Chemometric analysis of integrated FTIR and Raman spectra obtained by non-invasive exfoliative cytology for the screening of oral cancer

Ghosh, Aritri; Raha, Sreyan; Dey, Susmita; Chatterjee, Kabita; Chowdhury, Amit Roy; Barui, Ananya

doi:10.1039/c8an02092b

Cited by 43 publications

(34 citation statements)

References 71 publications

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“…A multivariate statistics algorithm with PCA-LDA analysis was used to analyze the identity between the control group and the three drugs treated groups. This algorithm is widely used in biomedical applications as a powerful spectral analysis method [45][46][47]. The normalized data of the whole Raman spectra was input into the SPSS software for factor analysis.…”

Section: Discussionmentioning

confidence: 99%

Study on the chemodrug-induced effect in nasopharyngeal carcinoma cells using laser tweezer Raman spectroscopy

Qiu¹,

Li²,

Li³

et al. 2020

Biomed. Opt. Express

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To explore the effect in nasopharyngeal carcinoma (NPC) cells after treatment with chemodrugs, Raman profiles were characterized by laser tweezer Raman spectroscopy. Two NPC cell lines (CNE2 and C666-1) were treated with gemcitabine, cisplatin, and paclitaxel, respectively. The high-quality Raman spectra of cells without or with treatments were recorded at the single-cell level with label-free laser tweezers Raman spectroscopy (LTRS) and analyzed for the differences of alterations of Raman profiles. Tentative assignments of Raman peaks indicated that the cellular specific biomolecular changes associated with drug treatment include changes in protein structure (e.g. 1655 cm −1), changes in DNA/RNA content and structure (e.g. 830 cm −1), destruction of DNA/RNA base pairs (e.g. 785 cm −1), and reduction in lipids (e.g. 970 cm −1). Besides, both principal components analysis (PCA) combined with linear discriminant analysis (LDA) and the classification and regression trees (CRT) algorithms were employed to further analyze and classify the spectral data between control group and treated group, with the best discriminant accuracy of 96.7% and 90.0% for CNE2 and C666-1 group treated with paclitaxel, respectively. This exploratory work demonstrated that LTRS technology combined with multivariate statistical analysis has promising potential to be a novel analytical strategy at the single-cell level for the evaluation of NPC-related chemotherapeutic drugs.

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Section: Discussionmentioning

confidence: 99%

Study on the chemodrug-induced effect in nasopharyngeal carcinoma cells using laser tweezer Raman spectroscopy

Qiu¹,

Li²,

Li³

et al. 2020

Biomed. Opt. Express

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“…This is the first time; breast cancer biopsy data was explored using AI and ML approaches based on subtype classification. AI approach studies have identified malignant tissues from normal and benign in various cancers such as lung cancer [54,60], skin cancer [61,62], brain cancer [18,63], gastro intestinal cancer [64,65], and oral cancer [66].…”

Section: Discussionmentioning

confidence: 99%

Advancing cancer diagnostics with artificial intelligence and spectroscopy: identifying chemical changes associated with breast cancer

Talari

Rehman

2019

Expert Review of Molecular Diagnostics

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Background: Artificial intelligence (AI) and machine learning (ML) approaches in combination with Raman spectroscopy (RS) to obtain accurate medical diagnosis and decision-making is a way forward for understanding not only the chemical pathway to the progression of disease, but also for tailor-made personalized medicine. These processes remove unwanted affects in the spectra such as noise, fluorescence and normalization, and help in the optimization of spectral data by employing chemometrics. Methods: In this study, breast cancer tissues have been analyzed by RS in conjunction with principal component (PCA) and linear discriminate (LDA) analyses. Tissue microarray (TMA) breast biopsies were investigated using RS and chemometric methods and classified breast biopsies into luminal A, luminal B, HER2, and triple negative subtypes. Results: Supervised and unsupervised algorithms were applied on biopsy data to explore intra and inter data set biochemical changes associated with lipids, collagen, and nucleic acid content. LDA predicted specificity accuracy of luminal A, luminal B, HER2, and triple negative subtypes were 70%, 100%, 90%, and 96.7%, respectively. Conclusion: It is envisaged that a combination of RS with AI and ML may create a precise and accurate real-time methodology for cancer diagnosis and monitoring. ARTICLE HISTORY

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“…A step-wise increase in the MN index was observed from the control population to the pre-cancer patients to the cancer patients by 1.14 to 2.63 to 4.88, respectively [ 106 ]. In a recent study by Ghosh et al, Raman and FTIR data of exfoliated cells were used to distinguish the stages of oral cancer [ 107 ]. Few other spectroscopic methods used to detect the oral malignancy are elastic scattering spectroscopy [ 25 ], diffuse reflectance spectroscopy [ 22 ], and optical coherence tomography [ 44 ].…”

Section: Techniques Used For Diagnosis Of Oral Cancermentioning

confidence: 99%

Oral cancer diagnosis and perspectives in India

Borse

Konwar

Buragohain

2020

Sensors International

227

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Globally, oral cancer is the sixth most common type of cancer with India contributing to almost one-third of the total burden and the second country having the highest number of oral cancer cases. Oral squamous cell carcinoma (OSCC) dominates all the oral cancer cases with potentially malignant disorders, which is also recognized as a detectable pre-clinical phase of oral cancer. Tobacco consumption including smokeless tobacco, betel-quid chewing, excessive alcohol consumption, unhygienic oral condition, and sustained viral infections that include the human papillomavirus are some of the risk aspects for the incidence of oral cancer. Lack of knowledge, variations in exposure to the environment, and behavioral risk factors indicate a wide variation in the global incidence and increases the mortality rate. This review describes various risk factors related to the occurrence of oral cancer, the statistics of the distribution of oral cancer in India by various virtues, and the socio-economic positions. The various conventional diagnostic techniques used routinely for detection of the oral cancer are discussed along with advanced techniques. This review also focusses on the novel techniques developed by Indian researchers that have huge potential for application in oral cancer diagnosis.

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Chemometric analysis of integrated FTIR and Raman spectra obtained by non-invasive exfoliative cytology for the screening of oral cancer

Abstract: FTIR spectroscopy and Raman spectroscopy of biological analytes are increasingly explored as screening tools for early detection of cancer.

Cited by 43 publications

References 71 publications

Study on the chemodrug-induced effect in nasopharyngeal carcinoma cells using laser tweezer Raman spectroscopy

Study on the chemodrug-induced effect in nasopharyngeal carcinoma cells using laser tweezer Raman spectroscopy

Advancing cancer diagnostics with artificial intelligence and spectroscopy: identifying chemical changes associated with breast cancer

Oral cancer diagnosis and perspectives in India

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