The potential molecular markers of inflammatory response in KOA with AD based on single-cell transcriptome sequencing analysis and identification of ligands by virtual screening

Alzheimer's disease (AD) and osteoarthritis (OA) are both senile degenerative diseases. Clinical studies have found that OA patients have a significantly increased risk of AD in their later life. This study hypothesized that chronic aseptic inflammation might lead to AD in KOA patients. However, current research has not yet clarified the potential mechanism between AD and KOA. Therefore, this study intends to use KOA transcriptional profiling and single-cell sequencing analysis technology to explore the molecular mechanism of KOA affecting AD development, and screen potential molecular biomarkers and drugs for the prediction, diagnosis, and prognosis of AD in KOA patients. It was found that the higher the expression of TXNIP, MMP3, and MMP13, the higher the risk coefficient of AD was. In addition, the AUC of TXNIP, MMP3, and MMP13 were all greater than 0.70, which had good diagnostic significance for AD. Finally, through the virtual screening of core proteins in FDA drugs and molecular dynamics simulation, it was found that compound Cobicistat could be targeted to TXNIP, Itc could be targeted to MMP3, and Isavuconazonium could be targeted to MMP13. To sum up, TXNIP, MMP3, and MMP13 are prospective molecular markers in KOA with AD, which could be used to predict, diagnose, and prognosis.

Potential molecular biomarkers for the diagnosis and prognosis of bladder cancer

Bladder cancer (BC) is a common malignant tumor of urinary system, which can be divided into muscle-invasive BC (MIBC) and nonmuscle-invasive BC (NMIBC). The number of BC patients has been gradually increasing currently. At present, bladder tumours are diagnosed and followed-up using a combination of cystoscopic examination, cytology and histology. However, the detection of early grade tumors, which is much easier to treat effectively than advanced stage disease, is still insufficient. It frequently recurs and can progress when not expeditiously diagnosed and monitored following initial therapy for NMIBC. Treatment strategies are totally different for different stage diseases. Therefore, it is of great practical significance to study new biomarkers for diagnosis and prognosis. In this review, we summarize the current state of biomarker development in BC diagnosis and prognosis prediction. We retrospectively analyse eight diagnostic biomarkers and eight prognostic biomarkers, in which CK, P53, PPARγ, PTEN and ncRNA are emphasized for discussion. Eight molecular subtype systems are also identified. Clinical translation of biomarkers for diagnosis, prognosis, monitoring and treatment will hopefully improve outcomes for patients. These potential biomarkers provide an opportunity to diagnose tumors earlier and with greater accuracy, and help identify those patients most at risk of disease recurrence.

Upregulation of shelterin and CST genes and longer telomeres are associated with unfavorable prognostic characteristics in prostate cancer

INTRODUCTION

Search for new clinical biomarkers targets in prostate cancer (PC) is urgent. Telomeres might be one of these targets. Telomeres are the extremities of linear chromosomes, essential for genome stability and control of cell divisions. Telomere homeostasis relies on the proper functioning of shelterin and CST complexes. Telomeric dysfunction and abnormal expression of its components are reported in most cancers and are associated with PC. Despite this, there are only a few studies about the expression of the main telomere complexes and their relationship with PC progression. We aimed to evaluate the role of shelterin (POT1, TRF2, TPP1, TIN2, and RAP1) and CST (CTC1, STN1, and TEN1) genes and telomere length in the progression of PC.

METHODS

We evaluated genetic alterations of shelterin and CST by bioinformatics in samples of localized (n = 499) and metastatic castration-resistant PC (n = 444). We also analyzed the expression of the genes using TCGA (localized PC n = 497 and control n = 152) and experimental approaches, with surgical specimens (localized PC n = 81 and BPH n = 10) and metastatic cell lines (LNCaP, DU145, PC3 and PNT2 as control) by real-time PCR. Real-time PCR also determined the telomere length in the same experimental samples. All acquired data were associated with clinical parameters.

RESULTS

Genetic alterations are uncommon in PC, but POT1, TIN2, and TEN1 showed significantly more amplifications in the metastatic cancer. Except for CTC1 and TEN1, which are differentially expressed in localized PC samples, we did not detect an expression pattern relative to control and cell lines. Nevertheless, except for TEN1, the upregulation of all genes is associated with a worse prognosis in localized PC. We also found that increased telomere length is associated with disease aggressiveness in localized PC.

CONCLUSION

The upregulation of shelterin and CST genes creates an environment that favors telomere elongation, giving selective advantages for localized PC cells to progress to more aggressive stages of the disease.

Nomogram model including LATS2 expression was constructed to predict the prognosis of advanced gastric cancer after surgery

BACKGROUND

Gastric cancer is a leading cause of cancer-related deaths worldwide. Prognostic assessments are typically based on the tumor-node-metastasis (TNM) staging system, which does not account for the molecular heterogeneity of this disease. LATS2, a tumor suppressor gene involved in the Hippo signaling pathway, has been identified as a potential prognostic biomarker in gastric cancer.

AIM

To construct and validate a nomogram model that includes LATS2 expression to predict the survival prognosis of advanced gastric cancer patients following radical surgery, and compare its predictive performance with traditional TNM staging.

METHODS

A retrospective analysis of 245 advanced gastric cancer patients from the Fourth Hospital of Hebei Medical University was conducted. The patients were divided into a training group (171 patients) and a validation group (74 patients) to develop and test our prognostic model. The performance of the model was determined using C-indices, receiver operating characteristic curves, calibration plots, and decision curves.

RESULTS

The model demonstrated a high predictive accuracy with C-indices of 0.829 in the training set and 0.862 in the validation set. Area under the curve values for three-year and five-year survival prediction were significantly robust, suggesting an excellent discrimination ability. Calibration plots confirmed the high concordance between the predictions and actual survival outcomes.

CONCLUSION

We developed a nomogram model incorporating LATS2 expression, which significantly outperformed conventional TNM staging in predicting the prognosis of advanced gastric cancer patients postsurgery. This model may serve as a valuable tool for individualized patient management, allowing for more accurate stratification and improved clinical outcomes. Further validation in larger patient cohorts will be necessary to establish its generalizability and clinical utility.

Applications of Mass Spectrometry in the Characterization, Screening, Diagnosis, and Prognosis of COVID-19

Mass spectrometry (MS) is a powerful analytical technique that plays a central role in modern protein analysis and the study of proteostasis. In the field of advanced molecular technologies, MS-based proteomics has become a cornerstone that is making a significant impact in the post-genomic era and as precision medicine moves from the research laboratory to clinical practice. The global dissemination of COVID-19 has spurred collective efforts to develop effective diagnostics, vaccines, and therapeutic interventions. This chapter highlights how MS seamlessly integrates with established methods such as RT-PCR and ELISA to improve viral identification and disease progression assessment. In particular, matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) takes the center stage, unraveling intricate details of SARS-CoV-2 proteins, revealing modifications such as glycosylation, and providing insights critical to formulating therapies and assessing prognosis. However, high-throughput analysis of MALDI data presents challenges in manual interpretation, which has driven the development of programmatic pipelines and specialized packages such as MALDIquant. As we move forward, it becomes clear that integrating proteomic data with various omic findings is an effective strategy to gain a comprehensive understanding of the intricate biology of COVID-19 and ultimately develop targeted therapeutic paradigms.

Management of Microsatellite Instability High (MSI-H) Gastroesophageal Adenocarcinoma

BACKGROUND

Gastroesophageal cancer is a major cause of cancer-related mortality worldwide. Treatment of both early stage and advanced disease remains highly reliant on cytotoxic chemotherapy. About 4-24% of gastroesophageal cancers are microsatellite instability high (MSI-H). The MSI-H subtype is associated with favorable prognosis, resistance to cytotoxic chemotherapy, and sensitivity to immune checkpoint inhibitors (ICI). Recent studies have demonstrated promising activity of ICIs in the MSI-H subtype, resulting in fundamental changes in the management of MSI-H gastroesophageal adenocarcinoma.

PURPOSE

In this review, we discuss the prevalence, characteristics, prognosis, and management of MSI-H gastroesophageal adenocarcinoma, with a focus on recent and ongoing studies that have changed the landscape of treatment for the MSI-H subtype. We also discuss current challenges in the management of resectable and advanced MSI-H gastroesophageal cancer, including the need for more accurate biomarkers of response to ICI therapy.

A novel microRNA panel exhibited significant potential in evaluating the progression of laryngeal squamous cell carcinoma

Background

Laryngeal squamous cell carcinoma (LSCC) is a common cancer of the head and neck in humans. The 5-years survival rate of patients with LSCC have declined in the past four decades. microRNAs (miRNAs) has been reported to be capable of predicting the prognosis outcomes of patients with different cancers. However, there are no reports on the usage of multi-miRNAs model as signature for the diagnosis or prognosis of LSCC.

Methods

To establish the miRNAs expression-associated model for diagnosis, prognosis prediction and aided therapy of patients with LSCC, the present study enrolled 107 patients with LSCC in clinic and obtained 117 LSCC samples data from TCGA database for evaluation, respectively. Next generation sequencing (NGS), raw data processing, the least absolute shrinkage and selection operator algorithm, Cox regression analysis, construction of nomogram and cell function assays (including proliferation, migration and invasion assays) were sequentially performed.

Results

There were massively dysregulated miRNAs in the LSCC compared to normal tissues. A six-miRNAs signature consists of miR-137-3p, miR-3934-5p, miR-1276, miR-129-5p, miR-7-5p and miR-105-5p was built for prognosis prediction of LSCC patients. The six-miRNAs signature is strongly associated with the poor overall survival (OS, p = 2.5e-05, HR: 4.30 [2.20-8.50]), progression free interval (PFI, p = 0.025, HR: 1.94 [1.08-3.46]) and disease specific survival (DSS, p = 1.1e-05, HR: 5.00 [2.50-10.00]). A nomogram for prediction of 2-, 3- and 5-years OS was also developed based on the six-miRNAs signature and clinical features. Furthermore, blocking the function of each of the six miRNAs inhibited proliferation, invasion and migration of LSCC cells.

