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.

Omics Untargeted Key Script: R-Based Software Toolbox for Untargeted Metabolomics with Bladder Cancer Biomarkers Discovery Case Study.

Large-scale untargeted LC-MS-based metabolomic profiling is a valuable source for systems biology and biomarker discovery. Data analysis and processing are major tasks due to the high complexity of generated signals and the presence of unwanted variations. In the present study, we introduce an R-based open-source collection of scripts called OUKS (Omics Untargeted Key Script), which provides comprehensive data processing. OUKS is developed by integrating various R packages and metabolomics software tools and can be easily set up and prepared to create a custom pipeline. Novel computational features are related to quality control samples-based signal processing and are implemented by gradient boosting, tree-based, and other nonlinear regression algorithms. Bladder cancer biomarkers discovery study which is based on untargeted LC-MS profiling of urine samples is performed to demonstrate exhaustive functionality of the developed software tool. Unique examination among dozens of metabolomics-specific data curation methods was carried out at each processing step. As a result, potential biomarkers were identified, statistically validated, and described by metabolism disorders. Our study demonstrates that OUKS helps to make untargeted LC-MS metabolomic profiling with the latest computational features readily accessible in a ready-to-use unified manner to a research community.

Cancer-Retina Antigens in the Urine of Bladder and Prostate Cancer Patients.

It has recently been shown that combination of arrestin and recoverin can serve as an effective urinary biomarker for renal cell carcinoma with sensitivity and specificity of over 92%. In this work, we studied the possibility of detecting these antigens in the urine in other urological oncological diseases - bladder cancer (BC) and prostate cancer (PCa). Urine samples from 40 BC patients and 40 PCa patients were analyzed using an ultrasensitive microarray immunoassay with a detection limit of 0.1 pg/ml. It was shown that in BC the sensitivity of determining combination of arrestin with recoverin is 58% (AUC 0.76, 95% CI 0.66-0.86), while in PCa it is 60% (AUC 0.7, 95% CI 0.68-0.88). It has been established that in patients with bladder and prostate cancer who had a positive test, these antigens are not detected in 90% of cases after removal of the tumor. In the future, the obtained results could become the basis for developing new approaches for timely detection of relapses of such diseases and treatment control, as well as for the development of new diagnostic methods.

Non-Invasive Diagnostics of Renal Cell Carcinoma Using Ultrasensitive Immunodetection of Cancer-Retina Antigens.

Renal cell carcinoma (RCC) is the most common urological malignancy with a high mortality and low detection rate. One of the approaches to improving its diagnostics may be the search for new non-invasive biomarkers in liquid biopsy and development of more sensitive methods for their detection. Cancer-retina antigens, which are known to be aberrantly expressed in malignant tumors, are present in liquid biopsy at extremely low concentrations. Using the developed multiplex immunoassay with a detection limit of 0.1 pg/ml, urine and serum samples of 89 patients with RCC and 50 non-cancer patients were examined for the presence of cancer-retina antigens (arrestin, recoverin, rhodopsin kinase, and transducin); the difference between the RCC and control groups was evaluated with the χ2 test. The results showed high diagnostic efficiency of a combination of arrestin and recoverin: at a threshold of 0.1 pg/ml, the sensitivity was 96%, specificity 92%, and AUC = 0.96 (95% confidence interval, 0.93-0.99). Seven days after nephrectomy, the concentration of the antigens returned to the level characteristic of the control group. Therefore, arrestin in a combination with recoverin can serve as a diagnostic non-invasive urinary biomarker of RCC.

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.

Plasma metabolomic profile in prostatic intraepithelial neoplasia and prostate cancer and associations with the prostate-specific antigen and the Gleason score.

