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Updated: Jun 3, 2026

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A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells
Published on: August 22, 2025
Integration of Raman Spectroscopy and Metabolomics for Early Breast Cancer Detection and Classification
Xue Li1, He Ren1, Yuhan Deng1
1Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, P.R. China.
Cancer Medicine
|June 2, 2026
Summary
Confocal Raman spectroscopy combined with metabolomics offers a non-invasive method for early breast cancer detection and classification. This technique analyzes biochemical and morphological tissue features to distinguish between normal and cancerous tissues.
Area of Science:
- Biomedical Optics
- Molecular Spectroscopy
- Oncology
Background:
- Breast cancer is a leading cause of mortality, emphasizing the need for early detection.
- Conventional histopathology is invasive and subjective, hindering early diagnosis.
- Novel non-invasive techniques are crucial for improving breast cancer diagnosis and management.
Purpose of the Study:
- To integrate confocal Raman spectroscopy and metabolomics for analyzing breast tissue biochemical and morphological features.
- To differentiate between normal breast tissue and various types of breast cancer, including fibroadenoma, ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC).
- To explore the potential of Raman spectroscopy for non-invasive early detection and classification of breast cancer subtypes.
Main Methods:
- Confocal Raman spectroscopy was used to analyze biochemical components (proteins, lipids, nucleic acids) in different breast tissue types.
- Spectral analysis and unmixing techniques were employed to map molecular distributions.
- Metabolomic profiling was performed to validate spectral findings and identify metabolic pathway alterations.
- Raman imaging was utilized for precise classification of specific breast cancer subtypes.
Main Results:
- Distinct spectral signatures were observed for normal, benign, and malignant breast tissues.
- Cancerous tissues showed increased protein and nucleic acid signals, with decreased lipids and carotenoids.
- Metabolomic analysis confirmed upregulated glycolysis and lipid synthesis in tumor regions.
- Raman imaging successfully classified subtypes like mucinous carcinoma and phyllodes tumors.
Conclusions:
- Raman spectroscopy, integrated with metabolomics, provides a powerful non-invasive tool for breast cancer diagnosis and subtyping.
- The technique reveals significant metabolic alterations associated with breast cancer development.
- This approach holds promise for advancing precision oncology through enhanced early detection and classification.
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A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
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