"]=>
string(301) "Request for IHC, DNA/WES and RNA-Seq data from PHOENIX trial. The data will be merged with our own data from the ImbruVeRCHOP trial. We are happy to work collaboratively with the YODA project team on their proposed secure platform.
No exclusion criteria in terms of the requested data. "
["project_main_outcome_measure"]=>
string(1019) "3 groups from 2 datasets (PHOENIX and ImbruVeRCHOP trial) will be compared on the following parameters:
1) clinical outcome = response by imaging (complete remission, partial remission, stable disease, progression): progression-free survival, defined as time from start of treatment to progression of disease, death or last follow-up appointment
2) clinical risk stratifications at baseline using clinical parameters like tumor stage and LDH (IPI score), IHC (Cell-of-origin, HANS), mutational and gene expression profiles (LymphGen, DLBClass)
3) signatures for treatment response (pre-described signatures like the CD5-signature for BTKi sensitiviy[4] and new ones from our own data set)
4) prediction markers from IHC, DNA/WES and RNA-Seq
5) multi-Omics profiling/markers pre-treatment vs. under treatment [we have a small but highly characterized and longitudinal data-set with biopsies under treatment, but are missing a big cohort of RCHOP +/- Ibrutinib for validation]
"
["project_main_predictor_indep"]=>
string(188) "The main predictor will be the used treatment regimen, which will be divided into the follwoing groups:
1) RCHOP
2) RCHOP + Ibrutinib
3) RCHOP + Ibrutinib + Bortezomib"
["project_other_variables_interest"]=>
string(822) "The following variables will be explored as covariates in the analysis:
• response by imaging (complete remission, partial remission, stable disease, progression): progression-free survival = time from start of treatment to progression of disease,
death or last follow-up appointment
• IPI score
• NCCN-IPI
• timepoint (molecuar information pre-treatment, and - if available - under treatment or/and after treatment/at relapse)
• stroma and immune features (xCell, https://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1349-1)
• demographics: sex (male and female), age and weight
• lab values: hemoglobin, absolute neutrophil count, platelets, lactate dehydrogenase, albumin, total proteins and beta2-macroglobulin.
"
["project_stat_analysis_plan"]=>
string(1169) "The proposed project will be conducted at Charité – Universitätsmedizin Berlin, Germany and its associated institute for Medical Systems Biology (MDC-BIMSB) at Max Delbrück Center, Berlin, Germany by applying bioinformatic analysis methods to validate findings from our own investigator-initiated trial ImbruVeRCHOP (NCT03129828).
The clinical and genetic characteristics are dichotomized and analyzed using descriptive statistics. The characteristics between the groups 1) RCHOP, 2) RCHOP + ibrutinib, 3) RCHOP + ibrutinib + bortezomib are compared using the chi-square or the Fisher exact test.
Survival will be depicted using Kaplan-Meier plots (PFS, DFS, OS). Statistical analysis to identify differences between relevant subgroups will be performed using the Log-Rank/Mantle-Cox test.
Further biostatistical algorithms, new deep learning-based and off-the-shelf methods (Random Forests, Support Vector Machines) will be performed accordingly for every molecular analysis.
As the ImbruVeRCHOP study results are not yet published, further details on exact signatures or identified biomarkers cannot be shared at this point.
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string(408) "Since all other data are already available, the requested data could simply be included in the existing analysis pipeline.
Milestones are
• anticipated project start date: 01.01.2025
• analysis completion date: 20.04.2025
• date manuscript drafted and first submitted for publication: 15.05.2025
• date results reported back to the YODA Project: 31.12.2025
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["project_dissemination_plan"]=>
string(183) "The target audience of our work is primarily the scientific community. A conference presentation is planned for 2025 as well as a publication optimally in Blood or Lancet Hematology. "
["project_bibliography"]=>
string(2111) "
- Denker S, Bittner A, Frick M, Kase J, Hoffmann J, Trenker C, Keller U, Bogner C, Hüttmann A, Dürig J, Janz M, Mathas S, Marks R, Krohn U, Na IK, Bullinger L, Schmitt CA. Ibrutinib- and bortezomib-extended R-CHOP induction in elderly higher-risk patients newly diagnosed with diffuse large B-cell lymphoma – first analysis of toxicity and efficacy signals. Leuk Lymphoma. 2022 Jan;63(1):84-92. doi: 10.1080/10428194.2021.1964024. Epub 2021 Aug 20. PMID: 34414850.
