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Zhao, J.

Publications and source records attributed to Zhao, J..

At least 595 records · Page 33Linked to original sources

Genome structure and evolution of Antirrhnum majus L.

Snapdragon (Antirrhinum majus L.), a member of Plantaginaceae, is an important model for plant genetics and molecular studies on plant growth and development, transposon biology and self-incompatibility. Here we report a high-quality genome assembly of A. majus cultivated JI7 (A. majus cv.JI7) of a 510 Mb with 37,714 annotated protein-coding genes. The scaffolds covering 97.12% of the assembled genome were anchored on 8 chromosomes. Comparative and evolutionary analyses revealed that Plantaginaceae and Solanaceae diverged from their most recent ancestor around 62 million years ago (MYA). We also revealed the genetic architectures associated with complex traits such as flower asymmetry and self-incompatibility including a unique TCP duplication around 46-49 MYA and a near complete{psi} S-locus of ca.2 Mb. The genome sequence obtained in this study not only provides the first genome sequenced from Plantaginaceae but also bring the popular plant model system of Antirrhinum into a genomic age.

genomics↗

Relationship between ecological stoichiometry and community diversity of plant ecosystems in the upper reaches of the Tarim River, China

AimAlthough it is commonly proposed that nutrient cycling can impact plant community diversity, this relationship has not been fully examined in arid and semi-arid zones. Here, we expand on the framework for evaluating the relationship between biodiversity and ecological stoichiometry by scaling up from the level of the community.\n\nLocationThe upper reaches of the Tarim River (Northwest China, 80{degrees}10-84{degrees}36E, 0{degrees}25-41{degrees}10N).\n\nMethodsWe used multivariate analysis of variance to compare the stoichiometric characteristics and species diversity indices of sampled plant communities. We also measured carbon (C), nitrogen (N), and phosphorous (P) content of plants. We then assessed correlations between community stoichiometry and species diversity through structural equation models (SEM) and redundancy analysis (RDA).\n\nResultsWe found that the differences between stoichiometric characteristics and community diversity indices were highly significant. The Margalef index was strongly related to C and P content. The Simpsons index and Shannon-Weaner index were most strongly correlated with C content. Pielous index was closely related to C and N contents, and the C:N and C:P ratios were important at driving ecological dominance.\n\nMain ConclusionsOur study highlights the importance of ecological stoichiometry in driving community assembly and diversity within a desert ecosystems in northwestern China. The relationship between eclogical stoichiometry in the desert plant community had an effect on species diversity, and it was a good indicator of plant community diversity.

ecology↗

Rapid detection of cytochrome cd1-containing nitrite reductase encoding gene nirS with loop-mediated isothermal amplification assay

The cytochrome cd1-containing nitrite reductase, nirS, plays an important role in biological denitrification. Consequently, investigating the presence and abundance of nirS is a commonly used approach to understand the distribution and potential activity of denitrifying bacteria, in addition to denitrifier communities. Herein, a new molecular biology technique termed loop-mediated isothermal amplification (LAMP) was developed to rapidly detect nirS gene using those of Pseudomonas aeruginosa to optimize the assay. The LAMP assay relied on a set of four primers that were designed to recognize six target sequence sites, resulting in high target specificity. The specificity of the assay was confirmed by the lack of amplification when using DNA from 15 other bacterial species lacking nirS gene. The limit of detection for the LAMP assay under optimized conditions was 1.87 pg/reaction of genomic DNA, which was an order of magnitude lower than that required by conventional PCR assays. Moreover, a cell-template based LAMP assay was also developed for detecting nirS gene that directly used bacterial cells as template rather than genomic DNA. Only 1 h was needed from the addition of bacterial cells to the reaction to the verification of amplification success, and bulky and sophisticated equipment were not needed. Further, the nirS gene of P. aeruginosa in spiked seawater samples could be detected with both the DNA-template based LAMP assay and the cell-template based LAMP assay, thereby demonstrating the practicality of in-field use of them. In summary, the LAMP assays described here represent a rapid, user-friendly, and cost-effective alternative to conventional PCR.

