I-SPY 2: a Neoadjuvant Adaptive Clinical Trial Designed to Improve Outcomes in High-Risk Breast Cancer

Advancing randomized controlled trial methodologies: The place of innovative trial design in eating disorders research

Randomized controlled trials can be used to generate evidence on the efficacy and safety of new treatments in eating disorders research. Many of the trials previously conducted in this area have been deemed to be of low quality, in part due to a number of practical constraints. This article provides an overview of established and more innovative clinical trial designs, accompanied by pertinent examples, to highlight how design choices can enhance flexibility and improve efficiency of both resource allocation and participant involvement. Trial designs include individually randomized, cluster randomized, and designs with randomizations at multiple time points and/or addressing several research questions (master protocol studies). Design features include the use of adaptations and considerations for pragmatic or registry-based trials. The appropriate choice of trial design, together with rigorous trial conduct, reporting and analysis, can establish high-quality evidence to advance knowledge in the field. It is anticipated that this article will provide a broad and contemporary introduction to trial designs and will help researchers make informed trial design choices for improved testing of new interventions in eating disorders. PUBLIC SIGNIFICANCE: There is a paucity of high quality randomized controlled trials that have been conducted in eating disorders, highlighting the need to identify where efficiency gains in trial design may be possible to advance the eating disorder research field. We provide an overview of some key trial designs and features which may offer solutions to practical constraints and increase trial efficiency.

Enhancing pathological complete response prediction in breast cancer: the role of dynamic characterization of DCE-MRI and its association with tumor heterogeneity

BACKGROUND

Early prediction of pathological complete response (pCR) is important for deciding appropriate treatment strategies for patients. In this study, we aimed to quantify the dynamic characteristics of dynamic contrast-enhanced magnetic resonance images (DCE-MRI) and investigate its value to improve pCR prediction as well as its association with tumor heterogeneity in breast cancer patients.

METHODS

The DCE-MRI, clinicopathologic record, and full transcriptomic data of 785 breast cancer patients receiving neoadjuvant chemotherapy were retrospectively included from a public dataset. Dynamic features of DCE-MRI were computed from extracted phase-varying radiomic feature series using 22 CAnonical Time-sereis CHaracteristics. Dynamic model and radiomic model were developed by logistic regression using dynamic features and traditional radiomic features respectively. Various combined models with clinical factors were also developed to find the optimal combination and the significance of each components was evaluated. All the models were evaluated in independent test set in terms of area under receiver operating characteristic curve (AUC). To explore the potential underlying biological mechanisms, radiogenomic analysis was implemented on patient subgroups stratified by dynamic model to identify differentially expressed genes (DEGs) and enriched pathways.

RESULTS

A 10-feature dynamic model and a 4-feature radiomic model were developed (AUC = 0.688, 95%CI: 0.635-0.741 and AUC = 0.650, 95%CI: 0.595-0.705) and tested (AUC = 0.686, 95%CI: 0.594-0.778 and AUC = 0.626, 95%CI: 0.529-0.722), with the dynamic model showing slightly higher AUC (train p = 0.181, test p = 0.222). The combined model of clinical, radiomic, and dynamic achieved the highest AUC in pCR prediction (train: 0.769, 95%CI: 0.722-0.816 and test: 0.762, 95%CI: 0.679-0.845). Compared with clinical-radiomic combined model (train AUC = 0.716, 95%CI: 0.665-0.767 and test AUC = 0.695, 95%CI: 0.656-0.714), adding the dynamic component brought significant improvement in model performance (train p < 0.001 and test p = 0.005). Radiogenomic analysis identified 297 DEGs, including CXCL9, CCL18, and HLA-DPB1 which are known to be associated with breast cancer prognosis or angiogenesis. Gene set enrichment analysis further revealed enrichment of gene ontology terms and pathways related to immune system.

CONCLUSION

Dynamic characteristics of DCE-MRI were quantified and used to develop dynamic model for improving pCR prediction in breast cancer patients. The dynamic model was associated with tumor heterogeniety in prognostic-related gene expression and immune-related pathways.

Precision Oncology in Breast Cancer Surgery

Outcomes for patients with breast cancer have improved over time due to increased screening and the availability of more effective therapies. It is important to recognize that breast cancer is a heterogeneous disease that requires treatment based on molecular characteristics. Early endpoints such as pathologic complete response correlate with event-free survival, allowing the opportunity to consider de-escalation of certain cancer treatments to avoid overtreatment. This article discusses clinical trials of tailoring treatment (eg, I-SPY2) and screening (eg, WISDOM) to individual patients based on their unique risk features.

Systematic annotation of orphan RNAs reveals blood-accessible molecular barcodes of cancer identity and cancer-emergent oncogenic drivers

From extrachromosomal DNA to neo-peptides, the broad reprogramming of the cancer genome leads to the emergence of molecules that are specific to the cancer state. We recently described orphan non-coding RNAs (oncRNAs) as a class of cancer-specific small RNAs with the potential to play functional roles in breast cancer progression1. Here, we report a systematic and comprehensive search to identify, annotate, and characterize cancer-emergent oncRNAs across 32 tumor types. We also leverage large-scale in vivo genetic screens in xenografted mice to functionally identify driver oncRNAs in multiple tumor types. We have not only discovered a large repertoire of oncRNAs, but also found that their presence and absence represent a digital molecular barcode that faithfully captures the types and subtypes of cancer. Importantly, we discovered that this molecular barcode is partially accessible from the cell-free space as some oncRNAs are secreted by cancer cells. In a large retrospective study across 192 breast cancer patients, we showed that oncRNAs can be reliably detected in the blood and that changes in the cell-free oncRNA burden captures both short-term and long-term clinical outcomes upon completion of a neoadjuvant chemotherapy regimen. Together, our findings establish oncRNAs as an emergent class of cancer-specific non-coding RNAs with potential roles in tumor progression and clinical utility in liquid biopsies and disease monitoring.

Metformin and Breast Cancer: Current Findings and Future Perspectives from Preclinical and Clinical Studies

Over the last several decades, a growing body of research has investigated the potential to repurpose the anti-diabetic drug metformin for breast cancer prevention and/or treatment. Observational studies in the early 2000s demonstrated that patients with diabetes taking metformin had decreased cancer risk, providing the first evidence supporting the potential role of metformin as an anti-cancer agent. Despite substantial efforts, two decades later, the exact mechanisms and clinical efficacy of metformin for breast cancer remain ambiguous. Here, we have summarized key findings from studies examining the effect of metformin on breast cancer across the translational spectrum including in vitro, in vivo, and human studies. Importantly, we discuss critical factors that may help explain the significant heterogeneity in study outcomes, highlighting how metformin dose, underlying metabolic health, menopausal status, tumor subtype, membrane transporter expression, diet, and other factors may play a role in modulating metformin's anti-cancer effects. We hope that these insights will help with interpreting data from completed studies, improve the design of future studies, and aid in the identification of patient subsets with breast cancer or at high risk for the disease who are most likely to benefit from metformin treatment.

