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BackgroundOur preclinical work revealed tumour hypoxia induces homologous recombination deficiency (HRD), increasing sensitivity to Poly (ADP-ribose) polymerase inhibitors. We aimed to induce tumour hypoxia with ramucirumab thereby sensitising tumours to olaparib.Patients and methodsThis multi-institution single-arm Phase 1/2 trial enrolled patients with metastatic gastroesophageal adenocarcinoma refractory to ≥1 systemic treatment. In dose escalation, olaparib was evaluated at escalating dose levels with ramucirumab 8 mg/kg day 1 in 14-day cycles. The primary endpoint of Phase 1 was the recommended Phase 2 dose (RP2D), and in Phase 2 the primary endpoint was the overall response rate (ORR).ResultsFifty-one patients received ramucirumab and olaparib. The RP2D was olaparib 300 mg twice daily with ramucirumab 8 mg/kg. In evaluable patients at the RP2D the ORR was 6/43 (14%) (95% CI 4.7-25.6). The median progression-free survival (PFS) was 2.8 months (95% CI 2.3-4.2) and median overall survival (OS) was 7.3 months (95% CI 5.7-13.0). Non-statistically significant improvements in PFS and OS were observed for patients with tumours with mutations in HRD genes.ConclusionsOlaparib and ramucirumab is well-tolerated with efficacy that exceeds historical controls with ramucirumab single agent for gastric cancer in a heavily pre-treated patient population.

Patients with B-lymphoid malignancies have been consistently identified as a population at high risk of severe COVID-19. Whether this is exclusively due to cancer-related deficits in humoral and cellular immunity, or whether risk of severe COVID-19 is increased by anticancer therapy, is uncertain. Using data derived from the COVID-19 and Cancer Consortium (CCC19), we show that patients treated for B-lymphoid malignancies have an increased risk of severe COVID-19 compared with control populations of patients with non-B-lymphoid malignancies. Among patients with B-lymphoid malignancies, those who received anticancer therapy within 12 months of COVID-19 diagnosis experienced increased COVID-19 severity compared with patients with non-recently treated B-lymphoid malignancies, after adjustment for cancer status and several other prognostic factors. Our findings suggest that patients recently treated for a B-lymphoid malignancy are at uniquely high risk for severe COVID-19.SignificanceOur study suggests that recent therapy for a B-lymphoid malignancy is an independent risk factor for COVID-19 severity. These findings provide rationale to develop mitigation strategies targeted at the uniquely high-risk population of patients with recently treated B-lymphoid malignancies. This article is highlighted in the In This Issue feature, p. 171.

OBJECTIVES: To examine whether social determinants of health (SDH) factors are associated with time to diagnosis, treatment selection, and time to recurrent surgical intervention in idiopathic subglottic stenosis (iSGS) patients. METHODS: Adult patients with diagnosed iSGS were recruited prospectively (2015-2017) via clinical providers as part of the North American Airway Collaborative (NoAAC) and via an online iSGS support community on Facebook. Patient-specific SDH factors included highest educational attainment (self-reported), median household income (matched from home zip code via U.S. Census data), and number of close friends (self-reported) as a measure of social support. Main outcomes of interest were time to disease diagnosis (years from symptom onset), treatment selection (endoscopic dilation [ED] vs cricotracheal resection [CTR] vs endoscopic resection with adjuvant medical therapy [ERMT]), and time to recurrent surgical intervention (number of days from initial surgical procedure) as a surrogate for disease recurrence. RESULTS: The total 810 participants were 98.5% female, 97.2% Caucasian, and had a median age of 50 years (IQR, 43-58). The cohort had a median household income of $62 307 (IQR, $50 345-$79 773), a median of 7 close friends (IQR, 4-10), and 64.7% of patients completed college or graduate school. Education, income, and number of friends were not associated with time to diagnosis via multivariable linear regression modeling. Univariable multinominal logistic regression demonstrated an association between education and income for selecting ED versus ERMT, but no associations were noted for CTR. No associations were noted for time to recurrent surgical procedure via Kaplan Meier modeling and Cox proportional hazards regression. CONCLUSIONS: Patient education, income, and social support were not associated with time to diagnosis or time to disease recurrence. This suggests additional patient, procedure, or disease-specific factors contribute to the observed variations in iSGS surgical outcomes.

