Fourier Transform Infrared Spectroscopy: An Innovative Method for the Diagnosis of Ovarian Cancer

Figures & data

Figure 1 Schematic illustration for the FTIR spectroscopy measurement flow. The main procedures include sample preparation, spectral acquisition and data analysis. Pretreatment of the samples depends on the sample type. The sample is then placed on a substrate, such as BaF2 slides, for IR spectroscopy. The representative IR spectrum is presented from an A2780 ovarian cancer cell line. The main absorption bands indicating cellular components are the asymmetric and symmetric vibrations (ν_asym CH₃ and CH₂) of fatty acyl moieties, ester C=O stretching of phospholipids, protein absorption bands (Amide I and Amide II), asymmetric and symmetric phosphodiester vibrations of nucleic acids (ν_asPO₂⁻ and ν_sPO₂⁻), and C–O–C vibrations for sugars. Spectral features were extracted and the data analysis was complex according to the aim of the research. The schematic refers to previous studies.^15–17

Table 1 Diagnosis of Ovarian Cancer Using Tissue Samples Included in the Review

Author	Year	Sample	Preparation	No. of Patients	Method	Spectral Significance
Krishna et al^Citation41	2007	Normal, benign, and malignant ovarian tissues	Paraffin -fixed	24	FTIR and Raman spectroscopy	Normal vs malignant: higher protein content and lower DNA and lipid content
				8 normal, 10 benign, 6 malignant		Benign vs malignant: higher protein content and lower DNA and lipid content
Mehrotra et al^Citation42	2010	Normal and ovarian cancer tissues	Frozen sections	12	FTIR spectroscopy	Malignant vs normal: higher content of DNA and lipids
						Variations in protein secondary structures
Theophilou et al^Citation43	2015	Normal, borderline and malignant ovarian tissues	Paraffin -fixed sections	171	ATR-FTIR spectroscopy	Normal vs malignant: lower lipid/protein ratio, lower phosphate/carbohydrate ratio and higher RNA/DNA ratio
				35 benign, 30 borderline, 106 malignant		Normal vs borderline: lower phosphate/carbohydrate ratio and higher RNA/DNA ratio
						Borderline vs malignant: lower lipid/protein ratio and lower phosphate/carbohydrate ratio
						Normal and benign: similar
Grzelak et al^Citation44	2018	Borderline and malignant ovarian tissues	Frozen sections	8	SR-FTIR spectroscopy	Malignant vs borderline: higher content of proteins, DNA and lipids
				1 borderline, 7 malignant
Li et al^Citation45	2018	Normal and ovarian cancer cells/tissues	Frozen sections	12	FTIR spectroscopy	Malignant vs normal cell lines: higher content of proteins, variations in protein secondary structures Malignant vs normal tissues: lower content of DNA and lipids
				6 cell lines

Table 2 Examples of Applications of FTIR Spectroscopy in Other Areas

Sample	Method	Main Points	Ref.
Cancer
Brain cancer	ATR-FTIR spectroscopy	Using 1 µL serum per person, 3897 spectra from 433 patients, to discriminate cancer vs non-cancer, cancer severity and metastasis with high sensitivity and specificity	[^Citation66]
Lung cancer	Infrared spectral histopathology	Classification of cancer vs non-cancer, cancerous vs necrotic tissue, lung cancer subtypes with high accuracy using FFPE tissue sections	[^Citation67]
Prostate cancer	ATR-FTIR or Raman spectroscopy	Discriminating 156 prostate tissues from different years to indicate a trans-generational phenotypic change	[^Citation68]
Non-cancerous disease
Neurodegenerative disorders	ATR-FTIR spectroscopy	Using blood plasma samples from 347 patients and 202 controls to diagnosis various neurodegenerative diseases with high sensitivity and specificity	[^Citation69]
Nephropathy	FTIR spectroscopy	Prediction of nephropathy using FFPE tissue sections	[^Citation70]
Malaria	ATR-FTIR spectroscopy	Quantification of malaria parasitemia, glucose and urea using whole dried blood samples	[^Citation71]
Osteoarthritis	Near infrared spectroscopy	Distinguishing mild and advanced cartilage degeneration with high sensitivity	[^Citation72]
Microbiology
Scrapie	FTIR spectroscopy	Distinguishing normal and scrapie-infected animals and their clinical stage	[^Citation73]
Enterococci	ATR-FTIR spectroscopy	Phenotypic identification and discrimination of clinically relevant enterococcal species using 60 clinical isolated samples	[^Citation75]
Other areas
Food safety	Near infrared spectroscopy	Food safety surveillance and control	[^Citation77]
Environmental pollution	ATR-FTIR spectroscopy	Detecting levels of organochlorine pesticides in the brain of wild birds	[^Citation78]

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