Axillary management in breast cancer after neoadjuvant chemotherapy in the modern era: A national cancer database analysis

BACKGROUND

Axillary management for node-positive breast cancer continues to evolve. Data further supporting targeted axillary dissection after neoadjuvant chemotherapy was published in 2016 and may have induced changes in practice.

METHODS

Patients included in the National Cancer Database from 2014 to 2017 with clinical T1 to T4 and node-positive disease who underwent neoadjuvant chemotherapy before surgical axillary management were evaluated. Patients were divided into the following 3 groups: selective axillary dissection, minimal axillary dissection, and maximal axillary dissection, according to surgical axillary management and pathological node status.

RESULTS

Patients who underwent selective axillary dissection were younger (52.4 years ± 12.4, P < .0001) compared to maximal axillary dissection (55.1 ± 12.7) and minimal axillary dissection (54.6 ± 12.7). Patients with higher clinical stage more frequently underwent maximal axillary dissection, and those with lower tumor grade more frequently underwent minimal axillary dissection (P < .0001). Community cancer programs were more likely to perform maximal axillary dissection compared to all other types of programs and had the slowest rate of adoption of selective axillary dissection. Integrated Network Cancer Programs had the lowest proportion of maximal axillary dissection performed and the highest proportion of selective axillary dissection. Uninsured patients were more likely to receive maximal axillary dissection, and those with private insurance were more likely to undergo selective axillary dissection (P < .0001). Selective axillary dissection rates increased from 29.8% of procedures in 2016 to 41.5% in 2017, and MaxAD rates decreased from 62.4% in 2016 to 47.9% in 2017.

CONCLUSION

Utilization of selective axillary dissection has increased since 2016; however, discrepancies in surgical axillary management after neoadjuvant chemotherapy still exist.

Machine learning prediction of pathological complete response and overall survival of breast cancer patients in an underserved inner-city population

BACKGROUND

Generalizability of predictive models for pathological complete response (pCR) and overall survival (OS) in breast cancer patients requires diverse datasets. This study employed four machine learning models to predict pCR and OS up to 7.5 years using data from a diverse and underserved inner-city population.

METHODS

Demographics, staging, tumor subtypes, income, insurance status, and data from radiology reports were obtained from 475 breast cancer patients on neoadjuvant chemotherapy in an inner-city health system (01/01/2012 to 12/31/2021). Logistic regression, Neural Network, Random Forest, and Gradient Boosted Regression models were used to predict outcomes (pCR and OS) with fivefold cross validation.

RESULTS

pCR was not associated with age, race, ethnicity, tumor staging, Nottingham grade, income, and insurance status (p > 0.05). ER-/HER2+ showed the highest pCR rate, followed by triple negative, ER+/HER2+, and ER+/HER2- (all p < 0.05), tumor size (p < 0.003) and background parenchymal enhancement (BPE) (p < 0.01). Machine learning models ranked ER+/HER2-, ER-/HER2+, tumor size, and BPE as top predictors of pCR (AUC = 0.74-0.76). OS was associated with race, pCR status, tumor subtype, and insurance status (p < 0.05), but not ethnicity and incomes (p > 0.05). Machine learning models ranked tumor stage, pCR, nodal stage, and triple-negative subtype as top predictors of OS (AUC = 0.83-0.85). When grouping race and ethnicity by tumor subtypes, neither OS nor pCR were different due to race and ethnicity for each tumor subtype (p > 0.05).

CONCLUSION

Tumor subtypes and imaging characteristics were top predictors of pCR in our inner-city population. Insurance status, race, tumor subtypes and pCR were associated with OS. Machine learning models accurately predicted pCR and OS.

Physicians' Hierarchy of Tumor Biomarkers for Optimizing Chemotherapy in Breast Cancer Care

BACKGROUND

Tumor biomarkers are regularly used to guide breast cancer treatment and clinical trial enrollment. However, there remains a lack of knowledge regarding physicians' perspectives towards biomarkers and their role in treatment optimization, where treatment intensity is reduced to minimize toxicity.

METHODS

Thirty-nine academic and community oncologists participated in semi-structured qualitative interviews, providing perspectives on optimization approaches to chemotherapy treatment. Interviews were audio-recorded, transcribed, and analyzed by 2 independent coders utilizing a constant comparative method in NVivo. Major themes and exemplary quotes were extracted. A framework outlining physicians' conception of biomarkers, and their comfortability with their use in treatment optimization, was developed.

RESULTS

In the hierarchal model of biomarkers, level 1 is comprised of standard-of-care (SoC) biomarkers, defined by a strong level of evidence, alignment with national guidelines, and widespread utilization. Level 2 includes SoC biomarkers used in alternative contexts, in which physicians expressed confidence, yet less certainty, due to a lack of data in certain subgroups. Level 3, or experimental, biomarkers created the most diverse concerns related to quality and quantity of evidence, with several additional modulators.

CONCLUSION

This study demonstrates that physicians conceptualize the use of biomarkers for treatment optimization in successive levels. This hierarchy can be used to guide trialists in the development of novel biomarkers and design of future trials.

Shorter Durations of Anti-HER2 Therapy for Patients with Early-Stage, HER2-Positive Breast Cancer: The Physician Perspective

Despite evidence from clinical trials showing the efficacy of shorter durations of therapy, most HER2-positive early breast cancer (EBC) patients receive a year of anti-HER2 therapy. A survey of Canadian oncologists was conducted online, with electronic data collection, and the analysis is reported descriptively. Measures collected included current practices with respect to the duration of adjuvant anti-HER2 therapy, perspectives on data regarding shorter durations of treatment, and interest in further trials on this subject. Responses were received from 42 providers across Canada. Half (50%, 21/42) reported having never recommended 6 months of anti-HER2 therapy. The primary reason physicians consider a shorter duration is in response to treatment-related toxicities (76%, 31/41). Most participants (79%, 33/42) expressed the need for more data to determine which patients can be safely and effectively treated with shorter durations. Patient factors such as young age, initial stage, hormone receptor status, and type of neoadjuvant chemotherapy were attributed to reluctance to offer shorter durations of treatment. Many respondents (83%, 35/42) expressed interest in participating in the proposed clinical trial of 6 months of anti-HER2 therapy. In contemporary Canadian practice, 12 months of anti-HER2 therapy remains the primary practice. Future trials are required to better define the role of shorter treatment durations.

Electronic health records (EHRs) in clinical research and platform trials: Application of the innovative EHR-based methods developed by EU-PEARL

OBJECTIVE

Electronic Health Record (EHR) systems are digital platforms in clinical practice used to collect patients' clinical information related to their health status and represents a useful storage of real-world data. EHRs have a potential role in research studies, in particular, in platform trials. Platform trials are innovative trial designs including multiple trial arms (conducted simultaneously and/or sequentially) on different treatments under a single master protocol. However, the use of EHRs in research comes with important challenges such as incompleteness of records and the need to translate trial eligibility criteria into interoperable queries. In this paper, we aim to review and to describe our proposed innovative methods to tackle some of the most important challenges identified. This work is part of the Innovative Medicines Initiative (IMI) EU Patient-cEntric clinicAl tRial pLatforms (EU-PEARL) project's work package 3 (WP3), whose objective is to deliver tools and guidance for EHR-based protocol feasibility assessment, clinical site selection, and patient pre-screening in platform trials, investing in the building of a data-driven clinical network framework that can execute these complex innovative designs for which feasibility assessments are critically important.

