A CT-based radiomics nomogram for prediction of human epidermal growth factor receptor 2 status in patients with gastric cancer

Objective: To develop and validate a computed tomography(CT)-based radiomics nomogram for predicting human epidermal growth factor receptor 2(HER2) status in patients with gastric cancer.Methods: This retrospective study included 134 patients with gastric cancer(HER2-negative: n=87;HER2-positive: n=47) from April 2013 to March 2018, who were then randomly divided into training(n=94) and validation(n=40) cohorts. Radiomics features were obtained from the CT images showing gastric cancer. Least absolute shrinkage and selection operator(LASSO) regression analysis was utilized for building the radiomics signature. A multivariable logistic regression method was applied to develop a prediction model incorporating the radiomics signature and independent clinicopathologic risk predictors, which were then visualized as a radiomics nomogram. The predictive performance of the nomogram was assessed in the training and validation cohorts.Results: The radiomics signature was significantly associated with HER2 status in both training(P<0.001) and validation(P=0.023) cohorts. The prediction model that incorporated the radiomics signature and carcinoembryonic antigen(CEA) level demonstrated good discriminative performance for HER2 status prediction,with an area under the curve(AUC) of 0.799 [95% confidence interval(95% CI): 0.704-0.894] in the training cohort and 0.771(95% CI: 0.607-0.934) in the validation cohort. The calibration curve of the radiomics nomogram also showed good calibration. Decision curve analysis showed that the radiomics nomogram was useful.Conclusions: We built and validated a radiomics nomogram with good performance for HER2 status prediction in gastric cancer. This radiomics nomogram could serve as a non-invasive tool to predict HER2 status and guide clinical treatment.

Bioreactor design and validation for manufacturing strategies in tissue engineering

The fields of regenerative medicine and tissue engineering offer new therapeutic options to restore,maintain or improve tissue function following disease or injury.To maximize the biological function of a tissue-engineered clinical product,specific conditions must be maintained within a bioreactor to allow the maturation of the product in preparation for implantation.Specifically,the bioreactor should be designed to mimic the mechanical,electrochemical and biochemical environment that the product will be exposed to in vivo.Real-time monitoring of the functional capacity of tissue-engineered products during manufacturing is a critical component of the quality management process.The present review provides a brief overview of bioreactor engineering considerations.In addition,strategies for bioreactor automation,in-line product monitoring and quality assurance are discussed.

Switching variability index based multiple strategy CFAR detector

A switching variability index （SVl） constant false alarm rate （CFAR） detector is proposed for improving the detection performance of VI-CFAR detectors in multiple targets backgrounds. When the presence of non-homogeneity in CFAR reference windows is indicated by a VI-CFAR detector, a switching- CFAR detector is introduced to optimize the performance of the VI-CFAR detector in homogeneous, multiple targets and clutter edge backgrounds. The structure and parameters selection method of the SVI-CFAR detector is presented. Comparisons with classic CFAR detectors and recently proposed detectors are also given. Theoretical analysis and simulation results show that SVICFAR detector maintains the good performance of the VI-CFAR detector in homogeneous and clutter edge backgrounds, while greatly improving the capacity of anti-multi targets.

Super enhancer inhibitors suppress MYC driven transcriptional amplification and tumor progression in osteosarcoma

Osteosarcoma is the most common primary bone sarcoma that mostly occurs in young adults. The causes of osteosarcoma are heterogeneous and still not fully understood. Identification of novel, important oncogenic factors in osteosarcoma and development of better, effective therapeutic approaches are in urgent need for better treatment of osteosarcoma patients. In this study, we uncovered that the oncogene MYC is significantly upregulated in metastastic osteosarcoma samples. In addition, high MYC expression is associated with poor survival of osteosarcoma patients. Analysis of MYC targets in osteosarcoma revealed that most of the osteosarcoma super enhancer genes are bound by MYC. Treatment of osteosarcoma cells with super enhancer inhibitors THZ1 and JQ1 effectively suppresses the proliferation, migration, and invasion of osteosarcoma cells. Mechanistically,THZ1 treatment suppresses a large group of super enhancer containing MYC target genes including CDK6 and TGFB2. These findings revealed that the MYC-driven super enhancer signaling is crucial for the osteosarcoma tumorigenesis and targeting the MYC/super enhancer axis represents as a promising therapeutic strategy for treatment of osteosarcoma patients.

美国国家癌症学会生物医学信息战略

非常高兴有机会来到协和,这里有很多老朋友。我在美国国立肿瘤研究所（National Cancer Institute,NCI）工作了5年,专攻生物信息学。今天的演讲分为三个部分：第一部分,从NCI角度简要介绍生物信息领域出现的新动态与新需求;第二部分,如何把生物信息技术转化到一些平台的发展中;

RePhine: An Integrative Method for Identification of Drug Response-related Transcriptional Regulators

Transcriptional regulators(TRs)participate in essential processes in cancer pathogenesis and are critical therapeutic targets.Identification of drug response-related TRs from cell line-based compound screening data is often challenging due to low m RNA abundance of TRs,protein modifications,and other confounders(CFs).In this study,we developed a regression-based pharmacogenomic and Ch IP-seq data integration method(Re Phine)to infer the impact of TRs on drug response through integrative analyses of pharmacogenomic and Ch IP-seq data.Re Phine was evaluated in simulation and pharmacogenomic data and was applied to pan-cancer datasets with the goal of biological discovery.In simulation data with added noises or CFs and in pharmacogenomic data,Re Phine demonstrated an improved performance in comparison with three commonly used methods(including Pearson correlation analysis,logistic regression model,and gene set enrichment analysis).Utilizing Re Phine and Cancer Cell Line Encyclopedia data,we observed that Re Phinederived TR signatures could effectively cluster drugs with different mechanisms of action.Re Phine predicted that loss-offunction of EZH2/PRC2 reduces cancer cell sensitivity toward the BRAF inhibitor PLX4720.Experimental validation confirmed that pharmacological EZH2 inhibition increases the resistance of cancer cells to PLX4720 treatment.Our results support that Re Phine is a useful tool for inferring drug response-related TRs and for potential therapeutic applications.The source code for Re Phine is freely available at https://github.com/coexps/Re Phine.

