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Feng X, Zhang J, Liu J, Su J, Liu X, Yang M, Peng Y, Yan H, Chen Z. A stable thymidine kinase 1 tetramer for improved quality control of serum level quantification. Clin Chim Acta 2025; 565:119967. [PMID: 39304108 DOI: 10.1016/j.cca.2024.119967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 07/30/2024] [Accepted: 09/11/2024] [Indexed: 09/22/2024]
Abstract
DNA synthesis is a critical process for cell growth and division. In cancer patients, an enzyme called thymidine kinase 1 (TK1) is often elevated in the blood, making it a valuable biomarker for cancer diagnosis and treatment. However, previous studies have shown that recombinant TK1 can exist in unstable mixtures of tetramers and dimers, leading to inconsistent results and potentially affecting accuracy. To address this issue, we hypothesized that incorporating tetrameric coiled-coil peptides could enhance TK1 self-assembly into stable tetramers without requiring additional adenosine triphosphate. In this study, we successfully expressed a recombinant TK1 tetramer protein in the Escherichia coli system. We optimized the induction conditions, significantly increasing protein expression levels, functionality, and solubility. Size exclusion chromatography confirmed the formation of a tetrameric structure in the expressed TK1 protein, with a molecular weight of 127.2 KDa, consistent with our expectations. We also found that the TK1 tetramer exhibited higher affinity with anti-TK1 IgY than wild-type TK1, as shown by enzyme-linked immunosorbent assay experiments. Moreover, the TK1 tetramer demonstrated good stability against heating, freeze-thawing and lyophilization with almost no immunoactivity lost. These findings suggest that recombinant TK1 tetramers have the potential to serve as calibrators in diagnostic assay kits, becoming promising candidates for quality control of clinical laboratory and in vitro diagnostic reagents.
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Affiliation(s)
- Xiangning Feng
- NMPA Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, 1 Sun Yat-Sen University, Guangzhou 510080, China; One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou 510080, China
| | - Jinsong Zhang
- NMPA Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, 1 Sun Yat-Sen University, Guangzhou 510080, China; One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou 510080, China
| | - Jinsong Liu
- NMPA Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, 1 Sun Yat-Sen University, Guangzhou 510080, China; One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou 510080, China
| | - Jiayue Su
- NMPA Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, 1 Sun Yat-Sen University, Guangzhou 510080, China; One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou 510080, China
| | - Xinrui Liu
- NMPA Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, 1 Sun Yat-Sen University, Guangzhou 510080, China; One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou 510080, China
| | - Mingwei Yang
- NMPA Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, 1 Sun Yat-Sen University, Guangzhou 510080, China; One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou 510080, China
| | - Yuanli Peng
- NMPA Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, 1 Sun Yat-Sen University, Guangzhou 510080, China; One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou 510080, China
| | - Haozhen Yan
- NMPA Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, 1 Sun Yat-Sen University, Guangzhou 510080, China; One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou 510080, China
| | - Zeliang Chen
- NMPA Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, 1 Sun Yat-Sen University, Guangzhou 510080, China; One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou 510080, China; Key Laboratory of Zoonose Prevention and Control at Universities of Inner Mongolia Autonomous Region, Medical College, Inner Mongolia Minzu University, Tongliao 028000, China; Key Laboratory of Livestock Infectious Diseases, Ministry of Education, Shenyang Agricultural University, Shenyang 110866, China.