microbiology↗

Zero-preserving imputation of scRNA-seq data using low-rank approximation

Single cell RNA-sequencing (scRNA-seq) methods have revolutionized the study of gene expression but are plagued by dropout events, a phenomenon where genes actually expressed in a given cell are incorrectly measured as unexpressed. We present a method based on low-rank approximation which successfully replaces these dropouts (zero expression levels of unobserved expressed genes) by nonzero values, while preserving biologically non-expressed genes (true biological zeros) at zero expression levels. We validate our approach and compare it to two state-of-the-art methods. We show that it recovers true expression of marker genes while preserving biological zeros, increases separation of known cell types and improves correlation of simulated cells to their true profiles. Furthermore, our method is dramatically more scalable, allowing practitioners to quickly and easily recover expression of even the largest scRNA-seq datasets.

bioinformatics↗

TP promotes malignant progression in hepatocellular carcinoma through pentose Warburg effect

Tumor progression is dependent on metabolic reprogramming. Metastasis and vasculogenic mimicry (VM) are typical tumor progression. The relationship of metastasis, VM and metabolic reprogramming is not clear. In this study, we identified the novel role of Twist1, a VM regulator, in the transcriptional regulation of the expression of thymidine phosphorylase (TP). We demonstrated that TP promoted extracellular thymidine metabolization into ATP and amino acids through pentose Warburg effect by coupling the pentose phosphate pathway and glycolysis. Moreover, Twist1 relied on TP-induced metabolic reprogramming to promote hepatocellular carcinoma (HCC) metastasis and VM formation mediated by VE-Cad, VEGFR1, and VEGFR2 in vitro and in vivo. TP inhibitor tipiracil reduced promotion effect of TP enzyme activity on HCC VM formation and metastasis. Our findings demonstrate that TP, transcriptionally activated by Twist1, promotes HCC VM formation and metastasis through pentose Warburg effect, contributing to tumor progression.

cell biology↗

Composition and consistence of the bacterial microbiome in upper, middle and lower esophagus before and after Lugol’s iodine staining

Esophageal bacteria, as the integral composition of human ecosystem, have been reported to be associated with esophageal lesions. However, few studies focus on microbial compositions in different esophageal segments, especially after Lugols iodine staining (LIS) in the endoscopic examination for the screening of esophageal cancer. To investigate the composition of the bacterial microbiome in upper, middle and lower esophagus and if LIS would affect the detection of bacteria, 141 fasting samples including the upper, middle and lower esophagus from 27 participants were collected by brushing the mucosal surface of the esophagus before (Eso) and after (Lug) LIS. Bacterial V3-V4 region of 16S rRNA gene was amplified and sequenced by Illuminas sequencing platform and analyzed using LEfSe system to identify specific microbiota. The top six abundant bacterial phyla taxa among three locations from both Eso and Lug groups were Proteobacteria, Firmicutes, Bacteroidetes, Actinobacteria, Fusobacteria and TM7. In terms of genera, the bacterium in three locations from two groups was all characterized by a highest relative abundance of Streptococcus. Bacteria diversity and the relative abundance between Eso and Lug were comparable (P > 0.05). Bacteria diversity was consistent in different esophageal locations for an individual, but it was significantly distinguishing in different subjects (P < 0.05). In Conclusion, the bacterial microbiome in healthy esophagus are highly diverse and consistent even among three physiological stenosis at all clades. Lugols iodine staining would not change local microenvironment in term of microbial composition. These finding provide an essential baseline for future studies investigating local and systemic bacterial microbiome and esophageal diseases.

epidemiology↗

Expression profile analysis of circular RNAs in essential hypertension by microarray and bioinformatics.

Circular RNAs (circRNAs), widely found in human cells, are involved in disease and play an important role in progression. To determine whether circRNAs are related in essential hypertension (EH), we analyzed the expression profile of circRNAs and miRNAs in 5 EH and 5 healthy controls cases which were screened by microarray. Through microarray data and public data analysis, differently expressed transcripts were divided into modules, and circRNAs were functionally annotated by miRNAs. The expression of two circRNAs, has_circ_0037909 and has_circ_0105015, were validated in EH by qRT-PCR, which may be associated with EH. Further analysis showed that two circRNAs might through immune system by up-regulation circRNAs and down-regulation expression. These circRNAs biological functions need to be further validated.

genetics↗

The effects and mechanism of peiminine-induced apoptosis in human hepatocellular carcinoma HepG2 cells

