Xufei Zhang

Western University of Health Sciences, Pomona, California, United States

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Publications (5)15.42 Total impact

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    ABSTRACT: Background Accurate identification of linear B-cell epitopes plays an important role in peptide vaccine designs, immunodiagnosis, and antibody productions. Although several prediction methods have been reported, unsatisfied accuracy has limited the broad usages in linear B-cell epitope prediction. Therefore, developing a reliable model with significant improvement on prediction accuracy is highly desirable. Results In this study, we developed a novel model for prediction of linear B-cell epitopes, APCpred, which was derived from the combination of amino acid anchoring pair composition (APC) and Support Vector Machine (SVM) methods. Systematic comparisons with the existing prediction models demonstrated that APCpred method significantly improved the prediction accuracy both in fivefold cross-validation of training datasets and in independent blind datasets. In the fivefold cross-validation test with Chen872 dataset at window size of 20, APCpred achieved AUC of 0.809 and accuracy of 72.94%, which was much more accurate than the existing models, e.g., Bayesb, Chen’s AAP methods and the enhanced combination method of AAP with five AP scales. For the fivefold cross-validation test with ABC16 dataset, APCpred achieved an improved AUC of 0.794 and ACC of 73.00% at window size of 16, and attained an AUC of 0.748 and ACC of 67.96% on Blind387 dataset after being trained with ABC16 dataset. Trained with Lbtope_Confirm dataset, APCpred achieved an increased Acc of 55.09% on FBC934 dataset. Within sequence window sizes from 12 to 20, APCpred final model on homology-reduced dataset achieved an optimal AUC of 0.748 and ACC of 68.43% in fivefold cross-validation at the window size of 20. Conclusion APCpred model demonstrated a significant improvement in predicting linear B-cell epitopes using the features of amino acid anchoring pair composition (APC). Based on our study, a webserver has been developed for on-line prediction of linear B-cell epitopes, which is a free access at: http:/ccb.bmi.ac.cn/APCpred/.
    BioData Mining 04/2015; 8(14). DOI:10.1186/s13040-015-0047-3 · 1.54 Impact Factor
  • Cancer Research 10/2014; 74(19 Supplement):4551-4551. DOI:10.1158/1538-7445.AM2014-4551 · 9.28 Impact Factor
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    Li Zhong, Xufei Zhang, Mihai Covasa
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    ABSTRACT: Colorectal cancer (CRC) is the third leading cause of cancer deaths worldwide and the fourth most common cancer diagnosed among men and women in the United States. Considering the risk factors of CRC, dietary therapy has become one of the most effective approaches in reducing CRC morbidity and mortality. The use of probiotics is increasing in popularity for both the prevention and treatment of a variety of diseases. As the most common types of microbes used as probiotics, lactic acid bacteria (LAB) are comprised of an ecologically diverse group of microorganisms united by formation of lactic acid as the primary metabolite of sugar metabolism. LAB have been successfully used in managing diarrhea, food allergies, and inflammatory bowel disease. LAB also demonstrated a host of properties in preventing colorectal cancer development by inhibiting initiation or progression through multiple pathways. In this review, we discuss recent insights into cellular and molecular mechanisms of LAB in CRC prevention including apoptosis, antioxidant DNA damages, immune responses, and epigenetics. The emerging experimental findings from clinical trials as well as the proposed mechanisms of gut microbiota in carcinogenesis will also be briefly discussed.
    World Journal of Gastroenterology 06/2014; 20(24):7878-7886. DOI:10.3748/wjg.v20.i24.7878 · 2.43 Impact Factor
