Tenogenic modulating insider factor: Systematic assessment on the functions of tenomodulin gene

Tenomodulin (TNMD, Tnmd) is a gene highly expressed in tendon known to be important for tendon maturation with key implications for the residing tendon stem/progenitor cells as well as for the regulation of endothelial cell migration in chordae tendineae cordis in the heart and in experimental tumour models. This review aims at providing an encompassing overview of this gene and its protein. In addition, its known expression pattern as well as putative signalling pathways will be described. A chronological overview of the discovered functions of this gene in tendon and other tissues and cells is provided as well as its use as a tendon and ligament lineage marker is assessed in detail and discussed. Last, information about the possible connections between TNMD genomic mutations and mRNA expression to various diseases is delivered. Taken together this review offers a solid synopsis on the up-to-date information available about TNMD and aids at directing and focusing the future research to fully uncover the roles and implications of this interesting gene.

Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling

Background

Identification of biomarkers associated with the prognosis of different cancer subtypes is critical to achieve better therapeutic assistance. In colorectal cancer (CRC) the discovery of stable and consistent survival markers remains a challenge due to the high heterogeneity of this class of tumors. In this work, we identified a new set of gene markers for CRC associated to prognosis and risk using a large unified cohort of patients with transcriptomic profiles and survival information.

Results

We built an integrated dataset with 1273 human colorectal samples, which provides a homogeneous robust framework to analyse genome-wide expression and survival data. Using this dataset we identified two sets of genes that are candidate prognostic markers for CRC in stages III and IV, showing either up-regulation correlated with poor prognosis or up-regulation correlated with good prognosis. The top 10 up-regulated genes found as survival markers of poor prognosis (i.e. low survival) were: DCBLD2, PTPN14, LAMP5, TM4SF1, NPR3, LEMD1, LCA5, CSGALNACT2, SLC2A3 and GADD45B. The stability and robustness of the gene survival markers was assessed by cross-validation, and the best-ranked genes were also validated with two external independent cohorts: one of microarrays with 482 samples; another of RNA-seq with 269 samples. Up-regulation of the top genes was also proved in a comparison with normal colorectal tissue samples. Finally, the set of top 100 genes that showed overexpression correlated with low survival was used to build a CRC risk predictor applying a multivariate Cox proportional hazards regression analysis. This risk predictor yielded an optimal separation of the individual patients of the cohort according to their survival, with a p-value of 8.25e-14 and Hazard Ratio 2.14 (95% CI: 1.75–2.61).

Conclusions

The results presented in this work provide a solid rationale for the prognostic utility of a new set of genes in CRC, demonstrating their potential to predict colorectal tumor progression and evolution towards poor survival stages. Our study does not provide a fixed gene signature for prognosis and risk prediction, but instead proposes a robust set of genes ranked according to their predictive power that can be selected for additional tests with other CRC clinical cohorts.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5193-9) contains supplementary material, which is available to authorized users.

Single nucleotide variants of receptor for advanced glycation end-products (AGER) gene: is it a new opening in the risk assessment of diabetic retinopathy?-a review

BACKGROUND

Diabetic retinopathy (DR) is a common microvascular complication of diabetes. There is strong evidence suggesting that DR has an inheritable component. The interaction between advanced glycation end products (AGEs) and their receptor is integral in the pathogenesis of diabetic retinopathy and its various complications, retinopathy being one of them.

OVERVIEW AND METHODOLOGY

This review discusses the existing literature on the association between single nucleotide variants (SNV) of AGER gene and the risk of DR. It also discusses the current understanding of the AGE-AGER pathway in diabetic retinopathy. Through our article we have tried to consolidate all the available information about these SNVs associated with diabetic retinopathy in a succinct tabular form. Additionally, a current understanding of the AGE-AGER interaction and its deleterious effects on the cells of the retina has been discussed in detail to provide comprehensive information about the topic to the reader. A literature review was performed on PubMed, Cochrane Library, and Google Scholar for studies to find existing literature on the association between AGER gene SNVs and the risk, progression and severity of developing DR. This article will encourage scientific communication and discussion about possibly devising genetic markers for an important cause of blindness both in developed and developing countries, i.e., diabetic retinopathy.

RESULT

Based on genetic studies done in Indian and Chinese population G82S(rs2070600) was positively associated with Diabetic Retinopathy. Patients of diabetic retinopathy in Caucasian population had -T374A(rs1800624) polymorphism. + 20T/A was found to be associated with the disease in a study done in UK. Association with G1704T(rs184003) was seen in Chinese and Malaysian population. A Chinese study found its association with CYB242T. -T429C(rs1800625) SNV was not associated with DR in any of the studies. G2245A(rs55640627) was positively associated with the disease process in Malaysian population. It was not associated in Malaysian and Chinese population. Promoter variant rs1051993 has also been found to a susceptible SNV in the Chinese population.

CONCLUSION

While providing a comprehensive review of the existing information, we would like to emphasize on a large, multi-centric, trial with a much larger and varied population base to definitely determine these single nucleotide variants predisposing diabetic individuals.

