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ORIGINAL RESEARCH ARTICLE

Blood laboratory parameters can predict relapse-free survival of patients with advanced squamous cell lung cancer and adenocarcinoma

Anatoli D. Tahanovich1* ,  Mikalai M. Kauhanka1 ,  Alexander V. Kolb1 ,  Oxana V. Gotko2 ,  Violetta I. Prokharova2
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1 Department of Biochemistry, Educational Institution “Belarusian State Medical University”, Minsk, Belarus
2 Department of Laboratory Methods of Diagnostics, N.N. Alexandrov National Cancer Center of Belarus, a.g. Lesnoy, Belarus
Global Translational Medicine, 4865 https://doi.org/10.36922/gtm.4865
Submitted: 16 September 2024 | Accepted: 26 November 2024 | Published: 13 December 2024
© 2024 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

The aim of the work was to study the relationship between the concentration of cells and proteins in the blood of patients with Stage III squamous cell lung cancer (SCLC) and adenocarcinoma (AC) before surgical treatment and the duration of the relapse-free period after tumor resection to develop prognostic models for relapse-free survival in these diseases. Using logistic regression equations, the models incorporated variables included cytokeratin 19 fragment antigen 21-1 (CYFRA 21-1) concentration, the proportion of lymphocytes expressing the C-X-C motif chemokine receptor 1 (CXCR1), and monocytes expressing the C-X-C motif chemokine receptor 2 for SCLC. For AC, the models included the CYFRA 21-1 concentration, lymphocytes expressing the CXCR1 receptor, and the eosinophil-to-monocyte ratio. These models can predict the probability of tumor recurrence based on measurements of blood parameters in the pre-operative period, with a prediction efficiency of 87.7% for SCLC and 89.0% for AC.

Keywords
Squamous cell lung cancer
Adenocarcinoma
Relapse
Prognosis
CYFRA 21-1
CXCR1
CXCR2
Stage III
Funding
The work was carried out with financial support from the Ministry of Health of the Republic of Belarus, grant 2.17/20220385.
Conflict of interest
The authors declare that they have no competing interests.
References
  1. Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics. CA Cancer J Clin. 2023;73(1):17-48. doi: 10.3322/caac.21763

 

  1. Araghi M, Mannani R, Heidarnejad MA, et al. Recent advances in non-small cell lung cancer targeted therapy; an update review. Cancer Cell Int. 2023;23(1):162. doi: 10.1186/s12935-023-02990-y

 

  1. Lababede O, Meziane MA. The eighth edition of TNM staging of lung cancer: Reference chart and diagrams. Oncologist. 2018;23(7):844-848. doi: 10.1634/theoncologist.2017-0659

 

  1. Wu G, Pan B, Shi H, et al. Neutrophils’ dual role in cancer: From tumor progression to immunotherapeutic potential. Int Immunopharmacol. 2024;140:112788. doi: 10.1016/j.intimp.2024.112788

 

  1. Carvalho S, Troost EG, Bons J, Menheere P, Lambin P, Oberije C. Prognostic value of blood-biomarkers related to hypoxia, inflammation, immune response and tumour load in non-small cell lung cancer - a survival model with external validation. Radiother Oncol. 2016;119(3):487-494. doi: 10.1016/j.radonc.2016.04.024

 

  1. Ha H, Debnath B, Neamati N. Role of the CXCL8-CXCR1/2 axis in cancer and inflammatory diseases. Theranostics. 2017;7(6):1543-1588. doi: 10.7150/thno.15625

 

  1. Wu K, Yu S, Liu Q, Bai X, Zheng X, Wu K. The clinical significance of CXCL5 in non-small cell lung cancer. Onco Targets Ther. 2017;10:5561-5573. doi: 10.2147/OTT.S148772

 

  1. Tahanovich AD, Kauhanka NN, Prohorova VI, Murashka DI, Gotko OV. Determination of the risk of tumor progression in patients with early stages of adenocarcinoma and squamous cell lung carcinoma based on laboratory parameters. Biochem Moscow Suppl Ser B. 2022;16:154-163. doi: 10.1134/S1990750822020081