Conclusions

The performance of six-miRNAs signature described in the current study demonstrated remarkable potential for progression assessment of LSCC. Moreover, the six-miRNAs signature may serve as predictive tool for prognosis and therapeutic targets of LSCC in clinic.

Imaging biomarkers are underutilised but highly predictive prognostic factors for the more fatal breast cancer subtypes

PURPOSE

The development and refinement of breast imaging modalities offer a wealth of diagnostic information such as imaging biomarkers, which are primarily the mammographic appearance of the various breast cancer subtypes. These are readily available preoperatively at the time of diagnosis and can enhance the prognostic value of currently used molecular biomarkers. In this study, we investigated the relative utility of the molecular and imaging biomarkers, both jointly and independently, when predicting long-term patient outcome according to the site of tumour origin.

METHODS

We evaluated the association of imaging biomarkers and conventional molecular biomarkers, (ER, PR, HER-2, Ki67), separately and combined, with long-term patient outcome in all breast cancer cases having complete data on both imaging and molecular biomarkers (n = 2236) diagnosed in our Institute during the period 2008-2019. Large format histopathology technique was used to document intra- and intertumoural heterogeneity and select the appropriate foci for evaluating molecular biomarkers.

RESULTS

The breast cancer imaging biomarkers were strongly predictive of long-term patient outcome. The molecular biomarkers were predictive of outcome only for unifocal acinar adenocarcinoma of the breast (AAB), but less reliable in the multifocal AAB cases due to variability of molecular biomarkers in the individual tumour foci. In breast cancer of mesenchymal origin (BCMO), conventionally termed classic invasive lobular carcinoma, and in cancers originating from the major lactiferous ducts (ductal adenocarcinoma of the breast, DAB), the molecular biomarkers misleadingly indicated favourable prognosis, whereas the imaging biomarkers in BCMO and DAB reliably indicated the high risk of breast cancer death. Among the 2236 breast cancer cases, BCMO and DAB comprised 21% of the breast cancer cases, but accounted for 45% of the breast cancer deaths.

CONCLUSIONS

Integration of imaging biomarkers into the diagnostic workup of breast cancer yields a more precise, comprehensive and prognostically accurate diagnostic report. This is particularly necessary in multifocal AAB cases having intertumoural heterogeneity, in diffuse carcinomas (DAB and BCMO), and in cases with combined DAB and AAB. In such cases, the imaging biomarkers should be prioritised over molecular biomarkers in planning treatment because the latter fail to predict the severity of the disease. In combination with the use of the large section histopathology technique, imaging biomarkers help alleviate some of the current problems in breast cancer management, such as over- and under-assessment of disease extent, which carry the risk of overtreatment and undertreatment.

Biomarkers for diagnosis of stage III, grade C with molar incisor pattern periodontitis in children and young adults: a systematic review and meta-analysis

AIM

To explore the existing salivary, gingival crevicular fluid (GCF), blood, and serum biomarkers associated with grade C molar-incisor pattern (C/MIP) periodontitis in systemically healthy children and young adults.

MATERIALS AND METHODS

Cross-sectional, case-control, and cohort studies on stage III grade C periodontitis or former equivalent diagnosis with analysis of molecular biomarkers in saliva, GCF, blood, or serum were retrieved from six databases and screened based on the eligibility criteria. The risk of bias in included studies was evaluated. Meta-analysis was planned for biomarkers assessed using the same detection methods and sample type in at least two papers.

RESULTS

Out of 5621 studies identified at initial screening, 28 papers were included in the qualitative analysis of which 2 were eligible for meta-analysis for IgG in serum samples. Eighty-seven biomarkers were assessed with the majority being higher in cases than in controls. Only the meta-analysis of total serum IgG with low heterogeneity value revealed a significant increase in its levels in C/MIPs compared to controls (standardised mean difference: 1.08; 95% CI: 0.76, 1.40).

CONCLUSION

There is a paucity of data on biomarkers associated with molar-incisor pattern periodontitis. Although serum IgG levels are raised, other more specific biomarkers in saliva, GCF, and blood/serum may be promising but require further investigation.

Endogenous and viral microRNAs in nasal secretions of water buffaloes (Bubalus bubalis) after Bubaline alphaherpesvirus 1 (BuHV-1) challenge infection

Bubaline alphaherpesvirus 1 (BuHV-1) is a pathogen of water buffaloes responsible for economic loss worldwide. MicroRNAs (miRNAs) regulate gene expression produced by alphaherpesviruses and hosts. This study aimed at (a) unravelling the ability of BuHV-1 to produce miRNAs, including hv1-miR-B6, hv1-miR-B8, hv1-miR-B9; (b) measuring the host immune-related miRNAs associated to herpesvirus infection, including miR-210-3p, miR-490-3p, miR-17-5p, miR-148a-3p, miR-338-3p, miR-370-3p, by RT-qPCR; (c) identifying candidate markers of infection by receiver-operating characteristic (ROC) curves; (d) exploiting the biological functions by pathway enrichment analyses. Five water buffaloes BuHV-1 and Bovine alphaherpesvirus 1 (BoHV-1) free were immunized against Infectious Bovine Rhinotracheitis (IBR). Five additional water buffaloes served as negative controls. All animals were challenged with a virulent wild-type (wt) BuHV-1 via the intranasal route 120 days after the first vaccination. Nasal swabs were obtained at days (d) 0, 2, 4, 7, 10, 15, 30, and 63 post-challenge (pc). The animals of both groups shed wt BuHV-1 up to d7 pc. Results demonstrated that (a) miRNAs produced by the host and BuHV-1 could be efficiently quantified in the nasal secretion up to d63 and d15 pc, respectively; b) the levels of host and BuHV-1 miRNAs are different between vaccinated and control buffaloes; c) miR-370-3p discriminated vaccinated and control animals; d) host immune-related miRNAs may modulate genes involved in the cell adhesion pathway of the neuronal and immune system. Overall, the present study provides evidence that miRNAs can be detected in nasal secretions of water buffaloes and that their expression is modulated by BuHV-1.

Earthquake, floods and changing land use history: A 200-year overview of environmental changes in Selenga River basin as indicated by n-alkanes and related proxies in sediments from shallow lakes

The Selenga River basin, located in southern Siberia, is an important component of the Lake Baikal ecosystem, and comprises approximately 80 % of the Baikal watershed. Within the Selenga River basin, two localized study regions were chosen. The first, the Selenga Delta, is one of the largest inland freshwater floodplains in the world and plays an important role in the ecosystem functioning of Baikal. It purifies the river waters before they enter the lake and acts as a refuge for many of Baikal's endemic species. The second location, the Gusinoozersk region, is southwest of Lake Baikal and the Selenga Delta, and was chosen as a more heavily industrialized region within the Selenga River basin. Anthropogenic activities, including industry, urban settlements, aquaculture and agriculture, have historically increased ecological damage within this area. We assessed possible drivers of changes in sedimentary organic matter (OM) composition within two shallow lakes (SLNG04 and Black Lake), located in the Selenga Delta and the Selenga watershed, respectively. We focused on individual n-alkanes, one of the most abundant and common lipids used to provide information on past vegetation and used multivariate statistics to disentangle changes in the sources of sedimentary OM over time. The depositional OM history of SLNG04B core can be divided in four zones: (i) major influence of non-emergent vascular plants, typically found in transitional environments (ca. 1835 to ca. 1875); (ii) increased influence of grasses/herbs (ca. 1880 to ca. 1910); (iii) transition from non-emergent vascular plants and grasses/herbs to submerged and floating macrophytes and phytoplankton (ca. 1915 to ca. 1945); (iv) maintenance of autochthonous OM from submerged and floating macrophytes and phytoplankton (ca. 1945 to ca. 2014). The depositional OM history of the Black Lake core can be divided in two main zones: (i) major influence of non-emergent vascular plants and submerged and floating macrophytes (ca. 1915 to ca. 1980); (ii) increased influence of grasses/herbs and phytoplankton (ca. 1980 to ca. 2010). Natural events (e.g., an earthquake in 1862 caused flooding and subsidence of much of the land surrounding SLNG04 lake and a further catastrophic flood event in 1897) and anthropogenic activities (e.g., nutrient pollution from expansion of agricultural and livestock population) changed the composition of sedimentary OM resulting in ecological shifts across trophic levels in the Selenga River basin.

Evaluation of soil ecological health after exposure to environmentally relevant doses of Di (2-ethylhexyl) phthalate: Insights from toxicological studies of earthworms at different ecological niches

As one of the most critical soil faunas in agroecosystems, earthworms are significant in preserving soil ecological health. Di (2-ethylhexyl) phthalate (DEHP) is a major plasticizer and widely used in plastic products like agricultural films. However, it has become ubiquitous contaminant in agricultural soil and poses a potential threat to soil health. Although the awareness of the impacts of DEHP on soil ecology is increasing, its adverse effects on soil invertebrates, especially earthworms, are still not well developed. In this study, the ecotoxicological effects and underlying mechanisms of environmentally relevant doses DEHP on earthworms of different ecological niches were investigated at the individual, cytological, and biochemical levels, respectively. Results showed that the acute toxicity of DEHP to M. guillelmi was higher than E. foetida. DEHP induced reactive oxygen species (ROS) levels and further caused oxidative damage (including cellular DNA and lipid peroxidation damage) in both species, speculating that they may exhibit similar oxidative stress mechanisms. Furthermore, two earthworms presented the alleviated toxicity when re-cultured in uncontaminated circumstances, yet, the accumulated ROS in bodies could not be completely scavenged. Risk assessment indicated that the detrimental impacts of DEHP were more significant in the M. guillelmi than in E. foetida in whole experiments prides, and the biomarkers additionally showed a species-specific trend. Besides, molecular docking revealed that DEHP could bind to the active center of superoxide dismutase/catalase (SOD/CAT) by hydrogen bonding or hydrophobic interactions. Overall, this study will provide a novel insight for accurate contaminant risk assessment, and also highlight that the comprehensive biological effects of different species should be emphasized in soil ecological health diagnostics and environmental toxicology assays, as otherwise it may lead to underestimation or misestimation of the soil health risk of contaminants.