METHODS

ISO standards and relevant references informed a readiness survey, producing 354 criteria with corresponding questions selected and harmonised through a 7-round scoring process (0-1) in stakeholder meetings, with 85% of consensus being the threshold of acceptance for a criterium/question. ATLAS cohort definition and Cohort Diagnostics were mainly used to create the trial feasibility eligibility (I/E) criteria as executable interoperable queries.

RESULTS

The WP3/EU-PEARL group developed a readiness survey (eSurvey) for an efficient selection of clinical sites with suitable EHRs, consisting of yes-or-no questions, and a set-up of interoperable proxy queries using physicians' defined trial criteria. Both actions facilitate recruiting trial participants and alignment between study costs/timelines and data-driven recruitment potential.

CONCLUSION

The eSurvey will help create an archive of clinical sites with mature EHR systems suitable to participate in clinical trials/platform trials, and the interoperable proxy queries of trial eligibility criteria will help identify the number of potential participants. Ultimately, these tools will contribute to the production of EHR-based protocol design.

Interim monitoring of sequential multiple assignment randomized trials using partial information

The sequential multiple assignment randomized trial (SMART) is the gold standard trial design to generate data for the evaluation of multistage treatment regimes. As with conventional (single-stage) randomized clinical trials, interim monitoring allows early stopping; however, there are few methods for principled interim analysis in SMARTs. Because SMARTs involve multiple stages of treatment, a key challenge is that not all enrolled participants will have progressed through all treatment stages at the time of an interim analysis. Wu et al. (2021) propose basing interim analyses on an estimator for the mean outcome under a given regime that uses data only from participants who have completed all treatment stages. We propose an estimator for the mean outcome under a given regime that gains efficiency by using partial information from enrolled participants regardless of their progression through treatment stages. Using the asymptotic distribution of this estimator, we derive associated Pocock and O'Brien-Fleming testing procedures for early stopping. In simulation experiments, the estimator controls type I error and achieves nominal power while reducing expected sample size relative to the method of Wu et al. (2021). We present an illustrative application of the proposed estimator based on a recent SMART evaluating behavioral pain interventions for breast cancer patients.

The Breast Cancer Proteome and Precision Oncology

The goal of precision oncology is to translate the molecular features of cancer into predictive and prognostic tests that can be used to individualize treatment leading to improved outcomes and decreased toxicity. Success for this strategy in breast cancer is exemplified by efficacy of trastuzumab in tumors overexpressing ERBB2 and endocrine therapy for tumors that are estrogen receptor positive. However, other effective treatments, including chemotherapy, immune checkpoint inhibitors, and CDK4/6 inhibitors are not associated with strong predictive biomarkers. Proteomics promises another tier of information that, when added to genomic and transcriptomic features (proteogenomics), may create new opportunities to improve both treatment precision and therapeutic hypotheses. Here, we review both mass spectrometry-based and antibody-dependent proteomics as complementary approaches. We highlight how these methods have contributed toward a more complete understanding of breast cancer and describe the potential to guide diagnosis and treatment more accurately.

Neoadjuvant Talazoparib in Patients With Germline BRCA1/2 Mutation-Positive, Early-Stage Triple-Negative Breast Cancer: Results of a Phase II Study

BACKGROUND

The undetermined efficacy of the current standard-of-care neoadjuvant treatment, anthracycline/platinum-based chemotherapy, in patients with early-stage triple-negative breast cancer (TNBC) and germline BRCA mutations emphasizes the need for biomarker-targeted treatment, such as poly(ADP-ribose) polymerase inhibitors, in this setting. This phase II, single-arm, open-label study evaluated the efficacy and safety of neoadjuvant talazoparib in patients with germline BRCA1/2-mutated early-stage TNBC.

PATIENTS AND METHODS

Patients with germline BRCA1/2-mutated early-stage TNBC received talazoparib 1 mg once daily for 24 weeks (0.75 mg for moderate renal impairment) followed by surgery. The primary endpoint was pathologic complete response (pCR) by independent central review (ICR). Secondary endpoints included residual cancer burden (RCB) by ICR. Safety and tolerability of talazoparib and patient-reported outcomes were assessed.

RESULTS

Of 61 patients, 48 received ≥80% talazoparib doses, underwent surgery, and were assessed for pCR or progressed before pCR assessment and considered nonresponders. pCR rate was 45.8% (95% confidence interval [CI], 32.0%-60.6%) and 49.2% (95% CI, 36.7%-61.6%) in the evaluable and intent-to-treat (ITT) population, respectively. RCB 0/I rate was 45.8% (95% CI, 29.4%-63.2%) and 50.8% (95% CI, 35.5%-66.0%) in the evaluable and ITT population, respectively. Treatment-related adverse events (TRAE) were reported in 58 (95.1%) patients. Most common grade 3 and 4 TRAEs were anemia (39.3%) and neutropenia (9.8%). There was no clinically meaningful detriment in quality of life. No deaths occurred during the reporting period; 2 deaths due to progressive disease occurred during long-term follow-up (>400 days after first dose).

CONCLUSIONS

Neoadjuvant talazoparib monotherapy was active despite pCR rates not meeting the prespecified threshold; these rates were comparable to those observed with combination anthracycline- and taxane-based chemotherapy regimens. Talazoparib was generally well tolerated.

CLINICALTRIALS.GOV IDENTIFIER

NCT03499353.

Tumor Infiltrating Lymphocytes (TILS) and PD-L1 Expression in Breast Cancer: A Review of Current Evidence and Prognostic Implications from Pathologist's Perspective

With the rise of novel immunotherapies able to stimulate the antitumor immune response, increasing literature concerning the immunogenicity of breast cancer has been published in recent years. Numerous clinical studies have been conducted in order to identify novel biomarkers that could reflect the immunogenicity of BC and predict response to immunotherapy. In this regard, TILs have emerged as an important immunological biomarker related to the antitumor immune response in BC. TILs are more frequently observed in triple-negative breast cancer and HER2+ subtypes, where increased TIL levels have been linked to a better response to neoadjuvant chemotherapy and improved survival. PD-L1 is a type 1 transmembrane protein ligand expressed on T lymphocytes, B lymphocytes, and antigen-presenting cells and is considered a key inhibitory checkpoint involved in cancer immune regulation. PD-L1 immunohistochemical expression in breast cancer is observed in about 10-30% of cases and is extremely variable based on tumor stage and molecular subtypes. Briefly, TNBC shows the highest percentage of PD-L1 positivity, followed by HER2+ tumors. On the other hand, PD-L1 is rarely expressed (0-10% of cases) in hormone-receptor-positive BC. The prognostic role of PD-L1 expression in BC is still controversial since different immunohistochemistry (IHC) clones, cut-off points, and scoring systems have been utilized across published studies. In the present paper, an extensive review of the current knowledge of the immune landscape of BC is provided. TILS and PD-L1 expression across different BC subtypes are discussed, providing a guide for their pathological assessment and reporting.

