Raman in Vivo Analysis of Melanoma Invasion Level

Lyudmila A. Bratchenko orcid (Login required)
Samara National Research University, Russian Federation

Yulia A. Khristoforova
Samara National Research University, Russian Federation

Yulia G. Loginova
Samara State Medical University, Russian Federation

Alexander A. Moryatov
Samara State Medical University, Russian Federation

Valery P. Zakharov
Samara National Research University, Russian Federation

Oleg I. Kaganov
Samara State Medical University, Russian Federation

Ivan A. Bratchenko
Samara National Research University, Russian Federation




DOI: 10.18287/JBPE25.11.030303

Abstract

The number of diagnosed melanoma cases is increasing every year, and there is an urgent need for novel screening approaches that may help in the diagnosis and prognosis of melanoma. In this study we propose to utilize conventional Raman spectroscopy for the determination of Clark level of invasion. We collected spectral data from 59 melanoma samples and achieved accuracy of 75% for discrimination of I−II vs. III−V levels of invasion. This study is the first to explore the potential of spectral analysis, utilizing Raman scattering and autofluorescence techniques, for distinguishing melanoma tissues according to their invasion level. Analysis of spectral data was performed with the application of projection on latent structures and discriminant analysis. The most significant for the model is the spectrum bands, associated with autofluorescence. The most informative bands of the Raman component for the constructed discrimination of melanoma tissues by the degree of invasion are the bands of 1385 cm−1, 1445 cm−1, 1487 cm−1, 1565 cm−1, and 1695 cm−1, associated with the presence of pigments (melanin), protein components (e.g., amide bonds, collagen), and lipid structures. The proposed approach may be useful in fast screening analysis for the determination of the best treatment plan for the patient based solely on the analysis of Raman spectra.

Keywords

Clark level; melanoma; Raman spectroscopy; autofluorescence; optical biopsy; invasion, PLS

Full Text:

PDF

References


1. “Cancer Facts & Figures 2025,” American Cancer Society, Atlanta (accessed 4 August 2025). [https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer-facts-and-figures/2025/2025-cancer-facts-and-figures-acs.pdf].

2. D. Barh, A. Carpi, M. Verma, and M. Gunduz (Eds.), Cancer Biomarkers: Minimal and Noninvasive Early Diagnosis and Prognosis, CRC Press, Boca Raton (2017). eBook ISBN: 9780429169304.

3. M. Antohe, A. Coman, G. Turcu, R. I. Nedelcu, A. Brinzea, M. Balaban, A. Moroianu, L. Manea, I. Hulea, E. Balasescu, S. A. Zurac, M. Cioplea, C. Popp, L. Nichita, and D. A. Ion, “The prognostic significance of the clinical and histological parameters in primary cutaneous melanoma patients,” Medicine and Pharmacy Reports 95(3), 229–235 (2022).

4. W. H. Clark, L. From, E. A. Bernardino, and M. C. Mihm, “The histogenesis and biologic behavior of primary human malignant melanomas of the skin,” Cancer Research 29(3), 705–727 (1969).

5. K. Stawarz, A. Galazka, M. Misiak-Galazka, M. Durzynska, A. Gorzelnik, K. Bienkowska-Pluta, J. Korzon, F. Kissin, and J. Zwolinski, “Advances in skin ultrasonography for malignant and benign tumors of the head and neck: current insights and future directions,” Journal of Clinical Medicine 14(7), 2298 (2025).

6. M. Kawaguchi, H. Kato, Y. Noda, K. Kobayashi, T. Miyazaki, F. Hyodo, and M. Matsuo, “Imaging findings of malignant skin tumors: radiological–pathological correlation,” Insights Imaging 13(1), 52 (2022).

7. C. Burnette, T. E. Sivesind, and R. Dellavalle, “From the cochrane library: optical coherence tomography for diagnosing skin cancer in adults,” Journal of Medical Internet Research Dermatology 6, e41355 (2023).

8. M. Zafar, A. P. Siegel, K. Avanaki, and R. Manwar, “Skin imaging using optical coherence tomography and photoacoustic imaging: a mini-review,” Optics 5(2), 248–266 (2024).

9. F. S. L. Quintana, H. L. D. Almeida Jr., C. P. Ruas, and V. M. Jorge, “Scanning electron microscopy of dermatofibroma,” Anais Brasileiros de Dermatologia Journal 94(3), 358–360 (2019).

