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Abstract Detecting early-stage esophageal squamous cell carcinoma (ESCC) and precancerous lesions is critical for improving survival. Here, we conduct whole-genome bisulfite sequencing (WGBS) on 460 cfDNA samples from patients with non-metastatic ESCC or precancerous lesions and matched healthy controls. We develop an expanded multimodal analysis (EMMA) framework to simultaneously identify cfDNA methylation, copy number variants (CNVs), and fragmentation markers in cfDNA WGBS data. cfDNA methylation markers are the earliest and most sensitive, detectable in 70% of ESCCs and 50% of precancerous lesions, and associated with molecular subtypes and tumor microenvironments. CNVs and fragmentation features show high specificity but are linked to late-stage disease. EMMA significantly improves detection rates, increasing AUCs from 0.90 to 0.99, and detects 87% of ESCCs and 62% of precancerous lesions with >95% specificity in validation cohorts. Our findings demonstrate the potential of multimodal analysis of cfDNA methylome for early detection and monitoring of molecular characteristics in ESCC.

Abstract The rapid advancement of tumor immunotherapies poses challenges for the tools used in cancer immunology research, highlighting the need for highly effective biomarkers and reproducible experimental models. Current immunotherapy biomarkers encompass surface protein markers such as PD‐L1, genetic features such as microsatellite instability, tumor‐infiltrating lymphocytes, and biomarkers in liquid biopsy such as circulating tumor DNAs. Experimental models, ranging from 3D in vitro cultures (spheroids, submerged models, air–liquid interface models, organ‐on‐a‐chips) to advanced 3D bioprinting techniques, have emerged as valuable platforms for cancer immunology investigations and immunotherapy biomarker research. By preserving native immune components or coculturing with exogenous immune cells, these models replicate the tumor microenvironment in vitro. Animal models like syngeneic models, genetically engineered models, and patient‐derived xenografts provide opportunities to study in vivo tumor‐immune interactions. Humanized animal models further enable the simulation of the human‐specific tumor microenvironment. Here, we provide a comprehensive overview of the advantages, limitations, and prospects of different biomarkers and experimental models, specifically focusing on the role of biomarkers in predicting immunotherapy outcomes and the ability of experimental models to replicate the tumor microenvironment. By integrating cutting‐edge biomarkers and experimental models, this review serves as a valuable resource for accessing the forefront of cancer immunology investigation.

Abstract Esophageal squamous cell carcinoma (ESCC) is a deadly cancer with no clinically relevant biomarkers for early detection. Here, we comprehensively characterized the transcriptional landscape of long non-coding RNAs (lncRNAs) in paired tumor and normal tissue specimens from 93 ESCC patients, and identified six key malignancy-specific lncRNAs that were integrated into a Multi-LncRNA Malignancy Risk Probability model (MLMRPscore). The MLMRPscore performed robustly in distinguishing ESCC from normal controls in multiple in-house and external multicenter validation cohorts, including early-stage I/II cancer. In addition, five candidate lncRNAs were confirmed to have non-invasive diagnostic potential in our institute plasma cohort, showing superior or comparable diagnostic accuracy to current clinical serological markers. Overall, this study highlights the profound and robust dysregulation of lncRNAs in ESCC and demonstrates the potential of lncRNAs as non-invasive biomarkers for the early detection of ESCC.

Abstract Background IDH1/2 hotspot mutations are well known to drive oncogenic mutations in gliomas and are well-defined in the WHO 2021 classification of central nervous system tumors. Specifically, IDH mutations lead to aberrant hypermethylation of under-methylated regions (UMRs) in normal tissues through the disruption of TET enzymes. However, the chromatin reprogramming and transcriptional changes induced by IDH-related hypermethylation in gliomas remain unclear. Results Here, we have developed a precise computational framework based on Hidden Markov Model to identify altered methylation states of UMRs at single-base resolution. By applying this framework to whole-genome bisulfite sequencing data from 75 normal brain tissues and 15 IDH mutant glioma tissues, we identified two distinct types of hypermethylated UMRs in IDH mutant gliomas. We named them partially hypermethylated UMRs (phUMRs) and fully hypermethylated UMRs (fhUMRs), respectively. We found that the phUMRs and fhUMRs exhibit distinct genomic features and chromatin states. Genes related to fhUMRs were more likely to be repressed in IDH mutant gliomas. In contrast, genes related to phUMRs were prone to be up-regulated in IDH mutant gliomas. Such activation of phUMR genes is associated with the accumulation of active H3K4me3 and the loss of H3K27me3, as well as H3K36me3 accumulation in gene bodies to maintain gene expression stability. In summary, partial erosion on UMRs was accompanied by locus-specific changes in key chromatin marks, which may contribute to oncogene activation. Conclusions Our study provides a computational strategy for precise decoding of methylation encroachment patterns in IDH mutant gliomas, revealing potential mechanistic insights into chromatin reprogramming that contribute to oncogenesis.

Large eutrophic estuaries with long flushing times may become a greater carbon sink and acidify, while small estuaries with short flushing times are likely to remain a source of carbon to the atmosphere, according to coupled hydrodynamic-biogeochemical model and generalized box model simulations.

Summary: Background: DNA damage repair (DDR) is a critical process that maintains genomic integrity and plays essential roles at both the cellular and organismic levels. Here, we aimed to characterize the DDR profiling of esophageal squamous cell carcinoma (ESCC), investigate the prognostic value of DDR-related features, and explore their potential for guiding personalized treatment strategies. Methods: We analyzed bulk and single-cell transcriptomics data from 377 ESCC cases from our institution and other publicly available cohorts to identify major DDR subtypes. The heterogeneity in cellular and functional properties, tumor microenvironment (TME) characteristics, and prognostic significance of these DDR subtypes were investigated using immunogenomic analysis and in vitro experiments. Additionally, we experimentally validated a combinatorial immunotherapy strategy using syngeneic mouse models of ESCC. Findings: DDR alteration profiling enabled us to identify two distinct DDR subtypes, DDRactive and DDRsilent, which exhibited independent prognostic values in locoregional ESCC but not in metastatic ESCC. The DDRsilent subtype was characterized by an inflamed but immune-suppressed microenvironment with relatively high immune cell infiltration, abnormal immune checkpoint expression, T-cell exhaustion, and enrichment of cancer-related pathways. Moreover, DDR subtyping indicates that BRCA1 and HFM1 are robust and independent prognostic factors in locoregional ESCC. Finally, we proposed and verified that the concomitant triggering of GITR or blockade of BTLA with PD-1 blockade or cisplatin chemotherapy represents effective combination strategies for high-risk locoregional ESCC tumors. Interpretation: Our discovery of DDR-based molecular subtypes will enhance our understanding of tumor heterogeneity and have significant clinical implications for the therapeutic and management strategies of locoregional ESCC. Funding: This study was supported by the National Key R&D Program of China (2021YFC2501000, 2022YFC3401003), National Natural Science Foundation of China (82172882), the Beijing Natural Science Foundation (7212085), the CAMS Innovation Fund for Medical Sciences (2021-I2M-1-018, 2021-I2M-1-067), the Fundamental Research Funds for the Central Universities (3332021091), and the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2019PT310027).

