-
Heliyon Apr 2024Kaposi's sarcoma (KS) is the second most common tumor in human immunodeficiency virus (HIV) infected patients worldwide. While many miRNAs have been confirmed to be...
Kaposi's sarcoma (KS) is the second most common tumor in human immunodeficiency virus (HIV) infected patients worldwide. While many miRNAs have been confirmed to be involved in KS biological processes, no relevant studies have combined miRNA and mRNA expression profiles using KS patient tissue biopsies. In this study, we performed transcriptome sequencing on tumor and normal tissues from four KS patients and identified differentially expressed mRNA and miRNA, further performed target gene prediction and enrichment analysis. 19,551 target-mRNAs were identified by predicting 106 miRNAs, with 553 overlapping with 571 significantly differentially expressed mRNAs. Enrichment analysis showed significant involvement of the Ubiquitin-mediated proteolysis pathway. Additionally, the miRNA-mRNA interaction network was established, and the topological score of Cytohubba's algorithm was calculated for comparison with three other datasets. The Mutual Clustering Coefficient (MCC) scoring ranking placed ZBTB34, NFIB, and RORA as the top three mRNAs, while hsa-miR-16-5p, hsa-miR-27a-3p, hsa-miR-340-5p, hsa-miR-182-5p, and hsa-miR-186-5p ranked as the top five miRNAs. Hsa-miR-101-3p is the only miRNA that appears both in the top 10 MCC scores and at the intersection of the other two datasets. Finally, qRT-PCR was used to validate the findings at the cellular level. In summary, the miRNA analysis results indicated that hsa-miR-101-3p could be used as a potential diagnostic or therapeutic marker in future studies. Moreover, the mRNA analysis results suggested that the histone binding pathways involved in mRNAs and ubiquitin-related biological processes were closely associated with KS and could serve as promising biomarkers for the diagnosis and treatment of this disease.
PubMed: 38660282
DOI: 10.1016/j.heliyon.2024.e29502 -
Scientific Reports Apr 2024Long extrachromosomal circular DNA (leccDNA) regulates several biological processes such as genomic instability, gene amplification, and oncogenesis. The identification...
Long extrachromosomal circular DNA (leccDNA) regulates several biological processes such as genomic instability, gene amplification, and oncogenesis. The identification of leccDNA holds significant importance to investigate its potential associations with cancer, autoimmune, cardiovascular, and neurological diseases. In addition, understanding these associations can provide valuable insights about disease mechanisms and potential therapeutic approaches. Conventionally, wet lab-based methods are utilized to identify leccDNA, which are hindered by the need for prior knowledge, and resource-intensive processes, potentially limiting their broader applicability. To empower the process of leccDNA identification across multiple species, the paper in hand presents the very first computational predictor. The proposed iLEC-DNA predictor makes use of SVM classifier along with sequence-derived nucleotide distribution patterns and physicochemical properties-based features. In addition, the study introduces a set of 12 benchmark leccDNA datasets related to three species, namely Homo sapiens (HM), Arabidopsis Thaliana (AT), and Saccharomyces cerevisiae (SC/YS). It performs large-scale experimentation across 12 benchmark datasets under different experimental settings using the proposed predictor, more than 140 baseline predictors, and 858 encoder ensembles. The proposed predictor outperforms baseline predictors and encoder ensembles across diverse leccDNA datasets by producing average performance values of 81.09%, 62.2% and 81.08% in terms of ACC, MCC and AUC-ROC across all the datasets. The source code of the proposed and baseline predictors is available at https://github.com/FAhtisham/Extrachrosmosomal-DNA-Prediction . To facilitate the scientific community, a web application for leccDNA identification is available at https://sds_genetic_analysis.opendfki.de/iLEC_DNA/.
Topics: DNA, Circular; Humans; Saccharomyces cerevisiae; Arabidopsis; Computational Biology; Nucleotides; Support Vector Machine
PubMed: 38658614
DOI: 10.1038/s41598-024-57457-5 -
BMC Cancer Apr 2024Therapies for metastatic castration-resistant prostate cancer (mCRPC) include targeting the androgen receptor (AR) with androgen receptor inhibitors (ARIs) and...
