Biodistribution of Mesenchymal Stromal Cells Labeled with [89Zr]Zr-Oxine in Local Radiation Injuries in Laboratory Animals.

BACKGROUND: Tracking the migration pathways of living cells after their introduction into a patient's body is a topical issue in the field of cell therapy. Questions related to studying the possibility of long-term intravital biodistribution of mesenchymal stromal cells in the body currently remain open. METHODS: Forty-nine laboratory animals were used in the study. Modeling of local radiation injuries was carried out, and the dynamics of the distribution of mesenchymal stromal cells labeled with [89Zr]Zr-oxine in the rat body were studied. RESULTS: the obtained results of the labelled cell distribution allow us to assume that this procedure could be useful for visualization of local radiation injury using positron emission tomography. However, further research is needed to confirm this assumption. CONCLUSIONS: intravenous injection leads to the initial accumulation of cells in the lungs and their subsequent redistribution to the liver, spleen, and kidneys. When locally injected into tissues, mesenchymal stromal cells are not distributed systemically in significant quantities.

Nanoribbon Biosensor-Based Detection of microRNA Markers of Prostate Cancer.

Prostate cancer (PC) is one of the major causes of death among elderly men. PC is often diagnosed later in progression due to asymptomatic early stages. Early detection of PC is thus crucial for effective PC treatment. The aim of this study is the simultaneous highly sensitive detection of a palette of PC-associated microRNAs (miRNAs) in human plasma samples. With this aim, a nanoribbon biosensor system based on "silicon-on-insulator" structures (SOI-NR biosensor) has been employed. In order to provide biospecific detection of the target miRNAs, the surface of individual nanoribbons has been sensitized with DNA oligonucleotide probes (oDNA probes) complementary to the target miRNAs. The lowest concentration of nucleic acids, detectable with our biosensor, has been found to be 1.1 × 10-17 M. The successful detection of target miRNAs, isolated from real plasma samples of PC patients, has also been demonstrated. We believe that the development of highly sensitive nanotechnology-based biosensors for the detection of PC markers is a step towards personalized medicine.

Determination of Heterogeneous Proteomic and Metabolomic Response in anti-TNF and anti-IL-6 Treatment of Patients with Rheumatoid Arthritis.

Reduction in tumor necrosis factor (αTNF) and interleukin-6 (IL-6) activities is a widely utilized strategy for the treatment of rheumatoid arthritis (RA) with a high success rate. Despite both schemes targeting the deprivation of inflammatory reactions caused by the excessive activity of cytokines, their mechanisms of action and the final output are still unequal. This was a comparative longitudinal study that lasted for 24 weeks and aimed to find the answer to why the two schemes of therapy can pass out of proportion in attitude of their efficiency. What are the differences in metabolic and proteomic responses among patients who were being treated by either the anti-TNF or anti-IL-6 strategy? We found increased levels of immunoglobulins A and G (more than 2-fold in anti-IL-6 and more than 4-5-fold in anti-TNF groups) at the final stage (24 weeks) of monitoring but the most profound increase was determined for µ-chains of immunoglobulins in both groups of study. Metabolomic changes displayed main alterations with regard to arginine metabolism and collagen maintenance, where arginine increased 8.86-fold (p < 0.001) in anti-TNF and 5.71-fold (p < 0.05) in anti-IL-6 groups but patients treated by the anti-TNF scheme suffered a higher depletion of arginine before the start of therapy. Some indicators of matrix and bone tissue degradation also increased 4-hydroxyproline (4-HP) more than 6-fold (p < 0.001) in anti-TNF and more than 2-fold (p < 0.05) in the anti-IL-6 group, but the growth dynamics in the anti-IL6 group was delayed (gradually raised at week 24) compared to the anti-TNF group (raised at week 12) following a smooth reduction. The ELISA analysis of IL-6 and TNFα concentration in the study population supported proteomic and metabolomic data. A positive correlation between ΔCDAI and ΔDAS28 indicators and ESR and CRP was established for the majority of patients after 24 weeks of treatment where ESR and CRP reduced by 20% and 40% finally, respectively. A regression model using the Forest Plot was estimated to elucidate the impact of the most significant clinical, biochemical, and anthropometric indicators for the evaluation of differences between considered anti-TNF and anti-IL-6 schemes of therapy.

