Detection of collagens in brain tumors based on FTIR imaging and chemometrics

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.

A biospectroscopic approach toward colorectal cancer diagnosis from bodily fluid samples via ATR-MIR spectroscopy combined with multivariate data analysis

In this study, a biospectroscopic approach was reported for the detection of spectral changes and biomarkers for the diagnosis of colorectal cancer (CC) cases from different bodily fluids (blood plasma, blood serum, saliva and colonoscopy disinfection/wash fluids) by using attenuated total reflection-mid infrared (ATR-MIR) spectroscopy. To recognize the molecular level changes in the spectral characteristics of CC and their healthy/control (CH) groups, different multivariate data analyses (HCA, LDA, PCA and SIMCA) were successfully performed over the data of ATR-MIR spectroscopy. Two hundred specimens were characterized in detail over the data of spectral regions (4000-650 cm-1 and regions V-XXII). The findings revealed that significant changes were clearly observed in the concentrations of lipid, protein, nucleic acid and carbohydrate biomolecules for cancer cases based upon their necessity to overcome energy requirements. Supervised multivariate data methodology SIMCA, presented an excellent classification for the studied groups; similarly 100% of the specimens from different bodily fluids were correctly classified by supervised methodology LDA. As a result, the developed ATR-MIR methodology for the classification of CC and their healthy groups highlighted a rapid cancer diagnosis approach from different bodily fluids; therefore, it could be guide to make well decision before histopathological assessment and to screen CC populations existing in society.

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.

A rapid diagnostic approach for gastric and colon cancers via Fourier transform mid-infrared spectroscopy coupled with chemometrics from paraffin-embedded tissues

This paper describes the feasibility of Attenuated total reflection-Fourier transform mid-infrared (ATR-MIR) spectroscopy method coupled with chemometrics for the rapid diagnostic approach and screening spectral changes for gastric and colon cancers from paraffin-embedded tissues. A total number of 82 tissue samples were analyzed by a simple ATR-MIR method combined with PCA, HCA, SIMCA and LDA methodologies. Spectral analyses showed significant differences for the molecular contents particularly about the lipid, nucleic acid, protein and other biomolecules in the samples of gastric cancer (GC) and colon cancer (CC) groups from their control/healthy groups. Significant changes in the characteristic of these molecules were only observed for cancer groups based upon the increment in their biosynthesis, and they could be utilized as diagnostic spectral biomarkers. Under the optimum conditions, SIMCA provided excellent classification for diseased and control groups, with 5% significance level. As well, 97.75% of the studied tissue samples were correctly discriminated on the basis of their origin by LDA. Consequently, the findings of this study highlighted the rapid diagnosis of gastric and colon cancer cases from paraffin-embedded tissues via ATR-MIR spectroscopy complemented with chemometrics.

On 2D-FTIR-XRF microscopy - A step forward correlative tissue studies by infrared and hard X-ray radiation

Correlative Fourier Transform Infra-Red (FTIR) and hard X-Ray Fluorescence (XRF) microscopy studies of thin biological samples have recently evolved as complementary methods for biochemical fingerprinting of animal/human tissues. These are seen particularly useful for tracking the mechanisms of neurological diseases, i.e., in Alzheimer/Parkinson disease, in the brain where mishandling of trace metals (Fe, Cu, Zn) seems to be often associated with ongoing damage to molecular components via, among others, oxidative/reductive stress neurotoxicity. Despite substantial progress in state-of-the-art detection and data analysis methods, combined FTIR-XRF experiments have never benefited from correlation and co-localization analysis of molecular moieties and chemical elements, respectively. We here propose for the first time a completely novel data analysis pipeline, utilizing the idea of 2D correlation spectrometry for brain tissue analysis. In this paper, we utilized combined benchtop FTIR - synchrotron XRF mapping experiments on thin brain samples mounted on polypropylene membranes. By implementing our recently developed Multiple Linear Regression Multi-Reference (MLR-MR) algorithm, along with advanced image processing, artifact-free 2D FTIR-XRF spectra could be obtained by mitigating the impact of spectral artifacts, such as Etalon fringes and mild scattering Mie-like signatures, in the FTIR data. We demonstrated that the method is a powerful tool for co-localizing and correlating molecular arrangements and chemical elements (and vice versa) using visually attractive 2D correlograms. Moreover, the methods' applicability for fostering the identification of distinct (biological) materials, involving chemical elements and molecular arrangements, is also shown. Taken together, the 2D FTIR-XRF method opens up for new measures for in-situ investigating hidden complex biochemical correlations, and yet unraveled mechanisms in a biological sample. This step seems crucial for developing new strategies for facilitating the research on the interaction of metals/nonmetals with organic components. This is particularly important for enhancing our understanding of the diseases associated with metal/nonmetal mishandling.