BackgroundHospitalized 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.ObjectivesTo assess the incidence of and risk factors for thrombosis in hospitalized patients with cancer and COVID-19.MethodsAmong 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.ResultsFrom 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.ConclusionsHospitalized 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.

BackgroundData on patients with COVID-19 who have cancer are lacking. Here we characterise the outcomes of a cohort of patients with cancer and COVID-19 and identify potential prognostic factors for mortality and severe illness.MethodsIn this cohort study, we collected de-identified data on patients with active or previous malignancy, aged 18 years and older, with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection from the USA, Canada, and Spain from the COVID-19 and Cancer Consortium (CCC19) database for whom baseline data were added between March 17 and April 16, 2020. We collected data on baseline clinical conditions, medications, cancer diagnosis and treatment, and COVID-19 disease course. The primary endpoint was all-cause mortality within 30 days of diagnosis of COVID-19. We assessed the association between the outcome and potential prognostic variables using logistic regression analyses, partially adjusted for age, sex, smoking status, and obesity. This study is registered with ClinicalTrials.gov, NCT04354701, and is ongoing.FindingsOf 1035 records entered into the CCC19 database during the study period, 928 patients met inclusion criteria for our analysis. Median age was 66 years (IQR 57-76), 279 (30%) were aged 75 years or older, and 468 (50%) patients were male. The most prevalent malignancies were breast (191 [21%]) and prostate (152 [16%]). 366 (39%) patients were on active anticancer treatment, and 396 (43%) had active (measurable) cancer. At analysis (May 7, 2020), 121 (13%) patients had died. In logistic regression analysis, independent factors associated with increased 30-day mortality, after partial adjustment, were: increased age (per 10 years; partially adjusted odds ratio 1·84, 95% CI 1·53-2·21), male sex (1·63, 1·07-2·48), smoking status (former smoker vs never smoked: 1·60, 1·03-2·47), number of comorbidities (two vs none: 4·50, 1·33-15·28), Eastern Cooperative Oncology Group performance status of 2 or higher (status of 2 vs 0 or 1: 3·89, 2·11-7·18), active cancer (progressing vs remission: 5·20, 2·77-9·77), and receipt of azithromycin plus hydroxychloroquine (vs treatment with neither: 2·93, 1·79-4·79; confounding by indication cannot be excluded). Compared with residence in the US-Northeast, residence in Canada (0·24, 0·07-0·84) or the US-Midwest (0·50, 0·28-0·90) were associated with decreased 30-day all-cause mortality. Race and ethnicity, obesity status, cancer type, type of anticancer therapy, and recent surgery were not associated with mortality.InterpretationAmong patients with cancer and COVID-19, 30-day all-cause mortality was high and associated with general risk factors and risk factors unique to patients with cancer. Longer follow-up is needed to better understand the effect of COVID-19 on outcomes in patients with cancer, including the ability to continue specific cancer treatments.FundingAmerican Cancer Society, National Institutes of Health, and Hope Foundation for Cancer Research.