 

  1. Tahanovich AD, Kauhanka NN, Kolb AV, et al. Prediction of relapse-free survival of patients with stage III non-small cell lung cancer after treatment. The role of the concentration of blood cells. Lab Diagn Vost Eur. 2022;2:148-162. in Russian. doi: 10.34883/PI.2022.11.2.013

 

  1. Tahanovich AD, Kauhanka NN, Murashka DI, et al. Preoperative blood markers for prediction of recurrence-free survival after surgical treatment of patients with stage III lung adenocarcinoma. Rus Clin Lab Diagn. 2022;67(11):640-646. in Russian. doi: 10.51620/0869-2084-2022-67-11-640-646

 

  1. Duffy MJ, O’Byrne K. Tissue and blood biomarkers in lung cancer: A review. Adv Clin Chem. 2018;86:1-21. doi: 10.1016/bs.acc.2018.05.001

 

  1. Muley T, Rolny V, He Y, et al. The combination of the blood based tumor biomarkers cytokeratin 19 fragments (CYFRA 21-1) and carcinoembryonic antigen (CEA) as a potential predictor of benefit from adjuvant chemotherapy in early stage squamous cell carcinoma of the lung (SCC). Lung Cancer. 2018;120:46-53. doi: 10.1016/j.lungcan.2018.03.015

 

  1. Niklinski J, Furman M, Burzykowski T, et al. Preoperative CYFRA 21-1 level as a prognostic indicator in resected primary squamous cell lung cancer. Br J Cancer. 1996;74(6):956-960. doi: 10.1038/bjc.1996.464

 

  1. Holdenrieder S, Wehnl B, Hettwer K, Simon K, Uhlig S, Dayyani F. Carcinoembryonic antigen and cytokeratin-19 fragments for assessment of therapy response in non-small cell lung cancer: A systematic review and meta-analysis. Br J Cancer. 2017;116(8):1037-1045. doi: 10.1038/bjc.2017.45

 

  1. Svaton M, Blazek J, Krakorova G, et al. Prognostic role for CYFRA 21-1 in patients with advanced-stage NSCLC treated with bevacizumab plus chemotherapy. Anticancer Res. 2021;41(4):2053-2058. doi: 10.21873/anticanres.14974

 

  1. Baek AR, Seo HJ, Lee JH, et al. Prognostic value of baseline carcinoembryonic antigen and cytokeratin 19 fragment levels in advanced non-small cell lung cancer. Cancer Biomark. 2018;22(1):55-62. doi: 10.3233/CBM-170885

 

  1. Vodicka J, Skala M, Sebek J, et al. The role of serum tumor markers in follow-up after surgical treatment of malignant lung tumors. Anticancer Res. 2021;41(10):5117-5122. doi: 10.21873/anticanres.15328

 

  1. Zhang J, Huang SH, Li H, et al. Preoperative lymphocyte count is a favorable prognostic factor of disease-free survival in non-small-cell lung cancer. J Med Oncol. 2013;30(1):352-357. doi: 10.1007/s12032-012-0352-3

 

  1. Song X, Chen D, Yuan M, Wang H, Wang Z. Total lymphocyte count, neutrophil-lymphocyte ratio, and platelet-lymphocyte ratio as prognostic factors in advanced non-small cell lung cancer with chemoradiotherapy. Cancer Manag Res. 2018;10:6677-6683. doi: 10.2147/CMAR.S188578

 

  1. Agassandian M, Shurin GV, Ma Y, Shurin MR. C-reactive protein and lung diseases. Int J Biochem Cell Biol. 2014;53:77-88. doi: 10.1016/j.biocel.2014.05.016

 

