Raman spectroscopy for medulloblastoma

Label-free optical imaging for brain cancer assessment

Advances in label-free optical imaging offer a promising avenue for brain cancer assessment, providing high-resolution, real-time insights without the need for radiation or exogeneous agents. These cost-effective and intricately detailed techniques overcome the limitations inherent in magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) scans by offering superior resolution and more readily accessible imaging options. This comprehensive review explores a variety of such methods, including photoacoustic imaging (PAI), optical coherence tomography (OCT), Raman imaging, and IR microscopy. It focuses on their roles in the detection, diagnosis, and management of brain tumors. By highlighting recent advances in these imaging techniques, the review aims to underscore the importance of label-free optical imaging in enhancing early detection and refining therapeutic strategies for brain cancer.

Raman Spectroscopy: A Tool for Molecular Fingerprinting of Brain Cancer

Brain cancer is one of those few cancers with very high mortality and low five-year survival rate. First and foremost reason for the woes is the difficulty in diagnosing and monitoring the progression of brain tumors both benign and malignant, noninvasively and in real time. This raises a need in this hour for a tool to diagnose the tumors in the earliest possible time frame. On the other hand, Raman spectroscopy which is well-known for its ability to precisely represent the molecular markers available in any sample given, including biological ones, with great sensitivity and specificity. This has led to a number of studies where Raman spectroscopy has been used in brain tumors in various ways. This review article highlights the fundamentals of Raman spectroscopy and its types including conventional Raman, SERS, SORS, SRS, CARS, etc. are used in brain tumors for diagnostics, monitoring, and even theragnostics, collating all the major works in the area. Also, the review explores how Raman spectroscopy can be even more effectively used in theragnostics and the clinical level which would make them a one-stop solution for all brain cancer needs in the future.

Evolving Diagnostic and Treatment Strategies for Pediatric CNS Tumors: The Impact of Lipid Metabolism

Pediatric neurological tumors are a heterogeneous group of cancers, many of which carry a poor prognosis and lack a "standard of care" therapy. While they have similar anatomic locations, pediatric neurological tumors harbor specific molecular signatures that distinguish them from adult brain and other neurological cancers. Recent advances through the application of genetics and imaging tools have reshaped the molecular classification and treatment of pediatric neurological tumors, specifically considering the molecular alterations involved. A multidisciplinary effort is ongoing to develop new therapeutic strategies for these tumors, employing innovative and established approaches. Strikingly, there is increasing evidence that lipid metabolism is altered during the development of these types of tumors. Thus, in addition to targeted therapies focusing on classical oncogenes, new treatments are being developed based on a broad spectrum of strategies, ranging from vaccines to viral vectors, and melitherapy. This work reviews the current therapeutic landscape for pediatric brain tumors, considering new emerging treatments and ongoing clinical trials. In addition, the role of lipid metabolism in these neoplasms and its relevance for the development of novel therapies are discussed.

A Handheld Visible Resonance Raman Analyzer Used in Intraoperative Detection of Human Glioma

There is still a lack of reliable intraoperative tools for glioma diagnosis and to guide the maximal safe resection of glioma. We report continuing work on the optical biopsy method to detect glioma grades and assess glioma boundaries intraoperatively using the VRR-LRRTM Raman analyzer, which is based on the visible resonance Raman spectroscopy (VRR) technique. A total of 2220 VRR spectra were collected during surgeries from 63 unprocessed fresh glioma tissues using the VRR-LRRTM Raman analyzer. After the VRR spectral analysis, we found differences in the native molecules in the fingerprint region and in the high-wavenumber region, and differences between normal (control) and different grades of glioma tissues. A principal component analysis–support vector machine (PCA-SVM) machine learning method was used to distinguish glioma tissues from normal tissues and different glioma grades. The accuracy in identifying glioma from normal tissue was over 80%, compared with the gold standard of histopathology reports of glioma. The VRR-LRRTM Raman analyzer may be a new label-free, real-time optical molecular pathology tool aiding in the intraoperative detection of glioma and identification of tumor boundaries, thus helping to guide maximal safe glioma removal and adjacent healthy tissue preservation.

Infrared Spectroscopy as a Potential Diagnostic Tool for Medulloblastoma

INTRODUCTION

Medulloblastoma (MB) is the most common malignant tumor of the central nervous system in childhood. FTIR spectroscopy provides a holistic view of the chemical composition of biological samples, including the detection of molecules such as nucleic acids, proteins, and lipids. This study evaluated the applicability of FTIR spectroscopy as a potential diagnostic tool for MB.

