Efficient Biomarker Research Articles

Reconstruction and Evaluation of Co-expression Network of Genes Encoding Proteins in Gastric Cancer

Background: Gastric cancer is the second leading cause of cancer-related deaths worldwide. Computational studies of cancers facilitate understanding of the cancer development pathogenic process and lead researchers to discover efficient molecular biomarkers suitable for the prognosis or early detection of gastric cancer. In cancer systems, biology researchers seek to find the cellular mechanisms of cancer with a focus on the systemic perspective. It is not just a gene, a protein, a metabolite, or any other biological factor; it is how each of these factors works in a complex system with others and tries to look at the system behavior of each factor. Methods: In this study, 411 samples of gastric cancer and 35 samples of healthy individuals’ gene expression data were collected based on search results in the TCGA database. Then we normalized and filtered the input genes. After analyzing weighted gene co-expression networks, the resulting modules became candidates for enrichment analysis and literature review. Results: Examination of the results obtained from the reconstruction and analysis of gastric cancer weighted gene co-expression network led to the discovery of pink and blue modules. Then, the genes consisting of that module were enriched through the KEGG, EnrichR, and ToppGene databases. Some of these genes, such as DMB, CD6, CD8A, CDC45, and CDC20 are known to be involved in inflammation, cell cycle, and tissue damage in cancer, and some of these other genes are less commonly reported in scientific studies. Conclusions: We can select these candidate genes as potential biomarkers to determine the prognosis and even early detection of the clinical treatment.

Role of Biomarkers for the Diagnosis of Prion Diseases: A Narrative Review.

Prion diseases are progressive and irreversible neurodegenerative disorders with a low incidence (1.5–2 cases per million per year). Genetic (10–15%), acquired (anecdotal) and sporadic (85%) forms of the disease have been described. The clinical spectrum of prion diseases is very varied, although the most common symptoms are rapidly progressive dementia, cerebellar ataxia and myoclonus. Mean life expectancy from the onset of symptoms is 6 months. There are currently diagnostic criteria based on clinical phenotype, as well as neuroimaging biomarkers (magnetic resonance imaging), neurophysiological tests (electroencephalogram and polysomnogram), and cerebrospinal fluid biomarkers (14-3-3 protein and real-time quaking-induced conversion (RT-QuIC)). The sensitivity and specificity of some of these tests (electroencephalogram and 14-3-3 protein) is under debate and the applicability of other tests, such as RT-QuIC, is not universal. However, the usefulness of these biomarkers beyond the most frequent prion disease, sporadic Creutzfeldt–Jakob disease, remains unclear. Therefore, research is being carried out on new, more efficient cerebrospinal fluid biomarkers (total tau, ratio total tau/phosphorylated tau and neurofilament light chain) and potential blood biomarkers (neurofilament light chain, among others) to try to universalize access to early diagnosis in the case of prion diseases.

MicroRNA-Mediated Epigenetic Regulation of Rheumatoid Arthritis Susceptibility and Pathogenesis.

MicroRNAs (miRNAs) play crucial roles in regulating the transcriptome and development of rheumatoid arthritis (RA). Currently, a comprehensive map illustrating how miRNAs regulate transcripts, pathways, immune system differentiation, and their interactions with terminal cells such as fibroblast-like synoviocytes (FLS), immune-cells, osteoblasts, and osteoclasts are still laking. In this review, we summarize the roles of miRNAs in the susceptibility, pathogenesis, diagnosis, therapeutic intervention, and prognosis of RA. Numerous miRNAs are abnormally expressed in cells involved in RA and regulate target genes and pathways, including NF-κB, Fas-FasL, JAK-STAT, and mTOR pathways. We outline how functional genetic variants of miR-499 and miR-146a partly explain susceptibility to RA. By regulating gene expression, miRNAs affect T cell differentiation into diverse cell types, including Th17 and Treg cells, thus constituting promising gene therapy targets to modulate the immune system in RA. We summarize the diagnostic and prognostic potential of blood-circulating and cell-free miRNAs, highlighting the opportunity to combine these miRNAs with antibodies to cyclic citrullinated peptide (ACCP) to allow accurate diagnosis and prognosis, particularly for seronegative patients. Furthermore, we review the evidence implicating miRNAs as promising biomarkers of efficiency and response of, and resistance to, disease-modifying anti-rheumatic drugs and immunotherapy. Finally, we discuss the autotherapeutic effect of miRNA intervention as a step toward the development of miRNA-based anti-RA drugs. Collectively, the current evidence supports miRNAs as interesting targets to better understand the pathogenetic mechanisms of RA and design more efficient therapeutic interventions.

