Vibrational spectroscopic detection of radiation-induced structural changes in Chironomus hemoglobin.

Purpose: Chironomus hemoglobin is known to exhibit higher gamma radiation resistance compared to human hemoglobin. In the present study, we have introduced a sensitive method to analyze radiation-induced alterations in Chironomus hemoglobin using Vibrational spectroscopy and further highlighting its potential for monitoring radiotoxicity in aquatic environments. Materials and methods: Vibrational spectroscopic methods such as Raman and FT-IR spectroscopy were used to capture the distinctive chemical signature of Chironomus hemoglobin (ChHb) under both in vitro and in vivo conditions. Any radiation dose-dependent shifts could be analyzed Human hemoglobin (HuHb) as standard reference. Results: Distinctive Raman peak detected at 930 cm-1 in (ChHb) was attributed to C-N stretching in the heterocyclic ring surrounding the iron atom, preventing heme degradation even after exposure to 2400 Gy dose. In contrast, for (HuHb), the transition from deoxy-hemoglobin to met-hemoglobin at 1210 cm-1 indicated a disruption in oxygen binding after exposure to 1200 Gy dose. Furthermore, while ChHb exhibited a consistent peak at 1652 cm-1 in FT-IR analysis, HuHb on the other hand, suffered damage after gamma irradiation. Conclusion: The findings suggest that vibrational spectroscopic methods hold significant potential as a sensitive tool for detecting radiation-induced molecular alterations and damages. Chironomus hemoglobin, with its robust interaction of the pyrrole ring with Fe, serves as a reliable bioindicator molecule to detect radiation damage using vibrational spectroscopic method.

Distinct spectral signatures unfold ECM stiffness-triggered biochemical changes in breast cancer cells.

Cancer progression often accompanies the stiffening of extracellular matrix (ECM) in and around the tumor, owing to extra deposition and cross-linking of collagen. Stiff ECM has been linked with poor prognosis and is known to fuel invasion and metastasis, notably in breast cancer. However, the underlying biochemical or metabolic changes and the cognate molecular signatures remain elusive. Here, we explored Raman spectroscopy to unveil the spectral fingerprints of breast cancer cells in response to extracellular mechanical cues. Using stiffness-tuneable hydrogels, we showed that cells grown on stiff ECM displayed morphological changes with high proliferation. We further demonstrated that Raman Spectroscopy, a label-free and non-invasive technique, could provide comprehensive information about the biochemical environment of breast cancer cells in response to varying ECM stiffness. Raman spectroscopic analysis classified the cells into distinct clusters based on principal component-based linear discriminant analysis (PC-LDA). Multivariate curve resolution-alternating least squares (MCR-ALS) analysis indicated that cells cultured on stiff ECM exhibited elevated nucleic acid content and lesser lipids. Interestingly, increased intensity of Raman bands corresponding to cytochrome-c was also observed in stiff ECM conditions, suggesting mitochondrial modulation. The key findings harboured by spectral profiles were also corroborated by transmission electron microscopy, confirming altered metabolic status as reflected by increased mitochondria number and decreased lipid droplets in response to ECM stiffening. Collectively, these findings not only give the spectral signatures for mechanoresponse but also provide the landscape of biochemical changes in response to ECM stiffening.

Serum Raman spectroscopy: Evaluation of tumour load variations in experimental carcinogenesis.

Several serum Raman spectroscopy (RS) studies have demonstrated its potential as an oral cancer screening tool. This study investigates influence of low tumour load (LTL) and high tumour load (HTL) on serum RS using hamster buccal pouch model of experimental oral carcinogenesis. Sera of untreated control, LTL, and HTL groups at week intervals during malignant transformation were employed. Serum Raman spectra were subjected to multivariate analyses-principal component analysis, principal component-based linear discriminant analysis (for stratification of study groups), and multivariate curve resolution-alternating least squares (MCR-ALS) (to comprehend biomolecular differences). Multivariate analysis revealed misclassifications between LTL and HTL at all week intervals. MCR-ALS components showed statistically significant abundances between control versus LTL and control versus HTL, but could not discern LTL and HTL. MCR-ALS components exhibited spectral mixtures of proteins, lipids, heme and nucleic acids. Thus, these findings support use of serum RS as a screening tool as varying tumour load is not a confounding factor influencing the technique.

BSA-drug-ZnO-PEI conjugates interaction with glycans of gp60 endothelial cell receptor protein for targeted drug delivery: a comprehensive spectroscopic study.

