Significance analysis of microarrays applied to the ionizing radiation response

Tusher, Virginia Goss; Tibshirani, Robert; Chu, Gilbert

doi:10.1073/pnas.091062498

Cited by 10,435 publications

(9,772 citation statements)

References 30 publications

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“…To determine the significant pharmacological response to treatment, we performed a paired analysis using significance analysis of microarrays. 33 A gene was considered as significantly differential expressed if the false discovery rate was equal to or o5%. Cluster analysis 34 was used to define clusters of co-coordinately changed genes after which the data were visualized using Treeview (http://rana.lbl.gov/ EisenSoftware.htm).…”

Section: Pharmacogenomics Of Infliximab Treatmentmentioning

confidence: 99%

Pharmacogenomics of infliximab treatment using peripheral blood cells of patients with rheumatoid arthritis

et al. 2010

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Section: Pharmacogenomics Of Infliximab Treatmentmentioning

confidence: 99%

Pharmacogenomics of infliximab treatment using peripheral blood cells of patients with rheumatoid arthritis

et al. 2010

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“…We also compare our method with SAM using the same dataset for NSCLC lung cancer. SAM combines t-test and permutations to calculate a False Discovery Rate to provide a subset of genes that are considered significant [16]. Using SAM, we select four sets of 50, 100, 150, 200 and 250 most significant genes by using the parameter values of 0.556.…”

Section: Resultsmentioning

confidence: 99%

“…Comparing with recent publications in that the authors use currently available data mining techniques to find biomarkers for NSCLC lung cancer, we found that our new method finds significantly more cost-effective genetic markers and provides more accurate sub-classification of NSCLC lung cancer. Comparison with SAM [16], a popular method for significance analysis of microarrays, is also provided in this paper.…”

Section: Introductionmentioning

confidence: 99%

A novel method for finding non-small cell lung cancer diagnosis biomarkers

Tran

2013

BMC Med Genomics

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BackgroundOne of the most common causes of worldwide cancer premature death is non-small cell lung carcinoma (NSCLC) with a very low survival rate of 8%-15%. Since patients with an early stage diagnosis can have up to four times the survival rate, discovering cost-effective biological markers that can be used to improve the diagnosis and prognosis of the disease is an important clinical challenge.In the last few years, significant progress has been made to address this challenge with identified biomarkers ranging from 5-gene signatures to 133-gene signatures. However, A typical molecular sub-classification method for lung carcinomas would have a low predictive accuracy of 68%-71% because datasets of gene-expression profiles typically have tens of thousands of genes for just few hundreds of patients. This type of datasets create many technical challenges impacting the accuracy of the diagnostic prediction.ResultsWe discovered that a small set of nine gene-signatures (JAG1, MET, CDH5, ABCC3, DSP, ABCD3, PECAM1, MAPRE2 and PDF5) from the dataset of 12,600 gene-expression profiles of NSCLC acts like an inference basis for NSCLC lung carcinoma and hence can be used as genetic markers. This very small and previously unknown set of biological markers gives an almost perfect predictive accuracy (99.75%) for the diagnosis of the disease the sub-type of cancer. Furthermore, we present a novel method that finds genetic markers for sub-classification of NSCLC. We use generalized Lorenz curves and Gini ratios to overcome many challenges arose from datasets of gene-expression profiles. Our method discovers novel genetic changes that occur in lung tumors using gene-expression profiles.ConclusionsWhile proteins encoded by some of these gene-signatures (e.g., JAG1 and MAPRE2) have been showed to involve in the signal transduction of cells and proliferation control of normal cells, specific functions of proteins encoded by other gene-signatures have not yet been determined. Hence, this work opens new questions for structural and molecular biologists about the role of these gene-signatures for the disease.

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“…Significance analysis of microarray (SAM)26 was used to analyze gene expression difference by between high‐TRIM26‐NPCs and low‐TRIM26‐NPCs, and high‐TRIM26‐NPs and low‐TRIM26‐NPCs. The delta was set to 0.94 so that false discovery rate (FDR) was 5% for each group comparison.…”

Section: Methodsmentioning

confidence: 99%

A regulatory mutant on TRIM26 conferring the risk of nasopharyngeal carcinoma by inducing low immune response

et al. 2018

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The major histocompatibility complex (MHC) is most closely associated with nasopharyngeal carcinoma (NPC), but the complexity of its genome structure has proven challenging for the discovery of causal MHC loci or genes. We conducted a targeted MHC sequencing in 40 Cantonese NPC patients followed by a two‐stage replication in 1065 NPC cases and 2137 controls of Southern Chinese descendent. Quantitative RT‐PCR analysis (qRT‐PCR) was used to detect gene expression status in 108 NPC and 43 noncancerous nasopharyngeal (NP) samples. Luciferase reporter assay and chromatin immunoprecipitation (ChIP) were used to assess the transcription factor binding site. We discovered that a novel SNP rs117565607_A at TRIM26 displayed the strongest association (OR = 1.909, Pcombined = 2.750 × 10−19). We also observed that TRIM26 was significantly downregulated in NPC tissue samples with genotype AA/AT than TT. Immunohistochemistry (IHC) test also found the TRIM26 protein expression in NPC tissue samples with the genotype AA/AT was lower than TT. According to computational prediction, rs117565607 locus was a binding site for the transcription factor Yin Yang 1 (YY1). We observed that the luciferase activity of YY1 which is binding to the A allele of rs117565607 was suppressed. ChIP data showed that YY1 was binding with T not A allele. Significance analysis of microarray suggested that TRIM26 downregulation was related to low immune response in NPC. We have identified a novel gene TRIM26 and a novel SNP rs117565607_A associated with NPC risk by regulating transcriptional process and established a new functional link between TRIM26 downregulation and low immune response in NPC.

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Significance analysis of microarrays applied to the ionizing radiation response

Cited by 10,435 publications

References 30 publications

Pharmacogenomics of infliximab treatment using peripheral blood cells of patients with rheumatoid arthritis

Pharmacogenomics of infliximab treatment using peripheral blood cells of patients with rheumatoid arthritis

A novel method for finding non-small cell lung cancer diagnosis biomarkers

A regulatory mutant on TRIM26 conferring the risk of nasopharyngeal carcinoma by inducing low immune response

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