Data Mining for Biomarker Development: A Review of Tissue Specificity Analysis

Novel chitosan-magnetite-silica ternary capsules for highly efficient sequestration of reactive dyes from aqueous media

The main goal of this study was to synthesize novel Chitosan Magnetite Silica (CMS) adsorbent capsules and apply them for effective sequestration of anionic dyes Remazol brilliant blue 19 (RB-19) and Remazol golden yellow G -17 (RY-17) dye. The CMS capsules were synthesized and applied for batch study and evaluated using statistical modelling. Various analytical techniques, such as Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), Thermogravimetry-Differential Thermal Analysis (TG-DTA), Brunauer-Emmett-Teller (BET) surface area analysis, UV-Vis Spectrophotometry, and Vibrating Sample Magnetometry (VSM), were employed to validate the formation of the CMS. Rough surface as shown by SEM analysis, presence of various functional groups as shown by FT-IR spectrum and presence Fe atoms in EDX spectrum are indication of formation of complete composite. The surface area of CMS recorded by BJH method was 39.05 m2 g-1 with pore capacity 0.259 cm3 g-1. According to IUPAC classification, class IV isotherm was observed for nitrogen adsorption-desorption curves. The specific magnetization of CMS was 4.28 emu g-1 indicating fare degree of magnetism making it easily separable using external magnet. Batch trails as well as screening experiments were conducted for the sequestration of RB and RY dyes. Dose 50 mg, interface time 60 min and solution pH of 3.0 depicted maximum removal efficacy of more than 95 % in both dyes even at high initial concentration of 200 mg L-1. The adsorption capacities for RB-19 dye and RY-17 dye were found to be 455.86 and 344.06 mg g-1 respectively in accordance with pseudo second order kinetics (R2 = 0.997 and 0.962 respectively) and Langmuir adsorption isotherm (R2 = 0.972 and 0.992 respectively) models. Six adsorption-desorption cycles were conducted for regeneration potential of CMS showcasing repeated usability after regeneration in alkaline medium. E-factor value of 0.04 depicted CMS capsules was sustainable in and eco-friendly with low waste generation.

The impact of bleeding on outcomes following lung transplantation: a retrospective analysis using the universal definition of perioperative bleeding

BACKGROUND

Lung transplantation (LT) represents a high-risk procedure for end-stage lung diseases. This study describes the outcomes of patients undergoing LT that require massive transfusions as defined by the universal definition of perioperative bleeding (UDPB).

METHODS

Adult patients who underwent bilateral LT at a single academic center were surveyed retrospectively. Patients were grouped by insignificant, mild, or moderate perioperative bleeding (insignificant-to-moderate bleeders) and severe or massive perioperative bleeding (severe-to-massive bleeders) based on the UDPB classification. Outcomes included 1-year survival and primary graft dysfunction (PGD) of grade 3 at 72 h postoperatively. Multivariable models were adjusted for recipient age, sex, body mass index (BMI), Lung allocation score (LAS), preoperative hemoglobin (Hb), preoperative extracorporeal membrane oxygenation (ECMO) status, transplant number, and donor status. An additional multivariable model was created to find preoperative and intraoperative predictors of severe-to-massive bleeding. A p-value less than 0.05 was selected for significance.

RESULTS

A total of 528 patients were included, with 357 insignificant-to-moderate bleeders and 171 severe-to-massive bleeders. Postoperatively, severe-to-massive bleeders had higher rates of PGD grade 3 at 72 h, longer hospital stays, higher mortality rates at 30 days and one year, and were less likely to achieve textbook outcomes for LT. They also required postoperative ECMO, reintubation for over 48 h, tracheostomy, reintervention, and dialysis at higher rates. In the multivariate analysis, severe-to-massive bleeding was significantly associated with adverse outcomes after adjusting for recipient and donor factors, with an odds ratio of 7.73 (95% CI: 4.27-14.4, p < 0.001) for PGD3 at 72 h, 4.30 (95% CI: 2.30-8.12, p < 0.001) for 1-year mortality, and 1.75 (95% CI: 1.52-2.01, p < 0.001) for longer hospital stays. Additionally, severe-to-massive bleeders were less likely to achieve textbook outcomes, with an odds ratio of 0.07 (95% CI: 0.02-0.16, p < 0.001). Preoperative and intraoperative predictors of severe/massive bleeding were identified, with White patients having lower odds compared to Black patients (OR: 041, 95% CI: 0.22-0.80, p = 0.008). Each 1-unit increase in BMI decreased the odds of bleeding (OR: 0.89, 95% CI: 0.83-0.95, p < 0.001), while each 1-unit increase in MPAP increased the odds of bleeding (OR: 1.04, 95% CI: 1.02-1.06, p < 0.001). First-time transplant recipients had lower risk (OR: 0.16, 95% CI: 0.06-0.36, p < 0.001), whereas those with DCD donors had a higher risk of severe-to-massive bleeding (OR: 3.09, 95% CI: 1.63-5.87, p = 0.001).