Molecular biomarkers and cognitive impairment in multiple sclerosis: State of the field, limitations, and future direction - A systematic review and meta-analysis

OBJECTIVE

Multiple sclerosis (MS) is associated with cognitive impairment (CI) such as slowed information processing speed (IPS). Currently, no immunocellular or molecular markers have been established in cerebrospinal fluid and serum analysis as surrogate biomarkers with diagnostic or predictive value for the development of CI. This systematic review and meta-analysis aims to sum up the evidence regarding currently discussed markers for CI in MS.

METHODS

A literature search was conducted on molecular biomarkers of CI in MS, such as neurofilament light chain, chitinases, and vitamin D.

RESULTS

5543 publications were screened, of which 77 entered the systematic review. 13 studies were included in the meta-analysis. Neurofilament light chain (CSF: r_p = -0.294, p = 0.003; serum: r_p = -0.137, p = 0.001) and serum levels of vitamin D (r_p = 0.190, p = 0.014) were associated with IPS outcomes.

CONCLUSIONS

Neurofilament light chain and vitamin D are promising biomarkers to track impairments in IPS in MS. Further longitudinal research is needed to establish the use of molecular biomarkers to monitor cognitive decline.

Tumor mutation burden involving epigenetic regulatory genes and the RhoA GTPase predicts overall survival in nodal mature T-cell lymphomas

Nodal mature T-cell lymphomas (nMTCL) comprises a heterogeneous group of rare malignancies with aggressive biological behavior and poor prognosis. Epigenetic phenomena, including mutations in genes that control DNA methylation and histone deacetylation, in addition to inactivating mutations in the RhoA GTPase, play a central role in its pathogenesis and constitute potential new targets for therapeutic intervention. Tumor mutational burden (TMB) reflects the process of clonal evolution, predicts response to anti-cancer therapies and has emerged as a prognostic biomarker in several solid neoplasms; however, its potential prognostic impact remains unknown in nMTCL. In this study, we conducted Sanger sequencing of formalin-fixed paraffin-embedded (FFPE) diagnostic tumor samples using a target-panel to search for recurrent mutations involving the IDH-1/IDH-2, TET-2, DNMT3A and RhoA genes in 59 cases of nMTCL. For the first time, we demonstrated that high-TMB, defined by the presence of ≥ two mutations involving the aforementioned genes, was associated with decreased overall survival in nMTCL patients treated with CHOP-like regimens. Additionally, high-TMB was correlated with bulky disease, lower overall response rate, and higher mortality. Future studies using larger cohorts may validate our preliminary results that indicate TMB as a potential molecular biomarker associated with adverse prognosis in nMTCL.

Chemical and biochemical responses to sub-lethal doses of mercury and cadmium in gilthead seabream (Sparus aurata)

Specimens of Sparus aurata were exposed to sub-lethal concentrations of Hg and Cd for 25 days and the levels of both metals were investigated in organs and tissues. Bioaccumulation of Hg decreased as follow: gills > kidney > liver > skin > muscle, while the order of Cd bioaccumulation was: liver > kidney > gills > skin > muscle. Immediately after exposure, both metals showed the highest bioaccumulation in gills and skin indicating that these organs are reliable targets for biomonitoring studies after short term exposure. Metals introduction caused a significant time-dependent concentrations increase in kidney and liver, while in the muscle a significant increase of Hg was recorded only at the end of the experimentation. The effects of exposure were also investigated, at biochemical level, in the liver, which represents the main target of xenobiotics biotransformation and metabolism in fish. Exposed fishes exhibited a reduction of total lipid level, a decrease of polyunsaturated fatty acids (PUFA), together with a MDA increase. This suggests a direct effect of contaminants on oxidative stress induction that, through the MDA increase, altered the membrane fatty acids composition decreasing the PUFA content. As it regards molecular markers related to oxidative stress and lipid metanolism, a significant increase of Nrf2, Hif-1α and Ampk and a decrease of Fas were observed after exposure to both metals, while an Nf-kB increase was recorded in specimens exposed to Hg, docuemnting a correlation with oxidative stress and consequent metabolism adaptation. Finally, these results suggest the possibility to adopt these biomarkers to explore fish metabolic responses to environmental pollution.

The successful use of -omic technologies to achieve the 'One Health' concept in meat producing animals

Human health and wellbeing are closely linked to healthy domestic animals, a vital wildlife, and an intact ecosystem. This holistic concept is referred to as 'One Health'. In this review, we provide an overview of the potential and the challenges for the use of modern -omics technologies, especially transcriptomics and proteomics, to implement the 'One Health' idea for food-producing animals. These high-throughput studies offer opportunities to find new potential molecular biomarkers to monitor animal health, detect pharmacological interventions and evaluate the wellbeing of farm animals in modern intensive livestock systems.

Probing individual-level structural atrophy in frontal glioma patients

Although every glioma patient varies in tumor size, location, histological grade and molecular biomarkers, non-tumoral morphological abnormalities are commonly detected by a statistical comparison among patient groups, missing the information of individual morphological alterations. In this study, we introduced an individual-level structural abnormality detection method for glioma patients and proposed several abnormality indexes to depict individual atrophy patterns. Forty-five patients with a glioma in the frontal lobe and fifty-one age-matched healthy controls participated in the study. Individual structural abnormality maps (SAM) were generated using patients' preoperative T1 images, by calculating the degree of deviation of voxel volume in each patient with the normative model built from healthy controls. Based on SAM, a series of individual abnormality indexes were computed, and their relationship with glioma characteristics was explored. The results demonstrated that glioma patients showed unique non-tumoral atrophy patterns with overlapping atrophy regions mainly located at hippocampus, parahippocampus, amygdala, insula, middle temporal gyrus and inferior temporal gyrus, which are closely related to the human cognitive functions. The abnormality indexes were associated with several molecular biomarkers including isocitrate dehydrogenase (IDH) mutation, 1p/19q co-deletion and telomerase reverse transcriptase (TERT) promoter mutation. Our study provides an effective way to access the individual-level non-tumoral structural abnormalities in glioma patients, which has the potential to significantly improve individualized precision medicine.

Current status of precision medicine in pediatric oncology in Spain: a consensus report by the Spanish Society of Paediatric Haematology and Oncology (SEHOP)

The study analyzes the current status of personalized medicine in pediatric oncology in Spain. It gathers national data on the tumor molecular studies and genomic sequencing carried out at diagnosis and at relapse, the centers that perform these studies, the technology used and the interpretation and clinical applicability of the results. Current challenges and future directions to achieve a coordinated national personalized medicine strategy in pediatric oncology are also discussed. Next generation sequencing-based (NGS) gene panels are the technology used in the majority of centers and financial limitations are the main reason for not incorporating these studies into routine care. Nowadays, the application of precision medicine in pediatric oncology is a reality in a great number of Spanish centers. However, its implementation is uneven and lacks standardization of protocols; therefore, national coordination to overcome the inequalities is required. Collaborative work within the Personalized Medicine Group of SEHOP is an adequate framework for encouraging a step forward in the effort to move precision medicine into the national healthcare system.

Identification of a key glioblastoma candidate gene, FUBP3, based on weighted gene co-expression network analysis

BACKGROUND

Glioblastoma multiforme (GBM) is the most common aggressive malignant brain tumor. However, the molecular mechanism of glioblastoma formation is still poorly understood. To identify candidate genes that may be connected to glioma growth and development, weighted gene co-expression network analysis (WGCNA) was performed to construct a gene co-expression network between gene sets and clinical characteristics. We also explored the function of the key candidate gene.

METHODS

Two GBM datasets were selected from GEO Datasets. The R language was used to identify differentially expressed genes. WGCNA was performed to construct a gene co-expression network in the GEO glioblastoma samples. A custom Venn diagram website was used to find the intersecting genes. The GEPIA website was applied for survival analysis to determine the significant gene, FUBP3. OS, DSS, and PFI analyses, based on the UCSC Cancer Genomics Browser, were performed to verify the significance of FUBP3. Immunohistochemistry was performed to evaluate the expression of FUBP3 in glioblastoma and adjacent normal tissue. KEGG and GO enrichment analyses were used to reveal possible functions of FUBP3. Microenvironment analysis was used to explore the relationship between FUBP3 and immune infiltration. Immunohistochemistry was performed to verify the results of the microenvironment analysis.

RESULTS

GSE70231 and GSE108474 were selected from GEO Datasets, then 715 and 694 differentially expressed genes (DEGs) from GSE70231 and GSE108474, respectively, were identified. We then performed weighted gene co-expression network analysis (WGCNA) and identified the most downregulated gene modules of GSE70231 and GSE108474, and 659 and 3915 module genes from GSE70231 and GSE108474, respectively, were selected. Five intersection genes (FUBP3, DAD1, CLIC1, ABR, and DNM1) were calculated by Venn diagram. FUBP3 was then identified as the only significant gene by survival analysis using the GEPIA website. OS, DSS, and PFI analyses verified the significance of FUBP3. Immunohistochemical analysis revealed FUBP3 expression in GBM and adjacent normal tissue. KEGG and GO analyses uncovered the possible function of FUBP3 in GBM. Tumor microenvironment analysis showed that FUBP3 may be connected to immune infiltration, and immunohistochemistry identified a positive correlation between immune cells (CD4 + T cells, CD8 + T cells, and macrophages) and FUBP3.

CONCLUSION

FUBP3 is associated with immune surveillance in GBM, indicating that it has a great impact on GBM development and progression. Therefore, interventions involving FUBP3 and its regulatory pathway may be a new approach for GBM treatment.

