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Biological Analysis of MABs in NHL in a Translational Prospective Observational Study Within Italian Clinical Practice (BIO-FIL_MAB)

2026년 8월 11일 업데이트: Fondazione Italiana Linfomi - ETS

Multilayer Biological Analysis of Novel Monoclonal Antibodies (MABs) in B-Cell Non-Hodgkin Lymphoma (NHL): A Translational and Prospective Observational Study Within Italian Clinical Practice (BIO-FIL_MAB Trial)

This a prospective, multicenter, observational pharmacological translational study designed to investigate the biological and imaging correlates of treatment with novel monoclonal antibodies (NMABs) in patients with B-cell non-Hodgkin lymphoma (NHL), enrolled in the observationa FIL_MAB study. Patients enrolled in BIO FIL-MAB are concurrently participating in the FIL-MAB clinical cohort, ensuring that all clinical data-including treatment details, outcomes, and safety-are captured within the main observational study.

Patients will undergo systematic collection of biological specimens including tumor tissue, peripheral blood integrated with advanced imaging data. Biological analyses will encompass molecular, cellular, and immunological assessments, while imaging evaluations will include standardized functional and metabolic imaging techniques. All biological and imaging assessments will be performed as routine clinical visits, without requiring modifications to treatment or additional procedures beyond standard-of-care.

연구 개요

상태

아직 모집하지 않음

정황

상세 설명

This a prospective, multicenter, observational pharmacological translational study designed to investigate the biological and imaging correlates of treatment with novel monoclonal antibodies (NMABs) in patients with B-cell non-Hodgkin lymphoma (NHL), enrolled in the observational FIL_MAB study.

All clinical observations, including baseline characteristics, treatment exposure, and follow-up, are collected through the FIL-MAB study database, with a minimum follow-up of 60 months (5 years) from enrollment and correlated with biological findings for translational analysis performed in BIO-FIL_MAB study.

The BIO-FIL_MAB study will employ a structured schedule of biological and imaging assessments to monitor treatment outcomes and gather translational data. The timeline will be aligned with routine clinical practice:

  • Prior to NMAB Treatment
  • During NMAB Therapy (3 months after start of therapy, 9 months after start of therapy, progression/relapse).

This structured schedule ensures a comprehensive evaluation of both clinical and biological treatment effects, aligning with the study's translational objectives.

As an observational translational study primarily intended for descriptive and exploratory analyses, no formal statistical hypothesis testing is planned.

Therefore, the sample size has been determined based on feasibility considerations and the expected availability of patients participating in the parent FIL-MAB clinical cohort, thereby ensuring a robust population for integrated biological, immunological, and imaging analyses in association with clinical outcomes.

Overall, it is anticipated that at least 1000 patients will be consecutively enrolled and followed longitudinally in BIO-FIL_MAB study.

연구 유형

관찰

등록 (추정된)

1000

연락처 및 위치

이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.