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Murtola TJ, Siltari A, Raittinen P, Tammela TL, Linder S, Csizmarik A, Kramer G, Szarvas T. Elevated Levels of Serum Thymidine Kinase 1 Predict Poor Survival for Patients with Metastatic Prostate Cancer. EUR UROL SUPPL 2024; 70:135-141. [PMID: 39525979 PMCID: PMC11547961 DOI: 10.1016/j.euros.2024.10.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/09/2024] [Indexed: 11/16/2024] Open
Abstract
Background and objective Prostate-specific antigen (PSA) is of limited value as a surrogate marker for overall survival (OS) in prostate cancer (PC). Serum thymidine kinase 1 (sTK1) is an enzyme expressed by actively dividing cells. Our aim was to evaluate the value of sTK1 as prognostic biomarker in metastatic hormone-sensitive PC (mHSPC) and metastatic castration-resistant PC (mCRPC). Methods sTK1 was examined in three cohorts: (1) 43 men with de novo mHSPC managed with androgen deprivation monotherapy; (2) 99 patients with mCRPC managed with androgen receptor signaling inhibitors (ARSIs); and (3) 98 patients with mCRPC treated with docetaxel. sTK1 levels were determined at treatment initiation. OS was evaluated using Cox regression analysis. Key findings and limitations In the mHSPC cohort, sTK1 levels in the highest quartile were associated with OS (hazard ratio [HR] 7.77, 95% confidence interval [CI] 2.25-26.9) in comparison to the lowest quartile after multivariable adjustment for age, Gleason score, and PSA. Similarly, sTKI was associated with poor OS in the mCRPC group treated with ARSIs (upper quartile: HR 5.22, 95% CI 2.23-12.2) after multivariable adjustment for age, PSA, and Eastern Cooperative Oncology Group performance status. In the docetaxel-treated mCRPC group the association between OS and sTK1 was lower but still significant (multivariable-adjusted HR 2.28, 95% CI 1.13-4.60). Limitations include the nonrandomized inclusion of patients for different treatments, which could lead to selection bias. Conclusions and clinical implications sTK1 predicted OS in mHSPC and mCRPC, demonstrating additional value over established clinical risk factors. sTK1 should be measured in randomized clinical trials of treatments for advanced PC to validate its predictive value. Patient summary We found that for patients with metastatic prostate cancer, high levels of a protein called TK1 that is involved in cell division was linked to higher risk of death. Our findings need to be confirmed in other studies.
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Affiliation(s)
- Teemu J. Murtola
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Urology, TAYS Cancer Center, Tampere, Finland
| | - Aino Siltari
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Pharmacology, University of Helsinki, Helsinki, Finland
| | - Paavo Raittinen
- Department of Mathematics and Systems Analysis, Aalto University, Helsinki, Finland
| | - Teuvo L.J. Tammela
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Urology, TAYS Cancer Center, Tampere, Finland
| | - Stig Linder
- Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
- Department of Oncology-Pathology, Karolinska Institute, Stockholm, Sweden
| | - Anita Csizmarik
- Department of Urology, Semmelweis University, Budapest, Hungary
| | - Gero Kramer
- Department of Urology, Medical University of Vienna, Vienna, Austria
| | - Tibor Szarvas
- Department of Urology, Semmelweis University, Budapest, Hungary
- Department of Urology, University of Duisburg-Essen, Essen, Germany
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Ye L, Xu X, Qu A, Kuang H, Liu L, Xu C. Development of a gold nanoparticle-based lateral flow immunochromatographic assay for the rapid and quantitative detection of thymidine kinase 1 in human serum. J Pharm Biomed Anal 2024; 245:116146. [PMID: 38631069 DOI: 10.1016/j.jpba.2024.116146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 04/09/2024] [Accepted: 04/10/2024] [Indexed: 04/19/2024]
Abstract
Thymidine kinase 1 (TK1) is a marker of cell proliferation that can be used for early screening, treatment monitoring, and evaluating the prognosis of patients with tumors. The main purpose of this study was to develop clinically applicable TK1 antibodies, establish an appropriate detection method, and provide material and technical support for the research and clinical application for different types of tumors. Experimental mice were immunized with the C-terminal 31 peptide of human TK1 to screen monoclonal cell lines capable of stably secreting specific antibodies. Monoclonal antibodies were then prepared, purified and screened for optimal pairing following the identification of purity and isotype. Finally, based on the principles adopted by the double-antibody sandwich detection method, we constructed a lateral flow immunochromatographic assay (LFIA) to quantify the concentration of TK1 in serum samples when using a gold nanoparticle-labeled anti-TK1 monoclonal antibody as a probe. The limit of detection for TK1 in serum was 0.31 pmol/L with a detection range of 0.31-50 pmol/L. The spiked recoveries ranged from 97.7% to 109.0% with an analytical precision of 5.7-8.2%; there was no cross-reactivity with common proteins in the serum. The established LFIA also exhibited good consistency with commercially available chemiluminescent immunoassay kits for the detection of clinical samples. The LFIA developed in this study has the advantages of high sensitivity, accuracy, reproducibility and strong specificity, and provides a new technical tool for the quantitative detection of TK1.