INTRODUCTION: The metabolic alterations reflecting the influence of prostate cancer cells can be captured through metabolomic profiling. OBJECTIVE: To characterize the plasma metabolomic profile in prostatic intraepithelial neoplasia (PIN) and prostate cancer (PCa). METHODS: Metabolomics analyses were performed in plasma samples from individuals classified as non-cancerous control (n = 36), with PIN (n = 16), or PCa (n = 27). Untargeted [26 moieties identified after pre-processing by gas chromatography/mass spectrometry (GC/MS)] and targeted [46 amino acids, carbohydrates, organic acids and fatty acids by GC/MS, and 16 nucleosides and amino acids by ultra performance liquid chromatography-triple quadrupole/mass spectrometry (UPLC-TQ/MS)] analyses were performed. Prostate specific antigen (PSA) concentrations were measured in all samples. In PCa patients, the Gleason scores were determined. RESULTS: The metabolites that were best discriminated (p < 0.05, FDR < 0.2) for the Kruskal-Wallis test with Dunn's post-hoc comparing the control versus the PIN and PCa groups included isoleucine, serine, threonine, cysteine, sarcosine, glyceric acid, among several others. PIN was mainly characterized by alterations on steroidogenesis, glycine and serine metabolism, methionine metabolism and arachidonic acid metabolism, among others. In the case of PCa, the most predominant metabolic alterations were ubiquinone biosynthesis, catecholamine biosynthesis, thyroid hormone synthesis, porphyrin and purine metabolism. In addition, we identified metabolites that were correlated to the PSA [i.e. hypoxanthine (r = - 0.60, p < 0.05; r = - 0.54, p < 0.01) and uridine (r = - 0.58, p < 0.05; r = - 0.50, p < 0.01) in PIN and PCa groups, respectively] and metabolites that were significantly different in PCa patients with Gleason score < 7 and ≥ 7 [i.e. arachidonic acid, median (P25-P75) = 883.0 (619.8-956.4) versus 570.8 (505.6-651.8), respectively (p < 0.01)]. CONCLUSIONS: This human plasma metabolomic assessment contributes to the understanding of the unique metabolic features exhibited in PIN and PCa and provides a list of metabolites that can have the potential to be used as biomarkers for early detection of disease progression and management.

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.

Molecular Profiling of Athletes Performing High-Intensity Exercises in Extreme Environments.

The aim of this study was to determine the influence of high-intensity training under extreme conditions (T = 40 °C) on the metabolism and immunological reactions of athletes. Male triathletes (n = 11) with a high level of sports training performed load testing to failure (17 ± 2.7 min) and maximum oxygen consumption (64.1 ± 6.4 mL/min/kg). Blood plasma samples were collected before and immediately after exercise. Mass spectrometric metabolomic analysis identified 30 metabolites and 6 hormones in the plasma, of which 21 and 4 changed after exercise, respectively. Changes in the intermediate products of tricarboxylic and amino acids were observed (FC > 1.5) after exercise. The obtained data can be associated with the effect of physical activity on metabolism in athletes. Therefore, constant monitoring of the biochemical parameters of athletes can help coaches identify individual shortcomings in a timely manner and track changes, especially as the volume of training increases. In addition, it was revealed that the immunological reaction (manifestation of a hyperactive reaction to food components) is personalized in nature. Therefore, it is important for coaches and sports doctors to analyze and control the eating behavior of athletes to identify food intolerances or food allergies in a timely manner and develop an individual elimination diet.

In Silico, In Vitro, and Clinical Investigations of Cathepsin B and Stefin A mRNA Expression and a Correlation Analysis in Kidney Cancer.

The cysteine protease Cathepsin B (CtsB) plays a critical role in multiple signaling pathways, intracellular protein degradation, and processing. Endogenous inhibitors regulate its enzymatic activity, including stefins and other cystatins. Recent data proved that CtsB is implicated in tumor extracellular matrix remodeling, cell invasion, and metastasis: a misbalance between cathepsins and their natural inhibitors is often considered a sign of disease progression. In the present study, we investigated CtsB and stefin A (StfA) expression in renal cell carcinoma (RCC). mRNA analysis unveiled a significant CTSB and STFA increase in RCC tissues compared to adjacent non-cancerogenic tissues and a higher CtsB expression in malignant tumors than in benign renal neoplasms. Further analysis highlighted a positive correlation between CtsB and StfA expression as a function of patient sex, age, tumor size, grade, lymph node invasion, metastasis occurrence, and survival. Alternative overexpression and silencing of CtsB and StfA confirmed the correlation expression between these proteins in human RCC-derived cells through protein analysis and fluorescent microscopy. Finally, the ectopic expression of CtsB and StfA increased RCC cell proliferation. Our data strongly indicated that CtsB and StfA expression play an important role in RCC development by mutually stimulating their expression in RCC progression.

Proteolyzed Variant of IgG with Free C-Terminal Lysine as a Biomarker of Prostate Cancer.

The differential diagnosis of prostate cancer is problematic due to the lack of markers with high diagnostic accuracy. We previously demonstrated the increased binding of IgG to human plasminogen (PLG) in plasma of patients with prostate cancer (PC) compared to healthy controls. Heavy and light chains of PLG (PLG-H and PLG-L) were immobilized on 96-well plates and the binding of IgG to PLG-H and PLG-L was analyzed in serum from 30 prostate cancer (PC) patients, 30 patients with benign prostatic hyperplasia (BPH) and 30 healthy controls using enzyme-linked immunosorbent assay (ELISA). Our results demonstrate that IgG from PC sera bind to PLG-H but not to PLG-L. This interaction occurred through the free IgG C-terminal lysine (Lys) that becomes exposed as a result of IgG conformational changes associated with proteolysis. Circulating levels of modified IgG with exposed C-terminal Lys (IgG-Lys) were significantly higher in PC patients than in healthy controls and in BPH. We used Receiver Operating Characteristic (ROC) analysis to calculate the sensitivity (SN) and specificity (SP) of circulating IgG-Lys for differentiating PC from BPH as 77% and 90%, respectively. The area under the curve (AUC) was 0.87. We demonstrated that the diagnostic accuracy of circulating levels of IgG-Lys is much higher than diagnostic accuracy of total PSA (tPSA).

