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Integrative Analysis of lncRNA-mRNA Profile Reveals Potential Predictors for SAPHO Syndrome.

ABSTRACT: Synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome is known as a rare disease characterized by inflammatory lesions on bones and skin. Polymorphism of clinical manifestation and lack of molecular biomarkers have both limited its diagnosis. Our study performed RNA sequencing (RNA-seq) and integrative bioinformatics analysis of long noncoding RNA (lncRNA)-messenger RNA (mRNA) profile in patients with SAPHO syndrome and healthy controls. A total of 4,419 differentially expressed (DE) mRNAs and 2,713 lncRNAs were identified (p < 0.05, fold change > 2) and a coexpression network was constructed to further investigate their regulatory interactions. The DE lncRNAs were predicted to interact with mRNAs in both cis and trans manners. Functional prediction found that the lncRNA-targeted genes may function in SAPHO syndrome by participating in biological process such as adipocytokine signaling pathway, ErbB signaling pathway, FoxO signaling pathway, as well as production and function of miRNAs. The expression levels of three pairs of coexpressed lncRNA-mRNAs were validated by qRT-PCR, and their relative expression levels were consistent with the RNA-seq data. The deregulated RNAs GAS7 and lnc-CLLU1.1-1:2 may serve as potential diagnostic biomarkers, and the combined receiver operating characteristic (ROC) curve of the two showed more reliable diagnostic ability with an AUC value of 0.871 in distinguishing SAPHO patients from healthy controls. In conclusion, this study provides a first insight into long noncoding RNA transcriptome profile changes associated with SAPHO syndrome and inspiration for further investigation on clinical biomarkers and molecular regulators of this inadequately understood clinical entity.

SUBMITTER: Sun Y

PROVIDER: S-EPMC8255928 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background:Hepatocellular carcinoma (HCC) is an aggressive cancer with a poor prognosis and a high incidence. The molecular changes and novel biomarkers of HCC need to be identified to improve the diagnosis and prognosis of this disease. We investigated the current research concentrations of HCC and identified the transcriptomics-related biomarkers of HCC from The Cancer Genome Atlas (TGCA) database. Methods:We investigated the current research concentrations of HCC using literature metrology analysis for studies conducted from 2008 to 2018. We identified long noncoding RNAs (lncRNAs) that correlated with the clinical features and survival prognoses of HCC from The Cancer Genome Atlas (TGCA) database. Differentially expressed genes (lncRNAs, miRNAs, and mRNAs) were also identified by TCGA datasets in HCC tumor tissues. A lncRNA competitive endogenous RNA (ceRNA) network was constructed from lncRNAs based on intersected lncRNAs. Survival times and the association between the expression levels of the key lncRNAs of the ceRNA network and the clinicopathological characteristics of HCC patients were analyzed using TCGA. Real-time polymerase chain reaction (qRT-PCR) was used to validate the reliability of the results in tissue samples from 20 newly-diagnosed HCC patients. Results:Analysis of the literature pertaining to HCC research revealed that current research is focused on lncRNA functions in tumorigenesis and tumor development. A total of 128 HCC dysregulated lncRNAs were identified; 66 were included in the co-expressed ceRNA network. We analyzed survival times and the associations between the expression of 66 key lncRNAs and the clinicopathological features of the HCC patients identified from TCGA. Twenty-six lncRNAs were associated with clinical features of HCC (P < 0.05) and six key lncRNAs were associated with survival time (log-rank test P < 0.05). Six key lncRNAs were selected for the validation of their expression levels in 20 patients with newly diagnosed HCC using qRT-PCR. Consistent fold changes in the trends of up and down regulation between qRT-PCR validation and TCGA proved the reliability of our bioinformatics analysis. Conclusions:We used integrative bioinformatics analysis of the TCGA datasets to improve our understanding of the regulatory mechanisms involved with the functional features of lncRNAs in HCC. The results revealed that lncRNAs are potential diagnostic and prognostic biomarkers of HCC.