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Affiliation(s)
- Liya Ye
- International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, People's Republic of China
| | - Xinxin Xu
- International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, People's Republic of China
| | - Aihua Qu
- International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, People's Republic of China
| | - Hua Kuang
- International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, People's Republic of China
| | - Liqiang Liu
- International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, People's Republic of China
| | - Chuanlai Xu
- International Joint Research Laboratory for Biointerface and Biodetection, and School of Food Science and Technology, Jiangnan University, Wuxi, People's Republic of China.
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Song X, Skog S, Wei L, Qin J, Yang R, Li J, Zhou J, He E, Zhou J. Nomogram model of serum thymidine kinase 1 combined with ultrasonography for prediction of central lymph node metastasis risk in patients with papillary thyroid carcinoma pre-surgery. Front Endocrinol (Lausanne) 2024; 15:1366219. [PMID: 38887267 PMCID: PMC11180742 DOI: 10.3389/fendo.2024.1366219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 05/02/2024] [Indexed: 06/20/2024] Open
Abstract
Objective The aim of this study was to develop a nomogram, using serum thymidine kinase 1 protein (STK1p) combined with ultrasonography parameters, to early predict central lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC) pre-surgery. Methods Patients with PTC pre-surgery in January 2021 to February 2023 were divided into three cohorts: the observation cohort (CLNM, n = 140), the control cohort (NCLNM, n = 128), and the external verification cohort (CLNM, n = 50; NCLNM, n = 50). STK1p was detected by an enzyme immunodot-blot chemiluminescence analyzer and clinical parameters were evaluated by ultrasonography. Results A suitable risk threshold value for STK1p of 1.7 pmol/L was selected for predicting CLNM risk by receiver operating characteristic (ROC) curve analysis. Multivariate analysis identified the following six independent risk factors for CLNM: maximum tumor size >1 cm [odds ratio (OR) = 2.406, 95% confidence interval (CI) (1.279-4.526), p = 0.006]; capsule invasion [OR = 2.664, 95% CI (1.324-5.360), p = 0.006]; irregular margin [OR = 2.922; 95% CI (1.397-6.111), p = 0.004]; CLN flow signal [OR = 3.618, 95% CI (1.631-8.027), p = 0.002]; tumor-foci number ≥2 [OR = 4.064, 95% CI (2.102-7.859), p < 0.001]; and STK1p ≥1.7 pmol/L [OR = 7.514, 95% CI (3.852-14.660), p < 0.001]. The constructed nomogram showed that the area under the ROC curve for the main dataset was 0.867 and that for the validation dataset was 0.830, exhibiting effectivity, and was recalculated to a total score of approximately 383. Through monitoring the response post-surgery, all patients were assessed as tumor-free at 12 months post-surgery, which was significantly associated with a reduction in STK1p to disease-free levels. Conclusion We demonstrate for the first time that a novel nomogram including STK1p combined with ultrasonography can assist in the clinical prevention of CLNM, by facilitating timely, individualized prophylactic CLNM dissection, thereby reducing the risk of secondary surgery and the probability of recurrence.
