Systematic Assessment of Small RNA Profiling in Human Extracellular Vesicles.

MOTIVATION: Extracellular vesicles (EVs) are produced and released by most cells and are now recognized to play a role in intercellular communication through the delivery of molecular cargo, including proteins, lipids, and RNA. Small RNA sequencing (small RNA-seq) has been widely used to characterize the small RNA content in EVs. However, there is a lack of a systematic assessment of the quality, technical biases, RNA composition, and RNA biotypes enrichment for small RNA profiling of EVs across cell types, biofluids, and conditions. METHODS: We collected and reanalyzed small RNA-seq datasets for 2756 samples from 83 studies involving 55 with EVs only and 28 with both EVs and matched donor cells. We assessed their quality by the total number of reads after adapter trimming, the overall alignment rate to the host and non-host genomes, and the proportional abundance of total small RNA and specific biotypes, such as miRNA, tRNA, rRNA, and Y RNA. RESULTS: We found that EV extraction methods varied in their reproducibility in isolating small RNAs, with effects on small RNA composition. Comparing proportional abundances of RNA biotypes between EVs and matched donor cells, we discovered that rRNA and tRNA fragments were relatively enriched, but miRNAs and snoRNA were depleted in EVs. Except for the export of eight miRNAs being context-independent, the selective release of most miRNAs into EVs was study-specific. CONCLUSION: This work guides quality control and the selection of EV isolation methods and enhances the interpretation of small RNA contents and preferential loading in EVs.

A Grant-Based Experiment to Train Clinical Investigators: The AACR/ASCO Methods in Clinical Cancer Research Workshop.

To address the need for clinical investigators in oncology, American Association for Cancer Research (AACR) and American Society for Clinical Oncology (ASCO) established the Methods in Clinical Cancer Research Workshop (MCCRW). The workshop's objectives were to: (i) provide training in the methods, design, and conduct of clinical trials; (ii) ensure that clinical trials met federal and international ethical guidelines; (iii) evaluate the effectiveness of the workshop; and (iv) create networking opportunities for young investigators with mentoring senior faculty. Educational methods included: (i) didactic lectures, (ii) Small Group Discussion Sessions, (iii) Protocol Development Groups, and (iv) one-on-one mentoring. Learning focused on the development of an Institutional Review Board (IRB)-ready protocol, which was submitted on the last day of the workshop. Evaluation methods included: (i) pre- and postworkshop tests, (ii) students' workshop evaluations, (iii) faculty's ratings of protocol development, (iv) students' productivity in clinical research after the workshop, and (v) an independent assessment of the workshop. From 1996 to 2014, 1,932 students from diverse backgrounds attended the workshop. There was a significant improvement in the students' level of knowledge from the pre- to the postworkshop exams (P < 0.001). Across the classes, student evaluations were very favorable. At the end of the workshop, faculty rated 92% to 100% of the students' protocols as ready for IRB submission. Intermediate and long-term follow-ups indicated that more than 92% of students were actively involved in patient-related research, and 66% had implemented five or more protocols. This NCI-sponsored MCCRW has had a major impact on the training of clinicians in their ability to design and implement clinical trials in cancer research.

The CoVID-TE risk assessment model for venous thromboembolism in hospitalized patients with cancer and COVID-19.

