Immunotherapy Master Trial for Advanced Cancers

Over the past decade, cancer immunotherapy has profoundly transformed oncology by harnessing the patient's immune system to target tumors. These therapies have demonstrated the potential for durable responses and, in some cases, long-term remission or cure. However, despite these advances, only approximately 20-30% of patients derive significant clinical benefit from current immunotherapies. In parallel, investment in oncology drug development continues to grow, with global spending projected to reach $307 billion by 2026. Yet, the overall failure rate in oncology drug development remains extremely high, at around 95%, highlighting a critical gap between scientific innovation and clinical success. One major contributor to these failures lies in traditional drug development and regulatory paradigms, which have historically relied on cancer histology as the primary framework for patient selection and treatment evaluation. This approach is based on the flawed assumption that tumors of the same histological type share similar biological behavior and therapeutic vulnerabilities, and that localized and advanced disease are biologically comparable. In reality, tumor biology-rather than histology-plays a decisive role in determining immunotherapy efficacy. Substantial heterogeneity exists within the same cancer type, leading to widely variable patient outcomes even among individuals receiving identical treatments. The recent emergence of tumor-agnostic approvals for immunotherapies has reinforced the importance of shared biological features across cancer types. Approvals of anti-PD-1 therapies for microsatellite instability-high (MSI-H), mismatch repair-deficient (dMMR), or tumor mutational burden-high (TMB-H) cancers have demonstrated that biological characteristics can transcend tissue of origin. However, the predictive value of current companion diagnostic assays remains limited. Only 30-40% of biomarker-positive patients respond to treatment, underscoring the inadequacy of existing patient selection strategies. These limitations are partly driven by the methodologies used in industry-sponsored clinical trials, which typically rely on tumor samples processed by contract research organizations (CROs). For logistical reasons, analyses are performed on formalin-fixed paraffin-embedded (FFPE) or frozen tissues using conventional techniques such as immunohistochemistry (IHC) and DNA/RNA sequencing. While informative, these methods are often slow, complex, and insufficiently sensitive or specific to guide timely treatment decisions, particularly when results are required within the 3-4 week window following trial consent. Moreover, they offer limited insight into dynamic parameters such as target expression, saturation, and engagement during treatment. There is therefore a pressing need for innovative oncology drug development strategies that prioritize biologically driven patient selection, support tumor-agnostic approaches, and enable truly personalized cancer therapy. Addressing this need requires technologies capable of rapid, comprehensive, and functional immune and tumor profiling. METAREM is part of the broader REMISSION program, which aims to improve treatment stratification and generate early clinical evidence to support the development of novel therapies and patient selection strategies. METAREM is a master protocol designed to test innovative treatment approaches through dedicated sub-protocols in patients with unresectable locally advanced or metastatic cancers. All patients enrolled in METAREM undergo in-depth immuno-biological characterization at both tumor and blood levels using the PORTRAIT immunoprofiling platform. PORTRAIT analysis is performed on fresh whole blood and fresh tumor biopsies, enabling rapid, sensitive, and highly specific profiling of each patient's immune and tumor biology. This real-time approach overcomes the limitations of conventional tissue-based assays and allows for a comprehensive understanding of disease mechanisms at the individual level. By integrating these data, METAREM aims to stratify patients into the most appropriate therapeutic sub-protocols, thereby advancing personalized cancer treatment and supporting more efficient, biology-driven drug development.

Understanding cancer as a pathological condition, both clinically and biologically, has profoundly shaped the evolution of therapeutic strategies in oncology. Over the past decade, the emergence of immune checkpoint-targeted cancer immunotherapies has triggered a major paradigm shift. These treatments not only integrate fundamental insights from cancer and immune cell biology into clinical practice, but also demonstrate that targeting the immune system can, in many cases, provide superior and more durable outcomes compared with approaches focused solely on cancer cells. Despite this transformative progress, the success rate of novel anticancer agents in clinical development remains unacceptably low, with failure rates exceeding 90%. One key contributor to this persistent inefficiency is the continued enrollment of patients in clinical trials based on the flawed assumption that individuals with the same cancer histology and stage are biologically and functionally equivalent. After more than a decade of intensive clinical and translational research, it has become evident that this assumption does not reflect biological reality. First, within any given tumor indication and disease stage, there is marked inter-individual biological variability. This heterogeneity arises from multiple, interconnected factors, including somatic genetic and epigenetic alterations within cancer cells, inherited germline polymorphisms affecting immune regulation, environmental influences that shape the composition and function of innate and adaptive immune cells, and variability in the magnitude and quality of tumor antigen-specific immune responses. Together, these elements generate distinct tumor-host ecosystems that profoundly influence therapeutic responsiveness. Second, common biological features can be shared across different cancer indications and confer similar levels of treatment efficacy irrespective of tissue of origin. For example, tumors characterized by microsatellite instability-high (MSI-H) status or high tumor mutational burden (TMB-H) demonstrate objective response rates of approximately 30% across multiple cancer types when treated with immune checkpoint inhibitors. These observations have challenged the traditional histology-based framework and paved the way for tumor-agnostic therapeutic approvals. Third, the efficacy of immune checkpoint-targeted therapies depends far more on the tumor microenvironment and host-related factors than on cancer histology itself. Critical determinants of response include tumor-infiltrating lymphocytes, the presence of tertiary lymphoid structures, PD-L1 expression, tumor mutational burden, and other genomic features, as well as host parameters such as lactate dehydrogenase levels, metastatic burden (notably liver metastases), systemic