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Affiliation(s)
- Xiaolong Song
- Radioimmunoassay Center, Department of Clinical Laboratory, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Sven Skog
- Department of Medicine, Shenzhen Ellen-Sven Precision Medicine Institute, Shenzhen, China
| | - Long Wei
- Radioimmunoassay Center, Department of Clinical Laboratory, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Jinlv Qin
- Radioimmunoassay Center, Department of Clinical Laboratory, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Ru Yang
- Radioimmunoassay Center, Department of Clinical Laboratory, Shaanxi Provincial People’s Hospital, Xi’an, China
| | - Jin Li
- Department of Medicine, Shenzhen Ellen-Sven Precision Medicine Institute, Shenzhen, China
| | - Ji Zhou
- Department of Medicine, Shenzhen Ellen-Sven Precision Medicine Institute, Shenzhen, China
| | - Ellen He
- Department of Medicine, Shenzhen Ellen-Sven Precision Medicine Institute, Shenzhen, China
| | - Jianping Zhou
- Radioimmunoassay Center, Department of Clinical Laboratory, Shaanxi Provincial People’s Hospital, Xi’an, China
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Yao B, Huang X, Wu F, Li J, He E, Li X, Zhang M, Zhou J, Hong H, Skog S, Wang H. A Novel Model Using Serum Thymidine Kinase 1 and Low-dose Computed Tomography Parameters to Predict Three-year Lung Cancer Risk in People with Pulmonary Nodules: A Retrospective Study. J Cancer 2024; 15:737-746. [PMID: 38213734 PMCID: PMC10777045 DOI: 10.7150/jca.90428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 11/27/2023] [Indexed: 01/13/2024] Open
Abstract
This study was designed to develop a model of serum thymidine kinase 1 protein (STK1p) concentration in combination with low-dose computed tomography (LDCT) to predict the risk of benign pulmonary nodules progressing into lung cancer within three years in a large screening population. The study included a retrospective cohort of 6,841 individuals aged > 30 years who had LDCT-detected pulmonary nodules, but no cancer history or baseline cancer. The outcome was a lung cancer diagnosis recorded within three years after the first detection of pulmonary nodules. The adaptive least absolute shrinkage and selection operator was used to select candidate predictors and fit a logistic model. The model was validated internally by examining discrimination (area under the receiver operating characteristic curve (AUC), calibration (calibration plot)) and net benefit. A web application was developed based on the model. The results showed that the proportion of incident lung cancer cases was 0.79% (n=52). Predictors selected for the model were STK1p and three LDCT parameters (nodule size, type, and count). The AUC of the model was 0.91 (95% confidence interval (CI): 0.86, 0.96). The model had satisfactory discrimination at internal validation (AUC: 0.90 (0.84, 0.96)) and in subgroups (AUC=0.69-0.93). The high-risk group identified by the model exhibited a significantly higher three-year lung cancer risk than the low-risk group (odds ratio (OR): 66.03 (95% CI: 30.49, 162.98)). We concluded that the novel model of STK1p and LDCT parameters together can be used to accurately predict the three-year risk of lung cancer in people with pulmonary nodules.
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Affiliation(s)
- Bei Yao
- First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, China
| | - Xiaoyang Huang
- Department of Medicine, Shenzhen Ellen-Sven Precision Medicine Institute, Shenzhen, 518000, China
| | - Fei Wu
- China Health Promotion Foundation, Beijing, 100161, China
| | - Jin Li
- Department of Medicine, Shenzhen Ellen-Sven Precision Medicine Institute, Shenzhen, 518000, China
| | - Ellen He
- Department of Medicine, Shenzhen Ellen-Sven Precision Medicine Institute, Shenzhen, 518000, China
| | - Xiaojing Li
- First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, China
| | - Mukun Zhang
- First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, China
| | - Ji Zhou
- Department of Medicine, Shenzhen Ellen-Sven Precision Medicine Institute, Shenzhen, 518000, China
| | - Haiou Hong
- First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, China
| | - Sven Skog
- Department of Medicine, Shenzhen Ellen-Sven Precision Medicine Institute, Shenzhen, 518000, China
| | - Haidong Wang
- Department of Medicine, Shenzhen Ellen-Sven Precision Medicine Institute, Shenzhen, 518000, China
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Osredkar J, Jagarlamudi KK, Cviič D, Škof E, Cvjetićanin B, Zore A, Lukanović D, Eriksson S, Meglič L. Clinical Significance of the TK1-Specific Activity in the Early Detection of Ovarian Cancer. Oncology 2023; 102:17-29. [PMID: 37673047 DOI: 10.1159/000533428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 07/07/2023] [Indexed: 09/08/2023]
Abstract
INTRODUCTION Ovarian cancer is the eighth most common cause of cancer death in women. One of the major concerns is almost two-thirds of cases are typically diagnosed in the late stage as the symptoms are unspecific in the early stage of ovarian cancer. It is known that the combination of TK1 protein with CA 125 or HE4 showed better performance than either of them alone. That is why, the aim of the study was to investigate whether the TK1-specific activity (TK1 SA) could function as a complement marker for early-stage diagnosis of ovarian cancer. METHODS The study included a set of 198 sera consisting of 134 patients with ovarian tumors (72 benign and 62 malignant) and 64 healthy age-matched controls. The TK1 SA was determined using TK1 activity by TK-Liaison and TK1 protein by AroCell TK 210 ELISA. Further, CA 125, HE4, as well as risk of ovarian malignancy algorithm index were also determined in the same set of clinical samples. RESULTS The TK1 SA was significantly different between healthy compared to ovarian cancer patients (p < 0.0001). Strikingly, TK1 SA has higher sensitivity (55%) compared to other biomarkers in the detection of benign ovarian tumors. Further, the highest sensitivity was achieved by the combination of TK1 SA with CA 125 and HE4 for the detection of benign tumors as well as malignant ovarian tumors (72.2% and 88.7%). In addition, TK1 SA could significantly differentiate FIGO stage I/II from stage III/IV malignancies (p = 0.026). Follow-up of patients after surgery and chemotherapy showed a significant difference compared to TK1 SA at the time of diagnosis. CONCLUSIONS These results indicate that TK1 SA is a promising blood-based biomarker that could complement CA 125 and HE4 for the detection of early stages of ovarian cancer.