Prognostic Role of Subsequent Thrombocytopenia in Necrotizing Fasciitis Without Liver Disease.

Necrotizing fasciitis (NF) is a life-threatening disease with a fulminant presentation. Although early diagnosis can be aided by combining physical examination, the Laboratory Risk Indicator for Necrotizing Fasciitis score, and computed tomography, a mortality rate of 30% is still reported. In the modern times, an economical and efficient biomarker for predicting mortality in NF patients is still lacking. Platelet count is typically measured in routine blood tests and aids in predicting disease severity. We aimed to clarify the role of platelet count as a predictive factor for aspects of prognosis, such as mortality and surgical outcomes, in patients with NF. We identified 285 patients with NF between 2018 and 2020 in a single medical center in southern Taiwan. Medical records were collected for the evaluation of patients with thrombocytopenia. Univariate and multivariate analyses were performed for different outcomes. We included 115 patients with confirmed diagnoses of NF. Twelve patients died with a mortality rate of 10.4%. Patients with thrombocytopenia exhibited a higher mortality rate (20.9% vs 4.2%, P = 0.006), more shock episodes (51.2% vs 11.1%, P < 0.001), higher intensive care unit admission rate (46.5% vs 13.9%, P < 0.001), and longer hospital length of stay (37.49 ± 24.12 days vs 28.82 ± 14.63 days, P = 0.037) than those without thrombocytopenia. All patients infected with Vibrio species exhibited thrombocytopenia. In multivariate analysis, independent risk factors for mortality were thrombocytopenia (odds ratio, 4.57; 95% confidence interval, 1.08-19.25) and single gram-negative bacterial culture from the wound (odds ratio 6.88; 95% confidence interval, 1.58-29.96). In patients with NF and subsequent thrombocytopenia, a higher mortality rate, greater numbers of shock episodes, higher demand for intensive care unit, and longer hospital length of stay were observed than in those without thrombocytopenia. In patients with NF, platelet count is a valuable and economic indicator of prognosis. Once thrombocytopenia developed in patients with necrotizing fasciitis, aggressive antibiotic treatment and surgical management are required to improve the chances of recovery.

Prognostic Significance of PTTG1 and Its Methylation in Lung Adenocarcinoma.

Pituitary tumor-transforming gene-1 (PTTG1), one type of DNA repair-related gene, has been reported to be dysregulated in several tumors and serve as a tumor promotor. Previously, the oncogenic roles of PTTG1 were also reported in lung adenocarcinoma (LUAD). However, the prognostic values of PTTG1 in LUAD and the possible mechanism of its dysregulation have not been clarified. We analyzed TCGA datasets and reported that PTTG1 expression showed a distinct increase within LUAD specimens in comparison with nontumor specimens. Further survival study revealed that patients containing a great PTTG1 level had noticeably less overall survival and progression-free survival as compared with patients containing a low PTTG1 level. Multivariate analyses confirmed that PTTG1 expression was a factor of prognosis that is independent in terms of LUAD patients. Besides, PTTG1 methylation had a negative regulation on PTTG1, so PTTG1 had a high expressing level in LUAD tissues. However, the relation between hypermethylation and overall survival was not demonstrated using TCGA datasets. In addition, we observed that LUAD specimens with advanced stages exhibited a higher level of PTTG1. Finally, the dysregulated genes related to PTTG1 expression were screened, and KEGG assays revealed that the above genes were involved in the p53 signaling pathway, indicating the possible regulatory function of PTTG1 in the p53 signaling pathway. Overall, our findings suggest that PTTG1 may serve as an efficient clinical biomarker and a therapeutic target for patients suffering from LUAD.