Novel molecular biomarkers of cancer therapy-induced cardiotoxicity in adult population: a scoping review

Aim

Cancer treatments are associated with cardiotoxic events that predispose to cardiac pathology and compromise the survival of patients, making necessary the identification of new molecular biomarkers to detect cardiotoxicity. This scoping review aims to identify the available evidence on novel molecular biomarkers associated with cardiotoxicity in the adult population undergoing cancer therapy.

Methods and results

The databases Medline, Web of Science, Scopus, and Embase were screened for the identification of published studies until 23 August 2020, searching for novel molecular biomarkers reported in cancer therapy‐related cardiac dysfunction in adult patients. A total of 42 studies that met the eligibility criteria were included. Fourteen studies reported 44 new protein biomarkers, 18 studies reported 57 new single nucleotide polymorphism biomarkers, and 11 studies reported 171 new gene expression profiles associated with cardiotoxicity. Data were extracted for 272 novel molecular biomarkers reported and evaluated in 7084 cancer patients, of which only 13 were identified in more than one study (MPO, sST2, GDF‐15, TGF‐B1, rs1056892, rs1883112, rs4673, rs13058338, rs1695, miR‐1, miR‐25‐3p, miR‐34a‐5p, and miR‐423‐5p), showing values for area under the curve > 0.73 (range 0.74–0.85), odds ratio 0.26–7.17, and hazard ratio 1.28–1.80.

Conclusions

Multiple studies presented a significant number of novel molecular biomarkers as promising predictors for risk assessment of cardiac dysfunction related to cancer therapy, but the characteristics of the studies carried out and the determinations applied do not allow suggesting the clinical use of these molecular biomarkers in the assessment of cancer therapy‐induced cardiotoxicity.

Evaluation of transcriptional biomarkers using a high-resolution regression approach: Concentration-dependence of selected transcripts in copper-exposed freshwater mussels (Anodonta anatina)

We tested concentration-dependence of selected gene transcripts (cat, gst, hsp70, hsp90, mt and sod) for evaluation as biomarkers of chemical stress. Contrary to the common approach of factorial designs and few exposure concentrations, we used regression across a high-resolution concentration series. Specifically, freshwater mussels (Anodonta anatina) were acutely (96 h) exposed to Cu (13 nominal concentrations, measuring 0.13-1 600 µg/L), and transcripts were measured by RT-qPCR. In digestive glands, cat, hsp90 and mt decreased with water Cu (p < 0.05), but response magnitudes saturated at < 2-fold decreases. In gills, gst, hsp70, hsp90 and mt increased with water Cu (p < 0.05). While hsp70, hsp90 and mt exceeded 2-fold increases within the exposure range, high Cu concentrations were required (38-160 µg/L). Although gill responses were generally more robust compared to digestive glands, overall small response magnitudes and moderate sensitivity may set limit for potential application as general biomarkers of chemical stress.

Effects of tralopyril on histological, biochemical and molecular impacts in Pacific oyster, Crassostrea gigas

Recently, the toxic effects of tralopyril, as a new antifouling biocide, on aquatic organisms have aroused widespread attention about the potential toxicity. However, the mechanism of tralopyril on marine mollusks has not been elaborated clearly. In this study, the histological, biochemical and molecular impacts of tralopyril on adult Crassostrea gigas were investigated. The results indicated that the 96 h LC50 of tralopyril to adult Crassostrea gigas was 911 μg/L. After exposure to tralopyril (0, 40, 80 and 160 μg/L) for 6 days, the mantle mucus secretion coverage ratio of Crassostrea gigas was increased with a dose-dependent pattern. Catalase (CAT) activity was significantly increased, amylase (AMS) activity, acid phosphatase (ACP) activity and calcium ion (Ca²⁺) concentration significantly decreased. Meanwhile, integrated biomarker responses (IBR) index suggested that higher concentrations of tralopyril caused severer damage to Crassostrea gigas. In addition, the mRNA expression levels of biomineralization related genes in the mantle were significantly upregulated. Collectively, this study firstly revealed the histological, biochemical and molecular impacts of tralopyril exposure on adult Crassostrea gigas, which provided new insights for understanding the toxicity of tralopyril in marine mollusks.

Development of the DNA-based biosensors for high performance in detection of molecular biomarkers: More rapid, sensitive, and universal

The molecular biomarkers are molecules that are closely related to specific physiological states. Numerous molecular biomarkers have been identified as targets for disease diagnosis and biological research. To date, developing highly efficient probes for the precise detection of biomarkers has become an attractive research field which is very important for biological and biochemical studies. During the past decades, not only the small chemical probe molecules but also the biomacromolecules such as enzymes, antibodies, and nucleic acids have been introduced to construct of biosensor platform to achieve the detection of biomarkers in a highly specific and highly efficient way. Nevertheless, improving the performance of the biosensors, especially in clinical applications, is still in urgent demand in this field. A noteworthy example is the Corona Virus Disease 2019 (COVID-19) that breaks out globally in a short time in 2020. The COVID-19 was caused by the virus called SARS-CoV-2. Early diagnosis is very important to block the infection of the virus. Therefore, during these months scientists have developed dozens of methods to achieve rapid and sensitive detection of the virus. Nowadays some of these new methods have been applied for producing the commercial detection kit and help people against the disease worldwide. DNA-based biosensors are useful tools that have been widely applied in the detection of molecular biomarkers. The good stability, high specificity, and excellent biocompatibility make the DNA-based biosensors versatile in application both in vitro and in vivo. In this paper, we will review the major methods that emerged in recent years on the design of DNA-based biosensors and their applications. Moreover, we will also briefly discuss the possible future direction of DNA-based biosensors design. We believe this is helpful for people interested in not only the biosensor field but also in the field of analytical chemistry, DNA nanotechnology, biology, and disease diagnosis.

Molecular biomarkers correlate with brain grey and white matter changes in patients with mitochondrial m.3243A > G mutation

INTRODUCTION

The mitochondrial DNA (mtDNA) m.3243A > G mutation in the MT-TL1 gene results in a multi-systemic disease, that is commonly associated with neurodegenerative changes in the brain.

METHODS

Seventeen patients harboring the m3243A > G mutation were enrolled (age 43.1 ± 11.4 years, 10 M/7F). A panel of plasma biomarkers including lactate acid, alanine, L-arginine, fibroblast growth factor 21 (FGF-21), growth/differentiation factor 15 (GDF-15) and circulating cell free -mtDNA (ccf-mtDNA), as well as blood, urine and muscle mtDNA heteroplasmy were evaluated. Patients also underwent a brain standardized MR protocol that included volumetric T1-weighted images and diffusion-weighted MRI. Twenty sex- and age-matched healthy controls were included. Voxel-wise analysis was performed on T1-weighted and diffusion imaging, respectively with VBM (voxel-based morphometry) and TBSS (Tract-based Spatial Statistics). Ventricular lactate was also evaluated by ¹H-MR spectroscopy.

RESULTS

A widespread cortical gray matter (GM) loss was observed, more severe (p < 0.001) in the bilateral calcarine, insular, frontal and parietal cortex, along with infratentorial cerebellar cortex. High urine mtDNA mutation load, high levels of plasma lactate and alanine, low levels of plasma arginine, high levels of serum FGF-21 and ventricular lactate accumulation significantly (p < 0.05) correlated with the reduced brain GM density. Widespread microstructural alterations were highlighted in the white matter, significantly (p < 0.05) correlated with plasma alanine and arginine levels, with mtDNA mutation load in urine, with high level of serum GDF-15 and with high content of plasma ccf-mtDNA.

CONCLUSIONS

Our results suggest that the synergy of two pathogenic mechanisms, mtDNA-related mitochondrial respiratory deficiency and defective nitric oxide metabolism, contributes to the brain neurodegeneration in m.3243A > G patients.

Molecular Signatures of KRAS-Mutated Lung Adenocarcinoma: Analysis of Concomitant EGFR, ALK, STK11, and PD-L1 Status

Background

KRAS mutations are the most common oncogenic driver mutations of non-small cell lung cancer (NSCLC) in the Western world. Mutations of the KRAS gene are most prevalent in the patient population of current and former cigarette smokers. With the recent pivotal approval of a targeted inhibitor therapy for patients with KRAS p.G12C mutated and pretreated NSCLC, analysis of the heterogeneity of KRAS mutations and concomitant molecular alterations in patients with these tumors at all clinical stages is indicated.

Methods

In this retrospective analysis, patient pathology records were reviewed for all cases receiving a pathologic diagnosis of NSCLC within our hospital system. All data were collected with IRB approval. Cases of indeterminate tumor type favoring a non-lung primary, as well as non-adenocarcinoma NSCLC (eg, squamous) were excluded from the cohort. In this hospital system, molecular testing for KRAS mutations is part of a molecular biomarker panel that is reflex ordered at initial diagnosis by the pathologist and may be performed as a single gene test or as a solid organ cancer hotspot panel by next generation sequencing. For each patient, KRAS mutational status and specific KRAS mutations, if present, were collated. Additional information assessed for this study included patient demographics (age, gender, and smoking history), tumor staging if available, PD-L1 expression levels by immunohistochemistry (IHC), and the presence of other genetic alterations (EGFR, ALK, and STK11).

Results

Between January 1, 2017 and January 1, 2019, there were 276 patients diagnosed with NSCLC of all stages who had KRAS mutational analysis performed in our hospital system and who met the criteria for inclusion into the study cohort. A KRAS driver mutation was detected in 29% of these patients. The most frequently identified KRAS mutation was p.G12C (38%), followed by p.G12D (21%) and p.G12V (13%). KRAS-mutated lung adenocarcinoma was significantly associated with current or former patient smoking status in this cohort (29/202 (14%) smokers and 1/74 (1%) non-smokers; P = .0006). PD-L1 expression of at least 1% by IHC was present in 43% of KRAS-mutated lung adenocarcinomas and 45% of non-KRAS-mutated adenocarcinomas. In this study, KRAS mutations were not found to co-occur with gene alterations in EGFR, ALK, or STK11. In 48% of cases, at least one genetic alteration (KRAS, ALK, EGFR, or STK11) was identified.