CONCLUSION

These results suggest that patients at high risk of massive bleeding require higher utilization of hospital resources. Understanding their outcomes is important, as it may inform future decisions to transplant comparable patients.

In silico analysis of NAC gene family in the mangrove plant Avicennia marina provides clues for adaptation to intertidal habitats

NAC (NAM, ATAF1/2, CUC2) transcription factors (TFs) constitute a plant-specific gene family. It is reported that NAC TFs play important roles in plant growth and developmental processes and in response to biotic/abiotic stresses. Nevertheless, little information is known about the functional and evolutionary characteristics of NAC TFs in mangrove plants, a group of species adapting coastal intertidal habitats. Thus, we conducted a comprehensive investigation for NAC TFs in Avicennia marina, one pioneer species of mangrove plants. We totally identified 142 NAC TFs from the genome of A. marina. Combined with NAC proteins having been functionally characterized in other organisms, we built a phylogenetic tree to infer the function of NAC TFs in A. marina. Gene structure and motif sequence analyses suggest the sequence conservation and transcription regulatory regions-mediated functional diversity. Whole-genome duplication serves as the driver force to the evolution of NAC gene family. Moreover, two pairs of NAC genes were identified as positively selected genes of which AmNAC010/040 may be imposed on less constraint toward neofunctionalization. Quite a few stress/hormone-related responsive elements were found in promoter regions indicating potential response to various external factors. Transcriptome data revealed some NAC TFs were involved in pneumatophore and leaf salt gland development and response to salt, flooding and Cd stresses. Gene co-expression analysis found a few NAC TFs participates in the special biological processes concerned with adaptation to intertidal environment. In summary, this study provides detailed functional and evolutionary information about NAC gene family in mangrove plant A. marina and new perspective for adaptation to intertidal habitats.

Proof of Gene Doping in a Mouse Model with a Human Erythropoietin Gene Transferred Using an Adenoviral Vector

Despite the World Anti-Doping Agency (WADA) ban on gene doping in the context of advancements in gene therapy, the risk of EPO gene-based doping among athletes is still present. To address this and similar risks, gene-doping tests are being developed in doping control laboratories worldwide. In this regard, the present study was performed with two objectives: to develop a robust gene-doping mouse model with the human EPO gene (hEPO) transferred using recombinant adenovirus (rAdV) as a vector and to develop a detection method to identify gene doping by using this model. The rAdV including the hEPO gene was injected intravenously to transfer the gene to the liver. After injection, the mice showed significantly increased whole-blood red blood cell counts and increased expression of hematopoietic marker genes in the spleen, indicating successful development of the gene-doping model. Next, direct and potentially indirect proof of gene doping were evaluated in whole-blood DNA and RNA by using a quantitative PCR assay and RNA sequencing. Proof of doping could be detected in DNA and RNA samples from one drop of whole blood for approximately a month; furthermore, the overall RNA expression profiles showed significant changes, allowing advanced detection of hEPO gene doping.

Computational identification and characterization of glioma candidate biomarkers through multi-omics integrative profiling

BACKGROUND

Glioma is one of the most common malignant brain tumors and exhibits low resection rate and high recurrence risk. Although a large number of glioma studies powered by high-throughput sequencing technologies have led to massive multi-omics datasets, there lacks of comprehensive integration of glioma datasets for uncovering candidate biomarker genes.

RESULTS

In this study, we collected a large-scale assemble of multi-omics multi-cohort datasets from worldwide public resources, involving a total of 16,939 samples across 19 independent studies. Through comprehensive molecular profiling across different datasets, we revealed that PRKCG (Protein Kinase C Gamma), a brain-specific gene detectable in cerebrospinal fluid, is closely associated with glioma. Specifically, it presents lower expression and higher methylation in glioma samples compared with normal samples. PRKCG expression/methylation change from high to low is indicative of glioma progression from low-grade to high-grade and high RNA expression is suggestive of good survival. Importantly, PRKCG in combination with MGMT is effective to predict survival outcomes in a more precise manner.

CONCLUSIONS

PRKCG bears the great potential for glioma diagnosis, prognosis and therapy, and PRKCG-like genes may represent a set of important genes associated with different molecular mechanisms in glioma tumorigenesis. Our study indicates the importance of computational integrative multi-omics data analysis and represents a data-driven scheme toward precision tumor subtyping and accurate personalized healthcare.

An effective analytic method for detecting tissue-specific genes in RNA-seq experiments

AIM

To develop an analytic method for identifying tissue-specific (TS) genes from RNA-seq data.