BACKGROUND: Hospitalized patients with COVID-19 have increased risks of venous (VTE) and arterial thromboembolism (ATE). Active cancer diagnosis and treatment are well-known risk factors; however, a risk assessment model (RAM) for VTE in patients with both cancer and COVID-19 is lacking. OBJECTIVES: To assess the incidence of and risk factors for thrombosis in hospitalized patients with cancer and COVID-19. METHODS: Among patients with cancer in the COVID-19 and Cancer Consortium registry (CCC19) cohort study, we assessed the incidence of VTE and ATE within 90 days of COVID-19-associated hospitalization. A multivariable logistic regression model specifically for VTE was built using a priori determined clinical risk factors. A simplified RAM was derived and internally validated using bootstrap. RESULTS: From March 17, 2020 to November 30, 2020, 2804 hospitalized patients were analyzed. The incidence of VTE and ATE was 7.6% and 3.9%, respectively. The incidence of VTE, but not ATE, was higher in patients receiving recent anti-cancer therapy. A simplified RAM for VTE was derived and named CoVID-TE (Cancer subtype high to very-high risk by original Khorana score +1, VTE history +2, ICU admission +2, D-dimer elevation +1, recent systemic anti-cancer Therapy +1, and non-Hispanic Ethnicity +1). The RAM stratified patients into two cohorts (low-risk, 0-2 points, n = 1423 vs. high-risk, 3+ points, n = 1034) where VTE occurred in 4.1% low-risk and 11.3% high-risk patients (c statistic 0.67, 95% confidence interval 0.63-0.71). The RAM performed similarly well in subgroups of patients not on anticoagulant prior to admission and moderately ill patients not requiring direct ICU admission. CONCLUSIONS: Hospitalized patients with cancer and COVID-19 have elevated thrombotic risks. The CoVID-TE RAM for VTE prediction may help real-time data-driven decisions in this vulnerable population.

Quantitative Assessment of Learning Behaviors for Oncology Providers.

How health care providers select topics and activities for learning is key to meeting their needs. The goal of this study was to investigate how oncology providers identify knowledge gaps and choose learning activities. An online focus group within a larger longitudinal study was conducted between November 2015 and August 2016. Participants were chosen by convenience and stratified random sampling of diverse types of oncology providers. Providers were asked monthly to identify learning needs, explain how they identified those needs, and describe the learning activity they chose to meet those needs. Thirty-two oncology providers recorded 201 learning needs via online journal entries (mean 6 entries per person). Needs were associated with practice setting and professional role (p < .05). Colleague recommendation predicted learning needs for advanced practice providers (APPs) (p = .003). Patient cases drove > 50% of identified learning needs across groups. Learning activity preferences were associated with practice setting (p < .05). Choice of learning activity was associated with practice setting, professional role, and geographic location. Colleague recommendation was important for APPs (p = .025). Over 75% of learner responses identify convenience and content quality as important factors in choosing an activity. This study represents a quantitative assessment of learning behaviors for oncology providers and shows that identification of learning needs and activity selection differ by provider demographics. Limitations include small size and underrepresentation of some groups. Our findings should be confirmed with larger samples. Future research should focus on assessment of cohort versus individual needs and learning priorities.

Quantitative assessment of cell population diversity in single-cell landscapes.

Single-cell RNA sequencing (scRNA-seq) has become a powerful tool for the systematic investigation of cellular diversity. As a number of computational tools have been developed to identify and visualize cell populations within a single scRNA-seq dataset, there is a need for methods to quantitatively and statistically define proportional shifts in cell population structures across datasets, such as expansion or shrinkage or emergence or disappearance of cell populations. Here we present sc-UniFrac, a framework to statistically quantify compositional diversity in cell populations between single-cell transcriptome landscapes. sc-UniFrac enables sensitive and robust quantification in simulated and experimental datasets in terms of both population identity and quantity. We have demonstrated the utility of sc-UniFrac in multiple applications, including assessment of biological and technical replicates, classification of tissue phenotypes and regional specification, identification and definition of altered cell infiltrates in tumorigenesis, and benchmarking batch-correction tools. sc-UniFrac provides a framework for quantifying diversity or alterations in cell populations across conditions and has broad utility for gaining insight into tissue-level perturbations at the single-cell resolution.

Directed solutions to address differences in access to liver transplantation.

The United Network for Organ Sharing recently altered current liver allocation with the goal of decreasing Model for End-Stage Liver Disease (MELD) variance at transplant. Concerns over these and further planned revisions to policy include predicted decrease in total transplants, increased flying and logistical complexity, adverse impact on areas with poor quality health care, and minimal effect on high MELD donor service areas. To address these issues, we describe general approaches to equalize critical transplant metrics among regions and determine how they alter MELD variance at transplant and organ supply to underserved communities. We show an allocation system that increases minimum MELD for local allocation or preferentially directs organs into areas of need decreases MELD variance. Both models have minimal adverse effects on flying and total transplants, and do not disproportionately disadvantage already underserved communities. When combined together, these approaches decrease MELD variance by 28%, more than the recently adopted proposal. These models can be adapted for any measure of variance, can be combined with other proposals, and can be configured to automatically adjust to changes in disease incidence as is occurring with hepatitis C and nonalcoholic fatty liver disease.

