Phase II, open-label study evaluating the activity of imatinib in treating life-threatening malignancies known to be associated with imatinib-sensitive tyrosine kinases

Fusion Challenges in Solid Tumors: Shaping the Landscape of Cancer Care in Precision Medicine

Targeting actionable fusions has emerged as a promising approach to cancer treatment. Next-generation sequencing (NGS)-based techniques have unveiled the landscape of actionable fusions in cancer. However, these approaches remain insufficient to provide optimal treatment options for patients with cancer. This article provides a comprehensive overview of the actionability and clinical development of targeted agents aimed at driver fusions. It also highlights the challenges associated with fusion testing, including the evaluation of patients with cancer who could potentially benefit from testing and devising an effective strategy. The implementation of DNA NGS for all tumor types, combined with RNA sequencing, has the potential to maximize detection while considering cost effectiveness. Herein, we also present a fusion testing strategy aimed at improving outcomes in patients with cancer.

Biomarker-driven basket trial designs: origins and new methodological developments

Due to increased use of gene sequencing techniques, understanding of cancer on a molecular level has evolved, in terms of both diagnosis and evaluation in response to initial therapies. In parallel, clinical trials meant to evaluate molecularly-driven interventions through assessment of both treatment effects and putative predictive biomarker effects are being employed to advance the goals of precision medicine. Basket trials investigate one or more biomarker-targeted therapies across multiple cancer types in a tumor location agnostic fashion. The review article offers an overview of the traditional forms of such designs, the practical challenges facing each type of design, and then review novel adaptations proposed in the last few years, categorized into Bayesian and Classical Frequentist perspectives. The review article concludes by summarizing potential advantages and limitations of the new trial design solutions.

Clinical Activity of TGF-β Inhibitor Vactosertib in Combination with Imatinib in Desmoid Tumors: A Multicenter Phase Ib/II Study

PURPOSE

The study was to determine the activity and safety of the TGF-β inhibitor vactosertib in combination with imatinib in patients with desmoid tumors.

PATIENTS AND METHODS

In this investigator-initiated, open-label, multicenter, phase Ib/II trial, patients with desmoid tumors not amenable to locoregional therapies (surgery and/or radiotherapy) or with disease progression following at least one treatment were enrolled. Participants were administered 400 mg imatinib daily in combination with vactosertib (5 days on and 2 days off, twice a day) every 28 days. In phase Ib, the vactosertib dose was set at 100 mg (level -1) and 200 mg (level 1) to determine the recommended phase II dose (RP2D). Phase II assessed the efficacy, with the primary endpoint being progression-free rate (PFR) at 16 weeks.

RESULTS

No dose-limiting toxicities were observed during phase Ib; therefore RP2D was defined at doses of 400 mg imatinib daily in combination with 200 mg vactosertib. Of the 27 patients evaluated, 7 (25.9%) achieved a confirmed partial response and 19 (70.4%) were stable. The PFR at 16 weeks and 1 year were 96.3% and 81.0%, respectively. Most toxicities were mild to moderate myalgia (n = 10, 37%), anemia (n = 10, 37%), and nausea (n = 9, 33.3%). Common grade 3 to 4 toxicities included neutropenia (n = 6, 22.2%) and anemia (n = 5, 18.5%).

CONCLUSIONS

The vactosertib and imatinib combination was well tolerated, with promising clinical activity in patients with progressive, locally advanced desmoid tumors. This is the first study investigating a novel target agent, a TGF-β inhibitor, in this rare and difficult-to-treat desmoid tumor.

Functional Classification of Fusion Proteins in Sarcoma

Sarcomas comprise a heterogeneous group of malignant tumors of mesenchymal origin. More than 80 entities are associated with different mesenchymal lineages. Sarcomas with fibroblastic, muscle, bone, vascular, adipocytic, and other characteristics are distinguished. Nearly half of all entities contain specific chromosomal translocations that give rise to fusion proteins. These are mostly pathognomonic, and their detection by various molecular techniques supports histopathologic classification. Moreover, the fusion proteins act as oncogenic drivers, and their blockade represents a promising therapeutic approach. This review summarizes the current knowledge on fusion proteins in sarcoma. We categorize the different fusion proteins into functional classes, including kinases, epigenetic regulators, and transcription factors, and describe their mechanisms of action. Interestingly, while fusion proteins acting as transcription factors are found in all mesenchymal lineages, the others have a more restricted pattern. Most kinase-driven sarcomas belong to the fibroblastic/myofibroblastic lineage. Fusion proteins with an epigenetic function are mainly associated with sarcomas of unclear differentiation, suggesting that epigenetic dysregulation leads to a major change in cell identity. Comparison of mechanisms of action reveals recurrent functional modes, including antagonism of Polycomb activity by fusion proteins with epigenetic activity and recruitment of histone acetyltransferases by fusion transcription factors of the myogenic lineage. Finally, based on their biology, we describe potential approaches to block the activity of fusion proteins for therapeutic intervention. Overall, our work highlights differences as well as similarities in the biology of fusion proteins from different sarcomas and provides the basis for a functional classification.

A confirmatory basket design considering non-inferiority and superiority testing

For multiple rare diseases as defined by a common biomarker signature, or a disease with multiple disease subtypes of low frequency, it is often possible to provide confirmatory evidence for these disease or subtypes (baskets) as a combined group. A novel drug, as a second generation, may have marginal improvement in efficacy overall but superior efficacy in some baskets. In this situation, it is appealing to test hypotheses of both non-inferiority overall and superiority on certain baskets. The challenge is designing a confirmatory study efficient to address multiple questions in one trial. A two-stage adaptive design is proposed to test the non-inferiority hypothesis at the interim stage, followed by pruning and pooling before testing a superiority hypothesis at the final stage. Such a design enables an efficient and novel registration pathway, including an early claim of non-inferiority followed by a potential label extension with superiority on certain baskets and an improved benefit-risk profile demonstrated by longer term efficacy and safety data. Operating characteristics of this design are examined by simulation studies, and its appealing features make it ready for use in a confirmatory setting, especially in emerging markets, where both the need and the possibility for efficient use of resources may be the greatest.

