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Featured researches published by Junmei Ai.


PLOS ONE | 2011

Analysis of Common and Specific Mechanisms of Liver Function Affected by Nitrotoluene Compounds

Youping Deng; Sharon A. Meyer; Xin Guan; Barbara Lynn Escalon; Junmei Ai; Mitchell S. Wilbanks; Ruth Welti; Natàlia Garcia-Reyero; Edward J. Perkins

Background Nitrotoluenes are widely used chemical manufacturing and munitions applications. This group of chemicals has been shown to cause a range of effects from anemia and hypercholesterolemia to testicular atrophy. We have examined the molecular and functional effects of five different, but structurally related, nitrotoluenes on using an integrative systems biology approach to gain insight into common and disparate mechanisms underlying effects caused by these chemicals. Methodology/Principal Findings Sprague-Dawley female rats were exposed via gavage to one of five concentrations of one of five nitrotoluenes [2,4,6-trinitrotoluene (TNT), 2-amino-4,6-dinitrotoluene (2ADNT) 4-amino-2,6-dinitrotoulene (4ADNT), 2,4-dinitrotoluene (2,4DNT) and 2,6-dinitrotoluene (2,6DNT)] with necropsy and tissue collection at 24 or 48 h. Gene expression profile results correlated well with clinical data and liver histopathology that lead to the concept that hematotoxicity was followed by hepatotoxicity. Overall, 2,4DNT, 2,6DNT and TNT had stronger effects than 2ADNT and 4ADNT. Common functional terms, gene expression patterns, pathways and networks were regulated across all nitrotoluenes. These pathways included NRF2-mediated oxidative stress response, aryl hydrocarbon receptor signaling, LPS/IL-1 mediated inhibition of RXR function, xenobiotic metabolism signaling and metabolism of xenobiotics by cytochrome P450. One biological process common to all compounds, lipid metabolism, was found to be impacted both at the transcriptional and lipid production level. Conclusions/Significance A systems biology strategy was used to identify biochemical pathways affected by five nitroaromatic compounds and to integrate data that tie biochemical alterations to pathological changes. An integrative graphical network model was constructed by combining genomic, gene pathway, lipidomic, and physiological endpoint results to better understand mechanisms of liver toxicity and physiological endpoints affected by these compounds.


Journal of Cancer | 2016

Evaluation of Plasma miR-21 and miR-152 as Diagnostic Biomarkers for Common Types of Human Cancers.

Hankui Chen; Helu Liu; Hanqing Zou; Rui Chen; Yuhong Dou; Shile Sheng; Shengming Dai; Junmei Ai; Joshua E. Melson; Rick A. Kittles; Mehdi Pirooznia; Michael J. Liptay; Jeffrey A. Borgia; Youping Deng

Stable blood based miRNA species have allowed for the differentiation of patients with various types of cancer. Therefore, specific blood-based miRNA might be considered as a methodology which could be informative of the presence of cancer potentially from multiple distinct organ sites. Recently, miR-21 has been identified as an “oncomir” in various tumors while miR-152 as a tumor suppressor. In this study, we investigated whether circulating miR-21 and miR-152 can be used for early detection of lung cancer (LuCa), colorectal carcinoma (CRC), breast cancer (BrCa) and prostate cancer (PCa), with distinguishing cancer from various benign lesions on these organ sites. We measured the two miRNA levels by using real-time RT-PCR in plasma samples from a total of 204 cancer patients, 159 various benign lesions, and 228 normal subjects. We observed significantly elevated expression of miR-21 and miR-152 in LuCa, CRC, and BrCa when compared with normal controls. We also found upregulation of plasma miR-21 and miR-152 levels in patients with benign lesions of lung and breast, as compared to normal controls, respectively. No significant expression variation of the two miRNAs was observed in PCa or prostatic benign lesions as compared to healthy controls. Receiver operating characteristic (ROC) analyses revealed that miR-21 and/or miR-152 can discriminate LuCa, CRC and BrCa from normal controls. Our results suggest that plasma miR-21 and miR-152 may serve as non-specific noninvasive biomarkers for early screening of LuCa, CRC, and BrCa, but not PCa.


Oncotarget | 2016

Integrative microRNA and gene profiling data analysis reveals novel biomarkers and mechanisms for lung cancer.

