BackgroundCurrent normalization methods for RNA-sequencing data allow either for intersample comparison to identify differentially expressed (DE) genes or for intrasample comparison for the discovery and validation of gene signatures. Most studies on optimization of normalization methods typically use simulated data to validate methodologies. We describe a new method, GeTMM, which allows for both inter- and intrasample analyses with the same normalized data set. We used actual (i.e. not simulated) RNA-seq data from 263 colon cancers (no biological replicates) and used the same read count data to compare GeTMM with the most commonly used normalization methods (i.e. TMM (used by edgeR), RLE (used by DESeq2) and TPM) with respect to distributions, effect of RNA quality, subtype-classification, recurrence score, recall of DE genes and correlation to RT-qPCR data.ResultsWe observed a clear benefit for GeTMM and TPM with regard to intrasample comparison while GeTMM performed similar to TMM and RLE normalized data in intersample comparisons. Regarding DE genes, recall was found comparable among the normalization methods, while GeTMM showed the lowest number of false-positive DE genes. Remarkably, we observed limited detrimental effects in samples with low RNA quality.ConclusionsWe show that GeTMM outperforms established methods with regard to intrasample comparison while performing equivalent with regard to intersample normalization using the same normalized data. These combined properties enhance the general usefulness of RNA-seq but also the comparability to the many array-based gene expression data in the public domain.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2246-7) contains supplementary material, which is available to authorized users.

A recent comprehensive whole genome analysis of a large breast cancer cohort was used to link known and novel drivers and substitution signatures to the transcriptome of 266 cases. Here, we validate that subtypespecific aberrations show concordant expression changes for, for example, TP53, PIK3CA, PTEN, CCND1 and CDH1. We find that CCND3 expression levels do not correlate with amplification, while increased GATA3 expression in mutant GATA3 cancers suggests GATA3 is an oncogene. In luminal cases the total number of substitutions, irrespective of type, associates with cell cycle gene expression and adverse outcome, whereas the number of mutations of signatures 3 and 13 associates with immune-response specific gene expression, increased numbers of tumour-infiltrating lymphocytes and better outcome. Thus, while earlier reports imply that the sheer number of somatic aberrations could trigger an immune-response, our data suggests that substitutions of a particular type are more effective in doing so than others.

Circular RNAs (circRNAs) are a class of RNAs that is under increasing scrutiny, although their functional roles are debated. We analyzed RNA-seq data of 348 primary breast cancers and developed a method to identify circRNAs that does not rely on unmapped reads or known splice junctions. We identified 95,843 circRNAs, of which 20,441 were found recurrently. Of the circRNAs that match exon boundaries of the same gene, 668 showed a poor or even negative (R < 0.2) correlation with the expression level of the linear gene. In silico analysis showed only a minority (8.5%) of circRNAs could be explained by

Mutations and splice variants in the estrogen receptor (ER) gene, ESR1, may yield endocrine resistance in metastatic breast cancer (MBC) patients. These putative endocrine resistance markers are likely to emerge during treatment, and therefore, its detection in liquid biopsies, such as circulating tumor cells (CTCs) and cell‐free DNA (cfDNA), is of great interest. This research aimed to determine whether ESR1 mutations and splice variants occur more frequently in CTCs of MBC patients progressing on endocrine treatment. In addition, the presence of ESR1 mutations was evaluated in matched cfDNA and compared to CTCs. CellSearch‐enriched CTC fractions (≥5/7.5 mL) of two MBC cohorts were evaluated, namely (a) patients starting first‐line endocrine therapy (n = 43, baseline cohort) and (b) patients progressing on any line of endocrine therapy (n = 40, progressing cohort). ESR1 hotspot mutations (D538G and Y537S/N/C) were evaluated in CTC‐enriched DNA using digital PCR and compared with matched cfDNA (n = 18 baseline cohort; n = 26 progressing cohort). Expression of ESR1 full‐length and 4 of its splice variants (∆5, ∆7, 36 kDa, and 46 kDa) was evaluated in CTC‐enriched mRNA. It was observed that in the CTCs, the ESR1 mutations were not enriched in the progressing cohort (8%), when compared with the baseline cohort (5%) (P = 0.66). In the cfDNA, however, ESR1 mutations were more prevalent in the progressing cohort (42%) than in the baseline cohort (11%) (P = 0.04). Three of the same mutations were observed in both CTCs and cfDNA, 1 mutation in CTCs only, and 11 in cfDNA only. Only the ∆5 ESR1 splice variant was CTC‐specific expressed, but was not enriched in the progressing cohort. In conclusion, sensitivity for detecting ESR1 mutations in CTC‐enriched fractions was lower than for cfDNA. ESR1 mutations detected in cfDNA, rarely present at the start of first‐line endocrine therapy, were enriched at progression, strongly suggesting a role in conferring endocrine resistance in MBC.