BackgroundUnsuccessful KRAS-specific treatment approaches in non-small-cell lung cancer (NSCLC) might reflect underlying disease heterogeneity. We sought to define clinical "syndromes" within advanced KRAS mutant NSCLC to improve future clinical trials and create a clinical framework for future molecular development.Patients and methodsTo test a series of a priori hypotheses regarding KRAS-mutant NSCLC clinical syndromes, we conducted a multi-institutional retrospective medical record review. Survival probabilities were estimated using the Kaplan-Meier model. Between-group differences were assessed using the log-rank test. Multivariate Cox regression analyses and Wilcoxon rank sum testing were used to assess progression-free survival and overall survival (OS) differences.ResultsAmong 218 patients with advanced KRAS-mutant NSCLC, OS and progression-free survival with first-line chemotherapy did not differ by intrathoracic versus extrathoracic spread, smoking intensity, or the specific KRAS mutation. Metastatic disease at diagnosis resulted in significantly worse OS than recurrent, unresectable disease (median OS, 14.6 vs. 40.9 months; P = .001). Among the patients with metastatic disease at diagnosis, nonscalp, soft tissue metastases (syndrome X; 6% of cases; 95% confidence interval [CI], 2.5%-10.1%) signified a poor prognosis (median OS, 7.5 vs. 15.9 months for the controls; P = .021). The response to first-line chemotherapy (syndrome Y; 41% of cases; 95% CI, 32.3%-50.6%) signified a good prognosis (median OS, 26.7 vs. 11.9 months; P = .002). The overlap between these 2 syndromes was minimal (2 of 111). Multivariate analysis confirmed these observations. The hazard ratio for death for syndromes X and Y was 2.64 (95% CI, 1.13-6.14) and 0.45 (95% CI, 0.28-0.76), respectively.ConclusionChemotherapy-responsive disease and nonscalp, soft tissue spread might represent distinct clinical syndromes within KRAS-mutant NSCLC. The molecular biology underlying this heterogeneity warrants future studies.

BackgroundPediatric oncology patients are at an increased risk of invasive bacterial infection due to immunosuppression. The risk of such infection in the absence of severe neutropenia (absolute neutrophil count ≥ 500/μL) is not well established and a validated prediction model for blood stream infection (BSI) risk offers clinical usefulness.MethodsA 6-site retrospective external validation was conducted using a previously published risk prediction model for BSI in febrile pediatric oncology patients without severe neutropenia: the Esbenshade/Vanderbilt (EsVan) model. A reduced model (EsVan2) excluding 2 less clinically reliable variables also was created using the initial EsVan model derivative cohort, and was validated using all 5 external validation cohorts. One data set was used only in sensitivity analyses due to missing some variables.ResultsFrom the 5 primary data sets, there were a total of 1197 febrile episodes and 76 episodes of bacteremia. The overall C statistic for predicting bacteremia was 0.695, with a calibration slope of 0.50 for the original model and a calibration slope of 1.0 when recalibration was applied to the model. The model performed better in predicting high-risk bacteremia (gram-negative or Staphylococcus aureus infection) versus BSI alone, with a C statistic of 0.801 and a calibration slope of 0.65. The EsVan2 model outperformed the EsVan model across data sets with a C statistic of 0.733 for predicting BSI and a C statistic of 0.841 for high-risk BSI.ConclusionsThe results of this external validation demonstrated that the EsVan and EsVan2 models are able to predict BSI across multiple performance sites and, once validated and implemented prospectively, could assist in decision making in clinical practice. Cancer 2017;123:3781-3790. © 2017 American Cancer Society.

IntroductionSocial 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.MethodsAdults, 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.ResultsOf 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).ConclusionQuestion 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.

Proteins involved in tumor cell migration can potentially serve as markers of invasive disease. Activated Leukocyte Cell Adhesion Molecule (ALCAM) promotes adhesion, while shedding of its extracellular domain is associated with migration. We hypothesized that shed ALCAM in biofluids could be predictive of progressive disease. ALCAM expression in tumor (n = 198) and shedding in biofluids (n = 120) were measured in two separate VUMC bladder cancer cystectomy cohorts by immunofluorescence and enzyme-linked immunosorbent assay, respectively. The primary outcome measure was accuracy of predicting 3-year overall survival (OS) with shed ALCAM compared to standard clinical indicators alone, assessed by multivariable Cox regression and concordance-indices. Validation was performed by internal bootstrap, a cohort from a second institution (n = 64), and treatment of missing data with multiple-imputation. While ALCAM mRNA expression was unchanged, histological detection of ALCAM decreased with increasing stage (P = 0.004). Importantly, urine ALCAM was elevated 17.0-fold (P < 0.0001) above non-cancer controls, correlated positively with tumor stage (P = 0.018), was an independent predictor of OS after adjusting for age, tumor stage, lymph-node status, and hematuria (HR, 1.46; 95% CI, 1.03-2.06; P = 0.002), and improved prediction of OS by 3.3% (concordance-index, 78.5% vs. 75.2%). Urine ALCAM remained an independent predictor of OS after accounting for treatment with Bacillus Calmette-Guerin, carcinoma in situ, lymph-node dissection, lymphovascular invasion, urine creatinine, and adjuvant chemotherapy (HR, 1.10; 95% CI, 1.02-1.19; P = 0.011). In conclusion, shed ALCAM may be a novel prognostic biomarker in bladder cancer, although prospective validation studies are warranted. These findings demonstrate that markers reporting on cell motility can act as prognostic indicators.

