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Guo, Yichen

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Guo

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Yichen

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Guo, Yichen

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Now showing 1 - 3 of 3
  • Publication

    Whole blood microRNA markers are associated with acute respiratory distress syndrome

    (Springer International Publishing, 2017) Zhu, Zhaozhong; Liang, Liming; Zhang, Ruyang; Wei, Yongyue; Su, Li; Tejera, Paula; Guo, Yichen; Wang, Zhaoxi; Lu, Quan; Baccarelli, Andrea; Zhu, Xi; Bajwa, Ednan; Taylor Thompson, B.; Shi, Guo-Ping; Christiani, David

    Background: MicroRNAs (miRNAs) can play important roles in inflammation and infection, which are common manifestations of acute respiratory distress syndrome (ARDS). We assessed if whole blood miRNAs were potential diagnostic biomarkers for human ARDS. Methods: This nested case-control study (N = 530) examined a cohort of ARDS patients and critically ill at-risk controls. Whole blood miRNA profiles and logistic regression analyses identified miRNAs correlated with ARDS. Stratification analysis also assessed selected miRNA markers for their role in sepsis and pneumonia associated with ARDS. Receiver operating characteristic (ROC) analysis evaluated miRNA diagnostic performance, along with Lung Injury Prediction Score (LIPS). Results: Statistical analyses were performed on 294 miRNAs, selected from 754 miRNAs after quality control screening. Logistic regression identified 22 miRNAs from a 156-patient discovery cohort as potential risk or protective markers of ARDS. Three miRNAs—miR-181a, miR-92a, and miR-424—from the discovery cohort remained significantly associated with ARDS in a 373-patient independent validation cohort (FDR q < 0.05) and meta-analysis (p < 0.001). ROC analyses demonstrated a LIPS baseline area-under-the-curve (AUC) value of ARDS of 0.708 (95% CI 0.651–0.766). Addition of miR-181a, miR-92a, and miR-424 to LIPS increased baseline AUC to 0.723 (95% CI 0.667–0.778), with a relative integrated discrimination improvement of 2.40 (p = 0.005) and a category-free net reclassification index of 27.21% (p = 0.01). Conclusions: miR-181a and miR-92a are risk biomarkers for ARDS, whereas miR-424 is a protective biomarker. Addition of these miRNAs to LIPS can improve the risk estimate for ARDS. Electronic supplementary material The online version of this article (10.1186/s40635-017-0155-0) contains supplementary material, which is available to authorized users.

  • Publication

    Epigenetic modifications in KDM lysine demethylases associate with survival of early-stage NSCLC

    (BioMed Central, 2018) Wei, Yongyue; Liang, Junya; Zhang, Ruyang; Guo, Yichen; Shen, Sipeng; Su, Li; Lin, Xihong; Moran, Sebastian; Helland, Åslaug; Bjaanæs, Maria M.; Karlsson, Anna; Planck, Maria; Esteller, Manel; Fleischer, Thomas; Staaf, Johan; Zhao, Yang; Chen, Feng; Christiani, David

    Background: KDM lysine demethylase family members are related to lung cancer clinical outcomes and are potential biomarkers for chemotherapeutics. However, little is known about epigenetic alterations in KDM genes and their roles in lung cancer survival. Methods: Tumor tissue samples of 1230 early-stage non-small cell lung cancer (NSCLC) patients were collected from the five independent cohorts. The 393 methylation sites in KDM genes were extracted from epigenome-wide datasets and analyzed by weighted random forest (Ranger) in discovery phase and validation dataset, respectively. The variable importance scores (VIS) for the sites in top 5% of both discovery and validation sets were carried forward for Cox regression to further evaluate the association with patient’s overall survival. TCGA transcriptomic data were used to evaluate the correlation with the corresponding DNA methylation. Results: DNA methylation at sites cg11637544 in KDM2A and cg26662347 in KDM1A were in the top 5% of VIS in both discovery phase and validation for squamous cell carcinomas (SCC), which were also significantly associated with SCC survival (HRcg11637544 = 1.32, 95%CI, 1.16–1.50, P = 1.1 × 10−4; HRcg26662347 = 1.88, 95%CI, 1.37–2.60, P = 3.7 × 10−3), and correlated with corresponding gene expression (cg11637544 for KDM2A, P = 1.3 × 10−10; cg26662347 for KDM1A P = 1.5 × 10−5). In addition, by using flexible criteria for Ranger analysis followed by survival classification tree analysis, we identified four clusters for adenocarcinomas and five clusters for squamous cell carcinomas which showed a considerable difference of clinical outcomes with statistical significance. Conclusions: These findings highlight the association between somatic DNA methylation in KDM genes and early-stage NSCLC patient survival, which may reveal potential epigenetic therapeutic targets. Electronic supplementary material The online version of this article (10.1186/s13148-018-0474-3) contains supplementary material, which is available to authorized users.

  • Publication

    A multi‐omic study reveals BTG2 as a reliable prognostic marker for early‐stage non‐small cell lung cancer

    (John Wiley and Sons Inc., 2018) Shen, Sipeng; Zhang, Ruyang; Guo, Yichen; Loehrer, Elizabeth; Wei, Yongyue; Zhu, Ying; Yuan, Qianyu; Moran, Sebastian; Fleischer, Thomas; Bjaanæs, Maria M.; Karlsson, Anna; Planck, Maria; Staaf, Johan; Helland, Åslaug; Esteller, Manel; Su, Li; Chen, Feng; Christiani, David

    B‐cell translocation gene 2 (BTG2) is a tumour suppressor protein known to be downregulated in several types of cancer. In this study, we investigated a potential role for BTG2 in early‐stage non‐small cell lung cancer (NSCLC) survival. We analysed BTG2 methylation data from 1230 early‐stage NSCLC patients from five international cohorts, as well as gene expression data from 3038 lung cancer cases from multiple cohorts. Three CpG probes (cg01798157, cg06373167, cg23371584) that detected BTG2 hypermethylation in tumour tissues were associated with lower overall survival. The prognostic model based on methylation could distinguish patient survival in the four cohorts [hazard ratio (HR) range, 1.51–2.21] and the independent validation set (HR = 1.85). In the expression analysis, BTG2 expression was positively correlated with survival in each cohort (HR range, 0.28–0.68), which we confirmed with meta‐analysis (HR = 0.61, 95% CI 0.54–0.68). The three CpG probes were all negatively correlated with BTG2 expression. Importantly, an integrative model of BTG2 methylation, expression and clinical information showed better predictive ability in the training set and validation set. In conclusion, the methylation and integrated prognostic signatures based on BTG2 are stable and reliable biomarkers for early‐stage NSCLC. They may have new applications for appropriate clinical adjuvant trials and personalized treatments in the future.