Research progress on autoantibody liquid biopsy and AI-based radiomics in the diagnosis and treatment of non-small cell lung cancer_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

WANG Donghui ^1,2 , TANG Xu ^1,2 , ZHANG Zhiyuan ¹ , MA Nan ³ ,  DONG Xinchun ^1,2 ,  GOU Yunjiu ^1,2

1. Graduate School, Gansu University of Chinese Medicine, Lanzhou, 730000, P. R. China;
2. Department of Thoracic Surgery, Gansu Provincial Hospital, Lanzhou, 730000, P. R. China;
3. First Ward of Department of Cardiology, Gansu Provincial Hospital, Lanzhou, 730000, P. R. China;

Corresponding?author：

DONG Xinchun, Email: 3050319523@qq.com; GOU Yunjiu, Email: gouyunjiu@163.com

Keywords：

Lung cancer; non-small cell lung cancer; autoantibodies liquid biopsy; artificial intelligence; radiomics; review

DOI：

10.7507/1007-4848.202508010

Video：

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Abstract Full text Figures/Tables Video References Cited by

Lung cancer has the highest incidence and mortality rates among malignant tumors both in China and worldwide, with approximately 85% of cases being non-small cell lung cancer (NSCLC). In the diagnosis and treatment of lung cancer, conventional imaging and tissue biopsy are often limited by insufficient sensitivity or invasive risks, making it difficult to meet the demands of future precision medicine. In recent years, artificial intelligence (AI)-based radiomics and autoantibody-based liquid biopsy have developed rapidly and have become major research focuses. AI radiomics significantly improves the accuracy of traditional imaging diagnosis by autonomously learning from large-scale imaging databases. Autoantibody liquid biopsy, on the other hand, utilizes tumor-associated autoantigens and antibodies as biomarkers, offering the advantages of being non-invasive, precise, efficient, and capable of reflecting spatiotemporal tumor heterogeneity, thereby demonstrating great potential in NSCLC diagnosis and treatment. This review summarizes recent research advances in autoantibody liquid biopsy and AI radiomics for the management of lung cancer.

