Host gene expression signatures of H1N1, H3N2, HRV, RSV virus infection in adults
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ABSTRACT: Consider the problem of designing a panel of complex biomarkers to predict a patient's health or disease state when one can pair his or her current test sample, called a target sample, with the patient's previously acquired healthy sample, called a reference sample. As contrasted to a population averaged reference, this reference sample is individualized. Automated predictor algorithms that compare and contrast the paired samples to each other could result in a new generation of test panels that compare to a person's healthy reference to enhance predictive accuracy. This study develops such an individualized predictor and illustrates the added value of including the healthy reference for design of predictive gene expression panels. The objective is to predict each subject's state of infection, e.g., neither exposed nor infected, exposed but not infected, pre-acute phase of infection, acute phase of infection, post-acute phase of infection. Using gene microarray data collected in a large-scale serially sampled respiratory virus challenge study, we quantify the diagnostic advantage of pairing a person's baseline reference with his or her target sample.
Project description:Background/Aims: Recurrence-free survival (RFS) following curative resection of hepatocellular carcinoma (HCC) in subjects with hepatitis C virus (HCV) infection is highly variable. Traditional clinico-pathological endpoints are recognized as weak predictors of RFS. It has been suggested that gene expression profiling of HCC and nontumoral liver tissue may improve prediction of RFS, aid in understanding of the underlying liver disease, and guide individualized therapy. The goal of this study was to create a gene expression predictor of HCC recurrence in subjects with HCV. Methods: Frozen samples of the tumors and nontumoral liver were obtained from 47 subjects with HCV-associated HCC. Additional nontumoral liver samples were obtained from HCV-free subjects with metastatic liver tumors. Gene expression profiling data was used to determine the molecular signature of HCV-associated HCC and to develop a predictor of RFS. Results: The molecular profile of the HCV-associated HCC confirmed central roles for MYC and TGF-beta1 in liver tumor development. Gene expression in tumors was found to have poor predictive power with regards to RFS, but analysis of nontumoral tissues yielded a strong predictor for RFS in late-recurring (>1 year) subjects. Importantly, nontumoral tissue-derived gene expression predictor of RFS was highly significant in both univariable and multivariable Cox proportional hazard model analyses. Conclusions: Microarray analysis of the nontumoral tissues from subjects with HCV-associated HCC delivers novel molecular signatures of RFS, especially among the late-recurrence subjects. The gene expression signature of the predictor gives important insights into the pathobiology of HCC recurrence and used in design of the individualized therapy.
Project description:Background/Aims: Recurrence-free survival (RFS) following curative resection of hepatocellular carcinoma (HCC) in subjects with hepatitis C virus (HCV) infection is highly variable. Traditional clinico-pathological endpoints are recognized as weak predictors of RFS. It has been suggested that gene expression profiling of HCC and nontumoral liver tissue may improve prediction of RFS, aid in understanding of the underlying liver disease, and guide individualized therapy. The goal of this study was to create a gene expression predictor of HCC recurrence in subjects with HCV. Methods: Frozen samples of the tumors and nontumoral liver were obtained from 47 subjects with HCV-associated HCC. Additional nontumoral liver samples were obtained from HCV-free subjects with metastatic liver tumors. Gene expression profiling data was used to determine the molecular signature of HCV-associated HCC and to develop a predictor of RFS. Results: The molecular profile of the HCV-associated HCC confirmed central roles for MYC and TGF-beta1 in liver tumor development. Gene expression in tumors was found to have poor predictive power with regards to RFS, but analysis of nontumoral tissues yielded a strong predictor for RFS in late-recurring (>1 year) subjects. Importantly, nontumoral tissue-derived gene expression predictor of RFS was highly significant in both univariable and multivariable Cox proportional hazard model analyses. Conclusions: Microarray analysis of the nontumoral tissues from subjects with HCV-associated HCC delivers novel molecular signatures of RFS, especially among the late-recurrence subjects. The gene expression signature of the predictor gives important insights into the pathobiology of HCC recurrence and used in design of the individualized therapy. 43 tumor (JT) and 44 non-tumor (JNT) liver tissues surgically resected from patients with HCV-associated hepatocellular carcinoma; 8 non-tumor liver tissues (control samples, JC) surgically resected from HCV- or HBV-free patients with metastatic liver tumor. Inter-batch normalization was carried out using Distance Weighted Discrimination procedure. The supplementary file 'GSE17856_Readme.txt' contains a description of the replicates used for normalization. The 'GSE17856_US14702406_2514850*' files are the raw data files for the replicates.