Types and progress of clinical trial design for breast cancer: a narrative review

Background and Objective

In recent years, the field of breast cancer diagnosis and therapy has witnessed rapid technological advances. Concurrently, the emergence of molecular biology and novel detection methodologies has facilitated the transition of breast cancer management into the precision medicine era. The primary objective of this review is to discuss the transformation in the research and development paradigm for breast cancer therapies and strategies.

Methods

We systematically searched PubMed, EMBASE and Cochrane databases for relevant studies published over the past 20 years using keywords including "breast cancer", "clinical trial", "seamless", "master protocol", "umbrella", "basket", "platform", and "precision medicine". Articles were screened for eligibility and key data extracted. The search was limited to English-language publications.

Key Content and Findings

The review identifies three core innovations in breast cancer trial methodology: (I) in terms of research speed, the traditional three-stage drug development models are being substituted by "seamless designs" as exemplified by the immunotherapy combination study NCT0328056. (II) Addressing research breadth, "master protocols" such as basket trials (IMMU-132-01), umbrella trials (FUTURE), and platform trials (I-SPY 2) have been introduced, allowing the simultaneous assessment of multiple treatments or disease subtypes within a singular framework. (III) Pertaining to research precision, newer designs utilize biomarkers such as "enrichment" (seen in EMBRACA and OlympiA trials) and "marker stratification" (as in the SOLAR-1 trial), enabling the identification of appropriate patient subgroups and the provision of tailored therapy strategies, a stark contrast to traditional histopathology-based evaluations.

Conclusions

Clinical trial design in breast cancer research has been revolutionized, moving towards more efficient and targeted strategies. Despite the presence of ethical, logistical, and data complexities, it is anticipated that ongoing technological and regulatory enhancements will pave the way for even more refined research approaches, subsequently influencing future research, clinical practices, and policymaking in breast cancer care.

Immune Biomarkers in Triple-Negative Breast Cancer: Improving the Predictivity of Current Testing Methods

Triple-negative breast cancer (TNBC) poses a significant challenge in terms of prognosis and disease recurrence. The limited treatment options and the development of resistance to chemotherapy make it particularly difficult to manage these patients. However, recent research has been shifting its focus towards biomarker-based approaches for TNBC, with a particular emphasis on the tumor immune landscape. Immune biomarkers in TNBC are now a subject of great interest due to the presence of tumor-infiltrating lymphocytes (TILs) in these tumors. This characteristic often coincides with the presence of PD-L1 expression on both neoplastic cells and immune cells within the tumor microenvironment. Furthermore, a subset of TNBC harbor mismatch repair deficient (dMMR) TNBC, which is frequently accompanied by microsatellite instability (MSI). All of these immune biomarkers hold actionable potential for guiding patient selection in immunotherapy. To fully capitalize on these opportunities, the identification of additional or complementary biomarkers and the implementation of highly customized testing strategies are of paramount importance in TNBC. In this regard, this article aims to provide an overview of the current state of the art in immune-related biomarkers for TNBC. Specifically, it focuses on the various testing methodologies available and sheds light on the immediate future perspectives for patient selection. By delving into the advancements made in understanding the immune landscape of TNBC, this study aims to contribute to the growing body of knowledge in the field. The ultimate goal is to pave the way for the development of more personalized testing strategies, ultimately improving outcomes for TNBC patients.

The role of immune checkpoint inhibition in triple negative breast cancer

INTRODUCTION

Immunotherapy has revolutionized cancer treatment, including TNBC, which has limited options of treatment and poor prognosis. ICIs studied in TNBC include pembrolizumab, nivolumab, atezolizumab, and durvalumab. Initial studies exploring ICI monotherapy demonstrated promising yet limited responses. Subsequent studies, KEYNOTE 522 and KEYNOTE 355, which combined ICI with chemotherapy, have resulted in the FDA approval of pembrolizumab in the early-stage and metastatic setting, respectively.

AREAS COVERED

This article provides a comprehensive review of the role of ICI in the treatment of TNBC. We reviewed the trials that have evaluated ICI monotherapy, dual therapy, ICI in combination with chemotherapy, targeted therapy, vaccines and radiation. Additionally, we reviewed potential biomarkers of response and immune-related adverse events (irAEs). A literature search was conducted via PubMed and ClinicalTrials.gov as of 5 June 2023.

EXPERT OPINION

Various approaches combining immunotherapy with chemotherapy, targeted therapy, vaccines and radiation have been assessed. Pembrolizumab remains the only ICI approved in both the early stage and mTNBC. The role of adjuvant pembrolizumab in those who achieved pCR after neoadjuvant therapy is being investigated. Combining ICI with PARP inhibitors and radiation shows promise. More research is needed in identifying predictors of response. Monitoring of irAEs remains crucial.

Looking ahead in early-phase trial design to improve the drug development process: examples in oncology

BACKGROUND

Clinical trial design must consider the specific resource constraints and overall goals of the drug development process (DDP); for example, in designing a phase I trial to evaluate the safety of a drug and recommend a dose for a subsequent phase II trial. Here, we focus on design considerations that involve the sequence of clinical trials, from early phase I to late phase III, that constitute the DDP.

METHODS

We discuss how stylized simulation models of clinical trials in an oncology DDP can quantify important relationships between early-phase trial designs and their consequences for the remaining phases of development. Simulations for three illustrative settings are presented, using stylized models of the DDP that mimic trial designs and decisions, such as the potential discontinuation of the DDP.

RESULTS

We describe: (1) the relationship between a phase II single-arm trial sample size and the likelihood of a positive result in a subsequent phase III confirmatory trial; (2) the impact of a phase I dose-finding design on the likelihood that the DDP will produce evidence of a safe and effective therapy; and (3) the impact of a phase II enrichment trial design on the operating characteristics of a subsequent phase III confirmatory trial.

CONCLUSIONS

Stylized models of the DDP can support key decisions, such as the sample size, in the design of early-phase trials. Simulation models can be used to estimate performance metrics of the DDP under realistic scenarios; for example, the duration and the total number of patients enrolled. These estimates complement the evaluation of the operating characteristics of early-phase trial design, such as power or accuracy in selecting safe and effective dose levels.

Association of baseline ROR1 and ROR2 gene expression with clinical outcomes in the I-SPY2 neoadjuvant breast cancer trial

PURPOSE

ROR1 and ROR2 are Type 1 tyrosine kinase-like orphan receptors for Wnt5a that are associated with breast cancer progression. Experimental agents targeting ROR1 and ROR2 are in clinical trials. This study evaluated whether expression levels of ROR1 or ROR2 correlated with one another or with clinical outcomes.

