A Brief Review of FT-IR Spectroscopy Studies of Sphingolipids in Human Cells

In recent years, sphingolipids have attracted significant attention due to their pivotal role in cellular functions and physiological diseases. A valuable tool for investigating the characteristics of sphingolipids can be represented via FT-IR spectroscopy, generally recognized as a very powerful technique that provides detailed biochemical information on the examined sample with the unique properties of sensitivity and accuracy. In the present paper, some fundamental aspects of sphingolipid components of human cells are summarized, and the most relevant articles devoted to the FT-IR spectroscopic studies of sphingolipids are revised. A short description of different FT-IR experimental approaches adopted for investigating sphingolipids is also given, with details about the most commonly used data analysis procedures. The present overview of FT-IR investigations, although not exhaustive, attests to the relevant role this vibrational technique has played in giving significant insight into many aspects of this fascinating class of lipids.

Application of Label-Free Proteomics for Quantitative Analysis of Urothelial Carcinoma and Cystitis Tissue

A label-free approach based on a highly reproducible and stable workflow allows for quantitative proteome analysis . Due to advantages compared to labeling methods, the label-free approach has the potential to measure unlimited samples from clinical specimen monitoring and comparing thousands of proteins. The presented label-free workflow includes a new sample preparation technique depending on automatic annotation and tissue isolation via FTIR-guided laser microdissection, in-solution digestion, LC-MS/MS analyses, data evaluation by means of Proteome Discoverer and Progenesis software, and verification of differential proteins. We successfully applied this workflow in a proteomics study analyzing human cystitis and high-grade urothelial carcinoma tissue regarding the identification of a diagnostic tissue biomarker. The differential analysis of only 1 mm² of isolated tissue cells led to 74 significantly differentially abundant proteins.

Reciprocal Interplay Between Fibrillar Collagens and Collagen-Binding Integrins: Implications in Cancer Progression and Metastasis

Cancers are complex ecosystems composed of malignant cells embedded in an intricate microenvironment made of different non-transformed cell types and extracellular matrix (ECM) components. The tumor microenvironment is governed by constantly evolving cell-cell and cell-ECM interactions, which are now recognized as key actors in the genesis, progression and treatment of cancer lesions. The ECM is composed of a multitude of fibrous proteins, matricellular-associated proteins, and proteoglycans. This complex structure plays critical roles in cancer progression: it functions as the scaffold for tissues organization and provides biochemical and biomechanical signals that regulate key cancer hallmarks including cell growth, survival, migration, differentiation, angiogenesis, and immune response. Cells sense the biochemical and mechanical properties of the ECM through specialized transmembrane receptors that include integrins, discoidin domain receptors, and syndecans. Advanced stages of several carcinomas are characterized by a desmoplastic reaction characterized by an extensive deposition of fibrillar collagens in the microenvironment. This compact network of fibrillar collagens promotes cancer progression and metastasis, and is associated with low survival rates for cancer patients. In this review, we highlight how fibrillar collagens and their corresponding integrin receptors are modulated during cancer progression. We describe how the deposition and alignment of collagen fibers influence the tumor microenvironment and how fibrillar collagen-binding integrins expressed by cancer and stromal cells critically contribute in cancer hallmarks.

Application and Analysis of Biomedical Imaging Technology in Early Diagnosis of Breast Cancer

Breast cancer is the primary malignant tumor that endangers women's health. The incidence of breast cancer is increasing rapidly in recent years. Accurate disease evaluation before treatment is the key to the selection of treatment options. Biomedical imaging technology plays an irreplaceable role in the diagnosis and staging of tumors. Various imaging methods can provide excellent temporal and spatial resolution from multiple levels and perspectives and have become one of the most commonly used means of breast cancer early detection. With the development of radiomics, it has been found that early imaging diagnosis of breast cancer plays an important guiding role in clinical decision-making. The purpose of this study is to explore the characteristics of various breast cancer imaging technologies, promote the development of individualized accurate diagnosis and treatment of imaging, and improve the clinical application value of radiomics in the early diagnosis of breast cancer.

