Raman micro-spectroscopy reveals the metabolic alterations in primary prostate tumor tissues of patients with metastases
Abstract Background Distant metastases mainly influence the prognosis of patients with prostate cancer (PC), however, development of novel biomarkers for predicting metastatic PC and understanding of the molecular mechanisms remain essential. The objective of this study was to investigate the metabo...
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BMC
2025-06-01
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| Series: | Journal of Translational Medicine |
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| Online Access: | https://doi.org/10.1186/s12967-025-06655-4 |
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| author | Xiaoguang Shao Bo Liu Hongyang Qian Qihan Zhang Yinjie Zhu Shupeng Liu Heng Zhang Jiahua Pan Wei Xue |
| author_facet | Xiaoguang Shao Bo Liu Hongyang Qian Qihan Zhang Yinjie Zhu Shupeng Liu Heng Zhang Jiahua Pan Wei Xue |
| author_sort | Xiaoguang Shao |
| collection | DOAJ |
| description | Abstract Background Distant metastases mainly influence the prognosis of patients with prostate cancer (PC), however, development of novel biomarkers for predicting metastatic PC and understanding of the molecular mechanisms remain essential. The objective of this study was to investigate the metabolic differences in the primary tumor tissues between localized PC and metastatic PC using Raman micro-spectroscopy and metabolomics analysis, and then explore potential biomarkers for predicting metastasis and the potential metabolic pathways during the progression from localized prostate cancer to metastasis. Methods We used confocal Raman microscopy (CRM) and liquid chromatography-mass spectrometry (LC–MS) based metabolomics to analyze the primary prostate tumor tissues of localized PC and metastatic PC. Subsequently, we used a convolutional neural network (CNN) structure to develop a classification model to predict metastatic PC based on the tissue Raman spectra, and then explored potential metabolic pathways via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Results We collected a total of 547 spontaneous Raman spectra and 2D Raman images of primary prostate tumor from 21 localized PC and 21 metastatic PC. Compared with localized PC, the Raman peak associated with unsaturated fatty acids was significantly higher in metastatic PC, while the Raman peaks associated with amino acids and proteins were significantly lower. Subsequently, we used a CNN structure to develop a classification model to predict metastatic PC based on the tissue Raman spectra and the model showed a testing accuracy of 81.3 ± 3.7%. The LC–MS based metabolomics results of tissues validated the CRM findings that the primary prostate tumor tissue of metastatic PC exhibited a similar changing trend in prenol lipids, linolenic acid, and multiple classes of amino acids. Conclusion The CRM could be a potential tool for predicting metastases by analyzing prostate biopsy tissues at the time of diagnosis. Our study found that metabolic remodelling of primary tumors occurred during the metastasis process. The metabolic alterations in primary tumor tissue can help elucidate the underlying mechanisms of the metastasis process, leading to the development of new therapies. |
| format | Article |
| id | doaj-art-c1ec8cc8097e4b4e8d01b39d6adff10f |
| institution | OA Journals |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj-art-c1ec8cc8097e4b4e8d01b39d6adff10f2025-08-20T02:10:38ZengBMCJournal of Translational Medicine1479-58762025-06-0123111410.1186/s12967-025-06655-4Raman micro-spectroscopy reveals the metabolic alterations in primary prostate tumor tissues of patients with metastasesXiaoguang Shao0Bo Liu1Hongyang Qian2Qihan Zhang3Yinjie Zhu4Shupeng Liu5Heng Zhang6Jiahua Pan7Wei Xue8Department of Urology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong UniversityDepartment of Urology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong UniversityDepartment of Urology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong UniversityDepartment of Urology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong UniversityDepartment of Urology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong UniversityKey Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai Institute for Advanced Communication and Data Science, Shanghai UniversityKey Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai Institute for Advanced Communication and Data Science, Shanghai UniversityDepartment of Urology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong UniversityDepartment of Urology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong UniversityAbstract Background Distant metastases mainly influence the prognosis of patients with prostate cancer (PC), however, development of novel biomarkers for predicting metastatic PC and understanding of the molecular mechanisms remain essential. The objective of this study was to investigate the metabolic differences in the primary tumor tissues between localized PC and metastatic PC using Raman micro-spectroscopy and metabolomics analysis, and then explore potential biomarkers for predicting metastasis and the potential metabolic pathways during the progression from localized prostate cancer to metastasis. Methods We used confocal Raman microscopy (CRM) and liquid chromatography-mass spectrometry (LC–MS) based metabolomics to analyze the primary prostate tumor tissues of localized PC and metastatic PC. Subsequently, we used a convolutional neural network (CNN) structure to develop a classification model to predict metastatic PC based on the tissue Raman spectra, and then explored potential metabolic pathways via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Results We collected a total of 547 spontaneous Raman spectra and 2D Raman images of primary prostate tumor from 21 localized PC and 21 metastatic PC. Compared with localized PC, the Raman peak associated with unsaturated fatty acids was significantly higher in metastatic PC, while the Raman peaks associated with amino acids and proteins were significantly lower. Subsequently, we used a CNN structure to develop a classification model to predict metastatic PC based on the tissue Raman spectra and the model showed a testing accuracy of 81.3 ± 3.7%. The LC–MS based metabolomics results of tissues validated the CRM findings that the primary prostate tumor tissue of metastatic PC exhibited a similar changing trend in prenol lipids, linolenic acid, and multiple classes of amino acids. Conclusion The CRM could be a potential tool for predicting metastases by analyzing prostate biopsy tissues at the time of diagnosis. Our study found that metabolic remodelling of primary tumors occurred during the metastasis process. The metabolic alterations in primary tumor tissue can help elucidate the underlying mechanisms of the metastasis process, leading to the development of new therapies.https://doi.org/10.1186/s12967-025-06655-4Confocal Raman microscopyMetabolomicsProstate cancerMetastasis |
| spellingShingle | Xiaoguang Shao Bo Liu Hongyang Qian Qihan Zhang Yinjie Zhu Shupeng Liu Heng Zhang Jiahua Pan Wei Xue Raman micro-spectroscopy reveals the metabolic alterations in primary prostate tumor tissues of patients with metastases Journal of Translational Medicine Confocal Raman microscopy Metabolomics Prostate cancer Metastasis |
| title | Raman micro-spectroscopy reveals the metabolic alterations in primary prostate tumor tissues of patients with metastases |
| title_full | Raman micro-spectroscopy reveals the metabolic alterations in primary prostate tumor tissues of patients with metastases |
| title_fullStr | Raman micro-spectroscopy reveals the metabolic alterations in primary prostate tumor tissues of patients with metastases |
| title_full_unstemmed | Raman micro-spectroscopy reveals the metabolic alterations in primary prostate tumor tissues of patients with metastases |
| title_short | Raman micro-spectroscopy reveals the metabolic alterations in primary prostate tumor tissues of patients with metastases |
| title_sort | raman micro spectroscopy reveals the metabolic alterations in primary prostate tumor tissues of patients with metastases |
| topic | Confocal Raman microscopy Metabolomics Prostate cancer Metastasis |
| url | https://doi.org/10.1186/s12967-025-06655-4 |
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