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Tong Ren,Jing Suo,Shikai Liu,Shu Wang,Shan Shu,Yang Xiang,Jing-He Lang 대한부인종양학회 2018 Journal of Gynecologic Oncology Vol.29 No.5
Objectives: We analyzed the chromosomal-arm-level copy number alterations (CNAs) in the cervical exfoliative cell and tissue samples by using the low-coverage whole genomic sequencing technique. Methods: In this study, we retrospectively collected 55 archived exfoliated cervical cell suspension samples and the corresponding formalin-fixed and paraffin-embedded tissue section samples including 27 invasive cervical cancer and 28 control cases. We also collected 19 samples of the cervical exfoliative cells randomly from women to verify the new algorithm model. We analyzed the CNAs in cervical exfoliated cell and tissue samples by using the low-coverage next generation of sequencing. Results: In the model-building study, multiple chromosomal-arm-level CNAs were detected in both cervical exfoliated cell and tissue samples of all cervical cancer cases. By analyzing the consistency of CNAs between exfoliated cells and cervical tissue samples, as well as the heterogeneity in individual patient, we also established a C-score algorithm model according to the chromosomal-arm-level changes of 1q, 2q, 3p, 7q. The C-score model was then validated by the pathological diagnosis of all 74 exfoliated cell samples (including 55 cases in model-building group and 19 cases in verification group). In our result, a cutoff value of C-score >6 showed 100% sensitivity and 100% specificity in the diagnosis of cervical cancer. Conclusion: In this study, we found that CNAs of cervical exfoliated cell samples could robustly distinguish invasive cervical cancer from cancer-free tissues. And we have also developed a C-score algorithm model to process the sequencing data in a more standardized and automated way.
Sensor Configuration and Activation for Field Detection in Large Sensor Arrays
Sung, Youngchul,Zhang, Xin,Tong, Lang,Poor, H. Vincent IEEE 2008 IEEE transactions on signal processing Vol.56 No.2
<P> The problem of sensor configuration for the detection of correlated random fields using large sensor arrays is considered. Using error exponents that characterize the asymptotic behavior of the optimal detector, the detection performance of different sensor configurations is analyzed and compared. The dependence of the optimal configuration on parameters such as sensor signal-to-noise ratio (SNR), field correlation, etc., is examined, yielding insights into the most effective choices for sensor selection in various operating conditions. Simulation results validate the analysis based on asymptotic results for finite sample cases. </P>
Wu, Dong-Ming,Zhang, Peng,Xu, Guang-Chao,Tong, Ai-Ping,Zhou, Cong,Lang, Jin-Yi,Wang, Chun-Ting Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.4
Pemetrexed is an antifolate agent which has been used for treating malignant pleural mesothelioma and non small lung cancer in the clinic as a chemotherapeutic agent. In this study, pemetrexed inhibited cell growth and induced G1 phase arrest in the A549 cell line. To explore the molecular mechanisms of pemetrexed involved in cell growth, we used a two-dimensional polyacrylamide gel electrophoresis (2-DE) proteomics approach to analyze proteins changed in A549 cells treated with pemetrexed. As a result, twenty differentially expressed proteins were identified by ESI-Q-TOF MS/MS analysis in A549 cells incubated with pemetrexed compared with non-treated A549 cells. Three key proteins (GAPDH, HSPB1 and EIF4E) changed in pemetrexed treated A549 cells were validated by Western blotting. Accumulation of GAPDH and decrease of HSPB1 and EIF4E which induce apoptosis through inhibiting phosphorylation of Akt were noted. Expression of p-Akt in A549 cells treated with pemetrexed was reduced. Thus, pemetrexed induced apoptosis in A549 cells through inhibiting the Akt pathway.