Peiminine is a compound that is isolated from Bolbostemma paniculatum (Maxim) Franquet (Cucurbitaceae family), which has demonstrated antitumor activities. Its precise molecular mechanisms underlying antitumor activity remain elusive. In this study, peiminine-induced apoptosis towards human hepatocellular carcinoma and its molecular mechanisms were investigated. MTT assay was employed to assess anticancer effects of peiminine at concentrations of 2, 4, 6, 8, 10, 12, and 14 g/ml after 24, 48, or 72 h. Nuclear staining and flow cytometry were carried out to further assess apoptosis. Mitochondrial membrane potential evaluation and Western blot analysis were performed to investigate the mechanism of peiminine-induced apoptosis. Peiminine reduced the viability of HepG2 cells in a time- and dose-dependent manner and had an IC50 of 4.58 g/mL at 24h. Flow cytometry assessment indicated that peiminine markedly increased the cell number of apoptotic cells and the mitochondrial membrane potential dose-dependently in HepG2 cells. The results of Western blotting showed the expression of Bcl-2, procaspase-3, procaspase-8, procaspase-9, and PARP1 decreased in HepG2 cells treated with peiminine, while the expression of Bax, caspase-3, caspase-8, caspase-9, and cleaved PARP1 increased. The result suggest taht peiminine can induce apoptosis in human hepatocellular carcinoma HepG2 cells through both extrinsic and intrinsic apoptotic pathways.

cancer biology↗

Different subtypes of EGFR exon19 mutation can affect prognosis of patients with non-small cell lung adenocarcinoma

AimsIn this study, we determined whether different subtypes of epidermal growth factor receptor (EGFR) exon19 mutation are associated with the therapeutic effect of EGFR-tyrosine kinase inhibitors (TKIs) on advanced non-small cell lung adenocarcinoma.\n\nMethodsA total of 122 patients with stage III or IV non-small cell lung adenocarcinoma were retrospectively reviewed. Clinical characteristics of these patients, including progression-free survival (PFS) outcome for EGFR-TKI treatment, were analyzed.\n\nResultsAccording to the mutation pattern, we classified the in-frame deletions detected on EGFR Exon19 into three different types: codon deletion (CD), with a deletion of one or more original codons; codon substitution and skipping (CSS), with a deletion of one or two nucleotides but the residues could be translated into a new amino acid without changing following amino acid sequence; CD or CSS plus single nucleotide variant (SNV) (CD/CSS+SNV), exclude CD or CSS, theres another SNV nearby the deletion region. The clinical characteristics of three groups were analyzed and as a result, no significant difference was found. By comparing the average number of missing bases and amino acids of the three mutation subtypes, it could be discovered that the number of missing bases and amino acids of the three mutation subtypes is diverse, and group CSS> group CD> group CD/CSS+SNV. Finally, survival analysis was performed between three groups of patients. The median PFS of group CD, group CSS and group CD/CSS+SNV was 11 months, 9 months and 14 months respectively. There was a distinct difference in the PFS between group CSS and group CD/CSS+SNV (P=0.035<0.05), and the PFS of group CD/CSS+SNV was longer.\n\nConclusionsDifferent mutation subtypes of EGFR exon19 can predict the therapeutic effect of EGFR-TKIs on advanced non-small cell lung adenocarcinoma.

cancer biology↗

Dynamic plant height QTL revealed in maize through remote sensing phenotyping using a high-throughput unmanned aerial vehicle (UAV)

Plant height is the key factor for plant architecture, biomass and yield in maize (Zea mays). In this study, plant height was investigated using unmanned aerial vehicle high-throughput phenotypic platforms (UAV-HTPPs) for maize diversity inbred lines at four important growth stages. Using an automated pipeline, we extracted accurate plant heights. We found that in temperate regions, from sowing to the jointing period, the growth rate for temperate maize was faster than tropical maize. However, from jointing to flowering stage, tropical maize maintained a vigorous growth state, and finally resulted in a taller plant than temperate lines. Genome-wide association study for temperate, tropical and both groups identified a total of 238 quantitative trait locus (QTLs) for the 16 plant height related traits over four growth periods. And, we found that plant height at different stages were controlled by different genes, for example, PIN1 controlled plant height at the early stage and PIN11 at the flowering stages. In this study, the plant height data collected by the UAV-HTTPs were credible and the genetic mapping power is high, indicating that the application of this UAV-HTTPs into the study of plant height will have great prospects.\n\nHighlightWe used UAV-based sensing platform to investigate plant height over 4 growth stages for different maize populations, and detected numbers of reliable QTLs using GWAS.

genetics↗

Learning from Longitudinal Data in Electronic Health Record and Genetic Data to Improve Cardiovascular Event Prediction