Detecting androgen receptor (AR), AR variant 7 (AR-V7), prostate-specific membrane antigen (PSMA), and prostate-specific antigen (PSA) gene expression in CTCs and plasma exosome-derived cfRNA in patients with metastatic castration-resistant prostate cancer (mCRPC) by integrating the VTX-1 CTC...
BACKGROUND
Therapies for metastatic castration-resistant prostate cancer (mCRPC) include targeting the androgen receptor (AR) with androgen receptor inhibitors (ARIs) and prostate-specific membrane antigen (PSMA). Having the ability to detect AR, AR splice variant 7 (AR-V7), or PSMA in circulating tumor cells (CTCs) or circulating exosomal cell-free RNA (cfRNA) could be helpful to guide selection of the appropriate therapy for each individual patient. The Vortex Biosciences VTX-1 system is a label-free CTC isolation system that enables the detection of the expression of multiple genes in both CTCs and exosomal cfRNA from the same blood sample in patients with mCRPC. Detection of both AR-V7 and PSMA gene expression in both CTCs and cfRNA simultaneously has not yet been reported.
METHODS
To characterize the combined VTX-1-AdnaDetect workflow, 22Rv1 cancer cells were spiked into blood from healthy donors and processed with the VTX-1 to mimic patient samples and assess performances (capture efficiency, purity, AR and AR-V7 expression). Then, we collected 19 blood samples from 16 patients with mCRPC and therapeutic resistance to androgen receptor inhibitors (ARIs). Plasma was separated and the plasma-depleted blood was processed further with the VTX-1 to collect CTCs. Both plasma exosomal cfRNA and CTCs were subsequently analyzed for AR, AR-V7, PSMA, and prostate-specific antigen (PSA) mRNA expression using the AdnaTest ProstateCancerPanel AR-V7 assay.
RESULTS
AR-V7 expression could be detected in 22Rv1 cells spiked into blood from healthy volunteers as well as in CTCs and plasma-derived exosomal cfRNA from patients with mCRPC by processing blood with the VTX-1 CTC isolation system followed by the AdnaTest ProstateCancerPanel AR-V7 assay. 94.7% of patient blood samples (18/19) had detectable AR expression in either CTCs or exosomal cfRNA (16 in CTCs, 12 in cfRNA). 15.8% of the 19 patient blood samples (3/19) were found to have AR-V7-positive (AR-V7+) CTCs, one of which was also AR-V7+ in the exosomal cfRNA analysis. 42.1% of patient blood samples (8/19) were found to be PSMA positive (PSMA+): 26.3% (5/19) were PSMA+ in the CTC analysis and 31.6% (6/19) were PSMA+ in the exosomal cfRNA analysis. Of those 8 PSMA+ samples, 2 had detectable PSMA only in CTCs, and 3 had detectable PSMA only in exosomal cfRNA.
CONCLUSION
VTX-1 enables isolation of CTCs and plasma exosomes from a single blood draw and can be used for detecting AR-V7 and PSMA mRNA in both CTCs and cfRNA in patients with mCRPC and resistance to ARIs. This technology facilitates combining RNA measurements in CTCs and exosomal cfRNA for future studies to develop potentially clinically relevant cancer biomarker detection in blood.
Topics: Humans; Male; Androgen Receptor Antagonists; Biomarkers, Tumor; Cell-Free Nucleic Acids; Exosomes; Neoplastic Cells, Circulating; Prostate; Prostate-Specific Antigen; Prostatic Neoplasms, Castration-Resistant; Protein Isoforms; Receptors, Androgen; RNA, Messenger
PubMed: 38627648
DOI: 10.1186/s12885-024-12139-3 -
AMB Express Apr 2024Tuberculosis (TB) poses significant challenges due to its high transmissibility within populations and intrinsic resistance to treatment, rendering it a formidable...
