Analysis of Human Colon by Raman Spectroscopy and Imaging-Elucidation of Biochemical Changes in Carcinogenesis

Colon Tumor Discrimination Combining Independent Endoscopic Probe-Based Raman Spectroscopy and Optical Coherence Tomography Modalities with Bayes Rule

Colorectal cancer is one of the most prevalent forms of cancer globally. The most common routine diagnostic methods are the examination of the interior of the colon during colonoscopy or sigmoidoscopy, which frequently includes the removal of a biopsy sample. Optical methods, such as Raman spectroscopy (RS) and optical coherence tomography (OCT), can help to improve diagnostics and reduce the number of unnecessary biopsies. For in vivo use, we have developed fiber-optic probes, one for single-point Raman measurements and one for volumetric OCT. Here, we present the results of a clinical study using these fiber-optic probes in an ex vivo setting. The goal was to evaluate the beneficial effect of combining these two modalities on the AUC ROC score of the machine learning models for the discrimination of cancerous and healthy tissue. In the initial stage of the investigation, both modalities were validated separately using linear discriminant analysis. RS was subjected to spectral preprocessing, while OCT underwent texture feature extraction. Subsequently, both modalities were integrated using the Bayes rule, resulting in an enhanced area under the curve score of 0.93, representing an improvement over the 0.77 score for Raman spectroscopy and 0.86 for OCT.

A Novel HER2 Protein Identification Methodology in Breast Cancer Cells Using Raman Spectroscopy and Raman Imaging: An Analytical Validation Study

Conventional assays such as immunohistochemistry (IHC) and in situ hybridization (ISH) used in clinical procedures for quantification of the human epidermal growth factor receptor-2 (HER2) status in breast cancer have many limitations. In the current study, we have used HER2 expression in a broad range of breast cancer phenotypes to explore the potential utility of a novel immunodetection technique using Raman spectroscopy and Raman imaging combined with artificial intelligence models. The correlations between the Raman method and conventional HER2 testing methodologies (IHC and ISH) have been tested. Raman measurements showed a strong linear correlation (p = 0.05, R2=0,9816) with IHC analysis in the studied breast cell lines: MCF-10A, MCF-7, MDA-MB-231, HTB-30 (SK-BR-3), and AU-565 represent normal, nontumorigenic epithelial cells, triple-positive breast carcinoma, and triple-negative breast cancer cell lines. Analytic testing of Raman spectroscopy and Raman imaging demonstrated that this method may offer advantages over the currently used diagnostic methodologies.

Raman spectroscopy for classification of neoplastic and non-neoplastic CAM colon tumors

This paper demonstrates the potential of Raman spectroscopy for differentiating neoplastic from non-neoplastic colon tumors, obtained with the CAM (chicken chorioallantoic membrane) model. For the CAM model two human cell lines were used to generate two types of tumors, the RKO cell line for neoplastic colon tumors and the NCM460 cell line for non-neoplastic colon tumors. The Raman spectra were acquired with a 785 nm excitation laser. The measured Raman spectra from the CAM samples (n = 14) were processed with several methods for baseline correction and to remove artifacts. The corrected spectra were analyzed with PCA (principal component analysis). Additionally, machine learning based algorithms were used to create a model capable of classifying neoplastic and non-neoplastic tumors. The principal component scores showed a clear differentiation between neoplastic and non-neoplastic colon tumors. The classification model had an accuracy of 93 %. Thus, a complete methodology to process and analyze Raman spectra was validated, using a rapid, accessible, and well-established tumor model that mimics the human tumor pathology with minor ethical concerns.

A Dual-Modal, Label-Free Raman Imaging Method for Rapid Virtual Staining of Large-Area Breast Cancer Tissue Sections

As one of the most common cancers, accurate, rapid, and simple histopathological diagnosis is very important for breast cancer. Raman imaging is a powerful technique for label-free analysis of tissue composition and histopathology, but it suffers from slow speed when applied to large-area tissue sections. In this study, we propose a dual-modal Raman imaging method that combines Raman mapping data with microscopy bright-field images to achieve virtual staining of breast cancer tissue sections. We validate our method on various breast tissue sections with different morphologies and biomarker expressions and compare it with the golden standard of histopathological methods. The results demonstrate that our method can effectively distinguish various types and components of tissues, and provide staining images comparable to stained tissue sections. Moreover, our method can improve imaging speed by up to 65 times compared to general spontaneous Raman imaging methods. It is simple, fast, and suitable for clinical applications.

