Michael J. Eblan

Clinical Translation of Nanomedicine.

1. Introduction Nanomedicine, the application of nanotechnology to health and medicine, is a relatively new area of interdisciplinary science. The field involves a wide range of scientific disciplines, including physics, chemistry, engineering, biology, and medical science. The term nanomedicine can be traced back to the late 1990s and first appeared in research publications in the year 2000.1 Despite the wide adoption of the term nanomedicine, its definition varies among experts in this area.2 Some define nanomedicine broadly as any science that involves matters that are nanoscale. For example, the European Science Foundation in 2004 defined nanomedicine as “the science and technology of diagnosing, treating, and preventing disease and traumatic injury, of relieving pain, and of preserving and improving human health, using molecular tools and molecular knowledge of the human body”.2 While such a broad definition is all encompassing, it can be confusing. For example, such a definition would include traditional scientific fields such as molecular biology as part of nanomedicine, because molecules such as nucleic acids and proteins are also nanoscale materials. However, scientists have been studying these molecules decades before the term nanomedicine was even coined, and their research generally does not take advantage of unique properties that only exist for nanomaterials. A narrower definition of nanomedcine is the application of nanoscale material in medicine that takes advantage of the nanomaterials unique properties.1 This Review will adopt this narrower definition in our discussion of the clinical translation of nanomedicine. Nanomedicine has made a rapid and broad impact on healthcare. Despite being only several decades old, research in nanomedicine has already led to the development of a wide range of products including therapeutics, diagnostic imaging agents, in vitro diagnostics, and medical devices. There are more than 200 nanomedicine products that have been either approved or are under clinical investigation.3 On the other hand, successful clinical translation is a challenging process. It requires extensive preclinical research, carefully selected clinical indication, proper design of clinical trials, and the successful completion of these trials. Mistakes in clinical translation can be unforgiving. Unlike preclinical research where there are many if not unlimited chances of generating a successful study, a single failed clinical trial can doom a drugs translation. Hay et al. recently showed that the eventual success rate of approval for therapeutics entering phase I trial is only about 10%.4 Because of this sobering statistic, it is important for translational researchers to fully understand the clinical translation process and to develop a successful translation strategy in the early stages of research. As compared to diagnostics and devices, clinical translation of therapeutics is arguably the most challenging. The typical clinical translation path for a new drug starts with investigators generating robust preclinical data to demonstrate the safety and efficacy of the new drug to enable an investigational new drug (IND) application with the Food and Drug Administration (FDA).5 Once the FDA has approved the IND, the therapeutic will be evaluated in a first-in-human or a phase I clinical trial. The goal of such a study is to determine the safety profile and pharmacology of the drug. It will result in a dose and schedule for further clinical investigation, or the recommended phase 2 dose (RP2D). The typical phase I trial design used a “3 + 3” cohort expansion design.6 This design assumes toxicity increases with dose, and it aims to determine the dose level that has less than 1/3 chance of a dose-limiting toxicity (DLT).7 In general, such a trial starts with a low drug dose. If none of the three patients receiving this dose experiences a DLT, another three patients will be treated at the next higher dose level. If one of the three patients experiences a DLT, then three more patients will be treated at the same dose level. Dose escalation continues until two patients among a cohort of three to six patients experience DLT. The RP2D is the dose level just below this level. Dose escalation typically follows a modified Fibonacci sequence where dose increments decrease as the tested dose increases. Other types of phase I designs include the accelerated titration designs, Bayesian models-based designs, and many others.7 Each design has advantages and disadvantages, and investigators have to choose the design that best fits the therapeutic. The goal of a phase II clinical