Tuberculosis (TB) poses significant challenges due to its high transmissibility within populations and intrinsic resistance to treatment, rendering it a formidable respiratory disease with a substantial susceptibility burden. This study was designed to identify new potential therapeutic targets for TB and establish a diagnostic model. mRNA expression data for TB were from GEO database, followed by conducting differential expression analysis. The top 50 genes with differential expression were subjected to GO and KEGG enrichment analyses. To establish a PPI network, the STRING database was utilized, and hub genes were identified utilizing five algorithms (EPC, MCC, MNC, Radiality, and Stress) within the cytoHubba plugin of Cytoscape software. Furthermore, a hub gene co-expression network was constructed using the GeneMANIA database. Consistency clustering was performed on hub genes, and ssGSEA was utilized to analyze the extent of immune infiltration in different subgroups. LASSO analysis was employed to construct a diagnostic model, and ROC curves were used for validation. Through the analysis of GEO data, a total of 159 genes were identified as differentially expressed. Further, GO and KEGG enrichment analyses revealed that these genes were mainly enriched in viral defense, symbiotic defense, and innate immune response-related pathways. Hub genes, including DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15, were identified using cytoHubba analysis of the PPI network. The GeneMANIA analysis unmasked that the co-expression rate of hub genes was 81.55%, and the physical interaction rate was 12.27%. Consistency clustering divided TB patients into two subgroups, and ssGSEA revealed different degrees of immune infiltration in different subgroups. LASSO analysis identified IFIT1, IFIT2, IFIT3, IFIH1, RSAD2, OAS1, OAS2, and STAT1 as eight immune-related key genes, and a diagnostic model was constructed. The ROC curve demonstrated that the model exhibited excellent diagnostic performance. DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15 were hub genes in TB, and the diagnostic model based on eight immune-related key genes exhibited good diagnostic performance.
PubMed: 38615114
DOI: 10.1186/s13568-024-01691-7 -
Poultry Science Jun 2024As a Chinese local chicken breed, Hongshan chickens have 2 kinds of tail feather phenotypes, normal and taillessness. Our previous studies showed that taillessness was a...
As a Chinese local chicken breed, Hongshan chickens have 2 kinds of tail feather phenotypes, normal and taillessness. Our previous studies showed that taillessness was a sex-linked dominant trait. Abnormal development of the tail vertebrae could be explained this phenomenon in some chicken breeds. However, the number of caudal vertebrae in rumpless Hongshan chickens was normal, so rumplessness in Hongshan chicken was not related to the development of the caudal vertebrae. Afterwards, we found that rumplessness in Hongshan was due to abnormal development of tail feather rather than abnormal development of caudal vertebrae. In order to understand the genetic foundation of the rumplessness of Hongshan chickens, we compared and reanalyzed 2 sets of data in normal and rumpless Hongshan chickens from our previous studies. By joint analysis of genome-wide selection signature analysis and genome-wide association approach, we found that 1 overlapping gene (EDIL3) and 16 peak genes (ENSGALG00000051843, ENSGALG00000053498, ENSGALG00000054800, KIF27, PTPRD, ENSGALG00000047579, ENSGALG00000041052, ARHGEF28, CAMK4, SERINC5, ENSGALG00000050776, ERCC8, MCC, ADAMTS19, ENSGALG00000053322, CHRNA8) located on the Z chromosome was associated with the rumpless trait. The results of this study furtherly revealed the molecular mechanism of the rumpless trait in Hongshan chickens, and identified the candidate genes associated with this trait. Our results will help to improve the shape of chicken tail feathers and to rise individual economic value in some specific market in China.
Topics: Animals; Chickens; Male; Female; Feathers; Tail; Genome-Wide Association Study; Phenotype; China
PubMed: 38603937
DOI: 10.1016/j.psj.2024.103685 -
BMC Genomics Apr 2024Posterior capsular opacification (PCO) is the main reason affecting the long-term postoperative result of cataract patient, and it is well accepted that fibrotic PCO is...
BACKGROUND
Posterior capsular opacification (PCO) is the main reason affecting the long-term postoperative result of cataract patient, and it is well accepted that fibrotic PCO is driven by transforming growth factor beta (TGFβ) signaling. Ferroptosis, closely related to various ocular diseases, but has not been explored in PCO.
METHODS
RNA sequencing (RNA-seq) was performed on both TGF-β2 treated and untreated primary lens epithelial cells (pLECs). Differentially expressed genes (DEGs) associated with ferroptosis were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to investigate their biological function. Additionally, protein-to-protein interactions among selected ferroptosis-related genes by PPI network and the top 10 genes with the highest score (MCC algorithm) were selected as the hub genes. The top 20 genes with significant fold change values were validated using quantitative real-time polymerase chain reaction (qRT-PCR).