Simultaneous measurement of multiple modalities in single-cell analysis, represented by CITE-seq, is a promising approach to link transcriptional changes to cellular phenotype and function, requiring new computational methods to define cellular subtypes and states based on multiple data types. Here, we design a flexible single-cell multimodal analysis framework, called CITEMO, to integrate the transcriptome and antibody-derived tags (ADT) data to capture cell heterogeneity from the multi omics perspective. CITEMO uses Principal Component Analysis (PCA) to obtain a low-dimensional representation of the transcriptome and ADT, respectively, and then employs PCA again to integrate these low-dimensional multimodal data for downstream analysis. To investigate the effectiveness of the CITEMO framework, we apply CITEMO to analyse the cell subtypes of Cord Blood Mononuclear Cells (CBMC) samples. Results show that the CITEMO framework can comprehensively analyse single-cell multimodal samples and accurately identify cell subtypes. Besides, we find some specific immune cells that co-express multiple ADT markers. To better describe the co-expression phenomenon, we introduce the co-expression entropy to measure the heterogeneous distribution of the ADT combinations. To further validate the robustness of the CITEMO framework, we analyse Human Bone Marrow Cell (HBMC) samples and identify different states of the same cell type. CITEMO has an excellent performance in identifying cell subtypes and states for multimodal omics data. We suggest that the flexible design idea of CITEMO can be an inspiration for other single-cell multimodal tasks. The complete source code and dataset of the CITEMO framework can be obtained from https://github.com/studentiz/CITEMO.

Abstract Over the past two decades, liquid biopsy has been increasingly used as a supplement, or even, a replacement to the traditional biopsy in clinical oncological practice, due to its noninvasive and early detectable properties. The detections can be based on a variety of features extracted from tumor‑derived entities, such as quantitative alterations, genetic changes, and epigenetic aberrations, and so on. So far, the clinical applications of cancer liquid biopsy mainly aimed at two aspects, prediction (early diagnosis, prognosis and recurrent evaluation, therapeutic response monitoring, etc.) and intervention. In spite of the rapid development and great contributions achieved, cancer liquid biopsy is still a field under investigation and deserves more clinical practice. To better open up future work, here we systematically reviewed and compared the latest progress of the most widely recognized circulating components, including circulating tumor cells, cell‐free circulating DNA, noncoding RNA, and nucleosomes, from their discovery histories to clinical values. According to the features applied, we particularly divided the contents into two parts, beyond epigenetics and epigenetic‐based. The latter was considered as the highlight along with a brief overview of the advances in both experimental and bioinformatic approaches, due to its unique advantages and relatively lack of documentation.

Summary: Long non-coding RNAs (lncRNAs) have been implicated in diverse biological processes. However, the functional mechanisms have not yet been fully explored. Characterizing the interactions of lncRNAs with chromatin is central to determining their functions but, due to precise and efficient approaches lacking, our understanding of their functional mechanisms has progressed slowly. In this study, we demonstrate that a nuclear lncRNA linc1393 maintains mouse ESC pluripotency by recruiting SET1A near its binding sites, to establish H3K4me3 status and activate the expression of specific pluripotency-related genes. Moreover, we characterized the principles of lncRNA–chromatin interaction and transcriptional regulation. Accordingly, we developed a computational framework based on the XGBoost model, LncTargeter, to predict the targets of a given lncRNA, and validated its reliability in various cellular contexts. Together, these findings elucidate the roles and mechanisms of lncRNA on pluripotency maintenance, and provide a promising tool for predicting the regulatory networks of lncRNAs.

Abstract Food associated diseases pose significant public health threat in the United States. Health risks associated with food-borne pathogens drive the need for constant monitoring of food products. An efficient method that can diagnose food-borne pathogens rapidly will be invaluable and in high demand. In this study, we showed the feasibility of a novel rapid detection platform based on fluorescence imaging/detection that combines a user-friendly, portable loop mediated isothermal amplification (LAMP) reaction device and a smartphone-based detection system. The proposed platform was used to detect Staphylococcus aureus which is one of the most important food-borne pathogen especially dairy products. The complete protocol is quicker; the reaction is performed under isothermal conditions and completed in 1 h or less. Experimental results show that LAMP assays were ten-fold more sensitive than PCR-based detection. The proposed smartphone detection system was able to detect and quantify LAMP assay samples containing three different concentrations of S. aureus from 109 CFU/mL down to 103 CFU/mL. The present proof-of-concept study demonstrated that this platform offers a portable, easy to use method for measuring target pathogens with LAMP amplification.

This research presents a novel optimization modeling framework for the existing Soil and Water Assessment Tool (SWAT), which can be used to optimize perennial feedstock production. This novel multi-objective evolutionary algorithm (MOEA) uses SWAT outputs to determine optimal spatial placement of variant cropping systems, considering environmental impacts from land-cover change and management practices. The final solution to the multi-objective problem is presented as a set of Pareto optimal solutions, where one is suggested considering the proximity to the ideal vector [1,0,0,0]. This unique approach provides a well-suited method to assist researchers and stakeholders in understanding the environmental impacts when cultivating biofuel feedstocks. The application of the proposed MOEA is illustrated by analyzing SWAT's example data set for Lake Fork Watershed. Nine land-cover scenarios were evaluated in SWAT to determine their optimal spatial placement considering maximizing biomass production while minimizing sediment yield, organic nitrogen yield, and organic phosphorous yield.

IntroductionAge-related macular degeneration (AMD), an ever-increasing ocular disease, has become one of the leading causes of irreversible blindness. Recent advances in single-cell genomics are improving our understanding of the molecular mechanisms of AMD. However, the pathophysiology of this multifactorial disease is complicated and still an ongoing challenge. To better understand disease pathogenesis and identify effective targets, we conducted an in-depth analysis of the single-cell transcriptome of AMD.MethodsThe cell expression specificity of the gene (CESG) was selected as an index to identify the novel cell markers. A computational framework was designed to explore the cell-specific TF regulatory loops, containing the interaction of gene pattern signatures, transcription factors regulons, and differentially expressed genes.ResultsThree potential novel cell markers were DNASE1L3 for endothelial cells, ABCB5 for melanocytes, and SLC39A12 for RPE cells detected. We observed a notable change in the cell abundance and crosstalk of fibroblasts cells, melanocytes, schwann cells, and T/NK cells between AMD and controls, representing a complex cellular ecosystem in disease status. Finally, we identified six cell type related and three disease-associated ternary loops and elaborated on the robust association between key immune-pathway and AMD.DiscussionIn conclusion, this study facilitates the optimization of screening for AMD-related receptor ligand pathways and proposes to further improve the interpretability of disease associations from single-cell data. It illuminated that immune-related regulation paths could be used as potential diagnostic markers for AMD, and in the future, also as therapeutic targets, providing insights into AMD diagnosis and potential interventions.