Sarcoma care in the era of precision medicine

Sarcoma subtype classification is currently mainly based upon histopathological morphology. Molecular analyses have emerged as an efficient addition to the diagnostic workup and sarcoma care. Knowledge about the sarcoma genome increases, and genetic events that can either support a histopathological diagnosis or suggest a differential diagnosis are identified, as well as novel therapeutic targets. In this review, we present diagnostic, therapeutic, and prognostic molecular markers that are, or might soon be, used clinically. For sarcoma diagnostics, there are specific fusions highly supportive or pathognomonic for a diagnostic entity-for instance, SYT::SSX in synovial sarcoma. Complex karyotypes also give diagnostic information-for example, supporting dedifferentiation rather than low-grade central osteosarcoma or well-differentiated liposarcoma when detected in combination with MDM2/CDK4 amplification. Molecular treatment predictive sarcoma markers are available for gastrointestinal stromal tumor (GIST) and locally aggressive benign mesenchymal tumors. The molecular prognostic markers for sarcomas in clinical practice are few. For solitary fibrous tumor, the type of NAB2::STAT6 fusion is associated with the outcome, and the KIT/PDGFRA pathogenic variant in GISTs can give prognostic information. With the exploding availability of sequencing technologies, it becomes increasingly important to understand the strengths and limitations of those methods and their context in sarcoma diagnostics. It is reasonable to believe that most sarcoma treatment centers will increase the use of massive-parallel sequencing soon. We conclude that the context in which the genetic findings are interpreted is of importance, and the interpretation of genomic findings requires considering tumor histomorphology.

Modified study designs to expand treatment options in personalised oncology: a multistakeholder view

Personalised oncology, whereby patients are given therapies based on their molecular tumour profile, is rapidly becoming an essential part of optimal clinical care, at least partly facilitated by recent advances in next-generation sequencing-based technology using liquid- and tissue-based biopsies. Consequently, clinical trials have shifted in approach, from traditional studies evaluating cytotoxic chemotherapy in largely histology-based populations to modified, biomarker-driven studies (e.g. basket, umbrella, platform) of molecularly guided therapies and cancer immunotherapies in selected patient subsets. Such modified study designs may assess, within the same trial structure, multiple cancer types and treatments, and should incorporate a multistakeholder perspective. This is key to generating complementary, fit-for-purpose and timely evidence for molecularly guided therapies that can be used as proof-of-concept to inform further study designs, lead to approval by regulatory authorities and be used as confirmation of clinical benefit for health technology assessment bodies. In general, the future of cancer clinical trials requires a framework for the application of innovative technologies and dynamic design methodologies, in order to efficiently transform scientific discoveries into clinical utility. Next-generation, modified studies that involve the joint efforts of all key stakeholders will offer individualised strategies that ultimately contribute to globalised knowledge and collective learning. In this review, we outline the background and purpose of such modified study designs and detail key aspects from a multistakeholder perspective. We also provide methodological considerations for designing the studies and highlight how insights from already-ongoing studies may address current challenges and opportunities in the era of personalised oncology.

Inflammation across tissues: can shared cell biology help design smarter trials?

Immune-mediated inflammatory diseases (IMIDs) are responsible for substantial global disease burden and associated health-care costs. Traditional models of research and service delivery silo their management within organ-based medical disciplines. Very often patients with disease in one organ have comorbid involvement in another, suggesting shared pathogenic pathways. Moreover, different IMIDs are often treated with the same drugs (including glucocorticoids, immunoregulators and biologics). Unlocking the cellular basis of these diseases remains a major challenge, leading us to ask why, if these diseases have so much in common, they are not investigated in a common manner. A tissue-based, cellular understanding of inflammation might pave the way for cross-disease, cross-discipline basket trials (testing one drug across two or more diseases) to reduce the risk of failure of early-phase drug development in IMIDs. This new approach will enable rapid assessment of the efficacy of new therapeutic agents in cross-disease translational research in humans.

Pharmacogenomics: Driving Personalized Medicine

Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all "-omics" fields (e.g., proteomics, transcriptomics, metabolomics, and metagenomics). This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. Food and Drug Administration approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multicomponent biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues, providing insights into the current status and future direction of health care. SIGNIFICANCE STATEMENT: Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.

Unlocking multidimensional cancer therapeutics using geometric data science

Personalised approaches to cancer therapeutics primarily involve identification of patient sub-populations most likely to benefit from targeted drugs. Such a stratification has led to plethora of designs of clinical trials that are often too complex due to the need for incorporating biomarkers and tissue types. Many statistical methods have been developed to address these issues; however, by the time such methodology is available research in cancer has moved on to new challenges and therefore in order to avoid playing catch-up it is necessary to develop new analytic tools alongside. One of the challenges facing cancer therapy is to effectively and appropriately target multiple therapies for sensitive patient population based on a panel of biomarkers across multiple cancer types, and matched future trial designs. We present novel geometric methods (mathematical theory of hypersurfaces) to visualise complex cancer therapeutics data as multidimensional, as well as geometric representation of oncology trial design space in higher dimensions. The hypersurfaces are used to describe master protocols, with application to a specific example of a basket trial design for melanoma, and thus setup a framework for further incorporating multi-omics data as multidimensional therapeutics.

Tyrosine kinase inhibitors versus radiation therapy in unresectable dermatofibrosarcoma protuberans (DFSP): A narrative systematic review

BACKGROUND

In unresectable dermatofibrosarcoma protuberans (DFSP), no clear guideline exists regarding the use of tyrosine kinase inhibitors (TKI) versus radiotherapy. This study reviews current literature regarding TKI and radiotherapy in unresectable DFSP.

METHODS

Following PROSPERO registration (CRD42021232508), a systematic literature search was performed including all studies reporting clinical results of TKI and/or radiotherapy in the treatment of unresectable DFSP. A narrative synthesis was used to compare patient characteristics, outcomes, and adverse effects.

RESULTS

Of 1345 screened studies, 14 were included for review. Patient age ranged 18-77 years and 55% were male. Radiotherapy patients exhibited lower grade disease than TKI patients. Overall clinical benefit following TKI ranged from 70% to 96%. Radiotherapy patients exhibited control or resolution on last follow-up in 90% of cases. Radiotherapy adverse effects were mild, while TKI adverse effects were more severe and managed with dose reduction.

CONCLUSION

TKI may be employed in unresectable DFSP of all histology types whereas radiation alone may be limited to low-grade and classic-type DFSP. TKI may cause more severe adverse effects compared to radiation alone.

Bayesian hierarchical models for adaptive basket trial designs

Basket trials evaluate a single drug targeting a single genetic variant in multiple cancer cohorts. Empirical findings suggest that treatment efficacy across baskets may be heterogeneous. Most modern basket trial designs use Bayesian methods. These methods require the prior specification of at least one parameter that permits information sharing across baskets. In this study, we provide recommendations for selecting a prior for scale parameters for adaptive basket trials by using Bayesian hierarchical modeling. Heterogeneity among baskets attracts much attention in basket trial research, and substantial heterogeneity challenges the basic assumption of exchangeability of Bayesian hierarchical approach. Thus, we also allowed each stratum-specific parameter to be exchangeable or nonexchangeable with similar strata by using data observed in an interim analysis. Through a simulation study, we evaluated the overall performance of our design based on statistical power and type I error rates. Our research contributes to the understanding of the properties of Bayesian basket trial designs.

Targeted therapy for intractable cancer on the basis of molecular profiles: An open-label, phase II basket trial (Long March Pathway)

Purpose

We evaluated he effects of molecular guided-targeted therapy for intractable cancer. Also, the epidemiology of druggable gene alterations in Chinese population was investigated.

