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Background: Perioperative neurocognitive disorders (PND) refer to neurocognitive abnormalities during perioperative period, which are a great challenge for elderly patients and associated with increased morbidity and mortality. Our studies showed that long non-coding RNAs (lncRNAs) regulate mitochondrial function and aging-related pathologies in the aged hippocampus after anesthesia, and lncRNAs are associated with multiple neurodegenerations. However, the regulatory role of lncRNAs in PND-related pathological processes remains unclear. Methods: A total of 18-month mice were assigned to control and surgery (PND) groups, mice in PND group received sevoflurane anesthesia and laparotomy. Cognitive function was assessed with fear conditioning test. Hippocampal RNAs were isolated for sequencing, lncRNA and microRNA libraries were constructed, mRNAs were identified, Gene Ontology (GO) analysis were performed, and lncRNA-microRNA-mRNA networks were established. qPCR was performed for gene expression verification. Results: A total of 312 differentially expressed (DE) lncRNAs, 340 DE-Transcripts of Uncertain Coding Potential (TUCPs), and 2,003 DEmRNAs were identified in the hippocampus between groups. The lncRNA-microRNA-mRNA competing endogenous RNA (ceRNA) network was constructed with 29 DElncRNAs, 90 microRNAs, 493 DEmRNAs, 148 lncRNA-microRNA interaction pairs, 794 microRNA-mRNA interaction pairs, and 110 lncRNA-mRNA co-expression pairs. 795 GO terms were obtained. Based on the frequencies of involved pathological processes, BP terms were divided into eight categories: neurological system alternation, neuronal development, metabolism alternation, immunity and neuroinflammation, apoptosis and autophagy, cellular communication, molecular modification, and behavior changes. LncRNA-microRNA-mRNA ceRNA networks in these pathological categories were constructed, and involved pathways and targeted genes were revealed. The top relevant lncRNAs in these ceRNA networks included RP23-65G6.4, RP24-396L14.1, RP23-251I16.2, XLOC_113622, RP24-496E14.1, etc., and the top relevant mRNAs in these ceRNA networks included Dlg4 (synaptic function), Avp (lipophagy), Islr2 (synaptic function), Hcrt (regulation of awake behavior), Tnc (neurotransmitter uptake). Conclusion: In summary, we have constructed the lncRNA-associated ceRNA network during PND development in mice, explored the role of lncRNAs in multiple pathological processes in the mouse hippocampus, and provided insights into the potential mechanisms and therapeutic gene targets for PND.
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Redes Reguladoras de Genes , Hipocampo , MicroARNs , ARN Largo no Codificante , ARN Mensajero , Animales , ARN Largo no Codificante/genética , ARN Largo no Codificante/metabolismo , Hipocampo/metabolismo , Hipocampo/patología , Ratones , MicroARNs/genética , MicroARNs/metabolismo , ARN Mensajero/genética , ARN Mensajero/metabolismo , Trastornos Neurocognitivos/genética , Trastornos Neurocognitivos/metabolismo , Trastornos Neurocognitivos/patología , Masculino , Periodo Perioperatorio , Sevoflurano , Ratones Endogámicos C57BL , ARN Endógeno CompetitivoRESUMEN
OBJECTIVE: Hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), mostly characterised by HBV integrations, is prevalent worldwide. Previous HBV studies mainly focused on a few hotspot integrations. However, the oncogenic role of the other HBV integrations remains unclear. This study aimed to elucidate HBV integration-induced tumourigenesis further. DESIGN: Here, we illuminated the genomic structures encompassing HBV integrations in 124 HCCs across ages using whole genome sequencing and Nanopore long reads. We classified a repertoire of integration patterns featured by complex genomic rearrangement. We also conducted a clustered regularly interspaced short palindromic repeat (CRISPR)-based gain-of-function genetic screen in mouse hepatocytes. We individually activated each candidate gene in the mouse model to uncover HBV integration-mediated oncogenic aberration that elicits tumourigenesis in mice. RESULTS: These HBV-mediated rearrangements are significantly enriched in a bridge-fusion-bridge pattern and interchromosomal translocations, and frequently led to a wide range of aberrations including driver copy number variations in chr 4q, 5p (TERT), 6q, 8p, 16q, 9p (CDKN2A/B), 17p (TP53) and 13q (RB1), and particularly, ultra-early amplifications in chr8q. Integrated HBV frequently contains complex structures correlated with the translocation distance. Paired breakpoints within each integration event usually exhibit different microhomology, likely mediated by different DNA repair mechanisms. HBV-mediated rearrangements significantly correlated with young age, higher HBV DNA level and TP53 mutations but were less prevalent in the patients subjected to prior antiviral therapies. Finally, we recapitulated the TONSL and TMEM65 amplification in chr8q led by HBV integration using CRISPR/Cas9 editing and demonstrated their tumourigenic potentials. CONCLUSION: HBV integrations extensively reshape genomic structures and promote hepatocarcinogenesis (graphical abstract), which may occur early in a patient's life.
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Carcinoma Hepatocelular , Virus de la Hepatitis B , Neoplasias Hepáticas , Integración Viral , Carcinoma Hepatocelular/virología , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/patología , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/virología , Neoplasias Hepáticas/patología , Virus de la Hepatitis B/genética , Humanos , Integración Viral/genética , Animales , Ratones , Masculino , Persona de Mediana Edad , Femenino , Adulto , Secuenciación Completa del Genoma , Variaciones en el Número de Copia de ADN , AncianoRESUMEN
INTRODUCTION: Sarcomatoid hepatocellular carcinoma (SHC) is a rare subtype of liver cancer with extremely poor prognosis. This study aimed to identify the prognostic factors and develop an exclusive and efficient nomogram to predict cancer-specific survival (CSS) for SHC. METHODS: The data on patients diagnosed with SHC from January 1973 to December 2015 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database, and these patients were included as the training cohort. Least absolute shrinkage and selection operator (LASSO) and Cox proportional hazards regression analyses were used to identify the prognostic risk factors and construct a nomogram. The predictive accuracy and discriminative ability of the nomogram were determined using concordance index (C-index), calibration curve, and receiver operating characteristic (ROC) curve. Decision curve analysis (DCA) was used to compare the clinical benefits of the prognostic evaluation model (PEM) with that of the American Joint Committee on Cancer (AJCC) staging system. The results were validated with an external validation cohort. RESULTS: In total, 116 patients with SHC were included in the training cohort. Multivariate Cox analysis revealed M stage (distant metastasis), primary tumor surgery, and chemotherapy to be associated with CSS, and along with tumor size, an integrated PEM was constructed. A calibration curve for the probability of survival showed good agreement between the nomogram and actual observation. The C-index value of the nomogram for predicting CSS and AJCC was 0.853 and 0.649, respectively. In the validation cohort, the C-index value of the PEM discrimination was better than that of the Barcelona Clinic Liver Cancer (BCLC) staging system, CLIP score, and Okuda staging system, and no statistical difference was observed with eighth edition of the AJCC staging system and Izumi staging system. CONCLUSION: The proposed four-factor nomogram of PEM could accurately predict the prognosis of SHC and could be used in clinical practice.