Human serum mid-infrared spectroscopy combined with machine learning algorithms for rapid detection of gliomas

Glioma has a low cure rate and a high mortality rate. Therefore, correct diagnosis and treatment are essential for patients. This research aims to use mid-infrared spectroscopy combined with machine learning algorithms to identify patients with glioma. The glioma infrared spectra and the control group serum are smoothed and normalized, then the principal component analysis (PCA) algorithm is used to reduce the data dimensionality, and finally, the particle swarm optimization-support vector machine (PSO-SVM), backpropagation (BP) neural network and decision tree (DT) model are established. The classification accuracy of the three models was 92.00 %, 91.83 %, 87.20 %, and the AUC values were 0.919, 0.945, and 0.866, respectively. The results show that PCA-PSO-SVM has a better classification effect. This study shows that mid-infrared spectroscopy combined with machine learning algorithms has great potential in the application of non-invasive, rapid and accurate identification of glioma patients.

Physicochemical and Functional Potential of Hydrocolloids Extracted from Some Solanaceae Plants

Three different plants (Solanum indicum, Solanum surattense, and Solanum nigrum) of Solanaceae family were explored to extract and characterize hydrocolloids in aqueous solution. S. indicum fruit fractions bring in maximum hydrocolloid yield of 21.39 ± 0.42% based on % dry weight of the sample. The observed order of extracting hydrocolloid yield amongst investigating aerial parts of S. surattense, S. nigrum, and S. indicum (% dry weight) is fruits > stem > leaves. Maximum protein (22%) and starch (0.85%) contents were observed in fruit fractions of S. nigrum and S. indicum, respectively. Among the functional characteristics, the fruit fraction of S. indicum has higher water-holding capacity (24.80%), oil-holding capacity (2.96%), emulsifying activity (90%), emulsion stability (70%), foaming capacity (65%), and foaming stability (90%). Monosaccharide profiling results showed the presence of glucose, galacturonic acid, galactose, glucuronic acid, arabinose, and xylose in extracted fractions. The findings propose that hydrocolloids (extracted with water) are cost-effective and would be potential candidate as a substitute for pectin added into foamy and frothy food products and frothy beverages.

Tracking Extracellular Matrix Remodeling in Lungs Induced by Breast Cancer Metastasis. Fourier Transform Infrared Spectroscopic Studies

This work focused on a detailed assessment of lung tissue affected by metastasis of breast cancer. We used large-area chemical scanning implemented in Fourier transform infrared (FTIR) spectroscopic imaging supported with classical histological and morphological characterization. For the first time, we differentiated and defined biochemical changes due to metastasis observed in the lung parenchyma, atelectasis, fibrous, and muscle cells, as well as bronchi ciliate cells, in a qualitative and semi-quantitative manner based on spectral features. The results suggested that systematic extracellular matrix remodeling with the progress of the metastasis process evoked a decrease in the fraction of the total protein in atelectasis, fibrous, and muscle cells, as well as an increase of fibrillar proteins in the parenchyma. We also detected alterations in the secondary conformations of proteins in parenchyma and atelectasis and changes in the level of hydroxyproline residues and carbohydrate moieties in the parenchyma. The results indicate the usability of FTIR spectroscopy as a tool for the detection of extracellular matrix remodeling, thereby enabling the prediction of pre-metastatic niche formation.

3D Digital Pathology for a Chemical-Functional Analysis of Glomeruli in Health and Pathology

Determining the filtration function and biochemical status of kidney at the single glomerulus level remains hardly accessible, even from biopsies. Here, we provide evidence that IR spectro-microscopy is a suitable method to account for the filtration capacity of individual glomeruli along with related physio-pathological condition. A ∼4 μm voxel resolution 3D IR image reconstruction is built from consecutive tissue sections, thus, providing a 3D IR spectrum matrix of an individual glomerulus. The filtration capacity of glomeruli was quantitatively determined after BaSO₄ perfusion, and additional chemical data could be used to determined oxidative stress effects and fibrosis, thus, combining functional and biochemical information from the same 3D IR spectrum matrix. This analytical approach was applied on mice with unilateral ureteral obstruction (UUO) inducing chronic kidney disease. Compared to the healthy condition, UUO induced a significant drop in glomeruli filtration capacity (-17 ± 8% at day 4 and -48 ± 14% at day 14) and volume (36 ± 10% at day 4 and 67 ± 13% at day 14), along a significant increase of oxidative stress (+61 ± 19% at day 4 and +84 ± 17% at day 14) and a change in the lipid-to-protein ratio (-8.2 ± 3.6% at day 4 and -18.1 ± 5.9% at day 14). Therefore, IR spectro-microscopy might be developed as a new 3D pathology resource for analyzing functional and biochemical parameters of glomeruli.

