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Human genome u133a 2.0 array

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The Human Genome U133A 2.0 Array is a high-density oligonucleotide microarray designed for the expression analysis of a large number of human genes. It contains over 54,000 probe sets, representing approximately 47,000 transcripts and variants, which correspond to over 38,500 well-characterized human genes.

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Lab products found in correlation

Human genome u133 plus 2.0 array, by Thermo Fisher Scientific (35 mentions) Humanht 12 v4.0 expression beadchip, by Illumina (26 mentions) Human genome u133a array, by Thermo Fisher Scientific (17 mentions) Human exon 1.0 st array, by Thermo Fisher Scientific (3 mentions) Ht human genome u133a array, by Thermo Fisher Scientific (3 mentions) Tweak, by R&D Systems (2 mentions) Mirvana isolation kit, by Thermo Fisher Scientific (2 mentions) Hiseq 2500, by Illumina (2 mentions) Rneasy mini kit, by Qiagen (2 mentions) Mouse genome 430a 2.0 array, by Thermo Fisher Scientific (2 mentions) Gpl571platform, by Thermo Fisher Scientific (2 mentions) Genechip human genome u133 plus 2.0 array, by Thermo Fisher Scientific (2 mentions) Microarray analysis suite version 5, by Thermo Fisher Scientific (2 mentions) Human genome u133 plus 2, by Thermo Fisher Scientific (2 mentions) Human gene 1.0 st array, by Thermo Fisher Scientific (2 mentions) Affymetrix human genome u133 plus 2.0 array, by Thermo Fisher Scientific (2 mentions) Human x3p array, by Thermo Fisher Scientific (2 mentions) Trizol reagent, by Thermo Fisher Scientific (2 mentions) Nextseq 500, by Illumina (1 mentions) Human genome u95 version 2 array, by Thermo Fisher Scientific (1 mentions)

162 protocols using human genome u133a 2.0 array

1

Genome-wide expression profiling of tumor samples

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Fresh frozen tumor specimens were supplied by the MSKCC tumor bank. Total RNA was extracted from tumor specimens and hybridized to Human Genome U133A 2.0 Array (Affymetrix) GeneChips.
Total RNA was extracted from three to six replicates of each cell line (single replicate of MC01) and hybridized to the Human Genome U133A 2.0 Array (Affymetrix). Three replicates of all cell lines (excluding MC01) were also hybridized to the GeneChip Human Genome U133 Plus 2.0 Array (Affymetrix).
Daily K., Coxon A., Williams J.S., Lee C.C., Coit D.G., Busam K.J, & Brownell I. (2014). Assessment of Cancer Cell Line Representativeness using Microarrays for Merkel Cell Carcinoma. The Journal of investigative dermatology, 135(4), 1138-1146.
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2

Genome-wide expression profiling of tumor samples

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Fresh frozen tumor specimens were supplied by the MSKCC tumor bank. Total RNA was extracted from tumor specimens and hybridized to Human Genome U133A 2.0 Array (Affymetrix) GeneChips.
Total RNA was extracted from three to six replicates of each cell line (single replicate of MC01) and hybridized to the Human Genome U133A 2.0 Array (Affymetrix). Three replicates of all cell lines (excluding MC01) were also hybridized to the GeneChip Human Genome U133 Plus 2.0 Array (Affymetrix).
Daily K., Coxon A., Williams J.S., Lee C.C., Coit D.G., Busam K.J, & Brownell I. (2014). Assessment of Cancer Cell Line Representativeness using Microarrays for Merkel Cell Carcinoma. The Journal of investigative dermatology, 135(4), 1138-1146.
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3

Differential Gene Expression in ESCC and Normal Tissues

Cited 4 times
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ESCC and adjacent normal tissue gene expression profiles of GSE20347 [13 (link)], GSE29001 [12 (link)], GSE100942 [14 (link)], and GSE38129 [15 (link)] were downloaded from GEO (http://www.ncbi.nlm.nih.gov/geo/) database [16 (link)]. The microarray data of GSE29001 was based on GPL571 Platforms (Affymetrix Human Genome U133A 2.0 Array) and included 12 pairs of ESCC and non-tumor tissues (Submission date: May 02, 2011). The GSE20347 data was based on GPL571 Platforms (Affymetrix Human Genome U133A 2.0 Array) and included 17 ESCC tissues and 17 normal tissues (Submission date: Feb 16, 2010). The GSE100942 data was based on GPL570 Platforms (Affymetrix Human Genome U133 Plus 2.0 Array) and included 4 ESCC tissues and 4 non-tumor tissues (Submission date: Jul 07, 2017). The GSE38129 data was based on GPL571 Platforms (Affymetrix Human Genome U133A 2.0 Array) and included 30 pairs of ESCC and non-tumor tissues (Submission date: May 22, 2012). The above datasets met the following criteria: (1) they used tissue samples from human ESCC tissues and paired adjacent or non-tumor tissues; (2) each dataset involved more than eight samples.
Yang W., Zhao X., Han Y., Duan L., Lu X., Wang X., Zhang Y., Zhou W., Liu J., Zhang H., Zhao Q., Hong L, & Fan D. (2019). Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy. Cancer Cell International, 19, 142.
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4