Conclusions

In this study cohort, KRAS-mutated lung adenocarcinoma demonstrated significant mutational heterogeneity, which is consistent with previously published studies. KRAS mutational status was also significantly associated with a current or former smoking history. Notably, p.G12C was the most frequently identified KRAS mutation in this cohort, with a frequency of 38%. This finding is particularly relevant given the recent approval of a KRAS p.G12C-specific targeted inhibitor therapy and the continued development of additional KRAS targeted therapies that may prove effective in treating NSCLC. These findings also highlight the necessity of considering molecular testing for KRAS mutations in patients with NSCLC and a smoking history, as this population most frequently harbors KRAS mutations and may benefit from these emerging targeted therapies.

Data analysis methods for defining biomarkers from omics data

Omics mainly includes genomics, epigenomics, transcriptomics, proteomics and metabolomics. The rapid development of omics technology has opened up new ways to study disease diagnosis and prognosis and to define prospective information of complex diseases. Since omics data are usually large and complex, the method used to analyze the data and to define important information is crucial in omics study. In this review, we focus on advances in biomarker discovery methods based on omics data in the last decade, and categorize them as individual feature analysis, combinatorial feature analysis and network analysis. We also discuss the challenges and perspectives in this field.

Transcriptomic response of the intertidal limpet Patella vulgata to temperature extremes

Global warming is challenging wild species in land and water. In the intertidal zone, species are already living at their thermal limits, being vulnerable even to small increases in maximum habitat temperatures. Knowledge of the mechanisms by which many intertidal zone species cope with elevated temperatures is limited. We analysed the molecular thermal stress response of the limpet Patella vulgata under slight and frequent (one-day), and extreme and rare (three-day) warming events. Using RNA-seq to assess differential gene expression among treatments, differing molecular responses were obtained in the two treatments, with more changes in gene expression after the three-day event; with one-third of the differentially expressed transcripts being down-regulated. However, across treatments we observed shifts in gene expression for common aspects of the heat stress response including intra-cellular communication, protein chaperoning, proteolysis and cell cycle arrest. Of the 71,675 transcripts obtained, only 259 were differentially expressed after both heating events. From these, 218 defined the core group (i.e. genes induced by thermal stress with similar expression patterns irrespective of the magnitude of the warming event). The core group was composed of already well-studied genes in heat stress responses in intertidal organisms (e.g. heat shock proteins), but also genes from less explored metabolic pathways, e.g. the ubiquitin system, which were also fundamental regardless of the magnitude of the imposed warming. Moreover, we have also identified 41 signaling genes (i.e. a set of genes responding to both events and with expression patterns specific to the intensity of thermal stress), principally including genes involved in the maintenance of extracellular structure that have previously not been identified as part of the response to thermal stress in intertidal zone organisms. These signaling genes will be useful heat stress molecular biomarkers for monitoring heat stress in natural populations.

Molecular biomarkers as tool for early warning by chlorpyrifos exposure on Alpine chironomids

Pesticides used in agriculture can be transported at a medium-high distance due to the drift effect, reaching even remote areas as mountain regions, glaciers, and snow cover. With the melting process, pesticides enter freshwater glacier ecosystems, becoming a threat to wildlife fauna, mainly dominated by Diptera Chironomidae. Chlorpyrifos (CPF), as one of the most commonly used pesticides in alpine vineyards and apple orchards, is frequently detected in icemelt waters. We selected as target species, larvae of the cold stenothermal chironomid Diamesa zernyi, collected in two glacier-fed streams (Presena and Amola) in the Italian Alps. Firstly, a de novo transcriptome was obtained, and secondly, a gene array was designed to study the molecular response of a wild population of D. zernyi exposed to three sub-lethal CPF concentrations corresponding to 1/100 LC10 (0.011 μg/L), 1/10 LC10 (0.11 μg/L), and LC10 (1.1 μg/L), for 24 h. The sub-organismal response was evaluated by Real-Time Polymerase Chain Reaction (RT-PCR), employing 40 genes related to essential metabolic routes as future candidates for biomarkers in wildlife chironomids. After 24 h, the endocrine system (E75, E93, EcR, and Met), detoxification response (GSTO3, GSTS1), and stress response (hsp75, hsp83, HYOU1) were altered. CPF seems to act as an endocrine disruptor and could lead to defective larval development, disrupted cellular homeostasis through heat shock proteins (HSPs) alteration (defective protein folding and mitochondrial functions), as well as oxidative damage (confirmed by increased GST expression). For the first time, molecular studies detected early alarm signals in wildlife in glacier environments. Our findings confirm the high environmental risk of CPF affecting aquatic insect metabolism and raise the level of concern about this pesticide in high altitude water bodies, generally considered pristine. Furthermore, this study emphasizes the incipient need to use non-model organisms for the evaluation of natural ecosystems. We also highlight the demand for research into new molecular biomarkers, and the importance of including molecular approaches in toxicology evaluations to detect the early adverse effects of pollutants.

Metabolite patterns link diet, obesity, and type 2 diabetes in a Hispanic population

INTRODUCTION

Obesity is a precursor of type 2 diabetes (T2D).

OBJECTIVES

Our aim was to identify metabolic signatures of T2D and dietary factors unique to obesity.

METHODS

We examined a subsample of the Boston Puerto Rican Health Study (BPRHS) population with a high prevalence of obesity and T2D at baseline (n = 806) and participants (without T2D at baseline) at 5-year follow-up (n = 412). We determined differences in metabolite profiles between T2D and non-T2D participants of the whole sample and according to abdominal obesity status. Enrichment analysis was performed to identify metabolic pathways that were over-represented by metabolites that differed between T2D and non-T2D participants. T2D-associated metabolites unique to obesity were examined for correlation with dietary food groups to understand metabolic links between dietary intake and T2D risk. False Discovery Rate method was used to correct for multiple testing.

RESULTS

Of 526 targeted metabolites, 179 differed between T2D and non-T2D in the whole sample, 64 in non-obese participants and 120 unique to participants with abdominal obesity. Twenty-four of 120 metabolites were replicated and were associated with T2D incidence at 5-year follow-up. Enrichment analysis pointed to three metabolic pathways that were overrepresented in obesity-associated T2D: phosphatidylethanolamine (PE), long-chain fatty acids, and glutamate metabolism. Elevated intakes of three food groups, energy-dense takeout food, dairy intake and sugar-sweetened beverages, associated with 13 metabolites represented by the three pathways.

CONCLUSION

Metabolic signatures of lipid and glutamate metabolism link obesity to T2D, in parallel with increased intake of dairy and sugar-sweetened beverages, thereby providing insight into the relationship between dietary habits and T2D risk.

Preoperative ultrasound radiomics analysis for expression of multiple molecular biomarkers in mass type of breast ductal carcinoma in situ

BACKGROUND

The molecular biomarkers of breast ductal carcinoma in situ (DCIS) have important guiding significance for individualized precision treatment. This study was intended to explore the significance of radiomics based on ultrasound images to predict the expression of molecular biomarkers of mass type of DCIS.

METHODS

116 patients with mass type of DCIS were included in this retrospective study. The radiomics features were extracted based on ultrasound images. According to the ratio of 7:3, the data sets of molecular biomarkers were split into training set and test set. The radiomics models were developed to predict the expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), Ki67, p16, and p53 by using combination of multiple feature selection and classifiers. The predictive performance of the models were evaluated using the area under the curve (AUC) of the receiver operating curve.

RESULTS

The investigators extracted 5234 radiomics features from ultrasound images. 12, 23, 41, 51, 31 and 23 features were important for constructing the models. The radiomics scores were significantly (P < 0.05) in each molecular marker expression of mass type of DCIS. The radiomics models showed predictive performance with AUC greater than 0.7 in the training set and test set: ER (0.94 and 0.84), PR (0.90 and 0.78), HER2 (0.94 and 0.74), Ki67 (0.95 and 0.86), p16 (0.96 and 0.78), and p53 (0.95 and 0.74), respectively.

CONCLUSION

Ultrasonic-based radiomics analysis provided a noninvasive preoperative method for predicting the expression of molecular markers of mass type of DCIS with good accuracy.

Host-dependent molecular factors mediating SARS-CoV-2 infection to gain clinical insights for developing effective targeted therapy

Coronavirus disease 2019 (COVID-19), a recent viral pandemic that first began in December 2019, in Hunan wildlife market, Wuhan, China. The infection is caused by a coronavirus, SARS-CoV-2 and clinically characterized by common symptoms including fever, dry cough, loss of taste/smell, myalgia and pneumonia in severe cases. With overwhelming spikes in infection and death, its pathogenesis yet remains elusive. Since the infection spread rapidly, its healthcare demands are overwhelming with uncontrollable emergencies. Although laboratory testing and analysis are developing at an enormous pace, the high momentum of severe cases demand more rapid strategies for initial screening and patient stratification. Several molecular biomarkers like C-reactive protein, interleukin-6 (IL6), eosinophils and cytokines, and artificial intelligence (AI) based screening approaches have been developed by various studies to assist this vast medical demand. This review is an attempt to collate the outcomes of such studies, thus highlighting the utility of AI in rapid screening of molecular markers along with chest X-rays and other COVID-19 symptoms to enable faster diagnosis and patient stratification. By doing so, we also found that molecular markers such as C-reactive protein, IL-6 eosinophils, etc. showed significant differences between severe and non-severe cases of COVID-19 patients. CT findings in the lungs also showed different patterns like lung consolidation significantly higher in patients with poor recovery and lung lesions and fibrosis being higher in patients with good recovery. Thus, from these evidences we perceive that an initial rapid screening using integrated AI approach could be a way forward in efficient patient stratification.

