MOESM6 of Automated identification of reference genes based on RNA-seq data

Additional file 6. Best candidate RGs for normal and malignant lung samples according to Fig. 6b, ranked by CV. They were obtained with CV < 20% and minimum counted reads of 10,000. Transcript_id: human transcript identifiers in ENSEMBL database

MOESM2 of Automated identification of reference genes based on RNA-seq data

Additional file 2. Best RGs in olive tree pistil according to Fig. 2a, ranked by CV. They were obtained for different stages of pistil development with CV < 10% and minimum counted reads of 100. Transcript_id: transcript identifiers in the ReprOlive transcriptome

A microRNA Signature Associated with Early Recurrence in Breast Cancer

<div><p>Recurrent breast cancer occurring after the initial treatment is associated with poor outcome. A bimodal relapse pattern after surgery for primary tumor has been described with peaks of early and late recurrence occurring at about 2 and 5 years, respectively. Although several clinical and pathological features have been used to discriminate between low- and high-risk patients, the identification of molecular biomarkers with prognostic value remains an unmet need in the current management of breast cancer. Using microarray-based technology, we have performed a microRNA expression analysis in 71 primary breast tumors from patients that either remained disease-free at 5 years post-surgery (group A) or developed early (group B) or late (group C) recurrence. Unsupervised hierarchical clustering of microRNA expression data segregated tumors in two groups, mainly corresponding to patients with early recurrence and those with no recurrence. Microarray data analysis and RT-qPCR validation led to the identification of a set of 5 microRNAs (the 5-miRNA signature) differentially expressed between these two groups: miR-149, miR-10a, miR-20b, miR-30a-3p and miR-342-5p. All five microRNAs were down-regulated in tumors from patients with early recurrence. We show here that the 5-miRNA signature defines a high-risk group of patients with shorter relapse-free survival and has predictive value to discriminate non-relapsing versus early-relapsing patients (AUC = 0.993, p-value<0.05). Network analysis based on miRNA-target interactions curated by public databases suggests that down-regulation of the 5-miRNA signature in the subset of early-relapsing tumors would result in an overall increased proliferative and angiogenic capacity. In summary, we have identified a set of recurrence-related microRNAs with potential prognostic value to identify patients who will likely develop metastasis early after primary breast surgery.</p></div

Most significant deregulated miRNAs in breast tumors from relapsing patients.

#<p>Group A  =  no recurrence, Group B  =  early recurrence (≤24 months after surgery), Group C  =  late recurrence (50–60 months after surgery).</p><p><i>*limma F</i>, analysis of filtered data (sd>70%) using limma.</p><p>**<i>RankProd</i>, analysis of unfiltered data using RankProduct algorithm.</p><p>***<i>RT-qPCR</i>, Relative miRNA expression was calculated using the ΔΔC_t method. The standard error (SE) was calculated based on the theory of error propagation <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091884#pone.0091884-Quackenbush1" target="_blank">[107]</a>.</p

A 5-miRNA signature is associated with early recurrence in breast cancer.

<p>Hierarchical clustering of the 71 tumor samples based on expression of the 5-miRNA signature. Note that lower expression levels of the 5-miRNA signature defines a distinct cluster 2b wich mainly includes tumors from “high risk” patients (group B). On the contrary, most patients with good prognosis (group A) had tumors with normal or higher-than normal levels of the 5-miRNA signature, defining a different cluster 1b (“low risk”).</p

The 5-miRNA signature discriminates patients with diferent RFS.

<p><b>A</b>) Kaplan-Meier graph for the whole patient cohort included in this study. <b>B</b>) Those patients whose tumors showed an overall down-regulation of the 5-miRNA signature (i.e. those from cluster 2b in Fig. 2) were classified as “high risk” (red line) and their cumulative RFS was calculated (red line). RFS was also calculated for the remaining patients in the cohort (“low risk”, black line). The Kaplan-Meier plot shows that the 5-miRNA signature specifically discriminates tumors with an overall higher risk of early recurrence.</p

Receiver operating characteristic curve (ROC) for early breast cancer recurrence by the 5-miRNA signature status.

<p>ROC curves generated using the prognosis information and expression levels of the 5-miRNA signature can discriminate between patients who will develop early recurrence and those who will remain free of disease. Note that, although miR-30-3p and miR10a, individually have a high area under the curve (AUC) score, the 5-miRNA signature has the strongest predictive value (AUC = 0.993) to discriminate those patients likely to recur early (group B in our cohort).</p

Patients with a higher risk of relapse have tumors with increased proliferative capacitity.

<p>The angiogenic (VEGF), proliferative (Ki67) and hormone receptor (ER) status of the primary breast tumors were assessed by immunohistochemistry with specific antibodies. Interpretation of the immunohistochemical signal (low/high for VEGF and positive/negative for Ki67 and ER) followed the criteria specified in the methods section. Patients were classified according to the VEGF, Ki67 and ER status of their tumors and the cumulative RFS was calculated. The Kaplan-Meier plots show a reduced RFS in patients with tumors highly positive por VEGF, positive for Ki67 and negative for ER, although the differences were only statistically significant for Ki67 (Log-rank P = 0.044). All 71 tumors included in this study were processed for Ki67 and ER staining while only 67 could be processed for VEGF staining.</p

Gene Ontology (GO) terms associated with the predicted mRNA targets of the 5-miRNA signature.

<p>A GO term analysis was performed using terms of the “biological process” vocabulary. Shown are the GO identification number (GO ID), the name of the biological process (GO term) and the mRNA targets associated to each particular GO term. Only term ontologies with experimental evidence and corrected p-value≤0.01 are shown.</p

MicroRNA expression profiles in primary breast tumors from patients with different prognosis.

<p>Total RNA was obtained from 71 breast tumors, converted to cDNA and hybridized to Affymetrix miRNA Chip Array 2.0. After normalization, differential miRNA expression data was analysed by unsupervised hierarchical clustering. Color bars on top of the heatmap refer to the prognostic group and intrinsic subtype of each tumor. Group A included tumors from patients who were disease-free ≥60 months after surgery, group B included tumors from early-relapsing patients (≤24 months) and group C included tumors from late-relapsin patients (50–60 months after surgery). Tumors grouped in two main clusters (cluster 1 and cluster 2), showing opposite expression profiles and strongly associated with prognosis groups. Thus, cluster 1 included most luminal and/or non-relapsing tumors while cluster 2 mostly included basal-like and/or early-relapsing tumors.</p