Editorial Commentary

Molecular Analysis for Therapy Choice: NCI MATCH

Scientific and technologic advances have led to a boon of candidate therapeutics for patients with malignancies of the central nervous system. The path from drug development to clinical use has generally followed a regimented order of sequential clinical trial phases. The recent increase in novel therapies, however, has strained the regulatory process and unearthed limitations of the current system, including significant cost, prolonged development time, and difficulties in testing therapies for rarer tumors. Novel clinical trial designs have emerged to increase efficiencies in clinical trial conduct to better evaluate and bring impactful drugs to patients in a timely manner. In order to better capture meaningful benefits for brain tumor patients, new endpoints to complement or replace traditional endpoints are also an increasingly important consideration. This review will explore the current challenges in the current clinical trial landscape and discuss novel clinical trial concepts, including consideration of limitations and risks of novel trial designs, within the context of neuro-oncology.

Genomic profiling technologies have enabled the development of targeted therapies designed to target specific biomarkers and molecular pathways involved in the pathophysiology of tumor initiation, metastasis, and drug resistance. In recent years, clinical trials with innovative design focus on the development of novel agents based on specific patient molecular alterations or other tumor characteristics and include patients with heterogenous tumor types. Precision oncology studies with innovative design associated with novel dose-finding approaches and data analysis focusing on subgroups of patients are characteristic of master protocols. Real-world data, patient-reported outcomes, and N-of-1 trials enhance the knowledge base of evidence to deliver personalized treatment to patients. Master protocols accelerate drug development by enabling simultaneous multiple sub-studies that match the patient’s tumor molecular profile with experimental treatment arms. However, the increased flexibility of precision oncology trials is often associated with small subpopulations of patients, which may be underpowered to draw statistically robust conclusions. Despite their limitations, innovative clinical trials continue to rapidly translate the emerging discoveries of novel drugs into unprecedented clinical outcomes in patients with cancer and to accelerate the implementation of precision oncology.

Cancer progression has been attributed to somatic changes in single-nucleotide variants, copy-number aberrations, loss of heterozygosity, chromosomal instability, epistatic interactions, and the tumor microenvironment. It is not entirely clear which of these changes are essential and which are ancillary to cancer. The dynamic nature of cancer evolution in a patient can be illuminated using several concepts and tools from classical evolutionary biology. Neutral mutation rates in cancer cells are calculable from genomic data such as synonymous mutations, and selective pressures are calculable from rates of fixation occurring beyond the expectation by neutral mutation and drift. However, these cancer effect sizes of mutations are complicated by epistatic interactions that can determine the likely sequence of gene mutations. In turn, longitudinal phylogenetic analyses of somatic cancer progression offer an opportunity to identify key moments in cancer evolution, relating the timing of driver mutations to corresponding landmarks in the clinical timeline. These analyses reveal temporal aspects of genetic and phenotypic change during tumorigenesis and across clinical timescales. Using a related framework, clonal deconvolution, physical locations of clones, and their phylogenetic relations can be used to infer tumor migration histories. Additionally, genetic interactions with the tumor microenvironment can be analyzed with longstanding approaches applied to organismal genotype-by-environment interactions. Fitness landscapes for cancer evolution relating to genotype, phenotype, and environment could enable more accurate, personalized therapeutic strategies. An understanding of the trajectories underlying the evolution of neoplasms, primary, and metastatic tumors promises fundamental advances toward accurate and personalized predictions of therapeutic response.

Molecular profiling provides the insight that specific genetic alterations can be detected across a wide range of different histologically characterised tumour types. Thus, the basic concept of basket trials (BTs) to target those genetic alterations with the same anti-tumour agents independent of the underlying tumour type was tumour agnostic. BTs can be divided into tumour gnostic, tumour semi-gnostic, and tumour agnostic trials which cover BTs of the conventional and the complex multiple-parallel type.

At the beginning of the use of BTs, the expectation that they would function agnostically was dominating. This period was followed by an avalanche of experiments, analyses, and commentaries that underlined the importance of the microenvironment of tumours and thereby the impact of tissue also on molecularly targeted therapies. Intra-tumour heterogeneity with the phenomena of both intrinsic resistant cancer cell subclones and treatment-emergent acquired mutations that result in drug resistance as well as the co-occurrence of multiple potentially actionable molecular alterations within a tumour necessitate combinatorial treatment. However, this setting has only scarcely been addressed by BTs so far.

Each of the various subtypes of BTs has contributed to meet the main goal of drug development, the approval of the agents tested. The position of BTs within the drug approval process and their potential impact on the off-label use of targeted agents are referred to as well.

This review highlights the achievements reached with BTs along with failures. Selected issues of controversy are critically discussed, and potential solutions are addressed.

Recent years have seen a change in the way that clinical trials are being conducted. There has been a rise of designs more flexible than traditional adaptive and group sequential trials which allow the investigation of multiple substudies with possibly different objectives, interventions, and subgroups conducted within an overall trial structure, summarized by the term master protocol. This review aims to identify existing master protocol studies and summarize their characteristics. The review also identifies articles relevant to the design of master protocol trials, such as proposed trial designs and related methods.

We conducted a comprehensive systematic search to review current literature on master protocol trials from a design and analysis perspective, focusing on platform trials and considering basket and umbrella trials. Articles were included regardless of statistical complexity and classified as reviews related to planned or conducted trials, trial designs, or statistical methods. The results of the literature search are reported, and some features of the identified articles are summarized.

Most of the trials using master protocols were designed as single-arm (n = 29/50), Phase II trials (n = 32/50) in oncology (n = 42/50) using a binary endpoint (n = 26/50) and frequentist decision rules (n = 37/50). We observed an exponential increase in publications in this domain during the last few years in both planned and conducted trials, as well as relevant methods, which we assume has not yet reached its peak. Although many operational and statistical challenges associated with such trials remain, the general consensus seems to be that master protocols provide potentially enormous advantages in efficiency and flexibility of clinical drug development.

Master protocol trials and especially platform trials have the potential to revolutionize clinical drug development if the methodologic and operational challenges can be overcome.