Radiothermometric Study of the Effect of Amino Acid Mutation on the Characteristics of the Enzymatic System.

The radiothermometry (RTM) study of a cytochrome-containing system (CYP102 A1) has been conducted in order to demonstrate the applicability of RTM for monitoring changes in the functional activity of an enzyme in case of its point mutation. The study has been performed with the example of the wild-type cytochrome (WT) and its mutant type A264K. CYP102 A1 is a nanoscale protein-enzymatic system of about 10 nm in size. RTM uses a radio detector and can record the corresponding brightness temperature (Tbr) of the nanoscale enzyme solution within the 3.4-4.2 GHz frequency range during enzyme functioning. It was found that the enzymatic reaction during the lauric acid hydroxylation at the wild-type CYP102 A1 (WT) concentration of ~10-9 M is accompanied by Tbr fluctuations of ~0.5-1 °C. At the same time, no Tbr fluctuations are observed for the mutated forms of the enzyme CYP102 A1 (A264K), where one amino acid was replaced. We know that the activity of CYP102 A1 (WT) is ~4 orders of magnitude higher than that of CYP102 A1 (A264K). We therefore concluded that the disappearance of the fluctuation of Tbr CYP102 A1 (A264K) is associated with a decrease in the activity of the enzyme. This effect can be used to develop new methods for testing the activity of the enzyme that do not require additional labels and expensive equipment, in comparison with calorimetry and spectral methods. The RTM is beginning to find application in the diagnosis of oncological diseases and for the analysis of biochemical processes.

"Silicon-On-Insulator"-Based Biosensor for the Detection of MicroRNA Markers of Ovarian Cancer.

Ovarian cancer is a gynecological cancer characterized by a high mortality rate and tumor heterogeneity. Its early detection and primary prophylaxis are difficult to perform. Detecting biomarkers for ovarian cancer plays a pivotal role in therapy effectiveness and affects patients' survival. This study demonstrates the detection of microRNAs (miRNAs), which were reported to be associated with ovarian cancer tumorigenesis, with a nanowire biosensor based on silicon-on-insulator structures (SOI-NW biosensor). The advantages of the method proposed for miRNA detection using the SOI-NW biosensor are as follows: (1) no need for additional labeling or amplification reaction during sample preparation, and (2) real-time detection of target biomolecules. The detecting component of the biosensor is a chip with an array of 3 µm wide, 10 µm long silicon nanowires on its surface. The SOI-NW chip was fabricated using the "top-down" method, which is compatible with large-scale CMOS technology. Oligonucleotide probes (oDNA probes) carrying sequences complementary to the target miRNAs were covalently immobilized on the nanowire surface to ensure high-sensitivity biospecific sensing of the target biomolecules. The study involved two experimental series. Detection of model DNA oligonucleotides being synthetic analogs of the target miRNAs was carried out to assess the method's sensitivity. The lowest concentration of the target oligonucleotides detectable in buffer solution was 1.1 × 10-16 M. In the second experimental series, detection of miRNAs (miRNA-21, miRNA-141, and miRNA-200a) isolated from blood plasma samples collected from patients having a verified diagnosis of ovarian cancer was performed. The results of our present study represent a step towards the development of novel highly sensitive diagnostic systems for the early revelation of ovarian cancer in women.

Managing of Unassigned Mass Spectrometric Data by Neural Network for Cancer Phenotypes Classification.

Mass spectrometric profiling provides information on the protein and metabolic composition of biological samples. However, the weak efficiency of computational algorithms in correlating tandem spectra to molecular components (proteins and metabolites) dramatically limits the use of "omics" profiling for the classification of nosologies. The development of machine learning methods for the intelligent analysis of raw mass spectrometric (HPLC-MS/MS) measurements without involving the stages of preprocessing and data identification seems promising. In our study, we tested the application of neural networks of two types, a 1D residual convolutional neural network (CNN) and a 3D CNN, for the classification of three cancers by analyzing metabolomic-proteomic HPLC-MS/MS data. In this work, we showed that both neural networks could classify the phenotypes of gender-mixed oncology, kidney cancer, gender-specific oncology, ovarian cancer, and the phenotype of a healthy person by analyzing 'omics' data in 'mgf' data format. The created models effectively recognized oncopathologies with a model accuracy of 0.95. Information was obtained on the remoteness of the studied phenotypes. The closest in the experiment were ovarian cancer, kidney cancer, and prostate cancer/kidney cancer. In contrast, the healthy phenotype was the most distant from cancer phenotypes and ovarian and prostate cancers. The neural network makes it possible to not only classify the studied phenotypes, but also to determine their similarity (distance matrix), thus overcoming algorithmic barriers in identifying HPLC-MS/MS spectra. Neural networks are versatile and can be applied to standard experimental data formats obtained using different analytical platforms.

