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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT06321640
Other study ID # IEO 1777
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date July 8, 2022
Est. completion date December 31, 2025

Study information

Verified date March 2024
Source European Institute of Oncology
Contact Luca Mazzarella
Phone +390294375111
Email luca.mazzarella@ieo.it
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

Novel treatment modalities like targeted therapies and Immune checkpoint inhibitors have revolutionised the therapeutic landscape in oncology and hematology, significantly improving outcomes even in clinical contexts in which little improvement had been observed for decades such as metastatic melanoma, lung cancer, and lymphoproliferative neoplasms such as chronic lymphoid leukemia or Hodgkin lymphoma. However, major issues remain unsolved, given the frequent occurrence of primary or secondary resistance and the still incomplete understanding of the physiopathology of adverse events, which represent a major cause of morbidity and treatment interruption and often remain difficult to treat and diagnose. In this complex landscape, identifying the best treatment option for each patient remains challenging. For both targeted therapies and Immune checkpoint inhibitors, several biomarkers have been reported, but their implementation in clinical practice is still uncommon, and most of the decision-making process remains based on purely clinical considerations or constraints dictated by the regulatory bodies. Obstacles to biomarker-driven decision making are manifold and include insufficient understanding of the underlying biology, lack of strong evidence on their predictive power and limited tumor sampling, which may be circumvented by non-invasive techniques such as liquid biopsies.


Description:

Biomarkers to predict response and toxicity to Targeted Therapies. Targeted therapies such as kinase inhibitors are usually associated with extremely elevated response rates, precisely because their use requires the prior detection of a companion biomarker. However, secondary resistance almost invariably develops, resulting in often moderate improvements in overall survival despite major delays in disease progression. Resistance mechanisms can be broadly classified in two groups: i) "cis"-mutations that directly impinge on the binding of the drug to its target and ii) "trans" alterations that activate additional pathways able to override drug-induced inhibition or transcriptional upregulation of parallel pathways . In both cases these mutations are mostly acquired as an evolutionary response to the selective environment generated by the drug itself, and their identification is crucial to identify potential subsequent treatments able to circumvent the resistance mechanism. As more targeted therapies enter clinical practice, including novel classes like Antibody-drug conjugates (which maintain high target specificity but have completely different mechanisms of action), extensive investigation of the molecular mechanisms associated with secondary resistance becomes more and more relevant. Furthermore, many targeted therapies are associated with specific toxicities such as interstitial lung disease that are themselves poorly characterized from a mechanistic point of view, and this lack of knowledge prevents effective diagnosis and treatment. Biomarkers to predict response and toxicity to Immune Checkpoint Inhibitors. Several biomarkers with predictive power in Immune checkpoint inhibitorsI-treated patients have been reported (e.g. tumor mutational burden, extent of tumour T-cell infiltration at baseline, expression by tumor cells of the respective Immune checkpoint inhibitors targets). However each of these, individually, bears very little accuracy for outcome . A recent meta-analysis of tumor-intrinsic data across >1,000 patients and multiple tumor types elaborated a multivariable predictive model for each cancer type using 11 features derived from genomic (whole exome sequencing ) and transcriptomic (total ribonucleic acid sequencing ) data of primary tumors (see below for the list of markers). The multivariable predictor attained an Afea Under the Receiver-Operating Characteristic value of 0.86, thus strongly indicating that an integrated assessment of multiple and novel biomarkers achieves an accuracy that can significantly impact on decision making. Moreover, recent findings suggest a critical role for the gut microbiome. Notably, specific species in the gut microbiota promote anti-cancer immunity during Immune checkpoint inhibitors treatment, which can be transferred by faecal microbiome transplantation to rescues Immune checkpoint inhibitors sensitivity in model systems . Underlying molecular mechanisms, however, are unknown, and may involve immunological mimicry of tumour neoantigens by microbial peptides from the gut or tumor microbiota . The issue of drug-related toxicities (Immune-related Adverse events) is possibly even more crucial in Immune checkpoint inhibitors-treated patients. Immune-related Adverse events commonly develop after a long latency, are associated with significant morbidity and mortality and often represent a reason for treatment discontinuation and disease relapse. Immune-related Adverse events are often difficult to diagnose, since their pathophysiology is different from that of clinically similar idiopathic autoimmune disorders. Despite the definition of consensus guidelines on the diagnosis and treatment of Immune-related Adverse events, therapeutic options are limited and invariably include generalized immune suppression, to the detriment of the anticancer response. Biomarkers strongly predictive or diagnostic of Immune-related Adverse events have not been identified to date. Some studies have identified specific cytokine combinations but these studies remain correlative and require validation in larger cohorts and different clinical contexts.


