Sharif Hanan, Arabi Belaghi Reza, Jagarlamudi Kiran Kumar, Saellström Sara, Wang Liya, Rönnberg Henrik, Eriksson Staffan
Alertix Veterinary Diagnostics, Stockholm, Sweden.
Department of Animal Biosciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Front Vet Sci. 2025 Apr 25;12:1570106. doi: 10.3389/fvets.2025.1570106. eCollection 2025.
The demand for non-invasive tumor biomarkers in veterinary field has recently grown significantly. Thymidine kinase 1 (TK1) is one of the non-invasive proliferation biomarkers that has been used for diagnosis and treatment monitoring of different canine malignancies. However, recent studies showed that the combination of TK1 with inflammatory biomarkers such as canine C-reactive protein (cCRP) can enhance the sensitivity for early tumor detection. Herein, we developed a machine learning (ML) model, i.e., Alertix-Cancer Risk Index (Alertix-CRI) which incorporates canine TK1 protein, CRP levels in conjunction with an age factor.
A total of 287 serum samples were included in this study, consisting of 67 healthy dogs and dogs with different tumors (i.e., T-cell lymphoma = 24, B-cell lymphoma = 29, histiocytic sarcoma = 47, hemangiosarcoma = 26, osteosarcoma = 26, mastocytoma = 40, and mammary tumors = 28). Serum TK1 protein levels were measured using TK1-ELISA and cCRP levels by a quantitative ELISA. The whole data set was divided as training (70%) and validation (30%). The Alertix-Cancer Risk Index (Alertix-CRI) is a generalized boosted regression model (GBM) with high accuracy in the training set and further validation was carried out with the same model.
Both the TK1-ELISA and cCRP levels were significantly higher in the tumor group compared to healthy controls ( < 0.0001). For overall tumors, the ROC curve analysis showed that TK1-ELISA has similar sensitivity as cCRP (54% vs. 51%) at a specificity of 95%. However, the Alertix-CRI for all malignancies showed an area under the curve (AUC) of 0.98, demonstrating very high discriminatory capacity, with a sensitivity of 90% and a specificity of 97%.
These results demonstrate that the novel Alertix-CRI could be used as a decision-support tool helping clinicians to early differentiate dogs with malignant diseases from healthy. Additionally, these findings would facilitate the advancement of more precise and dependable diagnostic tools for early cancer detection and therapy monitoring within the realm of veterinary medicine.
近年来，兽医领域对非侵入性肿瘤生物标志物的需求显著增长。胸苷激酶1（TK1）是一种非侵入性增殖生物标志物，已用于不同犬类恶性肿瘤的诊断和治疗监测。然而，最近的研究表明，TK1与炎症生物标志物如犬C反应蛋白（cCRP）联合使用可提高早期肿瘤检测的敏感性。在此，我们开发了一种机器学习（ML）模型，即Alertix-癌症风险指数（Alertix-CRI），该模型结合了犬TK1蛋白、CRP水平以及年龄因素。
本研究共纳入287份血清样本，包括67只健康犬和患有不同肿瘤的犬（即T细胞淋巴瘤=24只、B细胞淋巴瘤=29只、组织细胞肉瘤=47只、血管肉瘤=26只、骨肉瘤=26只、肥大细胞瘤=40只和乳腺肿瘤=28只）。使用TK1-ELISA测定血清TK1蛋白水平，通过定量ELISA测定cCRP水平。整个数据集分为训练集（70%）和验证集（30%）。Alertix-癌症风险指数（Alertix-CRI）是一种广义增强回归模型（GBM），在训练集中具有较高的准确性，并使用相同模型进行进一步验证。
与健康对照组相比，肿瘤组的TK1-ELISA和cCRP水平均显著更高（<0.0001）。对于总体肿瘤，ROC曲线分析表明，TK1-ELISA在特异性为95%时的敏感性与cCRP相似（54%对51%）。然而，所有恶性肿瘤的Alertix-CRI曲线下面积（AUC）为0.98，显示出非常高的鉴别能力，敏感性为90%，特异性为97%。
这些结果表明，新型Alertix-CRI可作为一种决策支持工具，帮助临床医生早期区分患有恶性疾病的犬与健康犬。此外，这些发现将有助于在兽医学领域开发更精确、可靠的早期癌症检测和治疗监测诊断工具。