Detection of plasma exosomal miRNA-205 as a biomarker for early diagnosis and an adjuvant indicator of ovarian cancer staging

BackgroundOvarian cancer (OC) is one of the serious threats to the health of women worldwide, and accurate biomarkers are urgently demanded for early diagnosis of OC. We have previously confirmed that miR-205 promotes the invasion and metastasis of OC cells by inhibiting the expression of the tumor suppressor gene TCF21. In this study, we used liquid biopsy technology to detect the expression levels of the four genes, miR-205, CA125, HE4 and TCF21, in the exosomes of plasma of OC patients. Combined with analysis of clinicopathological parameters of OC patients, we aimed to provide efficient and non-invasive laboratory biomarkers for early diagnosis of OC.Methods36 OC patients who were diagnosed in local hospitals from September 2020 to July 2021 were selected as OC group, 31 cases of surgically diagnosed with ovarian benign lesions were selected as benign group, and 32 healthy people who underwent physical examination during the same period were selected as a control group. We employed transmission electron microscope (TEM), Western blotting (WB), and nanoparticle tracking analysis (NTA) to identify biomarkers in the exosomes extracted from plasma of the three groups. The RNA levels of miR-205, CA125, HE4 and TCF21 genes in plasma exosomes were detected by real-time quantitative PCR (qRT-PCR) method. We used clinical pathological parameters and the Receiver Operating Characteristic (ROC) curves to evaluate the diagnostic efficacy for the genes detected in plasma exosomes.ResultsWe found that the expression level of miR-205 in plasma exosomes of the OC group was significantly higher than that of the benign and control groups (P < 0.05), and the level of miR-205 was elevated during the III-IV periods of OC and lymph node metastasis.ConclusionThe level of miR-205 in plasma exosomes is a valuable tumor biomarker to improve OC diagnosis.

HOXD8 hypermethylation as a fully sensitive and specific biomarker for biliary tract cancer detectable in tissue and bile samples

BackgroundBiliary tract cancers (BTC) are rare but highly aggressive tumours with poor prognosis, usually detected at advanced stages. Herein, we aimed at identifying BTC-specific DNA methylation alterations.MethodsStudy design included statistical power and sample size estimation. A genome-wide methylation study of an explorative cohort (50 BTC and ten matched non-tumoral tissue samples) has been performed. BTC-specific altered CpG islands were validated in over 180 samples (174 BTCs and 13 non-tumoral controls). The final biomarkers, selected by a machine-learning approach, were validated in independent tissue (18 BTCs, 14 matched non-tumoral samples) and bile (24 BTCs, five non-tumoral samples) replication series, using droplet digital PCR.ResultsWe identified and successfully validated BTC-specific DNA methylation alterations in over 200 BTC samples. The two-biomarker panel, selected by an in-house algorithm, showed an AUC > 0.97. The best-performing biomarker (chr2:176993479-176995557), associated with HOXD8, a pivotal gene in cancer-related pathways, achieved 100% sensitivity and specificity in a new series of tissue and bile samples.ConclusionsWe identified a novel fully efficient BTC biomarker, associated with HOXD8 gene, detectable both in tissue and bile by a standardised assay ready-to-use in clinical trials also including samples from non-invasive matrices.

Comprehensive profiling of the TRIpartite motif family to identify pivot genes in hepatocellular carcinoma.