A Review on Emerging Techniques for Diagnosis of Colorectal Cancer

Common detection methods in practice for diagnosing colorectal cancer (CRC) are painful and invasive leading to less participation of individuals for CRC diagnosis. Whereas, improved or enhanced imaging systems and other minimally invasive techniques with shorter detection times deliver greater detail and less discomfort in individuals. Thus, this review is a summary of the diagnostic tests, ranging from the simple potential use in developing a flexible CRC treatment to the patient's potential benefits in receiving less invasive procedures and the advanced treatments that might provide a better assessment for the diagnosis of CRC and reduce the mortality related to CRC.

A new modality for cholesterol impact tracking in colon cancer development - Raman imaging, fluorescence and AFM studies combined with chemometric analysis

Colorectal cancer (CRC) is the third most common cancer worldwide. Obesity, alcohol consumption, smoking, high consumption of red or processed meat and a diet with low fibre, fruit, and vegetable intake increase CRC risk. Despite advances in surgery (the basic treatment for recovery), chemotherapy, and radiotherapy, CRC remains the second leading cause of cancer-related deaths in the world. Therefore the social importance of this problem stimulates research aimed at developing new tools for rapid CRC diagnosis and analysis of CRC risk factors. Considering the association between the cholesterol level and CRC, we hypothesize that cholesterol spectroscopic and AFM (atomic force microscopy) studies combined with chemometric analysis can be new, powerful tools used to visualize the cholesterol distribution, estimate cholesterol content and determine its influence on the biochemical and nanomechanical properties of colon cells. Our paper presents the analysis of human colon tissues: normal and cancer and human colon single cells normal CCD18-Co and cancer CaCo-2 in the physiological state and CaCo-2 upon mevastatin supplementation. Based on vibrational features we have shown that Raman spectroscopy and imaging allow cholesterol content in human colon tissues and human colon single cells of both types to be tracked and allow the effectiveness of mevastatin in the mevalonate pathway modulation and disruption of the cholesterol level to be proven. All observations have been confirmed by chemometric analysis including principal component analysis (PCA) and partial least squares discriminant analysis (PLSDA). The positive impact of statins on cholesterol content has also been studied by using fluorescence microscopy and atomic force microscopy (AFM). A significant increase in Young modulus as a mechanomarker for CaCo-2 human cancer colon cells upon mevastatin supplementation compared to CCD18-Co human normal colon cells was observed. This paper is one of the first reports about the use of Raman spectroscopic techniques in cholesterol investigations and the first one about cholesterol investigation using Raman spectroscopy (RS) on human cells ex vivo in the context of colon cancer development.

In vivo Raman spectroscopy in the diagnostics of colon cancer

Early detection and accurate diagnosis of colorectal carcinoma are crucial for successful treatment, yet current methods can be invasive and even inaccurate in some cases. In this work, we present a novel approach for in vivo tissue diagnostics of colorectal carcinoma using Raman spectroscopy. This almost non-invasive technique allows for fast and accurate detection of colorectal carcinoma and its precursors, adenomatous polyps, enabling timely intervention and improved patient outcomes. Using several methods of supervised machine learning, we were able to achieve over 91% accuracy in distinguishing colorectal lesions from healthy epithelial tissue and more than 90% classification accuracy for premalignant adenomatous polyps. Moreover, our models enabled the discrimination of cancerous and precancerous lesions with a mean accuracy of almost 92%. Such results demonstrate the potential of in vivo Raman spectroscopy to become a valuable tool in the fight against colon cancer.

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.