Nanoribbon Biosensor in the Detection of miRNAs Associated with Colorectal Cancer.

A nanoribbon biosensor (NRBS) was developed to register synthetic DNAs that simulate and are analogous to miRNA-17-3p associated with colorectal cancer. Using this nanoribbon biosensor, the ability to detect miRNA-17-3p in the blood plasma of a patient diagnosed with colorectal cancer has been demonstrated. The sensing element of the NRBS was a nanochip based on a silicon-on-insulator (SOI) nanostructure. The nanochip included an array of 10 nanoribbons and was designed with the implementation of top-down technology. For biospecific recognition of miRNA-17-3p, the nanochip was modified with DNA probes specific for miRNA-17-3p. The performance of the nanochip was preliminarily tested on model DNA oligonucleotides, which are synthetic analogues of miRNA-17-3p, and a detection limit of ~10-17 M was achieved. The results of this work can be used in the development of serological diagnostic systems for early detection of colorectal cancer.

Nanoribbon-Based Electronic Detection of a Glioma-Associated Circular miRNA.

Nanoribbon chips, based on "silicon-on-insulator" structures (SOI-NR chips), have been fabricated. These SOI-NR chips, whose surface was sensitized with covalently immobilized oligonucleotide molecular probes (oDNA probes), have been employed for the nanoribbon biosensor-based detection of a circular ribonucleic acid (circRNA) molecular marker of glioma in humans. The nucleotide sequence of the oDNA probes was complimentary to the sequence of the target oDNA. The latter represents a synthetic analogue of a glioma marker-NFIX circular RNA. In this way, the detection of target oDNA molecules in a pure buffer has been performed. The lowest concentration of the target biomolecules, detectable in our experiments, was of the order of ~10-17 M. The SOI-NR sensor chips proposed herein have allowed us to reveal an elevated level of the NFIX circular RNA in the blood of a glioma patient.

Convolutional neural network in proteomics and metabolomics for determination of comorbidity between cancer and schizophrenia.

The association between cancer risk and schizophrenia is widely debated. Despite many epidemiological studies, there is still no strong evidence regarding the molecular basis for the comorbidity between these two pathological conditions. The vast majority of assays have been performed using clinical records of schizophrenic patients or those undergoing cancer treatment and monitored for sufficient time to find shared features between the considered conditions. We performed mass spectrometry-based proteomic and metabolomic investigations of patients with different cancer phenotypes (breast, ovarian, renal, and prostate) and patients with schizophrenia. The resulting vast quantity of proteomic and metabolomic data were then processed using systems biology and one-dimensional (1D) convolutional neural network (1DCNN) machine learning approaches. Traditional systematic approaches permit the segregation of schizophrenia and cancer phenotypes on the level of biological processes, while 1DCNN recognized "signatures" that could segregate distinct cancer phenotypes and schizophrenia at the comorbidity level. The designed network efficiently discriminated unrelated pathologies with a model accuracy of 0.90 and different subtypes of oncophenotypes with an accuracy of 0.94. The proposed strategy integrates systematic analysis of identified compounds and application of 1DCNN model for unidentified ones to reveal the similarity between distinct phenotypes.

Micro-Raman Characterization of Structural Features of High-k Stack Layer of SOI Nanowire Chip, Designed to Detect Circular RNA Associated with the Development of Glioma.