The zinc oxide (ZnO) nanoparticles (NPs) have several biomedical applications such as drug delivery, bio-imaging, and biomedical research. ZnO NPs were remedied with polyethyleneimine (PEI) and modified with bovine serum albumin (BSA). Two anticancer drugs - Cisplatin (CIS) and Gemcitabine (GEM) were used in conjugation with BSA. BSA-ZnO-PEI (conjugate 1), BSA-CIS-ZnO-PEI (conjugate 2), and BSA-GEM-ZnO-PEI (conjugate 3) can be used for targeted drug delivery via glycans - N-acetylneuraminic acid (NANA), L-fucose (FUC), N-acetyl glucosamine (NAG), D-mannose (MAN), and D-galactose (GAL), of albumin binding membrane receptor protein (gp60). Considerable interaction and the strong binding of conjugate 2 and conjugate 3 with NANA were observed by UV-visible absorption and fluorescence spectra. The electrostatic stability of conjugate 2 and conjugate 3 with NANA was considerably increased in comparison to conjugate 1 as evident with zeta potential values. The fluorescence quenching data (Ksv and kq) and binding parameters (K and n) of BSA-CIS, BSA-GEM, conjugate 2, and conjugate 3 with NANA and FUC attributes to the strong binding. Amide I and amide III bands of the Raman signal suggested insignificant loss in alpha-helical and beta-sheet content of conjugate 2 and conjugate 3 with NANA and FUC. Therefore, the present study is going to assist in the comprehensive development of conjugates for targeted drug delivery based on the differential glycation pattern of gp60 protein.Communicated by Ramaswamy H. Sarma.

ß-Lactoglobulin-gold nanoparticles interface and its interaction with some anticancer drugs - an approach for targeted drug delivery.

The protein-nanoparticle interface plays a crucial role in drug binding and stability, in turn enhancing efficacy in targeted drug delivery. In the present study, whey protein ß-lactoglobulin (BLG) is conjugated with gold nanoparticles (AuNP) and its interaction with curcumin (CUR) and gemcitabine (GEM) has been explored. Further, AuNP-BLG conjugate interactions with anticancer drugs were characterized using dynamic light scattering (DLS), zeta potential, UV-visible, Raman spectroscopy, fluorescence, circular dichroism along with molecular dynamics simulation. The cytotoxicity studies were performed using breast cancer cell lines (MCF-7). ∼8 µM of BLG resides on AuNP (∼29 nm) surface revealed by DLS. Raman scattering of AuNP-BLG conjugate showed orientation of the central calyx of BLG towards solvent. BLG fluorescence confirmed the interaction between AuNP-BLG conjugate with drugs and indicated strong binding and affinity (for CUR KD = 3.71 x 108 M -1, n = 1.83, and for GEM KD = 3.78 x 103 M -1, n = 0.94), enhanced in the presence of AuNP. CD and Raman analysis exhibited selective hydrophilic and hydrophobic conformations induced by drug binding. Computational studies on BLG-drug complexes revealed that the residues Pro38, Leu39 and Met107 are largely associated with CUR binding, while GEM interaction is via hydrophilic contacts which significantly matches with spectroscopic investigation. IC50 values were calculated for all components of this loading system on MCF-7. The possible mechanisms of interaction between AuNP-BLG with anticancer drugs has been explored at the molecular level. We believe that these conjugates could be considered in the targeted drug delivery studies for cancer research.Communicated by Ramaswamy H. Sarma.

Identification of Molecular Basis for Objective Discrimination of Breast Cancer Cells (MCF-7) from Normal Human Mammary Epithelial Cells by Raman Microspectroscopy and Multivariate Curve Resolution Analysis.

Raman spectroscopy (RS), a non-invasive and label-free method, has been suggested to improve accuracy of cytological and even histopathological diagnosis. To our knowledge, this novel technique tends to be employed without concrete knowledge of molecular changes in cells. Therefore, identification of Raman spectral markers for objective diagnosis is necessary for universal adoption of RS. As a model study, we investigated human mammary epithelial cells (HMEpC) and breast cancer cells (MCF-7) by RS and employed various multivariate analyses (MA) including principal components analysis (PCA), linear discriminant analysis (LDA), and support vector machine (SVM) to estimate diagnostic accuracy. Furthermore, to elucidate the underlying molecular changes in cancer cells, we utilized multivariate curve resolution analysis-alternating least squares (MCR-ALS) with non-negative constraints to extract physically meaningful spectra from complex cellular data. Unsupervised PCA and supervised MA, such as LDA and SVM, classified HMEpC and MCF-7 fairly well with high accuracy but without revealing molecular basis. Employing MCR-ALS analysis we identified five pure biomolecular spectra comprising DNA, proteins and three independent unsaturated lipid components. Relative abundance of lipid 1 seems to be strictly regulated between the two groups of cells and could be the basis for excellent discrimination by chemometrics-assisted RS. It was unambiguously assigned to linoleate rich glyceride and therefore serves as a Raman spectral marker for reliable diagnosis. This study successfully identified Raman spectral markers and demonstrated the potential of RS to become an excellent cytodiagnostic tool that can both accurately and objectively discriminates breast cancer from normal cells.