Correlation between human colon cancer specific antigens and Raman spectra. Attempting to use Raman spectroscopy in the determination of tumor markers for colon cancer

Colorectal cancer is the second most common cause of cancer-related deaths worldwide. To follow up on the progression of the disease, tumor markers are commonly used. Here, we report serum analysis based on Raman spectroscopy to provide a rapid cancer diagnosis with tumor markers and two new cell adhesion molecules measured using the ELİSA method. Raman spectra showed higher Raman intensities at 1447 cm^-1 1560 cm^-1, 1665 cm^-1, and 1769 cm^-1, which originated from CH₂ proteins and lipids, amide II and amide I, and CO lipids vibrations. Furthermore, the correlation test showed, that only the CEA colon cancer marker correlated with the Raman spectra. Importantly, machine learning methods showed, that the accuracy of the Raman method in the detection of colon cancer was around 95 %. Obtained results suggest, that Raman shifts at 1302 cm^-1 and 1306 cm^-1 can be used as spectroscopy markers of colon cancer.

Raman Spectroscopy and Imaging Studies of Human Digestive Tract Cells and Tissues-Impact of Vitamin C and E Supplementation

Cancers of digestive tract such as colorectal cancer (CRC) and gastric cancer (GC) are the most commonly detected types of cancer worldwide and their origin can be associated with oxidative stress conditions. Commonly known and followed antioxidants, such as vitamin C and E, are widely considered as potential anti-cancer agents. Raman spectra have great potential in the biochemical characterization of matter based on the fact that each molecule has its own unique vibrational properties. Raman spectroscopy allows to precisely characterize components (proteins, lipids, nucleic acids). The paper presents the application of the Raman spectroscopy technique for the analysis of tissue samples and cells of the human colon and stomach. The main goal of this study is to show the differences between healthy and cancerous tissues from the human digestive tract and human normal and cancer colon and gastric cell lines. The paper presents the spectroscopic characterization of normal colon cells, CCD-18 Co, in physiological and oxidative conditions and effect of oxidative injury of normal colon cells upon supplementation with vitamin C at various concentrations based on Raman spectra. The obtained results were related to the Raman spectra recorded for human colon cancer cells-CaCo-2. In addition, the effect of the antioxidant in the form of vitamin E on gastric cancer cells, HTB-135, is presented and compared with normal gastric cells-CRL-7869. All measured gastric samples were biochemically and structurally characterized by means of Raman spectroscopy and imaging. Statistically assisted analysis has shown that normal, ROS injured and cancerous human gastrointestinal cells can be distinguished based on their unique vibrational properties. ANOVA tests, PCA (Principal Component Analysis) and PLSDA (Partial Least Squares Discriminant Analysis) have confirmed the main role of nucleic acids, proteins and lipids in differentiation of human colon and stomach normal and cancer tissues and cells. The conducted research based on Raman spectra proved that antioxidants in the form of vitamin C and E exhibit anti-cancer properties. In consequence, conducted studies proved that label-free Raman spectroscopy may play an important role in clinical diagnostic differentiation of human normal and cancerous gastrointestinal tissues and may be a source of intraoperative information supporting histopathological analysis.

Molecular Planarization of Raman Probes to Avoid Background Interference for High-Precision Intraoperative Imaging of Tumor Micrometastases and Lymph Nodes

The intraoperative imaging applications of a large number of Raman probes are hampered by the overlap of their signals with the background Raman signals generated by biological tissues. Here, we describe a molecular planarization strategy for adjusting the Raman shift of these Raman probes to avoid interference. Using this strategy, we modify the backbone of thiophene polymer-poly(3-hexylthiophene) (P3HT), and obtain the adjacent thiophene units planarized polycyclopenta[2,1-b;3,4-b']dithiophene (PCPDT). Compared with P3HT whose signal is disturbed by the Raman signal of lipids in tissues, PCPDT exhibits a 60 cm^-1 blueshift in its characteristic signal. Therefore, the PCPDT probe successfully avoids the signal of lipids, and achieves intraoperative imaging of lymph nodes and tumor micrometastasis as small as 0.30 × 0.36 mm. In summary, our study presents a concise molecular planarization strategy for regulating the signal shift of Raman probes, and brings a tunable thiophene polymer probe for high-precision intraoperative Raman imaging.

