Biology subjects

Rajaram, N.

Publications and source records attributed to Rajaram, N..

3 recordsLinked to original sources

bioRxiv2024

Optical imaging of treatment-naive human NSCLC reveals changes associated with metastatic recurrence

Lung cancer remains the leading cause of cancer deaths, comprising nearly 25% of all cancer deaths [1]. NSCLC accounts for approximately 85% of all cases and encompasses major subtypes such as adenocarcinoma and squamous cell carcinoma. Despite advances in surgical and therapeutic options, NSCLC remains associated with poor prognosis due to a high rate of recurrence, even in early stages. Around 30-55% of patients who undergo complete resection will experience metastatic recurrence, significantly lowering survival outcomes [2]. There is a critical need to develop prognostic markers capable of predicting risk of recurrence at earlier timepoints in order to improve NSCLC management, as it could help clinicians tailor treatment plans, optimize follow-up schedules, and identify high-risk patients who might benefit from adjuvant therapies. Two photon microscopy (TPM) techniques provide non-invasive high-resolution information on cell metabolism within tissue by utilizing an optical redox ratio (ORR) of FAD/[NADH+FAD] autofluorescence. The goal of this study is to use the ORR and NADH fluorescence lifetime decay to identify measurable differences in optical endpoints of human NSCLC that are indicative of their long-term outcome. Twenty-five treatment-naive NSCLC specimens were classified into metastatic and non-metastatic groups according to subject-detail reports. The ORR and mean NADH lifetime were determined for each sample, revealing a significant increase in the ORR for the metastatic group. Additionally, tumors presenting with high optical redox ratios were found to be correlated with low KEAP1, a prognostic indicator of poor clinical outcome in NSCLC. To evaluate the prognostic potential of optical metabolic endpoints, we trained three classifiers: logistic regression, SVM, and KNN on three different feature sets: optical endpoints, clinicopathological features, and combination of optical and clinical features. We found that SVM trained on optical endpoints alone (AUC = 0.74) outperformed the model built with only clinical features (AUC = 0.62), when classifying tumors based on their metastatic recurrence status. Together, these findings highlight the potential of optical metabolic imaging to provide markers of recurrence in NSCLC.

cancer biology↗

bioRxiv2021

Raman spectroscopy reveals phenotype switches in breast cancer metastasis

The accurate analytical characterization of metastatic phenotype at primary tumor diagnosis and its evolution with time are critical for controlling metastatic progression of cancer. Here, we report a label-free optical strategy using Raman spectroscopy and machine learning to identify distinct metastatic phenotypes observed in tumors formed by isogenic murine breast cancer cell lines of progressively increasing metastatic propensities. Our Raman spectra-based random forest analysis provided evidence that machine learning models built on spectral data can allow the accurate identification of metastatic phenotype of independent test tumors. By silencing genes critical for metastasis in highly metastatic cell lines, we showed that the random forest classifiers provided predictions consistent with the observed phenotypic switch of the resultant tumors towards lower metastatic potential. Furthermore, the spectral assessment of lipid and collagen content of these tumors was consistent with the observed phenotypic switch. Overall, our findings indicate that Raman spectroscopy may offer a novel strategy to evaluate metastatic risk during primary tumor biopsies in clinical patients.

bioengineering↗

bioRxiv2019

Diffuse Reflectance Spectroscopy reveals heat stress-induced changes in hemoglobin profile in chicken breast

Global rise in incidence of woody breast (WB) syndrome imposes a significant economic burden on the poultry industry. The increase in WB is due to the large increase in the weight of chickens these days within a very short period. An early determination of WB can significantly reduce losses to the poultry industry. Diffuse reflectance spectroscopy provides a noninvasive and rapid method to interrogate tissue function. The sensitivity of DRS to the distinct absorption spectra of oxygenated and deoxygenated hemoglobin allows accurate quantification of average hemoglobin concentration and vascular oxygenation within the sampled tissue. In this study, we used diffuse reflectance spectroscopy to monitor breast hemoglobin concentration (THb) and vascular oxygen saturation (sO2) of 16 chickens that were exposed to heat stress (HS). HS is an important cause of WB myopathy in chickens. Animals were exposed to heat-stress (HS) and optical data were acquired at three time points: at baseline prior to heat stress, 2 days, and 21 days after initiation of HS. Our results show that animals from control and HS groups had a steady decay in optically derived breast hemoglobin concentration consistent with independent i-STAT measurements made on blood sampled from the femoral artery and could provide a noninvasive technology for monitoring tissue function in the poultry industry.

bioengineering↗