Summary: High myopia (HM) is one of the leading causes of visual impairment and blindness worldwide. Here, we report a whole-exome sequencing (WES) study in 9,613 HM cases and 9,606 controls of Han Chinese ancestry to pinpoint HM-associated risk variants. Single-variant association analysis identified three newly identified -genetic loci associated with HM, including an East Asian ancestry-specific low-frequency variant (rs533280354) in FKBP5. Multi-ancestry meta-analysis with WES data of 2,696 HM cases and 7,186 controls of European ancestry from the UK Biobank discerned a newly identified European ancestry-specific rare variant in FOLH1. Functional experiments revealed a mechanism whereby a single G-to-A transition at rs533280354 disrupted the binding of transcription activator KLF15 to the promoter of FKBP5, resulting in decreased transcription of FKBP5. Furthermore, burden tests showed a significant excess of rare protein-truncating variants among HM cases involved in retinal blood vessel morphogenesis and neurotransmitter transport.

Epilepsy is a complex phenomena of a system of highly intensive and synchronized neurons simultaneously firing which can be traced to spatial and temporal patterns. Seizures are a well known physical feature for all types of epileptic disorders. The rhythms, patterns, and oscillatory dynamics explain the mechanistic nature of neurons especially in absence seizures. Previous models such as Wilson-Cowan (1973), introduced brain models showing the dynamics of a network of neurons consisting of excitatory and inhibitory neurons. Taylor et al. (2014) then adapted the Wilson-Cowan model to epileptic seizures using a thalamo-cortical based theory. Fan et al. (2018) projects that thalamic reticulus nuclei control spike wave discharges specifically in absence seizures. We identify brain activity patterns specific to Glucose (G1D) Transport Deficiency Epilepsy in a network model based on electroencephalogram device (EEG) data. Additionally, we study the EEG patterns to identify the plausible mechanism that causes G1D epileptic behavior. Our coupled thalamo-cortical model goes beyond a connection in a logical unidirectional pattern shown by Fan or in a bidirectional small world pattern. Our model is a network based on paired correlation of EEG signals more analogous to realistic seizure activity. Using our model, we are able to study stability analysis for equilibrium and periodic behavior. We also identify parameter values which cause synchronized activity or more stable activity. Lastly, we identify a synchronization index and sensitivity analysis regarding parameters that directly affect Spike Wave Discharges and other spiking behavior. We will show how our 32-unit data-driven network model reflects G1D seizure dynamics and discuss the limitations of the model.

Myocardin is known as an important transcriptional regulator in smooth and cardiac muscle development as well as a tumor suppressor. However, the pathological function of myocardin in NSCLC metastasis is poorly understood. Here, we have described novel roles for myocardin in the metastatic cascade using in vitro and in vivo models. We demonstrate that myocardin deficiency is sufficient to trigger epithelial–mesenchymal transition (EMT) process but reduces metastatic potential of NSCLC in vivo. Myocardin deficiency reduces lung cancer metastasis because of persistent EMT and decreasing colonization capacity. Restoring myocardin expression in colonization stage promotes the metastasis of lung cancer cells. An epigenetically negative feedback loop formed by myocardin and PRMT5/MEP50 complex prevents EMT. We also uncover the unknown mechanism of myocardin suppression in lung cancer tissues that PRMT5/MEP50 complex negatively regulates myocardin expression. It helps to reconcile conflicting results that have challenged the significance of EMT and cancer metastasis and explain the phenotype of myocardin suppression in lung cancer cells.

In this paper we study a harmonic function method for dipolar source reconstruction, and implemented the numerical simulations. We propose a new error estimate and provide a rigorous proof of the estimate. Then, we validate our method in computer-simulated data and study its numerical stability in different noise levels. It is shown that the harmonic function method can be used to quickly and accurately locate the active regions in EEG source reconstruction.

Abstract Background Understanding the host genetic architecture and viral immunity contributes to the development of effective vaccines and therapeutics for controlling the COVID-19 pandemic. Alterations of immune responses in peripheral blood mononuclear cells play a crucial role in the detrimental progression of COVID-19. However, the effects of host genetic factors on immune responses for severe COVID-19 remain largely unknown. Methods We constructed a computational framework to characterize the host genetics that influence immune cell subpopulations for severe COVID-19 by integrating GWAS summary statistics (N = 969,689 samples) with four independent scRNA-seq datasets containing healthy controls and patients with mild, moderate, and severe symptom (N = 606,534 cells). We collected 10 predefined gene sets including inflammatory and cytokine genes to calculate cell state score for evaluating the immunological features of individual immune cells. Results We found that 34 risk genes were significantly associated with severe COVID-19, and the number of highly expressed genes increased with the severity of COVID-19. Three cell subtypes that are CD16+monocytes, megakaryocytes, and memory CD8+T cells were significantly enriched by COVID-19-related genetic association signals. Notably, three causal risk genes of CCR1, CXCR6, and ABO were highly expressed in these three cell types, respectively. CCR1 +CD16+monocytes and ABO + megakaryocytes with significantly up-regulated genes, including S100A12, S100A8, S100A9, and IFITM1, confer higher risk to the dysregulated immune response among severe patients. CXCR6 + memory CD8+ T cells exhibit a notable polyfunctionality including elevation of proliferation, migration, and chemotaxis. Moreover, we observed an increase in cell-cell interactions of both CCR1 + CD16+monocytes and CXCR6 + memory CD8+T cells in severe patients compared to normal controls among both PBMCs and lung tissues. The enhanced interactions of CXCR6 + memory CD8+T cells with epithelial cells facilitate the recruitment of this specific population of T cells to airways, promoting CD8+T cell-mediated immunity against COVID-19 infection. Conclusions We uncover a major genetics-modulated immunological shift between mild and severe infection, including an elevated expression of genetics-risk genes, increase in inflammatory cytokines, and of functional immune cell subsets aggravating disease severity, which provides novel insights into parsing the host genetic determinants that influence peripheral immune cells in severe COVID-19.

Abstract This study investigates aberrant DNA methylations as potential diagnosis and prognosis markers for esophageal squamous-cell carcinoma (ESCC), which if diagnosed at advanced stages has