Proteins involved in tumor cell migration can potentially serve as markers of invasive disease. Activated Leukocyte Cell Adhesion Molecule (ALCAM) promotes adhesion, while shedding of its extracellular domain is associated with migration. We hypothesized that shed ALCAM in biofluids could be predictive of progressive disease. ALCAM expression in tumor (n = 198) and shedding in biofluids (n = 120) were measured in two separate VUMC bladder cancer cystectomy cohorts by immunofluorescence and enzyme-linked immunosorbent assay, respectively. The primary outcome measure was accuracy of predicting 3-year overall survival (OS) with shed ALCAM compared to standard clinical indicators alone, assessed by multivariable Cox regression and concordance-indices. Validation was performed by internal bootstrap, a cohort from a second institution (n = 64), and treatment of missing data with multiple-imputation. While ALCAM mRNA expression was unchanged, histological detection of ALCAM decreased with increasing stage (P = 0.004). Importantly, urine ALCAM was elevated 17.0-fold (P < 0.0001) above non-cancer controls, correlated positively with tumor stage (P = 0.018), was an independent predictor of OS after adjusting for age, tumor stage, lymph-node status, and hematuria (HR, 1.46; 95% CI, 1.03-2.06; P = 0.002), and improved prediction of OS by 3.3% (concordance-index, 78.5% vs. 75.2%). Urine ALCAM remained an independent predictor of OS after accounting for treatment with Bacillus Calmette-Guerin, carcinoma in situ, lymph-node dissection, lymphovascular invasion, urine creatinine, and adjuvant chemotherapy (HR, 1.10; 95% CI, 1.02-1.19; P = 0.011). In conclusion, shed ALCAM may be a novel prognostic biomarker in bladder cancer, although prospective validation studies are warranted. These findings demonstrate that markers reporting on cell motility can act as prognostic indicators.

BACKGROUND: Increasing evidence indicates that proteotoxicity plays a pathophysiologic role in experimental and human cardiomyopathy. In organ-specific amyloidoses, soluble protein oligomers are the primary cytotoxic species in the process of protein aggregation. While isolated atrial amyloidosis can develop with aging, the presence of preamyloid oligomers (PAOs) in atrial tissue has not been previously investigated. METHODS AND RESULTS: Atrial samples were collected during elective cardiac surgery in patients without a history of atrial arrhythmias, congestive heart failure, cardiomyopathy, or amyloidosis. Immunohistochemistry was performed for PAOs using a conformation-specific antibody, as well as for candidate proteins identified previously in isolated atrial amyloidosis. Using a myocardium-specific marker, the fraction of myocardium colocalizing with PAOs (PAO burden) was quantified (green/red ratio). Atrial samples were obtained from 92 patients, with a mean age of 61.7±13.8 years. Most patients (62%) were male, 23% had diabetes, 72% had hypertension, and 42% had coronary artery disease. A majority (n=62) underwent aortic valve replacement, with fewer undergoing coronary artery bypass grafting (n=34) or mitral valve replacement/repair (n=24). Immunostaining detected intracellular PAOs in a majority of atrial samples, with a heterogeneous distribution throughout the myocardium. Mean green/red ratio value for the samples was 0.11±0.1 (range 0.03 to 0.77), with a value ≥0.05 in 74 patients. Atrial natriuretic peptide colocalized with PAOs in myocardium, whereas transthyretin was located in the interstitium. Adjusting for multiple covariates, PAO burden was independently associated with the presence of hypertension. CONCLUSION: PAOs are frequently detected in human atrium, where their presence is associated with clinical hypertension.