- Younes A, Sehn LH, Johnson P, Zinzani PL, Hong X, Zhu J, Patti C, Belada D, Samoilova O, Suh C, Leppä S, Rai S, Turgut M, Jurczak W, Cheung MC, Gurion R, Yeh SP, Lopez-Hernandez A, Dührsen U, Thieblemont C, Chiattone CS, Balasubramanian S, Carey J, Liu G, Shreeve SM, Sun S, Zhuang SH, Vermeulen J, Staudt LM, Wilson W; PHOENIX investigators. Randomized Phase III Trial of Ibrutinib and Rituximab Plus Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone in Non-Germinal Center B-Cell Diffuse Large B-Cell Lymphoma. J Clin Oncol. 2019 May 20;37(15):1285-1295. doi: 10.1200/JCO.18.02403. Epub 2019 Mar 22. PMID: 30901302; PMCID: PMC6553835.
- Davies AJ, Barrans S, Stanton L, Caddy J, Wilding S, Saunders G, Mamot C, Novak U, McMillan A, Fields P, Collins GP, Stephens R, Cucco F, Sha C, van Hoppe M, Tooze R, Davies JR, Griffiths G, Schuh A, Burton C, Westhead DR, Du MQ, Johnson PWM. Differential Efficacy From the Addition of Bortezomib to R-CHOP in Diffuse Large B-Cell Lymphoma According to the Molecular Subgroup in the REMoDL-B Study With a 5-Year Follow-Up. J Clin Oncol. 2023 May 20;41(15):2718-2723. doi: 10.1200/JCO.23.00033. Epub 2023 Mar 27. PMID: 36972491; PMCID: PMC10414744.
- Cooper A, Tumuluru S, Kissick K, Venkataraman G, Song JY, Lytle A, Duns G, Yu J, Kotlov N, Bagaev A, Hodkinson B, Srinivasan S, Smith SM, Scott DW, Steidl C, Godfrey JK, Kline J. CD5 Gene Signature Identifies Diffuse Large B-Cell Lymphomas Sensitive to Bruton’s Tyrosine Kinase Inhibition. J Clin Oncol. 2024 Feb 1;42(4):467-480. doi: 10.1200/JCO.23.01574. Epub 2023 Dec 11. PMID: 38079587.
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Research Proposal
Project Title:
Outcome-comparison between different DLBCL first-line data sets with RCHOP + X
Scientific Abstract:
Background: ImbruVeRCHOP trial [1] treated DLBCL patients with RCHOP + Ibrutinib + Bortezomib, and performed re-biopsies under treatment with molecular profiling.
Objective: To validate our findings, we aim to compare our clinical and molecular data in a larger data set of DLBCL patients with RCHOP +/- Ibrutinib treatment.
Study Design: Cohort study.
Participants: 36 patients from our phase I/II trial were included for molecular characterization; the preferred validation cohort would be the 838 study patients of the PHOENIX trial.
Primary and Secondary Outcome Measures: 1)clinical outcome, 2)clinical risk stratifications using clinical parameters, IHC, mutational and gene expression profiles, 3) signatures for treatment response (pre-described) and new ones from our own data set, 4) prediction markers from IHC, DNA/WES and RNA-Seq, 5) multi-Omics profiling/markers pre-treatment vs. under treatment.
