Data Aggregation at the Level of Molecular Pathways Improves Stability of Experimental Transcriptomic and Proteomic Data

Abstract

High throughput technologies opened a new era in biomedicine by enabling massive analysis of gene expression at both RNA and protein levels. Unfortunately, expression data obtained in different experiments are often poorly compatible, even for the same biological samples. Here, using experimental and bioinformatic investigation of major experimental platforms, we show that aggregation of gene expression data at the level of molecular pathways helps to diminish cross- and intra-platform bias otherwise clearly seen at the level of individual genes. We created a mathematical model of cumulative suppression of data variation that predicts the ideal parameters and the optimal size of a molecular pathway. We compared the abilities to aggregate experimental molecular data for the five alternative methods, also evaluated by their capacity to retain meaningful features of biological samples. The bioinformatic method OncoFinder showed optimal performance in both tests and should be very useful for future cross-platform data analyses.

RNA sequencing profiles and diagnostic signatures linked with response to ramucirumab in gastric cancer

“…Similarly, we performed DESeq2 differential gene expression analysis for all genes forming this pathway (Table 4). For all individual genes, the expression differences did not reach p<0.05 significance threshold, thus confirming previous findings on superior robustness of molecular pathways as cancer biomarkers (Borisov et al 2014, Borisov et al 2017, Ozerov et al 2016).…”

DNA repair pathway activation features in follicular and papillary thyroid tumors, interrogated using 95 experimental RNA sequencing profiles

“…DNA repair has dual significance by simultaneously slowing down tumor evolution but also by protecting tumor cells from the treatment of replication targeting therapeutics. Thus, controlled inhibition of DNA repair activities can be considered personalized therapeutic option [81,82]. On the other hand, we found no differential DNA repair pathways between radioiodine resistant and sensitive tumor samples.…”

“…The gene structures and molecular architectures of 38 DNA repair pathways were obtained from the public databases Reactome [40], NCI Pathway Interaction Database [41], Kyoto Encyclopedia of Genes and Genomes [42], Biocarta [43], and Qiagen [44], and manually curated as described in [81]. Only molecular pathways which include ten or more genes [82] were considered in calculations of pathway activation level (PAL) in order to increase statistical accuracy.…”

Human blood serum can donor-specifically antagonize effects of EGFR-targeted drugs on squamous carcinoma cell growth

“…This method of PAL calculation was shown to suppress the batch effects in various series of gene expression measurement experiments [33], and to minimize the errors introduced by the high-throughput methods of transcriptome analysis [34,35]. PAL's absolute value reflects the strength of a pathway perturbation, and a positive or negative value indicates pathway activation or downregulation, respectively [32,36].…”