Materials and methods

The Long March Pathway (ClinicalTrials.gov identifier: NCT03239015) is a non-randomized, open-label, phase II trial consisting of several basket studies examining the molecular profiles of intractable cancers in the Chinese population. The trial aimed to 1) evaluate the efficacy of targeted therapy for intractable cancer and 2) identify the molecular epidemiology of the tier II gene alterations among Chinese pan-cancer patients.

Results

In the first stage, molecular profiles of 520 intractable pan-cancer patients were identified, and 115 patients were identified to have tier II gene alterations. Then, 27 of these 115 patients received targeted therapy based on molecular profiles. The overall response rate (ORR) was 29.6% (8/27), and the disease control rate (DCR) was 44.4% (12/27). The median duration of response (DOR) was 4.80 months (95% CI, 3.33-27.2), and median progression-free survival (PFS) was 4.67 months (95% CI, 2.33-9.50). In the second stage, molecular epidemiology of 17,841 Chinese pan-cancer patients demonstrated that the frequency of tier II gene alterations across cancer types is 17.7%. Bladder cancer had the most tier-II alterations (26.1%), followed by breast cancer (22.4%), and non-small cell lung cancer (NSCLC; 20.2%).

Conclusion

The Long March Pathway trial demonstrated a significant clinical benefit for intractable cancer from molecular-guided targeted therapy in the Chinese population. The frequency of tier II gene alterations across cancer types supports the feasibility of molecular-guided targeted therapy under basket trials.

Basket Trials: Review of Current Practice and Innovations for Future Trials

Advances in biology and immunology have elucidated genetic and immunologic origins of cancer. Innovations in sequencing technologies revealed that distinct cancer histologies shared common genetic and immune phenotypic traits. Pharmacologic developments made it possible to target these alterations, yielding novel classes of targeted agents whose therapeutic potential span multiple tumor types. Basket trials, one type of master protocol, emerged as a tool for evaluating biomarker-targeted therapies among multiple tumor histologies. Conventionally conducted within the phase II setting and designed to estimate high and durable objective responses, basket trials pose challenges to statistical design and interpretation of results. This article reviews basket trials implemented in oncology studies and discusses issues related to their statistical design and analysis.

Clinical trials in desmoid-type fibromatosis in children and adults: A systematic review

Desmoid-type fibromatosis (DTF) is a rare locally aggressive soft tissue neoplasm, which occurs in children and adults, with a peak incidence in young adults. For the majority of the patients, DTF is a chronic and symptomatic disease, which affects health-related quality of life. Systemic treatment regimens tend to differ for patients treated by pediatric oncologists compared to medical oncologists. This systematic review identified 14 clinical trials in children and adults with DTF. Tumor response and progression-free survival rates varied widely between studies and study populations. Treatment choices for patients with DTF are based on a paucity of (randomized) trials. Treatment principles of DTF are similar in pediatric and adult oncology, but the treatment itself is different. This seems mostly driven by a lack of tyrosine kinase inhibitor (TKI) accessibility in pediatric oncology. An insufficient number of studies examined patient-reported outcomes, which are extremely important for patients with a chronic disease like DTF.

Comprehensive Analysis of Acquired Genetic Variants and Their Prognostic Impact in Systemic Mastocytosis

Systemic mastocytosis (SM) is a rare clonal haematopoietic stem cell disease in which activating KIT mutations (most commonly KIT D816V) are present in virtually every (>90%) adult patient at similar frequencies among non-advanced and advanced forms of SM. The KIT D816V mutation is considered the most common pathogenic driver of SM. Acquisition of this mutation early during haematopoiesis may cause multilineage involvement of haematopoiesis by KIT D816V, which has been associated with higher tumour burden and additional mutations in other genes, leading to an increased rate of transformation to advanced SM. Thus, among other mutations, alterations in around 30 genes that are also frequently mutated in other myeloid neoplasms have been reported in SM cases. From these genes, 12 (i.e., ASXL1, CBL, DNMT3A, EZH2, JAK2, KRAS, NRAS, SF3B1, RUNX1, SF3B1, SRSF2, TET2) have been recurrently reported to be mutated in SM. Because of all the above, assessment of multilineage involvement of haematopoiesis by the KIT D816V mutation, in the setting of multi-mutated haematopoiesis as revealed by a limited panel of genes (i.e., ASXL1, CBL, DNMT3A, EZH2, NRAS, RUNX1 and SRSF2) and associated with a poorer patient outcome, has become of great help to identify SM patients at higher risk of disease progression and/or poor survival who could benefit from closer follow-up and eventually also early cytoreductive treatment.

Efficiency of a randomized confirmatory basket trial design constrained to control the family wise error rate by indication

Basket trials pool histologic indications sharing molecular pathophysiology, improving development efficiency. Currently, basket trials have been confirmatory only for exceptional therapies. Our previous randomized basket design may be generally suitable in the resource-intensive confirmatory phase, maintains high power even with modest effect sizes, and provides nearly k-fold increased efficiency for k indications, but controls false positives for the pooled result only. Since family wise error rate by indications may sometimes be required, we now simulate a variant of this basket design controlling family wise error rate at 0.025 k, the total family wise error rate of k separate randomized trials. We simulated this modified design under numerous scenarios varying design parameters. Only designs controlling family wise error rate and minimizing estimation bias were allowable. Optimal performance results when [Formula: see text]. We report efficiency (expected # true positives/expected sample size) relative to k parallel studies, at 90% power (“uncorrected”) or at the power achieved in the basket trial (“corrected,” because conventional designs could also increase efficiency by sacrificing power). Efficiency and power (percentage active indications identified) improve with a higher percentage of initial indications active. Up to 92% uncorrected and 38% corrected efficiency improvement is possible. Even under family wise error rate control, randomized confirmatory basket trials substantially improve development efficiency. Initial indication selection is critical.

Treatment of Recurrent or Metastatic Adenoid Cystic Carcinoma

PURPOSE OF REVIEW

Adenoid cystic carcinoma (ACC) is a rare and heterogeneous malignancy of secretory glands. Recurrence after curative-intent treatment is common, and approximately 40% of patients develop metastatic disease, for which consensus is lacking regarding therapeutic approaches. Here, we review the available therapies for recurrent/metastatic (R/M) ACC and offer our perspectives on future treatment options.

RECENT FINDINGS

Proteogenomic studies of ACC revealed two molecular subtypes with therapeutic implications: ACC-I (37% of cases) and ACC-II (63%); each has distinct disease biology and prognosis. Molecular drivers, such as NOTCH1, have emerged as potential therapeutic targets for ACC-I and are being explored in clinical trials. Despite its biological heterogeneity, treatment for R/M ACC is not personalized and limited to cytotoxic agents and VEGFR inhibitors, which produce modest responses and significant toxicity. The increasing understanding of ACC's molecular biology might guide the development of biomarkers for patient selection and new therapies development.