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Affiliation(s)
- Joško Osredkar
- Institute of Clinical Chemistry and Biochemistry, University Medical Centre Ljubljana, Ljubljana, Slovenia
- University of Ljubljana, Faculty of Pharmacy, Ljubljana, Slovenia
| | - Kiran Kumar Jagarlamudi
- Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Science, Uppsala, Sweden
- Research and Development Division, AroCell AB, Stockholm, Sweden
| | - Diana Cviič
- Institute of Clinical Chemistry and Biochemistry, University Medical Centre Ljubljana, Ljubljana, Slovenia
- University of Ljubljana, Faculty of Pharmacy, Ljubljana, Slovenia
| | - Erik Škof
- Institute of Oncology, Ljubljana, Slovenia
- University Ljubljana, Medical Faculty, Ljubljana, Slovenia
| | - Branko Cvjetićanin
- Division of Gynecology, Department of Gynecology, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Andrej Zore
- Division of Gynecology, Department of Gynecology, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - David Lukanović
- Division of Gynecology, Department of Gynecology, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Staffan Eriksson
- Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Science, Uppsala, Sweden
- Research and Development Division, AroCell AB, Stockholm, Sweden
| | - Leon Meglič
- University Ljubljana, Medical Faculty, Ljubljana, Slovenia
- Division of Gynecology, Department of Gynecology, University Medical Centre Ljubljana, Ljubljana, Slovenia
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A Dual Biomarker TK1 Protein and CA125 or HE4-Based Algorithm as a Better Diagnostic Tool than ROMA Index in Early Detection of Ovarian Cancer. Cancers (Basel) 2023; 15:cancers15051593. [PMID: 36900385 PMCID: PMC10000714 DOI: 10.3390/cancers15051593] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 02/20/2023] [Accepted: 02/26/2023] [Indexed: 03/08/2023] Open
Abstract
BACKGROUND The early detection of ovarian cancer is presently not effective, and it is crucial to establish biomarkers for the early diagnosis of ovarian cancer to improve the survival of patients. MATERIALS AND METHODS The aim of this study was to investigate the role of thymidine kinase 1 (TK1) in combination with CA 125 or HE4 to serve as a potential diagnostic biomarkers for ovarian cancer. In this study, a set of 198 serum samples consisting of 134 ovarian tumor patients and 64 healthy age-matched controls were analyzed. The TK1 protein levels in serum samples were determined using the AroCell TK 210 ELISA. RESULTS A combination of TK1 protein with CA 125 or HE4 showed better performance than either of them alone in the differentiation of early stage ovarian cancer from the healthy control group, but also a significantly better performance than the ROMA index. However, this was not observed using a TK1 activity test in combination with the other markers. Furthermore, the combination of TK1 protein and CA 125 or HE4 could differentiate early stage disease (stage I, II) more efficiently from advanced-stage (stage III, IV) disease (p < 0.0001). CONCLUSIONS The combination of TK1 protein with CA 125 or HE4 increased the potential of detecting ovarian cancer at early stages.
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