Salivary Raman Spectroscopy: Standardization of Sampling Protocols and Stratification of Healthy and Oral Cancer Subjects.

Minimally invasive cancer detection using bio-fluids has been actively pursued due to practical limitations, though there are better suited noninvasive and online in vivo methods. Saliva is one such clinically informative bio-fluid that offers the advantages of easy and multiple sample collection. Despite its potential in cancer diagnostics, saliva analysis is challenging due to its heterogeneous composition. Recently, there has been an upsurge in saliva exploration using optical techniques. Forms of saliva such as precipitate and supernatant have been monitored, but this sampling method needs to be standardized due to the obvious loss of analytes in processing. In that context, present work details the comparison of four different saliva sampling methodologies, i.e., air-dried, lyophilized, pellet, and supernatant using Raman spectroscopy collected from 10 healthy samples. Composition-driven spectral features of all forms were compared and classified using principal component analysis and linear discriminant analysis. Analysis was carried out on all four groups in the first step. In the second step, groups of pellet and supernatant , and air-dried and lyophilized were analyzed. Findings suggest that pellet and supernatant exhibit discrete spectroscopic features and demonstrate high classification efficiency, which is indicative of their distinctive biochemical composition. On the other hand, air-dried and lyophilized forms showed overlapping spectral features and low classification, suggesting these forms retain majority spectroscopic features of whole saliva and are less prone to sampling losses. Thus, this study indicates air-dried and lyophilized forms may be more appropriate for saliva sampling using Raman spectroscopy providing the comprehensive information required for cancer diagnosis. Furthermore, the method was also tested for the classification of oral cancer and healthy subjects (n = 27) which yielded 90% stratification. The findings of the study indicate the utility of minimally invasive salivary Raman-based diagnostics in oral cancers.

Emerging Advanced Technologies Developed by IPR for Bio Medical Applications ­.A Review.

Over the last decade, research has intensified worldwide on the use of low-temperature plasmas in medicine and healthcare. Researchers have discovered many methods of applying plasmas to living tissues to deactivate pathogens; to end the flow of blood without damaging healthy tissue; to sanitize wounds and accelerate its healing; and to selectively kill malignant cancer cells. This review paper presents the latest development of advanced and plasma-based technologies used for applications in neurology in particular. Institute for Plasma Research (IPR), an aided institute of the Department of Atomic Energy (DAE), has also developed various technologies in some of these areas. One of these is an Atmospheric Pressure Plasma Jet (APPJ). This device is being studied to treat skin diseases, for coagulation of blood at faster rates and its interaction with oral, lung, and brain cancer cells. In certain cases, in-vitro studies have yielded encouraging results and limited in-vivo studies have been initiated. Plasma activated water has been produced in the laboratory for microbial disinfection, with potential applications in the health sector. Recently, plasmonic nanoparticle arrays which allow detection of very low concentrations of chemicals is studied in detail to allow early-stage detection of diseases. IPR has also been developing AI-based software called DeepCXR and AIBacilli for automated, high-speed screening and detection of footprints of tuberculosis (TB) in Chest X-ray images and for recognizing single/multiple TB bacilli in sputum smear test images, respectively. Deep Learning systems are increasingly being used around the world for analyzing electroencephalogram (EEG) signals for emotion recognition, mental workload, and seizure detection.

Hexane Fraction of Turbo brunneus Inhibits Intermediates of RANK-RANKL Signaling Pathway and Prevent Ovariectomy Induced Bone Loss.