연구 연락처

연구 연락처 백업

연구 장소

      • Alessandria, 이탈리아, 15121
        • SCDU Ematologia -AOU SS. Antonio e Biagio e Cesare Arrigo di Alessandria
        • 연락하다:
      • Aviano, 이탈리아, 33081
        • Divisione di Oncologia e dei Tumori immuno-correlati - IRCCS Centro di Riferimento Oncologico di Aviano
        • 연락하다:
      • Bari, 이탈리아, 70124
        • U.O.C Ematologia - IRCCS Istituto Tumori Giovanni Paolo II - Bari
        • 연락하다:
      • Bergamo, 이탈리아, 24127
        • SC Ematologia - Azienda Ospedaliera Papa Giovanni XXIII - Bergamo
        • 연락하다:
      • Bologna, 이탈리아, 40138
        • Istituto di Ematologia "Seragnoli" - Policlinico S.Orsola-Malpighi
        • 연락하다:
      • Brescia, 이탈리아, 25123
      • Cuneo, 이탈리아, 12100
      • Florence, 이탈리아, 50141
        • Unità funzionale di Ematologia -Azienda Ospedaliera Universitaria Careggi
        • 연락하다:
      • Milan, 이탈리아, 20133
        • Ematologia - Fondazione IRCCS Istituto Nazionale dei Tumori di Milano
        • 연락하다:
      • Milan, 이탈리아, 20162
      • Novara, 이탈리아, 28100
      • Pescara, 이탈리아, 65124
        • UOC Ematologia Dipartimento Oncologico Ematologico - P.O. Spirito Santo di Pescara - ASL Pescara
        • 연락하다:
      • Reggio Emilia, 이탈리아, 42123
        • Ematologia - Arcispedale Santa Maria Nuova - IRCCS -Azienda Unità Sanitaria Locale
        • 연락하다:
      • Roma, 이탈리아, 00161
        • Dipartimento di Medicina Traslazionale e di Precisione - Istituto Ematologia - Policlinico Umberto I - Università "La Sapienza" - Roma
        • 연락하다:
      • Torino, 이탈리아, 10126
        • Ematologia Universitaria - A.O.U. Città della Salute e della Scienza di Torino
        • 연락하다:
      • Torino, 이탈리아, 10126
        • S.C. Ematologia - A.O.U. Città della Salute e della Scienza di Torino
        • 연락하다:
      • Verona, 이탈리아, 37134
        • U.O. Ematologia - AOU Integrata di Verona
      • Vicenza, 이탈리아, 36100
    • Torino
      • Candiolo, Torino, 이탈리아, 10060
        • Ematologia - Fondazione del Piemonte per l'Oncologia - IRCCS
        • 연락하다:
    • Treviso
      • Castelfranco Veneto, Treviso, 이탈리아, 31033

참여기준

연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.

자격 기준

공부할 수 있는 나이

  • 성인
  • 고령자

건강한 자원 봉사자를 받아들입니다

아니

샘플링 방법

비확률 샘플

연구 인구

Being an observational translational study primarily aimed at descriptive and exploratory analyses, no formal statistical hypothesis testing is planned for BIO-FIL_MAB. The sample size is therefore determined based on feasibility and the expected availability of patients participating in the parent FIL-MAB clinical cohort. Overall, it is anticipated that at least 1000 patients will be enrolled and followed, providing a robust population for integrated biology, immunology, and imaging analyses alongside clinical outcomes.

설명

Inclusion Criteria:

  • Adults (≥18 years old) are diagnosed with B-cell Non-Hodgkin Lymphoma;
  • Patients enrolled in the FIL_MAB trial (provided by Informed Consent Form (ICF) signature) who are scheduled to receive treatment with novel monoclonal antibodies (NMABs), either as monotherapy or in combination with other therapies;
  • Written informed consent to participate in this study.

Exclusion Criteria:

  • Patients not enrolled in the FIL_MAB study.
  • Evidence of other clinically significant uncontrolled condition(s) including, but not limited to:

    • Uncontrolled and/or active systemic infection (viral, bacterial or fungal), including active ongoing infection from SARSCoV-2;
    • Chronic or acute hepatitis B (HBV) or hepatitis C (HCV) requiring treatment. Note: subjects with serologic evidence of prior vaccination to HBV (i.e., HBsAg negative, HBsAb positive and HBcAb negative) or positive HBcAb from previous infection or intravenous immunoglobulins (IVIG) may participate; inactive carriers (HBsAg positive with undetectable HBV- DNA) are eligible. Patients with presence of HCV antibody are eligible only if PCR negative for HCV-RNA;
    • HIV seropositivity;
  • Refusal or inability to provide informed consent.
  • Refusal or inability to provide biological specimens.

공부 계획

이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.

연구는 어떻게 설계됩니까?

디자인 세부사항

코호트 및 개입

그룹/코호트
개입 / 치료
T-cell engager antibodies - Work package 1 (WP 1)
WP1 includes all the FIL-MAB-approved cohorts related to novel T-cell engager therapies (e.g. bi-specifics and others).

Objectives

  1. To investigate the value of circulating tumor DNA (ctDNA)/ Minimal Residual Disease (MRD) status as prognostic biomarker for B-NHL patients treated with commercial bi-specifics antibodies (bsAbs).
  2. To evaluate the potential role of clonal hematopoiesis (CH) in terms of therapy-related toxicities and treatment response.
  3. To evaluate the potential prognostic role of germline single-nucleotide polymorphisms (SNPs) involved in drug metabolic pathways and cell-to-cell interactions.