Elastic and inelastic light scattering spectroscopy and its possible use for label-free brain tumor typing

This paper presents an approach for label-free brain tumor tissue typing. For this application, our dual modality microspectroscopy system combines inelastic Raman scattering spectroscopy and Mie elastic light scattering spectroscopy. The system enables marker-free biomedical diagnostics and records both the chemical and morphologic changes of tissues on a cellular and subcellular level. The system setup is described and the suitability for measuring morphologic features is investigated. Graphical Abstract Bimodal approach for label-free brain tumor typing. Elastic and inelastic light scattering spectra are collected laterally resolved in one measurement setup. The spectra are investigated by multivariate data analysis for assigning the tissues to specific WHO grades according to their malignancy.

The combination of artificial neural networks and synchrotron radiation-based infrared micro-spectroscopy for a study on the protein composition of human glial tumors

Protein-related changes associated with the development of human brain gliomas are of increasing interest in modern neuro-oncology.

Rapid approach to analyze biochemical variation in rat organs by ATR FTIR spectroscopy

ATR FTIR spectra were collected from rat tissue homogenates (myocardium, brain, liver, lung, intestine, and kidney) to analyze their biochemical content. Based on the second derivative of an average spectral profile it was possible to assign bands e.g. to triglycerides and cholesterol esters, proteins, phosphate macromolecules (DNA, RNA, phospholipids, phosphorylated proteins) and others (glycogen, lactate). Peaks in the region of 1600-1700 cm(-1) related to amide I mode revealed the secondary structure of proteins. The collected spectra do not characterize morphological structure of the investigated tissues but show their different composition. The comparison of spectral information gathered from FTIR spectra of the homogenates and those obtained previously from FTIR imaging of the tissue sections implicates that the presented here approach can be successfully employed in the investigations of biochemical variation in animal tissues. Moreover, it can be used in the pharmacological and pharmacokinetic studies to correlate the overall biochemical status of the tissue with the pathological changes it has undergone.

FTIR spectro-imaging of collagen scaffold formation during glioma tumor development

Evidence has recently emerged that solid and diffuse tumors produce a specific extracellular matrix (ECM) for division and diffusion, also developing a specific interface with microvasculature. This ECM is mainly composed of collagens and their scaffolding appears to drive tumor growth. Although collagens are not easily analyzable by UV-fluorescence means, FTIR imaging has appeared as a valuable tool to characterize collagen contents in tissues, specially the brain, where ECM is normally devoid of collagen proteins. Here, we used FTIR imaging to characterize collagen content changes in growing glioma tumors. We could determine that C6-derived solid tumors presented high content of triple helix after 8-11 days of growth (typical of collagen fibrils formation; 8/8 tumor samples; 91 % of total variance), and further turned to larger α-helix (days 12-15; 9/10 of tumors; 94 % of variance) and β-turns (day 18-21; 7/8 tumors; 97 % of variance) contents, which suggest the incorporation of non-fibrillar collagen types in ECM, a sign of more and more organized collagen scaffold along tumor progression. The growth of tumors was also associated to the level of collagen produced (P < 0.05). This study thus confirms that collagen scaffolding is a major event accompanying the angiogenic shift and faster tumor growth in solid glioma phenotypes.

Infrared spectroscopic studies of cells and tissues: triple helix proteins as a potential biomarker for tumors

In this work, the infrared (IR) spectra of living neural cells in suspension, native brain tissue, and native brain tumor tissue were investigated. Methods were developed to overcome the strong IR signal of liquid water so that the signal from the cellular biochemicals could be seen. Measurements could be performed during surgeries, within minutes after resection. Comparison between normal tissue, different cell lineages in suspension, and tumors allowed preliminary assignments of IR bands to be made. The most dramatic difference between tissues and cells was found to be in weaker IR absorbances usually assigned to the triple helix of collagens. Triple helix domains are common in larger structural proteins, and are typically found in the extracellular matrix (ECM) of tissues. An algorithm to correct offsets and calculate the band heights and positions of these bands was developed, so the variance between identical measurements could be assessed. The initial results indicate the triple helix signal is surprisingly consistent between different individuals, and is altered in tumor tissues. Taken together, these preliminary investigations indicate this triple helix signal may be a reliable biomarker for a tumor-like microenvironment. Thus, this signal has potential to aid in the intra-operational delineation of brain tumor borders.