IntroductionTRIpartite motif (TRIM) proteins are important members of the Really Interesting New Gene‐finger‐containing E3 ubiquitin‐conjugating enzyme and are involved in the progression of hepatocellular carcinoma (HCC). However, the diverse expression patterns of TRIMs and their roles in prognosis and immune infiltrates in HCC have yet to be analyzed.MaterialsCombined with previous research, we used an Oncomine database and the Human Protein Atlas to compare TRIM family genes' transcriptional levels between tumor samples and normal liver tissues, as verified by the Gene Expression Profiling Interactive Analysis database. We investigated the patient survival data of TRIMs from the Kaplan–Meier plotter database. Clinicopathologic characteristics associations and potential diagnostic and prognostic values were validated with clinical and expressional data collected from the cancer genome atlas.ResultsWe identified TRIM28, TRIM37, TRIM45, and TRIM59 as high‐priority members of the TRIMs family that modulates HCC. Low expression of TRIM28 was associated with shorter overall survival (OS) than high expression (log‐rank p = 0.009). The same trend was identified for TRIM37 (p = 0.001), TRIM45 (p = 0.013), and TRIM59 (p = 0.011). Multivariate analysis indicated that the level of TRIM37 was a significant independent prognostic factor for both OS (p = 0.043) and progression‐free interval (p = 0.044). We performed expression and mutation analysis and functional pathways and tumor immune infiltration analysis of the changes in TRIM factors.ConclusionThese data suggested that TRIM28, TRIM37, TRIM45, and TRIM59 could serve as efficient prognostic biomarkers and therapeutic targets in HCC.

Identification and validation of a cigarette smoke-related five-gene signature as a prognostic biomarker in kidney renal clear cell carcinoma

Cigarette smoking greatly promotes the progression of kidney renal clear cell carcinoma (KIRC), however, the underlying molecular events has not been fully established. In this study, RCC cells were exposed to the tobacco specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK, nicotine-derived nitrosamine) for 120 days (40 passages), and then the soft agar colony formation, wound healing and transwell assays were used to explore characteristics of RCC cells. RNA-seq was used to explore differentially expressed genes. We found that NNK promoted RCC cell growth and migration in a dose-dependent manner, and RNA-seq explored 14 differentially expressed genes. In TCGA-KIRC cohort, Lasso regression and multivariate COX regression models screened and constructed a five-gene signature containing ANKRD1, CYB5A, ECHDC3, MT1E, and AKT1S1. This novel gene signature significantly associated with TNM stage, invasion depth, metastasis, and tumor grade. Moreover, when compared with individual genes, the gene signature contained a higher hazard ratio and therefore had a more powerful value for the prognosis of KIRC. A nomogram was also developed based on clinical features and the gene signature, which showed good application. Finally, AKT1S1, the most crucial component of the gene signature, was significantly induced after NNK exposure and its related AKT/mTOR signaling pathway was dramatically activated. Our findings supported that NNK exposure would promote the KIRC progression, and the novel cigarette smoke-related five-gene signature might serve as a highly efficient biomarker to identify progression of KIRC patients, AKT1S1 might play an important role in cigarette smoke exposure-induced KIRC progression.

Cysteine cathepsin C: a novel potential biomarker for the diagnosis and prognosis of glioma

BackgroundCysteine cathepsin C encoded by the CTSC gene is an important member of the cysteine cathepsin family that plays a key role regulation of many types of tumors. However, whether CTSC is involved in the pathological process of glioma has not yet been reported. We comprehensively analyzed data from multiple databases and for the first time revealed a role and specific mechanism of action of CTSC in glioma, identifying it as a novel and efficient biomarker for the diagnosis and treatment of this brain tumor.MethodsThe expression of CTSC in glioma and its relationship with clinical characteristics and prognosis of patients with glioma were analyzed at different levels by using clinical sample information from several databases. CTSC expression levels in glioma and normal brain tissues, as well as in glioma cells and normal brain cells, was validated by real-time quantitative polymerase chain reaction (RT-qPCR). Gene set enrichment analysis (GSEA) was used to reveal the signaling pathways that CTSC may participate in. The connectivity map was used to reveal small molecules that may inhibit CTSC expression in glioma, and the putative effect of these compounds was verified by RT-qPCR.ResultsOur analyses showed that the expression of CTSC in glioma was higher than that in non-cancerous cells. GSEA showed that CTSC expression may regulate the malignant development of glioma through Toll-like receptor signaling pathways, pathways in cancer, and extracellular matrix receptor interaction signaling pathways. And we proved piperlongumine and scopoletin could inhibit CTSC expression in glioma cells.ConclusionsCTSC may serve as an efficient molecular target for the diagnosis and therapy of glioma, thereby improving the poor prognosis of patients with glioma.