Improving Minutiae Image of Latent Fingerprint Detection on Non-Porous Surface Materials under UV Light Using Sulfur Doped Carbon Quantum Dots from Magnolia Grandiflora Flower

In this study, carbon quantum dots (CQDs) from Magnolia Grandiflora flower as a carbon precursor were obtained using a hydrothermal method under the optimized conditions affected by various heating times (14, 16, 18, and 20 min) and various electric power inputs (900-1400 W). Then, hydrogen sulfide (H₂S) was added to dope the CQDs under the same manner. The aqueous solution of the S-CQDs were characterized by FTIR, XPS, EDX/SEM, and TEM, with nanoparticle size at around 4 nm. Then, the as-prepared S-CQDs were successfully applied with fine corn starch for detection of minutiae latent fingerprints on non-porous surface materials. It is demonstrated that the minutiae pattern is more clearly seen under commercial UV lamps with a bright blue fluorescence intensity. Therefore, this research has proved that the S-CQDs derived from plant material have a better potential as fluorescent probes for latent fingerprint detection.

Biochemistry and Nanomechanical Properties of Human Colon Cells upon Simvastatin, Lovastatin, and Mevastatin Supplementations: Raman Imaging and AFM Studies

One of the most important areas of medical science is oncology, which is responsible for both the diagnostics and treatment of cancer diseases. Over the years, there has been an intensive development of cancer diagnostics and treatment. This paper shows the comparison of normal (CCD-18Co) and cancerous (CaCo-2) cell lines of the human gastrointestinal tract on the basis of nanomechanical and biochemical properties to obtain information on cancer biomarkers useful in oncological diagnostics. The research techniques used were Raman spectroscopy and imaging and atomic force microscopy (AFM). In addition, the studies also included the effect of the statin compounds—mevastatin, lovastatin, and simvastatin—and their influence on biochemical and nanomechanical changes of cell properties using Raman imaging and AFM techniques. The cytotoxicity of statins was determined using XTT tests.

Facile Microwave Assisted Synthesis of Silver Nanostars for Ultrasensitive Detection of Biological Analytes by SERS

We report a very simple, rapid and reproducible method for the fabrication of anisotropic silver nanostars (AgNS) that can be successfully used as highly efficient SERS substrates for different bioanalytes, even in the case of a near-infra-red (NIR) excitation laser. The nanostars have been synthesized using the chemical reduction of Ag+ ions by trisodium citrate. This is the first research reporting the synthesis of AgNS using only trisodium citrate as a reducing and stabilizing agent. The key elements of this original synthesis procedure are rapid hydrothermal synthesis of silver nanostars followed by a cooling down procedure by immersion in a water bath. The synthesis was performed in a sealed bottom flask homogenously heated and brought to a boil in a microwave oven. After 60 s, the colloidal solution was cooled down to room temperature by immersion in a water bath at 35 °C. The as-synthesized AgNS were washed by centrifugation and used for SERS analysis of test molecules (methylene blue) as well as biological analytes: pharmaceutical compounds with various Raman cross sections (doxorubicin, atenolol & metoprolol), cell lysates and amino acids (methionine & cysteine). UV-Vis absorption spectroscopy, (Scanning) Transmission Electron Microscopy ((S)TEM) and Atomic Force Microscopy (AFM) have been employed for investigating nanostars' physical properties.

Mevastatin in colon cancer by spectroscopic and microscopic methods - Raman imaging and AFM studies

One of the most important areas of medical science is oncology, which is responsible for both the diagnostics and treatment of cancer diseases. Simultaneously one of the main challenges of oncology is the development of modern drugs effective in the fight against cancer. Statins are a group of biologically active compounds with the activity of 3-hydroxy-3-methyl glutaryl-CoA reductase inhibitors, an enzyme catalyzing the reduction of 3-hydroxy-3-methyl-glutaryl-CoA (HMG-CoA) to mevalonic acid. By acting on this enzyme, statins inhibit the endogenous cholesterol synthesis which in turn causes the reduction of its systemic concentrations. However, in vitro and in vivo studies confirm also the cytostatic and cytotoxic effects of statins against various types of cancer cells including colon cancer. In the presented studies the influence of mevastatin on cancerous colon cells CaCo-2 by Raman spectroscopy and imaging is discussed and compared with biochemistry characteristic for normal colon cells CCD-18Co. Based on vibrational features of colon cells: normal cells CCD-18Co, cancerous cells CaCo-2 and cancerous cells CaCo-2 treated by mevastatin in different concentrations and incubation times we have confirmed the influence of this statin on biochemistry composition of cancerous human colon cells. Moreover, the spectroscopic results for colon normal cells and cancerous cells based on data typical for nucleic acids, proteins, lipids have been compared. The cytotoxisity of mevastatin was determined by using XTT tests.