Ling Hu; Junmei Ai; Hui Long; Weijun Liu; Xiaomei Wang; Yi Zuo; Yan Li; Qingming Wu; Youping Deng

Background Studies on the accuracy of microRNAs (miRNAs) in diagnosing non-small cell lung cancer (NSCLC) have still controversial. Therefore, we conduct to systematically identify miRNAs related to NSCLC, and their target genes expression changes using microarray data sets. Methods We screened out five miRNAs and six genes microarray data sets that contained miRNAs and genes expression in NSCLC from Gene Expression Omnibus. Results Our analysis results indicated that fourteen miRNAs were significantly dysregulated in NSCLC. Five of them were up-regulated (miR-9, miR-708, miR-296-3p, miR-892b, miR-140-5P) while nine were down-regulated (miR-584, miR-218, miR-30b, miR-522, miR486-5P, miR-34c-3p, miR-34b, miR-516b, miR-592). The integrating diagnosis sensitivity (SE) and specificity (SP) were 82.6% and 89.9%, respectively. We also found that 4 target genes (p < 0.05, fold change > 2.0) were significant correlation with the 14 discovered miRNAs, and the classifiers we built from one training set predicted the validation set with higher accuracy (SE = 0.987, SP = 0.824). Conclusions Our results demonstrate that integrating miRNAs and target genes are valuable for identifying promising biomarkers, and provided a new insight on underlying mechanism of NSCLC. Further, our well-designed validation studies surely warrant the investigation of the role of target genes related to these 14 miRNAs in the prediction and development of NSCLC.


Oncotarget | 2016

Plasma lipidomics profiling identified lipid biomarkers in distinguishing early-stage breast cancer from benign lesions

Xiaoli Chen; Hankui Chen; Meiyu Dai; Junmei Ai; Yan Li; Brett Mahon; Shengming Dai; Youping Deng

Background Breast cancer is very common and highly fatal in women. Current non-invasive detection methods like mammograms are unsatisfactory. Lipidomics, a promising detection method, may serve as a novel prognostic approach for breast cancer in high-risk patients. Results According the predictive model, the combination of 15 lipid species had high diagnostic value. In the training set, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the combination of these 15 lipid species were 83.3%, 92.7%, 89.7%, and 87.9%, respectively. The AUC in the training set was 0.926 (95% CI 0.869-0.982). Similar results were found in the validation set, with the sensitivity, specificity, PPV and NPV at 81.0%, 94.5%, 91.9%, and 86.7%, respectively. The AUC was 0.938 (95% CI 0.889-0.986) in the validation set. Methods Using triple quadrupole liquid chromatography electrospray ionization tandem mass spectrometry, this study was to detect global lipid profiling of a total of 194 plasma samples from 84 patients with early-stage breast cancer (stage 0–II) and 110 patients with benign breast disease included in a training set and a validation set. A binary logistic regression was used to build a predictive model for evaluating the lipid species as potential biomarkers in the diagnosis of breast cancer. Conclusion The combination of these 15 lipid species as a panel could be used as plasma biomarkers for the diagnosis of breast cancer.


BMC Systems Biology | 2010

In vitro gene regulatory networks predict in vivo function of liver

Youping Deng; David R. Johnson; Xin Guan; Choo-Yaw Ang; Junmei Ai; Edward J. Perkins

BackgroundEvolution of toxicity testing is predicated upon using in vitro cell based systems to rapidly screen and predict how a chemical might cause toxicity to an organ in vivo. However, the degree to which we can extend in vitro results to in vivo activity and possible mechanisms of action remains to be fully addressed.ResultsHere we use the nitroaromatic 2,4,6-trinitrotoluene (TNT) as a model chemical to compare and determine how we might extrapolate from in vitro data to in vivo effects. We found 341 transcripts differentially expressed in common among in vitro and in vivo assays in response to TNT. The major functional term corresponding to these transcripts was cell cycle. Similarly modulated common pathways were identified between in vitro and in vivo. Furthermore, we uncovered the conserved common transcriptional gene regulatory networks between in vitro and in vivo cellular liver systems that responded to TNT exposure, which mainly contain 2 subnetwork modules: PTTG1 and PIR centered networks. Interestingly, all 7 genes in the PTTG1 module were involved in cell cycle and downregulated by TNT both in vitro and in vivo.ConclusionsThe results of our investigation of TNT effects on gene expression in liver suggest that gene regulatory networks obtained from an in vitro system can predict in vivo function and mechanisms. Inhibiting PTTG1 and its targeted cell cyle related genes could be key machanism for TNT induced liver toxicity.