Modelling approaches for histology-independent cancer drugs to inform NICE appraisals: a systematic review and decision-framework

BACKGROUND

The first histology-independent marketing authorisation in Europe was granted in 2019. This was the first time that a cancer treatment was approved based on a common biomarker rather than the location in the body at which the tumour originated. This research aims to explore the implications for National Institute for Health and Care Excellence appraisals.

METHODS

Targeted reviews were undertaken to determine the type of evidence that is likely to be available at the point of marketing authorisation and the analyses required to support National Institute for Health and Care Excellence appraisals. Several challenges were identified concerning the design and conduct of trials for histology-independent products, the greater levels of heterogeneity within the licensed population and the use of surrogate end points. We identified approaches to address these challenges by reviewing key statistical literature that focuses on the design and analysis of histology-independent trials and by undertaking a systematic review to evaluate the use of response end points as surrogate outcomes for survival end points. We developed a decision framework to help to inform approval and research policies for histology-independent products. The framework explored the uncertainties and risks associated with different approval policies, including the role of further data collection, pricing schemes and stratified decision-making.

RESULTS

We found that the potential for heterogeneity in treatment effects, across tumour types or other characteristics, is likely to be a central issue for National Institute for Health and Care Excellence appraisals. Bayesian hierarchical methods may serve as a useful vehicle to assess the level of heterogeneity across tumours and to estimate the pooled treatment effects for each tumour, which can inform whether or not the assumption of homogeneity is reasonable. Our review suggests that response end points may not be reliable surrogates for survival end points. However, a surrogate-based modelling approach, which captures all relevant uncertainty, may be preferable to the use of immature survival data. Several additional sources of heterogeneity were identified as presenting potential challenges to National Institute for Health and Care Excellence appraisal, including the cost of testing, baseline risk, quality of life and routine management costs. We concluded that a range of alternative approaches will be required to address different sources of heterogeneity to support National Institute for Health and Care Excellence appraisals. An exemplar case study was developed to illustrate the nature of the assessments that may be required.

CONCLUSIONS

Adequately designed and analysed basket studies that assess the homogeneity of outcomes and allow borrowing of information across baskets, where appropriate, are recommended. Where there is evidence of heterogeneity in treatment effects and estimates of cost-effectiveness, consideration should be given to optimised recommendations. Routine presentation of the scale of the consequences of heterogeneity and decision uncertainty may provide an important additional approach to the assessments specified in the current National Institute for Health and Care Excellence methods guide.

FURTHER RESEARCH

Further exploration of Bayesian hierarchical methods could help to inform decision-makers on whether or not there is sufficient evidence of homogeneity to support pooled analyses. Further research is also required to determine the appropriate basis for apportioning genomic testing costs where there are multiple targets and to address the challenges of uncontrolled Phase II studies, including the role and use of surrogate end points.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Evidence Synthesis programme and will be published in full in Health Technology Assessment; Vol. 25, No. 76. See the NIHR Journals Library website for further project information.

Repurposing old molecules for new indications: Defining pillars of success from lessons in the past

Drug repurposing or studying existing drugs for potential therapeutic utility in newer indications has been identified as an attractive option for treating a number of diseases. Various strategies of drug repurposing include serendipitous observation of drug's unexpected effects, directing the failed investigational drugs to new indications and currently adopted systematic approach to identify, screen and develop existing drug molecules for new off-label indications. Drug repurposing is able to constructively overcome the bottleneck restraints encountered during traditional de novo drug development process in grounds of timelines, cost and resources. However, success rates of drug repurposing programs are not very impressive. Through a meticulous examination of some failed repurposing attempts we aimed to identify key factors leading to high attrition rate in such studies. Based on the fundamental elements of knowledge and evaluation, we have defined four pillars toward improving success rate in drug repurposing programs viz. sound knowledge of the repurposed drug's pharmacological characteristics (pillar 1: drug pharmacology); drug formulation considerations in new indication (pillar 2: drug formulation); evaluation in representative biological assays with translational potential (pillar 3: evaluation in biological assays); and robust clinical trial methodologies including biomarker driven approach to provide conclusive evidence of repurposed drug's efficacy in new indication (pillar 4: clinical evaluation). In addition to the pharmacological challenges, certain regulatory concerns, including lack of clear guidelines for evaluation and market exclusivity pose hurdles in the application of drug repurposing, which may however be overcome to a great extent by adopting some strategies as discussed in this review.

Master protocol trial design for technical feasibility of MR-guided radiotherapy

The master protocol trial design aims to increase efficiency in terms of trial infrastructure and protocol administration which may accelerate development of (technical) innovations in radiation oncology. A master protocol to study feasibility of techniques/software for MR-guided adaptive radiotherapy with the MR-Linac is described and discussed.

Incorporating covariates information in adaptive clinical trials for precision medicine

Precision medicine is the systematic use of information that pertains to an individual patient to select or optimize that patient's preventative and therapeutic care. Recent studies have classified biomarkers into predictive and prognostic biomarkers based on their roles in clinical studies. To design a clinical trial for precision medicine, predictive biomarkers and prognostic biomarkers should both be included. In statistical analysis, biomarkers are mathematically treated as covariates. We first classify covariates into predictive and prognostic covariates according to their roles. We then provide a brief review of recent advances in adaptive designs that incorporate covariates. However, the literature includes no designs that incorporate both prognostic covariates and predictive covariates simultaneously. In this paper, we propose a new family of covariate-adjusted response-adaptive (CARA) designs that incorporate both prognostic and predictive covariates and the responses. It is important to note that the predictive biomarkers and prognostic biomarkers play different roles in the new designs. The advantages of the proposed methods are demonstrated via numerical studies, and some further statistical issues are also discussed.

PATHOGENIC AND DIAGNOSTIC RELEVANCE OF KIT IN PRIMARY MAST CELL ACTIVATION DISORDERS

OBJECTIVE

Mast cell (MC) activation (MCA) defines the mechanism by which certain patients suffer from symptoms due to the effect of a wide range of mediators released from MC upon their activation triggered by different stimuli. When these symptoms are severe and recurrent, the diagnosis of MCA syndrome (MCAS) might be considered. Here we review the relevant aspects related to the pathogenesis of MCAS, with special emphasis on the prevalence and diagnostic relevance of KIT mutations.

DATA SOURCES

PubMed was searched between 1980 and 2021 using the following terms: Mast cell activation syndromes, mast cell activation, anaphylaxis, KIT mutations, KIT D816V, indolent systemic mastocytosis, bone marrow mastocytosis, cutaneous mastocytosis, IgE anaphylaxis and idiopathic anaphylaxis.

STUDY SELECTIONS

Only articles published in English were selected based on their relevance to MCAS and/or severe and recurrent anaphylaxis.