Raman Spectroscopy: A Personalized Decision-Making Tool on Clinicians' Hands for In Situ Cancer Diagnosis and Surgery Guidance

Accurate in situ diagnosis and optimal surgical removal of a malignancy constitute key elements in reducing cancer-related morbidity and mortality. In surgical oncology, the accurate discrimination between healthy and cancerous tissues is critical for the postoperative care of the patient. Conventional imaging techniques have attempted to serve as adjuvant tools for in situ biopsy and surgery guidance. However, no single imaging modality has been proven sufficient in terms of specificity, sensitivity, multiplexing capacity, spatial and temporal resolution. Moreover, most techniques are unable to provide information regarding the molecular tissue composition. In this review, we highlight the potential of Raman spectroscopy as a spectroscopic technique with high detection sensitivity and spatial resolution for distinguishing healthy from malignant margins in microscopic scale and in real time. A Raman spectrum constitutes an intrinsic "molecular finger-print" of the tissue and any biochemical alteration related to inflammatory or cancerous tissue state is reflected on its Raman spectral fingerprint. Nowadays, advanced Raman systems coupled with modern instrumentation devices and machine learning methods are entering the clinical arena as adjunct tools towards personalized and optimized efficacy in surgical oncology.

Granulocyte colony-stimulating factor promotes an aggressive phenotype of colon and breast cancer cells with biochemical changes investigated by single-cell Raman microspectroscopy and machine learning analysis

Granulocyte colony-stimulating factor (G-CSF) is produced at high levels in several cancers and is directly linked with metastasis in gastrointestinal (GI) cancers. In order to further understand the alteration of molecular compositions and biochemical features triggered by G-CSF treatment at molecular and cell levels, we sought to investigate the long term treatment of G-CSF on colon and breast cancer cells measured by label-free, non-invasive single-cell Raman microspectroscopy. Raman spectrum captures the molecule-specific spectral signatures ("fingerprints") of different biomolecules presented on cells. In this work, mouse breast cancer line 4T1 and mouse colon cancer line CT26 were treated with G-CSF for 7 weeks and subsequently analyzed by machine learning based Raman spectroscopy and gene/cytokine expression. The principal component analysis (PCA) identified the Raman bands that most significantly changed between the control and G-CSF treated cells. Notably, here we proposed the concept of aggressiveness score, which can be derived from the posterior probability of linear discriminant analysis (LDA), for quantitative spectral analysis of tumorigenic cells. The aggressiveness score was effectively applied to analyze and differentiate the overall cell biochemical changes of G-CSF-treated two model cancer cells. All these tumorigenic progressions suggested by Raman analysis were confirmed by pro-tumorigenic cytokine and gene analysis. A high correlation between gene expression data and Raman spectra highlights that the machine learning based non-invasive Raman spectroscopy offers emerging and powerful tools to better understand the regulation mechanism of cytokines in the tumor microenvironment that could lead to the discovery of new targets for cancer therapy.

Tracking of the biochemical changes upon pleomorphic adenoma progression using vibrational microspectroscopy