Objectives

  1. evaluate association between levels and subtypes of T cell in PB before and after bsAbs with COs.
  2. Analyze expression of PD1, CD25, 41BB/CD137, CTLA4, CD28, and other T cell co-stimulatory molecules, and correlate with COs.
  3. Evaluate expansion of NK cells along with their markers of activation, exhaustion, maturation, chemotaxis.
  4. evaluate association between T cell exhaustion with treatment failure.
  5. evaluate association between T cell exhaustion with previous lines of treatment or other clinical factors such as relapsed time.
  6. evaluate association between T cell clusters with the development of cytopenia during treatment.
  7. investigate whether immunosenescence (composition and activation status of PBMCs) and inflammaging (soluble mediators) can predict response and clinical outcomes in elderly patients (≧70) undergoing treatment with bsAbs.
  8. Immunological characterization of T cell subset by bulk RNAseq before and after bsAbs with COs.

Objectives

  1. Association between specific mutational (Whole Genome Sequencing, WGS) and transcriptomic (Whole Transcriptome Sequencing, WTS) patterns with disease response to bsAbs therapy.
  2. To investigate TP53 mutation and del17p as predictive factor of response to bsAbs.
  3. Identifying specific relapse patterns, with the hypothesis that alterations in tumor genes facilitating immune evasion are enriched in clones emerging at relapse (i.e., secondary resistance).
  4. To characterize intratumoral immune effector cell distribution and to assess T-cell functional fitness and exhaustion states within tumor-draining lymph nodes using Digital Spatial Profiling (DSP).
  5. To investigate the association between bsAbs surface target antigens (e.g. CD20) expression level and response to bsAbs.

Objectives

  1. explore how tumor metabolic activity signature predict prognosis and treatment response during bsAbs-approved treatments.
  2. explore how tumor heterogeneity activity predicts prognosis and treatment response during bsAbs -approved treatments.
  3. explore how PET findings are integrated with other biomarkers, we refine predictions of prognosis and treatment efficacy during bsAbs-approved treatments.
  4. explore novel prognostic markers of progression in CT scans and PET scans.
  5. apply advanced artificial intelligence methods (radiomics and deep learning) for automated extraction of complex imaging features from PET/CT scans, aiming to enhance prediction of prognosis and treatment response in patients undergoing bsAbs-approved treatments.
  6. develop and validate AI-driven multimodal integration frameworks that combine imaging data with clinical and molecular biomarkers, refining risk stratification and enabling early detection of progression under bsAbs therapy.

Objectives

  1. To describe plasma and tissue microbiome composition and metabolomics during bsAbs -approved treatments.
  2. To investigate whether microbiome/metabolomics predicts outcomes during bsAbs -approved treatments.
  3. To investigate whether microbiome/metabolomics predicts treatment toxicity during bsAbs -approved treatments.
Immunoconjugates antibodies - Work package 2 (WP2)
WP2 includes all the FIL-MAB-approved cohorts related to novel immunoconjugate therapies (e.g. Antibody-Drug Conjugates (ADCs)).

Objectives

  1. To identify and validate biological and molecular biomarkers (i.e. ctDNA/MRD) that predict patient outcomes in patients treated with novel immunoconjugate therapies.
  2. To evaluate the potential role of clonal hematopoiesis (CH) in terms of therapy-related toxicities and treatment response.
  3. To evaluate the potential prognostic role of germline single-nucleotide polymorphisms (SNPs) involved in drug metabolic pathways and cell-to-cell interactions.

Objectives

  1. evaluate the association between levels and subtypes of T cells in PB before and after ADCs with COs.
  2. Analyze the expression of PD1, CD25, 41BB/CD137, CTLA4, CD28, and other T cell co-stimulatory molecules, and correlate them with COs.
  3. Evaluate the expansion of NK cells along with their markers of activation, exhaustion, maturation, chemotaxis.
  4. evaluate the association between T cell exhaustion with treatment failure.
  5. evaluate the association between T cell exhaustion with previous lines of treatment or other clinical factors such as relapsed time.
  6. evaluate the association between T cell clusters with the development of cytopenia during treatment.
  7. investigate whether immunosenescence and inflammaging can predict response and clinical outcomes in elderly patients (≧ 70) undergoing treatment with ADCs.
  8. Immunological characterization of T cell subset by bulk RNAseq before and after ADCs with clinical outcomes.