The application of micro-Raman spectroscopy was used for characterization of structural features of the high-k stack (h-k) layer of "silicon-on-insulator" (SOI) nanowire (NW) chip (h-k-SOI-NW chip), including Al2O3 and HfO2 in various combinations after heat treatment from 425 to 1000 °C. After that, the NW structures h-k-SOI-NW chip was created using gas plasma etching optical lithography. The stability of the signals from the monocrine phase of HfO2 was shown. Significant differences were found in the elastic stresses of the silicon layers for very thick (>200 nm) Al2O3 layers. In the UV spectra of SOI layers of a silicon substrate with HfO2, shoulders in the Raman spectrum were observed at 480-490 cm-1 of single-phonon scattering. The h-k-SOI-NW chip created in this way has been used for the detection of DNA-oligonucleotide sequences (oDNA), that became a synthetic analog of circular RNA-circ-SHKBP1 associated with the development of glioma at a concentration of 1.1 × 10-16 M. The possibility of using such h-k-SOI NW chips for the detection of circ-SHKBP1 in blood plasma of patients diagnosed with neoplasm of uncertain nature of the brain and central nervous system was shown.

Use of Silicon Nanowire Sensors for Early Cancer Diagnosis.

The review covers some research conducted in the field of medical and biomedical application of devices based on silicon sensor elements (Si-NW-sensors). The use of Si-NW-sensors is one of the key methods used in a whole range of healthcare fields. Their biomedical use is among the most important ones as they offer opportunities for early diagnosis of oncological pathologies, for monitoring the prescribed therapy and for improving the people's quality of life.

Raman Spectroscopy-Based Quality Control of "Silicon-On-Insulator" Nanowire Chips for the Detection of Brain Cancer-Associated MicroRNA in Plasma.

Application of micro-Raman spectroscopy for the monitoring of quality of nanowire sensor chips fabrication has been demonstrated. Nanowire chips have been fabricated on the basis of «silicon-on-insulator¼ (SOI) structures (SOI-NW chips). The fabrication of SOI-NW chips was performed by optical litography with gas-phase etching. The so-fabricated SOI-NW chips are intended for highly sensitive detection of brain cancer biomarkers in humans. In our present study, two series of experiments have been conducted. In the first experimental series, detection of a synthetic DNA oligonucleotide (oDNA) analogue of brain cancer-associated microRNA miRNA-363 in purified buffer solution has been performed in order to demonstrate the high detection sensitivity. The second experimental series has been performed in order to reveal miRNA-363 itself in real human plasma samples. To provide detection biospecificity, the SOI-NW chip surface was modified by covalent immobilization of probe oligonucleotides (oDNA probes) complementary to the target biomolecules. Using the SOI-NW sensor chips proposed herein, the concentration detection limit of the target biomolecules at the level of 3.3 × 10-17 M has been demonstrated. Thus, the approach employing the SOI-NW chips proposed herein represents an attractive tool in biomedical practice, aimed at the early revelation of oncological diseases in humans.

Highly Sensitive Detection of CA 125 Protein with the Use of an n-Type Nanowire Biosensor.

The detection of CA 125 protein in a solution using a silicon-on-insulator (SOI)-nanowire biosensor with n-type chip has been experimentally demonstrated. The surface of nanowires was modified by covalent immobilization of antibodies against CA 125 in order to provide the biospecificity of the target protein detection. We have demonstrated that the biosensor signal, which results from the biospecific interaction between CA 125 and the covalently immobilized antibodies, increases with the increase in the protein concentration. At that, the minimum concentration, at which the target protein was detectable with the SOI-nanowire biosensor, amounted to 1.5 × 10-16 M.

Revelation of Proteomic Indicators for Colorectal Cancer in Initial Stages of Development.