RESULTS
Our analysis revealed 1253 DEGs between TGF-β2 treated and untreated pLECs, uncovering 38 ferroptosis-related genes between two groups. Among these 38 ferroptosis-related genes,the most prominent GO enrichment analysis process involved in the response to oxidative stress (BPs), apical part of cell (CCs),antioxidant activity (MFs). KEGG were mainly concentrated in fluid shear stress and atherosclerosis, IL-17 and TNF signaling pathways, and validation of top 20 genes with significant fold change value were consistent with RNA-seq.
CONCLUSIONS
Our RNA-Seq data identified 38 ferroptosis-related genes in TGF-β2 treated and untreated pLECs, which is the first observation of ferroptosis related genes in primary human lens epithelial cells under TGF-β2 stimulation.
Topics: Humans; Transforming Growth Factor beta2; Transcriptome; Epithelial-Mesenchymal Transition; Ferroptosis; Blotting, Western; Capsule Opacification; Epithelial Cells
PubMed: 38594623
DOI: 10.1186/s12864-024-10244-y -
Immunobiology May 2024Trauma is statistically a significant cause of mortality among patients across countries. Nevertheless, the precise correlation between genetic diagnostic markers and...
BACKGROUND
Trauma is statistically a significant cause of mortality among patients across countries. Nevertheless, the precise correlation between genetic diagnostic markers and the intricate mechanism of trauma remains indistinct.
METHODS
Our study exclusively centered on trauma patients and selected three trauma-related datasets from the Gene Expression Omnibus (GEO) database, all of which had blood samples collected within post-traumatic 12 h. Differential gene screening, the WGCNA and Cytoscape software were employed to analyze the two datasets, with a particular emphasis on the top 100 genes selected based on MCC algorithm scores. A logistic diagnostic model was constructed by analyzing the intersection genes in the third dataset, leading to the identification of diagnostic biomarkers with high efficiency. The global immune landscape of these patients was extensively investigated using a multidimensional approach. Meanwhile, the underlying pathological and physiological mechanisms associated with early trauma status are summarized by integrating existing literature.
RESULTS
Out of these two GEO datasets, 21 overlapping genes were identified and incorporated into in the logistic diagnostic model constructed in the GSE36809 dataset. A panel of 9 genes was uncovered as a diagnostic biomarker, and their expression and correlation were subsequently verified. Additionally, by virtue of various algorithms, the findings revealed an upregulation of neutrophil expression and a downregulation of CD8+ T cell expression, indicating characteristic early trauma-induced inflammation activation and immune suppression. The correlation observed between the feature genes and immune cells serves to validate the exceptional diagnostic capability of these 9 genes in identifying trauma status and their promising potential for patients who could benefit from targeted immune interventions. Drawing from these findings, the discussion section offers insights into the underlying pathological and physiological mechanisms at play.
CONCLUSION
Our research has discovered a novel diagnostic biomarker and unveiled its association with post-traumatic immune alterations. This breakthrough enables accurate and timely diagnosis of early trauma, facilitating the implementation of appropriate healthcare interventions.
Topics: Humans; Wounds and Injuries; Inflammation; Biomarkers; Gene Expression Profiling; Computational Biology; Transcriptome; Databases, Genetic; Immune Evasion; Gene Regulatory Networks
PubMed: 38593729
DOI: 10.1016/j.imbio.2024.152801 -
Journal of King Saud University.... Oct 2023Gene expression data is typically high dimensional with a limited number of samples and contain many features that are unrelated to the disease of interest. Existing...
AIM
Gene expression data is typically high dimensional with a limited number of samples and contain many features that are unrelated to the disease of interest. Existing unsupervised feature selection algorithms primarily focus on the significance of features in maintaining the data structure while not taking into account the redundancy among features. Determining the appropriate number of significant features is another challenge.
METHOD
In this paper, we propose a clustering-guided unsupervised feature selection (CGUFS) algorithm for gene expression data that addresses these problems. Our proposed algorithm introduces three improvements over existing algorithms. For the problem that existing clustering algorithms require artificially specifying the number of clusters, we propose an adaptive -value strategy to assign appropriate pseudo-labels to each sample by iteratively updating a change function. For the problem that existing algorithms fail to consider the redundancy among features, we propose a feature grouping strategy to group highly redundant features. For the problem that the existing algorithms cannot filter the redundant features, we propose an adaptive filtering strategy to determine the feature combinations to be retained by calculating the potentially effective features and potentially redundant features of each feature group.