Does mismatch negativity have utility for NMDA receptor drug development in depression?

Rapid antidepressant effects associated with ketamine have shifted the landscape for the development of therapeutics to treat major depressive disorder (MDD) from a monoaminergic to glutamatergic model. Treatment with ketamine, an N-methyl-D-aspartate (NMDA) receptor antagonist, may be effective, but has many non-glutamatergic targets, and clinical and logistical problems are potential challenges. These factors underscore the importance of manipulations of binding mechanics to produce antidepressant effects without concomitant clinical side effects. This will require identification of efficient biomarkers to monitor target engagement. The mismatch negativity (MMN) is a widely used electrophysiological signature linked to the activity of NMDA receptors (NMDAR) in humans and animals and validated in pre-clinical and clinical studies of ketamine. In this review, we explore the flexibility of the MMN and its capabilities for reliable use in drug development for NMDAR antagonists in MDD. We supplement this with findings from our own research with three distinct NMDAR antagonists. The research described illustrates that there are important distinctions between the mechanisms of NMDAR antagonism, which are further crystallized when considering the paradigm used to study the MMN. We conclude that the lack of standardized methodology currently prevents MMN from being ready for common use in drug discovery.Clinical trial registration:This manuscript describes data collected from the following National Institutes of Health (NIH) and Veterans Affairs (VA) studies: AV-101, NCT03583554; lanicemine, NCT03166501; ketamine, NCT02556606.

Creatine as a Promising Component of Paternal Preconception Diet.

Male fertility has been declining globally over the past several decades, advancing from a personal issue to a public health problem. Beyond any doubt, a reduction in fertility (often characterized by low sperm count or motility) can severely threaten reproductive health and lifecourse framework in a long-term fashion. Aside from uncovering the currently unknown etiology of modern-day male infertility, the scientific and medical community faces a double burden: finding an efficient biomarker of impaired fertility and exploring any intervention that can act to enhance fertility. A plethora of nutritional compounds have been recognized as possible modulators of semen quality, and specific dietary patterns and nutrients appear to be accompanied by a lower risk of male infertility. Creatine, a conditionally essential nutrient, has caught attention as a male fertility-promoting candidate due to its role in sperm energy metabolism. This mini-review describes the creatine-related bioenergetics of spermatozoa, explores a connection between creatine levels and sperm quality in men, and critically examines available evidence for interventional studies with creatine to affect sperm viability.

Exosomal miRNA Profiling is a Potential Screening Route for Non-Functional Pituitary Adenoma.