Institute of Medicine Measures of Social and Behavioral Determinants of Health: A Feasibility Study.

INTRODUCTION: Social and behavioral factors are known to affect health but are not routinely assessed in medical practice. To date, no studies have assessed a parsimonious panel of measures of social and behavioral determinants of health (SBDs). This study evaluated the panel of SBD measures recommended by the Institute of Medicine and examined the effect of question order. METHODS: Adults, aged ≥18 years, were recruited using ResearchMatch.org for this randomized, parallel design study conducted in 2015 (data analyzed in 2015-2016). Three versions of the SBD measures, sharing the same items but in different orders of presentation (Versions 1-3), were developed. Randomized to six groups, participants completed each version at least 1 week apart (Weeks 1-3). Version order was counterbalanced across each administration and randomization was stratified by gender, race, and age. Main outcomes were effect of question order, completion time, and non-response rates. RESULTS: Of 781 participants, 624 (80%) completed the Week 1 questionnaire; median completion time for answering all SBD questions was 5 minutes, 583/624 participants answered all items, and no statistically significant differences associated with question order were observed when comparing responses across all versions. No significant differences in responses within assignment groups over time were found, with the exception of the stress measure for Group 5 (p=0.036). CONCLUSION: Question order did not significantly impact participant responses. Time to complete the questionnaire was brief, and non-response rate was low. Findings support the feasibility of using the Institute of Medicine-recommended questionnaire to capture SBDs.

New tools for the quantitative assessment of prodrug delivery and neurotoxicity.

Systemic off-target toxicities, including neurotoxicity, are prevalent side effects in cancer patients treated with a number of otherwise highly efficacious anticancer drugs. In the current study, we have: (1) developed a new analytical metric for the in vivo preclinical assessment of systemic toxicities/neurotoxicity of new drugs and delivery systems; and (2) evaluated, in mice, the in vivo efficacy and toxicity of a versatile and modular NanoDendron (ND) drug delivery and imaging platform that we recently developed. Our paclitaxel-carrying ND prodrug, ND(PXL), is activated following proteolytic cleavage by MMP9, resulting in localized cytotoxic chemotherapy. Using click chemistry, we combined ND(PXL) with a traceable beacon, ND(PB), yielding ND(PXL)-ND(PB) that functions as a theranostic compound. In vivo fluorescence FRET imaging of this theranostic platform was used to confirm localized delivery to tumors and to assess the efficiency of drug delivery to tumors, achieving 25-30% activation in the tumors of an immunocompetent mouse model of breast cancer. In this model, ND-drug exhibited anti-tumor efficacy comparable to nab-paclitaxel, a clinical formulation. In addition, we combined neurobehavioral metrics of nociception and sensorimotor performance of individual mice to develop a novel composite toxicity score that reveals and quantifies peripheral neurotoxicity, a debilitating long-term systemic toxicity of paclitaxel therapy. Importantly, mice treated with nab-paclitaxel developed changes in behavioral metrics with significantly higher toxicity scores indicative of peripheral neuropathy, while mice treated with ND(PXL) showed no significant changes in behavioral responses or toxicity score. Our ND formulation was designed to be readily adaptable to incorporate different drugs, imaging modalities and/or targeting motifs. This formulation has significant potential for preclinical and clinical tools across multiple disease states. The studies presented here report a novel toxicity score for assessing peripheral neuropathy and demonstrate that our targeted, theranostic NDs are safe and effective, providing localized tumor delivery of a chemotherapeutic and with reduced common neurotoxic side-effects.

A cell-based systems biology assessment of human blood to monitor immune responses after influenza vaccination.