Identifying statistically significant combinatorial markers for survival analysis

Background

Survival analysis methods have been widely applied in different areas of health and medicine, spanning over varying events of interest and target diseases. They can be utilized to provide relationships between the survival time of individuals and factors of interest, rendering them useful in searching for biomarkers in diseases such as cancer. However, some disease progression can be very unpredictable because the conventional approaches have failed to consider multiple-marker interactions. An exponential increase in the number of candidate markers requires large correction factor in the multiple-testing correction and hide the significance.

Methods

We address the issue of testing marker combinations that affect survival by adapting the recently developed Limitless Arity Multiple-testing Procedure (LAMP), a p-value correction technique for statistical tests for combination of markers. LAMP cannot handle survival data statistics, and hence we extended LAMP for the log-rank test, making it more appropriate for clinical data, with newly introduced theoretical lower bound of the p-value.

Results

We applied the proposed method to gene combination detection for cancer and obtained gene interactions with statistically significant log-rank p-values. Gene combinations with orders of up to 32 genes were detected by our algorithm, and effects of some genes in these combinations are also supported by existing literature.

Conclusion

The novel approach for detecting prognostic markers presented here can identify statistically significant markers with no limitations on the order of interaction. Furthermore, it can be applied to different types of genomic data, provided that binarization is possible.

Diagnostic potential of a gradient boosting-based model for detecting pediatric sepsis

Pediatric sepsis is a major cause of mortality of children worldwide. However, there is still a lack of easy-to-use predictive tools that can accurately diagnose sepsis in children. This study aimed to develop an optimal gene model for the diagnosis of pediatric sepsis using statistics and machine learning approaches. Combining gene expression profiles from a training cohort of 364 pediatric samples with a Least Absolute Shrinkage and Selection Operator analysis produced eighteen genes as diagnostic markers. With the implementation of a Gradient Boosting algorithm, a model designated PEDSEPS-GBM, that aggregated these markers was developed with optimal performance for the diagnosis of pediatric samples in the validation and two independent cohorts. Moreover, a web calculator with a user-friendly interface was established for PEDSEPS-GBM. This study presents a diagnostic model that holds great potential for the detection of pediatric sepsis, and demonstrates the biologic and clinical relevance of this model.

The challenges in the identification of Escherichia coli from environmental samples and their genetic characterization

Escherichia coli bacteria are an essential indicator in evaluations of environmental pollution, which is why they must be correctly identified. This study aimed to determine the applicability of various methods for identifying E. coli strains in environmental samples. Bacterial strains preliminary selected on mFc and Chromocult media as E. coli were identified using MALDI Biotyper techniques, based on the presence of genes characteristic of E. coli (uidA, uspA, yaiO), as well as by 16S rRNA gene sequencing. The virulence and antibiotic resistance genes pattern of bacterial strains were also analyzed to investigate the prevalence of factors that may indicate adaptation to unsupportive environmental conditions and could have any significance in further identification of E. coli. Of the strains that had been initially identified as E. coli with culture-based methods, 36-81% were classified as E. coli with the use of selected techniques. The value of Cohen's kappa revealed the highest degree of agreement between the results of 16S rRNA gene sequencing, the results obtained in the MALDI Biotyper system, and the results of the analysis based on the presence of the yaiO gene. The results of this study could help in the selection of more accurate and reliable methods which can be used in a preliminary screening and more precise identification of E. coli isolated from environmental samples.

CXCR3 predicts the prognosis of endometrial adenocarcinoma

OBJECTIVES

Currently, endometrial adenocarcinoma lacks an effective prognostic indicator. This study was to develop and validate a gene biomarker and a nomogram to predict the survival of endometrial adenocarcinoma, explore potential mechanisms and select sensitive drugs.

METHODS

425 endometrial adenocarcinoma cases with RNA sequencing data from TCGA were used to identify the most immune-related module by WGCNA. As an external test set, 103 cases from GSE17025 were used. Immune-related genes were downloaded from Innate DB. The three sets of data were used to identify the prognostic genes. Based on 397 cases with complete clinical data from TCGA, randomly divided into the training set (n = 199) and test set (n = 198), we identified CXCR3 as the prognostic gene biomarker. Age, grade, FIGO stage, and risk were used to develop and validate a predictive nomogram. AUC, C-index, calibration curve and K-M estimate evaluated the model's predictive performance. KEGG enrichment analysis, immune functions, TMB, the effectiveness of immunotherapy, and drug sensitivity between the high-risk and low-risk groups.

