Nondestructive molecular imaging by Raman spectroscopy vs. marker detection by MALDI IMS for an early diagnosis of HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide with a steadily increasing mortality rate. Fast diagnosis at early stages of HCC is of key importance for the improvement of patient survival rates. In this regard, we combined two imaging techniques with high potential for HCC diagnosis in order to improve the prediction of liver cancer. In detail, Raman spectroscopic imaging and matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS) were applied for the diagnosis of 36 HCC tissue samples. The data were analyzed using multivariate methods, and the results revealed that Raman spectroscopy alone showed a good capability for HCC tumor identification (sensitivity of 88% and specificity of 80%), which could not be improved by combining the Raman data with MALDI IMS. In addition, it could be shown that the two methods in combination can differentiate between well-, moderately- and poorly-differentiated HCC using a linear classification model. MALDI IMS not only classified the HCC grades with a sensitivity of 100% and a specificity of 80%, but also showed significant differences in the expression of glycerophospholipids and fatty acyls during HCC differentiation. Furthermore, important differences in the protein, lipid and collagen compositions of differentiated HCC were detected using the model coefficients of a Raman based classification model. Both Raman and MALDI IMS, as well as their combination showed high potential for resolving concrete questions in liver cancer diagnosis.

Towards an Interpretable Classifier for Characterization of Endoscopic Mayo Scores in Ulcerative Colitis Using Raman Spectroscopy.

Ulcerative colitis (UC) is one of the main types of chronic inflammatory diseases that affect the bowel, but its pathogenesis is yet to be completely defined. Assessing the disease activity of UC is vital for developing a personalized treatment. Conventionally, the assessment of UC is performed by colonoscopy and histopathology. However, conventional methods fail to retain biomolecular information associated to the severity of UC and are solely based on morphological characteristics of the inflamed colon. Furthermore, assessing endoscopic disease severity is limited by the requirement for experienced human reviewers. Therefore, this work presents a nondestructive biospectroscopic technique, for example, Raman spectroscopy, for assessing endoscopic disease severity according to the four-level Mayo subscore. This contribution utilizes multidimensional Raman spectroscopic data to generate a predictive model for identifying colonic inflammation. The predictive modeling of the Raman spectroscopic data is performed using a one-dimensional deep convolutional neural network (1D-CNN). The classification results of 1D-CNN achieved a mean sensitivity of 78% and a mean specificity of 93% for the four Mayo endoscopic scores. Furthermore, the results of the 1D-CNN are interpreted by a first-order Taylor expansion, which extracts the Raman bands important for classification. Additionally, a regression model of the 1D-CNN model is constructed to study the extent of misclassification and border-line patients. The overall results of Raman spectroscopy with 1D-CNN as a classification and regression model show a good performance, and such a method can serve as a complementary method for UC analysis.

Transcriptional Suppression of the NLRP3 Inflammasome and Cytokine Release in Primary Macrophages by Low-Dose Anthracyclines.

Tissue-resident macrophages play critical roles in controlling homeostasis, tissue repair, and immunity. Inflammatory macrophages can sustain tissue damage and promote the development of fibrosis during infections and sterile tissue injury. The NLRP3 inflammasome and its effector cytokine IL-1ß have been identified as important mediators of fibrosis. Epirubicin, an anthracycline topoisomerase II inhibitor, has been reported to inhibit myeloid inflammatory cytokine production and to promote tissue tolerance following bacterial infection. We investigated the anti-inflammatory properties of epirubicin on the NLRP3 inflammasome and TLR4-mediated inflammation in PMA-primed THP-1 and in primary human peritoneal macrophages (PM). Low-dose epirubicin at non-cytotoxic doses downregulated NLRP3 inflammasome components and reduced the release of cleaved caspase-1, bioactive IL-1ß, and TNF-α following NLRP3 activation in a dose-dependent fashion. In addition, epirubicin attenuated inflammatory macrophage responses after TLR4 and TLR2 ligation. These anti-inflammatory effects were not mediated by the induction of autophagy or altered MAPK signaling, but as the result of a global transcriptional suppression of LPS-dependent genes. Epirubicin-treated macrophages displayed reduced acetylation of histone 3 lysine 9 (H3K9ac), suggesting anti-inflammatory epigenetic imprinting as one underlying mechanism.

Biodegradable Porous Silicon Nanocontainers as an Effective Drug Carrier for Regulation of the Tumor Cell Death Pathways.

Nanocontainers based on solid materials have great potential for drug delivery applications. However, since nanocontainer-mediated delivery can alter the drug internalization pathways and metabolism, it is important to find out what are the mechanisms of cancer cell death induced by nanocontainers and, moreover, is it possible to regulate them. Here, we report on the detailed investigation of the internalization kinetics and intracellular spatial distribution of porous silicon nanoparticles (PSi NPs) loaded with doxorubicin (DOX) and response of cancer cells to treatment with DOX-PSi NPs as well as studies of nanocontainer biodegradation by applying various microscopy methods, Raman microspectroscopy and biological experiments with cancer cells of different etiology. The obtained results revealed the absence of toxicity of unloaded PSi NPs to cancer cells up to a concentration of 700 µg/mL during the prolonged incubation time. Thus, given the fact that the nanocontainers themselves are not toxic, it is easy to adjust the dose of the drug that they deliver to the cells. It is shown, that the treatment with DOX-loaded PSi NPs more efficiently eliminates cancer cells in comparison with the free DOX. At the same time, the obtained results demonstrate the possibility of regulating the initiation of apoptosis or necrosis in tumor cells after treatment with different concentrations of DOX-PSi NPs, as revealed by the analysis of the caspase-3 processing, the accumulation of sub-G1 cell fraction, and morphological changes determined by electron and light microscopy. The obtained results are important for future applications of porous silicon nanocontainers in drug delivery for apoptotic pathway-targeted cancer therapy.

A droplet-based microfluidic chip as a platform for leukemia cell lysate identification using surface-enhanced Raman scattering.

A new approach is presented for cell lysate identification which uses SERS-active silver nanoparticles and a droplet-based microfluidic chip. Eighty-nanoliter droplets are generated by injecting silver nanoparticles, KCl as aggregation agent, and cell lysate containing cell constituents, such as nucleic acids, carbohydrates, metabolites, and proteins into a continuous flow of mineral oil. This platform enables accurate mixing of small volumes inside the meandering channels of the quartz chip and allows acquisition of thousands of SERS spectra with 785 nm excitation at an integration time of 1 s. Preparation of three batches of three leukemia cell lines demonstrated the experimental reproducibility. The main advantage of a high number of reproducible spectra is to apply statistics for large sample populations with robust classification results. A support vector machine with leave-one-batch-out cross-validation classified SERS spectra with sensitivities, specificities, and accuracies better than 99% to differentiate Jurkat, THP-1, and MONO-MAC-6 leukemia cell lysates. This approach is compared with previous published reports about Raman spectroscopy for leukemia detection, and an outlook is given for transfer to single cells. A quartz chip was designed for SERS at 785 nm excitation. Principal component analysis of SERS spectra clearly separates cell lysates using variations in band intensity ratios.