Investigation of the Effect of PD-L1 Blockade on Triple Negative Breast Cancer Cells Using Fourier Transform Infrared Spectroscopy

Interactions between programmed death-1 (PD-1) with its ligand PD-L1 on tumor cells can antagonize T cell responses. Inhibiting these interactions using immune checkpoint inhibitors has shown promise in cancer immunotherapy. MDA-MB-231 is a triple negative breast cancer cell line that expresses PD-L1. In this study, we investigated the biochemical changes in MDA-MB-231 cells following treatment with atezolizumab, a specific PD-L1 blocker. Our readouts were Fourier Transform Infrared (FTIR) spectroscopy and flow cytometric analyses. Chemometrical analysis, such as principal component analysis (PCA), was applied to delineate the spectral differences. We were able to identify the chemical alterations in both protein and lipid structure of the treated cells. We found that there was a shift from random coil and α-helical structure to β-sheet conformation of PD-L1 on tumor cells due to atezolizumab treatment, which could hinder binding with its receptors on immune cells, ensuring sustained T cell activation for potent immune responses. This work provides novel information about the effects of atezolizumab at molecular and cellular levels. FTIR bio-spectroscopy, in combination with chemometric analyses, may expedite research and offer new approaches for cancer immunology.

An Innovative Platform Merging Elemental Analysis and Ftir Imaging for Breast Tissue Analysis

Histopathology and immunohistology remain the gold standard for breast cancer diagnostic. Yet, these approaches do not usually provide a sufficiently detailed characterization of the pathology. The purpose of this work is to demonstrate for the first time that elemental analysis and Fourier transform infrared spectroscopy microscopic examination of breast tissue sections can be merged into one dataset to provide a single set of markers based on both organic molecules and inorganic trace elements. For illustrating the method, 6 mammary tissue sections were used. Fourier transform infrared (FTIR) spectroscopy images reported a fingerprint of the organic molecules present in the tissue section and laser ablation elemental analysis (LA-ICP-MS) images brought inorganic element profiles. The 6 tissue sections provided 31 10⁶ and 150,000 spectra for FTIR and LA-ICP-MS spectra respectively. The results bring the proof of concept that breast tissue can be analyzed simultaneously by FTIR spectroscopy and laser ablation elemental analysis (LA-ICP-MS) to provide in both case reasonably high resolution images. We show how to bring the images obtained by the two methods to a same spatial resolution and how to use image registration to analyze the data originating from both techniques as one block of data. We finally demonstrates the elemental analysis is orthogonal to all FTIR markers as no significant correlation is found between FTIR and LA-ICP-MS data. Combining FTIR and LA-ICP-MS imaging becomes possible, providing two orthogonal methods which can bring an unprecedented diversity of information on the tissue. This opens a new avenue of tissue section analyses providing unprecedented diagnostic potential.

Integrated Fourier Transform Infrared Imaging and Proteomics for Identification of a Candidate Histochemical Biomarker in Bladder Cancer

Histopathological differentiation between severe urocystitis with reactive urothelial atypia and carcinoma in situ (CIS) can be difficult, particularly after a treatment that deliberately induces an inflammatory reaction, such as intravesical instillation of Bacillus Calmette-Guèrin. However, precise grading in bladder cancer is critical for therapeutic decision making and thus requires reliable immunohistochemical biomarkers. Herein, an exemplary potential biomarker in bladder cancer was identified by the novel approach of Fourier transform infrared imaging for label-free tissue annotation of tissue thin sections. Identified regions of interest are collected by laser microdissection to provide homogeneous samples for liquid chromatography-tandem mass spectrometry-based proteomic analysis. This approach afforded label-free spatial classification with a high accuracy and without interobserver variability, along with the molecular resolution of the proteomic analysis. Cystitis and invasive high-grade urothelial carcinoma samples were analyzed. Three candidate biomarkers were identified and verified by immunohistochemistry in a small cohort, including low-grade urothelial carcinoma samples. The best-performing candidate AHNAK2 was further evaluated in a much larger independent verification cohort that also included CIS samples. Reactive urothelial atypia and CIS were distinguishable on the basis of the expression of this newly identified and verified immunohistochemical biomarker, with a sensitivity of 97% and a specificity of 69%. AHNAK2 can differentiate between reactive urothelial atypia in the setting of an acute or chronic cystitis and nonmuscle invasive-type CIS.