RESULTS

MCAS can be classified in clonal MCAS and non-clonal MCAS depending on the presence vs. absence of an underlying KIT mutation (mostly KIT D816V), respectively. In contrast to clonal MCAS in which MCA is associated with a primary MC disorder (i.e. primary MCAS) such as mastocytosis or monoclonal MCAS, non-clonal MCAS can be secondary to known or unidentified triggers (i.e. secondary and idiopathic MCAS, respectively).

CONCLUSION

The clinical heterogeneity and complexity of the molecular assays needed for the study of MCAS patients might lead to misdiagnosis, particularly when patients are evaluated at non-specialized centers. Thus, referral of patients suffering from clinical manifestations suggestive of MCAS to Reference Centers on mastocytosis and MC diseases is strongly recommended.

Rationale for the use of tyrosine kinase inhibitors in the treatment of paediatric desmoid-type fibromatosis

In children with desmoid-type fibromatosis (DTF) in whom disease progression occurs after an initial watch-and-wait strategy, prolonged low-dose chemotherapy using vinblastine and methotrexate (VBL-MTX) is currently the standard of care. These conventional drugs have been prospectively evaluated but their efficacy and safety profiles are limited, and alternative therapeutic options are therefore essential. Based on the results of clinical trials, the use of tyrosine kinase inhibitors (TKIs) in the treatment of DTF is currently considered only in adult patients. TKIs such as imatinib show superior therapeutic efficacy to VBL-MTX and tolerable short-term side effects for the treatment of adult DFT, supporting the concept of the use of TKIs for the treatment of paediatric DFT. Moreover, new-generation TKIs, such as pazopanib and sorafenib, have shown improved therapeutic efficacy compared to imatinib in adult non-comparative studies. A tolerable safety profile of TKI therapy in children with disease entities other than DTF, such as leukaemia, has been reported. However, the efficacy and, in particular, the long-term safety of TKIs, including childhood-specific aspects such as growth and fertility, for the treatment of children with DTF should be investigated prospectively, as DFT therapy requires long-term drug exposure.

Long-Term Outcome of Neoadjuvant Tyrosine Kinase Inhibitors Followed by Complete Surgery in Locally Advanced Dermatofibrosarcoma Protuberans

Simple Summary

Wide surgical excision is the standard treatment for dermatofibrosarcoma protuberans. Imatinib mesylate has been reported as an efficient neoadjuvant therapy to surgery in order to reduce tumor size and post-operative relapses for locally advanced or unresectable tumors. The aim of this study was to evaluate the long-term status of patients with advanced dermatofibrosarcoma protuberans treated by neoadjuvant tyrosine kinase inhibitors. Based on the data of 27 patients in our center, locally advanced and unresectable DFSP were efficiently treated with neoadjuvant tyrosine kinase inhibitors followed by complete surgery with micrographic analysis with durable local recurrence disease-free survival and few severe adverse events.

Abstract

In locally advanced dermatofibrosarcoma protuberans (DFSP), imatinib mesylate has been described as an efficient neoadjuvant therapy. This retrospective study included patients with locally advanced DFSP who received neoadjuvant TKI (imatinib or pazopanib) from 2007 to 2017 at Saint Louis Hospital, Paris. The primary endpoint was the evaluation of the long-term status. A total of 27 patients were included, of whom nine had fibrosarcomatous transformation. The median duration of treatment was 7 months. The best response to TKI treatment before surgery, evaluated according to RECIST1.1 on MRI, consisted of complete/partial response (38.5%) or stability (46.2%). DFSP was surgically removed in 24 (89%) patients. A total of 23 patients (85%) were disease-free after 64.8 months of median follow-up (95% confidence interval 47.8; 109.3). One patient developed distant metastases 37 months after surgical tumor resection and finally died. Two patients (7%) did not get surgery because of metastatic progression during TKI treatment, and one patient refused surgery even though the tumor decreased by 30%. Treatment-related adverse events (AE) occurred in 23 patients (85%). Only four patients (imatinib: n = 3, pazopanib: n = 1) had grade ≥3 AE requiring temporary treatment disruption. Neoadjuvant TKI followed by complete surgery with micrographic analysis is an effective strategy for locally advanced and unresectable DFSP, with durable local recurrence disease-free survival.

Correlation Between KIT Expression and c-Kit Mutations in 2 Subtypes of Canine Oral Melanocytic Neoplasms

c-Kit mutations have been reported in 15% to 40% of certain human melanoma subtypes, including those histologically similar to canine oral malignant melanomas. Therapeutic response to tyrosine kinase inhibitors has been demonstrated in those human patients. As canine oral malignant melanomas tend to have a poor prognosis despite aggressive surgical removal, evaluation of KIT expression and identification of c-Kit mutations in canine oral melanocytic neoplasms was performed to determine if there is any indication that tyrosine kinase inhibitor drugs might effectively treat any of these cases. This study evaluated 27 canine oral malignant melanomas and 12 canine histologically well-differentiated oral melanocytic neoplasms for activating c-Kit mutations, determined differences in immunohistochemical expression of KIT and c-Kit mutation status, and determined if KIT expression could predict c-Kit mutation status. Among samples that contained intraepithelial nests of neoplastic melanocytes in the KIT-labeled sections, KIT was expressed within cells in these nests in 22/23 (96%) malignant melanomas and 5/7 histologically well-differentiated neoplasms. KIT was expressed in 10% to 30% of neoplastic melanocytes in the lamina propria in 3/24 (13%) malignant melanomas, but 0/9 (0%) histologically well-differentiated neoplasms. Next-generation sequencing identified 85 variants in c-Kit, including 9 nonsynonymous mutations that resulted in amino acid changes predicted to affect protein function. c-Kit mutations with predicted deleterious protein effects were more common in malignant melanomas (8/27 [30%] vs 1/12 [8%]). There was no apparent relationship between detected c-Kit mutations and KIT expression. These results do not support the use of therapies that target c-Kit.

