Prognostic implications of immune-related eight-gene signature in pediatric brain tumors

Genomic studies have provided insights into molecular subgroups and oncogenic drivers of pediatric brain tumors (PBT) that may lead to novel therapeutic strategies. Participants of the cohort Pediatric Brain Tumor Atlas: CBTTC (CBTTC cohort), were randomly divided into training and validation cohorts. In the training cohort, Kaplan-Meier analysis and univariate Cox regression model were applied to preliminary screening of prognostic genes. The LASSO Cox regression model was implemented to build a multi-gene signature, which was then validated in the validation and CBTTC cohorts through Kaplan-Meier, Cox, and receiver operating characteristic curve (ROC) analyses. Also, gene set enrichment analysis (GSEA) and immune infiltrating analyses were conducted to understand function annotation and the role of the signature in the tumor microenvironment. An eight-gene signature was built, which was examined by Kaplan-Meier analysis, revealing that a significant overall survival difference was seen, either in the training or validation cohorts. The eight-gene signature was further proven to be independent of other clinic-pathologic parameters via the Cox regression analyses. Moreover, ROC analysis demonstrated that this signature owned a better predictive power of PBT prognosis. Furthermore, GSEA and immune infiltrating analyses showed that the signature had close interactions with immune-related pathways and was closely related to CD8 T cells and monocytes in the tumor environment. Identifying the eight-gene signature (CBX7, JADE2, IGF2BP3, OR2W6P, PRAME, TICRR, KIF4A, and PIMREG) could accurately identify patients' prognosis and the signature had close interactions with the immunodominant tumor environment, which may provide insight into personalized prognosis prediction and new therapies for PBT patients.

Insights into the signal transduction pathways of mouse lung type II cells revealed by transcription factor profiling in the transcriptome

Alveolar type II cells constitute a small fraction of the total lung cell mass. However, they play an important role in many cellular processes including trans-differentiation into type I cells as well as repair of lung injury in response to toxic chemicals and respiratory pathogens. Transcription factors are the regulatory proteins dynamically modulating DNA structure and gene expression. Transcription factor profiling in microarray datasets revealed that several members of AP1, ATF, NF-kB, and C/EBP families involved in diverse responses were expressed in mouse lung type II cells. A transcriptional factor signature consisting of Cebpa, Srebf1, Stat3, Klf5, and Elf3 was identified in lung type II cells, Sox9+ pluripotent lung stem cells as well as in mouse lung development. Identification of the transcription factor profile in mouse lung type II cells will serve as a useful resource and facilitate the integrated analysis of signal transduction pathways and specific gene targets in a variety of physiological conditions.

Analysis of the transcriptional regulatory mechanisms mediated by microRNAs in Metabolic Syndrome / Análise dos mecanismos regulatórios transcricionais mediados por microRNAs na Síndrome Metabólica

Metabolic Syndrome (MetS) is a combination of diseases interrelated and associated with increased mortality and risk of cardiovascular events. Among the elucidated molecular mechanisms of MetS, there are several genes regulated by miRNAs - small non-coding RNAs. A large number of transcriptomic studies in public databases integrated with new analysis methods can generate new insights. Therefore, this study aimed to identify circulating miRNAs and their target genes in MetS using a Systems Biology approach. For this, we used GEO-NCBI to download and analyse 26 microarray transcriptome studies of MetS and obesity. After preprocessing, the data underwent differential expression (LIMMA method), gene co-expression (CEMiTool), and enrichment (GSEA, Reactome) analyses. We retrieved a gene expression signature for subcutaneous adipose tissue (SAT) for obese individuals that included 291 consistent differentially expressed genes (DEG). This signature had a positive normalized enrichment score (NES) for adaptive immune system activation responses, and negative NES for metabolic pathways. The consensus co-expression network of SAT revealed 3 communities (CM) of densely interconnected genes. These CMs had a high number of up regulated genes and a consistent positive NES among the studies. The co-expressed genes of these 3 CMs were related to neutrophil degranulation, infiltration of immune system cells, and inflammatory processes. Also, a small brazillian cohort (6 individuals with MetS and 6 controls) underwent a seric miRNA profiling using PCR array. From the 222 miRNAs detected in serum, the differential expression analysis identified 4 upregulated miRNAs (miR-30c-5p, miR-421, miR-542-5p and miR-574) in MetS patients (p<0.01). The integrative miRNAs-mRNAs analysis revealed that the circulating upregulated miRNAs had 12 targets in the SAT, 3 targets in the liver; and no targets in the muscle and blood. Many of these target genes are known modulators of proinflammatory pathways. In conclusion, the use of Systems Biology in the analysis of gene networks and circulating miRNAs identified some potential molecular and pathophysiological mechanisms of the Metabolic Syndrome. The circulating miRNAs identified in this study are potential biomarkers and/or therapeutic targets. However, further studies are needed to validate these miRNAs and their target mRNA