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1. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 2021, 71(3): 209-249.
2. 唐旭, 王瑾, 周文生, 等. 基于循環腫瘤DNA液體活檢監測分子殘留病灶在非小細胞肺癌診療中的應用進展. 中國胸心血管外科臨床雜志, 2025.Epub ahead of print]. Tang X, Wang J, Zhou WS, et al. Application progress of circulating tumor DNA liquid biopsy in monitoring minimal residual disease in non-small cell lung cancer. Chin J Clin Thorac Cardiovasc Surg, 2025, [Epub ahead of print].
3. Minami Y. The notable topics of the 5th edition of WHO classification for the thoracic tumours (2021). Gan To Kagaku Ryoho, 2022, 49(8): 847-852.
4. Goldstraw P, Chansky K, Crowley J, et al. The IASLC lung cancer staging project: proposals for revision of the TNM stage groupings in the forthcoming (eighth) edition of the TNM classification for lung cancer. J Thorac Oncol, 2016, 11(1): 39-51.
5. Liu Y, Gao Y, Wu Y, et al. Autoantibodies as potential liquid biopsy biomarker in detection of pancreatic cancer: a diagnostic test accuracy review and meta-analysis. Scand J Immunol, 2025, 101(4): e70012.
6. Ouyang R, Wu S, Zhang B, et al. Clinical value of tumor-associated antigens and autoantibody panel combination detection in the early diagnostic of lung cancer. Cancer Biomark, 2021, 32(3): 401-409.
7. Graeve VIJ, Laures S, Spirig A, et al. Implementation of an AI algorithm in clinical practice to reduce missed incidental pulmonary embolisms on chest CT and its impact on short-term survival. Invest Radiol, 2025, 60(4): 260-266.
8. 桑亞麗, 宋麗沙, 彭明月, 等. 肺癌患者血清中外泌體潛在自身抗體標志物的研究進展. 內蒙古醫學雜志, 2025, 57(5): 569-573.Sang YL, Song LS, Peng MY, et al. Research progress on potential autoantibody markers in serum exosomes of lung cancer patients. Inner Mongol Med J, 2025, 57(5): 569-573.
9. 孫碩, 王鋒, 何立, 等. 液體活檢生物標志物及其聯合影像學在肺癌早期診斷中應用的研究進展. 中國胸心血管外科臨床雜志, 2023, 30(2): 313-319.Sun S, Wang F, He L, et al. Research progress on liquid biopsy biomarkers and their combination with imaging in the early diagnosis of lung cancer. Chin J Clin Thorac Cardiovasc Surg, 2023, 30(2): 313-319.
10. 王冰, 邱紅. 腫瘤標志物在肺癌診斷中的研究進展. 國際檢驗醫學雜志, 2013, 34(24): 3384-3386.Wang B, Qiu H. Research progress on tumor markers in the diagnosis of lung cancer. Int J Lab Med, 2013, 34(24): 3384-3386.
11. 王柳倩, 馬為. 腫瘤標志物在肺癌的早期診斷及預后評估中的研究進展. 現代腫瘤醫學, 2014, 22(12): 3004-3007.Wang LQ, Ma W. Research progress on tumor markers in early diagnosis and prognosis evaluation of lung cancer. J Mod Oncol, 2014, 22(12): 3004-3007.
12. 吳東霞, 沈溪明. 腫瘤標志物在肺癌早期診斷與治療中的價值. 吉林醫學, 2016, 37(8): 1976-1977.Wu DX, Shen XM. The value of tumor markers in the early diagnosis and treatment of lung cancer. Jilin Med J, 2016, 37(8): 1976-1977.
13. Xu Y, Zhang W, Xia T, et al. Diagnostic value of tumor-associated autoantibodies panel in combination with traditional tumor markers for lung cancer. Front Oncol, 2023, 13: 1022331.
14. 周瀟, 鄒強, 張巖. 7項腫瘤相關抗原自身抗體在不同分期非小細胞肺癌診斷中臨床意義. 臨床軍醫雜志, 2022, 50(9): 922-925.Zhou X, Zou Q, Zhang Y. Clinical significance of seven tumor-associated antigen autoantibodies in the diagnosis of non-small cell lung cancer at different stages. J Clin Military Surgeon, 2022, 50(9): 922-925.
15. Tong L, Sun J, Zhang X, et al. Development of an autoantibody panel for early detection of lung cancer in the Chinese population. Front Med (Lausanne), 2023, 10: 1209747.
16. 張少華, 杜文水. 人血清涎液化糖鏈抗原磁微粒化學發光免疫分析方法的建立及對肺癌的診斷價值. 醫療裝備, 2024, 37(1): 95-101.Zhang SH, Du WS. Establishment of a magnetic particle chemiluminescence immunoassay for human serum sialylated glycoprotein antigen and its diagnostic value for lung cancer. Med Equipment, 2024, 37(1): 95-101.
17. He T, Wu Z, Xia P, et al. The combination of a seven-autoantibody panel with computed tomography scanning can enhance the diagnostic efficiency of non-small cell lung cancer. Front Oncol, 2022, 12: 1047019.
18. Qin J, Zeng N, Yang T, et al. Diagnostic value of autoantibodies in lung cancer: a systematic review and meta-analysis. Cell Physiol Biochem, 2018, 51(6): 2631-2646.
19. Xie F, Xu L, Mu Y, et al. Diagnostic value of seven autoantibodies combined with CEA and CA199 in non-small cell lung cancer. Clin Lab, 2023, 69(5): 789-795.