Project description:Transcription signatures have been used to stratify breast cancer patients into clinically distinct subgroups. However, transcription alone does not determine protein expression. Of potentially equal importance for determining the tumor phenotype is the rate at which transcripts are translated to form protein. Protein translation is controlled to a major degree by miRNA, and cancer cells may deregulate the expression of key genes by altering the activity of relevant miRNAs. The importance of miRNA deregulation and the extent to which multiple miRNAs coordinately deregulate key proteins in breast cancer is only partly understood. To gain such insight, we analyzed genome-wide miRNA expression and mRNA/protein expression for a panel of 105 selected cancer related genes in breast carcinomas from 283 patients. The miRNA-mRNA-protein interactome for the selected genes was constructed by modeling protein expression as a joint function of mRNA and miRNA expression, considering the effect of both one miRNA at a time, and all studied miRNAs simultaneously. The interactome represents a map of the global effects of miRNAs on protein expression, capturing direct as well as indirect effects. The results reveal extensive association between miRNA and protein expression as well as coordinated effects of multiple miRNAs on individual proteins. Applying the model onto two other independent primary breast cancer cohorts confirmed the generalizability of key aspects of the interactome map. The mRNA expression profiling of 283 breast cancer samples was performed using the SurePrint G3 Human GE 8x60K one-color microarrays from Agilent (Agilent Technologies, Santa Clara, CA, USA) according to the manufacturer’s protocol (One-Color Microarray-Based Gene Expression Analysis, Low Input Quick Amp Labeling, v.6.5, May 2010). For each sample, 100 ng of RNA was amplified and hybridized on the array. Scanning was performed with Agilent Scanner G2565A, using AgilentG3_GX_1Color as profile. Signals were extracted using FE v.10.7.3.1 and protocol GE1_107_Sep09 (Agilent Technologies). Arrays were log2-transformed, quantile normalized and hospital-adjusted by subtracting from each probe value the mean probe value among samples from the same hospital. The Oslo Breast Cancer Consortium (OSBREAC)

Project description:ObjectiveThis study aimed to investigate the functions of mRNA, long non-coding RNA (lncRNA), and circular RNA (circRNA) in paroxysmal and persistent atrial fibrillation (AF) patients.MethodsA total of 9 left atrial appendage (LAA) tissues were collected from patients with AF (ParoAF patients = 3 and PersAF patients = 3) and donors (n=3). Genes and circRNAs were identified by per kilobase per million reads (RPKM) and number of circular reads/number of mapped reads/read length (SRPBM), respectively. Differentially expressed mRNAs (DE mRNAs), lncRNAs (DE lncRNAs), and circRNAs (DE circRNAs) were identified by | log2 (Fold Change) | ≥ 2 and p-value < 0.05. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Protein-protein, mRNA-lncRNA, and circRNA-miRNA interaction networks were constructed. In addition, logistic analysis was conducted among AF and circRNAs.ResultsA total of 285 (116 up-regulated and 169 down-regulated) and 275 (110 up-regulated and 165 down-regulated) DE mRNAs, 575 (276 up-regulated and 299 down-regulated) and 583 (330 up-regulated and 253 down-regulated) DE lncRNAs, and 83 (48 up-regulated and 35 down-regulated) and 99 (58 up-regulated and 41 down-regulated) circRNAs were detected in ParoAF and PersAF, respectively, as compared with control. MAPK signal pathway as well as voltage-dependent, L type, and alpha 1C subunit calcium channel (CACNA1C) might participate in AF occurrence by preventing atrial parasympathetic remodeling. Collagen type I alpha 1 (COL1A1) and COL1A2 mostly participated in the enriched GO and KEGG terms and connected with most of the DE mRNAs. The expression of chr10: 69902697|69948883 was a protective factor against PersAF after adjusting for age (p=0.022, 95% CI: 0.003-0.634).ConclusionWe found that some mRNAs, lncRNAs, circRNAs, and pathways play essential roles in AF pathogenesis and development. Moreover, one protective factor against PersAF was detected.

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Integrative Analysis of lncRNA-mRNA Profile Reveals Potential Predictors for SAPHO Syndrome.

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