New clinical trial designs in the era of precision medicine

Risk and Benefit for Basket Trials in Oncology: A Systematic Review and Meta-Analysis

BACKGROUND

Oncology research is increasingly adopting new clinical trial models that implement the concept of precision medicine. One of these is the basket clinical trial design. Basket clinical trials allow new treatments to be evaluated across multiple tumor types. Patients recruited to basket clinical trials share certain molecular characteristics of their cancer that are predictive of clinical benefit from the experimental treatment.

OBJECTIVE

Our aim was to describe the risks and benefits of basket clinical trials in oncology.

METHODS

Our study was prospectively registered in PROSPERO (CRD42023406401). We systematically searched PubMed, Embase, and ClinicalTrials.gov for reports of basket clinical trials in oncology published between 1 January, 2001, and 14 June, 2023. We measured the risk by treatment-related adverse events (grades 3, 4, and 5), and the benefit by objective response rate. We also extracted and analyzed data on progression-free survival and overall survival. When possible, data were meta-analyzed.

RESULTS

We included 126 arms of 75 basket clinical trials accounting for 7659 patients. The pooled objective response rate was 18.0% (95% confidence interval [CI] 14.8-21.1). The rate of treatment-related death was 0.7% (95% CI 0.4-1.0), while 30.4% (95% CI 24.2-36.7) of patients experienced grade 3/4 drug-related toxicity. The median progression-free survival was 3.1 months (95% CI 2.6-3.9), and the median overall survival was 8.9 months (95% CI 6.7-10.2).

CONCLUSIONS

Our results provide an empirical basis for communicating about the risks and benefits of basket clinical trials and for refining new models of clinical trials applied in precision medicine.

Personalized Treatment Strategies via Integration of Gene Expression Biomarkers in Molecular Profiling of Laryngeal Cancer

Laryngeal cancer poses a substantial challenge in head and neck oncology, and there is a growing focus on customized medicine techniques. The present state of gene expression indicators in laryngeal cancer and their potential to inform tailored therapy choices are thoroughly examined in this review. We examine significant molecular changes, such as TP53, CDKN2A, PIK3CA, and NOTCH1 mutations, which have been identified as important participants in the development of laryngeal cancer. The study investigates the predictive and prognostic significance of these genetic markers in addition to the function of epigenetic changes such as the methylation of the MGMT promoter. We also go over the importance of cancer stem cell-related gene expression patterns, specifically CD44 and ALDH1A1 expression, in therapy resistance and disease progression. The review focuses on indicators, including PD-L1, CTLA-4, and tumor mutational burden (TMB) in predicting immunotherapy responses, highlighting recent developments in our understanding of the intricate interactions between tumor genetics and the immune milieu. We also investigate the potential for improving prognosis accuracy and treatment selection by the integration of multi-gene expression panels with clinicopathological variables. The necessity for uniform testing and interpretation techniques is one of the difficulties, in implementing these molecular insights into clinical practice, that are discussed. This review seeks to provide a comprehensive framework for promoting personalized cancer therapy by combining the most recent data on gene expression profiling in laryngeal cancer. Molecularly guided treatment options may enhance patient outcomes.

Precision psychiatry: predicting predictability

Precision psychiatry is an emerging field that aims to provide individualized approaches to mental health care. An important strategy to achieve this precision is to reduce uncertainty about prognosis and treatment response. Multivariate analysis and machine learning are used to create outcome prediction models based on clinical data such as demographics, symptom assessments, genetic information, and brain imaging. While much emphasis has been placed on technical innovation, the complex and varied nature of mental health presents significant challenges to the successful implementation of these models. From this perspective, I review ten challenges in the field of precision psychiatry, including the need for studies on real-world populations and realistic clinical outcome definitions, and consideration of treatment-related factors such as placebo effects and non-adherence to prescriptions. Fairness, prospective validation in comparison to current practice and implementation studies of prediction models are other key issues that are currently understudied. A shift is proposed from retrospective studies based on linear and static concepts of disease towards prospective research that considers the importance of contextual factors and the dynamic and complex nature of mental health.

Can precision medicine be integrated into routine therapeutic decisions at the bedside of patients?

Therapeutic strategies are shifting from a "one-size-fits-all" population-based approach to a stratified approach targeting groups with similar characteristics, or even individuals, tailoring treatments to the unique characteristics of each patient. Since such strategies rely on increasingly complex knowledge and healthcare technologies, along with an understanding of the tools of precision medicine, the appropriate dissemination and use of these strategies involves a number of challenges for the medical community. Having evaluation methodologies that have been jointly designed with the institutional, industrial, academic stakeholders, and also patients, like streamlining the processes and externally validating performances, could enhance the relevance of the "evaluation" aspect of precision medicine. Creating a network of expert precision-medicine centers and ensuring that precision-medicine procedures are reimbursed by social security would guarantee fair and sustainable access. Finally, training healthcare professionals, creating interfaces between precision-medicine expert centers and primary care professionals as well as patients, and integrating individual patient data into medical records are all key drivers that will enable information from precision-medicine to be made available and guarantee the proper use of these approaches.

A Strategy Utilizing Protein-Protein Interaction Hubs for the Treatment of Cancer Diseases

We describe a strategy for the development of a rational approach of neoplastic disease therapy based on the demonstration that scale-free networks are susceptible to specific attacks directed against its connective hubs. This strategy involves the (i) selection of up-regulated hubs of connectivity in the tumors interactome, (ii) drug repurposing of these hubs, (iii) RNA silencing of non-druggable hubs, (iv) in vitro hub validation, (v) tumor-on-a-chip, (vi) in vivo validation, and (vii) clinical trial. Hubs are protein targets that are assessed as targets for rational therapy of cancer in the context of personalized oncology. We confirmed the existence of a negative correlation between malignant cell aggressivity and the target number needed for specific drugs or RNA interference (RNAi) to maximize the benefit to the patient's overall survival. Interestingly, we found that some additional proteins not generally targeted by drug treatments might justify the addition of inhibitors designed against them in order to improve therapeutic outcomes. However, many proteins are not druggable, or the available pharmacopeia for these targets is limited, which justifies a therapy based on encapsulated RNAi.

Candidate composite biomarker to inform drug treatments for diabetic kidney disease

Introduction

Current guidelines recommend renin angiotensin system inhibitors (RASi) as key components of treatment of diabetic kidney disease (DKD). Additional options include sodium-glucose cotransporter-2 inhibitors (SGLT2i), glucagon-like peptide 1 receptor agonists (GLP1a), and mineralocorticoid receptor antagonists (MCRa). The identification of the optimum drug combination for an individual is difficult because of the inter-, and longitudinal intra-individual heterogeneity of response to therapy.