Response Criteria in Advanced Systemic Mastocytosis: Evolution in the Era of KIT Inhibitors

Systemic mastocytosis (SM) is a rare clonal hematologic neoplasm, driven, in almost all cases, by the activating KIT D816V mutation that leads to the growth and accumulation of neoplastic mast cells. While patients with advanced forms of SM have a poor prognosis, the introduction of KIT inhibitors (e.g., midostaurin, and avapritinib) has changed their outlook. Because of the heterogenous nature of advanced SM (advSM), successive iterations of response criteria have tried to capture different dimensions of the disease, including measures of mast cell burden (percentage of bone marrow mast cells and serum tryptase level), and mast cell-related organ damage (referred to as C findings). Historically, response criteria have been anchored to reversion of one or more organ damage finding(s) as a minimal criterion for response. This is a central principle of the Valent criteria, Mayo criteria, and International Working Group-Myeloproliferative Neoplasms Research and Treatment and European Competence Network on Mastocytosis (IWG-MRT-ECNM) consensus criteria. Irrespective of the response criteria, an ever-present challenge is how to apply response criteria in patients with SM and an associated hematologic neoplasm, where the presence of both diseases complicates assignment of organ damage and adjudication of response. In the context of trials with the selective KIT D816V inhibitor avapritinib, pure pathologic response (PPR) criteria, which rely solely on measures of mast cell burden and exclude consideration of organ damage findings, are being explored as more robust surrogate of overall survival. In addition, the finding that avapritinib can elicit complete molecular responses of KIT D816V allele burden, establishes a new benchmark for advSM and motivates the inclusion of definitions for molecular response in future criteria. Herein, we also outline how the concept of PPR can inform a proposal for new response criteria which use a tiered evaluation of pathologic, molecular, and clinical responses.

Novel Study Designs in Precision Medicine - Basket, Umbrella and Platform Trials

The concept of 'one size fits all' - one treatment for patients with a particular disease, seems to be outdated. The advent of precision medicine has prompted profound changes in clinical research and it allows researchers to predict, more accurately, the prevention and treatment strategies for a specific disease population. Novel study designs are, therefore, essential to establish safe and effective personalized medicine. Basket, umbrella and platform trial designs (collectively referred to as master protocols) are biomarker enrichment designs that allow for testing more than one hypothesis within a protocol, thus accelerating drug development. These trial designs tailor intervention strategies based on patient's risk factor(s) that can help predict whether they will respond to a specific treatment. Basket trials evaluate therapy for various diseases that share a common molecular alteration while umbrella trials evaluate multiple targeted therapies for a single disease that is stratified into subgroups based on different molecular alterations/ risk factors. These designs are complex and their major limitations stem from the fact that it would be inappropriate to completely replace histological typing with molecular profiling alone. However, in the upcoming decades, these trial designs are likely to gain popularity and improve the efficiency of clinical research. This article briefly overviews the characteristics of master protocol designs with examples of completed and ongoing clinical trials utilizing these study designs.

Statistical design considerations for trials that study multiple indications

Breakthroughs in cancer biology have defined new research programs emphasizing the development of therapies that target specific pathways in tumor cells. Innovations in clinical trial design have followed with master protocols defined by inclusive eligibility criteria and evaluations of multiple therapies and/or histologies. Consequently, characterization of subpopulation heterogeneity has become central to the formulation and selection of a study design. However, this transition to master protocols has led to challenges in identifying the optimal trial design and proper calibration of hyperparameters. We often evaluate a range of null and alternative scenarios; however, there has been little guidance on how to synthesize the potentially disparate recommendations for what may be optimal. This may lead to the selection of suboptimal designs and statistical methods that do not fully accommodate the subpopulation heterogeneity. This article proposes novel optimization criteria for calibrating and evaluating candidate statistical designs of master protocols in the presence of the potential for treatment effect heterogeneity among enrolled patient subpopulations. The framework is applied to demonstrate the statistical properties of conventional study designs when treatments offer heterogeneous benefit as well as identify optimal designs devised to monitor the potential for heterogeneity among patients with differing clinical indications using Bayesian modeling.

The changing perspective of clinical trial designs

Maintaining health and well-being of the population is a universal priority. Governments around the globe are therefore seeking greater efficiency and better outcomes from researches being held. Although large randomized trials or systematic review of several large trials provides the highest level of evidence, the intricate cost, time, and difficulties of conventional trials have led to questions about their sustainability commanding search for alternative approaches. Demands for improved competences in medical research have led to mounting interest in newer clinical trial designs. This article provides an insight into newer clinical trial designs, including cluster trials, adaptive designs, the master protocols along with their strengths, weaknesses, and which trials design should be opted for in different clinical scenarios.

Comparing the Efficacy of Cancer Therapies between Subgroups in Basket Trials

The need to test anticancer drugs in multiple indications has been addressed by basket trials, which are Phase I or II clinical trials involving multiple tumor subtypes and a single master protocol. Basket trials typically involve few patients per type, making it challenging to rigorously compare responses across types. We describe the use of permutation testing to test for differences among subgroups using empirical null distributions and the Benjamini-Hochberg procedure to control for false discovery. We apply the approach retrospectively to tumor-volume changes and progression-free survival in published basket trials for neratinib, larotrectinib, pembrolizumab, and imatinib and uncover examples of therapeutic benefit missed by conventional binomial testing. For example, we identify an overlooked opportunity for use of neratinib in lung cancers carrying ERBB2 Exon 20 mutations. Permutation testing can be used to design basket trials but is more conservatively introduced alongside established approaches to enrollment such as Simon’s two-stage design.

Basket clinical trials simultaneously test a single drug in multiple tumor subtypes, but statistical challenges limit the comparison of responses across subtypes. We describe a rigorous approach to permutation testing using empirical null distributions that can identify previously overlooked opportunities for use of targeted therapy in genetically defined cancer subtypes.

Innovative highlights of clinical drug trial design

Clinical trials serve as the gold standard to evaluate the efficacy and safety of tested drugs prior to marketing authorization. Nevertheless, there have been a few challenging issues well noted in traditional clinical trials such as tedious processing duration and escalating high costs among others. To improve the efficiency of clinical studies, a spectrum of expedited clinical trial modes has been designed, and selectively implemented in contemporary drug developing landscape. Herein this article presents an update on the innovated human trial designs that are corroborated through coming up with approval of notable therapeutic compounds for clinical utilization including delivery of several blockbuster products. It is intended to inspire clinical investigators and pharmaceutical development not only timely communicating with the regulatory agencies, but also insightful translating from cutting-edge scientific discoveries.

Collaborative, Multidisciplinary Evaluation of Cancer Variants Through Virtual Molecular Tumor Boards Informs Local Clinical Practices

PURPOSE

The cancer research community is constantly evolving to better understand tumor biology, disease etiology, risk stratification, and pathways to novel treatments. Yet the clinical cancer genomics field has been hindered by redundant efforts to meaningfully collect and interpret disparate data types from multiple high-throughput modalities and integrate into clinical care processes. Bespoke data models, knowledgebases, and one-off customized resources for data analysis often lack adequate governance and quality control needed for these resources to be clinical grade. Many informatics efforts focused on genomic interpretation resources for neoplasms are underway to support data collection, deposition, curation, harmonization, integration, and analytics to support case review and treatment planning.

METHODS

In this review, we evaluate and summarize the landscape of available tools, resources, and evidence used in the evaluation of somatic and germline tumor variants within the context of molecular tumor boards.