  1. Huang Q, Diao P, Li CL, et al. Preoperative platelet-lymphocyte ratio is a superior prognostic biomarker to other systemic inflammatory response markers in non-small cell lung cancer. Medicine (Baltimore). 2020;99(4):e18607. doi: 10.1097/MD.0000000000018607

 

  1. Li X, Qin S, Sun X, et al. Prognostic significance of albumin-globulin score in patients with operable non-small-cell lung cancer. Ann Surg Oncol. 2018;25(12):3647-3659. doi: 10.1245/s10434-018-6715-z

 

  1. Okugawa Y, Toiyama Y, Yamamoto A, et al. Lymphocyte- C-reactive protein ratio as promising new marker for predicting surgical and oncological outcomes in colorectal cancer. Ann. Surg. 2020;272(2):342-351. doi: 10.1097/SLA.0000000000003239

 

  1. Yang R, Chang Q, Meng X, Gao N, Wang W. Prognostic value of systemic immune-inflammation index in cancer: A meta-analysis. J Cancer. 2018;9(18):3295-3302. doi: 10.7150/jca.25691

 

  1. Dirican N, Dirican A, Anar C, et al. New inflammatory prognostic index, based on C-reactive protein, the neutrophil to lymphocyte ratio and serum albumin is useful for predicting prognosis in non-small cell lung cancer cases. Asian Pac J Cancer Prev. 2016;17(12):5101-5106. doi: 10.22034/APJCP.2016.17.12.5101

 

  1. Wang Y, Hu X, Xu W, Wang H, Huang Y, Che G. Prognostic value of a novel scoring system using inflammatory response biomarkers in non-small cell lung cancer: A retrospective study. Thorac Cancer. 2019;10(6):1402-1411. doi: 10.1111/1759-7714.13085

 

  1. van den Heuvel M, Holdenrieder S, Schuurbiers M, et al. Serum tumor markers for response prediction and monitoring of advanced lung cancer: A review focusing on immunotherapy and targeted therapies. Tumour Biol. 2024;46(S1):S233-S268. doi: 10.3233/TUB-220039

 

  1. Wang BY, Huang JY, Chen HC, et al. The comparison between adenocarcinoma and squamous cell carcinoma in lung cancer patients. J Cancer Res Clin Oncol. 2020;146(1):43-52.doi: 10.1007/s00432-019-03079-8

 

  1. Lu J, Wang Y, Yan M, et al. High serum haptoglobin level is associated with tumor progression and predicts poor prognosis in non-small cell lung cancer. Oncotarget. 2016;7(27):41758-41766. doi: 10.18632/oncotarget.9676

 

  1. Burki TK. Late detection of lung cancer. Lancet Oncol. 2014;15(13):e590. doi: 10.1016/S1470-2045(14)70371-7

 

  1. Maeda R, Yoshida J, Ishii G, Hishida T, Nishimura M, Nagai K. Risk factors for tumor recurrence in patients with early-stage (stage I and II) non-small cell lung cancer: Patient selection criteria for adjuvant chemotherapy according to the seventh edition TNM classification. Chest. 2011;140(6):1494-1502. doi: 10.1378/chest.10-3279

 

  1. Berghmans T, Paesmans M, Sculier JP. Prognostic factors in stage III non-small cell lung cancer: A review of conventional, metabolic and new biological variables. Ther Adv Med Oncol. 2011;3(3):127-138. doi: 10.1177/1758834011401951

 

  1. Yun JK, Lee GD, Choi S, et al. Various recurrence dynamics for non-small cell lung cancer depending on pathological stage and histology after surgical resection. Transl Lung Cancer Res. 2022;11(7):1327-1336. doi: 10.21037/tlcr-21-1028

 

  1. Hosmer DW, Lemeshow S, Sturdivant RX. Applied Logistic Regression. 3rd ed. Hoboken, NJ: John Wiley & Sons; 2013. doi: 10.1002/9781118548387
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Global Translational Medicine, Electronic ISSN: 2811-0021 Print ISSN: 3060-8600, Published by AccScience Publishing
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