BackgroundCurrent approaches to predicting Cardiovascular disease rely on conventional risk factors and cross-sectional data. In this study, we asked whether: i) machine learning and deep learning models with longitudinal EHR information can improve the prediction of 10-year CVD risk, and ii) incorporating genetic data can add values to predictability.\n\nMethodsWe conducted two experiments. In the first experiment, we modeled longitudinal EHR data with aggregated features and temporal features. We applied logistic regression (LR), random forests (RF) and gradient boosting trees (GBT) and Convolutional Neural Networks (CNN) and Recurrent Neural Networks, using Long Short-Term Memory (LSTM) units. In the second experiment, we proposed a late-fusion framework to incorporate genetic features.\n\nResultsOur study cohort included 109, 490 individuals (9,824 were cases and 99, 666 were controls) from Vanderbilt University Medical Centers (VUMC) de-identified EHRs. American College of Cardiology and the American Heart Association (ACC/AHA) Pooled Cohort Risk Equations had areas under receiver operating characteristic curves (AUROC) of 0.732 and areas under receiver under precision and recall curves (AUPRC) of 0.187. LSTM, CNN and GBT with temporal features achieved best results, which had AUROC of 0.789, 0.790, and 0.791, and AUPRC of 0.282, 0.280 and 0.285, respectively. The late fusion approach achieved a significant improvement for the prediction performance.\n\nConclusionsMachine learning and deep learning with longitudinal features improved the 10-year CVD risk prediction. Incorporating genetic features further enhanced 10-year CVD prediction performance, underscoring the importance of integrating relevant genetic data whenever available in the context of routine care.

epidemiology↗

Identification of pyroptosis inhibitors that target a reactive cysteine in gasdermin D

Inflammasomes are multi-protein signalling scaffolds that assemble in response to invasive pathogens and sterile danger signals to activate inflammatory caspases (1/4/5/11), which trigger inflammatory death (pyroptosis) and processing and release of pro-inflammatory cytokines1,2. Inflammasome activation contributes to many human diseases, including inflammatory bowel disease, gout, type II diabetes, cardiovascular disease, Alzheimers disease, and sepsis, the often fatal response to systemic infection3-6. The recent identification of the pore-forming protein gasdermin D (GSDMD) as the final pyroptosis executioner downstream of inflammasome activation presents an attractive drug target for these diseases7-11. Here we show that disulfiram, a drug used to treat alcohol addiction12, and Bay 11-7082, a previously identified NF-{kappa}B inhibitor13, potently inhibit GSDMD pore formation in liposomes and inflammasome-mediated pyroptosis and IL-1{beta} secretion in human and mouse cells. Moreover, disulfiram, administered at a clinically well-tolerated dose, inhibits LPS-induced septic death and IL-1{beta} secretion in mice. Both compounds covalently modify a conserved Cys (Cys191 in human and Cys192 in mouse GSDMD) that is critical for pore formation8,14. Inflammatory caspases employ Cys active sites, and many previously identified inhibitors of inflammatory mediators, including those against NLRP3 and NF-{kappa}B, covalently modify reactive cysteine residues15. Since NLRP3 and noncanonical inflammasome activation are amplified by cellular oxidative stress16-22, these redox-sensitive reactive cysteine residues may regulate inflammation endogenously, and compounds that covalently modify reactive cysteines may inhibit inflammation by acting at multiple steps. Indeed, both disulfiram and Bay 11-7082 also directly inhibit inflammatory caspases and pleiotropically suppress multiple processes in inflammation triggered by both canonical and noncanonical inflammasomes, including priming, puncta formation and caspase activation. Hence, cysteine-reactive compounds, despite their lack of specificity, may be attractive agents for reducing inflammation.

immunology↗

Phylogenetic relationships in the genus Avena based on the nuclear Pgk1 gene

The phylogenetic relationships among 76 Avena taxa, representing 14 diploids, eight tetraploids, and four hexaploids were investigated by using the nuclear plastid 3-phosphoglycerate kinase gene(pgk1). A significant deletion (131 bp) was detected in all the C genome homoeologues which reconfirmed a major structural divergence between the A and C genomes. Phylogenetic analysis indicated the Cp genome is more closely related to the polyploid species than is the Cv genome. Two haplotypes of pgk1 gene were obtained from most of the AB genome tetraploids. Both types of the barbata group showed a close relationship with the As genome diploid species, supporting the hypothesis that both the A and B genomes are derived from an As genome. Two haplotypes were also detected in A. agadiriana, which showed close relationships with the As genome diploid and the Ac genome diploid, respectively, emphasizing the important role of the Ac genome in the evolution of A. agadiriana. Three homoeologues of thepgK1 gene were detected in five hexaploid accessions. The homoeologues that might represent the D genome were tightly clustered with the tetraploids A. marrocana and A. murphyi, but did not show a close relationship with any extant diploid species.