10. Y. Ouyang, Y. Liu, Z. M. Wang, Z. Liu, and M. Wu, “FLIM as a promising tool for cancer diagnosis and treatment monitoring,” Nano-Micro Letters 13(1), 133 (2021).

11. L. Rey-Barroso, S. Peña-Gutiérrez, C. Yáñez, F. J. Burgos-Fernández, M. Vilaseca, and S. Royo, “Optical technologies for the improvement of skin cancer diagnosis: A review,” Sensors 21(1), 252 (2021).

12. D. Lunter, V. Klang, D. Kocsis, Z. Varga-Medveczky, S. Berkó, and F. Erdő, “Novel aspects of Raman spectroscopy in skin research,” Experimental Dermatology 31(9), 1311–1329 (2022).

13. L. Franzen, M. Windbergs, “Applications of Raman spectroscopy in skin research − From skin physiology and diagnosis up to risk assessment and dermal drug delivery,” Advanced Drug Delivery Reviews 89, 91–104 (2015).

14. I. A. Bratchenko, L. A. Bratchenko, A. A. Moryatov, Y. A. Khristoforova, D. N. Artemyev, O. O. Myakinin, A. E. Orlov, S. V. Kozlov, and V. P. Zakharov, “In vivo diagnosis of skin cancer with a portable Raman spectroscopic device,” Experimental Dermatology 30(5), 652–663 (2021).

15. C. Delrue, R. Speeckaert, M. Oyaert, S. De Bruyne, and M. M. Speeckaert, “From vibrations to visions: raman spectroscopy’s impact on skin cancer diagnostics,” Journal of Clinical Medicine 12(23), 7428 (2023).

16. V. Mieites, M. G. Fernández-Manteca, I. Santiuste Torcida, F. Madrazo Toca, M. J. Marín Vidalled, and O. M. Conde, “Assessment of blood serum stability with Raman spectroscopy and explanatory AI,” Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 340, 126297 (2025).

17. W. Liu, Z. Sun, J. Chen, and C. Jing, “Raman spectroscopy in colorectal cancer diagnostics: comparison of PCA-LDA and PLS-DA models,” Journal of Spectroscopy 2016, 1–6 (2016).

18. J. Zhao, H. Lui, S. Kalia, T. K. Lee, and H. Zeng, “Improving skin cancer detection by Raman spectroscopy using convolutional neural networks and data augmentation,” Frontiers in Oncology 14, 1320220 (2024).

19. S. Kucheryavskiy, “mdatools – R package for chemometrics,” Chemometrics and Intelligent Laboratory Systems 198, 103937 (2020).

20. L. A. Bratchenko, Y. A. Khristoforova, I. A. Pimenova, E. N. Tupikova, M. A. Skuratova, G. A. Dvoynikov-Sechnoy, S. Wang, P. A. Lebedev, and I. A. Bratchenko, “SERS-based technique for accessible and rapid diagnosis of multiple myeloma in blood serum analysis,” Light: Advanced Manufacturing 6(2), 284–294 (2025).

21. L. A. Bratchenko and I. A. Bratchenko, “Avoiding overestimation and the “black box” problem in biofluids multivariate analysis by raman spectroscopy: interpretation and transparency with the SP-LIME algorithm,” Journal of Raman Spectroscopy 56(4), 353–364 (2025).

22. D. Wu, A. Fedorov Kukk, R. Panzer, S. Emmert, and B. Roth, “In vivo Raman spectroscopic and fluorescence study of suspected melanocytic lesions and surrounding healthy skin,” Journal of Biophotonics 17(8), e202400050 (2024).

23. L. A. Bratchenko, Y. A. Khristoforova, A. A. Moryatov, and I. A. Bratchenko, “Raman spectroscopy based diagnosis of dermatofibrosarcoma protuberans: Case report,” Photodiagnosis and Photodynamic Therapy 35, 102351 (2021).

24. S. Wang, J. Zhao, H. Lui, Q. He, and H. Zeng, “In vivo near-infrared autofluorescence imaging of pigmented skin lesions: methods, technical improvements and preliminary clinical results,” Skin Research and Technology 19(1), 20–26 (2013).

25. S. Kalia, J. Zhao, H. Zeng, D. McLean, N. Kollias, and H. Lui, “Melanin quantification by in vitro and in vivo analysis of near-infrared fluorescence,” Pigment Cell & Melanoma Research 31(1), 31–38 (2018).