Identification of a novel autophagy signature for predicting survival in patients with lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the most commonhistological lung cancer subtype, with an overall five-year survivalrate of only 17%. In this study, we aimed to identify autophagy-related genes (ARGs) and develop an LUAD prognostic signature.

Methods

In this study, we obtained ARGs from three databases and downloaded gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We used TCGA-LUAD (n = 490) for a training and testing dataset, and GSE50081 (n = 127) as the external validation dataset.The least absolute shrinkage and selection operator (LASSO) Cox and multivariate Cox regression models were used to generate an autophagy-related signature. We performed gene set enrichment analysis (GSEA) and immune cell analysis between the high- and low-risk groups. A nomogram was built to guide the individual treatment for LUAD patients.

Results

We identified a total of 83 differentially expressed ARGs (DEARGs) from the TCGA-LUAD dataset, including 33 upregulated DEARGs and 50 downregulated DEARGs, both with thresholds of adjusted P < 0.05 and |Fold change| > 1.5. Using LASSO and multivariate Cox regression analyses, we identified 10 ARGs that we used to build a prognostic signature with areas under the curve (AUCs) of 0.705, 0.715, and 0.778 at 1, 3, and 5 years, respectively. Using the risk score formula, the LUAD patients were divided into low- or high-risk groups. Our GSEA results suggested that the low-risk group were enriched in metabolism and immune-related pathways, while the high-risk group was involved in tumorigenesis and tumor progression pathways. Immune cell analysis revealed that, when compared to the high-risk group, the low-risk group had a lower cell fraction of M0- and M1- macrophages, and higher CD4 and PD-L1 expression levels.

Conclusion

Our identified robust signature may provide novel insight into underlying autophagy mechanisms as well as therapeutic strategies for LUAD treatment.

Identification of molecular biomarkers and pathways of NSCLC: insights from a systems biomedicine perspective

BACKGROUND

Worldwide, more than 80% of identified lung cancer cases are associated to the non-small cell lung cancer (NSCLC). We used microarray gene expression dataset GSE10245 to identify key biomarkers and associated pathways in NSCLC.

RESULTS

To collect Differentially Expressed Genes (DEGs) from the dataset GSE10245, we applied the R statistical language. Functional analysis was completed using the Database for Annotation Visualization and Integrated Discovery (DAVID) online repository. The DifferentialNet database was used to construct Protein-protein interaction (PPI) network and visualized it with the Cytoscape software. Using the Molecular Complex Detection (MCODE) method, we identify clusters from the constructed PPI network. Finally, survival analysis was performed to acquire the overall survival (OS) values of the key genes. One thousand eighty two DEGs were unveiled after applying statistical criterion. Functional analysis showed that overexpressed DEGs were greatly involved with epidermis development and keratinocyte differentiation; the under-expressed DEGs were principally associated with the positive regulation of nitric oxide biosynthetic process and signal transduction. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway investigation explored that the overexpressed DEGs were highly involved with the cell cycle; the under-expressed DEGs were involved with cell adhesion molecules. The PPI network was constructed with 474 nodes and 2233 connections.

CONCLUSIONS

Using the connectivity method, 12 genes were considered as hub genes. Survival analysis showed worse OS value for SFN, DSP, and PHGDH. Outcomes indicate that Stratifin may play a crucial role in the development of NSCLC.

DNA repair pathway activation features in follicular and papillary thyroid tumors, interrogated using 95 experimental RNA sequencing profiles

DNA repair can prevent mutations and cancer development, but it can also restore damaged tumor cells after chemo and radiation therapy. We performed RNA sequencing on 95 human pathological thyroid biosamples including 17 follicular adenomas, 23 follicular cancers, 3 medullar cancers, 51 papillary cancers and 1 poorly differentiated cancer. The gene expression profiles are annotated here with the clinical and histological diagnoses and, for papillary cancers, with BRAF gene V600E mutation status. DNA repair molecular pathway analysis showed strongly upregulated pathway activation levels for most of the differential pathways in the papillary cancer and moderately upregulated pattern in the follicular cancer, when compared to the follicular adenomas. This was observed for the BRCA1, ATM, p53, excision repair, and mismatch repair pathways. This finding was validated using independent thyroid tumor expression dataset PRJEB11591. We also analyzed gene expression patterns linked with the radioiodine resistant thyroid tumors (n = 13) and identified 871 differential genes that according to Gene Ontology analysis formed two functional groups: (i) response to topologically incorrect protein and (ii) aldo-keto reductase (NADP) activity. We also found RNA sequencing reads for two hybrid transcripts: one in-frame fusion for well-known NCOA4-RET translocation, and another frameshift fusion of ALK oncogene with a new partner ARHGAP12. The latter could probably support increased expression of truncated ALK downstream from 4th exon out of 28. Both fusions were found in papillary thyroid cancers of follicular histologic subtype with node metastases, one of them (NCOA4-RET) for the radioactive iodine resistant tumor. The differences in DNA repair activation patterns may help to improve therapy of different thyroid cancer types under investigation and the data communicated may serve for finding additional markers of radioiodine resistance.

Season specific influence of projected ocean changes on the response to cadmium of stress-related genes in Mytilus galloprovincialis

Anthropogenic inputs of carbon dioxide in the atmosphere are driving ocean warming and acidification. The potential threat represented by these changes for marine species could be amplified in coastal areas, characterized by higher levels of pollutants. In addition, temperate organisms may exhibit a different seasonal tolerance to stressors influenced by fluctuations of environmental and physiological factors. In this study, Mediterranean mussels Mytilus galloprovincialis collected both in summer and winter were exposed to combinations of two temperatures (SST, seasonal surface temperature and SST+5 °C) and two levels of pH (8.20 and 7.40) in clean or cadmium contaminated seawater (20 μg/L Cd). mRNA levels of genes related to metal-induced stress response were investigated, including metallothionein mt-20, heat-shock protein hsp70, superoxide dismutase Cu/Zn-sod, catalase cat, glutathione peroxidase gpx1 and glutathione S-transferase gst-pi. To further elucidate if tissues with different physiological roles could exhibit different responsiveness, such analyses were carried out in digestive gland and in gills of exposed mussels. mt-20 mRNA increase after Cd-exposure was higher in the digestive gland than in the gills, with few modulations by temperature or pH only in the latter. Acidification, alone or in combination with other stressors, increased hsp70 mRNA, with seasonal- and tissue-specificities (higher in summer and in digestive gland). Among antioxidants, gpx1 mRNA was affected by Cd in both tissues and seasons, with further modulations due to pH and temperature variation tissue- and season-specific; in winter the combination of Cd, warming and acidification affected Cu/Zn-sod both in digestive gland and gills and cat only in gills, while weak seasonal variations were observed for gst-pi transcripts only in digestive gland. The overall results highlighted the importance of considering seasonality and responsiveness of different tissues to predict the effects of sudden changes in environmental parameters on responsiveness to and toxicity of chemicals in marine coastal organisms.

An integrated autophagy-related gene signature predicts prognosis in human endometrial Cancer

Background

Globally, endometrial cancer is the fourth most common malignant tumor in women and the number of women being diagnosed is increasing. Tumor progression is strongly related to the cell survival-promoting functions of autophagy. We explored the relationship between endometrial cancer prognoses and the expression of autophagy genes using human autophagy databases.

Methods

The Cancer Genome Atlas was used to identify autophagy related genes (ARGs) that were differentially expressed in endometrial cancer tissue compared to healthy endometrial tissue. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were referenced to identify important biological functions and signaling pathways related to these differentially expressed ARGs. A prognostic model for endometrial cancer was constructed using univariate and multivariate Cox, and Least Absolute Shrinkage and Selection Operator regression analysis. Endometrial cancer patients were divided into high- and low-risk groups according to risk scores. Survival and receiver operating characteristic (ROC) curves were plotted for these patients to assess the accuracy of the prognostic model. Using immunohistochemistry the protein levels of the genes associated with risk were assessed.

Results

We determined 37 ARGs were differentially expressed between endometrial cancer and healthy tissues. These genes were enriched in the biological processes and signaling pathways related to autophagy. Four ARGs (CDKN2A, PTK6, ERBB2 and BIRC5) were selected to establish a prognostic model of endometrial cancer. Kaplan–Meier survival analysis suggested that high-risk groups have significantly shorter survival times than low-risk groups. The area under the ROC curve indicated that the prognostic model for survival prediction was relatively accurate. Immunohistochemistry suggested that among the four ARGs the protein levels of CDKN2A, PTK6, ERBB2, and BIRC5 were higher in endometrial cancer than healthy endometrial tissue.

Conclusions

Our prognostic model assessing four ARGs (CDKN2A, PTK6, ERBB2, and BIRC5) suggested their potential as independent predictive biomarkers and therapeutic targets for endometrial cancer.

Supplementary information

Supplementary information accompanies this paper at 10.1186/s12885-020-07535-4.