Objectives

  1. characterize intratumoral immune effector cell distribution and assess T-cell functional fitness and exhaustion states within tumor-draining lymphnodes using DSP.
  2. investigate correlation between ADCs surface target antigens expression level and response to ADCs treatment
  3. investigate MYC translocation alone or in association with BCL2 and or BCL6 translocation or other MYC chromosomal aberrations as predictive factors of response to ADCs assessed by FISH on diagnostic biopsy and last biopsy preADCs treatment.
  4. investigate TP53 mutation and del17p as predictive factor of response to ADCs.
  5. investigate mutations and CNVs as predictive factors of response to ADCs treatment.
  6. investigate ADCs target antigens RNA expression level and correlation with response to ADCs treatment.
  7. characterize transcriptomic and sRNA landscapes to identify gene expression signatures and microRNA profiles associated with response to ADCs treatment.

Objectives

  1. explore how tumor metabolic activity signature predict prognosis and treatment response during ADCs-approved treatments.
  2. explore how tumor heterogeneity activity predicts prognosis and treatment response during ADCs-approved treatments.
  3. explore how PET findings are integrated with other biomarkers, we refine predictions of prognosis and treatment efficacy during ADCs-approved treatments.
  4. explore novel prognostic markers of progression in CT scans and PET scans.
  5. apply advanced artificial intelligence methods (radiomics and deep learning) for automated extraction of complex imaging features from PET/CT scans, aiming to enhance prediction of prognosis and treatment response in patients undergoing ADCs-approved treatments.
  6. develop and validate AI-driven multimodal integration frameworks that combine imaging data (PET/CT) with clinical and molecular biomarkers, refining risk stratification and enabling early detection of progression under ADCs therapy.

Objectives

  1. To describe plasma and tissue microbiome and metabolomics composition during ADCs-treatments.
  2. To investigate whether microbiome/metabolomics predicts outcomes during ADCs-approved treatments.
  3. To investigate whether microbiome/metabolomics predicts treatment toxicity during ADCs-approved treatments.
Naked antibodies - Work package 3 (WP3)
WP3 includes all the FIL-MAB-approved cohorts related to novel naked antibodies- based therapies.

Objectives

  1. To identify and validate biological and molecular biomarkers (i.e. ctDNA/MRD) that predict patient outcomes in patients treated with novel naked antibodies.
  2. To evaluate the potential role of clonal hematopoiesis (CH) in terms of therapy-related toxicities and treatment response.
  3. To evaluate the potential prognostic role of germline single-nucleotide polymorphisms (SNPs) involved in drug metabolic pathways and cell-to-cell interactions.

Objective

1) Evaluate the expansion of immunological cells along with their markers of activation, exhaustion, maturation, and chemotaxis.

Objectives

  1. To investigate the correlation between naked antibodies surface target antigens (e.g. CD19) expression level and response to naked antibodies.
  2. To investigate MYC translocation alone or in association with BCL2 and or BCL6 translocation, or other MYC chromosomal aberrations as predictive factors of response to naked antibodies (assessed by FISH on diagnostic biopsy and last biopsy pre- naked antibodies).
  3. To investigate TP53 mutation and del17p as predictive factor of response to naked antibodies.
  4. To investigate mutations and copy number variations (CNVs) (either studied by targeted sequencing or by WES) as predictive factors of response to treatment.

Objectives

  1. explore how tumor metabolic activity signature predict prognosis and treatment response during naked Abs-approved treatments.
  2. explore how tumor heterogeneity activity predicts prognosis and treatment response during naked Abs-approved treatments.
  3. explore how PET findings are integrated with other biomarkers, we refine predictions of prognosis and treatment efficacy during naked Abs-approved treatments.
  4. explore novel prognostic markers of PD in CT and PET scans.
  5. apply advanced artificial intelligence methods (radiomics and deep learning) for automated extraction of complex imaging features from PET/CT, aiming to enhance prediction of prognosis and treatment response in patients undergoing naked Abs-approved treatments.
  6. develop and validate AI-driven multimodal integration frameworks that combine imaging data with clinical and molecular biomarkers, refining risk stratification and enabling early detection of progression under naked Abs therapy.

Objectives

  1. To describe plasma and tissue microbiome and metabolomics composition during naked antibodies -approved treatments.
  2. To investigate whether microbiome/metabolomics predicts outcomes during naked antibodies -approved treatments.
  3. To investigate whether microbiome/metabolomics predicts treatment toxicity during naked antibodies -approved treatment.

