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Updated: Apr 18, 2026
A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis
Published on: March 8, 2022
Infrared imaging of primary melanomas reveals hints of regional and distant metastases
1Center for Structural Biology and Bioinformatics, Laboratory for the Structure and Function of Biological Membranes; Université Libre de Bruxelles, Campus Plaine, Bld du Triomphe 2, CP206/2, B1050 Brussels, Belgium. egoor@ulb.ac.be.
Abstract:
Melanoma is the deadliest form of skin cancer. Metastatic melanomas are resistant to almost all existing adjuvant therapies such as chemotherapy and radiotherapy, so detection of metastases remains a challenge, and no biomarkers are currently available to detect primary tumors with the highest risk of metastasis. Results presented in this paper show that Fourier Transform Infrared (FTIR) imaging of histological sections followed by supervised partial least squares discriminant analysis (PLS-DA) can accurately (>90%) identify the main cell types commonly found in melanoma tumors. Here we define six cell types: melanoma cells, erythrocytes, connective tissue (includes blood vessel walls, dermis and collagen regions), keratinocytes, lymphocytes and necrotic cells. Interestingly, more than 98% of the melanoma cells are correctly identified. The spectra of the cells identified as melanomas were then further analyzed. First, we compared melanoma cells in primary tumors (from 26 patients) with melanoma cells from metastases (from 25 patients). Neither supervised nor unsupervised analyses revealed any significant difference. Similarly, we found no significant correlation between the infrared spectra of melanoma cells and the number of proliferative cells assessed by Ki67 immunostaining. Finally, we compared the infrared spectra of primary tumors from patients diagnosed at different stages of the disease. Infrared spectroscopy was capable of pointing out differences between primary tumors of patients at stage I or II and patients at stage III or IV, even by unsupervised analysis. We then developed a supervised PLS-DA model capable of predicting whether tumor cells belonged to one of the two aggregated disease stage groups. The model predicted a high rate of true positives (sensitivity of 88.9%) and a good rate of true negatives (specificity of 70.6%) in external validation. These results demonstrate that infrared spectroscopy can be used to help identify melanoma characteristics related to the cells' invasive capability.
Insights
Fourier Transform Infrared (FTIR) imaging accurately identifies melanoma cell types and stages. This infrared spectroscopy method shows potential for detecting melanoma
Area of Science:
- Biomedical Optics
- Cancer Research
- Spectroscopy
Background:
- Melanoma is a deadly skin cancer with limited treatment options for metastatic disease.
- Detecting melanoma metastases and predicting metastatic risk remain significant clinical challenges.
- Current biomarkers for identifying high-metastatic-risk primary melanomas are lacking.
Purpose of the Study:
- To evaluate the efficacy of Fourier Transform Infrared (FTIR) imaging combined with partial least squares discriminant analysis (PLS-DA) for melanoma cell type identification and staging.
- To explore FTIR spectroscopy as a potential biomarker for melanoma's invasive capability.
- To differentiate between primary melanoma tumors and metastases using spectral analysis.
Main Methods:
- Histological sections of melanoma tumors underwent FTIR imaging.
- Supervised PLS-DA was employed to classify six distinct cell types: melanoma cells, erythrocytes, connective tissue, keratinocytes, lymphocytes, and necrotic cells.
- Infrared spectra were analyzed to compare primary tumors with metastases and to correlate with disease stage and proliferation markers (Ki67).
Main Results:
- FTIR imaging achieved >90% accuracy in identifying melanoma cell types, with over 98% accuracy for melanoma cells specifically.
- No significant spectral differences were found between melanoma cells from primary tumors and metastases.
- FTIR spectroscopy successfully distinguished between early-stage (I/II) and late-stage (III/IV) primary melanomas, even with unsupervised analysis.
- A supervised PLS-DA model demonstrated 88.9% sensitivity and 70.6% specificity in predicting aggregated disease stages during external validation.
Conclusions:
- FTIR imaging and PLS-DA are effective tools for accurate melanoma cell type classification.
- Infrared spectroscopy shows promise in differentiating melanoma tumor stages and potentially assessing invasive capability.
- This technique offers a novel approach to aid in melanoma diagnosis and risk stratification, addressing the need for better biomarkers.