Abstract Background Identifying breast cancer patients with DNA repair pathway-related germline pathogenic variants (GPVs) is important for effectively employing systemic treatment strategies and risk-reducing interventions. However, current criteria and risk prediction models for prioritizing genetic testing among breast cancer patients do not meet the demands of clinical practice due to insufficient accuracy. Methods The study population comprised 3041 breast cancer patients enrolled from seven hospitals between October 2017 and 11 August 2019, who underwent germline genetic testing of 50 cancer predisposition genes (CPGs). Associations among GPVs in different CPGs and endophenotypes were evaluated using a case-control analysis. A phenotype-based GPV risk prediction model named DNA-repair Associated Breast Cancer (DrABC) was developed based on hierarchical neural network architecture and validated in an independent multicenter cohort. The predictive performance of DrABC was compared with currently used models including BRCAPRO, BOADICEA, Myriad, PENN II, and the NCCN criteria. Results In total, 332 (11.3%) patients harbored GPVs in CPGs, including 134 (4.6%) in BRCA2, 131 (4.5%) in BRCA1, 33 (1.1%) in PALB2, and 37 (1.3%) in other CPGs. GPVs in CPGs were associated with distinct endophenotypes including the age at diagnosis, cancer history, family cancer history, and pathological characteristics. We developed a DrABC model to predict the risk of GPV carrier status in BRCA1/2 and other important CPGs. In predicting GPVs in BRCA1/2, the performance of DrABC (AUC = 0.79 [95% CI, 0.74–0.85], sensitivity = 82.1%, specificity = 63.1% in the independent validation cohort) was better than that of previous models (AUC range = 0.57–0.70). In predicting GPVs in any CPG, DrABC (AUC = 0.74 [95% CI, 0.69–0.79], sensitivity = 83.8%, specificity = 51.3% in the independent validation cohort) was also superior to previous models in their current versions (AUC range = 0.55–0.65). After training these previous models with the Chinese-specific dataset, DrABC still outperformed all other methods except for BOADICEA, which was the only previous model with the inclusion of pathological features. The DrABC model also showed higher sensitivity and specificity than the NCCN criteria in the multi-center validation cohort (83.8% and 51.3% vs. 78.8% and 31.2%, respectively, in predicting GPVs in any CPG). The DrABC model implementation is available online at http://gifts.bio-data.cn/ . Conclusions By considering the distinct endophenotypes associated with different CPGs in breast cancer patients, a phenotype-driven prediction model based on hierarchical neural network architecture was created for identification of hereditary breast cancer. The model achieved superior performance in identifying GPV carriers among Chinese breast cancer patients.

Adenosine-to-inosine (A-to-I) RNA editing leads to functional change of neurotransmitter receptor which is essential for neurotransmission and normal neuronal development. As a highly accessible part of central nervous system, retina has been extensively studied, however, it remains largely unknown how RNA editing regulates its development. Here, a genome-wide screening of high-confidence RNA editing events were performed to decipher the dynamic transcriptome regulation by RNA editing during mouse retinal development. 2000 high-confidence editing sites across eight developmental stages of retina were called. Three unique patterns (RNA-editinghigh pattern, RNA-editingmedium pattern and RNA-editinglow pattern) were identified by clustering these editing sites based on their editing level during retinal development. Editing events from RNA-editinghigh pattern were significantly associated with glutamate receptors and regulated synaptic transmission. Interestingly, most non-synonymous high-editing sites were mapped to ion channel genes of glutamatergic synapse which were associated with neurotransmission by controlling ion channel permeability and affecting exocytosis. Meanwhile, these non-synonymous editing sites were evolutionarily conserved and exhibited a consistently increasing editing levels between mouse and human retinal development. Single-cell RNA-seq data analysis revealed that RNA editing events prefer to occur in two main cell types including bipolar and amacrine cells. Genes with non-synonymous high-editing sites were enriched in both bipolar cells and retina ganglion cells, which may mediate retina ganglion cell differentiation by altering channel ion permeability. Together, our results provide novel insights into mechanism of post-transcriptional regulation during retinal development and help to develop novel RNA editing-guided therapeutic strategies for retinal disorders.

Abstract Background Primary biliary cholangitis (PBC) is a classical autoimmune disease, which is highly influenced by genetic determinants. Many genome-wide association studies (GWAS) have reported that numerous genetic loci were significantly associated with PBC susceptibility. However, the effects of genetic determinants on liver cells and its immune microenvironment for PBC remain unclear. Results We constructed a powerful computational framework to integrate GWAS summary statistics with scRNA-seq data to uncover genetics-modulated liver cell subpopulations for PBC. Based on our multi-omics integrative analysis, 29 risk genes including ORMDL3, GSNK2B, and DDAH2 were significantly associated with PBC susceptibility. By combining GWAS summary statistics with scRNA-seq data, we found that cholangiocytes exhibited a notable enrichment by PBC-related genetic association signals (Permuted P

Abstract Background Myopia is the most common visual impairment in children and adolescents worldwide. This study described an economical and effective population-based screening pipeline and performed the project of a million scale children and adolescents myopia survey (CAMS), which will shed light on the further study of myopia from the level of epidemiology and precision medicine. Methods We developed a novel population-based screening pattern, an intelligent screening process and internet-based information transmission and analysis system to carry out the survey consisting of school children in Wenzhou, China. The examination items include unaided distance visual acuity, presenting distance visual acuity, and non-cycloplegic autorefraction. Myopia and high myopia were defined as spherical equivalent (SE) ≤ − 1.00 diopters (D) and SE ≤ − 6.00 D, respectively. Next, the reports of the vision checking were automatically sent to parents and the related departments. The CAMS project will be done two to four times annually with the support of the government. An online eyesight status information management system (OESIMS) was developed to construct comprehensive and efficient electronic vision health records (EVHRs) for myopia information inquiry, risk pre-warning, and further study. Results The CAMS completed the first-round of screening within 30 days for 99.41% of Wenzhou students from districts and counties, in June 2019. A total of 1,060,925 participants were eligible for CAMS and 1,054,251 (99.37% participation rate) were selected through data quality control, which comprised 1305 schools, and 580,609, 251,050 and 170,967 elementary, middle, and high school students. The mean age of participants was 12.21 ± 3.32 years (6–20 years), the female-to-male ratio was 0.82. The prevalence of myopia in elementary, middle, and high school students was 38.16%, 77.52%, and 84.00%, respectively, and the high myopia incidence was 0.95%, 6.90%, and 12.98%. Conclusions The CAMS standardized myopia screening model involves automating large-scale information collection, data transmission, data analysis and early warning, thereby supporting myopia prevention and control. The entire survey reduced 90% of staff, cost, and time consumption compared with previous surveys. This will provide new insights for decision support for public health intervention.

Abstract Trimethylation of histone H3 lysine 27 trimethylation (H3K27me3) may be recruited by repressive Polycomb complexes to mediate gene silencing, which is critical for maintaining embryonic stem cell pluripotency and differentiation. However, the roles of aberrant H3K27me3 patterns in tumorigenesis are not fully understood. Here, we discovered that grand silencer domains (breadth > 50 kb) for H3K27me3 were significantly associated with epithelial cell differentiation and exhibited high gene essentiality and conservation in human esophageal epithelial cells. These grand H3K27me3 domains exhibited high modification signals involved in gene silencing, and preferentially occupied the entirety of topologically associating domains and interact with each other. We found that widespread loss of the grand H3K27me3 domains in of esophageal squamous cell carcinomas (ESCCs) were enriched in genes involved in epithelium and endothelium differentiation, which were significantly associated with overexpression with increase of active modifications of H3K4me3, H3K4me1, and H3K27ac marks, as well as DNA hypermethylation in the gene bodies. A total of 208 activated genes with loss of grand H3K27me3 domains in ESCC were identified, where the higher expression and mutation of T-box transcription factor 20 (TBX20) were associated with worse patients’ outcomes. Our results showed that knockdown of TBX20 may have led to a striking defect in esophageal cancer cell growth and carcinogenesis-related pathway, including cell cycle and homologous recombination. Together, our results reveal that loss of grand H3K27me3 domains represent a catalog of remarkable activating regulators involved in carcinogenesis.