Results

Using data from a large observational study (PROVALID), we identified a set of parameters that can be combined into a meaningful composite biomarker that appears to be able to identify which of the various treatment options is clinically beneficial for an individual. It uses machine-earning techniques to estimate under what conditions a treatment of RASi plus an additional treatment is different from the treatment with RASi alone. The measure of difference is the annual percent change (ΔeGFR) in the estimated glomerular filtration rate (ΔeGFR). The 1eGFR is estimated for both the RASi-alone treatment and the add-on treatment.

Discussion

Higher estimated increase of eGFR for add-on patients compared with RASi-alone patients indicates that prognosis may be improved with the add-on treatment. The personalized biomarker value thus identifies which patients may benefit from the additional treatment.

Precision cancer medicine: Concepts, current practice, and future developments

Precision cancer medicine is a multidisciplinary team effort that requires involvement and commitment of many stakeholders including the society at large. Building on the success of significant advances in precision therapy for oncological patients over the last two decades, future developments will be significantly shaped by improvements in scalable molecular diagnostics in which increasingly complex multilayered datasets require transformation into clinically useful information guiding patient management at fast turnaround times. Adaptive profiling strategies involving tissue- and liquid-based testing that account for the immense plasticity of cancer during the patient's journey and also include early detection approaches are already finding their way into clinical routine and will become paramount. A second major driver is the development of smart clinical trials and trial concepts which, complemented by real-world evidence, rapidly broaden the spectrum of therapeutic options. Tight coordination with regulatory agencies and health technology assessment bodies is crucial in this context. Multicentric networks operating nationally and internationally are key in implementing precision oncology in clinical practice and support developing and improving the ecosystem and framework needed to turn invocation into benefits for patients. The review provides an overview of the diagnostic tools, innovative clinical studies, and collaborative efforts needed to realize precision cancer medicine.

Engaging European society at the forefront of cancer research and care: How discussions at the 5th Gago Conference on European Science policy led to the Heidelberg Manifesto

European cancer research stakeholders met in October 2022 in Heidelberg, Germany, at the 5th Gago conference on European Cancer Policy, to discuss the current cancer research and cancer care policy landscape in Europe. Meeting participants highlighted gaps in the existing European programmes focusing on cancer research, including Europe's Beating Cancer Plan (EBCP), the Mission on Cancer (MoC), Understanding Cancer (UNCAN.eu), and the joint action CRANE, and put forward the next priorities, in the form of the Heidelberg Manifesto for cancer research. This meeting report presents all discussions that shed light on how infrastructures can be effectively shaped for translational, prevention, clinical and outcomes cancer research, with a focus on implementation and sustainability and while engaging patients and the public. In addition, we summarize recommendations on how to introduce frameworks for the digitalization of European cancer research. Finally, we discuss what structures, commitment, and resources are needed to establish a collaborative cancer research environment in Europe to achieve the scale required for innovation.

Comprehensive Genomic Profiling and Therapeutic Implications for Patients with Advanced Cancers: The Experience of an Academic Hospital

Next-generation sequencing (NGS) can be used to detect tumor-specific genomic alterations. This retrospective single-center study aims to assess the application of an extensive NGS panel to identify actionable alterations and initiate matched targeted treatment for patients with advanced cancer. We analyzed genomic alterations in solid tumor biopsies from 464 patients with advanced cancer with the Foundation Medicine assay (FoundationOne®CDx). Therapeutic implications were determined using the Memorial Sloan Kettering Precision Oncology Knowledge Base (OncoKB) classification. The FoundationOne®CDx was successfully applied in 464/521 patients (89%). The most common altered genes were TP53 (61%), KRAS (20%), CDKN2A (20%), TERT (16%), and APC (16%). Among the 419 patients with successfully analyzed tumor mutational burden (TMB), 43 patients presented with a high TMB (≥10 mutations/megabase). Out of the 126 patients with an actionable target, 40 patients received matched treatment (32%) of which 17 were within a clinical trial. This study shows that the application of NGS is feasible in an academic center and increases the detection of actionable alterations and identification of patients eligible for targeted treatment or immunotherapy regardless of tumor histology. Strategies such as early referral for NGS, inclusion in clinical (basket) trials, and the development of new targeted drugs are necessary to improve the matched treatment rate.

Prognostication in inflammatory bowel disease

Personalized care in inflammatory bowel diseases (IBD) hinges on parsing the heterogeneity of IBD patients through prognostication of their disease course and therapeutic response to allow for tailor-made treatment and monitoring strategies to optimize care. Herein we review the currently available predictors of outcomes in IBD and those on the both near and far horizons. We additionally discuss the importance of worldwide collaborative efforts and tools to support clinical use of these prognostication tools.

MatchMiner: an open-source platform for cancer precision medicine

Widespread, comprehensive sequencing of patient tumors has facilitated the usage of precision medicine (PM) drugs to target specific genomic alterations. Therapeutic clinical trials are necessary to test new PM drugs to advance precision medicine, however, the abundance of patient sequencing data coupled with complex clinical trial eligibility has made it challenging to match patients to PM trials. To facilitate enrollment onto PM trials, we developed MatchMiner, an open-source platform to computationally match genomically profiled cancer patients to PM trials. Here, we describe MatchMiner’s capabilities, outline its deployment at Dana-Farber Cancer Institute (DFCI), and characterize its impact on PM trial enrollment. MatchMiner’s primary goals are to facilitate PM trial options for all patients and accelerate trial enrollment onto PM trials. MatchMiner can help clinicians find trial options for an individual patient or provide trial teams with candidate patients matching their trial’s eligibility criteria. From March 2016 through March 2021, we curated 354 PM trials containing a broad range of genomic and clinical eligibility criteria and MatchMiner facilitated 166 trial consents (MatchMiner consents, MMC) for 159 patients. To quantify MatchMiner’s impact on trial consent, we measured time from genomic sequencing report date to trial consent date for the 166 MMC compared to trial consents not facilitated by MatchMiner (non-MMC). We found MMC consented to trials 55 days (22%) earlier than non-MMC. MatchMiner has enabled our clinicians to match patients to PM trials and accelerated the trial enrollment process.

Molecular oncology: what is needed to speed access to innovative therapies in clinical research?

PURPOSE OF REVIEW

A better understanding of the biology of cancer cells has led in the past 20 years to more and more molecular and immunological driven treatment strategies impacting both clinical trials and day-to-day practice. The aim of this review is to describe new approaches to conduct clinical trials in this area to speed up drug development and increase access to innovation for cancer patients.

RECENT FINDINGS

The design of an early phase trial has an impact on its clinical benefit. Trials deriving from a specific biomarker or histologic characteristic (also known as enrichment design) are more likely to demonstrate benefit than trials based on a more conventional design. However, the increase of low incidence cancer molecular subtypes poses a major hurdle in the clinical management and drug development research for cancer patients.