METHODS

We interrogated the clinical significance of high-level gene expression of ROR1 and/or ROR2 in the annotated transcriptome dataset from 989 patients with high-risk early breast cancer enrolled in one of nine completed/graduated/experimental and control arms in the neoadjuvant I-SPY2 clinical trial (NCT01042379).

RESULTS

High ROR1 or high ROR2 was associated with breast cancer subtypes. High ROR1 was more prevalent among hormone receptor-negative and human epidermal growth factor receptor 2-negative (HR-HER2-) tumors and high ROR2 was less prevalent in this subtype. Although not associated with pathologic complete response, high ROR1 or high ROR2 each was associated with event-free survival (EFS) in distinct subtypes. High ROR1 associated with a worse EFS in HR + HER2- patients with high post-treatment residual cancer burden (RCB-II/III) (HR 1.41, 95% CI = 1.11-1.80) but not in patients with minimal post-treatment disease (RCB-0/I) (HR 1.85, 95% CI = 0.74-4.61). High ROR2 associated with an increased risk of relapse in patients with HER2 + disease and RCB-0/I (HR 3.46, 95% CI = 1.33-9.020) but not RCB-II/III (HR 1.07, 95% CI = 0.69-1.64).

CONCLUSION

High ROR1 or high ROR2 distinctly identified subsets of breast cancer patients with adverse outcomes. Further studies are warranted to determine if high ROR1 or high ROR2 may identify high-risk populations for studies of targeted therapies.

An Inflection Point in Cancer Protein Biomarkers: What Was and What's Next

Biomarkers remain the highest value proposition in cancer medicine today - especially protein biomarkers. Yet despite decades of evolving regulatory frameworks to facilitate the review of emerging technologies, biomarkers have been mostly about promise with very little to show for improvements in human health. Cancer is an emergent property of a complex system and deconvoluting the integrative and dynamic nature of the overall system through biomarkers is a daunting proposition. The last two decades have seen an explosion of multi-omics profiling and a range of advanced technologies for precision medicine, including the emergence of liquid biopsy, exciting advances in single cell analysis, artificial intelligence (machine and deep learning) for data analysis and many other advanced technologies that promise to transform biomarker discovery. Combining multiple omics modalities to acquire a more comprehensive landscape of the disease state, we are increasingly developing biomarkers to support therapy selection and patient monitoring. Furthering precision medicine, especially in oncology, necessitates moving away from the lens of reductionist thinking towards viewing and understanding that complex diseases are, in fact, complex adaptive systems. As such, we believe it is necessary to re-define biomarkers as representations of biological system states at different hierarchical levels of biological order. This definition could include traditional molecular, histologic, radiographic, or physiological characteristics, as well as emerging classes of digital markers and complex algorithms. To succeed in the future, we must move past purely observational individual studies and instead start building a mechanistic framework to enable integrative analysis of new studies within the context of prior studies. Identifying information in complex systems and applying theoretical constructs, such as information theory, to study cancer as a disease of dysregulated communication could prove to be "game changing" for the clinical outcome of cancer patients.

A platform trial approach to proof-of-concept (POC) studies in autism spectrum disorder: Autism spectrum POC initiative (ASPI)

Background

Over the past decade, autism spectrum disorder (ASD) research has blossomed, and multiple clinical trials have tested potential interventions, with varying results and no clear demonstration of efficacy. Lack of clarity concerning appropriate biological mechanisms to target and lack of sensitive, objective tools to identify subgroups and measure symptom changes have hampered the efforts to develop treatments. A platform trial for proof-of-concept studies in ASD could help address these issues. A major goal of a platform trial is to find the best treatment in the most expeditious manner, by simultaneously investigating multiple treatments, using specialized statistical tools for allocation and analysis. We describe the setup of a platform trial and perform simulations to evaluate the operating characteristics under several scenarios. We use the Autism Behavior Inventory (ABI), a psychometrically validated web-based rating scale to measure the change in ASD core and associated symptoms.

Methods

Detailed description of the setup, conduct, and decision-making rules of a platform trial are explained. Simulations of a virtual platform trial for several scenarios are performed to compare operating characteristics. The success and futility criteria for treatments are based on a Bayesian posterior probability model.

Results

Overall, simulation results show the potential gain in terms of statistical properties especially for improved decision-making ability, while careful planning is needed due to the complexities of a platform trial.

Conclusions

Autism research, shaped particularly by its heterogeneity, may benefit from the platform trial approach for POC clinical studies.

Building the foundation for a community-generated national research blueprint for inherited bleeding disorders: facilitating research through infrastructure, workforce, resources and funding

BACKGROUND

The National Hemophilia Foundation (NHF) conducted extensive, inclusive community consultations to guide prioritization of research in coming decades in alignment with its mission to find cures and address and prevent complications enabling people and families with blood disorders to thrive.

RESEARCH DESIGN AND METHODS

With the American Thrombosis and Hemostasis Network, NHF recruited multidisciplinary expert working groups (WG) to distill the community-identified priorities into concrete research questions and score their feasibility, impact, and risk. WG6 was charged with identifying the infrastructure, workforce development, and funding and resources to facilitate the prioritized research. Community input on conclusions was gathered at the NHF State of the Science Research Summit.

RESULTS

WG6 detailed a minimal research capacity infrastructure threshold, and opportunities to enable its attainment, for bleeding disorders centers to participate in prospective, multicenter national registries. They identified challenges and opportunities to recruit, retain, and train the diverse multidisciplinary care and research workforce required into the future. Innovative collaborative approaches to trial design, resource networking, and funding to surmount obstacles facing research in rare disorders were elucidated.

CONCLUSIONS

The innovations in infrastructure, workforce development, and resources and funding proposed herein may contribute to facilitating a National Research Blueprint for Inherited Bleeding Disorders.

Primary endpoints to assess the efficacy of novel therapeutic approaches in epidermal growth factor receptor-mutated, surgically resectable non-small cell lung cancer: A review

While the discovery of oncogenic driver mutations has personalized the metastatic non-small cell lung cancer (NSCLC) treatment landscape with effective targeted therapies, implementation of new treatments in resectable NSCLC has been limited due to the long follow-up needed for overall survival (OS). Until recently, treatment for patients with early-stage resectable NSCLC has been limited to perioperative chemotherapy, which provides modest benefits. However, the regulatory acceptance of two surrogate endpoints for OS has allowed recent approval of both adjuvant osimertinib and atezolizumab, providing patients with new treatment options to improve outcomes. In phase 3 oncology trials, OS has historically been viewed as the gold-standard efficacy measure, but disease-free survival and event-free survival (EFS) are now validated surrogate endpoints for OS in clinical trials and should be considered when mature OS data is unavailable. Another potential surrogate endpoint in the adjuvant NSCLC setting is circulating tumor DNA (ctDNA)-based minimal residual disease (MRD), although prospective validation is needed. For neoadjuvant targeted therapies, EFS, major pathologic response and ctDNA-based MRD are potential surrogate endpoints. To fully translate the success of the personalized treatment advances in the metastatic setting to earlier-stage disease, prospective validation studies of these potential surrogate endpoints that can accelerate the evaluation of drug efficacy are needed. A collaborative effort is also needed from all clinical and regulatory parties to collate surrogate endpoint data for large-scale validation. In this review we discuss the trends in surrogate endpoints used in oncology trials, with a focus on considerations for selecting appropriate primary endpoints in early-stage resectable EGFR-mutant NSCLC, an area of unmet need for novel treatment options.