Spatial and molecular resolution of diffuse malignant mesothelioma heterogeneity by integrating label-free FTIR imaging, laser capture microdissection and proteomics

Diffuse malignant mesothelioma (DMM) is a heterogeneous malignant neoplasia manifesting with three subtypes: epithelioid, sarcomatoid and biphasic. DMM exhibit a high degree of spatial heterogeneity that complicates a thorough understanding of the underlying different molecular processes in each subtype. We present a novel approach to spatially resolve the heterogeneity of a tumour in a label-free manner by integrating FTIR imaging and laser capture microdissection (LCM). Subsequent proteome analysis of the dissected homogenous samples provides in addition molecular resolution. FTIR imaging resolves tumour subtypes within tissue thin-sections in an automated and label-free manner with accuracy of about 85% for DMM subtypes. Even in highly heterogeneous tissue structures, our label-free approach can identify small regions of interest, which can be dissected as homogeneous samples using LCM. Subsequent proteome analysis provides a location specific molecular characterization. Applied to DMM subtypes, we identify 142 differentially expressed proteins, including five protein biomarkers commonly used in DMM immunohistochemistry panels. Thus, FTIR imaging resolves not only morphological alteration within tissue but it resolves even alterations at the level of single proteins in tumour subtypes. Our fully automated workflow FTIR-guided LCM opens new avenues collecting homogeneous samples for precise and predictive biomarkers from omics studies.

Characterization of human breast cancer tissues by infrared imaging

Fourier Transform InfraRed (FTIR) spectroscopy coupled to microscopy (IR imaging) has shown unique advantages in detecting morphological and molecular pathologic alterations in biological tissues. The aim of this study was to evaluate the potential of IR imaging as a diagnostic tool to identify characteristics of breast epithelial cells and the stroma. In this study a total of 19 breast tissue samples were obtained from 13 patients. For 6 of the patients, we also obtained Non-Adjacent Non-Tumor tissue samples. Infrared images were recorded on the main cell/tissue types identified in all breast tissue samples. Unsupervised Principal Component Analyses and supervised Partial Least Square Discriminant Analyses (PLS-DA) were used to discriminate spectra. Leave-one-out cross-validation was used to evaluate the performance of PLS-DA models. Our results show that IR imaging coupled with PLS-DA can efficiently identify the main cell types present in FFPE breast tissue sections, i.e. epithelial cells, lymphocytes, connective tissue, vascular tissue and erythrocytes. A second PLS-DA model could distinguish normal and tumor breast epithelial cells in the breast tissue sections. A patient-specific model reached particularly high sensitivity, specificity and MCC rates. Finally, we showed that the stroma located close or at distance from the tumor exhibits distinct spectral characteristics. In conclusion FTIR imaging combined with computational algorithms could be an accurate, rapid and objective tool to identify/quantify breast epithelial cells and differentiate tumor from normal breast tissue as well as normal from tumor-associated stroma, paving the way to the establishment of a potential complementary tool to ensure safe tumor margins.

Fundamental developments in infrared spectroscopic imaging for biomedical applications

Infrared chemical imaging is a rapidly emerging field with new advances in instrumentation, data acquisition and data analysis. These developments have had significant impact in biomedical applications and numerous studies have now shown that this technology offers great promise for the improved diagnosis of the diseased state. Relying on purely biochemical signatures rather than contrast from exogenous dyes and stains, infrared chemical imaging has the potential to revolutionise histopathology for improved disease diagnosis. In this review we discuss the recent advances in infrared spectroscopic imaging specifically related to spectral histopathology (SHP) and consider the current state of the field. Finally we consider the practical application of SHP for disease diagnosis and consider potential barriers to clinical translation highlighting current directions and the future outlook.