Osteoporosis is a "silent disease" characterized by fragile and impaired bone quality. Bone fracture results in increased mortality and poor quality of life in aged people particularly in postmenopausal women. Bone is maintained through the delicate balance between osteoclast-mediated bone resorption and osteoblast-mediated bone formation. The imbalance is caused most often by overly active osteoclasts due to estrogen deficiency. Natural products have long been used to prevent and treat osteoporosis since they have fewer side effects. The marine environment is a potential source of biologically and structurally novel biomolecules with promising biological activities but is less explored for the treatment of bone-related diseases. The present study aims to evaluate the antiosteoporotic effect of Hexane fraction of Turbo brunneus methanolic extract (HxTME) and to investigate its role in RANK-RANKL signaling pathway using in vitro osteoclasts cultures and in vivo ovariectomized (OVX) Swiss mice model. The present study demonstrated that the HxTME significantly inhibited RANKL induced osteoclast differentiation and maturation in vitro. HxTME completely downregulated the mRNA expression of key transcription factors such as NFATc1, c-FOS, and osteoclasts related genes involved in osteoclastogenesis. In vivo studies also depicted the effectiveness of HxTME in ovariectomized mice by preserving bone microarchitecture, mineral content, and inhibiting bone loss in treated mice as analyzed by Histomorphometry, MicroCT, and Raman spectroscopy. Oral administration of HxTME fraction resulted in the decreased percentage of F4/80+, CD11b+, and CD4+ RANKL+ T cells in OVX mice whereas pro-osteoclastic cytokine, IL6 was markedly reduced upon treatment with HxTME. On stimulation with PMA/Io and PHA, a significant decrease in proliferative response in the splenocytes of HxTME treated OVX mice was observed. Fatty acid profiling revealed that HxTME is rich in ω3 and ω6 polyunsaturated fatty acids (PUFAs), which have high nutraceutical properties and are known to play important role in growth, development and maintenance of health. Therefore, HxTME may be a good source of nutraceutical in the treatment of bone-related diseases particularly in postmenopausal osteoporosis and may be pursued as a potential candidate for treatment and management of osteoporosis.

Rapid Discrimination of Malaria- and Dengue-Infected Patients Sera Using Raman Spectroscopy.

Malaria and dengue have overlapping clinical symptoms and are prevalent in the same geographic region (tropical and subtropical), hence precise diagnosis is challenging. The high mortality rate associated with both malaria and dengue could be attributed to "false", "delayed", or "missed" diagnosis. The present study thus aims to stratify malaria and dengue using Raman spectroscopy (RS). In total, 130 human sera were analyzed for model development and double-blinded testing. Principal components linear discriminant analysis (PC-LDA) of acquired RS-spectra could classify malaria and dengue with a minor overlap of 16.7%. Receiver operating characteristic (ROC) analysis of test samples showed sensitivity/specificity of 0.9529 for malaria vs healthy controls (HC) and 0.9584 for dengue vs HC. The Raman findings were complemented by mass spectroscopy (MS)-based metabolite analysis of 8 individuals, each from malaria, dengue, and HC. Several of the metabolites, including amino acids, cell-free DNA, creatinine, and bilirubin, assigned for the predominant RS-bands were also identified by MS and showed similar trends. Our data clearly indicates that RS-based serum analysis using a microprobe has immense potential for early, accurate, and automated detection and discrimination of malaria and dengue, and in the future, it could be extrapolated in field-settings combined with hand-held RS. Further, this approach might be extended to diagnose other closely related infections with similar clinical manifestations.

Optical diagnostics in oral cancer: An update on Raman spectroscopic applications.

Raman spectroscopy (RS) is a sensitive vibrational spectroscopic method that can detect even subtle biochemical changes during the onset of disease. Consequently, RS has been extensively investigated for disease diagnosis, including cancers. Oral cancers are known to suffer from dismal survival rates, which have not improved for several decades. As delayed diagnosis contributes to the low disease-free survival rate observed in oral cancers, RS has also been explored for the early diagnosis of oral cancers. This review summarizes the major developments in the field, including diagnosis, surgical margin assessment and prediction of treatment response, and in the overall management of oral cancers. The article comprises an overview of epidemiology, diagnosis, treatment, and recently introduced diagnostic adjuncts for oral cancers, the basic principle, instrumentation of RS, multivariate analysis that impart objectivity to the approach, and finally a discussion on the recent applications in oral cancers. PubMed and Google Scholar database have been used to compile information available online till December 2015.

Identification of morphological and biochemical changes in keratin-8/18 knock-down cells using Raman spectroscopy.

