AccScience Publishing / EJMO / Online First / DOI: 10.36922/EJMO025310326
Submit to EJMO
Cite this article
2
Download
35
Views
Journal Browser
Volume | Year
Issue
Search
Forthcoming Issue
Current Issue
View All
News and Announcements
View All
ORIGINAL RESEARCH ARTICLE

Machine learning-enhanced immune signatures optimize cancer antigen 125 performance for epithelial ovarian carcinoma detection

Yuanhong Zhou1† ,  Xuehui Chen1† ,  Jia Liu1† ,  Qianwen Zhang1† ,  Youzheng Luo1 ,  Qiang Liu1*
Show Less
1 The First College of Clinical Medical Science, Yichang Central People’s Hospital, China Three Gorges University, Yichang, Hubei, China
†These authors contributed equally to this work.
EJMO, 025310326 https://doi.org/10.36922/EJMO025310326
Received: 28 July 2025 | Revised: 31 October 2025 | Accepted: 14 November 2025 | Published online: 17 December 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Download PDF
XML
Cite
Abstract

Introduction: Ovarian cancer (OC) ranks as the fifth most common gynecologic malignancy among women worldwide.

Objective: The present study evaluates the diagnostic potential of hematological biomarkers for the early detection and differential diagnosis of OC.

Methods: A bioinformatic analysis was performed to compare immune cell profiles in blood and tissue samples from patients with OC using data from The Cancer Genome Atlas and Gene Expression Omnibus databases. Subsequently, a retrospective clinical study was conducted at Yichang Central People’s Hospital between January 2015 and January 2021, including three cohorts: (i) Patients with benign ovarian tumors (n = 70), (ii) Patients with OC (n = 70), and (iii) Healthy controls (n = 60). A comprehensive analysis of routine blood parameters and the tumor marker cancer antigen 125 (CA125) was performed.

Results: The findings revealed that peripheral blood immune markers exhibited superior diagnostic utility compared with tissue-based indicators. The combination of CA125 with erythrocyte sedimentation rate (ESR) and neutrophil-to-lymphocyte ratio showed high accuracy in differentiating benign ovarian tumors from OC (area under the curve [AUC]: 0.87). Furthermore, a panel combining CA125 and platelet-to-neutrophil ratio showed enhanced diagnostic performance in distinguishing early-stage from advanced epithelial OC (sensitivity: 81.3%; specificity: 96.6%). Notably, the triad of CA125, ESR, and white blood cell count demonstrated strong screening performance for detecting epithelial OC (AUC: 0.941; p<0.001).

Conclusion: These results suggest that integrating CA125 with routine hematological parameters significantly enhances the diagnostic accuracy and early detection of epithelial OC compared to CA125 alone, providing a practical and cost-effective screening strategy for clinical implementation.

Keywords
Epithelial ovarian cancer
Hematological parameters
Screening
Cancer antigen 125
Bioinformatics
Funding
The work was supported by the National Nature Science Foundation of China (award numbers: 81403163 and 81402404), the Science and Technology Research Project of Hubei Provincial Education Department (award number: D20201204), the Yi Chang Scientific and Technological Bureau (award number: A222017), the Hubei Provincial Natural Science Foundation (award numbers: 2022CFB037 and 2024AFB832), the Hubei Provincial Administration of Traditional Chinese Medicine (grant no.: ZY2023M039), Education Reform Project of Three Gorges University (grant no.: 202427) and the Higher Education Research Project of Three Gorges University (grant no.: GJ2434).
Conflict of interest
The authors declare that they have no competing interests.
References
  1. Bachmann C. New achievements from molecular biology and treatment options for refractory/relapsed ovarian cancer-a systematic review. Cancers (Basel). 2023;15(22):5356. doi: 10.3390/cancers15225356

 

  1. Webb PM, Jordan SJ. Epidemiology of epithelial ovarian cancer. Best Pract Res Clin Obstet Gynaecol. 2017;41:3-14. doi: 10.1016/j.bpobgyn

 

  1. Bonifácio VDB. Ovarian cancer biomarkers: Moving forward in early detection. Adv Exp Med Biol. 2020;1219:355-363. doi: 10.1007/978-3-030-34025-4_18

 

  1. Cabasag CJ, Fagan PJ, Ferlay J, et al. Ovarian cancer today and tomorrow: A global assessment by world region and Human Development Index using GLOBOCAN 2020. Int J Cancer. 2022;151(9):1535-1541. doi: 10.1002/ijc.34002

 

  1. Jelovac D, Armstrong DK. Recent progress in the diagnosis and treatment of ovarian cancer. CA Cancer J Clin. 2011;61(3):183-203. doi: 10.3322/caac.20113

 

  1. Zhang XY, Hong LL, Ling ZQ. MUC16/CA125 in cancer: New advances. Clin Chim Acta. 2025;15:119981. doi: 10.1016/j.cca.2024.119981

 

  1. Modrak DE, Karacay H, Cardillo TM, Newsome G, Goldenberg DM, Gold DV. Identification of a Mu-9 (anti-colon-specific antigen-p)-reactive peptide having homology to CA125 (MUC16). Int J Oncol. 2005;26(6):1591-1596.