The role of regulatory cis-elements in carcinogenesis and metastasis in esophageal squamous cell carcinoma remains crucial. Here the authors investigate H3K27ac-marked active enhancer profiles and transcriptomes in different types of esophageal tissues and identify oncogenic events and potential therapeutic targets.

Summary: Background: Ocular diseases may exhibit common clinical symptoms and epidemiological comorbidity. However, the extent of pleiotropic mechanisms across ocular diseases remains unclear. We aim to examine shared genetic etiology in age-related macular degeneration (AMD), diabetic retinopathy (DR), glaucoma, retinal detachment (RD), and myopia. Methods: We analyzed genome-wide association analyses for the five ocular diseases in 43,877 cases and 44,373 controls of European ancestry from UK Biobank, estimated their genetic relationships (LDSC, GNOVA, and Genomic SEM), and identified pleiotropic loci (ASSET and METASOFT). Findings: The genetic correlation of common SNPs revealed a meaningful genetic structure within these diseases, identifying genetic correlations between AMD, DR, and glaucoma. Cross-trait meta-analysis identified 23 pleiotropic loci associated with at least two ocular diseases and 14 loci unique to individual disorders (non-pleiotropic). We found that the genes associated with these shared genetic loci are involved in neuron differentiation (P = 8.80 × 10−6) and eye development systems (P = 3.86 × 10−5), and single cell RNA sequencing data reveals their heightened gene expression from multipotent progenitors to other differentiated retinal cells during retina developmental process. Interpretation: These results highlighted the potential common genetic architectures among these ocular diseases and can deepen the understanding of the molecular mechanisms underlying the related diseases. Funding: The National Natural Science Foundation of China (61871294), Zhejiang Provincial Natural Science Foundation of China (LR19C060001), and the Scientific Research Foundation for Talents of Wenzhou Medical University (QTJ18023).

Abstract Early detection is crucial to improve breast cancer (BC) patients’ outcomes and survival. Mammogram and ultrasound adopting the Breast Imaging Reporting and Data System (BI-RADS) categorization are widely used for BC early detection, while suffering high false-positive rate leading to unnecessary biopsy, especially in BI-RADS category-4 patients. Plasma cell-free DNA (cfDNA) carrying on DNA methylation information has emerged as a non-invasive approach for cancer detection. Here we present a prospective multi-center study with whole-genome bisulfite sequencing data to address the clinical utility of cfDNA methylation markers from 203 female patients with breast lesions suspected for malignancy. The cfDNA is enriched with hypo-methylated genomic regions. A practical computational framework was devised to excavate optimal cfDNA-rich DNA methylation markers, which significantly improved the early diagnosis of BI-RADS category-4 patients (AUC from 0.78–0.79 to 0.93–0.94). As a proof-of-concept study, we performed the first blood-based whole-genome DNA methylation study for detecting early-stage breast cancer from benign tumors at single-base resolution, which suggests that combining the liquid biopsy with the traditional diagnostic imaging can improve the current clinical practice, by reducing the false-positive rate and avoiding unnecessary harms.

Here, the authors introduce Cell Heterogeneity–Adjusted cLonal Methylation (CHALM) as a methylation quantification method that considers the heterogeneity of sequenced bulk cells. They apply CHALM to methylation datasets to detect differentially methylated genes that exhibit distinct biological functions supporting underlying mechanisms.

Abstract Background Breast cancer (BC) is the most frequently diagnosed cancer and the leading cause of cancer-associated deaths in women. Recent studies have indicated that microRNA (miRNA) regulation in genomic instability (GI) is associated with disease risk and clinical outcome. Herein, we aimed to identify the GI-derived miRNA signature in extracellular vesicles (EVs) as a minimally invasive biomarker for early diagnosis and prognostic risk stratification. Experimental design Integrative analysis of miRNA expression and somatic mutation profiles was performed to identify GI-associated miRNAs. Then, we constructed a discovery and validation study with multicenter prospective cohorts. The GI-derived miRNA signature (miGISig) was developed in the TCGA discovery cohort (n = 261), and was subsequently independently validated in internal TCGA validation (n = 261) and GSE22220 (n = 210) cohorts for prognosis prediction, and in GSE73002 (n = 3966), GSE41922 (n = 54), and in-house clinical exosome (n = 30) cohorts for diagnostic performance. Results We identified a GI-derived three miRNA signature (MIR421, MIR128-1 and MIR128-2) in the serum extracellular vesicles of BC patients, which was significantly associated with poor prognosis in all the cohorts tested and remained as an independent prognostic factor using multivariate analyses. When integrated with the clinical characteristics, the composite miRNA-clinical prognostic indicator showed improved prognostic performance. The miGISig also showed high accuracy in differentiating BC from healthy controls with the area under the receiver operating characteristics curve (ROC) with 0.915, 0.794 and 0.772 in GSE73002, GSE41922 and TCGA cohorts, respectively. Furthermore, circulating EVs from BC patients in the in-house cohort harbored elevated levels of miGISig, with effective diagnostic accuracy. Conclusions We report a novel GI-derived three miRNA signature in EVs, as an excellent minimally invasive biomarker for the early diagnosis and unfavorable prognosis in BC.

Biological pathway analysis provides new insights for cell clustering and functional annotation from single-cell RNA sequencing (scRNA-seq) data. Many pathway analysis algorithms have been developed to transform gene-level scRNA-seq data into functional gene sets representing pathways or biological processes. Here, we collected seven widely-used pathway activity transformation algorithms and 32 available datasets based on 16 scRNA-seq techniques. We proposed a comprehensive framework to evaluate their accuracy, stability and scalability. The assessment of scRNA-seq preprocessing showed that cell filtering had the less impact on scRNA-seq pathway analysis, while data normalization of sctransform and scran had a consistent well impact across all tools. We found that Pagoda2 yielded the best overall performance with the highest accuracy, scalability, and stability. Meanwhile, the tool PLAGE exhibited the highest stability, as well as moderate accuracy and scalability.

Abstract Background Identifying how pain transitions from acute to chronic is critical in designing effective prevention and management techniques for patients’ well-being, physically, psychosocially, and financially. There is an increasingly pressing need for a quantitative and predictive method to evaluate how low back pain trajectories are classified and, subsequently, how we can more effectively intervene during these progression stages. Methods In order to better understand pain mechanisms, we investigated, using computational modeling, how best to describe pain trajectories by developing a platform by which we studied the transition of acute chronic pain. Results The present study uses a computational neuroscience-based method to conduct such trajectory research, motivated by the use of hypothalamic–pituitary–adrenal (HPA) axis activity-history over a time-period as a way to mimic pain trajectories. A numerical simulation study is presented as a “proof of concept” for this modeling approach. Conclusions This model and its simulation results have highlighted the feasibility and the potential of developing such a broader model for patient evaluations.