When research becomes practice: the concept of the therapeutic misconception and challenges to consent in clinical trials

Many factors influence patients' decisions to participate in clinical trials. For many, the primary motivation is the possibility that they might derive some benefit from participation. This is particularly true for patients with limited treatment options, such as patients with advanced cancer. While this is not surprising, it is potentially problematic if patients fail to recognise the distinction between research and clinical care (a phenomenon known as the 'therapeutic misconception'). This is becoming increasingly problematic as clinical trial designs become more complex, as clinical trials become more embedded in routine clinical care, and as trials are increasingly used by patients and clinicians to access new diagnostic platforms and therapies. We outline some of these recent trends, focusing on the cancer clinical trials landscape as this provides a good case study of the phenomenon. We conclude by making preliminary suggestions that changes to the consent process, perhaps using 'dynamic consent' platforms, might help to mitigate the therapeutic misconception and note the need for further research to guide strategies for improving communication and decision-making.

Preoperative Radio(Chemo)Therapy in Breast Cancer: Time to Switch the Perspective?

AIM

Radiation therapy represents, together with surgery and systemic treatment, the triad on which the current management of patients with breast cancer is based, achieving high control and survival rates. In recent years we have witnessed a (r)evolution in the conception of breast cancer treatment. The classic scheme of surgery followed by systemic treatment and radiotherapy is being subverted and it is becoming more and more frequent to propose the primary administration of systemic treatment before surgery, seeking to maximize its effect and favoring not only the performance of more conservative surgeries but also, in selected cases, increasing the rates of disease-free survival and overall survival. Radiotherapy is also evolving toward a change in perspective: considering preoperative primary administration of radiotherapy may be useful in selected groups. Advances in radiobiological knowledge, together with technological improvements that are constantly being incorporated into clinical practice, support the administration of increasingly reliable, precise, and effective radiotherapy, as well as its safe combination with antitumor drugs or immunotherapy in the primary preoperative context. In this paper, we present a narrative review of the usefulness of preoperative radiotherapy for breast cancer patients and the possibilities for its combination with other therapies.

Optimization of Neoadjuvant Therapy for Early-Stage Triple-Negative and HER2 + Breast Cancer

PURPOSE OF REVIEW

Neoadjuvant, or pre-operative, therapy for the treatment of early-stage breast cancer has several potential benefits, especially for patients with triple-negative or HER2 + subtypes. This review provides an overview of optimal practices for utilizing neoadjuvant therapy, guidelines for decision-making, and ongoing clinical trials that are expected to help refine therapy choices.

RECENT FINDINGS

For triple-negative disease, the addition of the checkpoint inhibitor pembrolizumab to chemotherapy has shown remarkable efficacy, increasing response rates and survival. In the HER2 + setting, we are now able to safely avoid use of anthracyclines in most patients and refine adjuvant treatment choices based on response to neoadjuvant therapy. Results from recent clinical studies highlight advancements in systemic therapy and mark steps toward precision medicine, although reliable biomarkers of therapy response are still needed.

Updates in combined approaches of radiotherapy and immune checkpoint inhibitors for the treatment of breast cancer

Breast cancer is the most prevalent non-skin cancer diagnosed in females and developing novel therapeutic strategies to improve patient outcomes is crucial. The immune system plays an integral role in the body’s response to breast cancer and modulating this immune response through immunotherapy is a promising therapeutic option. Although immune checkpoint inhibitors were recently approved for the treatment of breast cancer patients, not all patients respond to immune checkpoint inhibitors as a monotherapy, highlighting the need to better understand the biology underlying patient response. Additionally, as radiotherapy is a critical component of breast cancer treatment, understanding the interplay of radiation and immune checkpoint inhibitors will be vital as recent studies suggest that combined therapies may induce synergistic effects in preclinical models of breast cancer. This review will discuss the mechanisms supporting combined approaches with radiotherapy and immune checkpoint inhibitors for the treatment of breast cancer. Moreover, this review will analyze the current clinical trials examining combined approaches of radiotherapy, immunotherapy, chemotherapy, and targeted therapy. Finally, this review will evaluate data regarding treatment tolerance and potential biomarkers for these emerging therapies aimed at improving breast cancer outcomes.

GLORIA: phase III, open-label study of adagloxad simolenin/OBI-821 in patients with high-risk triple-negative breast cancer

Triple-negative breast cancer (TNBC) has the highest rate of distant metastasis and poorest overall survival among breast cancer subtypes. In a phase II study, adagloxad simolenin (AdaSim), a synthetic Globo H conjugate vaccine administered with adjuvant OBI-821, was shown to induce IgM and IgG anti-Globo H humoral responses in patients with metastatic breast cancer overexpressing the glycosphingolipid Globo H. GLORIA is an ongoing phase III, randomized, open-label clinical trial to evaluate the safety and efficacy of AdaSim and the quality of life (QoL) of patients receiving AdaSim plus standard of care (SOC) versus SOC alone in high-risk, early-stage TNBC. The primary end point is invasive progression-free survival; secondary end points include overall survival, QoL, breast cancer-free interval, distant disease-free survival, safety, and tolerability.

Quantitative DCE-MRI prediction of breast cancer recurrence following neoadjuvant chemotherapy: a preliminary study

INTRODUCTION

Breast cancer patients treated with neoadjuvant chemotherapy (NACT) are at risk of recurrence depending on clinicopathological characteristics. This preliminary study aimed to investigate the predictive performances of quantitative dynamic contrast-enhanced (DCE) MRI parameters, alone and in combination with clinicopathological variables, for prediction of recurrence in patients treated with NACT.

METHODS

Forty-seven patients underwent pre- and post-NACT MRI exams including high spatiotemporal resolution DCE-MRI. The Shutter-Speed model was employed to perform pharmacokinetic analysis of the DCE-MRI data and estimate the Ktrans, ve, kep, and τi parameters. Univariable logistic regression was used to assess predictive accuracy for recurrence for each MRI metric, while Firth logistic regression was used to evaluate predictive performances for models with multi-clinicopathological variables and in combination with a single MRI metric or the first principal components of all MRI metrics.

RESULTS

Pre- and post-NACT DCE-MRI parameters performed better than tumor size measurement in prediction of recurrence, whether alone or in combination with clinicopathological variables. Combining post-NACT Ktrans with residual cancer burden and age showed the best improvement in predictive performance with ROC AUC = 0.965.