Recruitment information / eligibility

Status Recruiting
Enrollment 265
Est. completion date December 31, 2025
Est. primary completion date December 31, 2024
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - age>18 yrs old - histological diagnosis of any cancer - signed informed consent - fulfills criteria described in cohort definition - Clinical indication for a diagnostic biopsy Exclusion Criteria: Performance Status (ECOG) >2 - life expectancy < 3 months - unwilling to receive treatment at IEO for at least 6 months after enrolment - active pregnancy at the moment of enrolment - for cohort F: use of steroids (higher than 10 mg prednisone-equivalent) or other major immunosuppressive drug (e.g. tocilizumab) in the 14 days prior to the baseline sample collection.

Study Design


Intervention

Genetic:
Cohort A: primarily operable disease, candidate to adjuvant
This cohort includes any patient with nonmetastatic disease, candidate to surgery as primary treatment, for whom adjuvant therapy with targeted or immune therapy is recommended based on prior information obtained on the diagnostic biopsy. This cohort represents a control group, for whom high-throughput DNA/RNA sequencing is considered feasible in the vast majority of cases, and will not be considered in the computation of the primary endpoint
Cohort B: locally advanced disease
Patients in this cohort are eligible if diagnosed with or highly suspected of locally advanced (nonmetastatic) neoplasm and candidate to a diagnostic/confirmatory biopsy and subsequent treatment with targeted therapy, immune therapy or radiotherapy, where the treatment is administered with potentially curative intent. Patients in this cohort may be considered for enrolment prior to a formal diagnosis, so the study should be offered on the basis of a high suspicion of invasive cancer upon radiological evidence.
Cohort C: metastatic disease
In this cohort, patients are eligible if diagnosed with invasive cancer with radiologically proven metastatic localization and candidate to treatment with targeted or immune therapy.
Cohort D: Progressive disease
In this cohort, patients are eligible if a tumor biopsy is considered indicated by the referring physician upon disease progression to prior treatment in the metastatic setting or for hematological neoplasms. Definition of progression is based on the investigator's judgement and does not strictly require RECIST 1.1 definition, although all relevant radiological data will be collected whenever possible. Tumor biopsy must be collected no more than 6 months after the documented date of progression.
Cohort E: Hematological neoplasms
Any patient that is expected to be treated with targeted agents. Special consideration will be given to patients affected by chronic lymphoid leukemia and follicular lymphoma treated with BTKi, PI3Ki, BCL-2i +/- monoclonal antibodies. Any patient that is expected to be treated with immunotherapy. Special consideration will be given to patients affected by Hodgkin lymphoma and Diffuse Large B-cell lymphoma treated with ICIs, Tafasitamab/Lenalidomide, immunoconjugates.
Cohort F: Toxicity
In this cohort, patients are enrolled upon experiencing an adverse event of grade 3/4 as per CTCAE v 5.0 that, in the opinion of the investigator, is unequivocally caused by a targeted or immune therapeutic. The event may occur at any time after the last dose of the drug. Events may be of any nature but particular attention will be given to those events for which pathophysiology is currently poorly understood (severe myocardial or neurologic Immune-related events or DS-8201-induced pneumonitis)

Locations

Country Name City State
Italy European Institute of oncology Milan

Sponsors (1)

Lead Sponsor Collaborator
European Institute of Oncology

Country where clinical trial is conducted

Italy, 

Outcome

Type Measure Description Time frame Safety issue
Primary Percentage of patients in each cohort that will obtain a full "core" omic characterization. For cohorts A-E:
i) Whole Exome Sequencing of tumor samples (biopsy/surgery) ii) ribonucleic acid sequence iii) Whole-genome "shotgun" metagenomic sequencing of fecal samples
For cohorts C and D:
i) Computation of the 11-parameter multivariable score: clonal Tumor Mutation Load, indel Tumor Mutation Load, nonsense mediated decay-escape Tumor Mutation Load, tobacco signature etc.
For cohorts E,F i) High throughput cytokine bead array on plasma samples ii) ribonucleic acid sequence iii) Whole-genome "shotgun" metagenomic sequencing of fecal samples
2 months
Secondary Percentage of patients with complete clinical data collection over the expected follow-up time and with successful biobanking. Percentage of patients with complete clinical and laboratory data collection over the expected follow-up time (2 years); Percentage of patients with successful biobanking (presence of at least 1 frozen tumor sample, 1 vial of EDTA blood, 2 vials of plasma at T0, T1, T2, 1 vial of feces at T0, T1, T2).Somatic mutations associated with sensitivity, primary/secondary resistance and toxicity;Prevalence of specific signaling-pathway transcriptional-activation signatures associated with sensitivity, primary/secondary resistance and toxicity;Prevalence of specific microbiota signatures associated with sensitivity, primary/secondary resistance and toxicity; Prevalence of germline variants associated with sensitivity, primary/secondary resistance and toxicity; 2 years
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