TWEAK-induced NFκB signaling in DU145/RasB1 cells

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DU145/RasB1 cells were treated with TWEAK (25ng/mL, R&D Systems, Minneapolis, MN, USA) for 60 min. Total RNA was extracted using mirVana Isolation Kit (Thermo Fisher Scientific, Waltham, MA, USA). After TWEAK treatment, samples were validated for increased expression levels of known NFκB target genes, IL8 and IκBα, and submitted for microarray analysis. Microarray analysis was performed with Affymetrix Human Genome U133A 2.0 Array. Fold changes in gene expression were determined by ANOVA using Partek Genomics Suite (Partek, Chesterfield, MO, USA).
Li L., Ameri A.H., Wang S., Jansson K.H., Casey O.M., Yang Q., Beshiri M.L., Fang L., Lake R.G., Agarwal S., Alilin A.N., Xu W., Yin J, & Kelly K. (2019). EGR1 Regulates Angiogenic and Osteoclastogenic Factors in Prostate Cancer and Promotes Metastasis. Oncogene, 38(35), 6241-6255.
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5

Integrative Immune Profiling of Breast Cancer

Cited 2 times
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Immune gene list and category information were obtained from IMMPORT (https://www.immport.org/). Transcripts per million (TPM) data and clinicopathological information of GSE163882 and GSE123845 datasets were obtained from Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) and the literature (26 (link)). GSE163882 was sequenced on Illumina NextSeq 500 platform and served as a training set in this study. GSE123845 was sequenced on Illumina HiSeq 2500 platform and served as an independent external test set in this study. The detailed information on the training and test datasets was described in Table S1. Raw sequencing data of GSE163882 were downloaded from Sequence Read Archive (SRA, https://www.ncbi.nlm.nih.gov/sra, Accession: PRJNA688066). Raw data and clinicopathological information of GSE20271 profiled on a DNA microarray platform (Affymetrix Human Genome U133A 2.0 Array), were obtained from GEO. Samples in the datasets with incomplete pCR information were removed. Another RNA-seq dataset of BC patients was downloaded from The Cancer Genome Atlas (TCGA, https://portal.gdc.cancer.gov/, Accession: TCGA-BRCA), and the relevant mutation and immune microenvironment data were obtained from the literature (27 (link)). Hallmark and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway gene sets were collected from MSigDB (https://www.gsea-msigdb.org/).
Chen J., Hao L., Qian X., Lin L., Pan Y, & Han X. (2022). Machine learning models based on immunological genes to predict the response to neoadjuvant therapy in breast cancer patients. Frontiers in Immunology, 13, 948601.
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6

Comparative Transcriptional Analysis of CML and Normal Bone Marrow Cells

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We downloaded CML bone marrow LSCs and normal bone marrow HSCs gene expression profiles of GSE11889 and GSE11675 from the GEO database. GSE11889 data is based on the GPL571 ([HG‐U133A_2] Affymetrix Human Genome U133A 2.0 Array) platform, including seven CML patient marrow LSCs and five normal bone marrow HSCs (Submission date Jun 26, 2008). GSE11675 data is based on the GPL8300 ([HG_U95Av2] Affymetrix Human Genome U95 Version 2 Array) platform, including three CML patient marrow LSCs and three normal bone marrow HSCs (Submission date 4 Jun 2008). We selected these two microarray datasets for comprehensive analysis; both groups were based on gene expression profiles of HSC in the bone marrow. We used the GEO2R online analysis tool identify statistically significant DEGs between CML patient marrow LSCs and normal bone marrow HSCs. Statistically significant DEGs were defined as p < .05 and [logFC] > 1 as the cut‐off criteria.
Venny 2.0.2 (http://bioinfogp.cnb.csic.es/tools/venny/index2.0.2.html) is a free online website. To enhance the accuracy of the research results, we screened out common DEGs of two high‐throughput microarray databases using Venny 2.0.2.
Li H., Liu L., Zhuang J., Liu C., Zhou C., Yang J., Gao C., Liu G, & Sun C. (2019). Identification of key candidate targets and pathways for the targeted treatment of leukemia stem cells of chronic myelogenous leukemia using bioinformatics analysis. Molecular Genetics & Genomic Medicine, 7(9), e851.
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7

