Hesham Kamaleldin Yosef

Studying human skin biology can aid in understanding the pathophysiology of skin diseases and developing novel therapies, including tissue engineering approaches. Among various optical and spectroscopic techniques, Raman micro-spectroscopy stands out. This non-invasive method requires minimal sample preparation and provides molecular-level information on healthy and diseased cell types. The following chapter aims to provide a comprehensive guide to the basic methods of Raman micro-spectroscopy analysis of human epidermal samples from the perspective of their biochemical-molecular relationship, without the need for a deep and specialized knowledge in the field of spectroscopy. We do this based on two distinct examples: (1) Unstained cell subpopulations identified by hierarchical cluster analysis are compared with antibody treated sorted cell populations, and (2) skin cell type-specific molecular features are determined, and the composition of unknown cellular mixtures is revealed.

Microtia is a congenital condition of abnormal development of the outer ear. Tissue engineering of the ear is an alternative treatment option for microtia patients. However, for this approach, the identification of high regenerative cartilage progenitor cells is of vital importance. Raman analysis provides a novel, non-invasive, label-free diagnostic tool to detect distinctive biochemical features of single cells or tissues. Using micro-Raman spectroscopy, we were able to distinguish and characterize the particular molecular fingerprints of differentiated chondrocytes and perichondrocytes and their respective progenitors isolated from healthy individuals and microtia patients. We found that microtia chondrocytes exhibited lower lipid concentrations in comparison to healthy cells, thus indicating the importance of fat storage. Moreover, we suggest that collagen is a useful biomarker for distinguishing between populations obtained from the cartilage and perichondrium because of the higher spectral contributions of collagen in the chondrocytes compared to perichondrocytes from healthy individuals and microtia patients. Our results represent a contribution to the identification of cell markers that may allow the selection of specific cell populations for cartilage tissue engineering. Moreover, the observed differences between microtia and healthy cells are essential for gaining better knowledge of the cause of microtia. It can be useful for designing novel treatment options based on further investigations of the discovered biochemical substrate alterations.

The basal layer of human interfollicular epidermis has been described to harbour both quiescent keratinocyte stem cells and a transit amplifying cell population that maintains the suprabasal epidermal layers. We performed immunofluorescence analyses and revealed that the main proliferative keratinocyte pool in vivo resides suprabasally. We isolated from the human epidermis two distinct cell populations, the basal and the suprabasal keratinocytes, according to the expression of integrin β4 (iβ4). We compared basal iβ4⁺ or suprabasal iβ4⁻ keratinocytes with respect to their proliferation and colony-forming ability and their Raman spectral properties. In addition, we generated dermo–epidermal substitutes using freshly isolated and sorted basal iβ4⁺ or suprabasal iβ4⁻ keratinocytes and transplanted them on immuno-compromised rats. We show that suprabasal iβ4⁻ keratinocytes acquire a similar proliferative capacity as basal iβ4⁺ keratinocytes after two weeks of culture in vitro, with expression of high levels of iβ4 and downregulation of K10 expression. In addition, both basal iβ4⁺ and suprabasal iβ4⁻ keratinocytes acquire authentic self-renewing properties during the in vitro 3D-culture phase and are able to generate and maintain a fully stratified epidermis for 16 weeks in vivo. Therefore, against the leading dogma, we propose that human suprabasal keratinocytes can retro-differentiate into true basal stem cells in a wound situation and/or when in contact with the basement membrane.

In endometriosis, an aberrant immune response in the peritoneal environment is evident, but the underlying mechanism remains unclear. In recent years, some emerging data support an important role for the changes in intracellular metabolic pathways of immune cells in controlling their function. In this study, we aim to investigate the phenotypic and immunometabolism profiling of peritoneal fluid cells in endometriosis patients. By flow cytometry, our results show phenotypic profiling of peritoneal fluid cells with higher percentages of CD45⁺, CD3⁺, CD3⁺CD8⁺, CD3⁺CD56^+, and CD14⁺CD68⁺ cells and the ratio of M2 to M1 macrophages but less CD14⁻CD86⁺ dendritic cells in endometriosis when compared with control. Label‐free single‐cell Raman trapping analysis shows intracellular changes in decreased collagen, proteins and lipids levels in CD45⁺ immune cells in endometriosis. In the supernatant of peritoneal fluid from endometriosis patients, Raman results reveal extracellular decreased protein and carbohydrate levels but increased lipid and fatty acid levels. Especially, Raman bands indicate both intracellular and extracellular levels of cholesterol and carotenoids decrease in endometriosis patients when compared with controls. This study provides immunometabolism features of the specific microenvironment in the peritoneal cavity and identifies some biological molecules associated with immune dysfunction in endometriosis, which may offer new clues for understanding disease pathology and therapeutic targets.