SUMMARY

With the identification of news targets and the subsequent introduction of precision medicine, new strategies and tools are needed to provide access to biomarker identification and target-oriented clinical trials to all cancer patients. We propose to set up a new patient-centered model to conduct clinical trials allowing simply to 'bring the trial to the patient'.

Management of Adverse Events in Early Clinical Trials by Advanced Practice Providers in the Outpatient Setting: The University of Texas MD Anderson Cancer Center Experience

Background

Advanced practice providers (APPs) play important roles in enrolling, educating, and caring for patients in clinical trials. However, much remains unknown about the role of APPs in managing adverse events (AEs) in early (phase I to II) clinical trials. In this study, we assessed the outpatient management of grade 3 to 4 AEs by APPs in early trials and characterized the workflow of our APP Phase I to II Fast Track (FT) Clinic.

Patients and Methods

We retrospectively reviewed records of patients with advanced or metastatic solid tumors enrolled in phase I to II clinical trials who were seen by APPs from September 2017 to August 2018 in the APP phase I to II FT clinic in the Department of Investigational Cancer Therapeutics.

Results

A total of 808 patients enrolled in 159 clinical trials were seen in 2,697 visits (median 3 visits per patient; range 1-28) by 10 APPs. Treatment was interrupted in 6.9% of visits, and grade 3 to 4 AEs were seen in 5.4% of visits; however, patients from 1.4% of visits were sent to the emergency center (EC) and/or admitted. Patients referred to the EC and/or admitted were more likely to have baseline hypoalbuminemia, high lactate dehydrogenase, and poor Eastern Cooperative Oncology Group performance status (i.e., ECOG > 1; p < .001). There were no associations between EC referral and gender, APP years of experience, or type of treatment.

Conclusions

The APP Phase I to II FT Clinic has an important role in the management of AEs by APPs in early clinical trials in the outpatient setting, potentially avoiding EC visits and admissions.

The Effect of Biomarker Use on the Speed and Duration of Clinical Trials for Cancer Drugs

Background

The purpose of this study was to explore the effects biomarkers have on the duration and speed of clinical trials in oncology.

Materials and Methods

Clinical trial data was pooled from www.clinicaltrials.gov within the 4 cancer indications of non-small cell lung cancer, breast cancer, melanoma, and colorectal cancer. Heatmaps of clinical timelines were used to display differences in the frequency and timing of clinical trials across trials that used or did not use biomarkers, for all 4 indications.

Results

Screening of 8630 clinical trials across the 4 indications yielded 671 unique drugs corresponding to 1224 eligible trials used in our analysis. The constructed heatmaps visually represented that biomarkers did not have an effect on the time gap between trial phases for non-small cell lung cancer and melanoma but did for colorectal and breast cancer trials, reducing the speed of trial timelines. It was also observed that biomarker trials were more often concurrent over shorter periods of time and began later in the timeline for non-small cell lung and colorectal cancers.

Conclusion

The novel visualization method revealed longer gaps between trial phases, later clinical trial start times, and shorter periods of concurrently run trials for drugs that used biomarkers. The study highlights that biomarker-driven trials might impact drug approval timelines and need to be considered carefully in clinical development plan.

New Drug Development and Clinical Trial Design by Applying Genomic Information Management

Depending on the patients’ genotype, the same drug may have different efficacies or side effects. With the cost of genomic analysis decreasing and reliability of analysis methods improving, vast amount of genomic information has been made available. Several studies in pharmacology have been based on genomic information to select the optimal drug, determine the dose, predict efficacy, and prevent side effects. This paper reviews the tissue specificity and genomic information of cancer. If the tissue specificity of cancer is low, cancer is induced in various organs based on a single gene mutation. Basket trials can be performed for carcinomas with low tissue specificity, confirming the efficacy of one drug for a single gene mutation in various carcinomas. Conversely, if the tissue specificity of cancer is high, cancer is induced in only one organ based on a single gene mutation. An umbrella trial can be performed for carcinomas with a high tissue specificity. Some drugs are effective for patients with a specific genotype. A companion diagnostic strategy that prescribes a specific drug for patients selected with a specific genotype is also reviewed. Genomic information is used in pharmacometrics to identify the relationship among pharmacokinetics, pharmacodynamics, and biomarkers of disease treatment effects. Utilizing genomic information, sophisticated clinical trials can be designed that will be better suited to the patients of specific genotypes. Genomic information also provides prospects for innovative drug development. Through proper genomic information management, factors relating to drug response and effects can be determined by selecting the appropriate data for analysis and by understanding the structure of the data. Selecting pre-processing and appropriate machine-learning libraries for use as machine-learning input features is also necessary. Professional curation of the output result is also required. Personalized medicine can be realized using a genome-based customized clinical trial design.

Outcomes and endpoints in clinical trials supporting the marketing authorisation of treatments in paediatric acute lymphoblastic leukaemia

The improvement in acute lymphoblastic leukaemia (ALL) treatment has led research efforts to focus on the unmet medical needs of an increasingly smaller patient cohort with resistant leukaemia and to develop more-targeted agents. Survival and response rates remain the most-prevalent endpoints in paediatric ALL research, but other intermediate clinical endpoints and molecular biomarkers for efficacy and mid- and long-term safety endpoints are also being investigated. The success of current ALL treatment appears to be driving new paradigms to optimise clinical drug development, while at the same time, regulatory tools in place are supporting meaningful drug development in the area.

Operational complexity versus design efficiency: challenges of implementing a phase IIa multiple parallel cohort targeted treatment platform trial in advanced breast cancer

BACKGROUND

Platform trial designs are used increasingly in cancer clinical research and are considered an efficient model for evaluating multiple compounds within a single disease or disease subtype. However, these trial designs can be challenging to operationalise. The use of platform trials in oncology clinical research has increased considerably in recent years as advances in molecular biology enable molecularly defined stratification of patient populations and targeted therapy evaluation. Whereas multiple separate trials may be deemed infeasible, platform designs allow efficient, parallel evaluation of multiple targeted therapies in relatively small biologically defined patient sub-populations with the promise of increased molecular screening efficiency and reduced time for drug evaluation. Whilst the theoretical efficiencies are widely reported, the operational challenges associated with these designs (complexity, cost, regulatory, resource) are not always well understood. MAIN: In this commentary, we describe our practical experience of the implementation and delivery of the UK plasmaMATCH trial, a platform trial in advanced breast cancer, comprising an integrated screening component and multiple parallel downstream mutation-directed therapeutic cohorts. plasmaMATCH reported its primary results within 3 years of opening to recruitment. We reflect on the operational challenges encountered and share lessons learnt to inform the successful conduct of future trials. Key to the success of the plasmaMATCH trial was well co-ordinated stakeholder engagement by an experienced clinical trials unit with expert methodology and trial management expertise, a federated model of clinical leadership, a well-written protocol integrating screening and treatment components and including justification for the chosen structure and intentions for future adaptions, and an integrated funding model with streamlined contractual arrangements across multiple partners. Findings based on our practical experience include the importance of early engagement with the regulators and consideration of a flexible resource infrastructure to allow adequate resource allocation to support concurrent trial activities as adaptions are implemented in parallel to the continued management of patient safety and data quality of the ongoing trial cohorts.