trial is to examine the effectiveness of a drug or treatment. Secondarily, it will acquire more data on the toxicity and tolerability of the therapeutic. Therapeutics will progress to phase III clinical investigation only if they can demonstrate efficacy in phase II. The designs of phase II trials are either single-arm trials or randomized trials.8 Single-arm trials are cheaper, require fewer patients, and are typically easier to accrue. However, the outcome is less reliable as there is no comparison/control arm, and data are more susceptible to bias. Data from randomized phase II trials are more predictive of phase III results. However, it requires more patients and can be more difficult to accrue. Randomized phase II trials do not replace phase III investigations. Although they are randomized, patients are generally stratified on the basis of very few variables, such as age, sex, and disease status in phase II trials to keep the accrual goal low. Randomized phase III trials stratify patients on the basis of a large number of variables, which leads to less bias and more robust data. Because of the stratifications, the sample size required for phase III investigation is much higher than that of randomized phase II trials. The goal of randomized phase III trials is to demonstrate that the investigational treatment is more effective than the “gold standard” treatment. In general, phase III data are required for FDA approval. However, in select cases where there are robust data and unmet clinical needs, conditional approval can be granted on the basis of phase II data or interim phase III data. The FDA has a range of programs to speed up the approval process, including accelerated approvals and the recent “break through therapy” designation.9 There is a “short-cut” to FDA approval for agents that are based on already approved drugs. This pathway is called the 505(b)(2) pathway. The process of timeline for 505(b)(2) is much more abbreviated when compared to a typical approval process. For nanomedicine, this pathway will typically require that the exact nanoparticle platform is already approved with another agent and the drug being delivered by the nanoparticle is also approved. Past examples of this include the approval of liposomal bupivacaine with the DepoFoam liposome platform. The FDA was granted the authority to regulate medical devices in 1976.10 The approval process for medical devices is very different from that of drugs. First, for devices that predate May 28, 1976, these devices can remain on the market without needing approval. For the devices entering the market after that date, they are classified into different classes (I, II, and III) on the basis of their risks (Table 1).10 Class I devices are of low risk and are generally exempt from premarket notification (referred to as 510(k)) and may even be exempt from compliance with the good manufacturing practice requirement. Class II devices typically will require 510(k) submission before marketing. Class III devices are subject to the most stringent regulatory controls. Their approval will require a premarket approval (PMA) application. The 510(k) pathway is for devices that can be compared to existing, legally marketed “predicate” devices. The new device needs to be shown to be at least as safe and as effective as the “predicate” device. For devices that do not have a “predicate” device with which to compare, they are classified as class III and will need PMA. PMA needs to include scientific evidence that the device is safe and effective for its intended use. Unlike therapeutics where approvals generally require large randomized studies, scientific evidence for devices can include randomized controlled trials, single-arm studies, well-documented case series, and reports of significant human experience. For new devices that pose significant potential risks, an investigational device exemption (IDE) application is required prior to clinical investigation. Overall, the approval process is much simpler for devices than for therapeutics. Table 1 Summary of the FDA Device Regulation Processa In this Review, we will examine preclinical evidence, chosen clinical path to translation, and clinical data of clinically approved nanomedicine products. We will also discuss the clinical data on nanomedicines that are under clinical investigation or failed clinical translation. Each of these clinical nanomedicine products has a unique clinical translation story. By examining this body of evidence, we aim to formulate important concepts that are keys to nanomedicines clinical translation and to identify challenges. Such concepts will facilitate the translation of future nanomedicine products.

