Abstract
Cervical cancer, the fourth most common female cancer, is one of the major global health challenges. Because of the high prevalence rate, women are frequently screened for cervical cancer using Pap smears; however, the low sensitivity of Pap smear results in a late-stage diagnosis of cervical cancer. This study was designed to identify candidate biomarkers of cervical cancer, which can be explored for their utility as diagnostic markers and/or therapeutic targets. Cervical cancer and healthy tissue proteins were identified by tandem mass spectrometry (LC–MS/MS) and quantified by a label-free method. Candidate biomarkers were selected by applying stringent statistical methods. A total of 201 differentially expressed proteins were identified, which displayed statistical power to classify cervical cancer and control groups. The top proteins with higher abundance in cervical cancer included integrin beta-2, catenin alpha-1, stathmin, and tax1-binding protein 3; while the top proteins with higher abundance in healthy tissue samples included alpha-2-HS-glycoprotein, serotransferrin, afamin, hemopexin, plasminogen, apolipoprotein A-II, and immunoglobulin lambda variable 1–51. Stathmin and afamin expressions were also validated by western blot analysis. Upregulated proteins in cervical cancer were mainly associated with cell adhesion, protein folding, inflammatory disorders, and tumorigenesis. The KEGG pathways over-represented in cervical cancer were antigen processing and presentation, cell adhesion, spliceosome, adherens junction, and ferroptosis. Applying stringent statistical selection criteria, 46 DEPs were selected as candidate biomarkers of cervical cancer, which can be explored for their utility as diagnostic markers and/or therapeutic targets of cervical cancer.
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Acknowledgements
The authors thank AIIMS, New Delhi for intramural financial support and Vproteomics, New Delhi for their support in performing LC-MS/MS experiments. AT also thanks University Grants Commission (UGC), New Delhi, India for her Senior Research Fellowship.
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Conceptualization, SY, AKT, and KBC; Project administration, and supervision, SY, JBS, and NB; Recruitment of study participants, sample collection, analysis, and processing, KBC, AT, NB, and JBS; Methodology, KBC, AT, and AKT; Data analysis, AT, and AKT; Writing—original draft preparation, KBC, AT, and AKT; Writing—review and editing, AKT. All authors reviewed and approved the final version of the manuscript.
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42485_2023_114_MOESM2_ESM.xlsx
Supplementary file2 List of proteins identified by LC-MS/MS analysis (sheet 1) and abundance data of 1343 proteins sorted for statistical analysis (XLSX 632 KB)
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Chandra, K.B., Tomar, A.K., Thapliyal, A. et al. Differential proteomics reveals overexpression of ferroptosis-related proteins in cervical cancer tissue. J Proteins Proteom 14, 163–174 (2023). https://doi.org/10.1007/s42485-023-00114-8
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DOI: https://doi.org/10.1007/s42485-023-00114-8