inflammation, and the gut microbiome. These tumor and host characteristics also explain why the majority of patients still fail to benefit from immune checkpoint blockade. Collectively, these insights indicate that clinical outcomes in oncology would be substantially improved by better orientation and stratification of patients based on their individual tumor and host biological profiles. However, the diagnostic and molecular screening techniques currently used in routine clinical practice are poorly suited to this task. Many lack sufficient sensitivity or specificity-particularly when assessing protein expression on defined cellular subsets-and are associated with long turnaround times that are incompatible with real-time clinical decision-making. Compounding this issue, clinical drug development in oncology traditionally begins with first-in-human phase I trials conducted in patients with relapsing or refractory advanced, often metastatic, disease. When efficacy is not demonstrated in this late-stage setting, drug development programs are frequently terminated under the assumption that the therapy would not perform better in earlier disease stages. Emerging evidence, however, clearly shows that the biology of early-stage cancers differs fundamentally from that of advanced disease. Consequently, therapies with limited activity in metastatic settings may exhibit substantial efficacy in localized or early-stage disease, highlighting a critical limitation of current development paradigms. Against this backdrop, the oncology field would greatly benefit from strategies capable of characterizing patients' cancer biology in real time. Such approaches should enable accurate assessment of pharmacodynamic parameters, including target expression, target occupancy, and target engagement, while supporting biomarker-driven therapeutic stratification. In this context, master protocols offer a powerful and efficient framework for clinical research. A master protocol provides a unified structure for the simultaneous evaluation of multiple investigational therapies within a single overarching clinical framework. Guided by predefined mechanistic hypotheses and tailored endpoints, this approach ensures consistency across operational, regulatory, and methodological aspects while streamlining review processes, facilitating site participation, and accelerating study implementation. By eliminating redundancies, master protocols optimize resource utilization and expedite patient access to innovative therapies. The inherent adaptability of a master protocol, supported by individual sub-protocols, allows for the rapid initiation or closure of specific investigations without disrupting ongoing studies. The integration of innovative trial designs and adaptive analytical methods, including Bayesian decision rules, maximizes knowledge generation by leveraging data across related sub-protocols and incorporating relevant historical information. This strategy enables meaningful clinical investigation with fewer patients while maintaining robust scientific rigor. Additional advantages of master protocols include centralized governance to ensure patient safety and methodological consistency, standardized systems and processes to enhance operational efficiency, uniform study language across sub-protocols and informed consent documents, simplified registration and recruitment procedures, centralized data and informatics infrastructure, and the flexibility to adapt investigational priorities based on emerging safety and efficacy signals. Together, these features support faster and more reliable generation of early-stage data to inform subsequent confirmatory studies. Importantly, while many immune- and tumor-targeted therapies enter clinical development with strong preclinical rationale, sponsors and investigators often lack real-time confirmation that enrolled patients actually express the intended therapeutic targets. This represents a major limitation of evidence-based drug development in oncology. Routine diagnostic tools-including immunohistochemistry on formalin-fixed or frozen tissues and bulk DNA or RNA sequencing-are poorly sensitive or specific, provide limited spatial or cellular resolution, and are associated with long turnaround times of several weeks to months. Moreover, these methods cannot adequately address critical questions related to target saturation and engagement following treatment. Routine blood tests offer only coarse information on systemic immune and inflammatory status and fail to capture the complexity of the immune landscape. Recent data demonstrate that novel approaches based on fresh biological samples can more accurately define the biological context of individual patients and better predict responses to cancer immunotherapies. Ultrasensitive, multiplexed cytokine profiling in patient plasma can identify baseline levels of interleukin-6 or interleukin-8 associated with primary resistance to PD-(L)1 blockade. Similar analyses performed on supernatants from freshly collected tumor biopsies reveal key cytokines and soluble factors linked to treatment efficacy at baseline and during therapy. In parallel, multiparametric flow cytometry applied to fresh whole blood or dissociated tumor tissues enables precise identification of cellular subsets and quantification of protein expression levels relevant to immunotherapy response. These techniques require minimal pre-analytical processing and can deliver actionable results on the day of sample acquisition, making them uniquely suited for real-time clinical application. The PORTRAIT method (Profile in Onco-immunology for a Rapid Treatment Research Adapted to Immunity and Tumor) has been developed to address these unmet needs. By integrating advanced cellular and molecular analyses of fresh tumor and blood samples, PORTRAIT provides oncologists and patients with timely, relevant information on tumor and immune biology. This enables informed treatment selection and dynamic assessment of therapeutic impact on both the disease and the host. Within this framework, the METAREM master protocol will apply baseline PORTRAIT profiling across its sub-protocols using freshly collected tumor biopsies and blood samples from cancer patients. Multicolor flow cytometry of fresh mononuclear cells from blood and tumor tissues will be used for targeted biomarker screening, while plasma and tumor secretomes will be analyzed for cytokines, chemokines, and soluble factors. PORTRAIT analyses will be conducted at baseline prior to initiation of a new line of therapy and, when specified, at defined on-treatment time points. For investigational immunotherapeutic agents whose predictive biomarkers are not yet established, PORTRAIT data will not be used for prospective patient selection but instead will support retrospective discovery of biomarkers associated with therapeutic efficacy. Through this approach, METAREM aims to enable biologically informed patient stratification, accelerate the development of effective immunotherapies, and ultimately improve outcomes across the cancer continuum.