Molecular Biomarkers for Early Detection and Prevention of Ovarian Cancer-A Gateway for Good Prognosis: A Narrative Review

Gynecological cancers are one of the most lethal and deadliest cancers in the world. In India, the prevalence of ovarian cancer accounts for 2.5% to 3%. Despite the availability of improved treatment option along with improved technology, the survival rate of ovarian cancer in the early-stage and the advanced stage is poor. Therefore, due to the heterogeneity of ovarian cancer, to detect it at an early stage and to prevent further mortality turns out to be a big challenge. Researchers are still in the process to identify any single biomarker with good sensitivity and specificity. Various traditional and serum approaches to identify ovarian cancer have been successful in the early stages. The invention of molecular biomarkers such as the use of genomic profiling, DNA methylation, and other approaches have proven to be of higher sensitivity and specificity, which overall affects the prognosis of ovarian cancer. With the use of whole-genome analysis, the detection of possible location of critical tumor suppressor gene (TSGs) in the paired region of chromosomes has been identified, which are associated with BRCA1 and BRCA2 which further makes these novel molecular biomarkers as potential biomarkers. Moreover, studies are required to assess the combined use of traditional, molecular biomarkers that might be useful for enhanced sensitivity and specificity for early detection and prevention of ovarian cancer in early stages which will lead to reduced mortality and good prognosis

Q-switched Nd-YAG laser alone and in combination with innovative hyaluronic acid gels improve keratinocytes wound healing in vitro

During the last years, several attempts have been accomplished to improve the wound healing. Device application aimed at enhancing skin ability to reconstruct its damaged sites through a proper dermal regenerative process. In particular, Q-switched Nd-YAG laser (Medlite C6 laser, Conbio, USA) applied with a fluence of 8 J/cm², a pulse width of 5 ns, and a spot size of 4 mm exerts a photo-mechanical action that improve skin repair. Besides, hyaluronan hybrid cooperative complexes (HCC) widely exploited in dermoesthetic applications proved specific actions on keratinocytes and fibroblasts monolayer repair. We evaluated this specific laser treatment in vitro on a wound healing model based on human keratinocytes (HaCaT) alone and in combination with HCC. In addition, we evaluated key biomarkers of dermal repair. Scratched HaCaT monolayers were treated with laser and successively with HA-based formulations (HHA and HCC). For each treatment and the control samples, at least 3 different wells were analyzed. Wound closure was quantified, measuring five view filed for each well at increasing incubation time, exploiting time lapse videomicroscopy and image analysis, permitting to compare the different healing rate of treatments respect to control. By real-time PCR and western blotting, we evaluated biomarkers of wound regeneration, such as integrins, aquaporin three (AQP3), and proinflammatory cytokines. The ANOVA test was used to assess statistical significance of the results obtained. Laser-treated cells achieved wound closure in about 37 h, faster than the control, while when coupled to HCC, the complete reparation was obtained in 24 h. Integrin αV was upregulated by treatments, with in particular about four-fold increase respect to the control when HCC + laser was used. In addition, integrin β3 was upregulated by all treatments especially with the combination of laser and HCC proved more efficient than others (~ 14-folds). A slighter but significant increase of AQP3 gene expression of 61% was found for laser treatment while the latter combined with HCC determined an upregulation of 72%. By coupling laser treatment and HCC, further healing improvement and consistent biomarker modulation was observed. Our results may support clinical implementation of new dermatology protocols conjugating laser treatments with topical or injective HA formulations as a valid tool in treatments to repair scars or other skin defects.

The emerging role of the BDNF-TrkB signaling pathway in the modulation of pain perception

The brain derived neurotrophic factor (BDNF) is a crucial neuromodulator in pain transmission both in peripheral and central nervous system (CNS). Despite evidence of a pro-nociceptive role of BDNF, recent studies have reported contrasting results, including anti-nociceptive and anti-inflammatory activities. Moreover, BDNF polymorphisms can interfere with BDNF role in pain perception. In Val66Met carriers, the Met allele may have a dual role, with anti-nociceptive actions in normal condition and pro-nociceptive effects during chronic pain. In order to elucidate the main effects of BDNF in nociception, we reviewed the main characteristics of this neurotrophin, focusing on its involvement in pain.

Distinguishing Benign Renal Tumors with an Oncocytic Gene Expression (ONEX) Classifier

Renal oncocytoma (RO) accounts for 5% of renal cancers and generally behaves as a benign tumor with favorable long-term prognosis. It is difficult to confidently distinguish between benign RO and other renal malignancies, particularly chromophobe renal cell carcinoma (chRCC). Therefore, RO is often managed aggressively with surgery. We sought to identify molecular biomarkers to distinguish RO from chRCC and other malignant renal cancer mimics. In a 44-patient discovery cohort, we identified a significant differential abundance of nine genes in RO relative to chRCC. These genes were used to train a classifier to distinguish RO from chRCC in an independent 57-patient cohort. The trained classifier was then validated in five independent cohorts comprising 89 total patients. This nine-gene classifier trained on the basis of differential gene expression showed 93% sensitivity and 98% specificity for distinguishing RO from chRCC across the pooled validation cohorts, with a c-statistic of 0.978. This tool may be a useful adjunct to other diagnostic modalities to decrease the diagnostic and management uncertainty associated with small renal masses and to enable clinicians to recommend more confidently less aggressive management for some tumors. PATIENT SUMMARY: Renal oncocytoma is generally a benign form of kidney cancer that does not necessarily require surgical removal. However, it is difficult to distinguish renal oncocytoma from other more aggressive forms of kidney cancer, so it is treated most commonly with surgery. We built a classification tool based on the RNA levels of nine genes that may help avoid these surgeries by reliably distinguishing renal oncocytoma from other forms of kidney cancer.

The combination of an inflammatory peripheral blood gene expression and imaging biomarkers enhance prediction of radiographic progression in knee osteoarthritis

OBJECTIVE

Predictive biomarkers of progression in knee osteoarthritis are sought to enable clinical trials of structure-modifying drugs. A peripheral blood leukocyte (PBL) inflammatory gene signature, MRI-based bone marrow lesions (BML) and meniscus extrusion scores, meniscal lesions, and osteophytes on X-ray each have been shown separately to predict radiographic joint space narrowing (JSN) in subjects with symptomatic knee osteoarthritis (SKOA). In these studies, we determined whether the combination of the PBL inflammatory gene expression and these imaging findings at baseline enhanced the prognostic value of either alone.

METHODS

PBL inflammatory gene expression (increased mRNA for IL-1β, TNFα, and COX-2), routine radiographs, and 3T knee MRI were assessed in two independent populations with SKOA: an NYU cohort and the Osteoarthritis Initiative (OAI). At baseline and 24 months, subjects underwent standardized fixed-flexion knee radiographs and knee MRI. Medial JSN (mJSN) was determined as the change in medial JSW. Progressors were defined by an mJSN cut-point (≥ 0.5 mm/24 months). Models were evaluated by odds ratios (OR) and area under the receiver operating characteristic curve (AUC).

RESULTS

We validated our prior finding in these two independent (NYU and OAI) cohorts, individually and combined, that an inflammatory PBL inflammatory gene expression predicted radiographic progression of SKOA after adjustment for age, sex, and BMI. Similarly, the presence of baseline BML and meniscal lesions by MRI or semiquantitative osteophyte score on X-ray each predicted radiographic medial JSN at 24 months. The combination of the PBL inflammatory gene expression and medial BML increased the AUC from 0.66 (p = 0.004) to 0.75 (p < 0.0001) and the odds ratio from 6.31 to 19.10 (p < 0.0001) in the combined cohort of 473 subjects. The addition of osteophyte score to BML and PBL inflammatory gene expression further increased the predictive value of any single biomarker. A causal analysis demonstrated that the PBL inflammatory gene expression and BML independently influenced mJSN.

CONCLUSION

The use of the PBL inflammatory gene expression together with imaging biomarkers as combinatorial predictive biomarkers, markedly enhances the identification of radiographic progressors. The identification of the SKOA population at risk for progression will help in the future design of disease-modifying OA drug trials and personalized medicine strategies.

Lung cancer screening, what has changed after the latest evidence?

Lung cancer (LC) is still one of the most frequent cancers with a high related mortality. Their prognosis is directly proportional to the stage at the time of diagnosis. Seventy percent are currently diagnosed in advanced or locally advanced stage (higher than stage III), making a cure unlikely for the majority of patients. Developments in LC treatment are significant however they do not seem to be enough to reverse the current situation, at least, in a short period of time. Despite recent advances in treatment, primary prevention and early diagnosis appear to be the key to reduce the incidence and mortality of this disease. Many countries have developed LC screening programs based on the results of clinical trials published in recent years. The aim of this paper is to review the latest results of the NEderlands Leuvens Longkanker Screenings Onderzoek and compare them with the findings of the National Lung Screening Trial. We address the question whether it is necessary to continue discussing the evidence regarding LC screening. In both trials, there is a clear impact on LC mortality but, with a modest reduction in over all mortality. Undoubtedly, the benefit of screening can be expected to grow as low-dose computed tomographys are performed over longer periods of time.

Metal body burden and tissue oxidative status in the bivalve Venerupis decussata from Tunisian coastal lagoons

Coastal transitional waters are exposed to many anthropogenic threats. This study aims to assess the trace metals' pollution status of transitional waters by evaluating its biological effects in the clam Venerupis decussata. Among the studied sites along the Tunisian littoral, South Tunis and Boughrara were the most impacted, since clams from these two lagoons presented significant differences in: (i) trace metal contents, (ii) in-cell hydrogen peroxide, (iii) enzymatic and non-enzymatic defenses, (iv) damage to lipids and proteins, and (v) protein post-translational modifications. These changes related to evident histopathological traits. PCA showed a clear separation between the digestive gland and gills tissues and illustrated an impact gradient in Tunisian coastal lagoons. Water temperature was revealed as an added natural stressor that, when concurring with high pollution, may jeopardize an ecosystem's health and contribute to the accumulation of hazardous metals in organisms.

Development and validation of an individualized DNA repair-related gene signature in localized clear cell renal cell carcinoma

BACKGROUND

To establish a robust, individualized DNA repair-related gene signature to estimate prognosis for patients with localized clear cell renal cell carcinoma (ccRCC).

MATERIALS AND METHODS

We retrospectively analyzed gene expression profiles of 541 localized ccRCC patients from two public ccRCC cohorts. The DNA repair-related gene pair index (DRPI) was constructed with the least absolute shrinkage and selection operator (LASSO) regression model. The associations between DRPI, overall survival (OS), and disease-specific survival (DSS) were evaluated by Kaplan-Meier analysis, univariate analysis, and multivariate Cox regression survival analysis. We compared the predictive accuracy of different risk models with Harrel's C-index.

