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ANALYTICA CHIMICA ACTA · 2025 · IF 6

Nasopharyngeal cancer screening and immunotherapy efficacy evaluation based on plasma separation combined with label-free SERS technology

Ruiying Lin,Zhangying Jiang,Jinyong Lin,Feifei Tong,Yangmin Wu,Jinquan Hong,Sufang Qiu,Qiong Wu

Background In recent years, significant progress has been made in the treatment of nasopharyngeal carcinoma (NPC). The application of immunotherapy, especially the use of Programmed Cell Death Protein 1 inhibitors, has demonstrated excellent therapeutic effects. However, inconsistent immunotherapy outcomes due to individual differences in patients remain a major challenge, making the search for specific biomarkers to screen for the population who may benefit from immunotherapy a priority. Surface-enhanced Raman spectroscopy (SERS) has shown great potential as a highly sensitive and specific optical analytical tool for identifying and monitoring tumor-related markers in NPC. Results In this study, plasma samples from Nasopharyngeal cancer patients before and after immunotherapy, along with those from healthy volunteers, were tested using label-free SERS combined with plasmapheresis. Especially, the components with varying molecular weight sizes were analyzed via the separation process, thereby preventing the potential loss of diagnostic information that could result from competitive adsorption. Subsequently, a robust machine learning algorithm based on principal component analysis and linear discriminant analysis (PCA-LDA) was used to extract features from plasma SERS data and establish an effective discriminant model. The results showed that in the upper plasma layer, the most optimal discrimination was found between normal patients and those post-treatment, with sensitivity and specificity of 88.5% and 92.3%, respectively. In the lower plasma layer, the most optimal discrimination was found between the pre-treatment and post-treatment patients, with sensitivity and specificity of 84.6% and 80.8%, respectively. Significance and novelty Plasmapheresis can reveal latent diagnostic information in the plasma and holds promise for treating NPC, the screening of the population who may benefit from immunotherapy, and the postoperative evaluation of immunotherapy. Further exploration of the feasibility of using SERS to detect tumor markers in the population who may benefit from immunotherapy for NPC will help improve the therapeutic efficacy, optimize clinical practice, and promote the development of individualized treatment strategies.

CAS / MDL: 5470-11-1 7761-88-8
研究领域: 肿瘤学 · 医学诊断 · 生物信息学
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JOURNAL OF RAMAN SPECTROSCOPY · 2022 ·Vol. 53 ·期 8 ·1371-1379 · IF 2.727

A comparative study based on serum SERS spectra in and on the coffee ring for high precision breast cancer detection

Xueliang Lin,Xianggang Jia,Jin Yong Lin,Ping Hui Wu,Youliang Weng,Shangyuan Feng

Human blood contains a variety of biomolecules that are highly related to the occurrence, progression, and prognosis of diseases, including cancer. The development of rapid and accurate methods for the detection of these biomarkers with extremely low concentration is vital for improving cancer screening. Herein, a label-free surface-enhanced Raman scattering (SERS) technology was employed to detect human serum samples from healthy volunteers ( n = 51) and breast cancer patients ( n = 58) with the aim of exploring the differences in bio-components between them. Moreover, the influence of measurement location during SERS assay was evaluated due to the occurrence of “coffee-ring (CR)” effect associated with this work. Results showed that the SERS spectra obtained from the CR area can better reflect the overall biochemical information of serum samples and exhibited excellent diagnostic sensitivity (94.8%) and specificity (98%) for identifying breast cancer from healthy groups using principal component analysis and linear discriminant analysis (PCA-LDA) algorithm. This work showed a preliminary study of the serum SERS method for breast cancer detection, providing a potential rapid and accurate liquid biopsy strategy for clinical cancer screening.

研究领域: 医学诊断 · 光谱学 · 癌症研究
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