RESULTS

Molecular tumor boards (MTBs) are collaborative efforts of multidisciplinary cancer experts equipped with genomic interpretation resources to aid in the delivery of accurate and timely clinical interpretations of complex genomic results for each patient, within an institution or hospital network. Virtual MTBs (VMTBs) provide an online forum for collaborative governance, provenance, and information sharing between experts outside a given hospital network with the potential to enhance MTB discussions. Knowledge sharing in VMTBs and communication with guideline-developing organizations can lead to progress evidenced by data harmonization across resources, crowd-sourced and expert-curated genomic assertions, and a more informed and explainable usage of artificial intelligence.

CONCLUSION

Advances in cancer genomics interpretation aid in better patient and disease classification, more streamlined identification of relevant literature, and a more thorough review of available treatments and predicted patient outcomes.

Infectious Complications of Biological and Small Molecule Targeted Immunomodulatory Therapies

The past 2 decades have seen a revolution in our approach to therapeutic immunosuppression. We have moved from relying on broadly active traditional medications, such as prednisolone or methotrexate, toward more specific agents that often target a single receptor, cytokine, or cell type, using monoclonal antibodies, fusion proteins, or targeted small molecules. This change has transformed the treatment of many conditions, including rheumatoid arthritis, cancers, asthma, and inflammatory bowel disease, but along with the benefits have come risks. Contrary to the hope that these more specific agents would have minimal and predictable infectious sequelae, infectious complications have emerged as a major stumbling block for many of these agents. Furthermore, the growing number and complexity of available biologic agents makes it difficult for clinicians to maintain current knowledge, and most review articles focus on a particular target disease or class of agent. In this article, we review the current state of knowledge about infectious complications of biologic and small molecule immunomodulatory agents, aiming to create a single resource relevant to a broad range of clinicians and researchers. For each of 19 classes of agent, we discuss the mechanism of action, the risk and types of infectious complications, and recommendations for prevention of infection.

Histology-agnostic drug development - considering issues beyond the tissue

With advances in tumour biology and immunology that continue to refine our understanding of cancer, therapies are now being developed to treat cancers on the basis of specific molecular alterations and markers of immune phenotypes that transcend specific tumour histologies. With the landmark approvals of pembrolizumab for the treatment of patients whose tumours have high microsatellite instability and larotrectinib and entrectinib for those harbouring NTRK fusions, a regulatory pathway has been created to facilitate the approval of histology-agnostic indications. Negative results presented in the past few years, however, highlight the intrinsic complexities faced by drug developers pursuing histology-agnostic therapeutic agents. When patient selection and statistical analysis involve multiple potentially heterogeneous histologies, guidance is needed to navigate the challenges posed by trial design. Additionally, as new therapeutic agents are tested and post-approval data become available, the regulatory framework for acting on these data requires further optimization. In this Review, we summarize the development and testing of approved histology-agnostic therapeutic agents and present data on other agents currently under development. Finally, we discuss the challenges intrinsic to histology-agnostic drug development in oncology, including biological, regulatory, design and statistical considerations.

Master protocols: New directions in drug discovery

A master protocol is a unifying study construct that includes multiple subgroups and substudies, with patients having same or different diseases and that employ one or multiple drugs to treat it. Initially designed for oncology, master protocol trials are intended to simultaneously evaluate more than one investigational drug and/or more than one cancer type within the same overall trial structure. The ability to use a single infrastructure, trial design, and protocol to simultaneously evaluate multiple drugs and/or disease populations in multiple substudies, speeds up drug development and makes it more efficient. Thus, it is important for the clinical trial professionals to understand both the basic principles of master protocol trials and the way innovative trial designs are starting to change the landscape of clinical research.

Imatinib Treatment for Locally Advanced or Metastatic Dermatofibrosarcoma Protuberans: A Systematic Review

Importance

Dermatofibrosarcoma protuberans (DFSP) has the potential for local destruction and recurrence, although it carries a low risk of metastasis. Complete surgical resection with negative margins is considered the gold standard for treatment; however, there are cases that are unresectable owing to tumor extension or size or owing to risk of cosmetic and/or functional impairment. Imatinib treatment has been used for locally advanced or metastatic DFSP.

Objective

To evaluate the usefulness of imatinib for treating DFSP.

Evidence Review

We conducted a systematic review on the PubMed and Embase databases for articles published from September 2002 through October 2017 using the key words "dermatofibrosarcoma" or "dermatofibrosarcoma protuberans" AND "therapy" AND "imatinib." References within retrieved articles were also reviewed to identify additional studies. Studies of adults with histologically proven DFSP treated with imatinib as monotherapy or as an adjuvant or neoadjuvant therapy to surgery were included. Extracted data were analyzed using descriptive statistics. PRISMA guidelines were followed. All analysis took place October through December 2017.

Findings

Nine studies met inclusion criteria; 152 patients were included. The calculated mean patient age was 49.3 years (range, 20-73 years). Calculated mean tumor diameter was 9.9 cm (range, 1.2-49.0 cm). When COL1A1-PDGFβ protein translocation (collagen, type 1, alpha 1-platelet-derived growth factor β) was reported, it was present in 90.9% of patients (111 of 122). Complete response was seen in 5.2% of patients (8 of 152), partial response in 55.2% (84 of 152), stable disease in 27.6% (42 of 152), and progression in 9.2% (14 of 152). Four of the 152 patients (2.6%) were excluded from the analysis owing to unknown or unevaluable response. There were no differences in response rate using 400-mg or 800-mg daily doses (67.5% or 27 of 40 patients for 400-mg dose vs 67.1% or 49 of 73 patients for 800-mg dose complete or partial response; P > .99). Adverse events were present in at least 73.5% of cases (78 of 106); severe adverse events were present in 15.1% of cases (20 of 132).

Conclusions and Relevance

Imatinib is a useful directed therapy in patients with DFSP who are not surgical candidates owing to disease extension or significant cosmetic or functional impairment. There seems to be no difference between 400- or 800-mg daily doses.

[Biology and signaling pathways involved in the oncogenesis of desmoid tumors]

Desmoid tumors (TDs) are derived from mesenchymal stem cells and their pathogenesis is strongly linked to the Wingless/Wnt cascade where the deregulation of β-catenin plays a major role. A mutation of the CTNNB1 encoding β-catenin is found in the majority of sporadic TD cases and constitutional mutations of APC have been described in heritable forms in patients with familial adenomatous polyposis (FAP). Estrogens could also play a role in pathogenesis and this is the basis for the use of hormone therapy. Other signaling pathways have been involved in the development of TDs such as Notch, Hedgehog, JAK/STAT, PI3 Kinase/AKT and mTOR. Metalloproteases are expressed in TDs and play a role in invasiveness. TGF-ß, as a growth factor, stimulates the transcriptional activity of β-catenin. Future studies will need to focus on better describing and understanding the immune environment of TDs. One of the major difficulties for the experimental study of TDs is the virtual absence of a preclinical model, either in vitro or in vivo. This is partly why the interactions between the different signaling pathways presented here and their consequences for the development of TDs are still poorly understood.