evolutionary biology↗

Detecting spatiotemporal pattern of tuberculosis and the relationship between ecological environment and tuberculosis, a spatial panel data analysis in Guangxi, China

Guangxi is one of the provinces having the highest reported incidence of tuberculosis (TB) in China. However, spatial and temporal pattern and causation of the situation are still unclear. In order to detect the spatiotemporal pattern of TB and the association with ecological environment factors in Guangxi Zhuang autonomous region, China, We performed a spatiotemporal analysis with prediction using time series analysis, Morans I global and local spatial autocorrelation statistics, and space-time scan statistics, to detect temporal and spatial clusters. Spatial panel models were employed to identify the influence factors. The time series analysis shows that the number of reported cases peaked in spring and summer and decreased in autumn and winter with the annual reported incidence of 113.1/100,000 population. Morans I global statistics were greater than 0 (0.363 - 0.536) during the study period. The most significant hot spots were mainly located in the central part. The east part exhibited a low-low relation. By spacetime scanning, the clusters identified were similar to that of the local autocorrelation statistics, and were clustered toward the early of 2016. Duration of sunshine, per capita gross domestic product (PGDP), the recovery rate of TB and participation rate of new cooperative medical care insurance in rural areas had a significant negative association with TB. In conclusion, the reported incidence of TB in Guangxi remains high. The main cluster was located in the central part of Guangxi, a region where promoting the productivity, improving TB treatment pathway and strengthening environmental protective measures (increasing sunshine exposure) are urgently needed.

epidemiology↗

Using Topic Modeling via Non-negative Matrix Factorization to Identify Relationships between Genetic Variants and Disease Phenotypes: A Case Study of Lipoprotein(a) (LPA)

Genome-wide and phenome-wide association studies are commonly used to identify important relationships between genetic variants and phenotypes. Most of these studies have treated diseases as independent variables and suffered from heavy multiple adjustment burdens due to the large number of genetic variants and disease phenotypes. In this study, we propose using topic modeling via non-negative matrix factorization (NMF) for identifying associations between disease phenotypes and genetic variants. Topic modeling is an unsupervised machine learning approach that can be used to learn the semantic patterns from electronic health record data. We chose rs10455872 in LPA as the predictor since it has been shown to be associated with increased risk of hyperlipidemia and cardiovascular diseases (CVD). Using data of 12,759 individuals from the biobank at Vanderbilt University Medical Center, we trained a topic model using NMF from 1,853 distinct phecodes extracted from the cohorts electronic health records and generated six topics. We quantified their associations with rs10455872 in LPA. Topics indicating CVD had positive correlations with rs10455872 (P < 0.001), replicating a previous finding. We also identified a negative correlation between LPA and a topic representing lung cancer (P < 0.001). Our results demonstrate the applicability of topic modeling in exploring the relationship between the genome and clinical diseases.\n\nAuthor summaryIdentifying the clinical associations of genetic variants remains crucial in understanding how the human genome modulates disease risk. Traditional phenome-wide association studies consider each disease phenotype as an independent variable, however, diseases often present as complex clusters of comorbid conditions. In this study, we propose using topic modeling to model electronic health record data as a mixture of topics (e.g., disease clusters or relevant comorbidities) and testing associations between topics and genetic variants. Our results demonstrated the feasibility of using topic modeling to replicate and discover novel associations between the human genome and clinical diseases.

genetics↗

An Event-related Potential Comparison of Facial Expression Processing between Cartoon and Real Faces

