Gene expression differences between matched tumor and normal samples of NSCLC patients (qRT-PCR)
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE10937 | GEO | 2009/10/01
SECONDARY ACCESSION(S): PRJNA108781
REPOSITORIES: GEO
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Project description:Gene expression differences between the tumor subtypes AC and SCC were analyzed using t-test. Keywords: disease subtype analysis
2009-10-01 | GSE10936 | GEO
Project description:Our aim was to decipher the underlying molecular mechanism of synchronous ovarian metastasis of gastric cancer. We hereby conducted transcriptome sequencing of triple-matched samples including normal gastric mucosa, primary gastric cancer and ovarian metastatic tumors from 3 individual patients with the application of Illumina sequencing platform with 150-bp paired-end. Follow-up analyses not only identified differentially expressed genes between different sample sets (a threshold of fold change >2 and adjusted P value <0.05) but also uncovered significantly enriched signaling pathways of individual type. To sum up, our comparative transcriptomic analyses of triple-matched fresh samples stored in liquid nitrogen profiled the molecular expression and revealed functionally enriched pathways underlying the ovarian metastasis of gastric cancer.
2022-06-20 | GSE206329 | GEO
Project description:ObjectivesThe accurate detection of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is essential for the diagnosis of coronavirus disease 2019 (COVID-19). We compared the quantitative RT-PCR results between nasopharyngeal swabs and saliva specimens.MethodsA COVID-19 outbreak occurred on a cruise ship at Nagasaki port, Japan. We obtained 123 nasopharyngeal swabs and saliva each from asymptomatic or mild patients in the late phase of infection.ResultsThe intervals from the diagnosis to the sampling were 25.5 days for nasopharyngeal swabs and 28.9 days for saliva. The positive rate was 19.5% (24/123) for nasopharyngeal swabs and 38.2% (47/123) for saliva (P = 0.48). The quantified viral copies (mean ± SEM copies/5 μl) were 9.3±2.6 in nasopharyngeal swabs and 920±850 in saliva (P = 0.0006).ConclusionsThe advantages of saliva specimens include positive rate improvement and accurate viral load detection. Saliva may be used as a reliable sample for SARS-CoV-2 detection.
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Project description:BackgroundObservations of recurrent somatic mutations in tumors have led to identification and definition of signaling and other pathways that are important for cancer progression and therapeutic targeting. As tumor cells contain both an individual's inherited genetic variants and somatic mutations, challenges arise in distinguishing these events in massively parallel sequencing datasets. Typically, both a tumor sample and a "normal" sample from the same individual are sequenced and compared; variants observed only in the tumor are considered to be somatic mutations. However, this approach requires two samples for each individual.ResultsWe evaluate a method of detecting somatic mutations in tumor samples for which only a subset of normal samples are available. We describe tuning of the method for detection of mutations in tumors, filtering to remove inherited variants, and comparison of detected mutations to several matched tumor/normal analysis methods. Filtering steps include the use of population variation datasets to remove inherited variants as well a subset of normal samples to remove technical artifacts. We then directly compare mutation detection with tumor-only and tumor-normal approaches using the same sets of samples. Comparisons are performed using an internal targeted gene sequencing dataset (n = 3380) as well as whole exome sequencing data from The Cancer Genome Atlas project (n = 250). Tumor-only mutation detection shows similar recall (43-60%) but lesser precision (20-21%) to current matched tumor/normal approaches (recall 43-73%, precision 30-82%) when compared to a "gold-standard" tumor/normal approach. The inclusion of a small pool of normal samples improves precision, although many variants are still uniquely detected in the tumor-only analysis.ConclusionsA detailed method for somatic mutation detection without matched normal samples enables study of larger numbers of tumor samples, as well as tumor samples for which a matched normal is not available. As sensitivity/recall is similar to tumor/normal mutation detection but precision is lower, tumor-only detection is more appropriate for classification of samples based on known mutations. Although matched tumor-normal analysis is preferred due to higher precision, we demonstrate that mutation detection without matched normal samples is possible for certain applications.