Finding relationships among biological entities

Confusion over the concepts of “relationships” and “similarities” lies at the heart of many battles over the direction and intent of research projects. Here is a short story that demonstrates the difference between the two concepts: You look up at the clouds, and you begin to see the shape of a lion. The cloud has a tail, like a lion’s tale, and a fluffy head, like a lion’s mane. With a little imagination the mouth of the lion seems to roar down from the sky. You have succeeded in finding similarities between the cloud and a lion. If you look at a cloud and you imagine a tea kettle producing a head of steam and you recognize that the physical forces that create a cloud and the physical forces that produced steam from a heated kettle are the same, then you have found a relationship. Most popular classification algorithms operate by grouping together data objects that have similar properties or values. In so doing, they may miss finding the true relationships among objects. Traditionally, relationships among data objects are discovered by an intellectual process. In this chapter, we will discuss the scientific gains that come when we classify biological entities by relationships, not by their similarities.

Basket Designs: Statistical Considerations for Oncology Trials

Progress in the areas of genomics, disease pathways, and drug discovery has advanced into clinical and translational cancer research. The latest innovations in clinical trials have followed with master protocols, which are defined by inclusive eligibility criteria and devised to interrogate multiple therapies for a given tumor histology and/or multiple histologies for a given therapy under one protocol. The use of master protocols for oncology has become more common with the desire to improve the efficiency of clinical research and accelerate overall drug development. Basket trials have been devised to ascertain the extent to which a treatment strategy offers benefit to various patient subpopulations defined by a common molecular target. Conventionally conducted within the phase II setting, basket designs have become popular as drug developers seek to effectively evaluate and identify preliminary efficacy signals among clinical indications identified as promising in preclinical study. This article reviews basket trial designs in oncology settings and discusses several issues that arise with their design and analysis.

Systematic review of basket trials, umbrella trials, and platform trials: a landscape analysis of master protocols

BACKGROUND

Master protocols, classified as basket trials, umbrella trials, and platform trials, are novel designs that investigate multiple hypotheses through concurrent sub-studies (e.g., multiple treatments or populations or that allow adding/removing arms during the trial), offering enhanced efficiency and a more ethical approach to trial evaluation. Despite the many advantages of these designs, they are infrequently used.

METHODS

We conducted a landscape analysis of master protocols using a systematic literature search to determine what trials have been conducted and proposed for an overall goal of improving the literacy in this emerging concept. On July 8, 2019, English-language studies were identified from MEDLINE, EMBASE, and CENTRAL databases and hand searches of published reviews and registries.

RESULTS

We identified 83 master protocols (49 basket, 18 umbrella, and 16 platform trials). The number of master protocols has increased rapidly over the last five years. Most have been conducted in the US (n = 44/83) and investigated experimental drugs (n = 82/83) in the field of oncology (n = 76/83). The majority of basket trials were exploratory (i.e., phase I/II; n = 47/49) and not randomized (n = 44/49), and more than half (n = 28/48) investigated only a single intervention. The median sample size of basket trials was 205 participants (interquartile range, Q3-Q1 [IQR]: 500-90 = 410), and the median study duration was 22.3 (IQR: 74.1-42.9 = 31.1) months. Similar to basket trials, most umbrella trials were exploratory (n = 16/18), but the use of randomization was more common (n = 8/18). The median sample size of umbrella trials was 346 participants (IQR: 565-252 = 313), and the median study duration was 60.9 (IQR: 81.3-46.9 = 34.4) months. The median number of interventions investigated in umbrella trials was 5 (IQR: 6-4 = 2). The majority of platform trials were randomized (n = 15/16), and phase III investigation (n = 7/15; one did not report information on phase) was more common in platform trials with four of them using seamless II/III design. The median sample size was 892 (IQR: 1835-255 = 1580), and the median study duration was 58.9 (IQR: 101.3-36.9 = 64.4) months.

CONCLUSIONS

We anticipate that the number of master protocols will continue to increase at a rapid pace over the upcoming decades. More efforts to improve awareness and training are needed to apply these innovative trial design methods to fields outside of oncology.

Expression Levels of Therapeutic Targets as Indicators of Sensitivity to Targeted Therapeutics

Cancer precision medicine aims to predict the drug likely to yield the best response for a patient. Genomic sequencing of tumors is currently being used to better inform treatment options; however, this approach has had a limited clinical impact due to the paucity of actionable mutations. An alternative to mutation status is the use of gene expression signatures to predict response. Using data from two large-scale studies, The Genomics of Drug Sensitivity of Cancer (GDSC) and The Cancer Therapeutics Response Portal (CTRP), we investigated the relationship between the sensitivity of hundreds of cell lines to hundreds of drugs, and the relative expression levels of the targets these drugs are directed against. For approximately one third of the drugs considered (73/222 in GDSC and 131/360 in CTRP), sensitivity was significantly correlated with the expression of at least one of the known targets. Surprisingly, for 8% of the annotated targets, there was a significant anticorrelation between target expression and sensitivity. For several cases, this corresponded to drugs targeting multiple genes in the same family, with the expression of one target significantly correlated with sensitivity and another significantly anticorrelated suggesting a possible role in resistance. Furthermore, we identified nontarget genes that are significantly correlated or anticorrelated with drug sensitivity, and find literature linking several to sensitization and resistance. Our analyses provide novel and important insights into both potential mechanisms of resistance and relative efficacy of drugs against the same target.

Sample size computation in phase II designs combining the A'Hern design and the Sargent and Goldberg design

This work focuses on the modification of two classical phase II trials designs, the A'Hern design, a single-arm single-stage design, and the Sargent and Goldberg design introduced in the context of flexible screening designs. In the first part of the paper, we have proposed a drift-adjusted A'Hern design, a hybrid design combining the A'Hern design and the Sargent and Goldberg design. Indeed, classical single-arm phase II designs such as the A'Hern design are still widely used in oncology. Conducting randomized comparative phase II trials may be challenging in many settings due to the increased sample size and this despite larger type 1 errors. Randomized non-comparative phase II designs first introduced by Herson and Carter include a simultaneous randomized standard-treatment reference arm to detect any drift in the reference arm assumption, but the trial is analyzed against historical controls as if it were a single-arm study. However, not incorporating at all an internal control arm in the trial design has been criticized in the literature. Our new design takes into account the observed response rate in a non-comparative reference arm to reduce the trial's risk of a false-positive conclusion. In the second part, we have proposed an alternative strategy to determining the sample size of the screened selection design. The latter, introduced in recent years by Yap et al. and Wu et al., extended the Sargent and Goldberg design to include a comparison to a historical control. However, their sample size computations may have potential weaknesses, which motivated us to revisit the existing approaches. A detailed simulation study has been carried out to evaluate the operating characteristics of the drift-adjusted A'Hern design and the different sample size strategies of the screened selection designs.