Head and neck tumors can be very challenging to treat because of the risk of problems or complications after surgery. Therefore, prompt and accurate diagnosis is extremely important to drive appropriate treatment decisions, which may reduce the chance of recurrence. This paper presents the original research exploring the feasibility of Fourier transform infrared (FT-IR) and Raman spectroscopy (RS) methods to investigate biochemical alterations upon the development of the pleomorphic adenoma. Principal component analysis (PCA) was used for a detailed assessment of the observed changes and to determine the spectroscopic basis for salivary gland neoplastic pathogenesis. It is implied that within the healthy margin, as opposed to the tumoral tissue, there are parts that differ significantly in lipid content. This observation shed new light on the crucial role of lipids in tissue physiology and tumorigenesis. Thus, a novel approach that eliminates the influence of lipids on the elucidation of biochemical changes is proposed. The performed analysis suggests that the highly heterogeneous healthy margin contains more unsaturated triacylglycerols, while the tumoral section is rich in proteins. The difference in protein content was also observed for these two tissue types, i.e. the healthy tissue possesses more proteins in the anti-parallel β-sheet conformation, whereas the tumoral tissue is dominated by proteins rich in unordered random coils. Furthermore, the pathogenic tissue shows a higher content of carbohydrates and reveals noticeable differences in nucleic acid content. Finally, FT-IR and Raman spectroscopy methods were proposed as very promising methods in the discrimination of tumoral and healthy tissues of the salivary gland.

Non-invasive diagnosis of colorectal cancer by Raman spectroscopy: Recent developments in liquid biopsy and endoscopy approaches

Colorectal cancer (CRC) is the third most common cancer diagnosed globally and is also one of the leading causes of cancer deaths in both men and women. The progression of CRC is slow and is often contained in colon but the risk increases with age. Based on the high certainty that the net benefit of screening in an age group is substantial, screening for CRC is recommended beginning at the age of 50. Currently, most of the incidence is concentrated in developed countries but the rate is increasing rapidly in developing geographies. Detecting CRC at an early stage is critical to reduce morbidity and mortality. Colonoscopy is the most preferred screening method but not very widely implemented due to practical considerations such as cost involved, lack of personnel and facility. To address these concerns, Raman spectroscopy (RS) has been suggested as a viable alternative due to its potential as a rapid non-invasive diagnostic tool. Recently, several studies have been reported but many variations of RS applications in CRC exists and are not well understood by non-specialists. This review focuses particularly on developments of Raman based liquid biopsy and endoscopic studies in order to throw light on each of their significance and limitations. Necessary developments in the future to translate RS into a clinical tool for screening and diagnosis of CRC are also briefly presented.

Feature fusion of Raman chemical imaging and digital histopathology using machine learning for prostate cancer detection

The diagnosis of prostate cancer is challenging due to the heterogeneity of its presentations, leading to the over diagnosis and treatment of non-clinically important disease. Accurate diagnosis can directly benefit a patient's quality of life and prognosis. Towards addressing this issue, we present a learning model for the automatic identification of prostate cancer. While many prostate cancer studies have adopted Raman spectroscopy approaches, none have utilised the combination of Raman Chemical Imaging (RCI) and other imaging modalities. This study uses multimodal images formed from stained Digital Histopathology (DP) and unstained RCI. The approach was developed and tested on a set of 178 clinical samples from 32 patients, containing a range of non-cancerous, Gleason grade 3 (G3) and grade 4 (G4) tissue microarray samples. For each histological sample, there is a pathologist labelled DP-RCI image pair. The hypothesis tested was whether multimodal image models can outperform single modality baseline models in terms of diagnostic accuracy. Binary non-cancer/cancer models and the more challenging G3/G4 differentiation were investigated. Regarding G3/G4 classification, the multimodal approach achieved a sensitivity of 73.8% and specificity of 88.1% while the baseline DP model showed a sensitivity and specificity of 54.1% and 84.7% respectively. The multimodal approach demonstrated a statistically significant 12.7% AUC advantage over the baseline with a value of 85.8% compared to 73.1%, also outperforming models based solely on RCI and mean and median Raman spectra. Feature fusion of DP and RCI does not improve the more trivial task of tumour identification but does deliver an observed advantage in G3/G4 discrimination. Building on these promising findings, future work could include the acquisition of larger datasets for enhanced model generalization.