CONCLUSION

Platform trial designs allow the efficient reporting of multiple treatment cohorts. Operational challenges can be overcome through multidisciplinary engagement, streamlined contracting processes, rationalised protocol and database design and appropriate resourcing.

The Promise of Nanotechnology in Personalized Medicine

Both personalized medicine and nanomedicine are new to medical practice. Nanomedicine is an application of the advances of nanotechnology in medicine and is being integrated into diagnostic and therapeutic tools to manage an array of medical conditions. On the other hand, personalized medicine, which is also referred to as precision medicine, is a novel concept that aims to individualize/customize therapeutic management based on the personal attributes of the patient to overcome blanket treatment that is only efficient in a subset of patients, leaving others with either ineffective treatment or treatment that results in significant toxicity. Novel nanomedicines have been employed in the treatment of several diseases, which can be adapted to each patient-specific case according to their genetic profiles. In this review, we discuss both areas and the intersection between the two emerging scientific domains. The review focuses on the current situation in personalized medicine, the advantages that can be offered by nanomedicine to personalized medicine, and the application of nanoconstructs in the diagnosis of genetic variability that can identify the right drug for the right patient. Finally, we touch upon the challenges in both fields towards the translation of nano-personalized medicine.

Clinical and economic impact of molecular testing for BRAF fusion in pediatric low-grade Glioma

Background

Treatment personalization via tumor molecular testing holds promise for improving outcomes for patients with pediatric low-grade glioma (PLGG). We evaluate the health economic impact of employing tumor molecular testing to guide treatment for patients diagnosed with PLGG, particularly the avoidance of radiation therapy (RT) for patients with BRAF-fusion.

Methods

We performed a model-based cost-utility analysis comparing two strategies: molecular testing to determine BRAF fusion status at diagnosis against no molecular testing. We developed a microsimulation to model the lifetime health and cost outcomes (in quality-adjusted life years (QALYs) and 2018 CAD, respectively) for a simulated cohort of 100,000 patients newly diagnosed with PLGG after their initial surgery.

Results

The life expectancy after diagnosis for individuals who did not receive molecular testing was 39.01 (95% Confidence Intervals (CI): 32.94;44.38) years and 40.08 (95% CI: 33.19;45.76) years for those who received testing. Our findings indicate that patients who received molecular testing at diagnosis experienced a 0.38 (95% CI: 0.08;0.77) gain in QALYs and $1384 (95% CI: $-3486; $1204) reduction in costs over their lifetime. Cost and QALY benefits were driven primarily by the avoidance of long-term adverse events (stroke, secondary neoplasms) associated with unnecessary use of radiation.

Conclusions

We demonstrate the clinical benefit and cost-effectiveness of molecular testing in guiding the decision to provide RT in PLGG. While our results do not consider the impact of targeted therapies, this work is an example of the value of simulation modeling in assessing the long-term costs and benefits of precision oncology interventions for childhood cancer, which can aid decision-making about health system reimbursement.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-021-03069-1.

Patient and public understanding of the concept of 'personalised medicine' in relation to cancer treatment: a systematic review

Personalised medicine (PM) is becoming increasingly integrated into standard clinical practice for treating numerous diseases, including cancer. Implementing PM into healthcare systems will only be successful with the acceptance and input of both patients' and public opinion. This review, therefore, aimed to identify both patients' and public understanding, and perceived benefits and concerns of PM in cancer treatment. A literature search was conducted using MEDLINE, EMBASE, PsycINFO and CINAHL databases. The eligibility criteria specified that papers must explore the public or patients' understanding of PM or pharmacogenomic (PGx) testing in relation to cancer treatment. Patients have a greater understanding of, and trust in, PM compared with members of the public, but often misunderstand how genomic testing in PM works. Key areas that can be targeted to inform future health literacy interventions include genetic literacy for the public and understanding of how PM testing and treatment works for patients.

Of some innovations in clinical trial design in hematology and oncology

The design of clinical trials, formalized in the immediate post-war period, has undergone major changes due to therapeutic innovations, particularly the arrival of targeted therapies in onco-hematology. The traditional phase I-II-III regimen is regularly questioned and multiple adaptations are proposed. This article proposes to expose some of these modifications and the issues they lead to.

Reinforcing Collaboration and Harmonization to Unlock the Potentials of Advanced Therapy Medical Products: Future Efforts Are Awaited From Manufacturers and Decision-Makers

Some advanced therapy medicinal products (ATMPs) hold great promises for life-threatening diseases with high unmet needs. However, ATMPs are also associated with significant challenges in market access, which necessitates the joint efforts between all relevant stakeholders to navigate. In this review, we will elaborate on the importance of collaborations and harmonization across different stakeholders, to expedite the market access of promising ATMPs. Manufacturers of ATMPs should proactively establish collaborations with other stakeholders throughout the whole lifecycle of ATMPs, from early research to post-market activities. This covered engagements with (1) external developers (i.e., not-for-profit organizations and commercial players) to obtain complementary knowledge, technology, or infrastructures, (2) patient groups and healthcare providers to highlight their roles as active contributors, and (3) decision-makers, such as regulators, health technology assessment (HTA) agencies, and payers, to communicate the uncertainties in evidence package, where parallel consultation will be a powerful strategy. Harmonization between decision-makers is desired at (1) regulatory level, in terms of strengthening the international standardization of regulatory framework to minimize discrepancies in evidence requirements for market authorization, and (2) HTA level, in terms of enhancing alignments between regional and national HTA agencies to narrow inequity in patient access, and cross-border HTA cooperation to improve the quality and efficiency of HTA process. In conclusion, manufacturers and decision-makers shared the common goals to safeguard timely patient access to ATMPs. Collaboration and harmonization will be increasingly leveraged to enable the value delivery of ATMPs to all stakeholders.

Master Protocols for Precision Medicine in Oncology: Overcoming Methodology of Randomized Clinical Trials

Randomized clinical trials are considered the milestones of clinical research in oncology, and guided the development and approval of new compounds so far. In the last few years, however, molecular and genomic profiling led to a change of paradigm in therapeutic algorithms of many cancer types, with the spread of different biomarker-driven therapies (or targeted therapies). This scenario of "personalized medicine" revolutionized therapeutic strategies and the methodology of the supporting clinical research. New clinical trial designs are emerging to answer to the unmet clinical needs related to the development of these targeted therapies, overcoming the "classical" structure of randomized studies. Innovative trial designs able to evaluate more than one treatment in the same group of patients or many groups of patients with the same treatment (or both) are emerging as a possible future standard in clinical trial methodology. These are identified as "master protocols", and include umbrella, basket and platform trials. In this review, we described the main characteristics of these new trial designs, focusing on the opportunities and limitations of their use in the era of personalized medicine.