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    ABSTRACT: Atypical adenomatous hyperplasia (AAH) and squamous cell dysplasia (SCD) are associated with the development of malignant lesions in the lung. Accurate diagnosis of AAH and SCD could facilitate earlier clinical intervention and provide useful information for assessing lung cancer risk in human populations. Detection of AAH and SCD has been achieved by imaging and bronchoscopy clinically, but sensitivity and specificity remain less than satisfactory. We utilized the ability of the immune system to identify lesion specific proteins for detection of AAH and SCD. AAH and SCD tissue was surgically removed from six patients of Chinese descent (3 AAH and 3 SCD) with corresponding serum samples. Total RNA was extracted from the tissues and a cDNA library was generated and incorporated into a T7 bacteriophage vector. Following enrichment to remove "normal" reactive phages, a total of 200 AAH related and 200 SCD related phage clones were chosen for statistical classifier development and incorporation into a microarray. Microarray slides were tested with an independent double-blinded population consisting of 100 AAH subjects, 100 SCD subjects and 200 healthy control subjects. Sensitivity of 82% and specificity of 70% were achieved in the detection of AAH using a combination of 9 autoantibody biomarkers. Likewise, 86% sensitivity and 78% specificity were achieved in the detection of SCD using a combination of 13 SCD-associated markers. Sequencing analysis identified that most of these 22 autoantibody biomarkers had known malignant associations. Both diagnostic values showed promising sensitivity and specificity in detection of pre-neoplastic lung lesions. Hence, this technology could be a useful non-invasive tool to assess lung cancer risk in human populations.
    Molecular Cancer 04/2014; 13(1):78. DOI:10.1186/1476-4598-13-78 · 5.40 Impact Factor
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    ABSTRACT: The malignant mesothelioma (MM) survival rate has been hampered by the lack of efficient and accurate early detection methods. The immune system may detect the early changes of tumor progression by responding with tumor-associated autoantibody production. Hence, in this study, we translated the humoral immune response to cancer proteins into a potential blood test for MM. A T7 phage MM cDNA library was constructed using MM tumor tissues and biopanned for tumor-associated antigens (TAAs) using pooled MM patient and normal serum samples. About 1008 individual phage TAA clones from the biopanned library were subjected to protein microarray construction and tested with 53 MM and 52 control serum samples as a training group. Nine candidate autoantibody markers were selected from the training group using Tclass system and logistic regression statistical analysis, which achieved 94.3% sensitivity and 90.4% specificity with an AUC value of 0.89 in receiver operating characteristic analysis. The classifier was further evaluated with 50 patient and 50 normal serum samples as an independent blind validation, and the sensitivity of 86.0% and the specificity of 86.0% were obtained with an AUC of 0.82. Sequencing and BLASTN analysis of the classifier revealed that five of these nine candidate markers were found to have strong homology to cancer related proteins (PDIA6, MEG3, SDCCAG3, IGHG3, IGHG1). Our results indicated that using a panel of 9 autoantibody markers presented a promising accuracy for MM detection. Although the results need further validation in high-risk groups, they provided the potentials in developing a serum-based assay for MM diagnosis.
    PLoS ONE 08/2013; 8(8):e72458. DOI:10.1371/journal.pone.0072458 · 3.53 Impact Factor
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    ABSTRACT: To evaluate the diagnostic values of autoantibodies against lymphocyte antigen 6 complex locus K (LY6K) in esophageal squamous cell carcinoma (ESCC). After cloning, expressing, and purifying LY6K as fusion proteins, LY6K autoantibodies were measured in 62 patient and 58 control serum samples using enzyme-linked immunosorbent assay (ELISA). Reverse transcription polymerase chain reaction (RT-PCR) was used to measure the LY6K mRNA levels in ESCC and adjacent tissues. LY6K autoantibodies were found significantly higher in patients than controls. The area under the receiver-operating characteristic (ROC) curve (AUC) was 0.85, and the optimal sensitivity and specificity for ESCC detection were 80.6 and 78.7%, respectively. LY6K mRNA expressions in patients were upregulated. Autoantibodies against LY6K may be a good diagnostic biomarker for ESCC.
    Biomarkers 04/2012; 17(4):372-8. DOI:10.3109/1354750X.2012.680609 · 2.52 Impact Factor

Publication Stats

6 Citations
15.42 Total Impact Points

Institutions

  • 2014
    • Western University of Health Sciences
      Pomona, California, United States
  • 2012
    • Hebei University
      Pao-ting-shih, Hebei, China