Systems biology is an approach to comprehensively study complex interactions within a biological system. Most published systems vaccinology studies have utilized whole blood or peripheral blood mononuclear cells (PBMC) to monitor the immune response after vaccination. Because human blood is comprised of multiple hematopoietic cell types, the potential for masking responses of under-represented cell populations is increased when analyzing whole blood or PBMC. To investigate the contribution of individual cell types to the immune response after vaccination, we established a rapid and efficient method to purify human T and B cells, natural killer (NK) cells, myeloid dendritic cells (mDC), monocytes, and neutrophils from fresh venous blood. Purified cells were fractionated and processed in a single day. RNA-Seq and quantitative shotgun proteomics were performed to determine expression profiles for each cell type prior to and after inactivated seasonal influenza vaccination. Our results show that transcriptomic and proteomic profiles generated from purified immune cells differ significantly from PBMC. Differential expression analysis for each immune cell type also shows unique transcriptomic and proteomic expression profiles as well as changing biological networks at early time points after vaccination. This cell type-specific information provides a more comprehensive approach to monitor vaccine responses.

Local breast cancer spatial patterning: a tool for community health resource allocation to address local disparities in breast cancer mortality.

Despite available demographic data on the factors that contribute to breast cancer mortality in large population datasets, local patterns are often overlooked. Such local information could provide a valuable metric by which regional community health resources can be allocated to reduce breast cancer mortality. We used national and statewide datasets to assess geographical distribution of breast cancer mortality rates and known risk factors influencing breast cancer mortality in middle Tennessee. Each county in middle Tennessee, and each ZIP code within metropolitan Davidson County, was scored for risk factor prevalence and assigned quartile scores that were used as a metric to identify geographic areas of need. While breast cancer mortality often correlated with age and incidence, geographic areas were identified in which breast cancer mortality rates did not correlate with age and incidence, but correlated with additional risk factors, such as mammography screening and socioeconomic status. Geographical variability in specific risk factors was evident, demonstrating the utility of this approach to identify local areas of risk. This method revealed local patterns in breast cancer mortality that might otherwise be overlooked in a more broadly based analysis. Our data suggest that understanding the geographic distribution of breast cancer mortality, and the distribution of risk factors that contribute to breast cancer mortality, will not only identify communities with the greatest need of support, but will identify the types of resources that would provide the most benefit to reduce breast cancer mortality in the community.

Identification of blood protein biomarkers that aid in the clinical assessment of patients with malignant glioma.

Analyzing molecular biomarkers using blood is an important approach for clinical assessment of malignant glioma. We investigated a molecular proteomic biomarker-based approach for glioblastoma using patients' blood samples. The expression levels of a list of candidate proteins were quantified in plasma and serum samples from two different cohorts of patients with malignant glioma and normal controls. The biological function was studied for one of the identified markers. Additionally, the prognostic significance of protein marker expression was measured by survival analysis. As a result, protein biomarkers associated with malignant glioma were identified from the blood specimens and five of the protein biomarkers were common to both cohorts. Immunohistochemical analysis demonstrated that many of the protein biomarkers identified in peripheral blood specimens were expressed in malignant gliomas. Staining levels for one of the biomarkers, MIP-1α, was found to correlate with WHO grade among invasive gliomas, and we demonstrate that MIP-1α promotes human glioblastoma cell proliferation and migration. Additionally, four prognostic protein biomarkers were identified. In conclusion, we demonstrate that both peripheral blood plasma and serum specimens are highly valuable and complementary to each other in the quest for protein biomarkers of malignant glioma. Sets of novel protein biomarkers were identified that may aid in the diagnosis and prognosis of patients with malignant glioma.

Genetic and clinical predictors for breast cancer risk assessment and stratification among Chinese women.