Statistical Analysis: The clinical and genetic characteristics are dichotomized and analyzed using descriptive statistics. The characteristics between the groups 1) RCHOP, 2) RCHOP + ibrutinib, 3) RCHOP + ibrutinib + bortezomib are compared using the chi-square or the Fisher exact test. Survival will be depicted using Kaplan-Meier plots (PFS, DFS, OS). Statistical analysis to identify differences between relevant subgroups will be performed using the Log-Rank/Mantle-Cox test. Further biostatistical algorithms, new deep learning-based and off-the-shelf methods (Random Forests, Support Vector Machines) will be performed accordingly for every molecular analysis.
Brief Project Background and Statement of Project Significance:
To date, we clinicians still find it difficult to select the right therapy for DLBCL patients at increased risk. We conducted an all-comer, investigator-initiated phase I/II trial at Charité and 11 centers in Germany and Austria, to identify signatures and markers for DLBCL patients with targeted treatment additions (ImbruVeRCHOP, ClinicalTrials.gov identifier: NCT03129828). Using an all-comers approach, but subjecting patients to another lymphoma biopsy acutely under first-cycle immune-chemo drug exposure, ImbruVeRCHOP seeks to identify an unbiased molecular responder signature that marks diffuse large B-cell lymphoma patients at risk and likely to benefit from this regimen as a double, proximal and distal B-cell receptor/NF-κB-co-targeting extension of the current R-CHOP standard of care. First-in human treatment with RCHOP+Ibrutinib as well as Bortezomib was well tolerated and the patients showed good response. For these signals to be more relevant for other patients in the future, validation in larger cohorts is needed; in addition to further clinical studies. In general, study results should be used as much as possible to get the most out of the money and effort spent so far for the patients of tomorrow. In addition to a unique combination of therapies, our study also has longitudinal multi-Omics data (WES, Bulk- and small RNA seq) prior to treatment and from up to two re-biopsies under therapy and plasma samples as liquid biopsy. No prior study has this and we can therefore deliver a great benefit to the scientific community.
Specific Aims of the Project:
- compare clinical outcome and clinical risk stratifications in patients with RCHOP, RCHOP-Ibrutinib and RCHOP-Ibrutinib-Bortezomib
- test and compare mutational profiles in patients with RCHOP, RCHOP-Ibrutinib and RCHOP-Ibrutinib-Bortezomib
- test and compare different gene expression signatures for treatment response in patients with RCHOP, RCHOP-Ibrutinib and RCHOP-Ibrutinib-Bortezomib (pre-described signatures like the CD5-signature for BTKi sensitiviy3 and new ones from our own data set)
- evaluate prediction markers in patients with RCHOP +/- Ibrutinib +/- Bortezomib
Lymphoma biopsies were collected and analyzed with whole exome sequencing and Bulk-RNA-Seq in order to determine which subset of patients benefits from this combination i.e. the treatment additions of Ibrutinib and Bortezomib. In search of a molecular comparator cohort, we were able to get access to the data of a clinical trial using RCHOP + Bortezomib (REMoDL-B[2]) but this data set does not contain such good and sophisticated molecular characterization of the patients and their lymphomas at PHOENIX[3]. Therefore, we would like to apply for data access in order to validate our findings of a molecular subtype and biomarker study of our clinical trial.
Study Design:
Individual trial analysis
What is the purpose of the analysis being proposed? Please select all that apply.:
New research question to examine treatment effectiveness on secondary endpoints and/or within subgroup populations
Confirm or validate previously conducted research on treatment effectiveness
Participant-level data meta-analysis
Meta-analysis using data from the YODA Project and other data sources
Research on comparison group
Research on clinical prediction or risk prediction
Software Used:
RStudio
Data Source and Inclusion/Exclusion Criteria to be used to define the patient sample for your study:
Request for IHC, DNA/WES and RNA-Seq data from PHOENIX trial. The data will be merged with our own data from the ImbruVeRCHOP trial. We are happy to work collaboratively with the YODA project team on their proposed secure platform.
No exclusion criteria in terms of the requested data.
