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.