26. P. T. Tran, P. Tawornchat, B. Kleuser, S. B. Lohan, J. Schleusener, M. C. Meinke, and M. E. Darvin, “Red- and near-infrared-excited autofluorescence as a marker for acute oxidative stress in skin exposed to cigarette smoke Ex Vivo and In Vivo,” Antioxidants 12(5), 1011 (2023).

27. M. Emanuelli, D. Sartini, E. Molinelli, R. Campagna, V. Pozzi, E. Salvolini, O. Simonetti, A. Campanati, and A. Offidani, “The double-edged sword of oxidative stress in skin damage and melanoma: From physiopathology to therapeutical approaches,” Antioxidants 11(4), 612 (2022).

28. M. Pietruszewska, G. Biesiada, J. Czepiel, M. Birczyńska, P. Moskal, M. Kozicki, E. Hola, A. Garlicki, and A. Wesełucha-Birczyńska, “Lymphocytes studied by Raman microspectroscopy,” Chapter 6 in Lymphocytes, E. S. Istifli, H. B. İla (Eds.), IntechOpen (2019). eBook ISBN: 978-1-83881-749-7.

29. M. Pietruszewska, G. Biesiada, J. Czepiel, M. Birczyńska-Zych, P. Moskal, A. Garlicki, and A. Wesełucha-Birczyńska, “Raman spectroscopy of lymphocytes from patients with the Epstein–Barr virus infection,” Scientific Reports 14(1), 6417 (2024).

30. W. H. Clark, “From the melanocyte to melanoma to tumor biology,” Advances in Cancer Research 65, 113–140 (1194).

31. Z. Huang, H. Lui, X. K. Chen, A. Alajlan, D. I. McLean, and H. Zeng, “Raman spectroscopy of in vivo cutaneous melanin,” Journal of Biomedical Optics 9(6), 1198 (2004).

32. B. R. Uslu, B. Ozdil, E. Tarhan, S. Özçelik, H. Aktuğ, and G. Güler, “Vibrational spectroscopy unveils distinct cell cycle features of cancer stem cells in melanoma,” Scientific Reports 15(1), 28494 (2025).

33. Z. Movasaghi, S. Rehman, and I. U. Rehman, “Raman spectroscopy of biological tissues,” Applied Spectroscopy Reviews 42(5), 493–541 (2007).

34. W. H. Clark, D. E. Elder, and M. Van Horn, “The biologic forms of malignant melanoma,” Human Pathology 17(5), 443–450 (1986).

35. A. A. Marghoob, K. Koenig, F. V. Bittencourt, A. W. Kopf, and R. S. Bart, “Breslow thickness and Clark level in melanoma: Support for including level in pathology reports and in American joint committee on cancer staging,” Cancer 88(3), 589–595 (2000).

36. O. Vița, A. Jurescu, A. Văduva, R. Cornea, M. Cornianu, S. Tăban, D. Szilagyi, C. Micșescu, B. Natarâș, and A. Dema, “Invasive cutaneous melanoma: Evaluating the prognostic significance of some parameters associated with lymph node metastases,” Medicina 59(7), 1241 (2023).

37. M. Prodan, S. Costescu, A. Elagez, S. M. D. Laitin, V. Bloanca, Z. Crainiceanu, E. Seclaman, A.-O. Toma, R. M. Fericean, G. Puenea, and G. V. Cozma, “Molecular markers in melanoma progression: A study on the expression of miRNA gene subtypes in tumoral vs. benign nevi,” Current Oncology 31(5), 2881–2894 (2024).

38. Y. Li, J. M. Krahn, G. P. Flake, D. M. Umbach, and L. Li, “Toward predicting metastatic progression of melanoma based on gene expression data,” Pigment Cell & Melanoma Research 28(4), 453–463 (2015).

39. S. J. Kirkpatrick, R. K. Wang, D. D. Duncan, M. Kulesz-Martin, and K. Lee, “Imaging the mechanical stiffness of skin lesions by in vivo acousto-optical elastography,” Optics Express 14(21), 9770 (2006).




Bookmark and Share


Сontact

34 Moskovskoe shosse, Samara, 443086, Russian Federation
Email: j-bpe@ssau.ru
Phone: +7-846-267-4550
© 2014-2025 J-BPE