Perspectives on emerging technologies, personalised medicine, and clinical research for cancer control in Latin America and the Caribbean

Challenges of health systems in Latin America and the Caribbean include accessibility, inequity, segmentation, and poverty. These challenges are similar in different countries of the region and transcend national borders. The increasing digital transformation of health care holds promise of more precise interventions, improved health outcomes, increased efficiency, and ultimately reduced health-care costs. In Latin America and the Caribbean, the adoption of digital health tools is in early stages and the quality of cancer registries, electronic health records, and structured databases are problematic. Cancer research and innovation in the region are limited due to inadequate academic resources and translational research is almost fully dependent on public funding. Regulatory complexity and extended timelines jeopardise the potential improvement in participation in international studies. Emerging technologies, artificial intelligence, big data, and cancer research represent an opportunity to address the health-care challenges in Latin America and the Caribbean collectively, by optimising national capacities, sharing and comparing best practices, and transferring scientific and technical capabilities.

The Porto European Cancer Research Summit 2021

Key stakeholders from the cancer research continuum met in May 2021 at the European Cancer Research Summit in Porto to discuss priorities and specific action points required for the successful implementation of the European Cancer Mission and Europe's Beating Cancer Plan (EBCP). Speakers presented a unified view about the need to establish high-quality, networked infrastructures to decrease cancer incidence, increase the cure rate, improve patient's survival and quality of life, and deal with research and care inequalities across the European Union (EU). These infrastructures, featuring Comprehensive Cancer Centres (CCCs) as key components, will integrate care, prevention and research across the entire cancer continuum to support the development of personalized/precision cancer medicine in Europe. The three pillars of the recommended European infrastructures - namely translational research, clinical/prevention trials and outcomes research - were pondered at length. Speakers addressing the future needs of translational research focused on the prospects of multiomics assisted preclinical research, progress in Molecular and Digital Pathology, immunotherapy, liquid biopsy and science data. The clinical/prevention trial session presented the requirements for next-generation, multicentric trials entailing unified strategies for patient stratification, imaging, and biospecimen acquisition and storage. The third session highlighted the need for establishing outcomes research infrastructures to cover primary prevention, early detection, clinical effectiveness of innovations, health-related quality-of-life assessment, survivorship research and health economics. An important outcome of the Summit was the presentation of the Porto Declaration, which called for a collective and committed action throughout Europe to develop the cancer research infrastructures indispensable for fostering innovation and decreasing inequalities within and between member states. Moreover, the Summit guidelines will assist decision making in the context of a unique EU-wide cancer initiative that, if expertly implemented, will decrease the cancer death toll and improve the quality of life of those confronted with cancer, and this is carried out at an affordable cost.

Validation of an NGS Panel Designed for Detection of Actionable Mutations in Tumors Common in Latin America

Next-generation sequencing (NGS) is progressively being used in clinical practice. However, several barriers preclude using this technology for precision oncology in most Latin American countries. To overcome some of these barriers, we have designed a 25-gene panel that contains predictive biomarkers for most current and near-future available therapies in Chile and Latin America. Library preparation was optimized to account for low DNA integrity observed in formalin-fixed paraffin-embedded tissue. The workflow includes an automated bioinformatic pipeline that accounts for the underrepresentation of Latin Americans in genome databases. The panel detected small insertions, deletions, and single nucleotide variants down to allelic frequencies of 0.05 with high sensitivity, specificity, and reproducibility. The workflow was validated in 272 clinical samples from several solid tumor types, including gallbladder (GBC). More than 50 biomarkers were detected in these samples, mainly in BRCA1/2, KRAS, and PIK3CA genes. In GBC, biomarkers for PARP, EGFR, PIK3CA, mTOR, and Hedgehog signaling inhibitors were found. Thus, this small NGS panel is an accurate and sensitive method that may constitute a more cost-efficient alternative to multiple non-NGS assays and costly, large NGS panels. This kind of streamlined assay with automated bioinformatics analysis may facilitate the implementation of precision medicine in Latin America.

Multi-omic molecular profiling guide's efficacious treatment selection in refractory metastatic breast cancer: a prospective phase II clinical trial

This prospective phase II clinical trial (Side Out 2) explored the clinical benefits of treatment selection informed by multi‐omic molecular profiling (MoMP) in refractory metastatic breast cancers (MBCs). Core needle biopsies were collected from 32 patients with MBC at trial enrollment. Patients had received an average of 3.94 previous lines of treatment in the metastatic setting before enrollment in this study. Samples underwent MoMP, including exome sequencing, RNA sequencing (RNA‐Seq), immunohistochemistry, and quantitative protein pathway activation mapping by Reverse Phase Protein Microarray (RPPA). Clinical benefit was assessed using the previously published growth modulation index (GMI) under the hypothesis that MoMP‐selected therapy would warrant further investigation for GMI ≥ 1.3 in ≥ 35% of the patients. Of the 32 patients enrolled, 29 received treatment based on their MoMP and 25 met the follow‐up criteria established by the trial protocol. Molecular information was delivered to the tumor board in a median time frame of 14 days (11–22 days), and targetable alterations for commercially available agents were found in 23/25 patients (92%). Of the 25 patients, 14 (56%) reached GMI ≥ 1.3. A high level of DNA topoisomerase I (TOPO1) led to the selection of irinotecan‐based treatments in 48% (12/25) of the patients. A pooled analysis suggested clinical benefit in patients with high TOPO1 expression receiving irinotecan‐based regimens (GMI ≥ 1.3 in 66.7% of cases). These results confirmed previous observations that MoMP increases the frequency of identifiable actionable alterations (92% of patients). The MoMP proposed allows the identification of biomarkers that are frequently expressed in MBCs and the evaluation of their role as predictors of response to commercially available agents. Lastly, this study confirmed the role of MoMP for informing treatment selection in refractory MBC patients: more than half of the enrolled patients reached a GMI ≥ 1.3 even after multiple lines of previous therapies for metastatic disease.

Pragmatic patient engagement in designing pragmatic oncology clinical trials

Oncology trials are the cornerstone of effective and safe therapeutic discoveries. However, there is increasing demand for pragmatism and patient engagement in the design, implementation and dissemination of oncology trials. Many researchers are uncertain about making trials more practical and even less knowledgeable about how to meaningfully engage patients without compromising scientific rigor to meet regulatory requirements. The present work provides practical guidance for addressing both pragmaticism and meaningful patient engagement. Applying evidence-based approaches like PRECIS-2-tool and the 10-Step Engagement Framework offer practical guidance to make future trials in oncology truly pragmatic and patient-centered. Consequently, such patient-centered trials have improved participation, faster recruitment and greater retention, and uptake of innovative technologies in community-based care.