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Project description:To identify new oncogenic drivers in prostate cancer, we performed transcriptome analysis of localized primary prostate cancer samples and the matched normal tissues.
2021-05-01 | GSE114740 | GEO
Project description:BACKGROUND: Given the epidemic proportions of obesity worldwide and the concurrent prevalence of metabolic syndrome, there is an urgent need for better understanding the underlying mechanisms of metabolic syndrome, in particular, the gene expression differences which may participate in obesity, insulin resistance and the associated series of chronic liver conditions. Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in different tissues and experimental conditions. However, variations in amount of starting material, enzymatic efficiency and presence of inhibitors can lead to quantification errors. Hence the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Recent studies have shown that both obesity and presence of insulin resistance influence an expression of commonly used reference genes in omental fat. In this study we validated candidate reference genes suitable for qRT-PCR profiling experiments using visceral adipose samples from obese and lean individuals. RESULTS: Cross-validation of expression stability of eight selected reference genes using three popular algorithms, GeNorm, NormFinder and BestKeeper found ACTB and RPII as most stable reference genes. CONCLUSIONS: We recommend ACTB and RPII as stable reference genes most suitable for gene expression studies of human visceral adipose tissue. The use of these genes as a reference pair may further enhance the robustness of qRT-PCR in this model system.
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Project description:The protocols herein outline the use of qRT-PCR to detect the presence of SARS-CoV-2 genomic RNA in patient samples. In order to cope with potential fluctuations in supply chain and testing demands and to enable expedient adaptation of reagents and assays on hand, we include details for three parallel methodologies (one- and two-step singleplex and one-step multiplex assays). The diagnostic platforms described can be easily adapted by basic science research laboratories for SARS-CoV-2 diagnostic testing with relatively short turnaround time. For complete details on the use and execution of this protocol, please refer to Vanuytsel et al. (2020).
| S-EPMC7490627 | biostudies-literature
Project description:DNA sequencing of tumours to identify somatic mutations has become a critical tool to guide the type of treatment given to cancer patients. The gold standard for mutation calling is comparing sequencing data from the tumour to a matched normal sample to avoid mis-classifying inherited SNPs as mutations. This procedure works extremely well, but in certain situations only a tumour sample is available. While approaches have been developed to find mutations without a matched normal, they have limited accuracy or require specific types of input data (e.g. ultra-deep sequencing). Here we explore the application of single molecule long read sequencing to calling somatic mutations without matched normal samples. We develop a simple theoretical framework to show how haplotype phasing is an important source of information for determining whether a variant is a somatic mutation. We then use simulations to assess the range of experimental parameters (tumour purity, sequencing depth) where this approach is effective. These ideas are developed into a prototype somatic mutation caller, smrest, and its use is demonstrated on two highly mutated cancer cell lines. Finally, we argue that this approach has potential to measure clinically important biomarkers that are based on the genome-wide distribution of mutations: tumour mutation burden and mutation signatures.
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Project description:We generated primary cultures from renal cell carcinoma and matched normal primary kidney cortex tubule cell cultures from 3 patients. Early passage cultures of these two cell types were subjected to chromatin accessibility profiling (DNase-seq) and gene expression profiling (RNA-seq). Studying these paired and patient-matched controlled data sets will shed light on the epigenomic changes that underlie transformation of kidney tubules into malignant cancers.
2018-07-19 | GSE117323 | GEO
Project description:We generated primary cultures from renal cell carcinoma and matched normal primary kidney cortex tubule cell cultures from 3 patients. Early passage cultures of these two cell types were subjected to chromatin accessibility profiling (DNase-seq) and gene expression profiling (RNA-seq). Studying these paired and patient-matched controlled data sets will shed light on the epigenomic changes that underlie transformation of kidney tubules into malignant cancers.
2018-07-19 | GSE117313 | GEO