BACKGROUND: Most of the genetic variants identified from genome-wide association studies of breast cancer have not been validated in Asian women. No risk assessment model that incorporates both genetic and clinical predictors is currently available to predict breast cancer risk in this population. METHODS: We analyzed 12 single-nucleotide polymorphisms (SNPs) identified in recent genome-wide association studies mostly of women of European ancestry as being associated with the risk of breast cancer in 3039 case patients and 3082 control subjects who participated in the Shanghai Breast Cancer Study. All participants were interviewed in person to obtain information regarding known and suspected risk factors for breast cancer. The c statistic, a measure of discrimination ability with a value ranging from 0.5 (random classification) to 1.0 (perfect classification), was estimated to evaluate the contribution of genetic and established clinical predictors of breast cancer to a newly established risk assessment model for Chinese women. Clinical predictors included in the model were age at menarche, age at first live birth, waist-to-hip ratio, family history of breast cancer, and a previous diagnosis of benign breast disease. The utility of the models in risk stratification was evaluated by estimating the proportion of breast cancer patients in the general population that could be accounted for above a given risk threshold as predicted by the models. All statistical tests were two-sided. RESULTS: Eight SNPs (rs2046210, rs1219648, rs3817198, rs8051542, rs3803662, rs889312, rs10941679, and rs13281615), each of which reflected a genetically independent locus, were found to be associated with the risk of breast cancer. A dose-response association was observed between the risk of breast cancer and the genetic risk score, which is an aggregate measure of the effect of these eight SNPs (odds ratio for women in the highest quintile of genetic risk score vs those in the lowest = 1.85, 95% confidence interval = 1.58 to 2.18, P(trend) = 2.5 x 10(-15)). The genetic risk score, the waist-to-hip ratio, and a previous diagnosis of benign breast disease were the top three predictors of the risk of breast cancer, each contributing statistically significantly (P < .001) to the full risk assessment model. The model, with a c statistic of 0.6295 after adjustment for overfitting, showed promise for stratifying women into different risk groups; women in the top 30% risk group accounted for nearly 50% of the breast cancers diagnosed in the general population. CONCLUSION: A risk assessment model that includes both genetic markers and clinical predictors may be useful to classify Asian women into relevant risk groups for cost-efficient screening and other prevention programs.

Delay in diagnostic testing after abnormal mammography in low-income women.

PURPOSE/OBJECTIVES: To identify factors associated with diagnostic delay after an incomplete or abnormal mammogram among women participating in a state mammography screening program. RESEARCH APPROACH: Retrospective case-control design using bivariate and multivariate logistic regression analyses to explore the associations between age, race, ethnicity, marital status, breast cancer history, and self-reported breast symptoms and delay. SETTING: A statewide program of free screening mammography for women who are under- or uninsured. PARTICIPANTS: 11,460 women enrolled in a free, statewide screening program from 2002-2006. METHODOLOGIC APPROACH: Using the Tennessee Breast and Cervical Cancer Screening Program database, further analyses were conducted. MAIN RESEARCH VARIABLES: The outcome measure was delay in completion of all diagnostic tests and was defined as women who did not complete testing within 60 days. FINDINGS: Thirty-seven percent of women required follow-up, and of a subset used in the analysis, 30% experienced delay of more than 60 days. Controlling for marital status, age, and breast cancer history, women who experienced delay were more likely to be African American versus Caucasian (odds ratio [OR] = 1.45, 95% confidence interval [CI] = 1.13, 1.85) or Hispanic (OR = 0.72, 95% CI = 0.55, 0.93) and to have self-reported breast symptoms (OR = 1.50, 95% CI = 1.27, 1.77). CONCLUSIONS: In a sample of women with low income needing mammography follow-up, delay was associated with three intrapersonal variables, potentially reducing the effectiveness of mammography screening for women who were African American, or Hispanic, or had self-reported breast symptoms. INTERPRETATION: Nurses providing cancer screening examinations are uniquely positioned to assess the knowledge, beliefs, and resources of women using the program and to navigate women through barriers to completion. Knowledge of factors associated with delay is valuable for planning interventions and allocating program resources.

Management of occult fractures in the skeletally immature patient: cost analysis of implementing a limited trauma magnetic resonance imaging protocol.