MATERIALS AND METHODS

FTIR spectra of MB samples from 40 children (boys/girls: 31/9; age: median 7.8 years, range 1.5-21.5 years) treated in the Oncology Department of the Children's Memorial Health Institute in Warsaw between 2010 and 2019 were analyzed. The control group consisted of normal brain tissue taken from four children diagnosed with causes other than cancer. Formalin-fixed and paraffin-embedded tissues were sectioned and used for FTIR spectroscopic analysis. The sections were examined in the mid-infrared range (800-3500 cm^-1) by ATR-FTIR. Spectra were analysed using a combination of principal component analysis, hierarchical cluster analysis, and absorbance dynamics.

RESULTS

FTIR spectra in MB were significantly different from those of normal brain tissue. The most significant differences related to the range of nucleic acids and proteins in the region 800-1800 cm^-1. Some major differences were also revealed in the quantification of protein conformations (α-helices, β-sheets, and others) in the amide I band, as well as in the absorbance dynamics in the 1714-1716 cm^-1 range (nucleic acids). It was not, however, possible to clearly distinguish between the various histological subtypes of MB using FTIR spectroscopy.

CONCLUSIONS

MB and normal brain tissue can be distinguished from one another to some extent using FTIR spectroscopy. As a result, it may be used as a further tool to hasten and enhance histological diagnosis.

Revision of Commonly Accepted Warburg Mechanism of Cancer Development: Redox-Sensitive Mitochondrial Cytochromes in Breast and Brain Cancers by Raman Imaging

We used Raman imaging to monitor changes in the redox state of the mitochondrial cytochromes in ex vivo human brain and breast tissues, surgically resected specimens of human tissues and in vitro human brain cells of normal astrocytes (NHA), astrocytoma (CRL-1718), glioblastoma (U87-MG) and medulloblastoma (Daoy), and human breast cells of normal cells (MCF 10A), slightly malignant cells (MCF7) and highly aggressive cells (MDA-MB-231) by means of Raman microspectroscopy at 532 nm. We visualized localization of cytochromes by Raman imaging in the major organelles in cancer cells. We demonstrated that the "redox state Raman marker" of the ferric low-spin heme in cytochrome c at 1584 cm^-1 can serve as a sensitive indicator of cancer aggressiveness. We compared concentration of reduced cytochrome c and the grade of cancer aggressiveness in cancer tissues and single cells and specific organelles in cells: nucleous, mitochondrium, lipid droplets, cytoplasm and membrane. We found that the concentration of reduced cytochrome c becomes abnormally high in human brain tumors and breast cancers in human tissues. Our results reveal the universality of Raman vibrational characteristics of mitochondrial cytochromes in metabolic regulation in cancers that arise from epithelial breast cells and brain glial cells.

Redox Imbalance and Biochemical Changes in Cancer by Probing Redox-Sensitive Mitochondrial Cytochromes in Label-Free Visible Resonance Raman Imaging

Simple Summary

Gliomas comprise around 30% of human brain tumors, while invasive ductal carcinoma (IDC) comprises around 80% of human breast cancers. The aim of our study was to show that cancerogenesis affects the redox status of mitochondrial cytochromes, which can be tracked by using Raman spectroscopy and imaging. Our results confirmed that human breast cancer and brain tumor demonstrate a redox imbalance compared to normal tissues. We have shown the correlation between the intensity of cytochromes Raman bands at 750, 1126, 1337 and 1584 cm⁻¹ and malignancy grade for brain and breast cancers.

Abstract

To monitor redox state changes and biological mechanisms occurring in mitochondrial cytochromes in cancers improving methods are required. We used Raman spectroscopy and Raman imaging to monitor changes in the redox state of the mitochondrial cytochromes in ex vivo human brain and breast tissues at 532 nm, 633 nm, 785 nm. We identified the oncogenic processes that characterize human infiltrating ductal carcinoma (IDC) and human brain tumors: gliomas; astrocytoma and medulloblastoma based on the quantification of cytochrome redox status by exploiting the resonance-enhancement effect of Raman scattering. We visualized localization of cytochromes by Raman imaging in the breast and brain tissues and analyzed cytochrome c vibrations at 750, 1126, 1337 and 1584 cm⁻¹ as a function of malignancy grade. We found that the concentration of reduced cytochrome c becomes abnormally high in human brain tumors and breast cancers and correlates with the grade of cancer. We showed that Raman imaging provides additional insight into the biology of astrocytomas and breast ductal invasive cancer, which can be used for noninvasive grading, differential diagnosis.