MATERIALS & METHODS

Based on a negative binomial distribution, we develop a statistical method containing consecutive procedures incorporating data variability from replicates in each tissue.

RESULTS

Simulations show that our approach can effectively identify at least 94% of the truly TS genes if the sample size is 3 and at least 84% of the TS genes detected by our method are truly TS genes. We illustrated the utility of our method in an in-house RNA-seq project and produced sensible results.

CONCLUSION

Our approach not only directly works on discrete data but also naturally incorporates data variability. It works effectively for detecting TS genes.

Nanoparticle-GFP "chemical nose" sensor for cancer cell identification

Nanoparticle-based sensor arrays have been used to distinguish a wide range of bio-related molecules through pattern recognition. This "chemical nose" approach uses nanoparticles as receptors to selectively identify the analytes, while a transducer reports the binding through a readable signal (fluorescence). Here we describe a procedure that uses functionalized gold nanoparticles as receptors and green fluorescent protein (GFP) as the transducer to identify and differentiate cell state (normal, cancerous, and metastatic), an important tool in early diagnosis and treatment of tumors.

HOMER: a human organ-specific molecular electronic repository

BACKGROUND

Each organ has a specific function in the body. "Organ-specificity" refers to differential expressions of the same gene across different organs. An organ-specific gene/protein is defined as a gene/protein whose expression is significantly elevated in a specific human organ. An "organ-specific marker" is defined as an organ-specific gene/protein that is also implicated in human diseases related to the organ. Previous studies have shown that identifying specificity for the organ in which a gene or protein is significantly differentially expressed, can lead to discovery of its function. Most currently available resources for organ-specific genes/proteins either allow users to access tissue-specific expression over a limited range of organs, or do not contain disease information such as disease-organ relationship and disease-gene relationship.

RESULTS

We designed an integrated Human Organ-specific Molecular Electronic Repository (HOMER, http://bio.informatics.iupui.edu/homer), defining human organ-specific genes/proteins, based on five criteria: 1) comprehensive organ coverage; 2) gene/protein to disease association; 3) disease-organ association; 4) quantification of organ-specificity; and 5) cross-linking of multiple available data sources.HOMER is a comprehensive database covering about 22,598 proteins, 52 organs, and 4,290 diseases integrated and filtered from organ-specific proteins/genes and disease databases like dbEST, TiSGeD, HPA, CTD, and Disease Ontology. The database has a Web-based user interface that allows users to find organ-specific genes/proteins by gene, protein, organ or disease, to explore the histogram of an organ-specific gene/protein, and to identify disease-related organ-specific genes by browsing the disease data online.Moreover, the quality of the database was validated with comparison to other known databases and two case studies: 1) an association analysis of organ-specific genes with disease and 2) a gene set enrichment analysis of organ-specific gene expression data.

CONCLUSIONS

HOMER is a new resource for analyzing, identifying, and characterizing organ-specific molecules in association with disease-organ and disease-gene relationships. The statistical method we developed for organ-specific gene identification can be applied to other organism. The current HOMER database can successfully answer a variety of questions related to organ specificity in human diseases and can help researchers in discovering and characterizing organ-specific genes/proteins with disease relevance.

MicroRNAs as biomarkers of disease onset

MicroRNAs (miRNAs) are small, noncoding RNA molecules with the ability to posttranscriptionally regulate gene expression via targeting the 3' untranslated region of messenger RNAs. miRNAs are critical for normal cellular functions such as the regulation of the cell cycle, differentiation, and apoptosis, and they target genes during embryonal and postnatal development, whereas their expression is unbalanced in various pathological states. Importantly, miRNAs are abundantly present in body fluids (e.g., blood), which are routinely examined in patients. These molecules circulate in free and exosome encapsulated forms, and can be efficiently detected and amplified by means of molecular biology tools such as real-time PCR. Together with relative stability, specificity, and reproducibility, they are seen as good candidates for early recognition of the onset of disease. Thus, miRNAs might be considered as biomarkers for many pathological states.

Microarray data integration for genome-wide analysis of human tissue-selective gene expression

Background

Microarray gene expression data are accumulating in public databases. The expression profiles contain valuable information for understanding human gene expression patterns. However, the effective use of public microarray data requires integrating the expression profiles from heterogeneous sources.

Results

In this study, we have compiled a compendium of microarray expression profiles of various human tissue samples. The microarray raw data generated in different research laboratories have been obtained and combined into a single dataset after data normalization and transformation. To demonstrate the usefulness of the integrated microarray data for studying human gene expression patterns, we have analyzed the dataset to identify potential tissue-selective genes. A new method has been proposed for genome-wide identification of tissue-selective gene targets using both microarray intensity values and detection calls. The candidate genes for brain, liver and testis-selective expression have been examined, and the results suggest that our approach can select some interesting gene targets for further experimental studies.