Validating cell-free DNA from supernatant for molecular diagnostics on cytology specimens

BACKGROUND

Cytology specimens are often used for biomarker testing in the setting of neoplasia. On occasion, formalin-fixed paraffin-embedded (FFPE) cell blocks unfortunately may not yield sufficient material for testing. Recent studies have suggested that residual supernatant fluid from cell block preparation is a valuable source of DNA: both cellular and cell-free DNA (cfDNA). In the present study, the use of cfDNA from supernatant is compared against DNA from FFPE materials.

METHODS

cfDNA was extracted prospectively from residual supernatants of 30 cytology samples (29 neoplastic cases and 1 benign ascitic fluid from a patient with a history of melanoma). Samples were tested using clinically validated next-generation-sequencing platforms and the results were compared with data from paired FFPE cell blocks in a real-time prospective clinical setting. Thirteen samples were tested on an amplicon-based assay (Solid Tumor Hotspot), and 17 samples were tested using a comprehensive capture-based assay (UW-Oncoplex).

RESULTS

Neoplastic content was estimated by mutational variant allele fraction, with a mean content of 24.0% and 25.8% in supernatant and FFPE, respectively. The variant concordance between paired samples was 90%, and identical results were detected in both supernatant and FFPE samples in 74% of cases.

CONCLUSIONS

This study confirmed that cfDNA from supernatant is a viable alternative to FFPE cell blocks for molecular biomarker testing using both amplicon-based and capture-based assays with potential for decreasing additional tissue sampling and faster turnaround time.

Guidance for the Harmonisation and Improvement of Economic Evaluations of Personalised Medicine

OBJECTIVE

The objective of this study was to develop guidance contributing to improved consistency and quality in economic evaluations of personalised medicine (PM), given current ambiguity about how to measure the value of PM as well as considerable variation in the methodology and reporting in economic evaluations of PM.

METHODS

A targeted literature review of methodological papers was performed for an overview of modelling challenges in PM. Expert interviews were held to discuss best modelling practice. A systematic literature review of economic evaluations of PM was conducted to gain insight into current modelling practice. The findings were synthesised and used to develop a set of draft recommendations. The draft recommendations were discussed at a stakeholder workshop and subsequently finalised.

RESULTS

Twenty-two methodological papers were identified. Some argued that the challenges in modelling PM can be addressed within existing methodological frameworks, others disagreed. Eighteen experts were interviewed. They believed large uncertainty to be a key concern. Out of 195 economic evaluations of PM identified, 56% addressed none of the identified modelling challenges. A set of 23 recommendations was developed. Eight recommendations focus on the modelling of test-treatment pathways. The use of non-randomised controlled trial data is discouraged but several recommendations are provided in case randomised controlled trial data are unavailable. The parameterisation of structural uncertainty is recommended. Other recommendations consider perspective and discounting; premature survival data; additional value elements; patient and clinician compliance; and managed entry agreements.

CONCLUSIONS

This study provides a comprehensive list of recommendations to modellers of PM and to evaluators and reviewers of PM models.

The Yin and the Yang of Transformative Research During the COVID-19 Pandemic-A Perspective

The COVID-19 pandemic has highlighted the necessity for scientists from diverse disciplines to collaboratively mitigate the singular calamity facing humanity this century. The ability of researchers to combine exponential advances in technology and scientific acumen has resulted in landmark discoveries in pediatric research and is surmounting the COVID-19 challenge. Several of these discoveries exist in a realm of research that is not classically "basic" or "clinical." Translational research characterizes this domain partially, but does not fully capture the integrated research approaches that have spurred these discoveries. Herein, we share our perspective on the common themes underpinning the basic and clinical research. We also highlight major differences in the scope, emphasis, approach, and limitations of basic and clinical research that impede multi-disciplinary approaches that facilitate truly transformative research. These differences in research thinking and methodology are ingrained during training wherein the limitations of the chosen discipline, and strengths of alternate disciplines are not adequately explored. Insular approaches are particularly limited in impacting complex diseases pathophysiology in the era of precision medicine. We propose that integration of -omics technologies, systems biology, adaptive clinical trial designs, humanized animal models, and precision pre-clinical model systems must be incorporated into research training of future scientists. Several initiatives from the NIH and other institutions are facilitating such broad-based "research without frontiers" training that paves the way for seamless, multi-disciplinary, research. Such efforts become "transformative" when scientific challenges are tackled in partnership with a willingness to share ideas, tackle challenges, and develop tools/models from the very beginning.

Artificial intelligence in early drug discovery enabling precision medicine

Introduction: Precision medicine is the concept of treating diseases based on environmental factors, lifestyles, and molecular profiles of patients. This approach has been found to increase success rates of clinical trials and accelerate drug approvals. However, current precision medicine applications in early drug discovery use only a handful of molecular biomarkers to make decisions, whilst clinics gear up to capture the full molecular landscape of patients in the near future. This deep multi-omics characterization demands new analysis strategies to identify appropriate treatment regimens, which we envision will be pioneered by artificial intelligence.Areas covered: In this review, the authors discuss the current state of drug discovery in precision medicine and present our vision of how artificial intelligence will impact biomarker discovery and drug design.Expert opinion: Precision medicine is expected to revolutionize modern medicine; however, its traditional form is focusing on a few biomarkers, thus not equipped to leverage the full power of molecular landscapes. For learning how the development of drugs can be tailored to the heterogeneity of patients across their molecular profiles, artificial intelligence algorithms are the next frontier in precision medicine and will enable a fully personalized approach in drug design, and thus ultimately impacting clinical practice.

Proteomics, Personalized Medicine and Cancer

As of 2020 the human genome and proteome are both at >90% completion based on high stringency analyses. This has been largely achieved by major technological advances over the last 20 years and has enlarged our understanding of human health and disease, including cancer, and is supporting the current trend towards personalized/precision medicine. This is due to improved screening, novel therapeutic approaches and an increased understanding of underlying cancer biology. However, cancer is a complex, heterogeneous disease modulated by genetic, molecular, cellular, tissue, population, environmental and socioeconomic factors, which evolve with time. In spite of recent advances in treatment that have resulted in improved patient outcomes, prognosis is still poor for many patients with certain cancers (e.g., mesothelioma, pancreatic and brain cancer) with a high death rate associated with late diagnosis. In this review we overview key hallmarks of cancer (e.g., autophagy, the role of redox signaling), current unmet clinical needs, the requirement for sensitive and specific biomarkers for early detection, surveillance, prognosis and drug monitoring, the role of the microbiome and the goals of personalized/precision medicine, discussing how emerging omics technologies can further inform on these areas. Exemplars from recent onco-proteogenomic-related publications will be given. Finally, we will address future perspectives, not only from the standpoint of perceived advances in treatment, but also from the hurdles that have to be overcome.