Coagulase-negative Staphylococcus (CoNS) is the most common pathogen causing traumatic endophthalmitis. Among which, Staphylococcus epidermidis is the most common species that colonizes human skin, eye surfaces, and nasal cavity. It is also the main cause of nosocomial infection, specially foreign body-related bloodstream infections (FBR-BSIs). Although some studies have reported the genome characteristics of S. epidermidis, the genome of ocular trauma-sourced S. epidermidis strain and a comprehensive understanding of its pathogenicity are still lacking. Our study sequenced, analyzed, and reported the whole genomes of 11 ocular trauma-sourced samples of S. epidermidis that caused traumatic endophthalmitis. By integrating publicly available genomes, we obtained a total of 187 S. epidermidis samples from healthy and diseased eyes, skin, respiratory tract, and blood. Combined with pan-genome, phylogenetic, and comparative genomic analyses, our study showed that S. epidermidis, regardless of niche source, exhibits two founder lineages with different pathogenicity. Moreover, we identified several potential biomarkers associated with the virulence of S. epidermidis, including essD, uhpt, sdrF, sdrG, fbe, and icaABCDR. EssD and uhpt have high homology with esaD and hpt in Staphylococcus aureus, showing that the genomes of S. epidermidis and S. aureus may have communicated during evolution. SdrF, sdrG, fbe, and icaABCDR are related to biofilm formation. Compared to S. epidermidis from blood sources, ocular-sourced strains causing intraocular infection had no direct relationship with biofilm formation. In conclusion, this study provided additional data resources for studies on S. epidermidis and improved our understanding of the evolution and pathogenicity among strains of different sources.

The stress’s accumulation will critically affect optical device stability, leading to components’ deviation and film peeling. Stress control techniques based on strain cancelation cannot precisely match film stress, and it is difficult to reduce the total stress of multilayer film to ultra-low levels. Existing software for film system design is mainly based on 2D design concepts such as wavelength-spectrum and does not consider 3D design concepts such as wavelength-spectrum-stress, but the stress parameter plays an essential role in film performance, and it is necessary to use it as an optimization index for film design. In this paper, we introduce mechanical synchronization design into film system design. The multilayer film’s optimal structure is precisely matched by the genetic algorithm, and an ultra-low stress and wide-spectrum optical film element is developed under the dual requirements of optical performance and mechanical performance. This technique incorporates computer-aided design and automatically seeks an optimal combination of layered film nanostructures through self-compiled optical and mechanical compatible design software. While ensuring invariant optical properties, it can effectively reduce the total stress of multilayer film. This can provide a new idea for film stress control.

Patients with colon cancer are often faced a high risk of disease recurrence within 5 years of treatment that is the major cause of cancer mortality. Reliable molecular markers were required to improve the most effective personalized therapy. Here, we identified a recurrence-associated six-lncRNA (long non-coding RNA) signature (LINC0184, AC105243.1, LOC101928168, ILF3-AS1, MIR31HG, and AC006329.1) that can effectively distinguish between high and low risk of cancer recurrence from 389 patients of a discovery dataset, and validated its robust performance in four independent datasets comprising a total of 906 colon cancer patients. We found that the six-lncRNA signature was an independent predictive factor of disease recurrence in multivariate analysis and was superior to the performance of clinical factors and known gene signature. Furthermore, in silico functional analysis showed that the six-lncRNA-signature-associated coding genes are significantly enriched in proliferation and angiogenesis, cell death, as well as critical cancer pathways that could play important roles in colon cancer recurrence. Together, the six-lncRNA signature holds great potential for recurrence risk assessment and personalized management of colon cancer patients. Keywords: colon cancer, long non-coding RNAs, recurrence, signature

BackgroundIncreasing evidence has demonstrated the functional relevance of long non-coding RNAs (lncRNAs) to immunity regulation and the tumor microenvironment in non-small cell lung cancer (NSCLC). However, tumor immune infiltration-associated lncRNAs and their value in improving clinical outcomes and immunotherapy remain largely unexplored.MethodsWe developed a computational approach to identify an lncRNA signature (TILSig) as an indicator of immune cell infiltration in patients with NSCLC through integrative analysis for lncRNA, immune and clinical profiles of 115 immune cell lines, 187 NSCLC cell lines and 1533 patients with NSCLC. Then the influence of the TILSig on the prognosis and immunotherapy in NSCLC was comprehensively investigated.ResultsComputational immune and lncRNA profiling analysis identified an lncRNA signature (TILSig) consisting of seven lncRNAs associated with tumor immune infiltration. The TILSig significantly stratified patients into the immune-cold group and immune-hot group in both training and validation cohorts. These immune-hot patients exhibit significantly improved survival outcome and greater immune cell infiltration compared with immune-cold patients. Multivariate analysis revealed that the TILSig is an independent predictive factor after adjusting for other clinical factors. Further analysis accounting for TILSig and immune checkpoint gene revealed that the TILSig has a discriminatory power in patients with similar expression levels of immune checkpoint genes and significantly prolonged survival was observed for patients with low TILSig and low immune checkpoint gene expression implying a better response to immune checkpoint inhibitor (ICI) immunotherapy.ConclusionsOur finding demonstrated the importance and value of lncRNAs in evaluating the immune infiltrate of the tumor and highlighted the potential of lncRNA coupled with specific immune checkpoint factors as predictive biomarkers of ICI response to enable a more precise selection of patients.

Abstract Background Cancers have long been recognized to be not only genetically but also epigenetically distinct from their tissues of origin. Although genetic alterations underlying oncogene upregulation have been well studied, to what extent epigenetic mechanisms, such as DNA methylation, can also induce oncogene expression remains unknown. Results Here, through pan-cancer analysis of 4174 genome-wide profiles, including whole-genome bisulfite sequencing data from 30 normal tissues and 35 solid tumors, we discover a strong correlation between gene-body hypermethylation of DNA methylation canyons, defined as broad under-methylated regions, and overexpression of approximately 43% of homeobox genes, many of which are also oncogenes. To gain insights into the cause-and-effect relationship, we use a newly developed dCas9-SunTag-DNMT3A system to methylate genomic sites of interest. The locus-specific hypermethylation of gene-body canyon, but not promoter, of homeobox oncogene DLX1, can directly increase its gene expression. Conclusions Our pan-cancer analysis followed by functional validation reveals DNA hypermethylation as a novel epigenetic mechanism for homeobox oncogene upregulation.

Abstract Background DNA methylation is a heritable epigenetic mark, enabling stable but reversible gene repression. In mammalian cells, DNA methyltransferases (DNMTs) are responsible for modifying cytosine to 5-methylcytosine (5mC), which can be further oxidized by the TET dioxygenases to ultimately cause DNA demethylation. However, the genome-wide cooperation and functions of these two families of proteins, especially at large under-methylated regions, called canyons, remain largely unknown. Results Here we demonstrate that DNMT3A and TET1 function in a complementary and competitive manner in mouse embryonic stem cells to mediate proper epigenetic landscapes and gene expression. The longer isoform of DNMT3A, DNMT3A1, exhibits significant enrichment at distal promoters and canyon edges, but is excluded from proximal promoters and canyons where TET1 shows prominent binding. Deletion of Tet1 increases DNMT3A1 binding capacity at and around genes with wild-type TET1 binding. However, deletion of Dnmt3a has a minor effect on TET1 binding on chromatin, indicating that TET1 may limit DNA methylation partially by protecting its targets from DNMT3A and establishing boundaries for DNA methylation. Local CpG density may determine their complementary binding patterns and therefore that the methylation landscape is encoded in the DNA sequence. Furthermore, DNMT3A and TET1 impact histone modifications which in turn regulate gene expression. In particular, they regulate Polycomb Repressive Complex 2 (PRC2)-mediated H3K27me3 enrichment to constrain gene expression from bivalent promoters. Conclusions We conclude that DNMT3A and TET1 regulate the epigenome and gene expression at specific targets via their functional interplay.

