Raman spectroscopy of serum: A study on 'pre' and 'post' breast adenocarcinoma resection in rat models

Serum Raman spectroscopy: Prognostic applications in oral cancers

BACKGROUND

Loco-regional recurrences attributable to field cancerization and minimal residual cancer, remain prime causes of mortality in oral cancer (OC) subjects. The current study evaluates potential of serum Raman spectroscopy (SRS) to identify recurrence-prone OC subjects.

METHODS

Raman spectra of serum from eight healthy subjects (H) and 57 OC subjects (with-recurrence [R], without-recurrence [NR], and with suspicious-lesions [S]), before (BS) and after (AS) surgical excision of tumor were recorded. OC subjects were followed-up for 7-years.

RESULTS

DNA and protein alterations were observed in AS sera of all groups. 4-, 3-, and 2-model multivariate analyses were used to stratify BS and AS groups. H spectra were 100% distinguishable from all other groups. AS, R and NR were distinguished with high accuracy (84%) in all models. No stratification (~50%) was observed BS.

CONCLUSION

SRS shows potential to identify recurrence prone subjects, post-surgery, using serum collected as early as 1 week after surgery.

SERS-based differential diagnosis between multiple solid malignancies: breast, colorectal, lung, ovarian and oral cancer

Purpose

Surface-enhanced Raman scattering (SERS) spectroscopy on serum and other biofluids for cancer diagnosis represents an emerging field, which has shown promising preliminary results in several types of malignancies. The purpose of this study was to demonstrate that SERS spectroscopy on serum can be employed for the differential diagnosis between five of the leading malignancies, ie, breast, colorectal, lung, ovarian and oral cancer.

Patients and methods

Serum samples were acquired from healthy volunteers (n=39) and from patients diagnosed with breast (n=42), colorectal (n=109), lung (n=33), oral (n=17), and ovarian cancer (n=13), comprising n=253 samples in total. SERS spectra were acquired using a 532 nm laser line as excitation source, while the SERS substrates were represented by Ag nanoparticles synthesized by reduction with hydroxylamine. The classification accuracy yielded by SERS was assessed by principal component analysis–linear discriminant analysis (PCA-LDA).

Results

The sensitivity and specificity in discriminating between cancer patients and controls was 98% and 91%, respectively. Cancer samples were correctly assigned to their corresponding cancer types with an accuracy of 88% for oral cancer, 86% for colorectal cancer, 80% for ovarian cancer, 76% for breast cancer and 59% for lung cancer.

Conclusion

SERS on serum represents a promising strategy of diagnosing cancer which can discriminate between cancer patients and controls, as well as between cancer types such as breast, colorectal, lung ovarian and oral cancer.

An early investigative serum Raman spectroscopy study of meningioma

Meningiomas represent one of the most frequently reported non-glial, primary brain and central nervous system (CNS) tumors. Meningiomas often display a spectrum of anomalous locations and morphological attributes, deterring their timely diagnosis. Majority of them are sporadic in nature and thus the present-day screening strategies, including radiological investigations, often result in misdiagnosis due to their aberrant and equivocal radiological facets. Therefore, it is pertinent to explore less invasive and patient-friendly biofluids such as serum for their screening and diagnostics. The utility of serum Raman spectroscopy in diagnosis and therapeutic monitoring of cancers has been reported in the literature. In the present study, for the first time, to the best of our knowledge, we have explored Raman spectroscopy to classify the sera of meningioma and control subjects. For this exploration, 35 samples each of meningioma and control subjects were accrued and the spectra revealed variance in the levels of DNA, proteins, lipids, amino acids and β-carotene, i.e., a relatively higher protein, DNA and lipid content in meningioma. Subsequent Principal Component Analysis (PCA) and Principal Component-Linear Discriminant Analysis (PC-LDA) followed by Leave-One-Out Cross-Validation (LOOCV) and limited independent test data, in a patient-wise approach, yielded a classification efficiency of 92% and 80% for healthy and meningioma, respectively. Additionally, in the analogous analysis between healthy and different grades of meningioma, similar results were obtained. These results indicate the potential of Raman spectroscopy in differentiating meningioma. As present methods suffer from known limitations, with the prospective validation on a larger cohort, serum Raman spectroscopy could be an adjuvant/alternative approach in the clinical management of meningioma.

Raman spectroscopy based differentiation of typhoid and dengue fever in infected human sera

This study investigated the potential of Raman spectroscopy, to differentiate between two different types of human pathological conditions with some symptom similarity; typhoid and dengue. Raman spectra were recorded from 20 Salmonella Typhi infected and 22 dengue virus (DENV) infected sera samples using laser wavelength 785 nm. When Raman spectrum (540 to 1830 cm^-1) of serum samples was compared it showed significant variations. Twelve characteristic Raman bands at 562, 649, 716, 780, 838, 1099, 1144, 1156, 1260, 1386, 1556 and 1746 cm^-1 were recorded specifically in case of the typhoid infected samples, whereas four Raman bands at 756, 1218, 1672 and 1686 cm^-1 were found specifically in the DENV infected samples. For statistical differentiation principal component analysis (PCA) and linear discriminant analysis (LDA) was applied which successfully separated two sets of data. These disease specific Raman signatures may be labeled as biomarkers for identification as well as differential diagnosis of typhoid and dengue infection. Hence we propose that Raman spectroscopy has the potential to not only identify but also to differentiate between different pathological conditions, having some similar symptoms like high grade fever in this case.

Non-invasive and label-free detection of oral squamous cell carcinoma using saliva surface-enhanced Raman spectroscopy and multivariate analysis

Reported here is the application of silver nanoparticle-based surface-enhanced Raman spectroscopy (SERS) as a label-free, non-invasive technique for detection of oral squamous cell cancer (OSCC) using saliva and desquamated oral cells. A total of 180 SERS spectra were acquired from saliva and 120 SERS spectra from oral cells collected from normal healthy individuals and from confirmed oropharyngeal cancer patients. Notable biochemical peaks in the SERS spectra were tentatively assigned to various components. Data were subjected to multivariate statistical techniques including principal component analysis, linear discriminate analysis (PCA-LDA) and logistic regression (LR) revealing a sensitivity of 89% and 68% and a diagnostic accuracy of 73% and 60% for saliva and oral cells, respectively. The results from this study demonstrate the potential of saliva and oral cell SERS combined with PCA-LDA or PCA-LR diagnostic algorithms as a promising clinical adjunct for the non-invasive detection of oral cancer.