FTIR imaging of the 3D extracellular matrix used to grow colonies of breast cancer cell lines

Infrared imaging was applied to investigate a reconstituted basement membrane, known as Matrigel, in three-dimensional cell cultures.

Label-free phenotyping of peripheral blood lymphocytes by infrared imaging

It is now widely accepted that the immune microenvironment of tumors and more precisely Tumor Infiltrating Lymphocytes (TIL) play an important role in cancer development and outcome. TILs are considered to be important prognostic and predictive factors based on a growing body of clinical evidence; however, their presence at the tumor site is not currently assessed routinely. FTIR (Fourier transform infrared) imaging has proven it has value in studying a range of tumors, particularly for characterizing tumor cells. Currently, very little is known about the potential for FTIR imaging to characterize TIL. The present proof of concept study investigates the ability of FTIR imaging to identify the principal lymphocyte subpopulations present in human peripheral blood (PB). A negative cell isolation method was employed to select pure, label-free, helper T cells (CD4(+)), cytotoxic T cells (CD8(+)) and B cells (CD19(+)) from six healthy donors PB by Fluorescence Activated Cell Sorting (FACS). Cells were centrifuged onto Barium Fluoride windows and ten infrared images were recorded for each lymphocyte subpopulation from all six donors. After spectral pre-treatment, statistical analyses were performed. Unsupervised Principal Component Analyses (PCA) revealed that in the absence of donor variability, CD4(+) T cells, CD8(+) T cells and B cells each display distinct IR spectral features. Supervised Partial Least Square Discriminant Analyses (PLS-DA) demonstrated that the differences between the three lymphocyte subpopulations are reflected in their IR spectra, permitting their individual identification even when significant donor variability is present. Our results also show that a distinct spectral signature is associated with antibody binding. To our knowledge this is the first study reporting that FTIR imaging can effectively identify T and B lymphocytes and differentiate helper T cells from cytotoxic T cells. This proof of concept study demonstrates that FTIR imaging is a reliable tool for the identification of lymphocyte subpopulations and has the potential for use in characterizing TIL.

Dielectric and FT-Raman spectroscopic approach to molecular identification of breast tumor tissues

FT-Raman spectra and dielectric properties of benign and malignant women breast tissues in vitro were investigated. FT-Raman spectra for the malignant tissues showed a remarkably decrease in the lipid/protein ratio. Dielectric properties of women breast tissues measured in the low frequency range (42-10(6)Hz) were interpreted in spite of electrode polarization effect. Experimental results showed a contrast between the dielectric properties of malignant (Grade II) and benign tissues within the frequency range studied. The permittivity of malignant to normal breast tissue was found to be 160:1 while it could be 1.3:1 for fibrocystic breast tissues. These findings could contribute to distinguish between two breast tissues. The differences in spectral features between benign and malignant tissues may lead to breast cancer detection.

Infrared imaging of MDA-MB-231 breast cancer cell line phenotypes in 2D and 3D cultures

Breast cancer cell lines in 2D (top) and 3D (bottom) culture: H&H, unstained bright field, and IR images.

Using Fourier transform IR spectroscopy to analyze biological materials

IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing.

Collagen morphology and texture analysis: from statistics to classification

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage.

Objective assessment of endogenous collagen in vivo during tissue repair by laser induced fluorescence

Collagen, a triple helical protein with the primary role of mechanical function, provides tensile strength to the skin, and plays a pivotal task in tissue repair. During tissue regeneration, collagen level increases gradually and therefore, monitoring of such changes in vivo by laser induced fluorescence was the main objective behind the present study. In order to accomplish this, 15 mm diameter excisional wounds were created on six to eight week old Swiss albino mice. The collagen deposition accelerated upon irradiation of single exposure of 2 J/cm² He-Ne laser dose immediately after wounding was recorded by laser induced autofluorescence in vivo along with un-illuminated and un-wounded controls. Autofluorescence spectra were recorded for each animal of the experimental groups on 0, 5, 10, 30, 45 and 60 days post-wounding, by exciting the granulation tissue/skin with 325 nm He-Cd laser. The variations in the average collagen intensities from the granulation tissue/skin of mice were inspected as a function of age and gender. Further, the spectral findings of the collagen synthesis in wound granulation tissue/un-wounded skin tissues were validated by Picro-Sirius red- polarized light microscopy in a blinded manner through image analysis of the respective collagen birefringence. The in vivo autofluorescence studies have shown a significant increase in collagen synthesis in laser treated animals as compared to the un-illuminated controls. Image analysis of the collagen birefringence further authenticated the ability of autofluorescence in the objective monitoring of collagen in vivo. Our results clearly demonstrate the potential of laser induced autofluorescence in the monitoring of collegen synthesis during tissue regeneration, which may have clinical implications.