International Journal of Cancer | 2014

Commonality and differences of methylation signatures in the plasma of patients with pancreatic cancer and colorectal cancer

Joshua E. Melson; Yan Li; Elisa Cassinotti; Anatoliy A. Melnikov; Luigi Boni; Junmei Ai; Michael Greenspan; Sohrab Mobarhan; Victor V. Levenson; Youping Deng

Profiling of DNA methylation status of specific genes is a way to screen for colorectal cancer (CRC) and pancreatic cancer (PC) in blood. The commonality of methylation status of cancer‐related tumor suppressor genes between CRC and PC is largely unknown. Methylation status of 56 cancer‐related genes was compared in plasma of patients in the following cohorts: CRC, PC and healthy controls. Cross validation determined the best model by area under ROC curve (AUC) to differentiate cancer methylation profiles from controls. Optimal preferential gene methylation signatures were derived to differentiate either cancer (CRC or PC) from controls. For CRC alone, a three gene signature (CYCD2, HIC and VHL) had an AUC 0.9310, sensitivity (Sens) = 0.826, specificity (Spec) = 0.9383. For PC alone, an optimal signature consisted of five genes (VHL, MYF3, TMS, GPC3 and SRBC), AUC 0.848; Sens = 0.807, Spec = 0.666. Combined PC and CRC signature or “combined cancer signature” was derived to differentiate either CRC and PC from controls (MDR1, SRBC, VHL, MUC2, RB1, SYK and GPC3) AUC = 0.8177, Sens = 0.6316 Spec = 0.840. In a validation cohort, N = 10 CRC patients, the optimal CRC signature (CYCD2, HIC and VHL) had AUC 0.900. In all derived signatures (CRC, PC and combined cancer signature) the optimal panel used preferential VHL methylation. In conclusion, CRC and PC differ in specific genes methylated in plasma other than VHL. Preferential methylation of VHL is shared in the optimal signature for CRC alone, PC alone and combined PC and CRC. Future investigations may identify additional methylation markers informative for the presence of both CRC and PC.


BMC Genomics | 2010

A new approach to construct pathway connected networks and its application in dose responsive gene expression profiles of rat liver regulated by 2,4DNT.

Sudhir R Chowbina; Youping Deng; Junmei Ai; Xiaogang Wu; Xin Guan; Mitchell S. Wilbanks; Barbara Lynn Escalon; Sharon A. Meyer; Edward J. Perkins; Jake Y. Chen

BackgroundMilitary and industrial activities have lead to reported release of 2,4-dinitrotoluene (2,4DNT) into soil, groundwater or surface water. It has been reported that 2,4DNT can induce toxic effects on humans and other organisms. However the mechanism of 2,4DNT induced toxicity is still unclear. Although a series of methods for gene network construction have been developed, few instances of applying such technology to generate pathway connected networks have been reported.ResultsMicroarray analyses were conducted using liver tissue of rats collected 24h after exposure to a single oral gavage with one of five concentrations of 2,4DNT. We observed a strong dose response of differentially expressed genes after 2,4DNT treatment. The most affected pathways included: long term depression, breast cancer regulation by stathmin1, WNT Signaling; and PI3K signaling pathways. In addition, we propose a new approach to construct pathway connected networks regulated by 2,4DNT. We also observed clear dose response pathway networks regulated by 2,4DNT.ConclusionsWe developed a new method for constructing pathway connected networks. This new method was successfully applied to microarray data from liver tissue of 2,4DNT exposed animals and resulted in the identification of unique dose responsive biomarkers in regards to affected pathways.


Oncotarget | 2017

Global lipidomics identified plasma lipids as novel biomarkers for early detection of lung cancer

Zongtao Yu; Hankui Chen; Junmei Ai; Yong Zhu; Yan Li; Jeffrey A. Borgia; Jin-Song Yang; Jicai Zhang; Bin Jiang; Wei Gu; Youping Deng

Purpose Lipids play roles in membrane structure, energy storage, and signal transduction as well as in human cancers. Here we adopt lipidomics to identify plasma lipid markers for early screening and detection of lung cancer. Experimental Design Using mass spectrometry, we profiled 390 individual lipids using training and validation strategy in a total of 346 plasma samples from 199 early NSCLC patients, including 113 adenocacinoma and 86 squamous cell cancers (SqCC), and from 147 healthy controls. Results In the training stage, we found distinct lipid groups that were significantly distributed between NSCLC cases and healthy controls. We further defined a panel of four lipid markers (LPE(18:1), ePE(40:4), C(18:2)CE and SM(22:0)) for prediction of early cancer with a accuracy of 82.3% AUC (Area under ROC curve), sensitivity of 81.9% and specificity of 70.7% at the training stage and yielded the predictive power with accuracy (AUC,80.8%), sensitivity 78.7%, specificity 69.4% and in the validation stage. Conclusions Using lipidomics we identified several lipid markers capable of discerning early stage lung carcinoma from healthy individuals, which might be further developed as a quick, safe blood test for early diagnosis of this disease.