Morpho-Molecular Metabolic Analysis and Classification of Human Pituitary Gland and Adenoma Biopsies Based on Multimodal Optical Imaging

Pituitary adenomas count among the most common intracranial tumors. During pituitary oncogenesis structural, textural, metabolic and molecular changes occur which can be revealed with our integrated ultrahigh-resolution multimodal imaging approach including optical coherence tomography (OCT), multiphoton microscopy (MPM) and line scan Raman microspectroscopy (LSRM) on an unprecedented cellular level in a label-free manner. We investigated 5 pituitary gland and 25 adenoma biopsies, including lactotroph, null cell, gonadotroph, somatotroph and mammosomatotroph as well as corticotroph. First-level binary classification for discrimination of pituitary gland and adenomas was performed by feature extraction via radiomic analysis on OCT and MPM images and achieved an accuracy of 88%. Second-level multi-class classification was performed based on molecular analysis of the specimen via LSRM to discriminate pituitary adenomas subtypes with accuracies of up to 99%. Chemical compounds such as lipids, proteins, collagen, DNA and carotenoids and their relation could be identified as relevant biomarkers, and their spatial distribution visualized to provide deeper insight into the chemical properties of pituitary adenomas. Thereby, the aim of the current work was to assess a unique label-free and non-invasive multimodal optical imaging platform for pituitary tissue imaging and to perform a multiparametric morpho-molecular metabolic analysis and classification.

Design of a Multimodal Imaging System and Its First Application to Distinguish Grey and White Matter of Brain Tissue. A Proof-of-Concept-Study

Multimodal imaging gains increasing popularity for biomedical applications. This article presents the design of a novel multimodal imaging system. The centerpiece is a light microscope operating in the incident and transmitted light mode. Additionally, Raman spectroscopy and VIS/NIR reflectance spectroscopy are adapted. The proof-of-concept is realized to distinguish between grey matter (GM) and white matter (WM) of normal mouse brain tissue. Besides Raman and VIS/NIR spectroscopy, the following optical microscopy techniques are applied in the incident light mode: brightfield, darkfield, and polarization microscopy. To complement the study, brightfield images of a hematoxylin and eosin (H&E) stained cryosection in the transmitted light mode are recorded using the same imaging system. Data acquisition based on polarization microscopy and Raman spectroscopy gives the best results regarding the tissue differentiation of the unstained section. In addition to the discrimination of GM and WM, both modalities are suited to highlight differences in the density of myelinated axons. For Raman spectroscopy, this is achieved by calculating the sum of two intensity peak ratios (I2857 + I2888)/I2930 in the high-wavenumber region. For an optimum combination of the modalities, it is recommended to apply the molecule-specific but time-consuming Raman spectroscopy to smaller regions of interest, which have previously been identified by the microscopic modes.

Oxidative stress induced by tBHP in human normal colon cells by label free Raman spectroscopy and imaging. The protective role of natural antioxidants in the form of β-carotene

The present study aimed to investigate the protective effect of β-carotene on the oxidative stress injury of human normal colon cell line CCD-18Co triggered by tert-butyl hydroperoxide (tBHP). XTT examination was used to determine cell viability after β-carotene supplementation and to determine the optimal concentration of antioxidant in spectroscopic studies. Cell biochemistry for the CCD-18Co control group, after tBHP addition and for cells in the β-carotene-tBHP model was studied using label-free Raman microspectroscopy. Results for stress treated CCD-18Co human colon normal cells and human colon cancer cells Caco-2 based on vibration features were also compared. Pretreatment with β-carotene alleviated damage in CCD-18Co human normal colon cells induced by tBHP and showed the preventative effect on cell apoptosis. Treatment with β-carotene altered the level of ROS investigated based on intensities of Raman peaks typical for lipids, proteins and nucleic acids. The present study confirmed the antioxidant, protective role of β-carotene against ROS by using spectroscopic label-free Raman techniques.

Nanoscale infrared probing of amyloid formation within the pleomorphic adenoma tissue

BACKGROUND

The process of malignant transformations of many tumour cases is still unclear and more specific experimental approaches are necessary. The detailed identification of the pathological changes may help in the therapy progression through the development of drugs with more selective action.

METHODS

In this study, the AFM-IR nanospectroscopy was applied for the first time to the pleomorphic adenoma (TM) and the marginal tissue characterizations. In order to verify the obtained spectral information, conventional FT-IR investigations were also performed.