 

  1. Foda AAM, Atia T, Sakr HI, Elnaghi KAEA, Abdelhay WM, Enan ET. Clinicopathological characteristics and prognosis of diffuse large B-cell lymphoma in relation to CA-125 and CA 199 expression. J Evid Based Integr Med. 2023;28:2515690X231198315. doi: 10.1177/2515690X231198315

 

  1. Moss EL, Hollingworth J, Reynolds TM. The role of CA125 in clinical practice. J Clin Pathol. 2005;58(3):308-312. doi: 10.1136/jcp.2004.018077

 

  1. Forstner R. Early detection of ovarian cancer. Eur Radiol. 2020;30(10):5370-5373. doi: 10.1007/s00330-020-06937-z

 

  1. Hatamikia S, Nougaret S, Panico C, et al. Ovarian cancer beyond imaging: Integration of AI and multiomics biomarkers. Eur Radiol Exp. 2023;7(1):50. doi: 10.1186/s41747-023-00364-7

 

  1. Cress RD, Chen YS, Morris CR, Petersen M, Leiserowitz GS. Characteristics of long-term survivors of epithelial ovarian cancer. Obstet Gynecol. 2015;126(3):491-497. doi: 10.1097/AOG.0000000000000981

 

  1. Balkwill F, Mantovani A. Inflammation and cancer: Back to Virchow? Lancet. 2001;357(9255):539-545. doi: 10.1016/S0140-6736(00)04046-0

 

  1. Coussens LM, Werb Z. Inflammation and cancer. Nature. 2002;420(6917):860-867. doi: 10.1038/nature01322

 

  1. Balkwill FR, Mantovani A. Cancer-related inflammation: Common themes and therapeutic opportunities. Semin Cancer Biol. 2012;22(1):33-40. doi: 10.1016/j.semcancer.2011.12.005

 

  1. Macciò A, Madeddu C. Inflammation and ovarian cancer. Cytokine. 2012;58(2):133-147. doi: 10.1016/j.cyto.2012.01.015

 

  1. Medzhitov R, Schneider DS, Soares MP. Disease tolerance as a defense strategy. Science. 2012;335(6071):936-941. doi: 10.1126/science.1214935

 

  1. Naser R, Fakhoury I, El-Fouani A, Abi-Habib R, El-Sibai M. Role of the tumor microenvironment in cancer hallmarks and targeted therapy (Review). Int J Oncol. 2023;62(2):23. doi: 10.3892/ijo.2022.5471

 

  1. Fox P, Hudson M, Brown C, et al. Markers of systemic inflammation predict survival in patients with advanced renal cell cancer. Br J Cancer. 2013;109(1):147-153. doi: 10.1038/bjc.2013.300

 

  1. Winther Larsen A, Aggerholm Pedersen N, Sandfeld- Paulsen B. Inflammation scores as prognostic markers of overall survival in lung cancer: A register-based study of 6,210 Danish lung cancer patients. BMC Cancer. 2022;22(1):63. doi: 10.1186/s12885-021-09108-5

 

  1. Gschwantler-Kaulich D, Weingartshofer S, Rappaport- Fürhauser C, et al. Diagnostic markers for the detection of ovarian cancer in BRCA1 mutation carriers. PLoS One. 2017;12(12):e0189641. doi: 10.1371/journal.pone.0189641

 

  1. Bi KW, Wei XG, Qin XX, Li B. BTK has potential to be a prognostic factor for lung adenocarcinoma and an indicator for tumor microenvironment remodeling: A study based on TCGA data mining. Front Oncol. 2020;10:424. doi: 10.3389/fonc.2020.00424

 

  1. Huang J, Chan WC, Ngai CH, Lok V, et al. Worldwide burden, risk factors, and temporal trends of ovarian cancer: A global study. Cancers (Basel). 2022;14(9):2230. doi: 10.3390/cancers14092230

 

  1. Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin. 2022;72(1):7-33. doi: 10.3322/caac.21708

 

  1. Eo WK, Kim KH, Park EJ, et al. Diagnostic accuracy of inflammatory markers for distinguishing malignant and benign ovarian masses. J Cancer. 2018;9(7):1165-1172. doi: 10.7150/jca.23606

 

  1. Chung JYF, Tang PCT, Chan MKK, et al. Smad3 is essential for polarization of tumor-associated neutrophils in non-small cell lung carcinoma. Nat Commun. 2023;14(1):1794. doi: 10.1038/s41467-023-37515-8

 

  1. Huanhuan B, Ren D, Xiao Y, et al. Prognostic implications of neutrophil -to-lymphocyte ratio in patients with extensive-stage small cell lung cancer receiving chemoimmunotherapy: A multicenter, real-world study. Thorac Cancer. 2024; 15(7):559-569. doi: 10.1111/1759-7714

 

  1. Morimoto H, Tsujikawa T, Miyagawa Hayashino A, et al. Neutrophil-to-lymphocyte ratio associates with nutritional parameters, intratumoral immune profiles, and clinical outcomes of pembrolizumab in head and neck squamous cell carcinoma. Head Neck. 2024;46(8):1956-1964. doi: 10.1002/hed.27671

 

  1. Matuszczak M, Kiljańczyk A, Marciniak W, et al. Antioxidant properties of zinc and copper-blood zinc-to copper-ratio as a marker of cancer risk BRCA1 mutation carriers. Antioxidants (Basel). 2024;13(7):841. doi: 10.3390/antiox13070841
Share
Back to top
Eurasian Journal of Medicine and Oncology, Electronic ISSN: 2587-196X Print ISSN: 2587-2400, Published by AccScience Publishing
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here
Accept