Cardiac toxicity after radiotherapy for stage III non-small-cell lung cancer: Pooled analysis of dose-escalation trials delivering 70 to 90 Gy

Purpose The significance of radiotherapy (RT) -associated cardiac injury for stage III non-small-cell lung cancer (NSCLC) is unclear, but higher heart doses were associated with worse overall survival in the Radiation Therapy Oncology Group (RTOG) 0617 study. We assessed the impact of heart dose in patients treated at our institution on several prospective dose-escalation trials. Patients and Methods From 1996 to 2009, 127 patients with stage III NSCLC (Eastern Cooperative Oncology Group performance status, 0 to 1) received dose-escalated RT to 70 to 90 Gy (median, 74 Gy) in six trials. RT plans and cardiac doses were reviewed. Records were reviewed for the primary end point: symptomatic cardiac events (symptomatic pericardial effusion, acute coronary syndrome, pericarditis, significant arrhythmia, and heart failure). Cardiac risk was assessed by noting baseline coronary artery disease and calculating the WHO/International Society of Hypertension score. Competing risks analysis was used. Results In all, 112 patients were analyzed. Median follow-up for surviving patients was 8.8 years. Twenty-six patients (23%) had one or more events at a median of 26 months to first event (effusion [n = 7], myocardial infarction [n = 5], unstable angina [n = 3], pericarditis [n = 2], arrhythmia [n = 12], and heart failure [n = 1]). Heart doses (eg, heart mean dose; hazard ratio, 1.03/Gy; P = .002,), coronary artery disease ( P < .001), and WHO/International Society of Hypertension score ( P = .04) were associated with events on univariable analysis. Heart doses remained significant on multivariable analysis that accounted for baseline risk. Two-year competing risk-adjusted event rates for patients with heart mean dose < 10 Gy, 10 to 20 Gy, or ≥ 20 Gy were 4%, 7%, and 21%, respectively. Heart doses were not associated with overall survival. Conclusion Cardiac events were relatively common after high-dose thoracic RT and were independently associated with both heart dose and baseline cardiac risk. RT-associated cardiac toxicity after treatment of stage III NSCLC may occur earlier than historically understood, and heart doses should be minimized.

Antigen-capturing nanoparticles improve the abscopal effect and cancer immunotherapy

Immunotherapy holds tremendous promise for improving cancer treatment1. Administering radiotherapy with immunotherapy has been shown to improve immune responses and can elicit an “abscopal effect”2. Unfortunately, response rates for this strategy remain low3. Herein, we report an improved cancer immunotherapy approach that utilizes antigen-capturing nanoparticles (AC-NPs). We engineered several AC-NPs formulations and demonstrated that the set of protein antigens captured by each AC-NP formulation is dependent upon NP surface properties. We showed that AC-NPs deliver tumor specific proteins to antigen-presenting cells and significantly improve the efficacy of αPD-1 treatment using the B16F10 melanoma model, generating up to 20% cure rate as compared to 0% without AC-NPs. Mechanistic studies revealed that AC-NPs induced an expansion of CD8+ cytotoxic T cells and increased both CD4+/Treg and CD8+/Treg ratios. Our work presents a novel strategy for improving cancer immunotherapy with nanotechnology.

Heart dosimetric analysis of three types of cardiac toxicity in patients treated on dose-escalation trials for Stage III non-small-cell lung cancer

BACKGROUND AND PURPOSE To assess associations between radiation dose/volume parameters for cardiac subvolumes and different types of cardiac events in patients treated on radiation dose-escalation trials. MATERIAL AND METHODS Patients with Stage III non-small-cell lung cancer received dose-escalated radiation (median 74 Gy) using 3D-conformal radiotherapy on six prospective trials from 1996 to 2009. Volumes analyzed included whole heart, left ventricle (LV), right atrium (RA), and left atrium (LA). Cardiac events were divided into three categories: pericardial (symptomatic effusion and pericarditis), ischemia (myocardial infarction and unstable angina), and arrhythmia. Univariable competing risks analysis was used. RESULTS 112 patients were analyzed, with median follow-up 8.8 years for surviving patients. Nine patients had pericardial, seven patients had ischemic, and 12 patients had arrhythmic events. Pericardial events were correlated with whole heart, RA, and LA dose (eg, heart-V30 [p=0.024], RA-V30 [p=0.013], and LA-V30 [p=0.001]), but not LV dose. Ischemic events were correlated with LV and whole heart dose (eg, LV-V30 [p=0.012], heart-V30 [p=0.048]). Arrhythmic events showed borderline significant associations with RA, LA, and whole heart dose (eg, RA-V30 [p=0.082], LA-V30 [p=0.076], heart-V30 [p=0.051]). Cardiac events were associated with decreased survival on univariable analysis (p=0.008, HR 2.09), but only disease progression predicted for decreased survival on multivariable analysis. CONCLUSIONS Cardiac events were heterogeneous and associated with distinct heart subvolume doses. These data support the hypothesis of distinct etiologies for different types of radiation-associated cardiotoxicity.