Early detection of the chemical changes occurring during the induction and prevention of autoimmune-mediated demyelination detected by FT-IR imaging

Multiple sclerosis (MS) is an inflammatory, demyelinating and neurodegenerative disease of the central nervous system (CNS). Despite progress in understanding immunogenetic aspects of this disease, the mechanisms involved in lesion formation are unknown. To gain new insights into the neuropathology of MS, we used an innovative integration of Fourier transform infrared (FT-IR) microspectroscopy, bioinformatics, and a synchrotron light source to analyze macromolecular changes in the CNS during the course and prevention of experimental autoimmune encephalomyelitis (EAE), an animal model for MS. We report that subtle chemical and structural changes not observed by conventional histology were detected before the onset of clinical signs of EAE. Moreover, trained artificial neural networks (ANNs) could discriminate, with excellent sensitivity and specificity, pathology from surrounding tissues and the early stage of the disease progression. Notably, we show that this novel measurement platform can detect characteristic differences in biochemical composition of lesion pathology in animals partially protected against EAE by vaccination with Nogo-A, an inhibitor of neural outgrowth, demonstrating the potential for automated screening and evaluation of new therapeutic agents.

Analysis of breast cancer by small angle X-ray scattering (SAXS)

Small angle X-ray scattering (SAXS) images of normal breast tissue and benign and malignant breast tumour tissues, fixed in formalin, were measured at the momentum transfer range of 0.063 nm(-1) < or = q (= 4pisin(theta/2)/lambda) < or = 2.720 nm(-1). Four intrinsic parameters were extracted from the scattering profiles (1D SAXS image reduced) and, from the combination of these parameters, another three parameters were also created. All parameters, intrinsic and derived, were subject to discriminant analysis, and it was verified that parameters such as the area of diffuse scatter at the momentum transfer range 0.50 < or = q < or = 0.56 nm(-1), the ratio between areas of fifth-order axial and third-order lateral peaks and third-order axial spacing provide the most significant information for diagnosis (p < 0.001). Thus, in this work it was verified that by combining these three parameters it was possible to classify human breast tissues as normal, benign lesion or malignant lesion with a sensitivity of 83% and a specificity of 100%.

X-ray scattering for classifying tissue types associated with breast disease

Collagen types I and III can be characterized at the molecular level (at the tens to hundreds of nanometers scale) using small angle x-ray scattering (SAXS). Although collagen fibril structural parameters at this length scale have shown differences between diseased and nondiseased breast tissues, a comprehensive analysis involving a multitude of features with a large (>50) patient cohort has not previously been investigated. Breast tissue samples were excised from 80 patients presenting with either a breast lump or reduction mammoplasty. From these, invasive carcinoma, benign tissue, and normal parenchyma were analyzed. Parameters related to collagen structure, including longitudinal (axial) and lateral (equatorial) features, polar angle features, total scattering intensity, and tissue heterogeneity effects, were extracted from the SAXS patterns and examined. The amplitude of the third-order axial peak and the total scattering intensity (amorphous scatter) showed the most separation between tissue groups and a classification model using these two parameters demonstrated an accuracy of over 95% between invasive carcinoma and mammoplasty patients. Normal tissue taken from disease-free patients (mammoplasty) and normal tissue taken from patients with presence of disease showed significant differences, suggesting that SAXS may provide different diagnostic information from that of conventional histopathology.