A Síndrome Metabólica (MetS) é um conjunto de doenças inter-relacionadas e associadas ao aumento de mortalidade e risco de eventos cardiovasculares. Entre os mecanismos moleculares elucidados da MetS, existem muitos genes regulados por miRNAs - RNAs pequenos não codificadores. O grande número de estudos transcriptômicos em banco dados públicos integrado a novos métodos de análise podem gerar novas descobertas. Deste modo, o objetivo deste estudo foi identificar miRNAs circulantes e genes alvos na MetS usando a abordagem de Biologia de Sistemas. Para isso, GEO-NCBI foi usado para obter e analisar 26 estudos de transcriptoma por microarray de MetS e obesidade. Após o pré-processamento, realizamos análises de expressão diferencial (método LIMMA), co-expressão gênica (CEMiTool), e enriquecimento (GSEA, Reactome). Identificamos uma assinatura de expressão gênica do tecido adiposo subcutâneo (SAT) de indivíduos obesos, composta por 291 genes consistentemente diferencialmente expressos (DEG). Essa assinatura teve um escore de enriquecimento normalizado (NES) positivo para ativação de respostas do sistema imune adaptativo, e NES negativo para vias de metabolismo. A rede consenso de co-expressão do SAT revelou 3 comunidades (CM) de genes densamente interconectadas. Essas CMs continham muitos genes regulados positivamente e com consistência de NES positivo entre os estudos. Os genes co-expressos dessas 3 comunidades pertenciam a vias de a degranulação de neutrófilos, infiltração de células do sistema imune e processos inflamatórios. Além disso, uma pequena coorte brasileira (6 indivíduos com MetS e 6 controles) foi submetida à dosagem sérica de miRNAs por PCR array. Dos 222 miRNAs detectados no soro, a análise de expressão diferencial identificou 4 miRNAs regulados positivamente (miR-30c-5p, miR-421, miR-542-5p e miR-574) nos pacientes com MetS (p<0.01). A análise integrativa miRNAs-mRNAs revelou que osmiRNAs circulantes superexpressos tinham 12 alvos no SAT, 3 alvos no fígado; e nenhum alvo no músculo e no sangue. Muitos desses alvos são moduladores de vias ró-inflamatórias. Em conclusão, a utilização da Biologia de Sistemas na análise de redes gênicas e miRNAs circulantes identificou alguns potenciais mecanismos moleculares e fisiopatológicos da Síndrome Metabólica. Os miRNAs circulantes identificados neste trabalho são potenciais biomarcadores e/ou alvos terapêuticos. Entretanto, mais estudos são necessários para validar esses miRNAs e seus mRNAs alvos

Current situation and thinking of the prognostic gene markers' in early-stage non-small-cell lung cancer / 肿瘤研究与临床

Non-small-cell lung cancer (NSCLC) patients with the same TNM stage may suffer from large prognosis variations. Even patients with early-stage NSCLC still demonstrated lower-than-expecting survival rates after surgical resection, indicating that the current staging methods which were based on anatomy do not adequately predict outcome. Especially the insufficient growth of very early period tumors limited the prognostic prediction of anatomy characteristics, therefore studies focusing on tumor biologic characteristics were developed in order to identify prognostic gene markers. A variety of prognostic genomic models were based on microarray analysis and quantitative polymerase chain reaction (PCR) and analyzed by bioinformatics data processing. However, the prognostic gene lists reported to date overlapped poorly in the studies with similar background. To improve the cloudy situation, the research protocol should be standardized.On the other hand, instead of simple addition of several genes, sequential combination of prognostic gene markers based on signal pathway should be developed which may possess much more rationality and systematicness.