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.
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 (
< 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.
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.
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
(
), which provides comprehensive data processing.
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
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.
Post-translational processing leads to conformational changes in protein structure that modulate molecular functions and change the signature of metabolic transformations and immune responses. Some ...post-translational modifications (PTMs), such as phosphorylation and acetylation, are strongly related to oncogenic processes and malignancy. This study investigated a PTM pattern in patients with gender-specific ovarian or breast cancer. Proteomic profiling and analysis of cancer-specific PTM patterns were performed using high-resolution UPLC-MS/MS. Structural analysis, topology, and stability of PTMs associated with sex-specific cancers were analyzed using molecular dynamics modeling. We identified highly specific PTMs, of which 12 modified peptides from eight distinct proteins derived from patients with ovarian cancer and 6 peptides of three proteins favored patients from the group with breast cancer. We found that all defined PTMs were localized in the compact and stable structural motifs exposed outside the solvent environment. PTMs increase the solvent-accessible surface area of the modified moiety and its active environment. The observed conformational fluctuations are still inadequate to activate the structural degradation and enhance protein elimination/clearance; however, it is sufficient for the significant modulation of protein activity.
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
χ
2
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.
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•Systematic approach realizes common features between related and unrelated diseases.•Neural network can use both meaningful and unassigned mass spectrometry-based data.•Convolutional ...neural network discriminates closely related phenotypes.•Neural network suggests comorbidity between schizophrenia and oncophenotypes.
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.
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.
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).
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.
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.
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.
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