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.

Pharmacogenetic Testing: A Tool for Personalized Drug Therapy Optimization.

Pharmacogenomics is a study of how the genome background is associated with drug resistance and how therapy strategy can be modified for a certain person to achieve benefit. The pharmacogenomics (PGx) testing becomes of great opportunity for physicians to make the proper decision regarding each non-trivial patient that does not respond to therapy. Although pharmacogenomics has become of growing interest to the healthcare market during the past five to ten years the exact mechanisms linking the genetic polymorphisms and observable responses to drug therapy are not always clear. Therefore, the success of PGx testing depends on the physician's ability to understand the obtained results in a standardized way for each particular patient. The review aims to lead the reader through the general conception of PGx and related issues of PGx testing efficiency, personal data security, and health safety at a current clinical level.

Plasma Sarcosine Measured by Gas Chromatography-Mass Spectrometry Distinguishes Prostatic Intraepithelial Neoplasia and Prostate Cancer from Benign Prostate Hyperplasia.

OBJECTIVE: Sarcosine was postulated in 2009 as a biomarker for prostate cancer (PCa). Here, we assess plasma sarcosine as a biomarker that is complementary to prostate-specific antigen (PSA). METHODS: Plasma sarcosine was measured using gas chromatography-mass spectrometry (GC-MS) in adults classified as noncancerous controls (with benign prostate hyperplasia [BPH], n = 36), with prostatic intraepithelial neoplasia (PIN, n = 16), or with PCa (n = 27). Diagnostic accuracy was assessed using receiver operating characteristic curve analysis. RESULTS: Plasma sarcosine levels were higher in the PCa (2.0 µM [1.3-3.3 µM], P <.01) and the PIN (1.9 µM [1.2-6.5 µM], P <.001) groups than in the BPH (0.9 µM [0.6-1.4 µM]) group. Plasma sarcosine had "good" and "very good" discriminative capability to detect PIN (area under the curve [AUC], 0.734) and PCa (AUC, 0.833) versus BPH, respectively. The use of PSA and sarcosine together improved the overall diagnostic accuracy to detect PIN and PCa versus BPH. CONCLUSION: Plasma sarcosine measured by GC-MS had "good" and "very good" classification performance for distinguishing PIN and PCa, respectively, relative to noncancerous patients diagnosed with BPH.

Identification of Clinically Significant Prostate Cancer by Combined PCA3 and AMACR mRNA Detection in Urine Samples.

PURPOSE: Preclinical evaluation of PCA3 and AMACR transcript simultaneous detection in urine to diagnose clinical significant prostate cancer (prostate cancer with Gleason score ≥7) in a Russian cohort. PATIENTS AND METHODS: We analyzed urine samples of patients with a total serum PSA ≥2 ng/mL: 31 men with prostate cancer scheduled for radical prostatectomy, 128 men scheduled for first diagnostic biopsy (prebiopsy cohort). PCA3, AMACR, PSA and GPI transcripts were detected by multiplex reverse transcription quantitative polymerase chain reaction, and the results were used for scores for calculation and statistical analysis. RESULTS: There was no significant difference between clinically significant and nonsignificant prostate cancer PCA3 scores. However, there was a significant difference in the AMACR score (patients scheduled for radical prostatectomy p=0.0088, prebiopsy cohort p=0.029). We estimated AUCs, optimal cutoffs, sensitivities and specificities for PCa and csPCa detection in the prebiopsy cohort by tPSA, PCA3 score, PCPT Risk Calculator and classification models based on tPSA, PCA3 score and AMACR score. In the clinically significant prostate cancer ROC analysis, the PCA3 score AUC was 0.632 (95%CI: 0.511-0.752), the AMACR score AUC was 0.711 (95%CI: 0.617-0.806) and AUC of classification model based on the PCA3 score, the AMACR score and total PSA was 0.72 (95%CI: 0.58-0.83). In addition, the correlation of the AMACR score with the ratio of total RNA and RNA of prostate cells in urine was shown (tau=0.347, p=6.542e-09). Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. CONCLUSION: The AMACR score is a good predictor of clinically significant prostate cancer. Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. Evaluation of the AMACR score and classification models based on it for clinically significant prostate cancer detection with larger samples and a follow-up analysis is promising.