CONCLUSION

Accurate prediction of recurrence pre- and/or post-NACT through integration of imaging markers and clinicopathological variables may help improve clinical decision making in adjusting NACT and/or adjuvant treatment regimens to reduce the risk of recurrence and improve survival outcome.

Advances in Biomarkers and Endogenous Regulation of Breast Cancer Stem Cells

Breast cancer is one of the most common cancers. Even if breast cancer patients initially respond to treatment, developed resistance can lead to a poor prognosis. Cancer stem cells (CSCs) are a group of undifferentiated cells with self-renewal and multipotent differentiation characteristics. Existing evidence has shown that CSCs are one of the determinants that contribute to the heterogeneity of primary tumors. The emergence of CSCs causes tumor recurrence, metastasis, and therapeutic resistance. Previous studies indicated that different stemness-associated surface markers can identify other breast cancer stem cell (BCSC) subpopulations. Deciphering the critical signaling networks that are involved in the induction and maintenance of stemness is essential to develop novel BCSC-targeting strategies. In this review, we reviewed the biomarkers of BCSCs, critical regulators of BCSCs, and the signaling networks that regulate the stemness of BCSCs.

Dynamic characterization of breast cancer response to neoadjuvant therapy using biophysical metrics of spatial proliferation

Current tools to assess breast cancer response to neoadjuvant chemotherapy cannot reliably predict disease eradication, which if possible, could allow early cessation of therapy. In this work, we assessed the ability of an image data-driven mathematical modeling approach for dynamic characterization of breast cancer response to neoadjuvant therapy. We retrospectively analyzed patients enrolled in the I-SPY 2 TRIAL at the Atrium Health Wake Forest Baptist Comprehensive Cancer Center. Patients enrolled on the study received four MR imaging examinations during neoadjuvant therapy with acquisitions at baseline (T₀), 3-weeks/early-treatment (T₁), 12-weeks/mid-treatment (T₂), and completion of therapy prior to surgery (T₃). We use a biophysical mathematical model of tumor growth to generate spatial estimates of tumor proliferation to characterize the dynamics of treatment response. Using histogram summary metrics to quantify estimated tumor proliferation maps, we found strong correlation of mathematical model-estimated tumor proliferation with residual cancer burden, with Pearson correlation coefficients ranging from 0.88 and 0.97 between T₀ and T₂, representing a significant improvement from conventional assessment methods of change in mean apparent diffusion coefficient and functional tumor volume. This data shows the significant promise of imaging-based biophysical mathematical modeling methods for dynamic characterization of patient-specific response to neoadjuvant therapy with correlation to residual disease outcomes.

Triple-Negative Breast Cancer: A Review of Current Curative Intent Therapies

Breast cancer is the most commonly diagnosed malignancy in women, with triple-negative breast cancer (TNBC) accounting for 10–20% of cases. Historically, fewer treatment options have existed for this subtype of breast cancer, with cytotoxic chemotherapy playing a predominant role. This article aims to review the current treatment paradigm for curative-intent TNBC, while also reviewing potential future developments in this landscape. In addition to chemotherapy, recent advances in the understanding of the molecular biology of TNBC have led to promising new studies of targeted and immune checkpoint inhibitor therapies in the curative-intent setting. The appropriate selection of TNBC patient subgroups with a higher likelihood of benefit from treatment is critical to identify the best treatment approach.

Evolving Evidence for the Optimization of Neoadjuvant Therapy in Triple-Negative Breast Cancer

Representing 15% to 20% of all invasive breast cancers, adjuvant systemic treatment for early-stage, high-risk triple-negative breast cancer (TNBC) is preferentially done in the neoadjuvant setting based on a chemotherapy backbone of anthracyclines and taxanes. Pathological complete response to neoadjuvant treatment constitutes the main objective, regarding its correlation with oncological outcomes. The optimal neoadjuvant regimen to achieve the highest rates of pathological complete response is still under investigation, with the increasing knowledge on the molecular pathways, genomic sequencing, and immunological profile of TNBC allowing for the development of a wide array of new therapeutic options. This review aims to summarize the current evidence and ongoing clinical trials of new therapeutic options for the neoadjuvant treatment of TNBC patients.

Recently approved treatment options for patients with metastatic triple-negative and HER2-neu-positive breast cancer

Breast cancer (BC) is the most common cancer affecting women worldwide. In 2021, the estimated number of new breast cancer cases was 281 550 and about 43 500 women died from metastatic breast cancer (mBC). For women aged 20-59 years, mBC remains the leading cause of cancer death and is, therefore, an important public health concern. Only 5% of women initially present with metastatic disease. Approximately 20% of patients presenting with local or locoregional disease progress to mBC despite adjuvant therapy. Inspite of all the medicosurgical advancements, the overall prognosis for patients diagnosed with mBC remains poor, with median overall survival of approximately 31 months, although this varies based on tumor biology. In recent years, there has been significant progress in developing immunotargeted therapies such as antihuman epidermal growth factor receptor 2 (anti-HER2) or check point inhibitors that confirmed to have dramatically improve the prognosis of mBC, a historically unfavorable disease subset. Even with the major progress that has been made in understanding the biology of BC, challenges such as resistance frequency to therapies, unknown efficacy, concerns for safety of drug combination and toxicities still remain high. Therefore, a new targeted and more selective treatment approaches are the need of the hour. In this review, we aim to outline the most recently approved medications in treatment of Her2-positive and triple-negative breast cancers.

I-SPY COVID adaptive platform trial for COVID-19 acute respiratory failure: rationale, design and operations

INTRODUCTION

The COVID-19 pandemic brought an urgent need to discover novel effective therapeutics for patients hospitalised with severe COVID-19. The Investigation of Serial studies to Predict Your Therapeutic Response with Imaging And moLecular Analysis (ISPY COVID-19 trial) was designed and implemented in early 2020 to evaluate investigational agents rapidly and simultaneously on a phase 2 adaptive platform. This manuscript outlines the design, rationale, implementation and challenges of the ISPY COVID-19 trial during the first phase of trial activity from April 2020 until December 2021.

METHODS AND ANALYSIS

The ISPY COVID-19 Trial is a multicentre open-label phase 2 platform trial in the USA designed to evaluate therapeutics that may have a large effect on improving outcomes from severe COVID-19. The ISPY COVID-19 Trial network includes academic and community hospitals with significant geographical diversity across the country. Enrolled patients are randomised to receive one of up to four investigational agents or a control and are evaluated for a family of two primary outcomes-time to recovery and mortality. The statistical design uses a Bayesian model with 'stopping' and 'graduation' criteria designed to efficiently discard ineffective therapies and graduate promising agents for definitive efficacy trials. Each investigational agent arm enrols to a maximum of 125 patients per arm and is compared with concurrent controls. As of December 2021, 11 investigational agent arms had been activated, and 8 arms were complete. Enrolment and adaptation of the trial design are ongoing.