RESULTS

CXCR3 was identified as a prognostic biomarker. We calculated the risk score and divided the cases into the high-risk and low-risk groups by the median value of the risk score. The OS of the high-risk group was better than the low-risk group. The risk was the prognostic indicator independent of age, grade, and FIGO stage. We constructed the nomogram including age, grade, FIGO stage, and risk to predict the prognosis of endometrial adenocarcinoma. The top five KEGG pathways enriched by the DEGs between the high- and low-risk groups were viral protein interaction with cytokine and cytokine receptors, cytokine-cytokine receptor interaction, chemokine signaling pathway, natural killer cell-mediated cytotoxicity, and cell adhesion molecules. We analyzed the difference in immune cells and found that CD8+ T cells, activated CD4+ T cells, T helper cells, monocytes, and M1 macrophages were infiltrated more in the low-risk group. However, M0 macrophages and activated dendritic cells were more in the high-risk group. The immune function including APC coinhibition, APC costimulation, CCR, checkpoint, cytolytic activity, HLA, inflammation-promoting, MHC-I, parainflammation, T cell coinhibition, T cell costimulation, type I-IFN-response, and type II-IFN-response were better in the low-risk group. TMB and TIDE scores were both better in the low-risk group. By 'the pRRophetic' package, we found 56 sensitive drugs for different risk groups.

CONCLUSION

We identified CXCR3 as the prognostic biomarker. We also developed and validated a predictive nomogram model combining CXCR3, age, histological grade, and FIGO stage for endometrial adenocarcinoma, which could help explore the precise treatment.

Immunoglobulin gene expression as a biomarker for Streptococcosis resistance in Nile tilapia (Oreochromis niloticus)

Streptococcus agalactiae is a significant pathogen in Nile tilapia (Oreochromis niloticus) culture, causing economic losses in Thailand. Formalin-killed S. agalactiae vaccine in tilapia can be used in the prevention of diseases and mortalities. In this study, we administered a formalin-killed S. agalactiae vaccine to individual tilapia broodstock to activate immunoglobulin (IgM) gene expression. The IgM gene expression levels differed among individual broodstock and were grouped into four categories: high IgM males (HM), low IgM males (LM), high IgM females (HF), and low IgM females (LF). Using these categories, we designed matings to create four breeding groups: HM × HF, HM × LF, LM × HF, and LM × LF, generating three fry families per group. The tilapia fry was then orally challenged with S. agalactiae for 14 days. The results showed a significant difference (p < 0.05) in survival rates among the breeding groups. The HM × HF group had the highest survival at 93.33 ± 6.20 %, while the LM × LF group had the lowest at 21.11 ± 6.50 %. Gene expression analysis of toll-like receptor 2, hepcidin, immunoglobulin, MHC class II, and granzyme genes at 24, 48, 72, and 96 h post S. agalactiae challenge revealed significant temporal changes. IgM and granzyme expression levels varied notably among groups, with IgM peaking at 72-96 h and showing a significant difference (p < 0.05) between groups. The HM × HF, HM × LF, and LM × HF breeding groups displayed significantly higher IgM expression levels compared to the LM × LF group. Granzyme gene expression also showed significant differences (p < 0.05) from 48 h post-challenge, with the highest expression observed in the HM × HF group and the lowest in the LM × LF group. No significant difference (p > 0.05) was observed between the HM × LF and LM × HF groups for granzyme expression. This experiment concludes that high levels of IgM gene expression of broodstock tilapia induced by formalin-killed S. agalactiae vaccine could be used as a gene marker to select the S. agalactiae-resistant tilapia in breeding program.

Infectious myonecrosis virus (IMNV) induces upregulation of RNAi-related genes in white shrimp Penaeus vannamei

Infectious myonecrosis virus (IMNV) still causes significant economic and social losses in American and Asian shrimp farming. In this work, we investigated the transcription patterns of Sid-1, Dicer-2 and Argonaute-2 genes from the RNAi mechanism in Penaeus vannamei naturally infected with IMNV, and injected with inoculum containing 1.02 × 105, 1.02 × 104 or 1.02 × 103 IMNV copies‧μL-1. We observed that infection with increasing IMNV concentrations affected the transcription levels of these key genes. However, the viral load did not decrease during the experiment. We suggest that changes in Sid-1 mRNA expression could be used as marker of viral replication for evaluating sanitary status in P. vannamei farming.

Characterization of ccl20a.3 and ccl20l as gene markers for Th17 cell in turbot

T-helper 17 lymphocytes (Th17) are the most common inflammatory cells identified in mammals. However, the identification of Th17 cells and the clarification of their function in teleost fish remain largely unknown. In this study, we took advantage of the single-cell RNA sequencing-based immune cell atlas that was identified in turbot (Scophthalmus maximus), and revealed two chemokine-related genes, ccl20a.3 and ccl20l, that were specifically expressed in Th17 cells. Moreover, through immuno-fluorescence analysis, we found that CCL20a.3 or CCL20l was co-expressed with the classical makers in Th17 cells, including IL17a/f1 and IL22. Furthermore, through a Th17 lineage-specific transcription factor RORc inhibitor GSK805 treatment, we found that the expression of ccl20a.3 and ccl20l was significantly impaired, compared with other T cell markers. Besides, we also found that ccl20a.3 and ccl20l exhibited the same dynamic response with the classical markers that were identified in Th17 cells during bacterial infection. Taken together, these results provide potential gene markers for better understanding of the dynamic immune responses of Th17 cells in teleost fish.