Fabrication of serum-based SERS-tailored 3D structures for thyroid cancer diagnosis
Abstract Early detection of thyroid cancer improves patient survival rate from 51.9% to 99.9%. Fine needle aspiration cytology is the primary method for diagnosing thyroid cancer; however, this method is associated with limitations, including diagnostic uncertainty and potential complications. Despi...
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-06346-6 |
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| author | Sunwoo Park Yeongsu Jo Sung-Jo Kim Thanh Mien Nguyen Min Jin Lee Ji Hyun Bae Hyung Woo Lee Dongwon Yi Jin-Woo Oh |
| author_facet | Sunwoo Park Yeongsu Jo Sung-Jo Kim Thanh Mien Nguyen Min Jin Lee Ji Hyun Bae Hyung Woo Lee Dongwon Yi Jin-Woo Oh |
| author_sort | Sunwoo Park |
| collection | DOAJ |
| description | Abstract Early detection of thyroid cancer improves patient survival rate from 51.9% to 99.9%. Fine needle aspiration cytology is the primary method for diagnosing thyroid cancer; however, this method is associated with limitations, including diagnostic uncertainty and potential complications. Despite numerous studies to identify diagnostic biomarkers for thyroid cancer, none has been found to date. Therefore, new methods that do not rely on biomarkers are warranted to aid thyroid cancer diagnosis. Here, we suggest a novel approach using 3D gold nanoclusters to obtain Surface-enhanced Raman scattering (SERS) spectra using the serum samples of patients with thyroid cancer and normal individuals. Briefly, an evaporation-based 3D printing technique was employed to fabricate nanoclusters containing serum. SERS spectra were collected from 50 normal individuals and 50 patients with thyroid cancer. The spectra were then analysed using machine learning with 1D and 2D convolutional neural networks (CNNs) architecture. Notably, the 2D CNN exhibited superior performance for the classification of thyroid cancer cases, with sensitivity of 93.1% and specificity of 84.0%. Such findings suggest the potential use of metabolite analysis for the diagnosis of thyroid cancer without finding biomarkers. This SERS measurement approach using 3D nanoclusters may also be leveraged for the diagnosis of other diseases. |
| format | Article |
| id | doaj-art-8208d03f607b4a0a9b99da60646cbc1f |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-8208d03f607b4a0a9b99da60646cbc1f2025-08-20T04:01:51ZengNature PortfolioScientific Reports2045-23222025-07-011511910.1038/s41598-025-06346-6Fabrication of serum-based SERS-tailored 3D structures for thyroid cancer diagnosisSunwoo Park0Yeongsu Jo1Sung-Jo Kim2Thanh Mien Nguyen3Min Jin Lee4Ji Hyun Bae5Hyung Woo Lee6Dongwon Yi7Jin-Woo Oh8Department of Nanoenergy Engineering, Pusan National UniversityDepartment of Nano fusion Technology, Pusan National UniversityInstitute of NanoBio Convergence, Pusan National UniversityInstitute of NanoBio Convergence, Pusan National UniversityDivision of Endocrinology and Metabolism, Department of Internal Medicine, Pusan National University Yangsan Hospital, Pusan National University School of MedicineDivision of Endocrinology and Metabolism, Department of Internal Medicine, Pusan National University Yangsan Hospital, Pusan National University School of MedicineDepartment of Nanoenergy Engineering, Pusan National UniversityDivision of Endocrinology and Metabolism, Department of Internal Medicine, Pusan National University Yangsan Hospital, Pusan National University School of MedicineDepartment of Nanoenergy Engineering, Pusan National UniversityAbstract Early detection of thyroid cancer improves patient survival rate from 51.9% to 99.9%. Fine needle aspiration cytology is the primary method for diagnosing thyroid cancer; however, this method is associated with limitations, including diagnostic uncertainty and potential complications. Despite numerous studies to identify diagnostic biomarkers for thyroid cancer, none has been found to date. Therefore, new methods that do not rely on biomarkers are warranted to aid thyroid cancer diagnosis. Here, we suggest a novel approach using 3D gold nanoclusters to obtain Surface-enhanced Raman scattering (SERS) spectra using the serum samples of patients with thyroid cancer and normal individuals. Briefly, an evaporation-based 3D printing technique was employed to fabricate nanoclusters containing serum. SERS spectra were collected from 50 normal individuals and 50 patients with thyroid cancer. The spectra were then analysed using machine learning with 1D and 2D convolutional neural networks (CNNs) architecture. Notably, the 2D CNN exhibited superior performance for the classification of thyroid cancer cases, with sensitivity of 93.1% and specificity of 84.0%. Such findings suggest the potential use of metabolite analysis for the diagnosis of thyroid cancer without finding biomarkers. This SERS measurement approach using 3D nanoclusters may also be leveraged for the diagnosis of other diseases.https://doi.org/10.1038/s41598-025-06346-6Thyroid Cancer DiagnosisSERSSerum3D Printing |
| spellingShingle | Sunwoo Park Yeongsu Jo Sung-Jo Kim Thanh Mien Nguyen Min Jin Lee Ji Hyun Bae Hyung Woo Lee Dongwon Yi Jin-Woo Oh Fabrication of serum-based SERS-tailored 3D structures for thyroid cancer diagnosis Scientific Reports Thyroid Cancer Diagnosis SERS Serum 3D Printing |
| title | Fabrication of serum-based SERS-tailored 3D structures for thyroid cancer diagnosis |
| title_full | Fabrication of serum-based SERS-tailored 3D structures for thyroid cancer diagnosis |
| title_fullStr | Fabrication of serum-based SERS-tailored 3D structures for thyroid cancer diagnosis |
| title_full_unstemmed | Fabrication of serum-based SERS-tailored 3D structures for thyroid cancer diagnosis |
| title_short | Fabrication of serum-based SERS-tailored 3D structures for thyroid cancer diagnosis |
| title_sort | fabrication of serum based sers tailored 3d structures for thyroid cancer diagnosis |
| topic | Thyroid Cancer Diagnosis SERS Serum 3D Printing |
| url | https://doi.org/10.1038/s41598-025-06346-6 |
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