Raman microscopy is an emerging tool in biomedicine. It provides label-free and non-invasive analysis of biological cells. Due to its high biochemical specificity, Raman spectroscopy can be used to acquire spectral fingerprints that allow characterizing cells types and states. Here, we present a methodological approach for implementing Raman microscopy in skin cell measurements. Raman spectra can clearly identify keratinocytes, fibroblasts, and melanocytes cells that are involved in the production of autologous skin grafts. Consequently, Raman microscopy is a promising tool that can be used to analyze single cells and to test the quality of therapeutic cell products.

Cervical cancer is the fourth most common cancer in women worldwide and early detection of its pre-cancer lesions can decrease the mortality. Cytopathology, HPV testing, and histopathology are the most commonly used tools in clinical practice. However, these methods suffer from many limitations such as subjectivity, cost, and time. Therefore, there is an unmet clinical need for developing new non-invasive methods for the early detection of cervical cancer. Here, a novel non-invasive, fast, and label-free approach with high accuracy is presented using liquid-based cytology, Pap-smears. CARS and SHG/TPF imaging at one wavenumber of the Pap-smears from patients with specimen negative for intraepithelial lesion (NILM), low-grade (LSIL) and high-grade (HSIL) squamous intraepithelial lesions was acquired. The normal, LSIL, and HSIL cells were selected based on the ratio of the nucleus to the cytoplasm and cell morphology. Raman spectral imaging of single cells from the same smears was also performed providing integral biochemical information of cells. Deep convolutional neural networks (DCNNs) were trained independently with CARS, SHG/TPF, and Raman images, taking into account both morpho-textural and spectral information. DCNNs based on CARS, SHG/TPF, or Raman images have discriminated between the normal and cancerous Pap-smears with 100% accuracy. These results demonstrate that CARS/SHG/TPF microscopy has a prospective use as a label-free imaging technique for fast screening of a large number of cells in cytopathological samples

In recent years, many subcellular proteins have emerged as promising therapeutic targets in oncology. One crucial target is the epidermal growth factor receptor. Inhibition of this receptor has significantly improved the survival rate of patients for many cancers. However, oncogenic mutations such as B-RAF^V600E have rendered tumours resistant to this therapeutic approach. Therefore, this mutation has emerged as a potential target for cancer therapy. Sorafenib is developed to overcome the B-RAF^V600E mutation and restore the response of the mutated tumour to therapy. Here, we explore the efficacy and distribution of sorafenib at a cellular level using colon cancer cell lines with B-RAF^V600E or K-RAS^G12V mutations. The Raman results detected significant sorafenib-induced spectral differences in both cell lines. In addition, the western blot and real-time cell analysis in vitro assays revealed that the ERK phosphorylation and the cellular proliferation of cells are inhibited, respectively, in the sorafenib-treated cells. Thus, the observed Raman spectral changes illustrate the potent effect of sorafenib on cells despite the presence of the B-RAF^V600E or K-RAS^G12V mutations. These results are in agreement with the clinical studies, where patients with the B-RAF^V600E mutation respond to sorafenib. Furthermore, the Raman spectral imaging results have shown the uptake and the distribution of sorafenib in colon cancer cells with the B-RAF^V600E mutation through its label-free marker bands in the fingerprint region. The present results of sorafenib efficacy and distribution in cells demonstrate the potential of Raman micro-spectroscopy as the in vitro assay for the assessment of drugs, which is important in drug discovery.

Monitoring the drug efficacy or resistance in vitro is usually carried out by measuring the response of single few proteins. However, observation of single proteins instead of an integral cell response may lead to results that are not consistent with patient’s response to a drug. We present a Raman spectroscopic method that detects the integral cell response to drugs such as tyrosine kinase inhibitors (TKIs). Non-small cell lung cancer (NSCLC) patients with EGFR mutations develop acquired resistance to first (erlotinib)- and third (osimertinib)-generation TKIs. Large erlotinib-induced differences were detected by Raman micro-spectroscopy in NSCLC cells without T790M EGFR mutation but not in cells with this mutation. Additionally, Raman difference spectra detected the response of NSCLC cells with T790M EGFR mutation to second- (neratinib) and third-generation (osimertinib) TKIs, and the resistance of cells with T790M/C797S EGFR mutation to osimertinib. Thus, the in vitro Raman results indicated that NSCLC cells with T790M and T790M/C797S EGFR mutations are resistant to erlotinib- and osimertinib, respectively, consistent with the observed responses of patients. This study shows the potential of Raman micro-spectroscopy to monitor drug resistance and opens a new door to in vitro companion diagnostics for screening personalized therapies.

The image displays the construction of the first layers of a deep convolutional neural network for classifying Raman microscopic images of urotheleal cells as either cancerous or normal. The input layer is obtained by the intensity images of two selected wavenumbers, indicated as red and green, respectively. Deeper layers are constructed by convolution operations indicated in the yellow box. The final layer (not shown) will distinguish the two cell types.Further details can be found in the article by Sascha D. Krauß, Raphael Roy, Hesham K. Yosef, et al. (e201800022) image