Diagnosis of malignant pleural mesothelioma from pleural fluid by Fourier transform-infrared spectroscopy coupled with chemometrics

Abstract

of malignant pleural mesothelioma from pleural fluid by Fourier transform-infrared spectroscopy coupled with chemometrics," J.Abstract. This study was conducted to differentiate malignant pleural mesothelioma (MPM) from lung cancer (LC) and benign pleural effusion (BPE) from pleural fluids using the diagnostic power of Fourier transform-infrared spectroscopy with attenuated total reflectance mode coupled with chemometrics. Infrared spectra of MPM (n ¼ 24), LC (n ¼ 20), and BPE (n ¼ 25) were collected, and hierarchical cluster analysis (HCA) and principal component analysis (PCA) were applied to their spectra. HCA results indicated that MPM was differentiated from LC with 100% sensitivity and 100% specificity and from BPE, with 100% sensitivity and 88% specificity, which were also confirmed by PCA score plots. PCA loading plots indicated that these separations originated mainly from lipids, proteins, and nucleic acids-related spectral bands. There was significantly higher lipid, protein, nucleic acid, and glucose contents in the MPM and LC. However, the significant changes in triglyceride and cholesterol ester content, protein and nucleic acid structure, a lower membrane fluidity, and higher membrane order were only observed in the MPM. To check the classification success of some test samples/each group, soft independent modeling of class analogies was performed and 96.2% overall classification success was obtained. This approach can provide a rapid and inexpensive methodology for the efficient differentiation of MPM from other pleural effusions.

Saliva as a first-line diagnostic tool: A spectral challenge for identification of cancer biomarkers

“…1b-d), except in the case of M40TM5 (Fig. 1f) [33][34][35][36][37][38][39]44]. It is consistent with literature and may results from variations in the extent of intermolecular hydrogen bond in α-helical and β-sheet structures [64].…”

“…Table 1 lists the most characteristic ATR-FTIR bands together with suggested band assignments for averaged spectra of control (healthy volunteers) and salivary gland tumor patients. The vibrational analysis was based on the latest literature reports and databases on the application of FTIR spectroscopy in biological studies with particular emphasis on saliva analysis [31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48].…”

“…Briefly, peaks observed at the spectral interval between 3600 and 3000 cm −1 originate from C-H, O-H and N-H stretching modes of proteins, while strong band at~3286 cm −1 is attributed to amide A N-H stretching [33]. Another spectral feature appearing at~3073 cm −1 is due to amide B ν(NH)/ν(CH) vibrations in proteins (αamylase, albumin, cystains, mucins, proline-rich proteins, sIgA) [33][34][35]. On the other hand, the spectral region 3000-2800 cm −1 is rich in bands ascribed to symmetric and asymmetric CH 2 and CH 3 stretching oscillations of lipids [33,[36][37][38].…”

“…Nonetheless, some of bands in the fingerprint region may overlap. This spectral interval is regarded as a highly diagnostic region in studying various cancer types [33,[35][36][37][38][39][40][41][42][43][44][49][50][51][52][53][54][55][56][57]. Band arising at~1078 cm −1 is related to the asymmetric and symmetric PO 2 − stretching from symmetric PO 2 − stretching from inorganic phosphates [58] and phosphate group of phospholipids [48].…”

Activation of Macrophages by CpG DNA and LPS: an FTIR Spectroscopic Study

“…ATR-FTIR spectroscopy has multiple applications in hematology and was used in the analysis of live cell activation [6,7], the screening of numerous diseases [8][9][10][11], the response of cells to chemical stress [12], the identification of disease states in the early stages [13][14][15] and cellular differentiation [16].…”