Multivalent binding and biomimetic cell rolling improves the sensitivity and specificity of circulating tumor cell capture

Purpose: We aimed to examine the effects of multivalent binding and biomimetic cell rolling on the sensitivity and specificity of circulating tumor cell (CTC) capture. We also investigated the clinical significance of CTCs and their kinetic profiles in patients with cancer undergoing radiotherapy treatment. Experimental Design: Patients with histologically confirmed primary carcinoma undergoing radiotherapy, with or without chemotherapy, were eligible for enrollment. Peripheral blood was collected prospectively at up to five time points, including before radiotherapy, at the first week, mid-point and final week of treatment, as well as 4 to 12 weeks after completion of radiotherapy. CTC capture was accomplished using a nanotechnology-based assay (CapioCyte) functionalized with aEpCAM, aHER-2, and aEGFR. Results: CapioCyte was able to detect CTCs in all 24 cancer patients enrolled. Multivalent binding via poly(amidoamine) dendrimers further improved capture sensitivity. We also showed that cell rolling effect can improve CTC capture specificity (% of captured cells that are CK+/CD45−/DAPI+) up to 38%. Among the 18 patients with sequential CTC measurements, the median CTC decreased from 113 CTCs/mL before radiotherapy to 32 CTCs/mL at completion of radiotherapy (P = 0.001). CTCs declined throughout radiotherapy in patients with complete clinical and/or radiographic response, in contrast with an elevation in CTCs at mid or post-radiotherapy in the two patients with known pathologic residual disease. Conclusions: Our study demonstrated that multivalent binding and cell rolling can improve the sensitivity and specificity of CTC capture compared with multivalent binding alone, allowing reliable monitoring of CTC changes during and after treatment. Clin Cancer Res; 24(11); 2539–47. ©2018 AACR.

Clinical characteristics associated with racial disparities in endometrial cancer outcomes: A surveillance, epidemiology and end results analysis

OBJECTIVES Racial disparities exist for endometrial cancer. We examined patterns of care and factors associated with poor outcomes for Black women with endometrial cancer. METHODS We studied 110,826 endometrial cancer patients diagnosed between 1980 and 2008 with minimum 5years follow-up in the Surveillance, Epidemiology, and End Results database. Trends over time in sociodemographics, disease characteristics and treatment factors were analyzed over four eras: 1980-1989, 1990-1999, 2000-2004, 2005-2008. Using sequential Cox proportional hazards and Fine-Gray competing risk models we determined the association between potential explanatory variables and racial disparities in all-cause mortality (ACM) and cancer-specific mortality (CSM), respectively. RESULTS Clinical characteristics of Black and White women were relatively constant over time. The unadjusted hazard ratio (HR) among Black women for ACM and CSM were 1.91 (95% CI 1.86-1.97) and 2.35 (95% CI 2.26-2.43), respectively. Adjustment for sociodemographics, disease presentation and surgery decreased the ACM HR to 1.29 (95% CI 1.24-1.34) and CSM HR to 1.18 (95% CI 1.11-1.26) without further decrease from controlling for radiotherapy. Black women were less likely to undergo operative management even when prescribed. Total and radical hysterectomy, and vaginal brachytherapy (VBT) were associated with improved ACM and CSM. Combination VBT and external beam radiotherapy was associated with improved ACM. CONCLUSION Racial disparities in endometrial cancer survival are predominantly attributable to increased advanced stage, high-grade and aggressive histologic subtype tumors and differential use of surgery in Black women. Intensified surgical and radiation treatment is associated with improved survival, raising questions about treatment adaptations that may potentially reduce survival disparities.

Abstract 3954: Prospective evaluation of circulating tumor cells (CTCs) in head and neck cancer patients receiving definitive radiotherapy with a nanotechnology based system