Conclusion

A computational approach has been developed in this study for combining microarray expression profiles from heterogeneous sources. The integrated microarray data can be used to investigate tissue-selective expression patterns of human genes.

Human transcriptome nexuses: basic-eukaryotic and metazoan

Using a new approach, I analysed human transcriptome coexpression network and revealed two large-scale nexuses. Besides gene coexpression, each nexus is characterized by a combination of gene evolutionary origin, function and among-tissues expression breadth. The first nexus contains mostly genes of pre-metazoan origin, which are widely expressed and have cell-centred functions. The second nexus is enriched in genes of metazoan origin, which are expressed more narrowly and have organism-centred functions. The revealed nexuses are supported by asymmetry in distribution of transcription factor targets between them. Within the metazoan nexus, there is a subnexus that is more pronounced in the nervous tissues and is enriched in gene regulatory complexity. It mostly contains genes related to nervous system, cell communication and multicellular organism processes and development. The revealed nexuses indicate a dichotomy in the transcriptional regulation and can provide a framework for further functional genomics studies.

The pivotal role of the complement system in aging and age-related macular degeneration: hypothesis re-visited

During the past ten years, dramatic advances have been made in unraveling the biological bases of age-related macular degeneration (AMD), the most common cause of irreversible blindness in western populations. In that timeframe, two distinct lines of evidence emerged which implicated chronic local inflammation and activation of the complement cascade in AMD pathogenesis. First, a number of complement system proteins, complement activators, and complement regulatory proteins were identified as molecular constituents of drusen, the hallmark extracellular deposits associated with early AMD. Subsequently, genetic studies revealed highly significant statistical associations between AMD and variants of several complement pathway-associated genes including: Complement factor H (CFH), complement factor H-related 1 and 3 (CFHR1 and CFHR3), complement factor B (CFB), complement component 2 (C2), and complement component 3 (C3). In this article, we revisit our original hypothesis that chronic local inflammatory and immune-mediated events at the level of Bruch's membrane play critical roles in drusen biogenesis and, by extension, in the pathobiology of AMD. Secondly, we report the results of a new screening for additional AMD-associated polymorphisms in a battery of 63 complement-related genes. Third, we identify and characterize the local complement system in the RPE-choroid complex - thus adding a new dimension of biological complexity to the role of the complement system in ocular aging and AMD. Finally, we evaluate the most salient, recent evidence that bears directly on the role of complement in AMD pathogenesis and progression. Collectively, these recent findings strongly re-affirm the importance of the complement system in AMD. They lay the groundwork for further studies that may lead to the identification of a transcriptional disease signature of AMD, and hasten the development of new therapeutic approaches that will restore the complement-modulating activity that appears to be compromised in genetically susceptible individuals.

Testing the hypothesis of tissue selectivity: the intersection-union test and a Bayesian approach

Motivation: Finding genes that are preferentially expressed in a particular tissue or condition is a problem that cannot be solved by standard statistical testing procedures. A relatively unknown procedure that can be used is the intersection–union test (IUT). However, two disadvantages of the IUT are that it is conservative and it conveys only the information of the least differing target tissue–other tissue pair.

Results: We propose a Bayesian procedure that quantifies how much evidence there is in the overall expression profile for selective over-expression. In a small simulation study, it is shown that the proposed method outperforms the IUT when it comes to finding selectively expressed genes. An application to publicly available data consisting of 22 tissues shows that the Bayesian method indeed selects genes with functions that reflect the specific tissue functions. The proposed method can also be used to find genes that are underexpressed in a particular tissue.

Availability: Both MATLAB and R code that implement the IUT and the Bayesian procedure in an efficient way, can be downloaded at http://ppw.kuleuven.be/okp/software/BayesianIUT/.

Contact:katrijn.vandeun@psy.kuleuven.be

An integrated approach for the systematic identification and characterization of heart-enriched genes with unknown functions

Background

High throughput techniques have generated a huge set of biological data, which are deposited in various databases. Efficient exploitation of these databases is often hampered by a lack of appropriate tools, which allow easy and reliable identification of genes that miss functional characterization but are correlated with specific biological conditions (e.g. organotypic expression).

Results

We have developed a simple algorithm (DGSA = Database-dependent Gene Selection and Analysis) to identify genes with unknown functions involved in organ development concentrating on the heart. Using our approach, we identified a large number of yet uncharacterized genes, which are expressed during heart development. An initial functional characterization of genes by loss-of-function analysis employing morpholino injections into zebrafish embryos disclosed severe developmental defects indicating a decisive function of selected genes for developmental processes.

Conclusion

We conclude that DGSA is a versatile tool for database mining allowing efficient selection of uncharacterized genes for functional analysis.