Oncology Letters | 2018

Global lipidomics reveals two plasma lipids as novel biomarkers for the detection of squamous cell lung cancer: A pilot study

Zongtao Yu; Hankui Chen; Yong Zhu; Junmei Ai; Yan Li; Wei Gu; Jeffrey A. Borgia; Jicai Zhang; Bin Jiang; Wei Chen; Youping Deng

Lipids are known to serve important roles in energy storage, membrane structure and signal transduction as well as in human cancers. In the present study, lipidomics was employed in order to identify plasma lipid markers for the early detection of lung cancer. Mass spectrometry was performed to profile 390 individual lipids in 44 plasma samples obtained from a training discovery cohort, which included 22 patients with squamous cell lung carcinoma (SqCC) and 22 high-risk individuals. An additional cohort that included 22 high-risk individuals and 22 patients with SqCC was further used for validation. During the training stage, a total of 20 distinct lipids that were significantly distributed between the high-risk and SqCC cases, were identified. A panel of 2 lipid markers (C18:2 cholesterol esters and sphingomyelin 22:0) were then further defined using the training accuracy values of 95.5% sensitivity, 90.9% specificity and 95.2% area under the receiver operating characteristic curve (AUC). The validation accuracy values applied for the additional cohort were 93.9% sensitivity, 92.9% specificity and 98.7% AUC. Thus, in the present study, 2 lipid markers that were able to discern SqCC patients from high-risk individuals with a high sensitivity, specificity and accuracy, were identified. These results may provide vital information for the development of a quick and safe blood test for the early diagnosis of SqCC.


BMC Genomics | 2018

Plasma small ncRNA pair panels as novel biomarkers for early-stage lung adenocarcinoma screening

Yuhong Dou; Yong Zhu; Junmei Ai; Hankui Chen; Helu Liu; Jeffrey A. Borgia; Xiao Li; Fan Yang; Bin Jiang; Jun Wang; Youping Deng

BackgroundLung cancer is a major cause of cancer-related mortality worldwide, and around two-thirds of patients have metastasis at diagnosis. Thus, detecting lung cancer at an early stage could reduce mortality. Aberrant levels of circulating small non-coding RNAs (small ncRNAs) are potential diagnostic or prognostic markers for lung cancer. We aimed to identify plasma small ncRNA pairs that could be used for early screening and detection of lung adenocarcinoma (LAC).ResultsA panel of seven small ncRNA pair ratios could differentiate patients with LAC or benign lung disease from high-risk controls with an area under the curve (AUC) of 100.0%, a sensitivity of 100.0% and a specificity of 100.0% at the training stage (which included 50 patients with early-stage LAC, 35 patients with benign diseases and 29 high-risk controls) and an AUC of 90.2%, a sensitivity of 91.5% and a specificity of 80.4% at the validation stage (which included 44 patients with early-stage LAC, 32 patients with benign diseases and 51 high-risk controls). The same panel could distinguish LAC from high-risk controls with an AUC of 100.0%, a sensitivity of 100.0% and a specificity of 100.0% at the training stage and an AUC of 89.5%, a sensitivity of 85.4% and a specificity of 83.3% at the validation stage. Another panel of five small ncRNA pair ratios (different from the first) was able to differentiate LAC from benign disease with an AUC of 82.0%, a sensitivity of 81.1% and a specificity of 78.1% in the training cohort and an AUC of 74.2%, a sensitivity of 70.4% and a specificity of 72.7% in the validation cohort.ConclusionsSeveral small ncRNA pair ratios were identified as markers capable of discerning patients with LAC from those with benign lesions or high-risk control individuals.

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Youping Deng

Rush University Medical Center

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Hankui Chen

Rush University Medical Center

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Jeffrey A. Borgia

Rush University Medical Center

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Helu Liu

Guangzhou Medical University

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Bin Jiang

Nanjing University of Chinese Medicine

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Yong Zhu

Nanjing University of Chinese Medicine

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Edward J. Perkins

Engineer Research and Development Center

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Joshua E. Melson

Rush University Medical Center

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Xin Guan

United States Army Corps of Engineers

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