Faces play important roles in the social lives of humans. In addition to real faces, people also encounter numerous cartoon faces in daily life. These cartoon faces convey basic emotional states through facial expressions. Using a behavioral research methodology and event-related potentials (ERPs), we conducted a facial expression recognition experiment with 17 university students to compare the processing of cartoon faces with that of real faces. This study used face type (real vs. cartoon) and participant gender (male vs. female) as independent variables. Reaction time, recognition accuracy, and the amplitudes and latencies of emotion processing-related ERP components such as N170, vertex positive potential (VPP), and late positive potential (LPP) were used as dependent variables. The ERP results revealed that cartoon faces caused larger N170 and VPP amplitudes as well as a briefer N170 latency than did real faces; that real faces induced larger LPP amplitudes than did cartoon faces; and that angry faces induced larger LPP amplitudes than did happy faces. In addition, the results showed a significant difference in the brain regions associated with face processing as reflected in a right hemispheric advantage. The behavioral results showed that the reaction times for happy faces were shorter than those for angry faces; that females showed a higher facial expression recognition accuracy than did males; and that males showed a higher recognition accuracy for angry faces than happy faces. These results demonstrate differences in facial expression recognition and neurological processing between cartoon faces and real faces among adults. Cartoon faces showed a higher processing intensity and speed than real faces during the early processing stage. However, more attentional resources were allocated for real faces during the late processing stage.

neuroscience↗

A direct comparison of four high risk human papilloma virus tests versus the cobas test for detecting cervical intraepithelial neoplasia and cervical cancer

This study is to evaluate performances and genotyping capabilities of four human papilloma virus (HR-HPV) tests based on real-time polymerase chain reaction (PCR) technology platforms compared with the cobas test. Discordant results were further analyzed using INNO-LiPA HPV genotyping test, the gold standard laboratory test to determine presence and type of HPV infection. Over 200 samples from Hospital patients were collected and analyzed using five HR-HPV tests. Women with positive test results were referred directly to colposcopy. If a positive result was returned, biopsies were administered for pathological classification. Clinical performances and genotyping capabilities between the four HR-HPV and cobas tests were compared and contrasted. High levels of agreement were observed, though all HR-HPV tests presented discrepancies compared with the cobas test. Cervical intraepithelial neoplasia Grade 2 or higher lesions (CIN2+) was set as the threshold, and all five tests performed with equally high sensitivity. Lower levels of specificity were observed across all five tests. Results suggest the four HR-HPV tests analyzed are as effective as the cobas test in genotyping capacities and diagnosing CIN. Therefore, these test kits should be used for HPV screening, especially in developing nations because they are cost effective and reliable. Minor discrepancies between tests are generally unavoidable though this may add complexity to the clinical decision-making process. As such, we recommend that efforts be made to standardize HPV genotyping tests as well as to optimize clinical sensitivity and specificity. Focusing on these issues will drive the development of HPV detection techniques, therefore save lives.

epidemiology↗

Single Cell Transcriptomics of Pancreatic Cancer Precursors Demonstrates Epithelial and Microenvironmental Heterogeneity as an Early Event in Neoplastic Progression

BackgroundEarly detection of pancreatic ductal adenocarcinoma (PDAC) remains elusive. Precursor lesions of PDAC, specifically, intraductal papillary mucinous neoplasms (IPMNs) represent a bona fide pathway to invasive neoplasia, although the molecular correlates of progression remain to be fully elucidated. Single cell transcriptomics provides a unique avenue for dissecting both the epithelial and microenvironmental heterogeneity that accompany multistep progression from non-invasive IPMNs to PDAC.\n\nMethodsSingle cell RNA-sequencing was performed through droplet-based sequencing on 5,403 cells from two low-grade IPMNs (LGD-IPMN), two high-grade IPMNs (HGD-IPMN), and two PDACs (all surgically resected).\n\nResultsAnalysis of single cell transcriptomes revealed heterogeneous alterations within the epithelium and the tumor microenvironment during the progression of non-invasive dysplasia to invasive cancer. While HGD-IPMNs expressed many core-signaling pathways described in PDAC, LGD-IPMNs harbored subsets of single cells with a transcriptomic profile that overlapped with invasive cancer. Notably, a pro-inflammatory immune component was readily seen in low-grade IPMNs, comprised of cytotoxic T-cells, activated T-helper cells, and dendritic cells, which was progressively depleted during neoplastic progression, accompanied by infiltration of myeloid-derived suppressor cells. Finally, stromal myofibroblast populations were heterogeneous, and acquired a previously described tumor-promoting and immune-evading phenotype during invasive carcinogenesis.\n\nConclusionsThis study demonstrates the ability to perform high resolution profiling of the transcriptomic changes that occur during multistep progression of cystic PDAC precursors to cancer. Notably, single cell analysis provides an unparalleled insight into both the epithelial and microenvironmental heterogeneity that accompany early cancer pathogenesis, and might be a useful substrate to identify targets for cancer interception.

pathology↗