RESULT
Experimental results show that the average accuracy (ACC) and matthews correlation coefficient (MCC) indexes of the C4.5 classifier on the optimal features selected by the CGUFS algorithm reach 74.37% and 63.84%, respectively, significantly superior to the existing algorithms.
CONCLUSION
Similarly, the average ACC and MCC indexes of the Adaboost classifier on the optimal features selected by the CGUFS algorithm are significantly superior to the existing algorithms. In addition, statistical experiment results show significant differences between the CGUFS algorithm and the existing algorithms.
PubMed: 38567001
DOI: 10.1016/j.jksuci.2023.101731 -
Molecular Therapy. Methods & Clinical... Jun 2024Gene therapies and associated technologies are transforming biomedical research and enabling novel therapeutic options for patients living with debilitating and...
Gene therapies and associated technologies are transforming biomedical research and enabling novel therapeutic options for patients living with debilitating and incurable genetic disorders. The vector system based on recombinant adeno-associated viral vectors (AAVs) has shown great promise in recent clinical trials for genetic diseases of multiple organs, such as the liver and the nervous system. Despite recent successes toward the development of novel bioengineered AAV variants for improved transduction of primary human tissues and cells, vectors that can efficiently transduce human Schwann cells (hSCs) have yet to be identified. Here, we report the application of the functional transduction-RNA selection method in primary hSCs for the development of AAV variants for specific and efficient transgene delivery to hSCs. The two identified capsid variants, Pep2hSC1 and Pep2hSC2, show conserved potency for delivery across various , , and models of hSCs. These novel AAV capsids will serve as valuable research tools, forming the basis for therapeutic solutions for both SC-related disorders or peripheral nervous system injury.
PubMed: 38558569
DOI: 10.1016/j.omtm.2024.101234 -
Anais Brasileiros de Dermatologia Mar 2024Merkel cell polyomavirus (MCPyV), a human polyomavirus that is unequivocally linked to merkel cell carcinoma (MCC), has been found in association with keratinocytes...
BACKGROUND
Merkel cell polyomavirus (MCPyV), a human polyomavirus that is unequivocally linked to merkel cell carcinoma (MCC), has been found in association with keratinocytes carcinomas (KC), especially basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC). Nevertheless, there is scarce information about the possible involvement of MCPyV in the development of KC.
OBJECTIVES
To assess the presence of MCPyV DNA and Large-T Antigen (LT-Ag) via Polymerase Chain Reaction (PCR) and Immunohistochemistry (IHC) in cases of KC, and to correlate its presence with immunohistochemical markers p16, p53, and ki67, tumor type and subtype, sun-exposed location, and epidemiological data.
METHODS
The prevalence of MCPyV DNA, LT-Ag, and immunohistochemical markers p16, p53, and ki67 was assessed by PCR and Immunohistochemistry (IHC) in 127 cases of KC, these results were correlated with tumor type and subtype, sun-exposed location, and epidemiological data.
RESULTS
The MCPyV DNA was detected in 42.57% (43 of 101) cases by PCR, the LT-Ag was detected in 16.4% (20 of 122) of cases, p16 in 81.5% (97 of 119), p53 in 66.4% (83 of 125), ki67 in 89% (73 of 82). No correlation between MCPyV LT-Ag and DNA confronted with tumor type, subtype, location site, and immunohistochemical markers was found. A single correlation between the MCPyV LT-Ag and cSCC tumors and peri-tumoral lymphocyte cells was noted.
STUDY LIMITATIONS
Further steps need to be taken to better evaluate the MCPyV influence and its possible role in KC carcinogenesis, as the evaluation of the virus genome state, the gene sequence that encodes LT-Ag in the KC tumor cells, and in situ hybridization for viral DNA or RNA in these cells.
CONCLUSIONS
Despite the frequent detection of MCPyV in KC, the data available so far does not support the hypothesis of a causal relationship between them.
PubMed: 38555263
DOI: 10.1016/j.abd.2023.12.002