New Spectroscopy Techniques Offer Hope in Identifying Platinum-Resistant Ovarian Cancer
A recent study looks at using Fourier transform infrared (FT-IR) spectroscopy to distinguish between platinum-resistant and platinum-sensitive ovarian cancer tissues.
When coupled with machine learning, advanced spectroscopic techniques such as Fourier transform infrared (FT-IR) spectroscopy and FT-Raman spectroscopy can distinguish between platinum-resistant and platinum-sensitive ovarian cancer tissues, according to a recent study published in Scientific Reports (1).
Detecting and distinguishing cancer tissues are important in helping improve patient outcomes. Over the years, scientists have explored this issue at length (2–4). Ovarian cancer, in particular, is exceptionally lethal and has a high recurrence rate for women diagnosed with this disease (2). Earlier studies have indicated that FT-IR spectroscopy can be an effective technique on this front because it is noninvasive, convenient, and simple (2,3). FT-IR spectroscopy can unveil the spectral features that reveal molecular characteristics about the ovarian cancer cells, showing that it can distinguish between cancerous and non-cancerous cells (3).
3d illustration of ovarian cancer | Image Credit: © Lars Neumann - stock.adobe.com
The lethality of ovarian cancer is compounded by its resistance to platinum-based chemotherapy. As a result, platinum-resistant ovarian cancer significantly reduces the chances of successful treatment and complete recovery (1). Until now, clinicians have lacked effective methods to determine whether a patient's ovarian cancer is platinum-resistant, making it difficult to tailor treatment plans accordingly (1).
Researchers from Fryderyk Chopin University Hospital in Poland, led by Marta Kluz-Barłowska and Joanna Depciuch, explored this challenge in treating ovarian cancer by improving on traditional histopathology, which has fallen short because of its inability to determine differences between platinum-resistant and platinum-sensitive ovarian cancer tissues (1). In their study, Kluz-Barłowska and Depciuch employed FT-IR and FT-Raman spectroscopy to delve into the chemical composition of ovarian cancer tissues. These techniques are known for their ability to provide detailed molecular fingerprints of biological samples, making them ideal for this type of analysis (1).
The researchers collected ovarian cancer tissue samples and analyzed them using FT-IR and FT-Raman spectroscopy. They aimed to identify chemical differences that could serve as markers for platinum resistance (1). The study results revealed higher amounts of phospholipids, proteins, and lipids in platinum-resistant tissues. These findings were supported by principal component analysis (PCA), which showed that the first principal component (PC1) could effectively differentiate between the two types of tissues (1).
The researchers, however, took their study further by using machine algorithms. Using these algorithms allowed for near-perfect accuracy between platinum-resistant and platinum-sensitive tissues when they were combined with FT-IR spectroscopy and FT-Raman spectroscopy (1). For FT-IR spectroscopy, the values approached 100%, whereas for FT-Raman spectroscopy the values hovered around 95% (1).
Another outcome of this study was that the researchers can identify specific peaks in the spectroscopic data that could serve as markers for platinum resistance (1). Using decision tree analysis, the researchers pinpointed spectral peaks at 1777 cm−1 and 2974 cm−1 in FT-IR spectroscopy, and at 1714 cm−1 and 2817 cm−1 in FT-Raman spectroscopy, as potential indicators of platinum-resistant ovarian cancer (1).
By providing a reliable method to distinguish between platinum-resistant and platinum-sensitive ovarian cancer tissues, clinicians could tailor treatments more effectively, potentially improving outcomes for patients. Furthermore, the study highlights the power of combining advanced spectroscopy techniques with machine learning to tackle complex medical challenges (1).
As researchers continue to explore and refine these techniques, the hope is that similar methodologies can be developed for other types of cancer and drug resistance scenarios. By providing a method to identify platinum-resistant cancer tissues with high accuracy, it paves the way for more effective and personalized treatments, bringing us closer to the ultimate goal of conquering this devastating disease (1).
References
(1) Kluz-Barłowska, M.; Kluz, T.; Paja, W.; et al. FT-Raman and FTIR Spectroscopy as a Tools Showing Marker of Platinum-resistant Phenomena in Women Suffering From Ovarian Cancer. Sci. Rep. 2024, 14, 11025. DOI: 10.1038/s41598-024-61775-z
(2) Li, L.; Wu, J.; Yang, H.; et al. Fourier Transform Infrared Spectroscopy: An Innovative Method for the Diagnosis of Ovarian Cancer. Cancer Manag. Res. 2021, 13, 2389–2399. DOI: 10.2147/CMAR.S291906
(3) Li, L.; Bi, X.; Sun, H.; et al. Characterization of Ovarian Cancer Cells and Tissues by Fourier Transform Infrared Spectroscopy. J. Ovarian Res. 2018, 11, 64. DOI: 10.1186/s13048-018-0434-8
(4) Moothanchery, M.; Perumal, J.; Mahyuddin, A. P.; et al. Rapid and Sensitive Detection of Ovarian Cancer Biomarker Using a Portable Single Peak Raman Detection Method. Sci. Rep. 2022, 12, 12459. DOI: 10.1038/s41598-022-13859-x
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