Accurate understanding of cellular processes and responses to stimuli is of paramount importance in biomedical research and diagnosis. Raman spectroscopy (RS), a label-free and nondestructive spectroscopic method has the potential to serve as a novel 'theranostics' tool. Both fiber-optic and micro-Raman studies have demonstrated efficacy in diagnostics and therapeutic response monitoring. In the present study, we have evaluated the potential of micro-Raman spectroscopic maps in identifying changes induced by loss of K8/18 proteins in a tongue cancer cell line. Furthermore, we also evaluated the efficacy of less expensive and commercially available fiber probes to identify K8/18 wild and knock-down cell pellets, in view of the utility of cell pellet-based studies. The findings suggest that major differences in the cellular morphology and biochemical composition can be objectively identified and can be utilized for classification using both micro-Raman and fiber-probe-based RS. These findings highlight the potential of fiber-optic probe-based RS in noninvasive cellular phenotyping for diagnosis and therapeutic response monitoring, especially in low-resource settings.

A comparative evaluation of diffuse reflectance and Raman spectroscopy in the detection of cervical cancer.

Optical spectroscopic techniques show improved diagnostic accuracy for non-invasive detection of cervical cancers. In this study, sensitivity and specificity of two in vivo modalities, i.e diffuse reflectance spectroscopy (DRS) and Raman spectroscopy (RS), were compared by utilizing spectra recorded from the same sites (67 tumor (T), 22 normal cervix (C), and 57 normal vagina (V)). Data was analysed using principal component - linear discriminant analysis (PC-LDA), and validated using leave-one-out-cross-validation (LOOCV). Sensitivity, specificity, positive predictive value and negative predictive value for classification between normal (N) and tumor (T) sites were 91%, 96%, 95% and 93%, respectively for RS and 85%, 95%, 93% and 88%, respectively for DRS. Even though DRS revealed slightly lower diagnostic accuracies, owing to its lower cost and portability, it was found to be more suited for cervical cancer screening in low resource settings. On the other hand, RS based devices could be ideal for screening patients with centralised facilities in developing countries.

Unique spectral markers discern recurrent Glioblastoma cells from heterogeneous parent population.

An inability to discern resistant cells from bulk tumour cell population contributes to poor prognosis in Glioblastoma. Here, we compared parent and recurrent cells generated from patient derived primary cultures and cell lines to identify their unique molecular hallmarks. Although morphologically similar, parent and recurrent cells from different samples showed variable biological properties like proliferation and radiation resistance. However, total RNA-sequencing revealed transcriptional landscape unique to parent and recurrent populations. These data suggest that global molecular differences but not individual biological phenotype could differentiate parent and recurrent cells. We demonstrate that Raman Spectroscopy a label-free, non-invasive technique, yields global information about biochemical milieu of recurrent and parent cells thus, classifying them into distinct clusters based on Principal-Component-Analysis and Principal-Component-Linear-Discriminant-Analysis. Additionally, higher lipid related spectral peaks were observed in recurrent population. Importantly, Raman spectroscopic analysis could further classify an independent set of naïve primary glioblastoma tumour tissues into non-responder and responder groups. Interestingly, spectral features from the non-responder patient samples show a considerable overlap with the in-vitro generated recurrent cells suggesting their similar biological behaviour. This feasibility study necessitates analysis of a larger cohort of naïve primary glioblastoma samples to fully envisage clinical utility of Raman spectroscopy in predicting therapeutic response.

Raman Spectroscopy of Experimental Oral Carcinogenesis: Study on Sequential Cancer Progression in Hamster Buccal Pouch Model.

Oral cancers suffer from poor 5-year survival rates, owing to late detection of the disease. Current diagnostic/screening tools need to be upgraded in view of disadvantages like invasiveness, tedious sample preparation, long output times, and interobserver variances. Raman spectroscopy has been shown to identify many disease conditions, including oral cancers, from healthy conditions. Further studies in exploring sequential changes in oral carcinogenesis are warranted. In this Raman spectroscopy study, sequential progression in experimental oral carcinogenesis in Hamster buccal pouch model was investigated using 3 approaches-ex vivo, in vivo sequential, and in vivo follow-up. In all these studies, spectral changes show lipid dominance in early stages while later stages and tumors showed increased protein to lipid ratio and nucleic acids. On similar lines, early weeks of 7,12-dimethylbenz(a)anthracene-treated and control groups showed higher overlap and low classification. The classification efficiency increased progressively, reached a plateau phase and subsequently increased up to 100% by 14 weeks. The misclassifications between treated and control spectra suggested some changes in controls as well, which was confirmed by a careful reexamination of histopathological slides. These findings suggests Raman spectroscopy may be able to identify microheterogeneity, which may often go unnoticed in conventional biochemistry wherein tissue extracts are employed, as well as in histopathology. In vivo findings, quite comparable to gold-standard supported ex vivo findings, give further proof of Raman spectroscopy being a promising label-free, noninvasive diagnostic adjunct for future clinical applications.