Non-functional pituitary adenomas (NFPAs) are one of the most prevalent pituitary adenoma subtypes. The lack of reliable screening approach for NFPAs for the insidious clinical course usually leads to delays in medical therapy and consequently worse prognosis. Hence, we employed a sequence cohort (patient: control, 6:2) and a validation cohort (patient: control, 22:8) to develop a serum exosomal miRNA profile-based method for NFPA screening and prognosis prediction. We found that a total of 1,395 kinds of human miRNA were detected. Compared with healthy donors, 18 up-regulated and 36 down-regulated miRNAs showed significant expression alterations in NFPA patients. Target genes of differentially expressed miRNAs are mainly enriched in axonogenesis and cancer-associated terms. After validation, hsa-miR-486-5p, hsa-miR-151a-5p, hsa-miR-652-3p_R+1, and hsa-miR-1180-3p were promising biomarkers for NFPA, in which miR-486-5p was the most competent one. After a median of 33 months of prospective follow-up, exosomal hsa-miR-486-5p also was an efficient predictive biomarker for progression or relapse of NFPAs. By protein-protein interaction network construction of hsa-miR-486-5p targeted genes, the core modules revealed a high possibility that exosomal hsa-miR-486-5p regulated tumor progression by epigenetic regulation of MAPK signaling pathways. In conclusion, exosomal hsa-miR-486-5p, hsa-miR-151a-5p, hsa-miR-652-3p_R+1, and hsa-miR-1180-3p are candidate biomarkers for diagnosis and screening of NFPAs. More importantly, prospective follow-up reveals that hsa-miR-486-5p can be regarded as a significant predictor for prognosis of NFPAs.

Detection of Mitochondrial DNA Copy Number in Plasma Exosomes of Patients with Non-small Cell Lung Cancer

For the prevalence of lung cancer and its poor diagnosis, the seeking of the efficient biomarkers for this disease is an urgent requirement, especially from non-invasive samples such as plasma. The mitochondria DNA (mtDNA) copy number change has been evaluated as a potential indicator of cancer risk, however, there have been few studies regarding mtDNA in plasma derived exosomes. In this study, the mtDNA copy number was measured on 29 plasma exosome samples of patients with non-small cell lung cancer (NSCLC) and 29 plasma exosome samples of cancer-free controls by real-time PCR assay, then being statistically analyzed to evaluate the relationship between these figures and several pathological features of NSCLC patients. As the results, the existence of mtDNA in exosomes isolated from plasma was detected through PCR assay using primers covering most of the mtDNA length. The relative mtDNA copy numbers determined in the exosomes of the disease and control groups were 1619.1 ± 2589.0 and 1207.0 ± 1550.0, respectively, whereas these values in two disease stages were 783.6 ± 759.3 (stage I-II) and 2647.0 ± 3584.0 (stage III-IV). Comparing among these groups, the difference was only statistically significant between the disease groups of stage I-II and stage III-IV (p&lt;0.05), the group of stage III-IV and the control group (p&lt;0.05). Indeed, the mtDNA copy number is associated with tumor stage and stage N (p&lt;0.05). On the other aspect, the smoking habit of NSCLC patients could be an underlying reason behind the alteration in mtDNA copy number in the plasma exosomes. In short, our study demonstrates that the mtDNA copy number in exosomes resourced from plasma could be a potential biomarker for the detection and prognosis of NSCLC.

Analysis of Multifocal Visual Evoked Potentials Using Artificial Intelligence Algorithms.

PurposeClinical trials for remyelination in multiple sclerosis (MS) require an imaging biomarker. The multifocal visual evoked potential (mfVEP) is an accurate technique for measuring axonal conduction; however, it produces large datasets requiring lengthy analysis by human experts to detect measurable responses versus noisy traces. This study aimed to develop a machine-learning approach for the identification of true responses versus noisy traces and the detection of latency peaks in measurable signals.MethodsWe obtained 2240 mfVEP traces from 10 MS patients using the VS-1 mfVEP machine, and they were classified by a skilled expert twice with an interval of 1 week. Of these, 2025 (90%) were classified consistently and used for the study. ResNet-50 and VGG16 models were trained and tested to produce three outputs: no signal, up-sloped signal, or down-sloped signal. Each model ran 1000 iterations with a stochastic gradient descent optimizer with a learning rate of 0.0001.ResultsResNet-50 and VGG16 had false-positive rates of 1.7% and 0.6%, respectively, when the testing dataset was analyzed (n = 612). The false-negative rates were 8.2% and 6.5%, respectively, against the same dataset. The latency measurements in the validation and testing cohorts in the study were similar.ConclusionsOur models efficiently analyze mfVEPs with <2% false positives compared with human false positives of <8%.Translational RelevancemfVEP, a safe neurophysiological technique, analyzed using artificial intelligence, can serve as an efficient biomarker in MS clinical trials and signal latency measurement.

