Normalization strategies for mRNA expression data in cartilage research

11594 Background: FOLFIRI as adjuvant treatment in primary colon cancer was previously tested in two pivotal prospective randomized clinical trials (PETACC-3 and CALGB 89803), both of which failed to demonstrate significant beneficial effects when adding irinotecan to 5FU. As a consequence, FOLFIRI is presently not used as adjuvant treatment for colon cancer. Methods: The study included 580 patients with mRNA expression data performed on tumor samples (FFPE) from stage III colon cancer patients enrolled in the PETACC-3 study, which randomized the patients to 5FU plus Leucovorin +/- irinotecan. Primary end-points were recurrence-free survival (RFS) and overall survival (OS). Median ABCG2 and the 75 percentile TOP-1 mRNA expression data were used to allocate the patients into one of two groups: One with high ABCG2 expression (above median) and low TOP-1 expression (below 75 percentile) (n = 167) and another group including all other combinations of these two genes. Kaplan Meier curves and Cox proportional hazards model were used to visualize differences between groups and calculate p-values (log-rank test). Results: The survival statistics showed a significant difference for both RFS (HR: 0.63 (0.44-0.92); p = 0.017) and OS (HR: 0.6 (0.39-0.93); p = 0.021) between the two groups when the patients received FOLFIRI. In contrast, no significant differences were observed between the groups when patients received 5FU and Leucovorin alone (p-values: RFS: 0.58; OS: 0.75). Conclusions: We here show that the combination of two independent gene expression abundance with a strong association to irinotecan treatment (high ABCG2 drug efflux pump and low TOP-1, the latter being the target for irinotecan) identified a group of stage III colon cancer patients who will not benefit from FOLFIRI adjuvant treatment while patients with other combinations of expression of these two genes appear to significantly benefit from adjuvant FOLFIRI treatment. The lack of a similar effect in patients receiving treatment with 5FU and Leucovorin only, points to a predictive value of ABCG2 and TOP-1 measurements.

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A Bayesian Framework to Improve MicroRNA Target Prediction by Incorporating External Information

Cancer Informatics ◽

10.4137/cin.s16348 ◽

2014 ◽

Vol 13s7 ◽

pp. CIN.S16348 ◽

Cited By ~ 1

Author(s):

Zixing Wang ◽

Wenlong Xu ◽

Haifeng Zhu ◽

Yin Liu

Keyword(s):

Liver Cancer ◽

Mrna Expression ◽

Target Prediction ◽

Bayesian Framework ◽

External Information ◽

Sequence Information ◽

Expression Data ◽

Microrna Target ◽

Mrna Expression Data ◽

Mirna Targets

MicroRNAs (miRNAs) are small regulatory RNAs that play key gene-regulatory roles in diverse biological processes, particularly in cancer development. Therefore, inferring miRNA targets is an essential step to fully understanding the functional properties of miRNA actions in regulating tumorigenesis. Bayesian linear regression modeling has been proposed for identifying the interactions between miRNAs and mRNAs on the basis of the integrated sequence information and matched miRNA and mRNA expression data; however, this approach does not use the full spectrum of available features of putative miRNA targets. In this study, we integrated four important sequence and structural features of miRNA targeting with paired miRNA and mRNA expression data to improve miRNA-target prediction in a Bayesian framework. We have applied this approach to a gene-expression study of liver cancer patients and examined the posterior probability of each miRNA-mRNA interaction being functional in the development of liver cancer. Our method achieved better performance, in terms of the number of true targets identified, than did other methods.

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Polar Mapper: a computational tool for integrated visualization of protein interaction networks and mRNA expression data

Nature Precedings ◽

10.1038/npre.2008.2663.1 ◽

2008 ◽

Author(s):

Joana P. Gonçalves ◽

Mário Grãos ◽

Andre Valente

Keyword(s):

Mrna Expression ◽

Protein Interaction ◽

Protein Interaction Networks ◽

Interaction Networks ◽

Expression Data ◽

Computational Tool ◽

Mrna Expression Data

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ABCG2 and TOP1 mRNA expression as predictive biomarkers for adjuvant FOLFIRI treatment in stage III colon cancer patients: Results from the PETAAC-3 prospective randomized clinical trial.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.4_suppl.591 ◽

2017 ◽

Vol 35 (4_suppl) ◽

pp. 591-591 ◽

Cited By ~ 2

Author(s):

Nils Brunner ◽

Sune Boris Nygaard ◽

Eva Budinska ◽

Jan Stenvang

Keyword(s):

Colon Cancer ◽

Mrna Expression ◽

Cancer Patients ◽

Adjuvant Treatment ◽

Randomized Clinical Trials ◽

Stage Iii ◽

Expression Data ◽

Mrna Expression Data ◽

Stage Iii Colon Cancer ◽

Significant Difference

591 Background: FOLFIRI as adjuvant treatment in primary colon cancer was previously tested in two pivotal prospective randomized clinical trials (PETACC-3 and CALGB 89803), both of which failed to demonstrate significant beneficial effects when adding irinotecan to 5FU. As a consequence, FOLFIRI is presently not used as adjuvant treatment for colon cancer. Methods: The study included 580 patients with mRNA expression data performed on tumor samples (FFPE) from stage III colon cancer patients enrolled in the PETACC-3 study, which randomized the patients to 5FU plus Leucovorin +/- irinotecan. Primary end-points were disease free survival (DFS) and overall survival (OS). Median ABCG2 and the 75 percentile TOP-1 mRNA expression data were used to allocate the patients into one of two groups: One with high ABCG2 expression (above median) and low TOP-1 expression (below 75 percentile) (n = 167) and another group including all other combinations of these two genes. Kaplan Meier curves and Cox proportional hazards model were used to visualize differences between groups and calculate p-values (log-rank test). Results: The survival statistics showed a significant difference for both RFS (HR: 0.63 (0.44-0.92); p = 0.017) and OS (HR: 0.6 (0.39-0.93); p = 0.021) between the two groups when the patients received FOLFIRI. In contrast, no significant differences were observed between the groups when patients received 5FU and Leucovorin alone (RFS: 0.58; OS: 0.75). Conclusions: We here show that the combination of two independent gene expression abundance with a strong association to irinotecan treatment (high ABCG2 drug efflux pump and low TOP-1, which is the target for irinotecan) identified a group of stage III colon cancer patients who will not benefit from FOLFIRI adjuvant treatment while patients with other combinations of expression of these two genes appear to significantly benefit from adjuvant FOLFIRI treatment. The lack of a similar effect in patients receiving treatment with 5FU and Leucovorin only, points to a predictive value of ABCG2 and TOP-1 measurements.

Download Full-text