STUDY OBJECTIVE: Fractures in children may not be visible in the result of initial radiography, and undertreatment and overtreatment of such fractures routinely occur. The purpose of this study was to evaluate the potential cost of implementing limited magnetic resonance imaging (MRI) at initial encounter, when radiographs are unrevealing. METHODS: This was a retrospective review of 204 emergency department pediatric patients presenting between January 1, 2005 and February 28, 2006 with appendicular trauma, with initially negative radiographic result and follow-up. Emergency department treatment categorization of (1) no treatment, (2) ACE wrap, (3) brace, (4) splint, or (5) casting was evaluated. Final determination of presence or absence of fracture was based on follow-up. Patients with fractures were considered undertreated when they received categories 1 to 3 care; patients without fractures were considered overtreated when they received categories 4 and 5 care. The percentage of patients undertreated or overtreated and direct and total costs were determined and analyzed in conjunction with the cost of a limited MRI at initial encounter. Total costs include direct and indirect costs (lost wages for each day off work for the parent). Cost estimates assume patients determined to be without fractures at follow-up will not return for follow-up clinical care or obtain additional imaging after MRI at initial encounter. RESULTS: Twenty-eight (13.7%) of the 204 patients had fractures at follow-up. Fifty one percent of patients without fractures were overtreated; 29% with fractures were undertreated. Mean direct cost for all patients and cost estimation with limited MRI protocol were $843.81 and $891.79, respectively (P = 0.365). However, mean total cost for all patients and cost estimation with limited MRI protocol was $1059.49 and $929.10, respectively (P = 0.02). CONCLUSIONS: Based on clinical grounds and initially negative radiographic results, slightly more than half of patients without fractures can be overtreated, and nearly one third of patients with fractures can be undertreated. Instituting a protocol that includes limited trauma MRI lowers the total cost of care without increasing direct cost, and appropriate care may be instituted at the outset.

Comparing cost and complications of primary and staged surgical repair of neonatally diagnosed Hirschsprung's disease.

BACKGROUND/PURPOSE: We questioned whether primary surgical correction of neonatally diagnosed Hirschsprung's Disease (HD) incurs higher costs or increased incidence of adverse events (AE) when compared with staged repair. METHODS: We reviewed the medical records of all neonates diagnosed with HD at our institution between 1997 and 2007. Sixty subjects fulfilled criteria for inclusion. Twenty-seven neonates had primary repair, and 33 had staged repair. We measured inflation-adjusted total costs, direct costs, and total charges and 6 AE between the 2 groups. A generalized linear model was used to examine differences between group variables. RESULTS: We found no statistically significant difference in costs or AE between primary and staged repair. Inflation-adjusted median financial data for primary or staged repair were, respectively, as follows: total costs, $35,670 vs $38,538 (P = .617); direct costs, $18,453 vs $23,937 (P = .128); total charges, $107,315 vs $102,492 (P = .690). Adverse events occurred in 48% of primary repair subjects and 36% of staged repair subjects (P = .434); no single AE differed significantly between the two groups. CONCLUSIONS: We found no statistical evidence that primary neonatal correction of HD adds cost or risk of AE when compared with a traditional staged approach in neonates who met inclusion criteria.

Increased resting energy expenditure in patients with end-stage renal disease.

BACKGROUND: Protein-calorie malnutrition is a significant problem for patients with end-stage renal disease. Increased resting energy expenditure may be an important contributing factor. We postulate that resting energy expen diture in the different stages of renal disease and treatments may be different. METHODS: Resting energy expenditure was measured using a whole-room indirect calorimeter (metabolic chamber) along with nutritional parameters and body composition after 12-hour fasting in 15 patients with advanced chronic renal failure patients, 15 patients on chronic hemodialysis, and 10 patients on peritoneal dialysis. Patients on hemodialysis were assessed on a non-dialysis day. A 2-day dietary recall was used to assess energy intake. RESULTS: Resting energy expenditure, adjusted for fat-free mass, was similar in patients on hemodialysis and peritoneal dialysis but significantly higher than in patients with chronic renal failure (p < .05). Resting energy expenditure in all patients were generally higher (10% to 20%) than predicted values using standard equations derived in normal and obese populations, whereas daily energy intake was less (26% to 34%) than energy expenditure for all groups, adjusted for light daily activity. CONCLUSIONS: End-stage renal disease patients displayed increases in resting energy expenditure over the predicted values derived using normal populations. Resting energy expenditure was significantly higher in patients receiving dialysis, regardless of the modality, than patients with chronic renal failure. Daily energy intake was substantially less than required in all patient groups studied, suggesting that patients with renal failure could develop protein-calorie malnutrition because of increased resting energy expenditure, which is exacerbated by dialysis.