Comprehensive Analysis of Ubiquitously Expressed Genes in Humans from A Data-driven Perspective

Comprehensive characterization of spatial and temporal gene expression patterns in humans is critical for uncovering the regulatory codes of the human genome and understanding the molecular mechanisms of human diseases.Ubiquitously expressed genes(UEGs)refer to the genes expressed across a majority of,if not all,phenotypic and physiological conditions of an organism.It is known that many human genes are broadly expressed across tissues.However,most previous UEG studies have only focused on providing a list of UEGs without capturing their global expression patterns,thus limiting the potential use of UEG information.In this study,we proposed a novel data-driven framework to leverage the extensive collection of40,000 human transcriptomes to derive a list of UEGs and their corresponding global expression patterns,which offers a valuable resource to further characterize human transcriptome.Our results suggest that about half(12,234;49.01%)of the human genes are expressed in at least 80%of human transcriptomes,and the median size of the human transcriptome is 16,342 genes(65.44%).Through gene clustering,we identified a set of UEGs,named LoVarUEGs,which have stable expression across human transcriptomes and can be used as internal reference genes for expression measurement.To further demonstrate the usefulness of this resource,we evaluated the global expression patterns for 16 previously predicted disallowed genes in islet beta cells and found that seven of these genes showed relatively more varied expression patterns,suggesting that the repression of these genes may not be unique to islet beta cells.

Increasing prevalence and influencing factors of childhood asthma: a cross-sectional study in Shanghai, China

Background Asthma has been a global problem,especially in children.We aim to evaluate the contemporary prevalence and influencing factors of asthma among children aged 3–7 years in Shanghai,China.Methods A random sample of preschool children was included in this study.The International Study of Asthma and Allergies in Childhood questionnaire was adopted to assess the childhood asthma.Multivariable logistic regression models were used to evaluate the associations between independent variables and childhood asthma.Results Of 6389 preschool children who were invited to take part in this study,6163(response rate:96.5%)completed the questionnaire and were included in the analysis.The overall prevalence of asthma was 14.6%which increased more than six folds from 2.1%in 1990.Being male,younger age,preterm delivery,being born in spring or autumn,being delivered by elective cesarean section without indication,miscarriage,high socioeconomic status,having allergy history,and exposure to passive smoking,latex paint,and dust were potential risk factors for childhood asthma.Spending more time outdoors(>30 min/day),having indoor plants,and cleaning rooms more frequently were potential protective factors.Conclusions The prevalence of childhood asthma in Shanghai has increased dramatically during the past three decades.The findings about risk and protective factors of childhood asthma could be used to develop appropriate strategies to prevent and control childhood asthma in Shanghai and in other similar metropolitan cities.

FAIR Convergence Matrix:Optimizing the Reuse of Existing FAIR-Related Resources

The FAIR principles articulate the behaviors expected from digital artifacts that are Findable,Accessible,Interoperable and Reusable by machines and by people.Although by now widely accepted,the FAIR Principles by design do not explicitly consider actual implementation choices enabling FAIR behaviors.As different communities have their own,often well-established implementation preferences and priorities for data reuse,coordinating a broadly accepted,widely used FAIR implementation approach remains a global challenge.In an effort to accelerate broad community convergence on FAIR implementation options,the GO FAIR community has launched the development of the FAIR Convergence Matrix.The Matrix is a platform that compiles for any community of practice,an inventory of their self-declared FAIR implementation choices and challenges.The Convergence Matrix is itself a FAIR resource,openly available,and encourages voluntary participation by any self-identified community of practice(not only the GO FAIR Implementation Networks).Based on patterns of use and reuse of existing resources,the Convergence Matrix supports the transparent derivation of strategies that optimally coordinate convergence on standards and technologies in the emerging Internet of FAIR Data and Services.

Computational prediction and validation of specific EmbR binding site on PknH

Tuberculosis drug resistance continues to threaten global health but the underline molecular mechanisms are not clear.Ethambutol(EMB),one of the well-known first-line drugs in tuberculosis treatment is,unfortunately,not free from drug resistance problems.Genomic studies have shown that some genetic mutations in Mycobacterium tuberculosis(Mtb)EmbR,and EmbC/A/B genes cause EMB resistance.EmbR-PknH pair controls embC/A/B operon,which encodes EmbC/A/B genes,and EMB interacts with EmbA/B proteins.However,the EmbR binding site on PknH was unknown.We conducted molecular simulation on the EmbR-peptides binding structures and discovered phosphorylated PknH 273-280(N′-HEALS^(P)DPD-C′)makesβstrand with the EmbR FHA domain,asβ-MoRF(MoRF;molecular recognition feature)does at its binding site.Hydrogen bond number analysis also supported the peptides’β-MoRF forming activity at the EmbR FHA domain.Also,we discovered that previously known phosphorylation residues might have their chronological order according to the phosphorylation status.The discovery validated that Mtb PknH 273-280(N′-HEALSDPD-C′)has reliable EmbR binding affinity.This approach is revolutionary in the computer-aided drug discovery field,because it is the first trial to discover the protein-protein interaction site,and find binding partner in nature from this site.