Background: Circulating tumor cells (CTCs) are an important biomarker in cancer. There has been substantial interest in utilizing CTCs to enable personalized treatment. However, there is limited data on CTCs in patients with head and neck cancers (HNC) where there is growing data that curative treatment needs to be risk-based. The purpose of this prospective, correlative study is to investigate the clinical significance of CTCs, as measured by a highly sensitive CTC capture technology UiChip, in HNC patients undergoing definitive treatment. Methods: HNC patients (M0) undergoing definitive treatment (radiation+/- chemotherapy) were enrolled. Peripheral blood was collected prior to starting RT, at the first week, mid-point, final week of treatment, and every 4 to 12 weeks after completion. Quantification of CTCs was conducted using UiChip. The primary endpoint was change in CTCs pre- and post- RT. Results: 35 patients are included in this analysis (median age 58, 34% non-smokers, 69% HPV/p16 positive, and 17% node (-)) and 90% received chemotherapy. CTCs were detected in all patients pre-RT (100%). There was no association between pre-RT CTC level and tumor or nodal stage. Median CTCs significantly decreased from 71 CTCs/mL (range, 7-849) before RT to 32 (2-209) at completion of RT and 27 (2-78) at 4 to 12 weeks post-treatment. Ten patients had persistent disease and/or distant metastasis at a median follow-up of 10.6 months (range, 3.7-17). CTCs declined throughout treatment in patients with complete clinical and/or radiographic responses, in contrast to an elevation in CTCs at mid or post-RT in the 7 patients with pathologic residual disease/distant failures. Conclusions: We demonstrated that the novel UiChip can capture CTCs in a diverse population of head and neck cancer patients. Our pilot data suggest that individual patient CTC changes during and after treatment may be a predictive biomarker for radiotherapy response and clinical outcomes. Citation Format: Joseph M. Caster, Michael J. Eblan, Kyle Wang, Ja Hye Myung, Bhishamjit Chera, Seungpyo Hong, Andrew Z. Wang. Prospective evaluation of circulating tumor cells (CTCs) in head and neck cancer patients receiving definitive radiotherapy with a nanotechnology based system. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3954.

Abstract 1589: Investigation of circulating tumor cells from head and neck cancer patients undergoing radiation therapy: A pilot study

Background: Circulating tumor cell (CTC) enumeration provides prognostic information in patients with metastatic breast, prostate, colorectal and lung cancer. However, the effect of radiation therapy (RT) on CTCs in patients with primary head and neck malignancies has not been explored. The purpose of this exploratory study is to examine how CTCs, as measured by a novel cell capture technique, respond to RT in patients with head and neck cancer. Methods: A total of a 16 patients undergoing definitive radiation for primary, non-metastatic head and neck cancer were enrolled in this pilot study. Peripheral blood was collected at 5 time points, including at baseline prior to starting RT, at the first week, mid-point and final week during treatment, and at least 4 weeks after completion of RT. Quantification of CTCs was performed with a novel device that used a biomimetic combination of three cancer cell-specific antibodies (aEpCAM, aHer-2, and aEGFR) immobilized through poly(amidoamine) dendrimers and E-selectin, which respectively induce concurrent stationary binding and dynamic cell rolling of the tumor cells. Results: CTCs were successfully detected in all patients before the start of radiation (100%), including patients with HPV/p16 positive or negative tumors. The novel CTC device yielded up to a 4-fold enhancement in capture efficiency relative to the aEpCAM-functionalized surface. The average CTC count in patients before RT was 386 CTCs per mL (range, 18 to 1134 CTCs per mL), significantly higher than the average CTC count of 90 CTCs per mL after the completion of radiation (range, 5 to 393 CTCs per mL). All but one patient demonstrated a decrease in measured CTCs at sequential time points during the course of RT. The patient with an elevation in CTCs during RT had residual metastatic carcinoma detected after left level II selective cervical neck dissection, which was performed 12 weeks post-RT due to persistent radiographic lymph nodal abnormality. At a median follow-up of 1.5 months, no patient has had a local or distant failure. Conclusions: We have demonstrated that our novel technology can affectively capture CTCs in head and neck cancer patients. Importantly, our pilot data shows CTCs decrease over the course of RT, suggesting CTCs can be a predicative biomarker for radiotherapy response. Further study will investigate associations between CTC kinetics and clinical outcomes. Citation Format: Michael J. Eblan, Ja Hye Myung, Joseph M. Caster, Bhishamjit S. Chera, Seungpyo Hong, Andrew Z. Wang. Investigation of circulating tumor cells from head and neck cancer patients undergoing radiation therapy: A pilot study. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1589. doi:10.1158/1538-7445.AM2015-1589