Jetset: selecting the optimal microarray probe set to represent a gene
Qiyuan Li,Nicolai Juul Birkbak,Balazs Gyorffy,Zoltan Szallasi,Zoltan Szallasi,Aron Charles Eklund +5 more
TLDR
This method provides a simple, unambiguous mapping to allow assessment of the expression levels of specific genes of interest and evaluated concordance between protein measurements and gene expression values.Abstract:
Background: Interpretation of gene expression microarrays requires a mapping from probe set to gene. On many Affymetrix gene expression microarrays, a given gene may be detected by multiple probe sets, which may deliver inconsistent or even contradictory measurements. Therefore, obtaining an unambiguous expression estimate of a pre-specified gene can be a nontrivial but essential task. Results: We developed scoring methods to assess each probe set for specificity, splice isoform coverage, and robustness against transcript degradation. We used these scores to select a single representative probe set for each gene, thus creating a simple one-to-one mapping between gene and probe set. To test this method, we evaluated concordance between protein measurements and gene expression values, and between sets of genes whose expression is known to be correlated. For both test cases, we identified genes that were nominally detected by multiple probe sets, and we found that the probe set chosen by our method showed stronger concordance. Conclusions: This method provides a simple, unambiguous mapping to allow assessment of the expression levels of specific genes of interest.read more
Citations
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Inconsistency in large pharmacogenomic studies
Benjamin Haibe-Kains,Nehme El-Hachem,Nicolai Juul Birkbak,Andrew C. Jin,Andrew H. Beck,Hugo J.W.L. Aerts,John Quackenbush +6 more
TL;DR: Genomic data are well correlated between studies; however, the measured drug response data are highly discordant, which has potential implications for using these outcome measures to assess gene–drug associations or select potential anticancer drugs on the basis of their reported results.
Journal ArticleDOI
Telomeric Allelic Imbalance Indicates Defective DNA Repair and Sensitivity to DNA-Damaging Agents
Nicolai Juul Birkbak,Nicolai Juul Birkbak,Zhigang C. Wang,Zhigang C. Wang,Ji Young Kim,Aron Charles Eklund,Qiyuan Li,Qiyuan Li,Ruiyang Tian,Christian Bowman-Colin,Yang Li,April Greene-Colozzi,J. Dirk Iglehart,J. Dirk Iglehart,Nadine Tung,Paula D. Ryan,Judy Garber,Daniel P. Silver,Daniel P. Silver,Zoltan Szallasi,Zoltan Szallasi,Andrea L. Richardson,Andrea L. Richardson +22 more
TL;DR: NtAI, a genomic measure of unfaithfully repaired DNA, may identify cancer patients likely to benefit from treatments targeting defective DNA repair, and suggests impaired DNA repair in patients treated with platinum-based chemotherapy.
Journal ArticleDOI
Stemness of the hybrid Epithelial/Mesenchymal State in Breast Cancer and Its Association with Poor Survival.
Anne Grosse-Wilde,Aymeric Fouquier d'Hérouël,Ellie McIntosh,Gökhan Ertaylan,Alexander Skupin,Rolf E. Kuestner,Antonio del Sol,Kathie-Anne Walters,Sui Huang +8 more
TL;DR: The data support a novel model that links a mixed EM signature with stemness in individual cells, luminal and basal cell lines, in vivo xenograft mouse models, and in all breast cancer subtypes and suggest that targeting E/M heterogeneity by eliminating hybrid E-M cells and cooperation between E and M cell-types could improve breast cancer patient survival independent of breast cancer-subtype.
Journal ArticleDOI
Survival analysis across the entire transcriptome identifies biomarkers with the highest prognostic power in breast cancer
TL;DR: In this article, a reference ranking of all survival related genes in chemotherapy treated basal and estrogen positive/HER2 negative breast cancer was presented, and the results help to neglect those with unlikely clinical significance and focus future research on the most promising candidates.
Journal ArticleDOI
TNMplot.com: A Web Tool for the Comparison of Gene Expression in Normal, Tumor and Metastatic Tissues.
Áron Bartha,Balázs Győrffy +1 more
TL;DR: In this article, the authors established an integrated database using available transcriptome-level datasets and created a web platform which enables the mining of this database by comparing normal, tumor and metastatic data across all genes in real time.
References
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