20. Mu YY, Xie FY, Wang FB, et al. Performance evaluation of an enzyme-linked immunosorbent assay for seven autoantibodies in lung cancer. Clin Lab, 2019, 65(4): 475-482.
21. Chen Q, Zhu S, Jiao N, et al. Improvement in the performance of an autoantibody panel in combination with heat shock protein 90a for the detection of early-stage lung cancer. Exp Ther Med, 2023, 25(2): 82.
22. Veronesi G, Bianchi F, Infante M, et al. The challenge of small lung nodules identified in CT screening: can biomarkers assist diagnosis? Biomark Med, 2016, 10(2): 137-143.
23. Chapman CJ, Healey GF, Murray A, et al. EarlyCDT-Lung test: improved clinical utility through additional autoantibody assays. Tumour Biol, 2012, 33(5): 1319-1326.
24. Jett JR, Peek LJ, Fredericks L, et al. Audit of the autoantibody test, EarlyCDT-Lung, in 1600 patients: an evaluation of its performance in routine clinical practice. Lung Cancer, 2014, 83(1): 51-55.
25. Massion PP, Healey GF, Peek LJ, et al. Autoantibody signature enhances the positive predictive power of computed tomography and nodule-based risk models for detection of lung cancer. J Thorac Oncol, 2017, 12(3): 578-584.
26. Ren S, Zhang S, Jiang T, et al. Early detection of lung cancer by using an autoantibody panel in Chinese population. Oncoimmunology, 2018, 7(2): e1384108.
27. Zhang R, Ma L, Li W, et al. Diagnostic value of multiple tumor-associated autoantibodies in lung cancer. Onco Targets Ther, 2019, 12: 457-469.
28. Huang H, Luo W, Ni Y, et al. The diagnostic efficiency of seven autoantibodies in lung cancer. Eur J Cancer Prev, 2020, 29(4): 315-320.
29. 羅國慶, 盧瀟, 李定慧, 等. 2024年第5版《NCCN腫瘤臨床實踐指南: 非小細胞肺癌》更新解讀. 中國胸心血管外科臨床雜志, 2024, 31(7): 955-961.Luo GQ, Lu X, Li DH, et al. Interpretation of the updated NCCN clinical practice guidelines in oncology: non-small cell lung cancer (version 5. 2024). Chin J Clin Thorac Cardiovasc Surg, 2024, 31(7): 955-961.
30. 王家樂, 邱天羽, 崔亞男, 等. 2024 CSCO非小細胞肺癌指南(晚期部分)解讀. 同濟大學學報(醫學版), 2024, 45(4): 465-470.Wang JL, Qiu TY, Cui YN, et al. Interpretation of the 2024 CSCO non-small cell lung cancer guidelines (advanced stage). J Tongji Univ (Med Sci), 2024, 45(4): 465-470.
31. Jiang P, Wang K, Wei Y, et al. Serum autoantibody-based biomarkers for prognosis in early-stage lung cancer patients with surgical resection. Biomarkers, 2025, 30(2): 131-139.
32. 張守宇, 陳勃江, 李為民. 人工智能在肺癌早期診斷與精準治療中的應用與挑戰. 腫瘤防治研究, 2024, 51(12): 1000-1006.Zhang SY, Chen BJ, Li WM. Application and challenges of artificial intelligence in the early diagnosis and precision treatment of lung cancer. Cancer Res Prev Treat, 2024, 51(12): 1000-1006.
33. Shimizu H, Nakayama KI. Artificial intelligence in oncology. Cancer Sci, 2020, 111(5): 1452-1460.
34. Li C, Yan Y, Lin W, et al. Enhancing cancer subtype classification through convolutional neural networks: a deepinsight analysis of TCGA gene expression data. Health Inf Sci Syst, 2025, 13(1): 33.
35. Lambin P, Rios-Velazquez E, Leijenaar R, et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer, 2012, 48(4): 441-446.
36. Zwanenburg A, Vallieres M, Abdalah MA, et al. The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping. Radiology, 2020, 295(2): 328-338.
37. Tuminello S, Flores R, Untalan M, et al. Predicted effect of incidental pulmonary nodule findings on NSCLC mortality. J Thorac Oncol, 2025, 20(3): 273-284.
38. Liu JA, Yang IY, Tsai EB. Artificial intelligence (AI) for lung nodules, from the AJR special series on AI applications. AJR Am J Roentgenol, 2022, 219(5): 703-712.
39. Boubnovski Martell M, Linton-Reid K, Chen M, et al. Radiomics for lung cancer diagnosis, management, and future prospects. Clin Radiol, 2025, 86: 106926.
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Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Latest ArticlesResearch progress on autoantibody liquid biopsy and AI-based radiomics in the diagnosis and treatment of non-small cell lung cancer

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