Pharmacoepidemiology: A time for a new multidisciplinary approach to precision medicine

The advent of the genomic age has created a rapid increase in complexity for the development and selection of drug treatments. A key component of precision medicine is the use of genetic information to improve therapeutic effectiveness of drugs and prevent potential adverse drug reactions. Pharmacoepidemiology, as a field, uses observational methods to evaluate the safety and effectiveness of drug treatments in populations. Pharmacoepidemiology by virtue of its focus, tradition, and research orientation can provide appropriate study designs and analysis methods for precision medicine. The objective of this manuscript is to demonstrate how pharmacoepidemiology can impact and shape precision medicine and serve as a reference for pharmacoepidemiologists interested in contributing to the science of precision medicine. This paper depicts the state of the science with respect to the need for pharmacoepidemiology and pharmacoepidemiological methods, tools and approaches for precision medicine; the need for and how pharmacoepidemiologists use their skills to engage with the precision medicine community; and recommendations for moving the science of precision medicine pharmacoepidemiology forward. We propose a new integrated multidisciplinary approach dedicated to the emerging science of precision medicine pharmacoepidemiology.

The Contribution of Clinical Pharmacologists in Precision Medicine: An Opportunity for Health Care Improvement

Background

Clinical pharmacologists play an important role and have professional value in the field, especially regarding their role within precision medicine (PM) and personalized therapies.

Objective

In this work, we sought to stimulate debate on the role of clinical pharmacologists.

Methods

A literature review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, through electronic consultation of 2 databases, PubMed/Medline and Embase, and Google Scholar with manual research taking into account the peer-reviewed literature such as observational studies, reviews, original research articles, comments, mini-reviews, and opinion papers published in English between 2010 and February 2020. Titles and abstracts were screened by 1 author, and studies identified for full-text analysis and selected according to inclusion criteria were agreed on by 2 reviewers.

Results

We identified a total of 535 peer-reviewed articles and the number of full texts eligible for the project was 43. Several publications highlight the clinical value of pharmacologists in highly complex hospitals, where the strategies of PM are implemented. Although there are still no studies measuring the clinical efficiency and the efficacy of clinical pharmacology services, and the applicability of PM protocols, this review shows the considerable debate around the future mission of clinical pharmacology services as a bridging discipline capable of combining the complex knowledge and different professional skills needed to fully implement PM.

Conclusions

Various strategies have been conceived and planned to facilitate the transition from mainstream medicine to PM, which will enable patients to be treated more accurately, with significant advantages in terms of safety and effectiveness of treatments. Therefore, in the future, to ensure that the evolutionary process of medicine can involve as many patients and caregivers as possible, infrastructures capable of bringing together different multidisciplinary skills among health professionals will have to be implemented. Clinical pharmacologists could be the main drivers of this strategy because they already, with their multidisciplinary training, operate in a series of services in high-level hospitals, facilitating the clinical governance of the most challenging patients. The implementation of these strategies will lastly allow national health organizations to adequately address the management and therapeutic challenges related to the advent of new drugs and cell and gene therapies by facilitating the removal of economic and organizational barriers to ensure equitable access to PM. (Curr Ther Res Clin Exp. 2021; 82:XXX–XXX)

Precision Oncology, Signaling and Anticancer Agents in Cancer Therapeutics

BACKGROUND

The global alliance for genomics and healthcare facilities provides innovational solutions to expedite research and clinical practices for complex and incurable health conditions. Precision oncology is an emerging field explicitly tailored to facilitate cancer diagnosis, prevention and treatment based on patients' genetic profile. Advancements in "omics" techniques, next-generation sequencing, artificial intelligence and clinical trial designs provide a platform for assessing the efficacy and safety of combination therapies and diagnostic procedures.

METHOD

Data were collected from Pubmed and Google scholar using keywords: "Precision medicine", "precision medicine and cancer", "anticancer agents in precision medicine" and reviewed comprehensively.

RESULTS

Personalized therapeutics including immunotherapy, cancer vaccines, serve as a groundbreaking solution for cancer treatment. Herein, we take a measurable view of precision therapies and novel diagnostic approaches targeting cancer treatment. The contemporary applications of precision medicine have also been described along with various hurdles identified in the successful establishment of precision therapeutics.

CONCLUSION

This review highlights the key breakthroughs related to immunotherapies, targeted anticancer agents, and target interventions related to cancer signaling mechanisms. The success story of this field in context to drug resistance, safety, patient survival and in improving quality of life is yet to be elucidated. We conclude that, in the near future, the field of individualized treatments may truly revolutionize the nature of cancer patient care.

Lights and Shadows in Immuno-Oncology Drug Development

The rapidly evolving landscape of immuno-oncology (IO) is redefining the treatment of a number of cancer types. IO treatments are becoming increasingly complex, with different types of drugs emerging beyond checkpoint inhibitors. However, many of the new drugs either do not progress from phase I-II clinical trials or even fail in late-phase trials. We have identified at least five areas in the development of promising IO treatments that should be redefined for more efficient designs and accelerated approvals. Here we review those critical aspects of IO drug development that could be optimized for more successful outcome rates in all cancer types. It is important to focus our efforts on the mechanisms of action, types of response and adverse events of these novel agents. The use of appropriate clinical trial designs with robust biomarkers of response and surrogate endpoints will undoubtedly facilitate the development and subsequent approval of these drugs. Further research is also needed to establish biomarker-driven strategies to select which patients may benefit from immunotherapy and identify potential mechanisms of resistance.

Adapting the randomised controlled trial (RCT) for precision medicine: introducing the nested-precision RCT (npRCT)

Adaptations to the gold standard randomised controlled trial (RCT) have been introduced to decrease trial costs and avoid high sample sizes. To facilitate development of precision medicine algorithms that aim to optimise treatment allocation for individual patients, we propose a new RCT adaptation termed the nested-precision RCT (npRCT). The npRCT combines a traditional RCT (intervention A versus B) with a precision RCT (stratified versus randomised allocation to A or B). This combination allows online development of a precision algorithm, thus providing an integrated platform for algorithm development and its testing. Moreover, as both the traditional and the precision RCT include participants randomised to interventions of interest, data from these participants can be jointly analysed to determine the comparative effectiveness of intervention A versus B, thus increasing statistical power. We quantify savings of the npRCT compared to two independent RCTs by highlighting sample size requirements for different target effect sizes and by introducing an open-source power calculation app. We describe important practical considerations such as blinding issues and potential biases that need to be considered when designing an npRCT. We also highlight limitations and research contexts that are less suited for an npRCT. In conclusion, we introduce the npRCT as a novel precision medicine trial design strategy which may provide one opportunity to efficiently combine traditional and precision RCTs.

