Cardiac magnetic resonance predictors for successful primary biventricular repair of unbalanced complete common atrioventricular canal.

BACKGROUND: Patients with unbalanced common atrioventricular canal can be difficult to manage. Surgical planning often depends on pre-operative echocardiographic measurements. We aimed to determine the added utility of cardiac MRI in predicting successful biventricular repair in common atrioventricular canal. METHODS: We conducted a retrospective cohort study of children with common atrioventricular canal who underwent MRI prior to repair. Associations between MRI and echocardiographic measures and surgical outcome were tested using logistic regression, and models were compared using area under the receiver operator characteristic curve. RESULTS: We included 28 patients (median age at MRI: 5.2 months). The optimal MRI model included the novel end-diastolic volume index (using the ratio of left ventricular end-diastolic volume to total end-diastolic volume) and the left ventricle-right ventricle angle in diastole (area under the curve 0.83, p = 0.041). End-diastolic volume index ≤ 0.18 and left ventricle-right ventricle angle in diastole ≤ 72° yield a sensitivity of 83% and specificity of 81% for successful biventricular repair. The optimal multimodality model included the end-diastolic volume index and the echocardiographic atrioventricular valve index with an area under the curve of 0.87 (p = 0.026). CONCLUSIONS: Cardiac MRI can successfully predict successful biventricular repair in patients with unbalanced common atrioventricular canal utilising the end-diastolic volume index alone or in combination with the MRI left ventricle-right ventricle angle in diastole or the echocardiographic atrioventricular valve index. A prospective cardiac MRI study is warranted to better define the multimodality characteristic predictive of successful biventricular surgery.

Cerebral microhemorrhages in children with congenital heart disease: Prevalence, risk factors, and impact on neurodevelopmental outcomes.

Background: Infants with complex congenital heart disease (CHD) require life-saving corrective/palliative heart surgery in the first weeks of life. These infants are at risk for brain injury and poor neurodevelopmental outcomes. Cerebral microhemorrhages (CMH) are frequently seen after neonatal bypass heart surgery, but it remains unknown if CMH are a benign finding or constitute injury. Herein, we investigate the risk factors for developing CMH and their clinical significance. Methods: 192 infants with CHD undergoing corrective cardiac surgery with cardiopulmonary bypass (CPB) at a single institution were prospectively evaluated with pre-(n = 183) and/or postoperative (n = 162) brain magnetic resonance imaging (MRI). CMH severity was scored based on total number of microhemorrhages. Antenatal, perioperative, and postoperative candidate risk factors for CMH and neurodevelopmental (ND) outcomes were analyzed. Eighteen-month neurodevelopmental outcomes were assessed using the Bayley-III Scales of Infants and Toddler Development in a subset of patients (n = 82). Linear regression was used to analyze associations between risk factors or ND outcomes and presence/number of CMH. Results: The most common CHD subtypes were hypoplastic left heart syndrome (HLHS) (37%) and transposition of the great arteries (TGA) (33%). Forty-two infants (23%) had CMH present on MRI before surgery and 137 infants (85%) post-surgery. No parameters evaluated were significant risk factors for preoperative CMH. In multivariate analysis, cardiopulmonary bypass (CPB) duration (p < 0.0001), use of extracorporeal membrane oxygenation (ECMO) support (p < 0.0005), postoperative seizure(s) (p < 0.03), and lower birth weight (p < 0.03) were associated with new or worsened CMH postoperatively. Higher CMH number was associated with lower scores on motor (p < 0.03) testing at 18 months. Conclusion: CMH is a common imaging finding in infants with CHD with increased prevalence and severity after CPB and adverse impact on neurodevelopmental outcomes starting at a young age. Longer duration of CPB and need for postoperative ECMO were the most significant risk factors for developing CMH. However, presence of CMH on preoperative scans indicates non-surgical risk factors that are yet to be identified. Neuroprotective strategies to mitigate risk factors for CMH may improve neurodevelopmental outcomes in this vulnerable population.

Diffuse Optical Monitoring of Cerebral Hemodynamics and Oxygen Metabolism during and after Cardiopulmonary Bypass: Hematocrit Correction and Neurological Vulnerability.

Cardiopulmonary bypass (CPB) provides cerebral oxygenation and blood flow (CBF) during neonatal congenital heart surgery, but the impacts of CPB on brain oxygen supply and metabolic demands are generally unknown. To elucidate this physiology, we used diffuse correlation spectroscopy and frequency-domain diffuse optical spectroscopy to continuously measure CBF, oxygen extraction fraction (OEF), and oxygen metabolism (CMRO2) in 27 neonatal swine before, during, and up to 24 h after CPB. Concurrently, we sampled cerebral microdialysis biomarkers of metabolic distress (lactate-pyruvate ratio) and injury (glycerol). We applied a novel theoretical approach to correct for hematocrit variation during optical quantification of CBF in vivo. Without correction, a mean (95% CI) +53% (42, 63) increase in hematocrit resulted in a physiologically improbable +58% (27, 90) increase in CMRO2 relative to baseline at CPB initiation; following correction, CMRO2 did not differ from baseline at this timepoint. After CPB initiation, OEF increased but CBF and CMRO2 decreased with CPB time; these temporal trends persisted for 0-8 h following CPB and coincided with a 48% (7, 90) elevation of glycerol. The temporal trends and glycerol elevation resolved by 8-24 h. The hematocrit correction improved quantification of cerebral physiologic trends that precede and coincide with neurological injury following CPB.

RNA Sequencing in Hypoxia-Adapted T98G Glioblastoma Cells Provides Supportive Evidence for IRE1 as a Potential Therapeutic Target.

Glioblastoma (GBM) is an aggressive brain cancer with a median survival time of 14.6 months after diagnosis. GBM cells have altered metabolism and exhibit the Warburg effect, preferentially producing lactate under aerobic conditions. After standard-of-care treatment for GBM, there is an almost 100% recurrence rate. Hypoxia-adapted, treatment-resistant GBM stem-like cells are thought to drive this high recurrence rate. We used human T98G GBM cells as a model to identify differential gene expression induced by hypoxia and to search for potential therapeutic targets of hypoxia adapted GBM cells. RNA sequencing (RNAseq) and bioinformatics were used to identify differentially expressed genes (DEGs) and cellular pathways affected by hypoxia. We also examined expression of lactate dehydrogenase (LDH) genes using qRT-PCR and zymography as LDH dysregulation is a feature of many cancers. We found 2630 DEGs significantly altered by hypoxia (p < 0.05), 1241 upregulated in hypoxia and 1389 upregulated in normoxia. Hypoxia DEGs were highest in pathways related to glycolysis, hypoxia response, cell adhesion and notably the endoplasmic reticulum, including the inositol-requiring enzyme 1 (IRE1)-mediated unfolded protein response (UPR). These results, paired with numerous published preclinical data, provide additional evidence that inhibition of the IRE1-mediated UPR may have therapeutic potential in treating GBM. We propose a possible drug repurposing strategy to simultaneously target IRE1 and the spleen tyrosine kinase (SYK) in patients with GBM.

Molecular response in newly diagnosed chronic-phase chronic myeloid leukemia: prediction modeling and pathway analysis.

Tyrosine kinase inhibitor therapy revolutionized chronic myeloid leukemia treatment and showed how targeted therapy and molecular monitoring could be used to substantially improve survival outcomes. We used chronic myeloid leukemia as a model to understand a critical question: why do some patients have an excellent response to therapy, while others have a poor response? We studied gene expression in whole blood samples from 112 patients from a large phase III randomized trial (clinicaltrials gov. Identifier: NCT00471497), dichotomizing cases into good responders (BCR::ABL1 ≤10% on the International Scale by 3 and 6 months and ≤0.1% by 12 months) and poor responders (failure to meet these criteria). Predictive models based on gene expression demonstrated the best performance (area under the curve =0.76, standard deviation =0.07). All of the top 20 pathways overexpressed in good responders involved immune regulation, a finding validated in an independent data set. This study emphasizes the importance of pretreatment adaptive immune response in treatment efficacy and suggests biological pathways that can be targeted to improve response.

Treatment of Severe Pincer-Type Femoroacetabular Impingement With Arthroscopic Significant Acetabular Rim Correction and Circumferential Labral Reconstruction Improves Patient-Reported Outcome Measures.

PURPOSE: To validate an arthroscopic approach for performing significant acetabular rim correction and circumferential labral reconstruction required to treat severe pincer-type femoroacetabular impingement. METHODS: Using a minimum of 2-year follow-up, data from 48 hips, including 47 patients (11 male, 36 female; mean age of 42 years) having undergone significant arthroscopic acetabuloplasty for severe pincer impingement (center edge angle >45°) with concomitant circumferential allograft labral reconstruction were analyzed to determine improvements in patient-reported outcomes and degree of radiographic correction. RESULTS: Findings demonstrated a 98% success rate, including substantial improvements on all radiographic measurements and patient-reported outcomes. Minimal clinically important differences were met with extremely strong measures of effect. The mean center edge angle improved from 49° to 36° (MΔ = 13.96, P ≤ .001, standard deviation [SD] = 55.97, confidence interval [CI] 12.17- 15.62, d = 2.33) and the mean Tönnis angle improved from -6° to 0° (MΔ = 6.2, P ≤ .001, SD = 2.76 CI -7.1 to -5.39, d = 2.29). Modified Hip Harris Scores improved by a mean of 34.45 points (P ≤ .001, SD = 20.64, 95% CI 28.45-40.44, d = 1.66). Lower extremity functional scale scores improved by a mean of 27.35 points (P ≤ .001, SD = 18.37, 95% CI 22.02-32.69, d =1.48). No complications were reported. One case converted to a total hip arthroplasty (2%). CONCLUSIONS: Findings validated that the significant acetabular rim correction required to treat severe pincer morphology is safe and feasible via an arthroscopic approach. This, in addition to concomitant circumferential allograft labral reconstruction, resulted in improvement in patient-reported outcomes and radiographic measurements. LEVEL OF EVIDENCE: Level IV, therapeutic case-series.

Deep learning image analysis quantifies tumor heterogeneity and identifies microsatellite instability in colon cancer.

BACKGROUND AND OBJECTIVES: Deep learning utilizing convolutional neural networks (CNNs) applied to hematoxylin & eosin (H&E)-stained slides numerically encodes histomorphological tumor features. Tumor heterogeneity is an emerging biomarker in colon cancer that is, captured by these features, whereas microsatellite instability (MSI) is an established biomarker traditionally assessed by immunohistochemistry or polymerase chain reaction. METHODS: H&E-stained slides from The Cancer Genome Atlas (TCGA) colon cohort are passed through the CNN. Resulting imaging features are used to cluster morphologically similar slide regions. Tile-level pairwise similarities are calculated and used to generate a tumor heterogeneity score (THS). Patient-level THS is then correlated with TCGA-reported biomarkers, including MSI-status. RESULTS: H&E-stained images from 313 patients generated 534 771 tiles. Deep learning automatically identified and annotated cells by type and clustered morphologically similar slide regions. MSI-high tumors demonstrated significantly higher THS than MSS/MSI-low (p < 0.001). THS was higher in MLH1-silent versus non-silent tumors (p < 0.001). The sequencing derived MSIsensor score also correlated with THS (r = 0.51, p < 0.0001). CONCLUSIONS: Deep learning provides spatially resolved visualization of imaging-derived biomarkers and automated quantification of tumor heterogeneity. Our novel THS correlates with MSI-status, indicating that with expanded training sets, translational tools could be developed that predict MSI-status using H&E-stained images alone.

Correlation of Cerebral Microdialysis with Non-Invasive Diffuse Optical Cerebral Hemodynamic Monitoring during Deep Hypothermic Cardiopulmonary Bypass.

Neonates undergoing cardiac surgery involving aortic arch reconstruction are at an increased risk for hypoxic-ischemic brain injury. Deep hypothermia is utilized to help mitigate this risk when periods of circulatory arrest are needed for surgical repair. Here, we investigate correlations between non-invasive optical neuromonitoring of cerebral hemodynamics, which has recently shown promise for the prediction of postoperative white matter injury in this patient population, and invasive cerebral microdialysis biomarkers. We compared cerebral tissue oxygen saturation (StO2), relative total hemoglobin concentration (rTHC), and relative cerebral blood flow (rCBF) measured by optics against the microdialysis biomarkers of metabolic stress and injury (lactate-pyruvate ratio (LPR) and glycerol) in neonatal swine models of deep hypothermic cardiopulmonary bypass (DHCPB), selective antegrade cerebral perfusion (SACP), and deep hypothermic circulatory arrest (DHCA). All three optical parameters were negatively correlated with LPR and glycerol in DHCA animals. Elevation of LPR was found to precede the elevation of glycerol by 30-60 min. From these data, thresholds for the detection of hypoxic-ischemia-associated cerebral metabolic distress and neurological injury are suggested. In total, this work provides insight into the timing and mechanisms of neurological injury following hypoxic-ischemia and reports a quantitative relationship between hypoxic-ischemia severity and neurological injury that may inform DHCA management.

Fetal Doppler Echocardiographic Assessment Predicts Severe Postnatal Obstruction in Total Anomalous Pulmonary Venous Connection.

BACKGROUND: Obstructed total anomalous pulmonary venous connection (TAPVC) is a form of critical congenital heart disease that usually requires urgent postnatal intervention. Knowing which patients have severe obstruction can aid delivery planning. The authors previously developed a novel quantitative metric of pulmonary venous flow, the pulmonary venous variability index (PVVI). The aim of this study was to test the hypothesis that fetal PVVI and vertical vein Doppler velocities are associated with severe pulmonary vein obstruction postnatally. METHODS: A retrospective cohort study of neonates with prenatally diagnosed TAPVC was performed. Patients who underwent fetal echocardiography at the Children's Hospital of Philadelphia with Doppler interrogation of the vertical vein were included for analysis. Twenty-nine patients met criteria (21 with heterotaxy, 18 with supracardiac TAPVC). The latest gestation fetal echocardiogram was used. Severe pulmonary vein obstruction was defined as preoperative death or urgent surgery or catheter-based intervention (first day of life). Measurements of PVVI, defined as (maximum velocity - minimum velocity)/mean velocity, were made offline. Wilcoxon rank sum models were used to assess the associations of severe obstruction and PVVI and maximum, mean, and minimum velocities. RESULTS: The mean gestational age at the latest fetal echocardiographic examination was 35 weeks (range, 30-39 weeks). Twelve of the 29 patients (41%) met criteria for severe pulmonary vein obstruction. Lower PVVI was associated with greater risk for severe pulmonary venous obstruction (P = .008). The maximum, mean, and minimum velocities in the vertical vein were all significantly associated with severe pulmonary venous obstruction (P = .03, P = .03, and P = .007, respectively). Qualitative assessment of obstruction was not significantly associated with the outcome. Interobserver reliability for all vertical vein Doppler metrics was high (intraclass correlation coefficient > 0.9). CONCLUSIONS: Fetal PVVI and maximum, mean, and minimum velocities are associated with severe postnatal pulmonary vein obstruction in TAPVC. Accurate prediction of obstructed TAPVC could allow safer delivery planning. Further research with larger sample sizes is needed to identify the ideal cutoff values for these Doppler measures.

Deep learning features encode interpretable morphologies within histological images.

Convolutional neural networks (CNNs) are revolutionizing digital pathology by enabling machine learning-based classification of a variety of phenotypes from hematoxylin and eosin (H&E) whole slide images (WSIs), but the interpretation of CNNs remains difficult. Most studies have considered interpretability in a post hoc fashion, e.g. by presenting example regions with strongly predicted class labels. However, such an approach does not explain the biological features that contribute to correct predictions. To address this problem, here we investigate the interpretability of H&E-derived CNN features (the feature weights in the final layer of a transfer-learning-based architecture). While many studies have incorporated CNN features into predictive models, there has been little empirical study of their properties. We show such features can be construed as abstract morphological genes ("mones") with strong independent associations to biological phenotypes. Many mones are specific to individual cancer types, while others are found in multiple cancers especially from related tissue types. We also observe that mone-mone correlations are strong and robustly preserved across related cancers. Importantly, linear mone-based classifiers can very accurately separate 38 distinct classes (19 tumor types and their adjacent normals, AUC = [Formula: see text] for each class prediction), and linear classifiers are also highly effective for universal tumor detection (AUC = [Formula: see text]). This linearity provides evidence that individual mones or correlated mone clusters may be associated with interpretable histopathological features or other patient characteristics. In particular, the statistical similarity of mones to gene expression values allows integrative mone analysis via expression-based bioinformatics approaches. We observe strong correlations between individual mones and individual gene expression values, notably mones associated with collagen gene expression in ovarian cancer. Mone-expression comparisons also indicate that immunoglobulin expression can be identified using mones in colon adenocarcinoma and that immune activity can be identified across multiple cancer types, and we verify these findings by expert histopathological review. Our work demonstrates that mones provide a morphological H&E decomposition that can be effectively associated with diverse phenotypes, analogous to the interpretability of transcription via gene expression values. Our work also demonstrates mones can be interpreted without using a classifier as a proxy.

PDXNet portal: patient-derived Xenograft model, data, workflow and tool discovery.

We created the PDX Network (PDXNet) portal (https://portal.pdxnetwork.org/) to centralize access to the National Cancer Institute-funded PDXNet consortium resources, to facilitate collaboration among researchers and to make these data easily available for research. The portal includes sections for resources, analysis results, metrics for PDXNet activities, data processing protocols and training materials for processing PDX data. Currently, the portal contains PDXNet model information and data resources from 334 new models across 33 cancer types. Tissue samples of these models were deposited in the NCI's Patient-Derived Model Repository (PDMR) for public access. These models have 2134 associated sequencing files from 873 samples across 308 patients, which are hosted on the Cancer Genomics Cloud powered by Seven Bridges and the NCI Cancer Data Service for long-term storage and access with dbGaP permissions. The portal includes results from freely available, robust, validated and standardized analysis workflows on PDXNet sequencing files and PDMR data (3857 samples from 629 patients across 85 disease types). The PDXNet portal is continuously updated with new data and is of significant utility to the cancer research community as it provides a centralized location for PDXNet resources, which support multi-agent treatment studies, determination of sensitivity and resistance mechanisms, and preclinical trials.

Clinical Factors Implicated in Antibiotic Resistance in Helicobacter pylori Patients.

Helicobacter pylori is a common gastric pathogen associated with multiple clinical syndromes, including cancer. Eradication rates of H. pylori remain suboptimal despite the progress made in the past few decades in improving treatment strategies. The low eradication rates are mainly driven by antibiotic resistance of H. pylori. Non-invasive molecular testing to identify patients with antibiotic-resistant H. pylori represents a promising therapeutic avenue, however this technology currently remains limited by availability, costs, and lack of robust validation. Moreover, there is insufficient evidence to demonstrate that resistance-testing-based treatment approaches are superior to appropriately designed empiric strategies. Consensus guidelines recommend use of proven locally effective regimens; however, eradication data are inconsistently generated in several regions of the world. In this review, we describe several clinical factors associated with increased rates of antibiotic resistant H. pylori, including history of previous antibiotic exposure, increasing age, female gender, ethnicity/race, extent of alcohol use, and non-ulcer dyspepsia. Assessment of these factors may aid the clinician in choosing the most appropriate empiric treatment strategy for each patient. Future study should aim to identify locally effective therapies and further explore the clinical factors associated with antibiotic resistance.

A community-based approach to image analysis of cells, tissues and tumors.

Emerging multiplexed imaging platforms provide an unprecedented view of an increasing number of molecular markers at subcellular resolution and the dynamic evolution of tumor cellular composition. As such, they are capable of elucidating cell-to-cell interactions within the tumor microenvironment that impact clinical outcome and therapeutic response. However, the rapid development of these platforms has far outpaced the computational methods for processing and analyzing the data they generate. While being technologically disparate, all imaging assays share many computational requirements for post-collection data processing. As such, our Image Analysis Working Group (IAWG), composed of researchers in the Cancer Systems Biology Consortium (CSBC) and the Physical Sciences - Oncology Network (PS-ON), convened a workshop on "Computational Challenges Shared by Diverse Imaging Platforms" to characterize these common issues and a follow-up hackathon to implement solutions for a selected subset of them. Here, we delineate these areas that reflect major axes of research within the field, including image registration, segmentation of cells and subcellular structures, and identification of cell types from their morphology. We further describe the logistical organization of these events, believing our lessons learned can aid others in uniting the imaging community around self-identified topics of mutual interest, in designing and implementing operational procedures to address those topics and in mitigating issues inherent in image analysis (e.g., sharing exemplar images of large datasets and disseminating baseline solutions to hackathon challenges through open-source code repositories).

Effects of circulatory arrest and cardiopulmonary bypass on cerebral autoregulation in neonatal swine.

BACKGROUND: Cerebral autoregulation mechanisms help maintain adequate cerebral blood flow (CBF) despite changes in cerebral perfusion pressure. Impairment of cerebral autoregulation, during and after cardiopulmonary bypass (CPB), may increase risk of neurologic injury in neonates undergoing surgery. In this study, alterations of cerebral autoregulation were assessed in a neonatal swine model probing four perfusion strategies. METHODS: Neonatal swine (n = 25) were randomized to continuous deep hypothermic cardiopulmonary bypass (DH-CPB, n = 7), deep hypothermic circulatory arrest (DHCA, n = 7), selective cerebral perfusion (SCP, n = 7) at deep hypothermia, or normothermic cardiopulmonary bypass (control, n = 4). The correlation coefficient (LDx) between laser Doppler measurements of CBF and mean arterial blood pressure was computed at initiation and conclusion of CPB. Alterations in cerebral autoregulation were assessed by the change between initial and final LDx measurements. RESULTS: Cerebral autoregulation became more impaired (LDx increased) in piglets that underwent DH-CPB (initial LDx: median 0.15, IQR [0.03, 0.26]; final: 0.45, [0.27, 0.74]; p = 0.02). LDx was not altered in those undergoing DHCA (p > 0.99) or SCP (p = 0.13). These differences were not explained by other risk factors. CONCLUSIONS: In a validated swine model of cardiac surgery, DH-CPB had a significant effect on cerebral autoregulation, whereas DHCA and SCP did not. IMPACT: Approximately half of the patients who survive neonatal heart surgery with cardiopulmonary bypass (CPB) experience neurodevelopmental delays. This preclinical investigation takes steps to elucidate and isolate potential perioperative risk factors of neurologic injury, such as impairment of cerebral autoregulation, associated with cardiac surgical procedures involving CPB. We demonstrate a method to characterize cerebral autoregulation during CPB pump flow changes in a neonatal swine model of cardiac surgery. Cerebral autoregulation was not altered in piglets that underwent deep hypothermic circulatory arrest (DHCA) or selective cerebral perfusion (SCP), but it was altered in piglets that underwent deep hypothermic CBP.

Preoperative high-resolution esophageal manometry and postoperative symptoms in patients undergoing bariatric surgery: a retrospective cohort study.

BACKGROUND: The increasing incidence of obesity has led to a rise in bariatric surgeries. Obesity can be associated with various gastrointestinal symptoms as well as abnormal findings on high-resolution esophageal manometry (HRM). Bariatric procedures have variable effects on esophageal function and may contribute to postoperative symptoms. Preoperative HRM is not performed routinely on patients undergoing bariatric surgery but may identify patients likely to experience postoperative esophageal symptoms via delineation of structural or functional abnormalities. OBJECTIVES: To evaluate whether prebariatric surgery HRM could predict persistent or de novo postoperative esophageal symptoms. SETTING: Academic tertiary care hospital, United States. METHODS: Retrospective data were collected for 20 patients undergoing HRM and 100 controls 18 years and older from May 2012 to May 2015. Propensity score matching was performed to adjust for baseline differences between the 2 groups. Preoperative and postoperative esophageal symptoms (reflux, dysphagia, nausea/vomiting, bloating, fullness, early satiety, pain, and intolerance) were compared between HRM and control patients, and associations among HRM findings, Chicago Classification, and symptoms were analyzed. All included patients had follow-up beyond 3 months postoperatively. Data were analyzed with 2-tailed Fisher's exact test, Wilcoxon rank-sum test, and odds ratio. RESULTS: Compared to controls, patients undergoing preoperative HRM had a higher rate of postoperative chronic intolerance (25% versus 8%, P = .041). This difference was not observed in propensity score matching analysis. Identification of elevated integrated relaxation pressure and esophagogastric junction outflow obstruction predicted chronic intolerance (odds ratio = 21.0; 95% confidence interval: 1.40-314; P = .027 for each). CONCLUSIONS: Preoperative HRM abnormalities were associated with postoperative symptoms in patients undergoing bariatric surgery. HRM can identify patients who are more likely to experience postoperative esophageal symptoms and may aid in discussion of suitability for surgery and selection of bariatric intervention.

Hyperpolarized Carbon-13 MRI for Early Response Assessment of Neoadjuvant Chemotherapy in Breast Cancer Patients.

Hyperpolarized 13C-MRI is an emerging tool for probing tissue metabolism by measuring 13C-label exchange between intravenously injected hyperpolarized [1-13C]pyruvate and endogenous tissue lactate. Here, we demonstrate that hyperpolarized 13C-MRI can be used to detect early response to neoadjuvant therapy in breast cancer. Seven patients underwent multiparametric 1H-MRI and hyperpolarized 13C-MRI before and 7-11 days after commencing treatment. An increase in the lactate-to-pyruvate ratio of approximately 20% identified three patients who, following 5-6 cycles of treatment, showed pathological complete response. This ratio correlated with gene expression of the pyruvate transporter MCT1 and lactate dehydrogenase A (LDHA), the enzyme catalyzing label exchange between pyruvate and lactate. Analysis of approximately 2,000 breast tumors showed that overexpression of LDHA and the hypoxia marker CAIX was associated with reduced relapse-free and overall survival. Hyperpolarized 13C-MRI represents a promising method for monitoring very early treatment response in breast cancer and has demonstrated prognostic potential. SIGNIFICANCE: Hyperpolarized carbon-13 MRI allows response assessment in patients with breast cancer after 7-11 days of neoadjuvant chemotherapy and outperformed state-of-the-art and research quantitative proton MRI techniques.

Characterization of gut microbiome and metabolome in Helicobacter pylori patients in an underprivileged community in the United States.

BACKGROUND: Helicobacter pylori (H. pylori), a bacterium that infects approximately half of the world's population, is associated with various gastrointestinal diseases, including peptic ulcers, non-ulcer dyspepsia, gastric adenocarcinoma, and gastric lymphoma. As the burden of antibiotic resistance increases, the need for new adjunct therapies designed to facilitate H. pylori eradication and reduce negative distal outcomes associated with infection has become more pressing. Characterization of the interactions between H. pylori, the fecal microbiome, and fecal fatty acid metabolism, as well as the mechanisms underlying these interactions, may offer new therapeutic approaches. AIM: To characterize the gut microbiome and metabolome in H. pylori patients in a socioeconomically challenged and underprivileged inner-city community. METHODS: Stool samples from 19 H. pylori patients and 16 control subjects were analyzed. 16S rRNA gene sequencing was performed on normalized pooled amplicons using the Illumina MiSeq System using a MiSeq reagent kit v2. Alpha and beta diversity analyses were performed in QIIME 2. Non-targeted fatty acid analysis of the samples was carried out using gas chromatography-mass spectrometry, which measures the total content of 30 fatty acids in stool after conversion into their corresponding fatty acid methyl esters. Multi-dimensional scaling (MDS) was performed on Bray-Curtis distance matrices created from both the metabolomics and microbiome datasets and a Procrustes test was performed on the metabolomics and microbiome MDS coordinates. RESULTS: Fecal microbiome analysis showed that alpha diversity was lowest in H. pylori patients over 40 years of age compared to control subjects of similar age group. Beta diversity analysis of the samples revealed significant differences in microbial community structure between H. pylori patients and control subjects across all ages. Thirty-eight and six taxa had lower and higher relative abundance in H. pylori patients, respectively. Taxa that were enriched in H. pylori patients included Atopobium, Gemellaceae, Micrococcaceae, Gemellales and Rothia (R. mucilaginosa). Notably, relative abundance of the phylum Verrucomicrobia was decreased in H. pylori patients compared to control subjects. Procrustes analysis showed a significant relationship between the microbiome and metabolome datasets. Stool samples from H. pylori patients showed increases in several fatty acids including the polyunsaturated fatty acids (PUFAs) 22:4n6, 22:5n3, 20:3n6 and 22:2n6, while decreases were noted in other fatty acids including the PUFA 18:3n6. The pattern of changes in fatty acid concentration correlated to the Bacteroidetes:Firmicutes ratio determined by 16S rRNA gene analysis. CONCLUSION: This exploratory study demonstrates H. pylori-associated changes to the fecal microbiome and fecal fatty acid metabolism. Such changes may have implications for improving eradication rates and minimizing associated negative distal outcomes.

Mutant U2AF1-induced alternative splicing of H2afy (macroH2A1) regulates B-lymphopoiesis in mice.

Somatic mutations in spliceosome genes are found in ∼50% of patients with myelodysplastic syndromes (MDS), a myeloid malignancy associated with low blood counts. Expression of the mutant splicing factor U2AF1(S34F) alters hematopoiesis and mRNA splicing in mice. Our understanding of the functionally relevant alternatively spliced target genes that cause hematopoietic phenotypes in vivo remains incomplete. Here, we demonstrate that reduced expression of H2afy1.1, an alternatively spliced isoform of the histone H2A variant gene H2afy, is responsible for reduced B cells in U2AF1(S34F) mice. Deletion of H2afy or expression of U2AF1(S34F) reduces expression of Ebf1 (early B cell factor 1), a key transcription factor for B cell development, and mechanistically, H2AFY is enriched at the EBF1 promoter. Induced expression of H2AFY1.1 in U2AF1(S34F) cells rescues reduced EBF1 expression and B cells numbers in vivo. Collectively, our data implicate alternative splicing of H2AFY as a contributor to lymphopenia induced by U2AF1(S34F) in mice and MDS.

Bayesian multi-source regression and monocyte-associated gene expression predict BCL-2 inhibitor resistance in acute myeloid leukemia.

The FDA recently approved eight targeted therapies for acute myeloid leukemia (AML), including the BCL-2 inhibitor venetoclax. Maximizing efficacy of these treatments requires refining patient selection. To this end, we analyzed two recent AML studies profiling the gene expression and ex vivo drug response of primary patient samples. We find that ex vivo samples often exhibit a general sensitivity to (any) drug exposure, independent of drug target. We observe that this "general response across drugs" (GRD) is associated with FLT3-ITD mutations, clinical response to standard induction chemotherapy, and overall survival. Further, incorporating GRD into expression-based regression models trained on one of the studies improved their performance in predicting ex vivo response in the second study, thus signifying its relevance to precision oncology efforts. We find that venetoclax response is independent of GRD but instead show that it is linked to expression of monocyte-associated genes by developing and applying a multi-source Bayesian regression approach. The method shares information across studies to robustly identify biomarkers of drug response and is broadly applicable in integrative analyses.

Venous Flow Variation Predicts Preoperative Pulmonary Venous Obstruction in Children with Total Anomalous Pulmonary Venous Connection.

BACKGROUND: Identifying preoperative pulmonary venous obstruction in total anomalous pulmonary venous connection is important to guide treatment planning and risk prognostication. No standardized echocardiographic definition of obstruction exists in the literature. Definitions based on absolute velocities are affected by technical limitations and variations in pulmonary venous return. The authors developed a metric to quantify pulmonary venous blood flow variation: pulmonary venous variability index (PVVI). The aim of this study was to demonstrate its accuracy in defining obstruction. METHODS: All patients with total anomalous pulmonary venous connection at a single institution were identified. Echocardiograms were reviewed, and maximum (Vmax), mean (Vmean), and minimum (Vmin) velocities along the pulmonary venous pathway were measured. PVVI was defined as (Vmax - Vmin)/Vmean. These metrics were compared with pressures measured on cardiac catheterization. Echocardiographic measures were then compared between patients with and without clinical preoperative obstruction (defined as a need for preoperative intubation, catheter-based intervention, or surgery within 1 day of diagnosis), as well as pulmonary edema by chest radiography and markers of lactic acidosis. One hundred thirty-seven patients were included, with 22 having catheterization pressure recordings. RESULTS: Vmax and Vmean were not different between patients with catheter gradients ≥ 4 and < 4 mm Hg, while PVVI was significantly lower and Vmin higher in those with gradients ≥ 4 mm Hg. The composite outcome of preoperative obstruction occurred in 51 patients (37%). Absolute velocities were not different between patients with and without clinical obstruction, while PVVI was significantly lower in patients with obstruction. All metrics except Vmax were associated with pulmonary edema; none were associated with blood gas metrics. CONCLUSIONS: The authors developed a novel quantitative metric of pulmonary venous flow, which was superior to traditional echocardiographic metrics. Decreased PVVI was highly associated with elevated gradients measured by catheterization and clinical preoperative obstruction. These results should aid risk assessment and diagnosis preoperatively in patients with total anomalous pulmonary venous connection.