Raman and FTIR spectroscopy in determining the chemical changes in healthy brain tissues and glioblastoma tumor tissues.

Glioblastoma, also called glioblastoma multiforme (GBM), is a particularly malignant form of primary brain tumor. This cancer accounts for 12-15% of all brain tumors. Despite the advances in neurosurgery, radio and chemotherapy the average survival rate is only 12.1-16.6 months. This is due not only to the late diagnosis of the disease, but also to ineffective treatment methods which result from the still low knowledge about the causes of glioblastoma development. Therefore, it is very important to look for new diagnostic methods of detection of the smallest features of cancer. Raman and infrared spectroscopy (FTIR) can be such methods. In this paper we discuss the chemical composition of sample glioblastoma brain tissues and marginal brain tissues using these two spectroscopy methods. Raman and FTIR spectra of cancer brain tissues showed that the highest differences in the chemical composition, compared to the control brain tissue, occur in the areas corresponding to lipids, collagen and proteins. Moreover, Raman spectroscopy also showed significant changes in the cancer tissues in the phosphatidylcholine and sphingomyelin. Interestingly, FTIR spectra after Kramers-Kronig transformations showed signals only for three peaks which corresponded to the vibrations of lipid function groups. Adjustment of the Lorenz function for these three peaks showed that only in the case of cancerous tissues the number of matching lines is different, compared to the control and marginal tissues. Therefore, we assume that lipids could be a spectroscopic marker for brain tumor. Furthermore, principal component analysis (PCA) showed that chemical changes seen between cancer and control tissues are significant and it is possible to differentiate the infected tissue from the healthy one. Interestingly, the PCA analysis also showed that adjacent brain tissues have different chemical composition than the control tissues.

Monitoring breast cancer treatment using a Fourier transform infrared spectroscopy-based computational model.

Breast cancer affects one in four women, therefore, the search for new diagnostic technologies and therapeutic approaches is of critical importance. This involves the development of diagnostic tools to facilitate the detection of cancer cells, which is useful for assessing the efficacy of cancer therapies. One of the major challenges for chemotherapy is the lack of tools to monitor efficacy during the course of treatment. Vibrational spectroscopy appears to be a promising tool for such a purpose, as it yields Fourier transformation infrared (FTIR) spectra which can be used to provide information on the chemical composition of the tissue. Previous research by our group has demonstrated significant differences between the infrared spectra of healthy, cancerous and post-chemotherapy breast tissue. Furthermore, the results obtained for three extreme patient cases revealed that the infrared spectra of post-chemotherapy breast tissue closely resembles that of healthy breast tissue when chemotherapy is effective (i.e., a good therapeutic response is achieved), or that of cancerous breast tissue when chemotherapy is ineffective. In the current study, we compared the infrared spectra of healthy, cancerous and post-chemotherapy breast tissue. Characteristic parameters were designated for the obtained spectra, spreading the function of absorbance using the Kramers-Kronig transformation and the best fit procedure to obtain Lorentz functions, which represent components of the bands. The Lorentz function parameters were used to develop a physics-based computational model to verify the efficacy of a given chemotherapy protocol in a given case. The results obtained using this model reflected the actual patient data retrieved from medical records (health improvement or no improvement). Therefore, we propose this model as a useful tool for monitoring the efficacy of chemotherapy in patients with breast cancer.

Use of FTIR spectroscopy and PCA-LDC analysis to identify cancerous lesions within the human colon.

Colorectal cancer constitutes 33% of all cancer morbidity, so the research of the new methods for colorectal cancer diagnosis and chemotherapy monitoring is gaining its momentum. Diagnostic instruments are being sought, which enable the detection of single malignant cells based on the analysis of tissue material potentially reusable at further stages of diagnostic management. The most common approach to tissue specimen processing is paraffin-embedding. Yet, paraffin may cause background noise in spectroscopic measurements with the wavenumber ranging between 900cm-1 and 3500cm-1. However, the study by Depciuch et al. (2016) proved that appropriate specimen processing and paraffin-embedding technique as well as a strict measurement methodology may eliminate paraffin vibrations. As a result, spectroscopic measurements may become a reliable and precise method for the diagnosis and treatment monitoring in patients with colorectal cancer as long as the high standards of specimen processing are maintained. Chemotherapy is the main medical treatment in colorectal cancer. Unfortunately, the absence of tools which enable monitoring its efficacy leads to the partial response or non-response frequently seen in affected patients. Hence, diagnostic instruments are also being sought capable of monitoring treatment efficacy so as to enable early changes of chemotherapy regimen thus increasing the chance of cure. The paper aims at comparing the results of FTIR (Fourier Transform Infrared) spectroscopy in several types of colon tissue: healthy colon, cancerous colon, post-chemotherapy colon and healthy surgical margin of colon cancer sample. The obtained FTIR spectra along with the Principal Component Analysis-Linear Discriminant Analysis (PCA-LDC) as well as bandwidth analysis of the primary amide region revealed some differences between the spectra of healthy tissues as compared to cancerous tissues (pre- or post-chemotherapy). Apart from confirming that FTIR spectroscopy is a good source of information on the composition of analysed samples, this fact supports its application as a tool to facilitate understanding the pathophysiology of various conditions and to monitor efficacy of chemotherapy in cancer patients.