Precision clinical trials: a framework for getting to precision medicine for neurobehavioural disorders

The goal of precision medicine (individually tailored treatments) is not being achieved for neurobehavioural conditions such as psychiatric disorders. Traditional randomized clinical trial methods are insufficient for advancing precision medicine because of the dynamic complexity of these conditions. We present a pragmatic solution: the precision clinical trial framework, encompassing methods for individually tailored treatments. This framework includes the following: (1) treatment-targeted enrichment, which involves measuring patients' response after a brief bout of an intervention, and then randomizing patients to a full course of treatment, using the acute response to predict long-term outcomes; (2) adaptive treatments, which involve adjusting treatment parameters during the trial to individually optimize the treatment; and (3) precise measurement, which involves measuring predictor and outcome variables with high accuracy and reliability using techniques such as ecological momentary assessment. This review summarizes precision clinical trials and provides a research agenda, including new biomarkers such as precision neuroimaging, transcranial magnetic stimulation-electroencephalogram digital phenotyping and advances in statistical and machine-learning models. Validation of these approaches - and then widespread incorporation of the precision clinical trial framework - could help achieve the vision of precision medicine for neurobehavioural conditions.

Low participation rates and disparities in participation in interventional clinical trials for myelodysplastic syndromes

BACKGROUND

The development of novel therapies for the myelodysplastic syndromes (MDS) is hampered by inadequate trial recruitment. Factors contributing to low trial accrual are incompletely understood.

METHODS

This study analyzed a pooled patient database from institutions of the US MDS Clinical Research Consortium to compare the characteristics of participants in interventional trials with those of patients who did not enroll in a trial.

RESULTS

Data were identified for 1919 patients with MDS, and 449 of these patients (23%) participated in an interventional clinical trial. The median age of all patients was 68 years, and 64% were male. Patients who participated in trials were significantly younger than nonparticipants (P = .014), and men were more likely to participate in a trial (71% of trial participants were male, whereas 61% of nonparticipants were; P < .001). Race and ethnicity were not associated with trial enrollment. Patients in more affluent ZIP codes had a higher participation rate (P < .001). Patients with intermediate- and high-risk disease according to the revised International Prognostic Scoring System were overrepresented (P = .004), and trial participants less frequently had treatment-related disease (P < .001). In multivariable analyses, participation in a clinical trial was associated with a reduced hazard of death (P = .004). Even at large referral centers, only a minority of patients with MDS enrolled in interventional trials.

CONCLUSIONS

Restrictive trial eligibility criteria that exclude patients with MDS on account of age, comorbidities, or a history of another cancer are limit enrollment of MDS patients to clinical trials. Gaining insight into the barriers to trial accrual may help investigators and study sponsors to design trials that will accrue more rapidly and augment treatment options for patients with MDS.

A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Purpose:

Pancreatic ductal adenocarcinoma (PDAC) arising in patients with a germline BRCA1 or BRCA2 (gBRCA) mutation may be sensitive to platinum and PARP inhibitors (PARPi). However, treatment stratification based on gBRCA mutational status alone is associated with heterogeneous responses.

Experimental Design:

We performed a seven-arm preclinical trial consisting of 471 mice, representing 12 unique PDAC patient-derived xenografts, of which nine were gBRCA mutated. From 179 patients whose PDAC was whole-genome and transcriptome sequenced, we identified 21 cases with homologous recombination deficiency (HRD), and investigated prognostic biomarkers.

Results:

We found that biallelic inactivation of BRCA1/BRCA2 is associated with genomic hallmarks of HRD and required for cisplatin and talazoparib (PARPi) sensitivity. However, HRD genomic hallmarks persisted in xenografts despite the emergence of therapy resistance, indicating the presence of a genomic scar. We identified tumor polyploidy and a low Ki67 index as predictors of poor cisplatin and talazoparib response. In patients with HRD PDAC, tumor polyploidy and a basal-like transcriptomic subtype were independent predictors of shorter survival. To facilitate clinical assignment of transcriptomic subtype, we developed a novel pragmatic two-marker assay (GATA6:KRT17).

Conclusions:

In summary, we propose a predictive and prognostic model of gBRCA-mutated PDAC on the basis of HRD genomic hallmarks, Ki67 index, tumor ploidy, and transcriptomic subtype.

Clinical Trial Subinvestigator: An Emerging Role for Oncology Nurse Practitioners

Phase 1 clinical trials are essential to improving outcomes in cancer care. The investigational agents in these trials may be associated with adverse events that can contribute to symptom burden and declining performance status for trial participants. The emerging role for oncology nurse practitioners (ONPs) as subinvestigators offers a unique practice setting for advanced practice nurses. In this role, ONPs provide expert oncology care, are responsible for swift recognition and management of adverse events, and ensure adherence to the clinical trial protocol.

Personalised medicine and the decision to withhold chemotherapy in early breast cancer with intermediate risk of recurrence - a systematic review and meta-analysis

PURPOSE

To assess the evidence for decision making, at the health care and the patient levels, regarding the use of gene expression assays to inform chemotherapy decisions in breast cancer patients with intermediate clinical risk of recurrence.

METHODS

Systematic literature searches were performed (January 2002-April 2020) in Medline, Embase, PubMed, Cochrane Library, PsycINFO and HTA databases.

INCLUSION CRITERIA

patients (P) were individuals with post-surgical breast cancer at intermediate clinical risk of recurrence; intervention (I)/comparison (C) was (i) use of, versus no use of, a gene expression assay and (ii) withholding versus providing chemotherapy; outcomes (O) were overall survival (OS), health-related quality of life (HRQL), and recurrence. Randomised controlled trials (RCTs) and non-RCTs were included. Random-effects meta-analyses were performed where possible.

RESULTS

Three inconclusive non-RCTs, respectively, compared OS and recurrence with and without a gene expression assay. No studies investigated HRQL. Regarding the comparison withholding versus providing chemotherapy based on a gene expression assay, one RCT and four non-RCTs evaluated OS. In the RCT, 93.9% (I) versus 93.8% (C) were alive at 9 years. Three RCTs and seven non-RCTs evaluated recurrence. Three RCTs could be pooled regarding distant recurrence; 4.29% versus 3.88% had such an event (risk ratio: 1.12 (95% confidence interval: 0.90 to 1.39).

CONCLUSION

Regarding the use of gene expression assays in breast cancer, evidence on patient effects, informing patient-level chemotherapy decision making, is available. However, evidence for prioritisation at the overall health care level, i.e. use of, versus no use of, such assays, is largely lacking.