Primary and Secondary Outcome Measure(s) and how they will be categorized/defined for your study:
3 groups from 2 datasets (PHOENIX and ImbruVeRCHOP trial) will be compared on the following parameters:
1) clinical outcome = response by imaging (complete remission, partial remission, stable disease, progression): progression-free survival, defined as time from start of treatment to progression of disease, death or last follow-up appointment
2) clinical risk stratifications at baseline using clinical parameters like tumor stage and LDH (IPI score), IHC (Cell-of-origin, HANS), mutational and gene expression profiles (LymphGen, DLBClass)
3) signatures for treatment response (pre-described signatures like the CD5-signature for BTKi sensitiviy[4] and new ones from our own data set)
4) prediction markers from IHC, DNA/WES and RNA-Seq
5) multi-Omics profiling/markers pre-treatment vs. under treatment [we have a small but highly characterized and longitudinal data-set with biopsies under treatment, but are missing a big cohort of RCHOP +/- Ibrutinib for validation]
Main Predictor/Independent Variable and how it will be categorized/defined for your study:
The main predictor will be the used treatment regimen, which will be divided into the follwoing groups:
1) RCHOP
2) RCHOP + Ibrutinib
3) RCHOP + Ibrutinib + Bortezomib
Other Variables of Interest that will be used in your analysis and how they will be categorized/defined for your study:
The following variables will be explored as covariates in the analysis:
- response by imaging (complete remission, partial remission, stable disease, progression): progression-free survival = time from start of treatment to progression of disease,
death or last follow-up appointment
- IPI score
- NCCN-IPI
- timepoint (molecuar information pre-treatment, and - if available - under treatment or/and after treatment/at relapse)
- stroma and immune features (xCell, https://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1349-1)
- demographics: sex (male and female), age and weight
- lab values: hemoglobin, absolute neutrophil count, platelets, lactate dehydrogenase, albumin, total proteins and beta2-macroglobulin.
Statistical Analysis Plan:
The proposed project will be conducted at Charité -- Universitätsmedizin Berlin, Germany and its associated institute for Medical Systems Biology (MDC-BIMSB) at Max Delbrück Center, Berlin, Germany by applying bioinformatic analysis methods to validate findings from our own investigator-initiated trial ImbruVeRCHOP (NCT03129828).
The clinical and genetic characteristics are dichotomized and analyzed using descriptive statistics. The characteristics between the groups 1) RCHOP, 2) RCHOP + ibrutinib, 3) RCHOP + ibrutinib + bortezomib are compared using the chi-square or the Fisher exact test.
Survival will be depicted using Kaplan-Meier plots (PFS, DFS, OS). Statistical analysis to identify differences between relevant subgroups will be performed using the Log-Rank/Mantle-Cox test.
Further biostatistical algorithms, new deep learning-based and off-the-shelf methods (Random Forests, Support Vector Machines) will be performed accordingly for every molecular analysis.
As the ImbruVeRCHOP study results are not yet published, further details on exact signatures or identified biomarkers cannot be shared at this point.
Narrative Summary:
Treating patients with diffuse-large B-cell lymphoma (DLBCL) is a very difficult task since the disease is very heterogeneous and undergoes a series of biological changes under treatment. We ran a phase I/II clinical trial, ImbruVeRCHOP, between 2017 and 2024, and treated DLBCL patients with RCHOP + Ibrutinib + Bortezomib and perfromed intensive molecular characterizations and re-biopsies under treatment to determine which subset of patients benefits from this combination. We would like to validate our findings on a molecular level and therefore apply for data access of the PHOENIX trial (DLBCL with RCHOP +/- Ibrutinib, NCT01855750).
Project Timeline:
Since all other data are already available, the requested data could simply be included in the existing analysis pipeline.
Milestones are
- anticipated project start date: 01.01.2025
- analysis completion date: 20.04.2025
- date manuscript drafted and first submitted for publication: 15.05.2025
- date results reported back to the YODA Project: 31.12.2025
Dissemination Plan:
The target audience of our work is primarily the scientific community. A conference presentation is planned for 2025 as well as a publication optimally in Blood or Lancet Hematology.
Bibliography:
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