Project description:Spinal Muscular Atrophy (SMA) is an autosomal recessive motor neuron disease and is the second most common genetic disorder leading to death in childhood. Motoneurons derived from induced pluripotent stem cells (iPS cells) obtained by reprogramming SMA patient and his healthy father fibroblasts, and genetically corrected SMA-iPSC obtained converting SMN2 into SMN1 with target gene correction (TGC), were used to study gene expression and splicing events linked to pathogenetic mechanisms. Microarray technology was used to assess global gene expression profiles of iPSC from SMA patient, unaffected father and iPS 19.9 (Prof. J. Thomson's lab) compared to transcriptomic data obtained by corresponding fibroblasts. The microarray data derived from three different individuals: SMA patient, healthy father and control iPS cells (19.9). We analyzed iPSC from SMA patient (n=2), iPS- from healthy father (n=1) and iPS-19.9 from Prof. Thomson's lab (n=3). The expression profile was compared to SMA patient's fibroblasts (n=2) and healthy father's fibroblasts (n=1)
Project description:The aim of this study was to construct and validate a prognostic risk model to predict the overall survival (OS) of patients with cervical cancer, providing a reference for individualized clinical treatment that may lead to better clinical outcomes. HLA-G-driven DEG signature consisting of the eight most important prognostic genes CD46, LGALS9, PGM1, SPRY4, CACNB3, PLIN2, MSMO1, and DAGLB was identified as a key predictor of cervical cancer. To summarize, we developed and validated a novel prognostic risk model for cervical cancer based on HLA-G-driven DEGs, and the prognostic signature showed great ability in predicting the overall survival of patients with cervical cancer.
Project description:The aim of this study was to construct and validate a prognostic risk model to predict the overall survival (OS) of patients with cervical cancer, providing a reference for individualized clinical treatment that may lead to better clinical outcomes. HLA-G-driven DEG signature consisting of the eight most important prognostic genes CD46, LGALS9, PGM1, SPRY4, CACNB3, PLIN2, MSMO1, and DAGLB was identified as a key predictor of cervical cancer. To summarize, we developed and validated a novel prognostic risk model for cervical cancer based on HLA-G-driven DEGs, and the prognostic signature showed great ability in predicting the overall survival of patients with cervical cancer.
Project description:For Samples GSM601017-28: The aim of this study was to use expression profiling to define transcriptional patterns and regulatory pathways that characterize the host liver response to E. multilocularis infection in the experimental model of secondary infection, to compare gene expression in this model to those described in the model of "primary infection", and to follow the changes in gene expression and in the expression of a cell proliferation marker over time during the complete chronic phase of E.multilocularis infection, following early and middle stages. For Samples GSM601029-40: The aim of this study was to use expression profiling to define transcriptional patterns and regulatory pathways that characterize the host liver response to E. multilocularis infection in the experimental model of secondary infection, to compare gene expression in this model to those described in the model of "primary infection", and to follow the changes in gene expression and in the expression of a cell proliferation marker over time during the complete chronic phase of E.multilocularis infection, following its middle and late stages. For Samples GSM601017-28: The anterior liver tissue sample of control mice group and alveolar echinococcosis mice group were obtained at each time point(1 month and 3 month). Biological replicates is 3. Then, total RNA from anterior liver of both groups were used as test sample, which labelled cy5 fluorescein, and the pool RNA of healthy BALB/c mice anterior liver was used as reference sample, which labelled cy3 fluorescein, and then hybridized to 32K Mouse Genome Array Genechips, representing about 25000 characterized murine genes. For Samples GSM601029-40: The anterior liver tissue sample of control mice group and alveolar echinococcosis mice group were obtained at each time point(2 month and 6 month). Biological replicates is 3. Then, total RNA from anterior liver of both groups were used as test sample, which labelled cy5 fluorescein, and the pool RNA of healthy BALB/c mice anterior liver was used as reference sample, which labelled cy3 fluorescein, and then hybridized to 36K Mouse Genome Array Genechips, representing about 25000 characterized murine genes.