Identifying gene expression-based biomarkers in online learning environments.

Gene expression-based classifiers are often developed using historical data by training a model on a small set of patients and a large set of features. Models trained in such a way can be afterwards applied for predicting the output for new unseen patient data. However, very often the accuracy of these models starts to decrease as soon as new data is fed into the trained model. This problem, known as concept drift, complicates the task of learning efficient biomarkers from data and requires special approaches, different from commonly used data mining techniques. Here, we propose an online ensemble learning method to continually validate and adjust gene expression-based biomarker panels over increasing volume of data. We also propose a computational solution to the problem of feature drift where gene expression signatures used to train the classifier become less relevant over time. A benchmark study was conducted to classify the breast tumors into known subtypes by using a large-scale transcriptomic dataset (∼3500 patients), which was obtained by combining two datasets: SCAN-B and TCGA-BRCA. Remarkably, the proposed strategy improves the classification performances of gold-standard biomarker panels (e.g. PAM50, OncotypeDX and Endopredict) by adding features that are clinically relevant. Moreover, test results show that newly discovered biomarker models can retain a high classification accuracy rate when changing the source generating the gene expression profiles. github.com/UEFBiomedicalInformaticsLab/OnlineLearningBD. Supplementary data are available at Bioinformatics Advances online.

Impacts of dissolved Zn and nanoparticle forms in the fatty acid landscape of Mytilus galloprovincialis

The introduction of waste containing heavy metals into the marine environment has been increasing for the past few decades, yet there are still several pending questions regarding how it impacts aquatic fauna. This study compared the effects of zinc exposure in its ionic- and nanoparticle forms on the mussel Mytilus galloprovincialis and sampled at different time-points. Zinc accumulation was observable after one week. Exposure to 100 μg L−1 of either form for 28 days also resulted in the higher depletion of fatty acids, lipid peroxidation products accumulation, and changes in the fatty acid profiles. This was also observed for lower concentrations, although to a smaller extent. Given the importance of fatty acids in the marine trophic chains, these zinc-induced alterations have significant potential of introducing negative impacts on the ecosystem and ultimately on human nutrition. Finally, we show that fatty acids may be used as efficient biomarkers of zinc-induced stress.

Non-invasive metabolomics biomarkers of production efficiency and beef carcass quality traits

The inter-cattle growth variations stem from the interaction of many metabolic processes making animal selection difficult. We hypothesized that growth could be predicted using metabolomics. Urinary biomarkers of cattle feed efficiency were explored using mass spectrometry-based untargeted and targeted metabolomics. Feed intake and weight-gain was measured in steers (n = 75) on forage-based growing rations (stage-1, 84 days) followed by high-concentrate finishing rations (stage-2, 84 days). Urine from days 0, 21, 42, 63, and 83 in each stage were analyzed from steers with the greater (n = 14) and least (n = 14) average-daily-gain (ADG) and comparable dry-matter-intake (DMI; within 0.32 SD of the mean). Steers were slaughtered after stage-2. Adjusted fat-thickness and carcass-yield-grade increased in greater-ADG-cattle selected in stage-1, but carcass traits did not differ between ADG-selected in stage-2. Overall 85 untargeted metabolites segregated greater- and least-ADG animals, with overlap across diets (both stages) and breed type, despite sampling time effects. Total 18-bile acids (BAs) and 5-steroids were quantified and associated with performance and carcass quality across ADG-classification depending on the stage. Stepwise logistic regression of urinary BA and steroids had > 90% accuracy identifying efficient-ADG-steers. Urine metabolomics provides new insight into the physiological mechanisms and potential biomarkers for feed efficiency.