The Future of Skull Base Surgery: A View Through Tinted Glasses

In the present report, we have broadly outlined the potential advances in the field of skull base surgery, which might occur within the next 20 years based on the many areas of current research in biology and technology. Many of these advances will also be broadly applicable to other areas of neurosurgery. We have grounded our predictions for future developments in an exploration of what patients and surgeons most desire as outcomes for care. We next examined the recent developments in the field and outlined several promising areas of future improvement in skull base surgery, per se, as well as identifying the new hospital support systems needed to accommodate these changes. These include, but are not limited to, advances in imaging, Raman spectroscopy and microscopy, 3-dimensional printing and rapid prototyping, master-slave and semiautonomous robots, artificial intelligence applications in all areas of medicine, telemedicine, and green technologies in hospitals. In addition, we have reviewed the therapeutic approaches using nanotechnology, genetic engineering, antitumor antibodies, and stem cell technologies to repair damage caused by traumatic injuries, tumors, and iatrogenic injuries to the brain and cranial nerves. Additionally, we have discussed the training requirements for future skull base surgeons and stressed the need for adaptability and change. However, the essential requirements for skull base surgeons will remain unchanged, including knowledge, attention to detail, technical skill, innovation, judgment, and compassion. We believe that active involvement in these rapidly evolving technologies will enable us to shape some of the future of our discipline to address the needs of both patients and our profession.

Raman spectroscopy and neuroscience: from fundamental understanding to disease diagnostics and imaging

Neuroscience would directly benefit from more effective detection techniques, leading to earlier diagnosis of disease. The specificity of Raman spectroscopy is unparalleled, given that a molecular fingerprint is attained for each species. It also allows for label-free detection with relatively inexpensive instrumentation, minimal sample preparation, and rapid sample analysis. This review summarizes Raman spectroscopy-based techniques that have been used to advance the field of neuroscience in recent years.

A look into the use of Raman spectroscopy for brain and breast cancer diagnostics: linear and non-linear optics in cancer research as a gateway to tumor cell identity

Introduction: Currently, intensely developing of linear and non-linear optical methods for cancer detection provides a valuable tool to improve sensitivity and specificity. One of the main reasons for insufficient progress in cancer diagnostics is related to the fact that most cancer types are not only heterogeneous in their genetic composition but also reside in varying microenvironments and interact with different cell types. Until now, no technology has been fully proven for effective detecting of invasive cancer, which infiltrating the extracellular matrix.Areas covered: This review investigates the current status of Raman spectroscopy and Raman imaging for brain and breast cancer diagnostics. Moreover, the review provides a comprehensive overview of the applicability of atomic force microscopy (AFM), linear and non-linear optics in cancer research as a gateway to tumor cell identity.Expert commentary: A combination of linear and non-linear optics, particularly Raman-driven methods, has many additional advantages to identify alterations in cancer cells that are crucial for their proliferation and that distinguish them from normal cells.

Optical biopsy identification and grading of gliomas using label-free visible resonance Raman spectroscopy

Glioma is one of the most refractory types of brain tumor. Accurate tumor boundary identification and complete resection of the tumor are essential for glioma removal during brain surgery. We present a method based on visible resonance Raman (VRR) spectroscopy to identify glioma margins and grades. A set of diagnostic spectral biomarkers features are presented based on tissue composition changes revealed by VRR. The Raman spectra include molecular vibrational fingerprints of carotenoids, tryptophan, amide I/II/III, proteins, and lipids. These basic in situ spectral biomarkers are used to identify the tissue from the interface between brain cancer and normal tissue and to evaluate glioma grades. The VRR spectra are also analyzed using principal component analysis for dimension reduction and feature detection and support vector machine for classification. The cross-validated sensitivity, specificity, and accuracy are found to be 100%, 96.3%, and 99.6% to distinguish glioma tissues from normal brain tissues, respectively. The area under the receiver operating characteristic curve for the classification is about 1.0. The accuracies to distinguish normal, low grade (grades I and II), and high grade (grades III and IV) gliomas are found to be 96.3%, 53.7%, and 84.1% for the three groups, respectively, along with a total accuracy of 75.1%. A set of criteria for differentiating normal human brain tissues from normal control tissues is proposed and used to identify brain cancer margins, yielding a diagnostic sensitivity of 100% and specificity of 71%. Our study demonstrates the potential of VRR as a label-free optical molecular histopathology method used for in situ boundary line judgment for brain surgery in the margins.

Raman Analysis of Tear Fluid Alteration Following Contact Lense Use

Tear fluid is a heterogeneous solution containing mainly proteins, lipids, mucins and electrolytes, which regulates the physiology of the human eye. The complex composition of tears can be altered in the presence of eye inflammations. The use of contact lenses is one of the most frequent causes of inflammatory responses of the eye, with the related discomfort often causing the wearer to give up using them. In this paper, we exploit the potentiality of Raman Spectroscopy to analyse the biochemical changes in tear fluid in a contact lens wearer. In particular, we analysed the tear fluid collected from a volunteer as a function of the wearing time for two types of monthly contact lenses (Hydrogel and Si-Hydrogel). Our experimental results show an alteration of the relative concentrations of proteins and lipids in both of the analysed cases. More importantly, our results highlight the diagnostic sensitivity of Raman analysis to select the proper contact lens type for each wearer and optimise the lens wearing conditions.