Background: Colorectal cancer (CRC) at a current clinical level is still hardly diagnosed, especially with regard to nascent tumors, which are typically asymptotic. Searching for reliable biomarkers of early diagnosis is an extremely essential task. Identification of specific post-translational modifications (PTM) may also significantly improve net benefits and tailor the process of CRC recognition. We examined depleted plasma samples obtained from 41 healthy volunteers and 28 patients with CRC at different stages to conduct comparative proteome-scaled analysis. The main goal of the study was to establish a constellation of protein markers in combination with their PTMs and semi-quantitative ratios that may support and realize the distinction of CRC until the disease has a poor clinical manifestation. Results: Proteomic analysis revealed 119 and 166 proteins for patients in stages I-II and III-IV, correspondingly. Plenty of proteins (44 proteins) reflected conditions of the immune response, lipid metabolism, and response to stress, but only a small portion of them were significant (p < 0.01) for distinguishing stages I-II of CRC. Among them, some cytokines (Clusterin (CLU), C4b-binding protein (C4BP), and CD59 glycoprotein (CD59), etc.) were the most prominent and the lectin pathway was specifically enhanced in patients with CRC. Significant alterations in Inter-alpha-trypsin inhibitor heavy chains (ITIH1, ITIH2, ITIH3, and ITIH4) levels were also observed due to their implication in tumor growth and the malignancy process. Other markers (Alpha-1-acid glycoprotein 2 (ORM2), Alpha-1B-glycoprotein (A1BG), Haptoglobin (HP), and Leucine-rich alpha-2-glycoprotein (LRG1), etc.) were found to create an ambiguous core involved in cancer development but also to exactly promote tumor progression in the early stages. Additionally, we identified post-translational modifications, which according to the literature are associated with the development of colorectal cancer, including kininogen 1 protein (T327-p), alpha-2-HS-glycoprotein (S138-p) and newly identified PTMs, i.e., vitamin D-binding protein (K75-ac and K370-ac) and plasma protease C1 inhibitor (Y294-p), which may also contribute and negatively impact on CRC progression. Conclusions: The contribution of cytokines and proteins of the extracellular matrix is the most significant factor in CRC development in the early stages. This can be concluded since tumor growth is tightly associated with chronic aseptic inflammation and concatenated malignancy related to loss of extracellular matrix stability. Due attention should be paid to Apolipoprotein E (APOE), Apolipoprotein C1 (APOC1), and Apolipoprotein B-100 (APOB) because of their impact on the malfunction of DNA repair and their capability to regulate mTOR and PI3K pathways. The contribution of the observed PTMs is still equivocal, but a significant decrease in the likelihood between modified and native proteins was not detected confidently.

Micro-Raman Spectroscopy for Monitoring of Deposition Quality of High-k Stack Protective Layer onto Nanowire FET Chips for Highly Sensitive miRNA Detection.

Application of micro-Raman spectroscopy for the monitoring of quality of high-k (h-k) dielectric protective layer deposition onto the surface of a nanowire (NW) chip has been demonstrated. A NW chip based on silicon-on-insulator (SOI) structures, protected with a layer of high-k dielectric ((h-k)-SOI-NW chip), has been employed for highly sensitive detection of microRNA (miRNA) associated with oncological diseases. The protective dielectric included a 2-nm-thick Al2O3 surface layer and a 8-nm-thick HfO2 layer, deposited onto a silicon SOI-NW chip. Such a chip had increased time stability upon operation in solution, as compared with an unprotected SOI-NW chip with native oxide. The (h-k)-SOI-NW biosensor has been employed for the detection of DNA oligonucleotide (oDNA), which is a synthetic analogue of miRNA-21 associated with oncological diseases. To provide biospecificity of the detection, the surface of (h-k)-SOI-NW chip was modified with oligonucleotide probe molecules (oDVA probes) complementary to the sequence of the target biomolecule. Concentration sensitivity of the (h-k)-SOI-NW biosensor at the level of DL~10-16 M has been demonstrated.

SOI nanowire for the high-sensitive detection of HBsAg and α-fetoprotein.

Silicon-on-isolator-nanowires (SOI-NWs) were used for the label-free, real-time biospecific detection of the hepatitis B marker HBsAg and cancer marker α-fetoprotein (AFP). Specific protein-protein recognition was carried out using individual NWs that were functionalized with antibodies. To solve the problem of non-specific binding of target protein molecules to the sensor element the use of a reference NW with immobilized antibodies against non-target proteins was proposed. Using individual SOI-NW surface functionalization allowed the fabrication of a NW array, containing working NWs and reference NWs within one chip. It was shown that this approach allows us to reach a detection limit up to 10(-14) and 10(-15) M for HBsAg and AFP, respectively. Our investigations also allowed us to reveal the influence of the charged state of the target protein molecules and antibodies in solutions with various pH values on the target protein detection limit. A high sensitivity NW-detector is of interest for the creation of diagnosticums for hepatitis B and for the early stages of cancer diseases.