Abstract Background DNA methylation has widespread effects on gene expression during development. However, our ability to assign specific function to regions of DNA methylation is limited by the poor correlation between global patterns of DNA methylation and gene expression. Results Here, we utilize nuclease-deactivated Cas9 protein fused to repetitive peptide epitopes (SunTag) recruiting multiple copies of antibody-fused de novo DNA methyltransferase 3A (DNMT3A) (dCas9-SunTag-DNMT3A) to amplify the local DNMT3A concentration to methylate genomic sites of interest. We demonstrate that dCas9-SunTag-DNMT3A dramatically increases CpG methylation at the HOXA5 locus in human embryonic kidney (HEK293T) cells. Furthermore, using a single guide RNA, dCas9-SunTag-DNMT3A is able to methylate a 4.5-kb genomic region and repress HOXA5 gene expression. Reduced representation bisulfite sequencing and RNA-seq show that dCas9-SunTag-DNMT3A methylates regions of interest with minimal impact on the global DNA methylome and transcriptome. Conclusions This effective and precise tool enables site-specific manipulation of DNA methylation and may be used to address the relationship between DNA methylation and gene expression.

Abstract Background Whole-genome bisulfite sequencing (WGBS) is the gold standard for studying landscape DNA methylation. Current computational methods for WGBS are mainly designed for gene regulatory regions with multiple under-methylated CpGs (UMCs), such as promoters and enhancers. Results To reliably predict the functional importance of single isolated UMCs across the genome, which is usually not achievable using traditional methods, we develop a multi-sample-based method. We identified 9421 sparse conserved under-methylated CpGs (scUMCs) from 31 high-quality methylomes, which are enriched in distal interacting anchor regions co-occupied by multiple chromatin-loop factors and are flanked by highly methylated CpGs. Moreover, cell lineage-specific scUMCs are associated with essential developmental genes, regulators of cell differentiation, and chromatin remodeling enzymes. Dynamic methylation levels of scUMCs correlate with the intensity of chromatin interactions and binding of looping factors as well as patterns of gene expression. Conclusions We introduce an innovative computational method for the identification of scUMCs, which are novel epigenetic features associated with high-order chromatin structure, opening new directions in the study of the inter-relationships between DNA methylation and chromatin structure.

Understanding how DNA methylation regulates gene expression requires the capacity to deploy it to regions of interest. The authors generate a highly rapid and locus-specific CpG methylation tool by fusing dCas9 to MQ1 DNA methyltransferase and show efficacy at multiple sitesin vitro and in vivo.

Few estuaries have inorganic carbon datasets with sufficient spatial and temporal coverage for identifying acidification baselines, seasonal cycles and trends. The Chesapeake Bay, though one of the most well-studied estuarine systems in the world, is no exception. To date, there have only been observational studies of inorganic carbon distribution and flux in lower bay sub-estuaries. Here, we address this knowledge gap with results from the first complete observational study of inorganic carbon along the main stem. Dissolved inorganic carbon (DIC) and total alkalinity (TA) increased from surface to bottom and north to south over the course of 2016, mainly driven by seasonal changes in river discharge, mixing, and biological carbon dioxide (CO2) removal at the surface and release in the subsurface. Upper, mid- and lower bay DIC and TA ranged from 1000–1300, 1300–1800, and 1700–1900 μmol kg-1, respectively. The pH range was large, with maximum values of 8.5 at the surface and minimums as low as 7.1 in bottom water in the upper and mid-bay. Seasonally, the upper bay was the most variable for DIC and TA, but pH was more variable in the mid-bay. Our results reveal that low pH is a continuing concern, despite reductions in nutrient inputs. There was active internal recycling of DIC and TA, with a large inorganic carbon removal in the upper bay and at salinities < 5 most months, and a large addition in the mid-salinities. In spring and summer, waters with salinities between 10 and 15 were a large source of DIC, likely due to remineralization of organic matter and dissolution of CaCO3. We estimate that the estuarine export flux of DIC and TA in 2016 was 40.3 ± 8.2 × 109 mol yr-1 and 47.1 ± 8.6 × 109 mol yr-1. The estuary was likely a large sink of DIC, and possibly a weak source of TA. These results support the argument that the Chesapeake Bay may be an exception to the long-standing assumption that estuaries are heterotrophic. Furthermore, they underline the importance of large estuarine systems for mitigating acidification in coastal ecosystems, since riverine chemistry is substantially modified within the estuary.

Background and objective The recurrence and metastasis of lung cancer is a tough problem worldwide. The aim of this study is to establish a novel Chinese lung adenocarcinoma cell line and its real bone-seeking clone sub-line for exploring the molecular mechanism of lung cancer metastasis. Methods The cells came from the pleural effusion of a sixtyfive years old female patient with lung adenocarcinoma and supraclavicular lymph node metastases. The gene expression was detected by real-time quantitative PCR. Intracardiac injection of the cells into nude mice was performed and in vivo imaging was obtained by bone scintigraphy and conventional radiography. Bone metastases were determined on bone scintigraphy and then the lesions were resected under deep anesthesia for bone metastasis cancer cell culture. The process was repeated for four cycles to obtain a real bone-seeking clone. Results The tumorigenesis rate started at 4th passage in immunodeficient mice via subcutaneously and as well as later passages. Approximately 1×106 cancer cells were injected into left cardiac ventricle of immunodeficient mice resulted bone metastasis sites were successfully revealed by bone scintigraphy and pathological diagnosis, the mandible (100%), scapula (33%), humerus (50%), vertebral column (50%), femur (66.7%) and accompanied invasion with other organs, the adrenal gland (17%), pulmonary (33%), liver (50%), submaxillary gland (33%) in the mice after inoculation two-three weeks. The chromosome karyotype analysis of the cells was subdiploid. Quantitative real-time PCR was used to examined and compared with SPC-A-1 lung adenocarcinoma, ESM1, VEGF-C, IL-6, IL-8, AR, SVIL, FN1 genes were overexpress. The novel cell was named CPA-Yang3. The femur metastasis cell was repeated in vivo-in vitro-in vivo with three cycles and harvested a real bone metastasis clone. It was named CPA-Yang3BM. Conclusion Tne characteristics of novel strain CPAYang3 is a highly metastasis cell line of Chinese lung adenocarcinoma and CPA-Yang3BM is a real bone-seeking clone.