RESULTS

In the primary univariate analysis, patients in DRPI-high-risk group had significantly shorter OS [P < 0.001, HR (95% CI) 2.093 (1.431-3.061)] and DSS [P < 0.001, HR (95% CI) 3.567 (2.017-6.339)]. After adjusted for stage and grade, DRPI-high-risk group remained an independent adverse risk factor for both OS [P = 0.026, HR (95% CI) 1.629 (1.094-2.452)] and DSS [P = 0.010, HR (95% CI) 2.209 (1.217-4.010)]. DPRI showed comparable predictive accuracy with cell cycle proliferation (CCP) score and ccA/ccB signature. Copy number alterations and tumor mutation burden were enriched in DRPI-high tumors. There were elevated number of Treg cells and higher T cell exhaustion marker expression in DRPI-high-risk tumors. The combined DNA repair-clinical score outperformed other risk models in terms of C-index.

CONCLUSION

We validated the proposed DRPI as a predictor of clinical outcome in localized ccRCC patients. It provides an individualized and more accurate risk assessment beyond clinicopathological characteristics.

Role of molecular biomarkers in glioma resection: a systematic review

New discoveries based on genetic and epigenetic evidence have significantly expanded the understanding of diffuse gliomas. Molecular biomarkers detected in diffuse gliomas are not only potential targets for radiotherapy, chemotherapy, and immunotherapy, but are also able to guide surgical treatment. Previous studies have suggested that the optimal extent of resection of diffuse gliomas varies according to the expression of specific molecular biomarkers. However, the specific guiding role of these biomarkers in the resection of diffuse gliomas has not been systemically analyzed. This review summarizes several critical molecular biomarkers of tumorigenesis and progression in diffuse gliomas and discusses different strategies of tumor resection in the context of varying genetic expression. With ongoing study and advances in technology, molecular biomarkers will play a more important role in glioma resection and maximize the survival benefit from surgery for diffuse gliomas.

Exposure of earthworm (Eisenia fetida) to bauxite residue: Implications for future rehabilitation programmes

Bauxite residue is typically alkaline, has high sodium content and elevated concentrations of trace elements. Effective rehabilitation strategies are needed to mitigate potential environmental risks from its disposal and storage. Increasingly, the importance of viable soil faunal populations as well as establishment of vegetation covers is recognized as key components of successful rehabilitation. Inoculation with earthworms is a strategy for accelerating mine site rehabilitation, but little is known on the effects of bauxite residue properties on earthworm survival and viability. In the current study, earthworms (Eisenia fetida) were exposed for 28 days to a series of bauxite residue/soil treatments (0, 10, 25, 35, 50, 75 and 100% residue) to evaluate possible toxic effects on earthworms, investigate the bioavailability of relevant elements (e.g. As, Cr, V), and assess the risk of element transfer. Results showed that soil containing ≥25% residue (pH ≥ 9.8; ESP ≥ 18.5%; extractable Na ≥ 1122 mg/kg) significantly impacted survival (mortality ≥28%) and reproduction (cocoon production inhibition ≥76%) of the exposed earthworms. Alkalinity, sodicity and bioavailable Na were identified as major factors causing toxicity and some earthworms were observed to adopt compensative response (i.e. swollen body) to cope with osmotic stress. Conversely, soil containing 10% residue (pH = 9.1; ESP = 9.2%; extractable Na = 472 mg/kg) did not elicit significant toxicity at the organism level, but biomarker analysis (i.e. superoxide dismutase and catalase) in earthworm coelomocytes showed an oxidative stress. Furthermore, earthworms exposed to soil containing ≥10% residue took up and accumulated elevated concentrations of Al, As, Cr and V in comparison to the control earthworms. We concluded that earthworm inoculation could be used in future rehabilitation programmes once the key parameters responsible for toxicity are lowered below specific target values (i.e. pH = 9.1, ESP = 18.5%, extractable Na = 1122 mg/kg for Eisenia fetida). Nonetheless, trace element uptake in earthworms should be regularly monitored and the risk to the food chain further investigated.

Microbial and metabolomic analysis of gingival crevicular fluid in general chronic periodontitis patients: lessons for a predictive, preventive, and personalized medical approach

Objectives

General chronic periodontitis (GCP) is a bacterial inflammatory disease with complex pathology. Despite extensive studies published on the variation in the oral microbiota and metabolic profiles of GCP patients, information is lacking regarding the correlation between host-bacterial interactions and biochemical metabolism. This study aimed to analyze the oral microbiome, the oral metabolome, and the link between them and to identify potential molecules as useful biomarkers for predictive, preventive, and personalized medicine (PPPM) in GCP.

Methods

In this study, gingival crevicular fluid (GCF) samples were collected from patients with GCP (n = 30) and healthy controls (n = 28). The abundance of oral microbiota constituents was obtained by Illumina sequencing, and the relative level of metabolites was measured by gas chromatography-mass spectrometry. Full-mouth probing depth, clinical attachment loss, and bleeding on probing were recorded as indices of periodontal disease.

Results

The relative abundances of 7 phyla and 82 genera differed significantly between the GCP and healthy groups. Seventeen differential metabolites involved in different metabolism pathways were selected based on variable influence on projection values (VIP > 1) and P values (P < 0.05). Through Spearman's correlation analysis, microorganisms, metabolites in GCF, and clinical data together showed a clear trend, and clinical data regarding periodontitis can be reflected in the shift of the oral microbial community and the change in metabolites in GCF. A combination of citramalic acid and N-carbamylglutamate yielded satisfactory accuracy (AUC = 0.876) for the predictive diagnosis of GCP.

Conclusions

Dysbiosis in the polymicrobial community structure and changes in metabolism could be mechanisms underlying periodontitis. The differential microorganisms and metabolites in GCF between periodontitis patients and healthy individuals are possibly biomarkers, pointing to a potential strategy for the prediction, diagnosis, prognosis, and management of personalized periodontal therapy.

Liver Transcriptome Profiling Reveals That Dietary DHA and EPA Levels Influence Suites of Genes Involved in Metabolism, Redox Homeostasis, and Immune Function in Atlantic Salmon (Salmo salar)

The optimal dietary requirement of omega-3 long-chain polyunsaturated fatty acids (ω3 LC-PUFA), namely docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), for Atlantic salmon that promotes growth and health warrants careful investigation. We used 44K microarrays to study the influence of increasing levels of dietary DHA + EPA (0, 1.0, and 1.4% of the diet, as formulated) in the presence of high linoleic acid (LA) on Atlantic salmon growth and liver transcriptome. After a 14-week feeding trial, Atlantic salmon fed diet ω3LC0 (i.e. 0% of DHA + EPA) showed significantly lower final weight and weight gain, and higher feed conversion ratio compared with ω3LC1.0 and ω3LC1.4 diet groups. The microarray experiment identified 55 and 77 differentially expressed probes (Rank Products analyses; PFP < 10%) in salmon fed diets ω3LC1.4 and ω3LC1.0 compared with those fed diet ω3LC0, respectively. The comparison between ω3LC1.4 and ω3LC1.0 revealed 134 differentially expressed probes. The microarray results were confirmed by qPCR analyses of 22 microarray-identified transcripts. Several key genes involved in fatty acid metabolism including LC-PUFA synthesis were upregulated in fish fed ω3LC0 compared with both other groups. Hierarchical clustering and linear regression analyses of liver qPCR and fatty acid composition data demonstrated significant correlations. In the current study, 1.0% ω3 LC-PUFA seemed to be the minimum requirement for Atlantic salmon based on growth performance; however, multivariate statistical analyses (PERMANOVA and SIMPER) showed that fish fed ω3LC1.0 and ω3LC1.4 diets had similar hepatic fatty acid profiles but marked differences in the transcript expression of biomarker genes involved in redox homeostasis (mgst1), immune responses (mxb, igmb, irf3, lect2a, srk2, and lyz2), and LC-PUFA synthesis (srebp1, fadsd5, and elovl2). This research has provided new insights into dietary requirement of DHA and EPA and their impact on physiologically important pathways in addition to lipid metabolism in Atlantic salmon.

Personalized Medicine in Infertile Men

Personalized medicine gathers the most relevant data involved in human health. Currently, the diagnosis of male infertility is limited to spermiogram, which does not provide information on the male fertile potential. New diagnostic methods are required. The application of omics techniques in the study of male reproductive health renders a huge amount of data providing numerous novel infertility biomarkers, from genes to metabolites, to diagnose the cause of male infertility. Recent studies hold the promise that these biomarkers will allow a noninvasive infertility diagnosis and the improvement of the sperm selection techniques.

Biological responses of shoal flounder (Syacium gunteri) to toxic environmental pollutants from the southern Gulf of Mexico

The Gulf of Mexico (GoM) is exposed to a diversity of contaminants, such as hydrocarbons and heavy metal(oid)s, either from natural sources or as a result of uncontrolled coastal urbanisation and industrialisation. To determine the effect of these contaminants on the marine biota along the Mexican GoM, the biological responses of the shoal flounder Syacium gunteri, naturally exposed, were studied. The study area included all the Mexican GoM, which was divided into three areas: West-southwest (WSW), South-southwest (SSW) and South-southeast (SSE). The biological responses included the global DNA methylation levels, the expression of biomarker genes related to contaminants (cytochrome P450 1A, glutathione S-transferase, glutathione reductase, glutathione peroxidase, catalase, and vitellogenin), histopathological lesions and PAH metabolites in bile (hydroxynaphthalene, hydroxyphenanthrene, hydroxypyrene and Benzo[a]pyrene). The correlation between the biological responses and the concentration of contaminants (hydrocarbons and metal(oid)s), present in both sediments and organisms, were studied. The shoal flounders in WSW and SSW areas presented higher DNA hypomethylation, less antioxidative response and biotransformation gene expression and a higher concentration of PAH metabolites in bile than SSE area; those responses were associated with total hydrocarbons and metals such as chromium (Cr). SSE biological responses were mainly associated with the presence of metals, such as cadmium (Cd) and copper (Cu), in the tissue of shoal flounders. The results obtained on the physiological response of the shoal flounder can be used as part of a permanent active environmental surveillance program to watch the ecosystem health of the Mexican GoM.