ETHICS AND DISSEMINATION

ISPY COVID-19 operates under a central institutional review board via Wake Forest School of Medicine IRB00066805. Data generated from this trial will be reported in peer-reviewed medical journals.

TRIAL REGISTRATION NUMBER

NCT04488081.

Radiation therapy for triple-negative breast cancer: emerging role of microRNAs as biomarkers and radiosensitivity modifiers. A systematic review

PURPOSE

Radiation therapy (RT) for triple-negative breast cancer (TNBC) treatment is currently delivered in the adjuvant setting and is under investigation as a booster of neoadjuvant treatments. However, TNBC radioresistance remains an obstacle, so new biomarkers are needed to select patients for any integration of RT in the TNBC therapy sequence. MicroRNAs (miRs) are important regulators of gene expression, involved in cancer response to ionizing radiation (IR) and assessable by tumor tissue or liquid biopsy. This systematic review aimed to evaluate the relationships between miRs and response to radiation in TNBC, as well as their potential predictive and prognostic values.

METHODS

A thorough review of studies related to miRs and RT in TNBC was performed on PubMed, EMBASE, and Web of Science. We searched for original English articles that involved dysregulation of miRs in response to IR on TNBC-related preclinical and clinical studies. After a rigorous selection, 44 studies were chosen for further analysis.

RESULTS

Thirty-five miRs were identified to be TNBC related, out of which 21 were downregulated, 13 upregulated, and 2 had a double-side expression in this cancer. Expression modulation of many of these miRs is radiosensitizing, among which miR-7, -27a, -34a, -122, and let-7 are most studied, still only in experimental models. The miRs reported as most influencing/reflecting TNBC response to IR are miR-7, -27a, -155, -205, -211, and -221, whereas miR-21, -33a, -139-5p, and -210 are associated with TNBC patient outcome after RT.

CONCLUSION

miRs are emerging biomarkers and radiosensitizers in TNBC, worth further investigation. Dynamic assessment of circulating miRs could improve monitoring and TNBC RT efficacy, which are of particular interest in the neoadjuvant and the high-risk patients' settings.

BRE12-158: A Postneoadjuvant, Randomized Phase II Trial of Personalized Therapy Versus Treatment of Physician's Choice for Patients With Residual Triple-Negative Breast Cancer

PURPOSE

Patients with triple-negative breast cancer (TNBC) with residual disease after neoadjuvant chemotherapy (NAC) have high risk of recurrence with prior data suggesting improved outcomes with capecitabine. Targeted agents have demonstrated activity across multiple cancer types. BRE12-158 was a phase II, multicenter trial that randomly allocated patients with TNBC with residual disease after NAC to genomically directed therapy versus treatment of physician choice (TPC).

PATIENTS AND METHODS

From March 2014 to December 2018, 193 patients were enrolled. Residual tumors were sequenced using a next-generation sequencing test. A molecular tumor board adjudicated all results. Patients were randomly allocated to four cycles of genomically directed therapy (arm A) versus TPC (arm B). Patients without a target were assigned to arm B. Primary end point was 2-year disease-free survival (DFS) among randomly assigned patients. Secondary/exploratory end points included distant disease-free survival, overall survival, toxicity assessment, time-based evolution of therapy, and drug-specific outcomes.

RESULTS

One hundred ninety-three patients were randomly allocated or were assigned to arm B. The estimated 2-year DFS for the randomized population only was 56.6% (95% CI, 0.45 to 0.70) for arm A versus 62.4% (95% CI, 0.52 to 0.75) for arm B. No difference was seen in DFS, distant disease-free survival, or overall survival for the entire or randomized populations. There was increased uptake of capecitabine for TPC over time. Patients randomly allocated later had less distant recurrences. Circulating tumor DNA status remained a significant predictor of outcome with some patients demonstrating clearance with postneoadjuvant therapy.

CONCLUSION

Genomically directed therapy was not superior to TPC for patients with residual TNBC after NAC. Capecitabine should remain the standard of care; however, the activity of other agents in this setting provides rationale for testing optimal combinations to improve outcomes. Circulating tumor DNA should be considered a standard covariate for trials in this setting.

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.

Harnessing DNA Repair Defects to Augment Immune-Based Therapies in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) has poor prognosis with limited treatment options, with little therapeutic progress made during the past several decades. DNA damage response (DDR) associated therapies, including radiation and inhibitors of DDR, demonstrate potential efficacy against TNBC, especially under the guidance of genomic subtype-directed treatment. The tumor immune microenvironment also contributes greatly to TNBC malignancy and response to conventional and targeted therapies. Immunotherapy represents a developing trend in targeted therapies directed against TNBC and strategies combining immunotherapy and modulators of the DDR pathways are being pursued. There is increasing understanding of the potential interplay between DDR pathways and immune-associated signaling. As such, the question of how we treat TNBC regarding novel immuno-molecular strategies is continually evolving. In this review, we explore the current and upcoming treatment options of TNBC in the context of DNA repair mechanisms and immune-based therapies, with a focus on implications of recent genomic analyses and clinical trial findings.

Toward the Next Generation of High-Grade Glioma Clinical Trials in the Era of Precision Medicine

ABSTRACT

In the era of precision medicine, there is a desire to harness our improved understanding of genomic and molecular underpinnings of gliomas to develop therapies that can be tailored to individual patients and tumors. With the rapid development of novel therapies, there has been a growing need to develop smart clinical trials that are designed to efficiently test promising agents, identify therapies likely to benefit patients, and discard ineffective therapies. We review clinical trial design in gliomas and developments designed to address the unique challenges of precision medicine. To provide an overview of this topic, we examine considerations for endpoints and response assessment, biomarkers, and novel clinical trial designs such as adaptive platform trials in the testing of new therapies for glioma patients.

Neoadjuvant approach as a platform for treatment personalization: focus on HER2-positive and triple-negative breast cancer

The neoadjuvant setting provides unquestionable clinical benefits for high-risk breast cancer (BC) patients, mainly in terms of expansion of locoregional treatment options and prognostic stratification. Additionally, it is also emerging as a strategical tool in the research field. In the present review, by focusing on HER2-positive and triple-negative subtypes, we examined the role of the neoadjuvant setting as a research platform to facilitate and rationalize the placement of escalation strategies, promote the adoption of biomarker-driven approaches for the investigation of de-escalated treatments, and foster the conduction of comprehensive translational analyses, thus ultimately aiming at pursuing treatment personalization. The solid prognostic role of pathologic complete response after neoadjuvant therapy, and its use as a surrogate endpoint to accelerate the drug approval process were discussed. In this context, available data on escalated treatment strategies capable of enhancing pathologic complete response (pCR) rate or improving prognosis of patients with residual disease (RD) after neoadjuvant treatment, were comprehensively reviewed. We also summarized evidence regarding the possibility of obtaining pCR with de-escalated strategies, with particular emphasis on the role of biomarker-driven approaches for patient selection. Pitfalls of the dichotomy of pCR/RD were also deepened, and data on alternative/complementary biomarkers with a possible clinical relevance in this regard were reviewed.