International study that will evaluate the association of prespecified biomarkers with resistance to Antibody-drug conjugates (ADCs), a type of targeted cancer treatment currently used in clinical practice for treating different tumor types.
Over the past five years, antibody-drug conjugates (ADCs) have dramatically improved survival in solid and hematologic malignancies. Among 14 ADCs approved worldwide, nine are now available in Europe, and over 370 others are in clinical development. This expanding landscape indicates that ADCs could soon replace conventional chemotherapy across multiple tumor types. Given this rapid evolution, clinicians will need to select the most suitable ADC for each patient, considering tumor biology, microenvironment (TME) and patient-specific factors. Yet, despite remarkable efficacy, resistance to ADCs eventually arises. Understanding resistance mechanisms is therefore essential to guide therapeutic sequencing and optimize next-generation ADCs. ADCs are complex molecules combining an antibody, a linker, and a cytotoxic payload. Their activity depends on factors such as antigen expression, internalization, linker stability, and payload sensitivity. Resistance can result from altered vascular perfusion, antigen downregulation, defective internalization or trafficking, impaired linker cleavage, drug efflux, or payload target modifications. These multifactorial processes differ from those driving resistance to traditional chemotherapies. Existing preclinical and clinical tools (Patient-Derived Xenograft(PDX)/Cell-line-Derived Xenograft (CDX) models, standard imaging, Immunohistochemistry (IHC), genomic profiling) fail to capture this complexity or predict ADC efficacy and resistance. Furthermore, ADCs often cause significant toxicities-on-target or off-target-affecting the ocular surface, skin, lungs, and peripheral nerves. Patient factors such as age, comorbidities, and weight influence these events. Understanding the determinants of toxicity is critical to maintain quality of life and treatment adherence. The OASIS program aims to identify predictive biomarkers of ADC response and toxicity to enable personalized ADC selection and toxicity prevention. This multicenter study will integrate advanced technologies-digital pathology, liquid biopsy, and Patient-derived organoids (PDOs)-to generate comprehensive biological and clinical data. Using these datasets, a multimodal machine-learning model (OASIS Multiparametric Score) will be developed to predict both efficacy and key toxicities of ADCs. The project will prospectively include patients receiving ADCs in standard practice, with longitudinal tumor and blood sampling to investigate biomarkers of resistance and toxicity. In parallel, preclinical models derived from patient tumors will explore resistance mechanisms and screen ADC sensitivity. A retrospective cohort of patients previously treated with ADCs will first be analyzed to prioritize biomarker candidates based on published data and prior findings. From this, five binary biomarkers will be selected for the primary objective. Combined with prospective data, this retrospective work will expand the translational biobank and support the construction of the OASIS score.
Biological samples collection (tumor tissue, blood, sputum) before initiation of treatment, during treatment, and at treatment discontinuation.
QLQ-C30, QLQ-FA12, HADS, EQ-5D 5L
Gustave Roussy Cancer Center
Villejuif, France
RECRUITINGBiomarkers of resistance to ADC
Resistance is defined by differences in the frequency (higher or lower) of molecular aberrations detected between paired baseline samples and progression samples (i.e., samples collected at the time of disease progression under ADC treatment)
Time frame: Through study completion, an average of 3 years
Additional biomarkers of resistance characterised by histology
Differences in the frequency of molecular aberrations characterised by histologic/proteomic/genomic/transcriptomic analysis between samples of patients progressing on ADC and paired pre-treatment samples (beyond biomarkers of primary outcome)
Time frame: Through study completion, an average of 3 years
Biomarkers of ADC outcome
Progression-Free Survival (PFS) defined as the time from start of treatment and radiological progression or death, whichever occurs first. Tumor assessments are made by local investigators as per standard practice (RECIST 1.1.). Patients still alive at the cut-off time without documented progression (including lost to follow-up) will be censored at the time of latest evaluable efficacy assessment.
Time frame: From first day of cycle 1 (each cycle is 21 to 28 days) to date of first documented progression or date of death from any cause, whichever came first, assessed up to 60 months
Biomarkers of ADC outcome
Objective Response Rate (ORR) defined as the proportion of patients with a confirmed complete response (CR) or partial response (PR) assessed by investigators after 6 months of treatment.
Time frame: From first day of cycle 1 (each cycle is 21 to 28 days) to date of 6 months of treatment completion
Biomarkers of ADC outcome
Clinical Benefit Rate (CBR) defined as the proportion of patients who had a CR, PR, or stable disease for 6 months or more.
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
BASIC_SCIENCE
Masking
NONE
Enrollment
400
Time frame: From first day of cycle 1 (each cycle is 21 to 28 days) to date of first documented progression or date of death from any cause, whichever came first, assessed up to 60 months
Biomarkers of resistance to ADC
Duration of response (DOR) defined as the time from treatment initiation to disease progression or death for patients who achieve CR or PR.
Time frame: From first day of cycle 1 (each cycle is 21 to 28 days) to date of first documented progression or date of death from any cause, whichever came first, assessed up to 60 months
Biomarkers of ADC outcome
Overall Survival (OS) defined as the time from inclusion to death due to any cause. Patients still alive at the cut-off time (including lost to follow-up) will be censored at the last known alive date.
Time frame: From first day of cycle 1 (each cycle is 21 to 28 days) to date of death from any cause, assessed up to 60 months
Expression of ADC target measured on CTC and within tumor tissue
Concordance between ADC target expression (HER2, TROP-2, Nectin-4) on pre- and post-treatment tumor biopsy (IHC) and antigen expression on Circulating Tumor Cells (CTCs).
Time frame: Through study completion, an average of 3 years
Patients' reported outcomes (PROs)
Overall quality of life will be assessed using the EORTC-QLQ-C30 and EQ-5D-5L at Baseline, after 3 months of treatment completion, at treatment discontinuation (for progression or any other reason)
Time frame: Through study completion, an average of 3 years
Patients' reported outcomes (PROs)
Fatigue will be assessed using QLQ-FA12 at Baseline, after 3 months of treatment completion, at treatment discontinuation (for progression or any other reason).
Time frame: Through study completion, an average of 3 years
Patients' reported outcomes (PROs)
Anxiety and depression will be assessed using HADS questionnaire at Baseline, after 3 months of treatment completion, at treatment discontinuation (for progression or any other reason)
Time frame: Through study completion, an average of 3 years
Treatment cost
Number of resources consumed in terms of treatment, hospitalization (for drug administration and toxicity), biological and radiological exams during the ADC treatment, in order to calculated the corresponding management cost.
Time frame: Through study completion, an average of 3 years
ADC-related specific toxicities
Safety as measured by the frequency and severity of key ADC toxicity (Interstitial Lung Disease, skin toxicity, ocular toxicity, peripheral neuropathy) as measured by NCI-CTCAE v 5.0.
Time frame: Through study completion, an average of 3 years