TWEAK-induced NFκB signaling in DU145/RasB1 cells

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DU145/RasB1 cells were treated with TWEAK (25ng/mL, R&D Systems, Minneapolis, MN, USA) for 60 min. Total RNA was extracted using mirVana Isolation Kit (Thermo Fisher Scientific, Waltham, MA, USA). After TWEAK treatment, samples were validated for increased expression levels of known NFκB target genes, IL8 and IκBα, and submitted for microarray analysis. Microarray analysis was performed with Affymetrix Human Genome U133A 2.0 Array. Fold changes in gene expression were determined by ANOVA using Partek Genomics Suite (Partek, Chesterfield, MO, USA).
Li L., Ameri A.H., Wang S., Jansson K.H., Casey O.M., Yang Q., Beshiri M.L., Fang L., Lake R.G., Agarwal S., Alilin A.N., Xu W., Yin J, & Kelly K. (2019). EGR1 Regulates Angiogenic and Osteoclastogenic Factors in Prostate Cancer and Promotes Metastasis. Oncogene, 38(35), 6241-6255.
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8

Microarray Analysis of MCF-7 Cell Lines

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The microarray analysis was carried out at the Genomics Core of the Tufts Center for Neuroscience Research, Tufts University School of Medicine. MCF-7 and MCF-7/PAR1 cells were quiesced overnight in serum-free media and RNA was isolated using the RNEasy kit (Qiagen). Target RNAs from each cell line (MCF-7, MCF-7/PAR1; n = 3) were fragmented and independently hybridized to Human Genome U133A 2.0 Array (Affymetrix, Santa Clara, CA, USA). Genechips were then washed and stained with Streptavidin R-phycoerythrin (Molecular Probes) and following washes, were scanned using the GeneChip scanner. Data analysis was conducted using the Bioconductor suite of programs. The 3’/5’ RNA degradation plot was used to confirm the quality of the RNA samples hybridized to microarrays. Background correction, normalization and summarization of the raw probe intensities were carried out using the GCRMA protocol with default options. LIMMA module and topTable function was used to generate the list of differentially expressed genes. TIGR Multiexperiment Viewer (MeV) was used for statistical analysis and heatmap production. Expression data were deposited in the Gene Expression Omnibus (GEO).
Yang E., Cisowski J., Nguyen N., O’Callaghan K., Xu J., Agarwal A., Kuliopulos A, & Covic L. (2015). Dysregulated protease activated receptor 1 (PAR1) promotes metastatic phenotype in breast cancer through HMGA2. Oncogene, 35(12), 1529-1540.
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9

Radiogenomic Analysis of Breast Cancer

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Two microarray datasets of GSE59732 (Affymetrix GPL571 platform, Affymetrix Human Genome U133A 2.0 Array) and GSE59733 (GPL18990 platform, Affymetrix Human Almac Xcel Array) were obtained from the GEO database. The samples in the MCF7 cell line (GSM1444569–GSM1444574) and ZR751 cell line (GSM1444563–GSM1444568) under the treatment of 0 and 5 Gy were employed for the analysis of DEGs were chosen from the GSE59732 dataset. The dataset GSE59733 contained gene expression profiles of the paired tumor samples from 18 breast cancer patients pre-radiotherapy (GM1444655–GSM1444657, GSM1444659–GSM1444664) and post-radiotherapy (GSM1444653, GSM1444654, GSM1444658, GSM1444666, GSM1444668–GSM1444671).
Zhao X., Liu X., Hu S., Pan Y., Zhang J., Tai G, & Shao C. (2022). GDF15 Contributes to Radioresistance by Mediating the EMT and Stemness of Breast Cancer Cells. International Journal of Molecular Sciences, 23(18), 10911.
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10

Comparative Gene Expression in ESCC

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Data from public databases were used in this study to analyze gene expression in patients with esophageal squamous cell carcinoma and healthy/control patients. GSE20347 and GSE75241 datasets were downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/geo/ (accessed on 1 July 2020)). The GSE20347 dataset is based on the GPL571 platform ( [HG-U133A_2] Affymetrix Human Genome U133A 2.0 Array), while the GSE75241 dataset is based on the GPL5175 platform ([HuEx-1_0-st] Affymetrix Human Exon 1.0 ST Array [transcript (gene) version]). The array data for GSE20347 include 17 esophageal squamous cells and their matched normal tissues as control. The GSE75241 dataset include 15 esophageal squamous cell carcinoma samples and 15 non-malignant mucosal samples. In addition to these, in order to obtain a sufficient number of ESCC samples, we also obtained 80 ESCC samples and 79 normal control tissues to be compared against them from The Cancer Genome Atlas (TCGA) using the USCS Refseq Gene Array (https://www.gtexportal.org/ (accessed on 2 July 2020)) and 1 adjacent non-tumor tissue sample (https://tcga-data.nci.nih.gov/tcga/ (accessed on 2 July 2020)).
Cui M.Y., Yi X., Zhu D.X, & Wu J. (2022). Identification of Differentially Expressed Genes Related to the Lipid Metabolism of Esophageal Squamous Cell Carcinoma by Integrated Bioinformatics Analysis. Current Oncology, 30(1), 1-18.
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