RESULTS

The AFM-IR data (topographies, intensity maps, and spectra) show structural changes observed for the margin and TM samples. Additionally, within the tumour tissue the fibril-like areas, characteristic for amyloid diseases, were distinguished.

CONCLUSIONS

The application of AFM-IR allows to determine changes in the protein secondary structures between the fibrils and the regions outside them. It has been proved that, for the former areas, the α-helix/random coil/ β-sheet components dominate, while for the latter regions the α-helix/random coil indicate the main contribution to the protein composition.

GENERAL SIGNIFICANCE

The FT-IR results remain in good agreement with the AFM-IR data recorded for the areas outside the fibrils of the TM. This observation confirms that by means of the conventional FT-IR method the identification of the considered fibrils structure would be impossible. Only application of the AFM-IR nanospectroscopy allow for characterization and visualization of the fibrillization process occurring within the investigated tumour tissue.

Zinc Phthalocyanine Photochemistry by Raman Imaging, Fluorescence Spectroscopy and Femtosecond Spectroscopy in Normal and Cancerous Human Colon Tissues and Single Cells

Photodynamic therapy is a clinically approved alternative method for cancer treatment in which a combination of nontoxic drugs known as photosensitizers and oxygen is used. Despite intensive investigations and encouraging results, zinc phthalocyanines (ZnPcs) have not yet been approved as photosensitizers for clinical use. Label-free Raman imaging of nonfixed and unstained normal and cancerous colon human tissues and normal human CCD18-Co and cancerous CaCo-2 cell lines, without and after adding ZnPcS4 photosensitizer, was analyzed. The biochemical composition of normal and cancerous colon tissues and colon cells without and after adding ZnPcS4 at the subcellular level was determined. Analyzing the fluorescence/Raman signals of ZnPcS4, we found that in normal human colon tissue samples, in contrast to cancerous ones, there is a lower affinity to ZnPcS4 phthalocyanine. Moreover, a higher concentration in cancerous tissue was concomitant with a blue shift of the maximum peak position specific for the photosensitizer from 691-695 nm to 689 nm. Simultaneously for both types of samples, the signal was observed in the monomer region, confirming the excellent properties of ZnPcS4 for photo therapy (PDT). For colon cell experiments with a lower concentration of ZnPcS4 photosensitizer, c = 1 × 10-6 M, the phthalocyanine was localized in mitochondria/lipid structures; for a higher concentration, c = 9 × 10-6 M, localization inside the nucleus was predominant. Based on time-resolved experiments, we found that ZnPcS4 in the presence of biological interfaces features longer excited-state lifetime photosensitizers compared to the aqueous solution and bare ZnPcS4 film on CaF2 substrate, which is beneficial for application in PDT.

HPV Infection Significantly Accelerates Glycogen Metabolism in Cervical Cells with Large Nuclei: Raman Microscopic Study with Subcellular Resolution

Using Raman microscopy, we investigated epithelial cervical cells collected from 96 women with squamous cell carcinoma (SCC) or belonging to groups I, IIa, IIID-1 and IIID-2 according to Munich III classification (IIID-1 and IIID-2 corresponding to Bethesda LSIL and HSIL groups, respectively). All women were tested for human papillomavirus (HPV) infection using PCR. Subcellular resolution of Raman microscopy enabled to understand phenotypic differences in a heterogeneous population of cervical cells in the following groups: I/HPV⁻, IIa/HPV⁻, IIa/HPV⁻, LSIL/HPV⁻, LSIL/HPV⁺, HSIL/HPV⁻, HSIL/HPV⁺ and cancer cells (SCC/HPV⁺). We showed for the first time that the glycogen content in the cytoplasm decreased with the nucleus size of cervical cells in all studied groups apart from the cancer group. For the subpopulation of large-nucleus cells HPV infection resulted in considerable glycogen depletion compared to HPV negative cells in IIa, LSIL (for both statistical significance, ca. 45%) and HSIL (trend, 37%) groups. We hypothesize that accelerated glycogenolysis in large-nucleus cells may be associated with the increased protein metabolism for HPV positive cells. Our work underlines unique capabilities of Raman microscopy in single cell studies and demonstrate potential of Raman-based methods in HPV diagnostics.