Project description:Spinal Muscular Atrophy (SMA) is an autosomal recessive motor neuron disease and is the second most common genetic disorder leading to death in childhood. Motoneurons derived from induced pluripotent stem cells (iPSC) obtained by reprogramming SMA patient and his healthy father fibroblasts, and genetically corrected SMA-iPSC obtained converting SMN2 into SMN1 with target gene correction (TGC), were used to study gene expression and splicing events linked to pathogenetic mechanisms. Microarray technology was used to assess the global gene expression profile as well as splicing events of iPS-derived motorneurons from SMA patient, unaffected father and TGC-treated cells. The microarray data derived from three different groups: SMA patient, healty father and treated SMA patient's cells. Each population consists of three RNA profiling cell samples.
Project description:We performed small RNA sequencing to explore small RNA profiles of serum exosomes derived from LTBI and TB patients and healthy controls (HC). Our results revealed distinct miRNA profile of the exosomes from the three samples. We identified many differentially expressed miRNAs, including some specifically expressed miRNAs in the three samples. Besides the specially expressed miRNAs, we demonstrated distinct expression panels of the serum exosomal miRNAs from LTBI and TB samples, and six expression patterns among the three samples. These specifically expressed miRNAs and differentially expressed miRNAs in different panels and patterns provide potential biomarkers for detection/diagnosis of latent and active TB using exosomal miRNAs. Additionally, we also discovered plenty of small RNAs derived from genomic repetitive sequences (e.g., SINEs, LINEs and LTR), which might play roles in host immune responses along with Mtb infection progresses. Overall, our findings provide important reference and improved understanding about miRNAs and repetitive region-derived small RNAs in exosome during Mtb infectious process, and facilitate the development of potential molecular targets for detection/diagnosis of latent and active tuberculosis.
Project description:Blood-based protein tests inform medical decision-making, but despite major investments, few new biomarkers reach the clinic. Plasma and serum are rich sources of information about an individual’s health state and mass spectrometry (MS)-based proteomics now allows highly specific and quantitative read-out of the plasma proteome. Here we employ plasma proteome profiling to define marker panels assessing the quality of plasma and serum samples and the likelihood that suggested biomarkers are instead artifacts related to sample handling and processing. We acquired reference proteomes of erythrocytes, platelets, plasma and whole blood of 20 individuals (>6000 proteins), and compared serum and plasma proteomes. Based on spike-in experiments we defined a panels of contamination-associated proteins, many of which have been reported as biomarker candidates. We provide sample preparation guidelines and an online resource (www.plasmaproteomeprofiling.com) to assess overall sample-related bias in clinical studies and to prevent costly miss-assignment of biomarker candidates.
Project description:Transcripional profiling of lymphocytes from patients with amyotrophic lateral sclerosis (ALS) (n=11) and healthy control subjects (n=11). The goal was to determine disease response expression signatures relevant of ALS pathogenesis that affect brain and spinal cord. The reference design was used: each Cy5-labeled cRNA sample from ALS patient or healthy control subject was cohybridized on Agilent-014850 Whole Human Genome Microarray 4x44K G4112F with the reference pool formed with equal amounts of Cy3-labeled cRNAs from each sample from the healthy control group.