Traditionally, there has been a widely accepted notion that the transition from acute to chronic pain follows a linear trajectory, where an injury leads to acute episodes, subacute stages, and progresses to a chronic pain condition. However, it appears that pain progression is much more complicated and individualized than this original unsupported assumption. It is now becoming apparent that, while this linear progression may occur, it is not the only path that pain, specifically low-back pain, follows. It is clear there is a definite need to evaluate how low-back pain trajectories are classified and, subsequently, how we can more effectively intervene during these progression stages. In order to better understand and manage pain conditions, we must examine the different pain trajectories, and develop a standard by which to use these classifications, so that clinicians can better identify and predict patient-needs and customize treatments for maximum efficacy. The present article examines the most recent trajectory research, and highlights the importance of developing a broader model for patient evaluation.

Background and objective The recurrence, metastasis and multidrug resistance (MDR) in lung cancer are the tough problems worldwide. This study was to establish a novel chinese lung adenocarcinoma cell line with high metastasis potential for exploring the mechanism of reccurrence, development and MDR in lung cancer. Methods The cell came from the abdominal dropsy of a fifty-six years old female patient with lung adenocarcinoma and the tumor markers CA125, CYFRA21-1, CEA, NSE were detected to be higher secretion by radioimmunoassay in the abdominal dropsy. Tumorigenicity of immunodeficient mice was confirmed in 8th passage. The cell growth curve was mapped. Analysis of chromosome karyotype was tested. The gene expression was measured by real-time quantitative PCR. Results The tumorigenesis rate started at 8th passage in 3/10 immunodeficient mice via subcutaneously and the fully tumorigenicity was at 11th passage as well as later passages. Under the microscope, the cell showed oval-shap and adherence. The chromosome karyotype analysis of the cells was sub-triploid. Approximately 1×106 and 1.5×106 cancerous cells were injected into left cardiac ventricle and tail vein of immunodeficient mice respectively. The results showed multiorgan metastasis in the mice after three-four weeks, including mandible, scapula, humerus, vertebral column, femur, rib and brain, liver, adrenal gland, pulmonary in the mice after inoculation. The bone metastasis rate was 100% in the tumor bearing mice by bone scintigraphy and pathology. Quantitative real-time PCR was used to examined and compared with SPC-A-1 lung adenocarcinoma, ESM1, VEGF-C, IL-6, IL-8, AR genes were overexpressed. The novel cell was named CPA-Yang2. Conclusion The characteristics of novel strain CPA-Yang2 is a highly metastasis cell line of Chinese lung adenocarcinoma. It has stable traits, highly metastasis ability and maybe is a MDR lung cancerous cell line. Of course, it’s a good experimental model for lung cancer research.

Background and objective Lung cancer is a common malignancy and is the major determinant of overall cancer mortality worldwidely. Approximately 70% of lung cancer patients will die from metastatic diseases. The aim of this study is to establish a Chinese lung adenocarcinoma cell line with high metastasis potency for exploring the mechanism of occurrence and development in lung cancer. Methods The cell came from the pericardial effusion of a fifty-year old male patient with lung adenocarcinoma and the cells in primary culture were obtained successfully. Immunodeficient mice tumorigenicity was assayed. The cell growth curve was mappinged. Analysis of chromosome karyotype was tested. Tumor marker was detected by radioimmunoassay. The gene expression was measured by real-time quantitative PCR. Results The first passage cells were planted in immunodeficient mice subcutaneously and the tumorigenesis rate was 100% as well as later passages. Under the microscope, the cell showed larger and semi-suspension, semi-adherence. Approximately 0.8×106 cancerous cells were injected into left cardiac ventricle or tail vein of immunodeficient mice resulted start to appear lower limb paralysis and spine swelling deformation in the mice after inoculation two-three weeks. The bone metastasis rate was 90% in the tumor bearing mice by bone scintigraphy and pathology and only pulmonary metastasis 10% at the same time. The chromosome karyotype analysis of the cells was sub-triploid. The tumor marker CEA was detected in higher secretion by radioimmunoassay in the cell culture suspension. Quantitative real-time PCR was used to examined and compared SPC-A-1 lung adenocarcinoma, VEGF-C, IL-6, IL-8, genes were overexpressed. The novel cell line was named CPA-Yang1. Conclusion Tne novel strain CPA-Yang1 is an parental cell with characteristics of bone metastasis of Chinese lung adenocarcinoma. It has stable traits, highly metastatic ability and a good experimental model for lung cancer research.

Breast cancer has various molecular subtypes and displays high heterogeneity. Aberrant DNA methylation is involved in tumor origin, development and progression. Moreover, distinct DNA methylation patterns are associated with specific breast cancer subtypes. We explored DNA methylation patterns in association with gene expression to assess their impact on the prognosis of breast cancer based on Infinium 450K arrays (training set) from The Cancer Genome Atlas (TCGA). The DNA methylation patterns of 12 featured genes that had a high correlation with gene expression were identified through univariate and multivariable Cox proportional hazards models and used to define the methylation risk score (MRS). An improved ability to distinguish the power of the DNA methylation pattern from the 12 featured genes (p = 0.00103) was observed compared with the average methylation levels (p = 0.956) or gene expression (p = 0.909). Furthermore, MRS provided a good prognostic value for breast cancers even when the patients had the same receptor status. We found that ER-, PR- or Her2- samples with high-MRS had the worst 5-year survival rate and overall survival time. An independent test set including 28 patients with death as an outcome was used to test the validity of the MRS of the 12 featured genes; this analysis obtained a prognostic value equivalent to the training set. The predict power was validated through two independent datasets from the GEO database. The DNA methylation pattern is a powerful predictor of breast cancer survival, and can predict outcomes of the same breast cancer molecular subtypes.

Abnormal DNA methylation is known as playing an important role in the tumorgenesis. It is helpful for distinguishing the specificity of diagnosis and therapeutic targets for cancers based on characteristics of DNA methylation patterns across cancers. High throughput DNA methylation analysis provides the possibility to comprehensively filter the epigenetics diversity across various cancers. We integrated whole-genome methylation data detected in 798 samples from seven cancers. The hierarchical clustering revealed the existence of cancer-specific methylation pattern. Then we identified 331 differentially methylated genes across these cancers, most of which (266) were specifically differential methylation in unique cancer. A DNA methylation correlation network (DMCN) was built based on the methylation correlation between these genes. It was shown the hubs in the DMCN were inclined to cancer-specific genes in seven cancers. Further survival analysis using the part of genes in the DMCN revealed high-risk group and low-risk group were distinguished by seven biomarkers (PCDHB15, WBSCR17, IGF1, GYPC, CYGB, ACTG2, and PRRT1) in breast cancer and eight biomarkers (ZBTB32, OR51B4, CCL8, TMEFF2, SALL3, GPSM1, MAGEA8, and SALL1) in colon cancer, respectively. At last, a protein-protein interaction network was introduced to verify the biological function of differentially methylated genes. It was shown that MAP3K14, PTN, ACVR1 and HCK sharing different DNA methylation and gene expression across cancers were relatively high degree distribution in PPI network. The study suggested that not only the identified cancer-specific genes provided reference for individual treatment but also the relationship across cancers could be explained by differential DNA methylation.