연구는 무엇을 측정합니까?

주요 결과 측정

결과 측정
측정값 설명
기간
T-cell engager antibodies - Work package (WP 1) -Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
1) Association between MRD status and Progression Free Survival (PFS).
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) -Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
2) Association between MRD status and Overall Survival (OS).
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) -Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
3) Association between between MRD status and clinical response.
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) -Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
4) Comparison between MRD negativity rates obtained by different BsAbs time to obtain MRD negativity by different BsAbs.
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) -Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
5) Correlation between baseline ctDNA levels and outcome (response, PFS, OS).
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) -Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
6) Association between MRD status and other clinical and biological prognostic markers (e.g. mutational patterns, T-cell phenotypes).
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) -Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
7) Association between baseline ctDNA and MRD with imaging biomarkers (Total Metabolic Tumor Value (TMTV), Maximum Tumor Dissemination (Dmax), Standardized Uptake Value maximum (SUVmax), Artificial Intelligence (AI) features etc).
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) -Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
8) Association of CH with PFS, OS and therapy-related toxicities.
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) -Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
9) Association of SNPs with PFS, OS and therapy-related toxicities.
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) - Task 2 -Immunological analyses
기간: from enrollment start to final analyses (15 years)
1) Quantification of CD4+ and CD8+T lymphocyte clusters and soluble mediators of inflammagin, at baseline, month +3 (M3) and End Of Treatment (EOT), and correlation with clinical outcome (PFS, OS).
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) - Task 2 -Immunological analyses
기간: from enrollment start to final analyses (15 years)
2) Measuring NK cells count at baseline and M3 and correlation with outcome.
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) - Task 2 -Immunological analyses
기간: from enrollment start to final analyses (15 years)
3) Association between CD4+ Treg, CD4+, and CD8+ T lymphocyte counts at M3 and Complete Metabolic Response (CMR)/MRD-.
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) - Task 2 -Immunological analyses
기간: from enrollment start to final analyses (15 years)
4) Association between CD4+ Treg, CD4+, and CD8+ T Lymphocyte counts at M3 and 2-Y PFS.
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) - Task 2 -Immunological analyses
기간: from enrollment start to final analyses (15 years)
5) Expression of co-stimulatory molecules such as PD1, CD25, 41BB/CD137, CTLA4, and CD28 on T cells at M3 and their correlation with achieving a CMR.
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) - Task 2 -Immunological analyses
기간: from enrollment start to final analyses (15 years)
6) Correlation between T cell exhaustion and treatment failure.
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) - Task 2 -Immunological analyses
기간: from enrollment start to final analyses (15 years)
7) Correlation of T lymphocyte clusters and soluble mediators of inflammaging with safety (e.g. Cytokine Release Syndrome (CRS), Immune Effector Cell-Associated Neurotoxicity Syndrome (ICANS), infections).
from enrollment start to final analyses (15 years)
T-cell engager antibodies - Work package (WP 1) - Task 3 - Tumor tissue analyses
기간: from enrollment start to final analyses (15 years)
  1. Correlation of specific mutational profiles with Overall Response Rate (ORR) rates, 2-Y PFS and 2-Y OS.
  2. Correlation of specific transcriptomic signatures with ORR rates, 2-Y PFS and 2-Y OS.
  3. Correlation of intra-tumoral T-cell populations and non-T-cell populations with ORR rates, 2-Y PFS and 2-Y OS.
  4. Identifying specific relapse patterns, with the hypothesis that alterations in tumor genes facilitating immune evasion are enriched in clones emerging at relapse (i.e., secondary resistance).
  5. Correlation between target antigen surface level (i.e. CD20) with ORR rates, 2-Y PFS and 2-Y OS.
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
1) Association between MRD status and PFS.
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
2) Association between MRD status and OS.
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
3) Association between MRD status and clinical response.
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
4) Comparison between MRD negativity rates obtained by different BsAbs time to obtain MRD negativity by different BsAbs.
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
5) Correlation between baseline ctDNA levels and outcome (response, PFS, OS).
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
6) Association between MRD status and other clinical and biological prognostic markers (e.g. mutational patterns, T-cell phenotypes).
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
7) Association between baseline ctDNA and MRD with imaging biomarkers (TMTV, Dmax, SUVmax, AI features etc).
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
8) Association of CH with PFS, OS and therapy-related toxicities.
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
9) Association of SNPs with PFS, OS and therapy-related toxicities.
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 2 - Immunological analyses
기간: from enrollment start to final analyses (15 years)
1) Quantification of CD4+ and CD8+T lymphocyte clusters and soluble mediators of inflammagin, at baseline, month +3 (M3) and EOT, and correlation with clinical outcome (PFS, OS).
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 2 - Immunological analyses
