Optical spectroscopy methods are fast emerging as potential alternatives for early diagnosis of cancer. A Raman spectroscopy method for discrimination of normal and malignant oral tissues has been developed by us earlier. It is necessary to evaluate and establish the validity of the approach before it can be routinely used. In the present study, our Raman spectroscopy investigations are extended further to evaluate the efficacy of the technique to discriminate between normal, inflammatory, premalignant, and malignant conditions in oral tissue. Spectral profiles of normal, malignant, premalignant, and inflammatory conditions show pronounced differences between one another. Spectra of normal tissues can be attributed mainly to lipids whereas pathological tissue spectra are dominated by proteins. Principal components analysis (PCA) of the spectral data sets belonging to the four different categories showed that scores of factors differentiated between
Early diagnosis of oral cancers, one of the major cancers, is of utmost importance as 5-year disease-free survival rates are some of the lowest, despite advances in treatment and surgical modalities. In vivo Raman spectroscopy has shown efficacy in the detection of normal, premalignant and malignant lesions and even of early changes such as cancer-field-effects/malignancy-associated-changes. However, the need for a dedicated instrument and stringent laboratory conditions, at all diagnostic centers, limits wide screening applications of this method. In light of this, it is pertinent to explore ex vivo samples like serum due to its ease of collection, storage, transport and analysis at a centralized facility. Hence, Raman studies were carried out on serum from 14 buccal mucosa and 40 tongue cancers as well as 16 healthy control samples. Spectral features indicate differential contributions of proteins, DNA, and amino acids like Phe, Trp and Tyr and β-carotene in the analyzed groups. Highly intense Raman bands assigned to β-carotene could be due to resonance Raman, and were observed in all sera with the highest relative intensity in normal samples. Higher DNA and protein content were observed in the mean cancer spectra. Principal component-linear discriminant analysis (PC-LDA) followed by cross-validation using leave-one-out cross-validation (LOOCV) were employed for data analysis which was carried out both spectra- and patient-wise. Findings indicate the possibility of classifying normal and oral cancer sera in both these approaches; however, the patient-wise approach could be the preferred mode for prospective studies. Besides, a tendency of classification for buccal mucosa and tongue cancers was also observed. Prospective validation of these results on a large sample size may help in the translation of this methodology to clinics.
The currently prescribed tests for asthma diagnosis require compulsory patient compliance, and are usually not sensitive to mild asthma. Development of an objective test using minimally invasive samples for diagnosing and monitoring of the response of asthma may help better management of the disease. Raman spectroscopy (RS) has previously shown potential in several biomedical applications, including pharmacology and forensics. In this study, we have explored the feasibility of detecting asthma and determining treatment response in asthma patients, through RS of serum. Serum samples from 44 asthma subjects of different grades (mild, moderate, treated severe and untreated severe) and from 15 reference subjects were subjected to Raman spectroscopic analysis and YKL-40 measurements. The force expiratory volume in 1 second (FEV1) values were used as gold standard and the serum YKL-40 levels were used as an additional parameter for diagnosing the different grades of asthma. For spectral acquisition, serum was placed on a calcium fluoride (CaF2) window and spectra were recorded using Raman microprobe. Mean and difference spectra comparisons indicated significant differences between asthma and reference spectra. Differences like changes in protein structure, increase in DNA specific bands and increased glycosaminoglycans-like features were more prominent with increase in asthma severity. Multivariate tools using Principal-component-analysis (PCA) and Principal-component based-linear-discriminant analysis (PC-LDA) followed by Leave-one-out-cross-validation (LOOCV), were employed for data analyses. PCA and PC-LDA results indicate separation of all asthma groups from the reference group, with minor overlap (19.4%) between reference and mild groups. No overlap was observed between the treated severe and untreated severe groups, indicating that patient response to treatment could be determined. Overall promising results were obtained, and a large scale validation study on random subjects is warranted before the routine clinical usage of this technique.
Radiotherapy is the choice of treatment for locally advanced stages of the cervical cancers, one of the leading female cancers. Because of intrinsic factors, tumors of same clinical stage and histological type often exhibit differential radioresponse. Radiotherapy regimen, from first fraction of treatment to clinical evaluation of response, spans more than 4 months. Clinical assessment by degree of tumor shrinkage is the only routinely practiced method to evaluate the tumor response. Hence, a need is created for development new methodologies that can predict the tumor response to radiotherapy at an early stage of the treatment which can lead to tailor-made protocols. To explore the feasibility of prediction of tumor radioresponse, Raman spectra of cervix cancer tissues that were collected before (malignant) and 24 h after patient was treated with 2nd fraction of radiotherapy (RT) were recorded. Data were analyzed by Principal Components Analysis (PCA) and results were correlated with clinical evaluation of radioresponse. Mean Raman spectra of RT tissues corresponding to different levels of tumor response, complete, partial, and no response, showed minute but significant variations. The unsupervised PCA of malignant tissues failed to provide any classification whereas RT spectra gave clear classification between responding (complete and partial response) and nonresponding conditions as well as a tendency of separation among responding conditions. These results were corroborated by supervised classification, by means of discrimination parameters: Mahalanobis distance and spectral residuals. Thus, findings of the study suggest the feasibility of Raman spectroscopic prediction of tumor radioresponse in cervical cancers.
Corona Virus Disease 19 (COVID-19) pandemic has created an alarming situation across the globe. Varieties of diagnostic protocols are being developed for the diagnosis of COVID-19. Many of these diagnostic protocols however, have limitations such as for example unacceptable no of false-positive and false-negative cases, particularly during the early stages of infection. At present, the real-time (quantitative) reverse transcriptase-polymerase chain reaction (RT-PCR) is considered the gold standard for COVID-19 diagnosis. However, RT-PCR based tests are complex, expensive, time consuming and involve pre-processing of samples. A swift, sensitive, inexpensive protocol for mass screening is urgently needed to contain this pandemic. There is urgent need to harness new powerful technologies for accurate detection not only of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) but also combating the emergence of pandemics of new viruses as well. To overcome the current challenges, the authors propose a diagnostic protocol based on surface-enhanced Raman Spectroscopy (SERS) coupled with microfluidic devices containing integrated microchannels functionalized either with vertically aligned Au/Ag coated carbon nanotubes or with disposable electrospun micro/nano-filter membranes. These devices have the potential to successfully trap viruses from diverse biological fluids/secretions including saliva, nasopharyngeal, tear etc. These can thus enrich the viral titre and enable accurate identification of the viruses from their respective Raman signatures. If the device is successfully developed and proven to detect target viruses, it would facilitate rapid screening of symptomatic as well as asymptomatic individuals of COVID-19. This would be a valuable diagnostic tool not only for mass screening of current COVID -19 pandemic but also in viral pandemic outbreaks of future.
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