Raman spectroscopy in cervical cancers: an update.

Cervical cancer is the third most common cancer among women worldwide. Developing countries contribute more than 80% towards global burden. Over the last 2 decades, Raman spectroscopy (RS) has been actively pursued for cervical cancer detection. In view of latest development in Raman spectroscopic applications in cervical cancers, especially in vivo studies, an update of the same is presented in this article. This articles opens with a brief note on Anatomy of cervix followed by Etiology, and conventional Screening and Diagnosis of Cervical cancers. In subsequent sections, brief description of Theory and Instrumentation of RS is followed by a review of recent developments in cervical cancer detection; with emphasis on cell lines, exfoliated cells, ex vivo and in vivo, and therapeutic response monitoring applications in cervical cancer.

Recurrence prediction in oral cancers: a serum Raman spectroscopy study.

High mortality rates associated with oral cancers can be primarily attributed to the failure of current histological procedures in predicting recurrence. Identifying recurrence related factors can lead to improved prognosis, optimized treatment and enhanced overall outcomes. Serum Raman spectroscopy has previously shown potential in the diagnosis of cancers, such as head and neck, cervix, breast, oral cancers, and also in predicting treatment response. In the present study, serum was collected from 22 oral cancer subjects [with recurrence (n = 10) and no-recurrence (n = 12)] before and after surgery and spectra were acquired using a Raman microprobe coupled with a 40× objective. Spectral acquisition parameters were as follows: λex = 785 nm, laser power = 30 mW, integration time: 12 s and averages: 3. Data was analyzed in a patient-wise approach using unsupervised PCA and supervised PC-LDA, followed by LOOCV. PCA and PC-LDA findings suggest that recurrent and non-recurrent cases cannot be classified in before surgery serum samples; an average classification efficiency of ∼78% was obtained in after-surgery samples. Mean and difference spectra and PCA loadings indicate that DNA and protein markers may be potential spectral markers for recurrence. RS of post surgery serum samples may have the potential to predict the probability of recurrence in clinics, after prospective large-scale validation.

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

Risk of recurrence is a major problem in breast cancer management. Currently available prognostic markers have several disadvantages including low sensitivity and specificity, highlighting the need for new prognostic techniques. One of the candidate techniques is serum-based Raman spectroscopy (RS). In this study, feasibility of using RS to distinguish 'pre' from 'post' breast tumor resection serum in rats was explored. Spectral analysis suggests change in proteins and amino acid profiles in 'post' compared to 'pre-surgical' group. Principal-Component-Linear-Discriminant-Analysis shows 87% and 91% classification efficiency for 'pre' and 'post-surgical' groups respectively. Thus, the study further supports efficacy of RS for theranostic applications.

A preliminary Raman spectroscopic study of urine: diagnosis of breast cancer in animal models.

Prognosis of breast cancer, the most common cancer in females worldwide, has been shown to improve with early detection. Owing to disadvantages like low sensitivity, specificity, tedious sample preparation, long output times and inter-observer variance of currently available screening/diagnostic tools, rapid and objective alternatives such as Raman spectroscopy (RS) are being extensively explored. Body fluid (serum and saliva) based RS assays have shown promising results in diagnosis of oral, lung and nasopharyngeal cancers. The current study aims to explore the feasibility of breast cancer diagnosis using urine based RS. In this study, spectra were acquired from unprocessed as well as concentrated urine of controls (C) and breast tumor bearing (T) rats and analyzed using Principal Component Analysis (PCA) and Principal Component-Linear Discriminant Analysis (PC-LDA). Classification efficiencies of 80% and 72% using unprocessed urine and 78% and 91% using concentrated urine for C and T rats were achieved. Thus, results suggest the possibility of breast cancer diagnosis using urine based RS. Further, spectra were also acquired from concentrated urine samples collected prior to breast tumor development (TT) in rats and from rats that did not develop tumors despite carcinogen treatment (NTT). Concentrated urine of NTT rats could be classified as 'normal' (C or NTT) with ∼83% efficiency whereas concentrated urine from visibly and palpably normal rats that eventually developed tumor (TT rats) could be classified as 'abnormal' (TT or T) with ∼72.5% efficiency using PC-LDA. These results suggest the possibility of detecting biochemical changes occurring prior to tumor development using urine based RS.