기간: from enrollment start to final analyses (15 years)
2) Measuring NK cells count at baseline and M3 and correlation with outcome.
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 2 - Immunological analyses
기간: from enrollment start to final analyses (15 years)
3) Association between CD4+ Treg, CD4+, and CD8+ T lymphocyte counts at M3 and CMR/MRD-.
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 2 - Immunological analyses
기간: from enrollment start to final analyses (15 years)
4) Association between CD4+ Treg, CD4+, and CD8+ T Lymphocyte counts at M3 and 2-Y PFS.
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 2 - Immunological analyses
기간: from enrollment start to final analyses (15 years)
5) Expression of co-stimulatory molecules such as PD1, CD25, 41BB/CD137, CTLA4, and CD28 on T cells at M3 and their correlation with achieving a CMR.
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 2 - Immunological analyses
기간: from enrollment start to final analyses (15 years)
6) Correlation between T cell exhaustion and treatment failure.
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 2 - Immunological analyses
기간: from enrollment start to final analyses (15 years)
7) Correlation of T lymphocyte clusters and soluble mediators of inflammaging with safety (e.g. infections).
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 3 - Tumor tissue analyses
기간: from enrollment start to final analyses (15 years)
1) Association between target antigen surface level and CRR with ADCs treatment, assessed in immunohistochemistry (IHC) on diagnosis or last relapse biopsy before ADCs treatment.
from enrollment start to final analyses (15 years)
Immunoconjugates antibodies - Work package 2 (WP2) Task 3 - Tumor tissue analyses
기간: from enrollment start to final analyses (15 years)
2) Association between target antigen surface level and OS, PFS and ORR with ADCs treatment, assessed in immunohistochemistry (IHC) on diagnosis or last relapse biopsy before ADCs treatment and correlation with biological and imaging predictors. Correlation of CH with PFS, OS and therapy-related toxicities and correlation of SNPs with PFS, OS and therapy-related toxicities.
from enrollment start to final analyses (15 years)
Naked antibodies - Work package 3 (WP3) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
1) Association between MRD status and PFS.
from enrollment start to final analyses (15 years)
Naked antibodies - Work package 3 (WP3) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
2) Association between MRD status and OS.
from enrollment start to final analyses (15 years)
Naked antibodies - Work package 3 (WP3) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
3) Association between MRD status and clinical response.
from enrollment start to final analyses (15 years)
Naked antibodies - Work package 3 (WP3) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
4) Comparison between MRD negativity rates obtained by different naked antibodies time to obtain MRD negativity by different naked antibodies.
from enrollment start to final analyses (15 years)
Naked antibodies - Work package 3 (WP3) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
5) Correlation between baseline ctDNA levels and outcome (response, PFS, OS).
from enrollment start to final analyses (15 years)
Naked antibodies - Work package 3 (WP3) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
6) Association between MRD status and other clinical and biological prognostic markers (e.g. mutational patterns, T-cell phenotypes).
from enrollment start to final analyses (15 years)
Naked antibodies - Work package 3 (WP3) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
7) Association between baseline ctDNA and MRD with imaging biomarkers (TMTV, Dmax, SUVmax, AI features etc).
from enrollment start to final analyses (15 years)
Naked antibodies - Work package 3 (WP3) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
8) Association of CH with PFS, OS and therapy-related toxicities.
from enrollment start to final analyses (15 years)
Naked antibodies - Work package 3 (WP3) Task 1 - Liquid analyses
기간: from enrollment start to final analyses (15 years)
9) Association of SNPs with PFS, OS and therapy-related toxicities.
from enrollment start to final analyses (15 years)
Naked antibodies - Work package 3 (WP3) Task 3 - Tumor tissue analyses
기간: from enrollment start to final analyses (15 years)
1) Association between target antigen surface level and CRR with naked antibodies-based treatment, assessed in immunohistochemistry (IHC) on diagnosis or last relapse biopsy before naked antibodies-based therapies.
from enrollment start to final analyses (15 years)
Naked antibodies - Work package 3 (WP3) Task 3 - Tumor tissue analyses
기간: from enrollment start to final analyses (15 years)
2) Association between target antigen surface level and OS, PFS and ORR with naked antibodies based-treatment, assessed in immunohistochemistry (IHC) on diagnosis or last relapse biopsy before naked antibodies based-treatment and correlation with biological and imaging predictors. Correlation of CH with PFS, OS and therapy-related toxicities and correlation of SNPs with PFS, OS and therapy-related toxicities.
from enrollment start to final analyses (15 years)
All Work packages
기간: from enrollment start to final analyses (15 years)
1) Prognostic quantitative PET indices: Metabolic Tumor Volume (MTV), Total Glycolytic Volumes (TLG), SUVmax and SUVpeak, other index of tumor dissemination (maximum distance between the lesion, product of distance and MTV, etc.…) and radiomics index.
from enrollment start to final analyses (15 years)
All Work packages
기간: from enrollment start to final analyses (15 years)
2) Association between plasma and lymph nodes microbiome and outcomes (ORR, Complete Response Rate (CRR), PFS, OS) in NMAB-approved treatments.
from enrollment start to final analyses (15 years)
All Work packages
기간: from enrollment start to final analyses (15 years)
3) Evaluation of correlations between immune cell subsets (T-cell subsets, NK cells), immunological clusters, soluble mediators, and clinical efficacy.
from enrollment start to final analyses (15 years)