The levels of circulating long non-coding RNA GAS5 in prostate cancer patients: Single center study

Background/Aim. Prostate cancer (PCa) is second occurring carcinoma that affect males population. Although PCa incidence rates are high, most cases has favorable prognosis, with comfortable long term life quality. This study was aimed to assess distinction of lncRNA GAS5 plasma levels between healthy individuals and patients with PCa, and also between PCa patients with different prognostic scores. Methods. The present study included a total of 40 patients with PCa and a control group of 20 healthy individuals. PCa patients were divided into two subgroups (20 patients each) based on the prognostic criteria of American Joint Committee on Cancer. The patient data were collected and analysed. GAS5 levels were quantified using Real-time PCR metod. Statistical analysis was conducted using the IBM SPSS Statistics 26.0 computer program (IBM, USA, 2019). Results. The relative quantification of GAS5 expression levels shows downregulation in PCa patients compared to healthy individuals, however the difference was marginaly statistically significant (p = 0.056). With further analysis of the given results, we have concluded that the expression level of GAS5 was not significantly different in the first patient subgroup and the healthy individuals (p = 0.268). Patients from second subgroup had significantly lower plasma levels of GAS5 than healthy individuals (p = 0.033). Levels of GAS5 expression between patients with favorable prognosis (Group 1) than in the patients with worse prognostic score (Group 2), did not indicate the statistical significance (p = 0.275). In both Group 1 (p = 0.805) and Group 2 (p = 0.454), the plasma levels of GAS5 were not significantly different in comparing to the age (? 65 vs &gt; 65 years). Conclusion. One of the main objective in PCa researching is identifying novel and more efficient biomarkers. Conducted research provides strong evidence about the significance of lncRNAs in PCa, as well as the correlation of decreased expression of GAS5 and poor prognosis in various tumours.

Identification of a 10-pseudogenes signature as a novel prognosis biomarker for ovarian cancer

The outcomes of ovarian cancer are complicated and usually unfavorable due to their diagnoses at a late stage. Identifying the efficient prognostic biomarkers to improve the survival of ovarian cancer is urgently warranted. The survival-related pseudogenes retrieved from the Cancer Genome Atlas database were screened by univariate Cox regression analysis and further assessed by least absolute shrinkage and selection operator (LASSO) method. A risk score model based on the prognostic pseudogenes was also constructed. The pseudogene-mRNA regulatory networks were established using correlation analysis, and their potent roles in the ovarian cancer progression were uncovered by functional enrichment analysis. Lastly, ssGSEA and ESTIMATE algorithms was used to evaluate the levels of immune cell infiltrations in cancer tissues and explore their relationship with risk signature. A prediction model of 10-pseudogenes including RPL10P6, AC026688.1, FAR2P4, AL391840.2, AC068647.2, FAM35BP, GBP1P1, ARL4AP5, RPS3AP2, and AMD1P1 was established. The 10-pseudogenes signature was demonstrated to be an independent prognostic factor in patient with ovarian cancer in the random set (hazard ratio [HR] = 2.512, 95% confidence interval [CI] = 2.03–3.11, P < 0.001) and total set (HR = 1.71, 95% CI = 1.472–1.988, P < 0.001). When models integrating with age, grade, stage, and risk signature, the Area Under Curve (AUC) of the 1-year, 3-year, 5-year and 10-year Receiver Operating Characteristic curve in the random set and total set were 0.854, 0.824, 0.855, 0.805 and 0.679, 0.697, 0.739, 0.790, respectively. The results of functional enrichment analysis indicated that the underlying mechanisms by which these pseudogenes influence cancer prognosis may involve the immune-related biological processes and signaling pathways. Correlation analysis showed that risk signature was significantly correlated with immune cell infiltration and immune score. We identified a novel 10-pseudogenes signature to predict the survival of patients with ovarian cancer, and that may serve as novel possible prognostic biomarkers and therapeutic targets for ovarian cancer.