Alterations in lipid metabolism accompanied by changes in protein and carotenoid content as spectroscopic markers of human T cell activation.

This work aims to understand better the mechanism of cellular processes accompanying the activation of human T cells and to develop a novel, fast, label-free approach to identify molecular biomarkers for this process. The standard methodology for confirming the activation state of T cells is based on flow cytometry and using antibodies recognizing activation markers. The method provide high specificity detection but may be susceptible to background staining or non-specific secondary antibody reactions. Here, we evaluated the potential of Raman-based molecular imaging in distinguishing non-activated and activated human T cells. Confocal Raman microscopy was performed on T cells followed by chemometrics to obtain comprehensive molecular information, while Stimulated Raman Scattering imaging was used to quickly provide high-resolution images of selected cellular components of activated and non-activated cells. For the first time, carotenoids, lipids, and proteins were shown to be important biomarkers of T-cell activation. We found that T-cell activation was accompanied by lipid accumulation and loss of carotenoid content. Our findings on the biochemical, morphological, and structural changes associated with activated mature T cells provide insights into the molecular changes that occur during therapeutic manipulation of the immune response. The methodology for identifying activated T cells is based on a novel imaging method and supervised and unsupervised chemometrics. It unambiguously identifies specific and unique molecular changes without the need for staining, fixation, or any other sample preparation.

Raman Spectroscopy as a Research and Diagnostic Tool in Clinical Hematology and Hematooncology.

Raman spectroscopy is a molecular spectroscopic technique able to provide detailed information about the chemical structure, phase, crystallinity, and molecular interactions of virtually any analyzed sample. Although its medical applications have been studied for several decades, only recent advances in microscopy, lasers, detectors, and better understanding of the principles of the Raman effect have successfully expanded its applicability to clinical settings. The promise of a rapid, label-free diagnostic method able to evaluate the metabolic status of a cell in vivo makes Raman spectroscopy particularly attractive for hematology and oncology. Here, we review widely studied hematological applications of Raman spectroscopy such as leukocyte activation status, evaluation of treatment response, and differentiation between cancer and non-malignant cells, as well as its use in still unexplored areas in hematology. We also discuss limitations and challenges faced by Raman spectroscopy-based diagnostics as well as recent advances and modifications of the method aimed to increase its applicability to clinical hematooncology.

Automatic subtyping of Diffuse Large B-cell Lymphomas (DLBCL): Raman-based genetic and metabolic classification.

Diffuse large B-cell lymphoma (DLBCL), the most common non-Hodgkin's lymphoma in adults, is a genetically and metabolically heterogeneous group of aggressive malignancies. The complexity of their molecular composition and the variability in clinical presentation make clinical diagnosis and treatment selection a serious challenge. The challenge is therefore to quickly and correctly classify DLBCL cells. In this work, we show that Raman imaging is a tool with high diagnostic potential, providing unique information about the biochemical components of tumor cells and their metabolism. We present models of classification of lymphoma cells based on their Raman spectra. The models automatically and efficiently identify DLBCL cells and assign them to a given cell-of-origin (COO) subtype (activated B cell-like (ABC) or germinal center B cell-like (GCB)) or, respectively, to a comprehensive cluster classification (CCC) subtype (OxPhos/non-OxPhos). In addition, we describe each lymphoma subtype by its unique spectral profile, linking it to biochemical, genetic, or metabolic features.

Thyroid gland in chronic obstructive pulmonary disease.

The risk of chronic obstructive pulmonary disease (COPD), as well as thyroid diseases increases with age. COPD is a common systemic disease associated with chronic inflammation. Many endocrinological disorders, including thyroid gland diseases are related to systemic inflammation. Epidemiological studies suggest that patients with COPD are at higher risk of thyroid disorders. These associations are not well-studied and thyroid gland diseases are not included on the broadly acknowledged list of COPD comorbidities. They may seriously handicap quality of life of COPD patients. Unfortunately, the diagnosis may be difficult, as many signs are masked by the symptoms of the index disease. The comprehension of the correlation between thyroid gland disorders and COPD may contribute to better care of patients. In this review, we attempt to revise available literature describing existing links between COPD and thyroid diseases.