공동 작업자 및 조사자

여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.

스폰서

수사관

  • 연구 의자: Riccardo Moia, MD, Divisione di Ematologia, Dipartimento di Medicina Traslazionale Università del Piemonte Orientale, AOU Maggiore della Carità, Novara (Italy)
  • 연구 의자: Simone Ferrero, Prof., Ematologia Universitaria, A.O.U. Città della Salute e della Scienza di Torino, Torino (Italy)
  • 연구 의자: Rita Tavarozzi, MD, SCDU Ematologia, Azienda Ospedaliera SS Antonio e Biagio e C. Arrigo, Alessandria, Italy

연구 기록 날짜

이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.

연구 주요 날짜

연구 시작 (추정된)

2026년 10월 1일

기본 완료 (추정된)

2041년 10월 1일

연구 완료 (추정된)

2041년 10월 1일

연구 등록 날짜

최초 제출

2026년 8월 5일

QC 기준을 충족하는 최초 제출

2026년 8월 11일

처음 게시됨 (실제)

2026년 8월 17일

연구 기록 업데이트

마지막 업데이트 게시됨 (실제)

2026년 8월 17일

QC 기준을 충족하는 마지막 업데이트 제출

2026년 8월 11일

마지막으로 확인됨

2026년 8월 1일

추가 정보

이 연구와 관련된 용어

기타 연구 ID 번호

  • BIO-FIL_MAB

개별 참가자 데이터(IPD) 계획

개별 참가자 데이터(IPD)를 공유할 계획입니까?

예

IPD 계획 설명

Qualified researchers may contact the FIL board at segreteriadirezione@filinf.it to share invidual-level patients' clinical data analysed for this manuscript (for the avoidance of doubt, no identifiable data, such as name, address, hospital name, date of birth, or any other identifying data, will be shared and should not be requested).

IPD 공유 기간

In compliance with the domestic ethics guideline and applicable legislation, invidual deindentified patients' data underlying the results reported in the publication article (including study protocol, statistical analysis plan and data coding) can be shared until 5 years after the publication of the article.

IPD 공유 액세스 기준

For each data sharing request, it is essential that a proforma (available on request) is completed that describes the general purpose, specific aims, data items requested, analysis plan and acknowledgment of the trial management team. Requests will be reviewed based on scientific merit and ethical principles. Requestors who are granted access to the data will be required to complete a data sharing agreement that will be signed by the requester and FIL.

IPD 공유 지원 정보 유형

  • 연구_프로토콜
  • 수액
  • ANALYTIC_CODE

약물 및 장치 정보, 연구 문서

미국 FDA 규제 의약품 연구

아니

미국 FDA 규제 기기 제품 연구

아니

이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .