Inflammation-associated intramyocellular lipid alterations in human pancreatic cancer cachexia.

BACKGROUND: Cancer cachexia is a multifactorial metabolic syndrome characterized by systemic inflammation and ongoing skeletal muscle loss resulting in weakness, poor quality of life, and decreased survival. Whereas lipid accumulation in skeletal muscle is associated with cancer cachexia as well as the prognosis of cancer patients, surprisingly little is known about the nature of the lipids that accumulate in the muscle during cachexia, and whether this is related to inflammation. We aimed to identify the types and distributions of intramyocellular lipids in patients with and without cancer cachexia. METHODS: Rectus abdominis muscle biopsies were collected during surgery of patients with pancreatic ductal adenocarcinoma (n = 10 without cachexia, n = 20 cachectic without inflammation (CRP < 10 mg/L), n = 10 cachectic with inflammation (CRP ≥ 10 mg/L). L3-CT scans were analysed to assess body composition based on validated thresholds in Hounsfield units (HU). Muscle sections were stained with Oil-Red O and H&E to assess general lipid accumulation and atrophy. Untargeted lipidomic analyses were performed on laser-microdissected myotubes using LC-MS/MS. The spatial distribution of intramyocellular lipids with differential abundance between groups was visualized by mass-spectrometry imaging. Genes coding for inflammation markers and enzymes involved in de novo ceramide synthesis were studied by qPCR. RESULTS: Muscle radiation attenuation was lower in cachectic patients with inflammation (median 24.3 [18.6-30.8] HU) as compared with those without inflammation (34.2 [29.3-38.7] HU, P = 0.033) or no cachexia (37.4 [33.9-42.9] HU, P = 0.012). Accordingly, intramyocellular lipid content was lower in non-cachectic patients (1.9 [1.6-2.1]%) as compared with those with cachexia with inflammation (5.5 [4.5-7.3]%, P = 0.002) or without inflammation (4.8 [2.6-6.0]%, P = 0.017). Intramyocellular lipid accumulation was associated with both local IL-6 mRNA levels (rs = 0.57, P = 0.015) and systemic CRP levels (rs = 0.49, P = 0.024). Compared with non-cachectic subjects, cachectic patients had a higher relative abundance of intramyocellular glycerophospholipids and a lower relative abundance of glycerolipids. Furthermore, increases in several intramyocellular lipids such as SM(d36:1), PC(34:1), and TG(48:1) were found in cachectic patients with inflammation and correlated with specific cachexia features. Altered intramyocellular lipid species such as PC(34:1), LPC(18:2), and TG(48:1) showed an uneven distribution in muscle sections of cachectic and non-cachectic patients, with areas featuring abundance of these lipids next to areas almost devoid of them. CONCLUSIONS: Intramyocellular lipid accumulation in patients with cachexia is associated with both local and systemic inflammation, and characterized by changes in defined lipid species such as glycerolipids and glycerophospholipids.

Sex differences in symptomatology and immune profiles of Long COVID.

Strong sex differences in the frequencies and manifestations of Long COVID (LC) have been reported with females significantly more likely than males to present with LC after acute SARS-CoV-2 infection 1-7 . However, whether immunological traits underlying LC differ between sexes, and whether such differences explain the differential manifestations of LC symptomology is currently unknown. Here, we performed sex-based multi-dimensional immune-endocrine profiling of 165 individuals 8 with and without LC in an exploratory, cross-sectional study to identify key immunological traits underlying biological sex differences in LC. We found that female and male participants with LC experienced different sets of symptoms, and distinct patterns of organ system involvement, with female participants suffering from a higher symptom burden. Machine learning approaches identified differential sets of immune features that characterized LC in females and males. Males with LC had decreased frequencies of monocyte and DC populations, elevated NK cells, and plasma cytokines including IL-8 and TGF-ß-family members. Females with LC had increased frequencies of exhausted T cells, cytokine-secreting T cells, higher antibody reactivity to latent herpes viruses including EBV, HSV-2, and CMV, and lower testosterone levels than their control female counterparts. Testosterone levels were significantly associated with lower symptom burden in LC participants over sex designation. These findings suggest distinct immunological processes of LC in females and males and illuminate the crucial role of immune-endocrine dysregulation in sex-specific pathology.

Longitudinal single-cell transcriptional dynamics throughout neurodegeneration in SCA1.

Neurodegeneration is a protracted process involving progressive changes in myriad cell types that ultimately results in the death of vulnerable neuronal populations. To dissect how individual cell types within a heterogeneous tissue contribute to the pathogenesis and progression of a neurodegenerative disorder, we performed longitudinal single-nucleus RNA sequencing of mouse and human spinocerebellar ataxia type 1 (SCA1) cerebellar tissue, establishing continuous dynamic trajectories of each cell population. Importantly, we defined the precise transcriptional changes that precede loss of Purkinje cells and, for the first time, identified robust early transcriptional dysregulation in unipolar brush cells and oligodendroglia. Finally, we applied a deep learning method to predict disease state accurately and identified specific features that enable accurate distinction of wild-type and SCA1 cells. Together, this work reveals new roles for diverse cerebellar cell types in SCA1 and provides a generalizable analysis framework for studying neurodegeneration.

scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles.

Many deep learning-based methods have been proposed to handle complex single-cell data. Deep learning approaches may also prove useful to jointly analyze single-cell RNA sequencing (scRNA-seq) and single-cell T cell receptor sequencing (scTCR-seq) data for novel discoveries. We developed scNAT, a deep learning method that integrates paired scRNA-seq and scTCR-seq data to represent data in a unified latent space for downstream analysis. We demonstrate that scNAT is capable of removing batch effects, and identifying cell clusters and a T cell migration trajectory from blood to cerebrospinal fluid in multiple sclerosis.

Causal identification of single-cell experimental perturbation effects with CINEMA-OT.

Recent advancements in single-cell technologies allow characterization of experimental perturbations at single-cell resolution. While methods have been developed to analyze such experiments, the application of a strict causal framework has not yet been explored for the inference of treatment effects at the single-cell level. Here we present a causal-inference-based approach to single-cell perturbation analysis, termed CINEMA-OT (causal independent effect module attribution + optimal transport). CINEMA-OT separates confounding sources of variation from perturbation effects to obtain an optimal transport matching that reflects counterfactual cell pairs. These cell pairs represent causal perturbation responses permitting a number of novel analyses, such as individual treatment-effect analysis, response clustering, attribution analysis, and synergy analysis. We benchmark CINEMA-OT on an array of treatment-effect estimation tasks for several simulated and real datasets and show that it outperforms other single-cell perturbation analysis methods. Finally, we perform CINEMA-OT analysis of two newly generated datasets: (1) rhinovirus and cigarette-smoke-exposed airway organoids, and (2) combinatorial cytokine stimulation of immune cells. In these experiments, CINEMA-OT reveals potential mechanisms by which cigarette-smoke exposure dulls the airway antiviral response, as well as the logic that governs chemokine secretion and peripheral immune cell recruitment.

Distinguishing features of long COVID identified through immune profiling.

Post-acute infection syndromes may develop after acute viral disease1. Infection with SARS-CoV-2 can result in the development of a post-acute infection syndrome known as long COVID. Individuals with long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions2-4. However, the biological processes that are associated with the development and persistence of these symptoms are unclear. Here 275 individuals with or without long COVID were enrolled in a cross-sectional study that included multidimensional immune phenotyping and unbiased machine learning methods to identify biological features associated with long COVID. Marked differences were noted in circulating myeloid and lymphocyte populations relative to the matched controls, as well as evidence of exaggerated humoral responses directed against SARS-CoV-2 among participants with long COVID. Furthermore, higher antibody responses directed against non-SARS-CoV-2 viral pathogens were observed among individuals with long COVID, particularly Epstein-Barr virus. Levels of soluble immune mediators and hormones varied among groups, with cortisol levels being lower among participants with long COVID. Integration of immune phenotyping data into unbiased machine learning models identified the key features that are most strongly associated with long COVID status. Collectively, these findings may help to guide future studies into the pathobiology of long COVID and help with developing relevant biomarkers.

Anatomical Diversity of the Adult Corticospinal Tract Revealed by Single-Cell Transcriptional Profiling.

The corticospinal tract (CST) forms a central part of the voluntary motor apparatus in all mammals. Thus, injury, disease, and subsequent degeneration within this pathway result in chronic irreversible functional deficits. Current strategies to repair the damaged CST are suboptimal in part because of underexplored molecular heterogeneity within the adult tract. Here, we combine spinal retrograde CST tracing with single-cell RNA sequencing (scRNAseq) in adult male and female mice to index corticospinal neuron (CSN) subtypes that differentially innervate the forelimb and hindlimb. We exploit publicly available datasets to confer anatomic specialization among CSNs and show that CSNs segregate not only along the forelimb and hindlimb axis but also by supraspinal axon collateralization. These anatomically defined transcriptional data allow us to use machine learning tools to build classifiers that discriminate between CSNs and cortical layer 2/3 and nonspinally terminating layer 5 neurons in M1 and separately identify limb-specific CSNs. Using these tools, CSN subtypes can be differentially identified to study postnatal patterning of the CST in vivo, leveraged to screen for novel limb-specific axon growth survival and growth activators in vitro, and ultimately exploited to repair the damaged CST after injury and disease.SIGNIFICANCE STATEMENT Therapeutic interventions designed to repair the damaged CST after spinal cord injury have remained functionally suboptimal in part because of an incomplete understanding of the molecular heterogeneity among subclasses of CSNs. Here, we combine spinal retrograde labeling with scRNAseq and annotate a CSN index by the termination pattern of their primary axon in the cervical or lumbar spinal cord and supraspinal collateral terminal fields. Using machine learning we have confirmed the veracity of our CSN gene lists to train classifiers to identify CSNs among all classes of neurons in primary motor cortex to study the development, patterning, homeostasis, and response to injury and disease, and ultimately target streamlined repair strategies to this critical motor pathway.

Identifying radiomics signatures in body composition imaging for the prediction of outcome following pancreatic cancer resection.

Background: Computerized radiological image analysis (radiomics) enables the investigation of image-derived phenotypes by extracting large numbers of quantitative features. We hypothesized that radiomics features may contain prognostic information that enhances conventional body composition analysis. We aimed to investigate whether body composition-associated radiomics features hold additional value over conventional body composition analysis and clinical patient characteristics used to predict survival of pancreatic ductal adenocarcinoma (PDAC) patients. Methods: Computed tomography images of 304 patients undergoing elective pancreatic cancer resection were analysed. 2D radiomics features were extracted from skeletal muscle and subcutaneous and visceral adipose tissue (SAT and VAT) compartments from a single slice at the third lumbar vertebra. The study population was randomly split (80:20) into training and holdout subsets. Feature ranking with Least Absolute Shrinkage Selection Operator (LASSO) followed by multivariable stepwise Cox regression in 1000 bootstrapped re-samples of the training data was performed and tested on the holdout data. The fitted regression predictors were used as "scores" for a clinical (C-Score), body composition (B-Score), and radiomics (R-Score) model. To stratify patients into the highest 25% and lowest 25% risk of mortality compared to the middle 50%, the Harrell Concordance Index was used. Results: Based on LASSO and stepwise cox regression for overall survival, ASA ≥3 and age were the most important clinical variables and constituted the C-score, and VAT-index (VATI) was the most important body composition variable and constituted the B-score. Three radiomics features (SATI_original_shape2D_Perimeter, VATI_original_glszm_SmallAreaEmphasis, and VATI_original_firstorder_Maximum) emerged as the most frequent set of features and yielded an R-Score. Of the mean concordance indices of C-, B-, and R-scores, R-score performed best (0.61, 95% CI 0.56-0.65, p<0.001), followed by the C-score (0.59, 95% CI 0.55-0.63, p<0.001) and B-score (0.55, 95% CI 0.50-0.60, p=0.03). Kaplan-Meier projection revealed that C-, B, and R-scores showed a clear split in the survival curves in the training set, although none remained significant in the holdout set. Conclusion: It is feasible to implement a data-driven radiomics approach to body composition imaging. Radiomics features provided improved predictive performance compared to conventional body composition variables for the prediction of overall survival of PDAC patients undergoing primary resection.

A machine learning method for the identification and characterization of novel COVID-19 drug targets.

In addition to vaccines, the World Health Organization sees novel medications as an urgent matter to fight the ongoing COVID-19 pandemic. One possible strategy is to identify target proteins, for which a perturbation by an existing compound is likely to benefit COVID-19 patients. In order to contribute to this effort, we present GuiltyTargets-COVID-19 ( https://guiltytargets-covid.eu/ ), a machine learning supported web tool to identify novel candidate drug targets. Using six bulk and three single cell RNA-Seq datasets, together with a lung tissue specific protein-protein interaction network, we demonstrate that GuiltyTargets-COVID-19 is capable of (i) prioritizing meaningful target candidates and assessing their druggability, (ii) unraveling their linkage to known disease mechanisms, (iii) mapping ligands from the ChEMBL database to the identified targets, and (iv) pointing out potential side effects in the case that the mapped ligands correspond to approved drugs. Our example analyses identified 4 potential drug targets from the datasets: AKT3 from both the bulk and single cell RNA-Seq data as well as AKT2, MLKL, and MAPK11 in the single cell experiments. Altogether, we believe that our web tool will facilitate future target identification and drug development for COVID-19, notably in a cell type and tissue specific manner.

Nasal host response-based screening for undiagnosed respiratory viruses: a pathogen surveillance and detection study.

BACKGROUND: Symptomatic patients who test negative for common viruses are an important possible source of unrecognised or emerging pathogens, but metagenomic sequencing of all samples is inefficient because of the low likelihood of finding a pathogen in any given sample. We aimed to determine whether nasopharyngeal CXCL10 screening could be used as a strategy to enrich for samples containing undiagnosed viruses. METHODS: In this pathogen surveillance and detection study, we measured CXCL10 concentrations from nasopharyngeal swabs from patients in the Yale New Haven health-care system, which had been tested at the Yale New Haven Hospital Clinical Virology Laboratory (New Haven, CT, USA). Patients who tested negative for a panel of respiratory viruses using multiplex PCR during Jan 23-29, 2017, or March 3-14, 2020, were included. We performed host and pathogen RNA sequencing (RNA-Seq) and analysis for viral reads on samples with CXCL10 higher than 1 ng/mL or CXCL10 testing and quantitative RT-PCR (RT-qPCR) for SARS-CoV-2. We used RNA-Seq and cytokine profiling to compare the host response to infection in samples that were virus positive (rhinovirus, seasonal coronavirus CoV-NL63, or SARS-CoV-2) and virus negative (controls). FINDINGS: During Jan 23-29, 2017, 359 samples were tested for ten viruses on the multiplex PCR respiratory virus panel (RVP). 251 (70%) were RVP negative. 60 (24%) of 251 samples had CXCL10 higher than 150 pg/mL and were identified for further analysis. 28 (47%) of 60 CXCL10-high samples were positive for seasonal coronaviruses. 223 (89%) of 251 samples were PCR negative for 15 viruses and, of these, CXCL10-based screening identified 32 (13%) samples for further analysis. Of these 32 samples, eight (25%) with CXCL10 concentrations higher than 1 ng/mL and sufficient RNA were selected for RNA-Seq. Microbial RNA analysis showed the presence of influenza C virus in one sample and revealed RNA reads from bacterial pathobionts in four (50%) of eight samples. Between March 3 and March 14, 2020, 375 (59%) of 641 samples tested negative for 15 viruses on the RVP. 32 (9%) of 375 samples had CXCL10 concentrations ranging from 100 pg/mL to 1000 pg/mL and four of those were positive for SARS-CoV-2. CXCL10 elevation was statistically significant, and a distinguishing feature was found in 28 (8%) of 375 SARS-CoV-2-negative samples versus all four SARS-CoV-2-positive samples (p=4·4 × 10-5). Transcriptomic signatures showed an interferon response in virus-positive samples and an additional neutrophil-high hyperinflammatory signature in samples with high amounts of bacterial pathobionts. The CXCL10 cutoff for detecting a virus was 166·5 pg/mL for optimal sensitivity and 1091·0 pg/mL for specificity using a clinic-ready automated microfluidics-based immunoassay. INTERPRETATION: These results confirm CXCL10 as a robust nasopharyngeal biomarker of viral respiratory infection and support host response-based screening followed by metagenomic sequencing of CXCL10-high samples as a practical approach to incorporate clinical samples into pathogen discovery and surveillance efforts. FUNDING: National Institutes of Health, the Hartwell Foundation, the Gruber Foundation, Fast Grants for COVID-19 research from the Mercatus Center, and the Huffman Family Donor Advised Fund.

A No-Chest-Drain Policy After Video-assisted Thoracoscopic Surgery Wedge Resection in Selected Patients: Our 12-Year Experience.

BACKGROUND: Postoperative pleural drainage omission after video-assisted thoracoscopic surgery (VATS) for wedge resections may facilitate faster recovery. This retrospective cohort study presents our 12-year experience with omitting thoracic drainage in patients who underwent a VATS wedge resection, aiming to assess its safety and efficacy. METHODS: Records from consecutive patients who underwent a VATS wedge resection at our hospital between February 2008 and October 2020 were retrospectively reviewed and assessed for eligibility. Patient and surgical characteristics as well as postoperative data were collected and compared between patients who received a chest drain (CD) or received no chest drain (NCD) after surgery. Univariable and multivariable analyses were performed to determine whether drain placement was associated with complications (primary outcome), and major complications requiring pleural drainage or length of hospital stay (secondary outcomes). RESULTS: Data of 348 patients were analyzed. The drainless group (n = 98) and drain group (n = 237) were significantly different in the following baseline and surgical characteristics: sex, pulmonary function, interstitial lung disease, final pathology, number of wedges, and surgical approach. No significant differences were detected in postoperative complications (NCD 8.2%, CD 14.8%; P = .10), major complications (NCD 5.1%, CD 5.1%; P > .99), or complications requiring pleural drainage (NCD 5.1%, CD 3.8%; P = .56). The drainless group did show a significantly shorter hospitalization (NCD 2 ± 2, CD 3 ± 2 days; P < .001). Multivariable analyses revealed that drain placement was not significantly correlated with postoperative complications. In contrast, prolonged hospitalization was significantly influenced by drain placement. CONCLUSIONS: Our findings suggest that a no-chest-drain policy after VATS wedge resections can safely fast-track rehabilitation for selected patients.

Distinguishing features of Long COVID identified through immune profiling.

SARS-CoV-2 infection can result in the development of a constellation of persistent sequelae following acute disease called post-acute sequelae of COVID-19 (PASC) or Long COVID 1-3 . Individuals diagnosed with Long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions 1-3 ; however, the basic biological mechanisms responsible for these debilitating symptoms are unclear. Here, 215 individuals were included in an exploratory, cross-sectional study to perform multi-dimensional immune phenotyping in conjunction with machine learning methods to identify key immunological features distinguishing Long COVID. Marked differences were noted in specific circulating myeloid and lymphocyte populations relative to matched control groups, as well as evidence of elevated humoral responses directed against SARS-CoV-2 among participants with Long COVID. Further, unexpected increases were observed in antibody responses directed against non-SARS-CoV-2 viral pathogens, particularly Epstein-Barr virus. Analysis of circulating immune mediators and various hormones also revealed pronounced differences, with levels of cortisol being uniformly lower among participants with Long COVID relative to matched control groups. Integration of immune phenotyping data into unbiased machine learning models identified significant distinguishing features critical in accurate classification of Long COVID, with decreased levels of cortisol being the most significant individual predictor. These findings will help guide additional studies into the pathobiology of Long COVID and may aid in the future development of objective biomarkers for Long COVID.

Interspecies commensal interactions have nonlinear impacts on host immunity.

The impacts of individual commensal microbes on immunity and disease can differ dramatically depending on the surrounding microbial context; however, the specific bacterial combinations that dictate divergent immunological outcomes remain largely undefined. Here, we characterize an immunostimulatory Allobaculum species from an inflammatory bowel disease patient that exacerbates colitis in gnotobiotic mice. Allobaculum inversely associates with the taxonomically divergent immunostimulatory species Akkermansia muciniphila in human-microbiota-associated mice and human cohorts. Co-colonization with A. muciniphila ameliorates Allobaculum-induced intestinal epithelial cell activation and colitis in mice, whereas Allobaculum blunts the A.muciniphila-specific systemic antibody response and reprograms the immunological milieu in mesenteric lymph nodes by blocking A.muciniphila-induced dendritic cell activation and T cell expansion. These studies thus identify a pairwise reciprocal interaction between human gut bacteria that dictates divergent immunological outcomes. Furthermore, they establish a generalizable framework to define the contextual cues contributing to the "incomplete penetrance" of microbial impacts on human disease.

Body Composition Is a Predictor for Postoperative Complications After Gastrectomy for Gastric Cancer: a Prospective Side Study of the LOGICA Trial.

PURPOSE: There is a lack of prospective studies evaluating the effects of body composition on postoperative complications after gastrectomy in a Western population with predominantly advanced gastric cancer. METHODS: This is a prospective side study of the LOGICA trial, a multicenter randomized trial on laparoscopic versus open gastrectomy for gastric cancer. Trial patients who received preoperative chemotherapy followed by gastrectomy with an available preoperative restaging abdominal computed tomography (CT) scan were included. The CT scan was used to calculate the mass (M) and radiation attenuation (RA) of skeletal muscle (SM), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT). These variables were expressed as Z-scores, depicting how many standard deviations each patient's CT value differs from the sex-specific study sample mean. Primary outcome was the association of each Z-score with the occurrence of a major postoperative complication (Clavien-Dindo grade ≥ 3b). RESULTS: From 2015 to 2018, a total of 112 patients were included. A major postoperative complication occurred in 9 patients (8%). A high SM-M Z-score was associated with a lower risk of major postoperative complications (RR 0.47, 95% CI 0.28-0.78, p = 0.004). Furthermore, high VAT-RA Z-scores and SAT-RA Z-scores were associated with a higher risk of major postoperative complications (RR 2.82, 95% CI 1.52-5.23, p = 0.001 and RR 1.95, 95% CI 1.14-3.34, p = 0.015, respectively). VAT-M, SAT-M, and SM-RA Z-scores showed no significant associations. CONCLUSION: Preoperative low skeletal muscle mass and high visceral and subcutaneous adipose tissue radiation attenuation (indicating fat depleted of triglycerides) were associated with a higher risk of developing a major postoperative complication in patients treated with preoperative chemotherapy followed by gastrectomy.

Single-cell multiomics reveals persistence of HIV-1 in expanded cytotoxic T cell clones.

Understanding the drivers and markers of clonally expanding HIV-1-infected CD4+ T cells is essential for HIV-1 eradication. We used single-cell ECCITE-seq, which captures surface protein expression, cellular transcriptome, HIV-1 RNA, and TCR sequences within the same single cell to track clonal expansion dynamics in longitudinally archived samples from six HIV-1-infected individuals (during viremia and after suppressive antiretroviral therapy) and two uninfected individuals, in unstimulated conditions and after CMV and HIV-1 antigen stimulation. Despite antiretroviral therapy, persistent antigen and TNF responses shaped T cell clonal expansion. HIV-1 resided in Th1-polarized, antigen-responding T cells expressing BCL2 and SERPINB9 that may resist cell death. HIV-1 RNA+ T cell clones were larger in clone size, established during viremia, persistent after viral suppression, and enriched in GZMB+ cytotoxic effector memory Th1 cells. Targeting HIV-1-infected cytotoxic CD4+ T cells and drivers of clonal expansion provides another direction for HIV-1 eradication.

Prdm6 controls heart development by regulating neural crest cell differentiation and migration.

The molecular mechanisms that drive the acquisition of distinct neural crest cell (NCC) fates is still poorly understood. Here, we identified Prdm6 as an epigenetic modifier that temporally and spatially regulates the expression of NCC specifiers and determines the fate of a subset of migrating cardiac NCCs (CNCCs). Using transcriptomic analysis and genetic and fate mapping approaches in transgenic mice, we showed that disruption of Prdm6 was associated with impaired CNCC differentiation, delamination, and migration and led to patent ductus arteriosus (DA) and ventricular noncompaction. Bulk and single-cell RNA-Seq analyses of the DA and CNCCs identified Prdm6 as a regulator of a network of CNCC specification genes, including Wnt1, Tfap2b, and Sox9. Loss of Prdm6 in CNCCs diminished its expression in the pre-epithelial-mesenchymal transition (pre-EMT) cluster, resulting in the retention of NCCs in the dorsal neural tube. This defect was associated with diminished H4K20 monomethylation and G1-S progression and augmented Wnt1 transcript levels in pre-EMT and neural tube clusters, which we showed was the major driver of the impaired CNCC migration. Altogether, these findings revealed Prdm6 as a key regulator of CNCC differentiation and migration and identified Prdm6 and its regulated network as potential targets for the treatment of congenital heart diseases.

Human pancreatic tumour organoid-derived factors enhance myogenic differentiation.

BACKGROUND: Most patients with pancreatic cancer develop cachexia, which is characterized by progressive muscle loss. The mechanisms underlying muscle loss in cancer cachexia remain elusive. Pancreatic tumour organoids are 3D cell culture models that retain key characteristics of the parent tumour. We aimed to investigate the effect of pancreatic tumour organoid-derived factors on processes that determine skeletal muscle mass, including the regulation of muscle protein turnover and myogenesis. METHODS: Conditioned medium (CM) was collected from human pancreatic cancer cell lines (PK-45H, PANC-1, PK-1, and KLM-1), pancreatic tumour organoid cultures from a severely cachectic (PANCO-9a) and a non-cachectic patient (PANCO-12a), and a normal pancreas organoid culture. Differentiating C2C12 myoblasts and mature C2C12 myotubes were exposed to CM for 24 h or maintained in control medium. In myotubes, NF-kB activation was monitored using a NF-κB luciferase reporter construct, and mRNA expression of E3-ubiquitin ligases and REDD1 was analysed by RT-qPCR. C2C12 myoblast proliferation and differentiation were monitored by live cell imaging and myogenic markers and myosin heavy chain (MyHC) isoforms were assessed by RT-qPCR. RESULTS: Whereas CM from PK-1 and KLM-1 cells significantly induced NF-κB activation in C2C12 myotubes (PK-1: 3.1-fold, P < 0.001; KLM-1: 2.1-fold, P = 0.01), Atrogin-1/MAFbx and MuRF1 mRNA were only minimally and inconsistently upregulated by the CM of pancreatic cancer cell lines. Similarly, E3-ubiquitin ligases and REDD1 mRNA expression in myotubes were not altered by exposure to pancreatic tumour organoid CM. Compared with the control condition, CM from both PANCO-9a and PANCO-12a tumour organoids increased proliferation of myoblasts, which was accompanied by significant downregulation of the satellite cell marker paired-box 7 (PAX7) (PANCO-9a: -2.1-fold, P < 0.001; PANCO-12a: -2.0-fold, P < 0.001) and myogenic factor 5 (MYF5) (PANCO-9a: -2.1-fold, P < 0.001; PANCO-12a: -1.8-fold, P < 0.001) after 48 h of differentiation. Live cell imaging revealed accelerated alignment and fusion of myoblasts exposed to CM from PANCO-9a and PANCO-12a, which was in line with significantly increased Myomaker mRNA expression levels (PANCO-9a: 2.4-fold, P = 0.001; PANCO-12a: 2.2-fold, P = 0.004). These morphological and transcriptional alterations were accompanied by increased expression of muscle differentiation markers such as MyHC-IIB (PANCO-9a: 2.5-fold, P = 0.04; PANCO-12a: 3.1-fold, P = 0.006). Although the impact of organoid CM on myogenesis was not associated with the cachexia phenotype of the donor patients, it was specific for tumour organoids, as CM of control pancreas organoids did not modulate myogenic fusion. CONCLUSIONS: These data show that pancreatic tumour organoid-derived factors alter the kinetics of myogenesis, which may eventually contribute to impaired muscle mass maintenance in cancer cachexia.

Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19.

Dysregulated immune responses against the SARS-CoV-2 virus are instrumental in severe COVID-19. However, the immune signatures associated with immunopathology are poorly understood. Here we use multi-omics single-cell analysis to probe the dynamic immune responses in hospitalized patients with stable or progressive course of COVID-19, explore V(D)J repertoires, and assess the cellular effects of tocilizumab. Coordinated profiling of gene expression and cell lineage protein markers shows that S100Ahi/HLA-DRlo classical monocytes and activated LAG-3hi T cells are hallmarks of progressive disease and highlights the abnormal MHC-II/LAG-3 interaction on myeloid and T cells, respectively. We also find skewed T cell receptor repertories in expanded effector CD8+ clones, unmutated IGHG+ B cell clones, and mutated B cell clones with stable somatic hypermutation frequency over time. In conclusion, our in-depth immune profiling reveals dyssynchrony of the innate and adaptive immune interaction in progressive COVID-19.

The association between preoperative body composition and aerobic fitness in patients scheduled for colorectal surgery.

AIM: Although cardiopulmonary exercise testing (CPET) is considered the gold standard, a preoperative abdominal CT scan might also provide information concerning preoperative aerobic fitness for risk assessment. This study aimed to investigate the association between preoperative CT-scan-derived body composition variables and preoperative CPET variables of aerobic fitness in colorectal surgery. METHOD: In this retrospective cohort study, CT images at level L3 were analysed for skeletal muscle mass, skeletal muscle radiation attenuation, visceral adipose tissue (VAT) mass and subcutaneous adipose tissue mass. Regression analyses were performed to investigate the relation between CT-scan-derived body composition variables, CPET-derived aerobic fitness and other preoperative patient-related variables. Logistic regression analysis was performed to predict a preoperative anaerobic threshold (AT) ≤ 11.1 ml/kg/min as cut-off for having a high risk for postoperative complications. RESULTS: Data from 78 patients (45 men; mean [SD] age 74.5 [6.4 years]) were analysed. A correlation coefficient of 0.55 was observed between absolute AT and skeletal muscle mass index. Absolute AT (R2 of 51.1%) was lower in patients with a lower skeletal muscle mass index, together with higher age, lower body mass and higher American Society of Anesthesiologists (ASA) score. Higher ASA score (odds ratio 5.64; P = 0.033) and higher VAT mass (odds ratio 1.02; P = 0.036) were associated with an increased risk of an AT ≤ 11.1 ml/kg/min. CONCLUSION: Body composition variables from the preoperative CT scan were moderately associated with preoperative CPET-derived aerobic fitness. Higher ASA score and higher VAT mass were associated with an increased risk of an AT ≤ 11.1 ml/kg/min.

Gut microbiota and short-chain fatty acid alterations in cachectic cancer patients.

BACKGROUND: Cancer cachexia is characterized by a negative energy balance, muscle and adipose tissue wasting, insulin resistance, and systemic inflammation. Because of its strong negative impact on prognosis and its multifactorial nature that is still not fully understood, cachexia remains an important challenge in the field of cancer treatment. Recent animal studies indicate that the gut microbiota is involved in the pathogenesis and manifestation of cancer cachexia, but human data are lacking. The present study investigates gut microbiota composition, short-chain fatty acids (SCFA), and inflammatory parameters in human cancer cachexia. METHODS: Faecal samples were prospectively collected in patients (N = 107) with pancreatic cancer, lung cancer, breast cancer, or ovarian cancer. Household partners (N = 76) of the patients were included as healthy controls with similar diet and environmental conditions. Patients were classified as cachectic if they lost >5% body weight in the last 6 months. Gut microbiota composition was analysed by sequencing of the 16S rRNA V4 gene region. Faecal SCFA levels were quantified by gas chromatography. Faecal calprotectin was assessed with enzyme-linked immunosorbent assay. Serum C-reactive protein and leucocyte counts were retrieved from medical records. RESULTS: Cachexia prevalence was highest in pancreatic cancer (66.7%), followed by ovarian cancer (25%), lung cancer (20.8%), and breast cancer (17.3%). Microbial α-diversity was not significantly different between cachectic cancer patients (N = 33), non-cachectic cancer patients (N = 74), or healthy controls (N = 76) (species richness P = 0.31; Shannon effective index P = 0.46). Community structure (ß-diversity) tended to differ between these groups (P = 0.053), although overall differences were subtle and no clear clustering of samples was observed. Proteobacteria (P < 0.001), an unknown genus from the Enterobacteriaceae family (P < 0.01), and Veillonella (P < 0.001) were more abundant among cachectic cancer patients. Megamonas (P < 0.05) and Peptococcus (P < 0.001) also showed differential abundance. Faecal levels of all SCFA tended to be lower in cachectic cancer patients, but only acetate concentrations were significantly reduced (P < 0.05). Faecal calprotectin levels were positively correlated with the abundance of Peptococcus, unknown Enterobacteriaceae, and Veillonella. We also identified several correlations and interactions between clinical and microbial parameters. CONCLUSIONS: This clinical study provided the first insights into the alterations of gut microbiota composition and SCFA levels that occur in cachectic cancer patients and how they are related to inflammatory parameters. These results pave the way for further research examining the role of the gut microbiota in cancer cachexia and its potential use as therapeutic target.