Abnormalities in atrial myocardium increase the likelihood of arrhythmias, including atrial fibrillation (AF). The deposition of misfolded protein, or amyloidosis, plays an important role in the pathophysiology of many diseases, including human cardiomyopathies. We have shown that genes implicated in amyloidosis are activated in a cellular model of AF, with the development of preamyloid oligomers (PAOs). PAOs are intermediates in the formation of amyloid fibrils, and they are now recognized to be the cytotoxic species during amyloidosis. To investigate the presence of PAOs in human atrium, we developed a microscopic imaging-based protocol to enable robust and reproducible quantitative analysis of PAO burden in atrial samples harvested at the time of elective cardiac surgery. Using PAO- and myocardial-specific antibodies, we found that PAO distribution was typically heterogeneous within a myocardial sample. Rigorous imaging and analysis protocols were developed to quantify the relative area of myocardium containing PAOs, termed the Green/Red ratio (G/R), for a given sample. Using these methods, reproducible G/R values were obtained when different sections of a sample were independently processed, imaged, and analyzed by different investigators. This robust technique will enable studies to investigate the role of this novel structural abnormality in the pathophysiology of and arrhythmia generation in human atrial tissue.

Motivation Single-cell RNA-seq normalization is an essential step to correct unwanted biases caused by sequencing depth, capture efficiency, dropout, and other technical factors. Existing normalization methods primarily reduce biases arising from sequencing depth by modeling count-depth relationship and/or assuming a specific distribution for read counts. However, these methods may lead to over or under-correction due to presence of technical biases beyond sequencing depth and the restrictive assumption on models and distributions. Results We present scKWARN, a K ernel W eighted A verage R obust N ormalization designed to correct known or hidden technical confounders without assuming specific data distributions or count-depth relationships. scKWARN generates a pseudo expression profile for each cell by borrowing information from its fuzzy technical neighbors through a kernel smoother. It then compares this profile against the reference derived from cells with the same bimodality patterns to determine the normalization factor. As demonstrated in both simulated and real datasets, scKWARN outperforms existing methods in removing a variety of technical biases while preserving true biological heterogeneity. Availability and Implementation scKWARN is freely available at https://github.com/cyhsuTN/scKWARN. [ABSTRACT FROM AUTHOR]

Adapter trimming is an essential step for analyzing small RNA sequencing data, where reads are generally longer than target RNAs ranging from 18 to 30 bp. Most adapter trimming tools require adapter information as input. However, adapter information is hard to access, specified incorrectly, or not provided with publicly available datasets, hampering their reproducibility and reusability. Manual identification of adapter patterns from raw reads is labor-intensive and error-prone. Moreover, the use of randomized adapters to reduce ligation biases during library preparation makes adapter detection even more challenging. Here, we present FindAdapt, a Python package for fast and accurate detection of adapter patterns without relying on prior information. We demonstrated that FindAdapt was far superior to existing approaches. It identified adapters successfully in 180 simulation datasets with diverse read structures and 3,184 real datasets covering a variety of commercial and customized small RNA library preparation kits. FindAdapt is stand-alone software that can be easily integrated into small RNA sequencing analysis pipelines. [ABSTRACT FROM AUTHOR]

Simple Summary: Small RNA sequencing has been widely used for characterizing the landscape of small non-coding RNAs—the most abundant cargo in extracellular vesicles (EVs). Here, we performed a systematic assessment of the quality, technical, and potential biological biases introduced by different EV isolation methods and the enrichment of specific, small RNA biotypes in EVs. The findings in this study guide the quality control of EV small RNA-seq and the selection of EV isolation techniques and enhance the interpretation of small RNA contents and the preferential loading of specific RNA biotypes into EVs. 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. [ABSTRACT FROM AUTHOR]