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Cervical cancer is the second most common gynecological malignancy, which immensely threatens the well-being of women. However, the pathogenesis of cervical cancer is still unclear. Using tandem mass tags-labeled quantitative proteomic technology and bioinformatics tools, we analyzed the exfoliated cervical cells from the normal and cervical cancer groups to establish a cancer-specific protein profile, thereby identifying key proteins related to cervical oncogenesis. When compared with the normal group, a total of 351 differentially expressed proteins were identified in the cervical cancer group, including 247 up-regulated and 104 down-regulated proteins. Gene ontology function annotation revealed that the differentially expressed proteins were mainly involved in the single-multicellular organism process, multicellular organismal process, and negative regulation of biological process. These proteins were discerned to play a role in the extracellular membrane-bounded organelle, exosome of cell components, protein binding, structural molecule activity, and enzyme binding of molecular functions. The results of Kyoto Encyclopedia of Genes and Genomes signaling pathway enrichment proved that these differentially expressed proteins were mainly involved in PI3K - Akt, ECM-receptor interaction, complement and coagulation cascades, and other signaling pathways. Particularly, peroxiredoxin-2 may be involved in cervical tumor oncogenesis through inhibition of apoptosis signaling. SIGNIFICANCE: In this study, we determined that the proteins of the cervical cancer group exhibited qualitative and quantitative changes, and a total of 351 differentially expressed proteins were identified. The functions and signaling pathways of these differentially expressed proteins have laid a theoretical foundation for elucidating the molecular mechanism of cervical cancer. Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.


Dianqin Xu, Xiaoyu Zhu, Ji Ren, Shan Huang, Ziwen Xiao, Hongmei Jiang, Yujie Tan. Quantitative proteomic analysis of cervical cancer based on TMT-labeled quantitative proteomics. Journal of proteomics. 2022 Feb 10;252:104453

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PMID: 34915198

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