Refinement of breast cancer risk prediction with concordant leading edge subsets from prognostic gene signatures

The extended concurrent genes signature for disease-free survival in breast cancer

BACKGROUND/PURPOSE

Previously we had identified concurrent genes, which highlighted the interplay between copy number variation (CNV) and differential gene expression (GE) for Han Chinese breast cancers. The merit of the approach is to discovery biomarkers not identifiable by conventional GE only data, for which phenotype-correlation or gene variability is the criteria of gene selection.

MATERIALS AND METHODS

Thirty-one comparative genomic hybridization (CGH) and 83 GE microarrays were performed, with 29 breast cancers assayed from both platforms. Potential targets were revealed by Genomic Identification of Significant Targets in Cancer (GISTIC) from CGH arrays. Concurrent genes and genes with significant GISTIC scores were used to derive the extended concurrent genes signature, which was consensus from leading edge analysis across all studies and a supervised partial least square (PLS) regression predictive model of disease-free survival was constructed.

RESULTS

There were 1584 concurrent genes from 29 samples with both CGH and GE microarrays. Enriched concurrent genes sets for disease-free survival were identified independently from 83 GE arrays and another one with Han Chinese origin as well as three studies of Western origin. For five studies with disease-free survival follow up, prognostic discrepancy was observed between predicted high-risk and low-risk group patients.

CONCLUSION

We concluded that through parallel analyses of CGH and GE microarrays, the proposed extended concurrent gene expression signature can identify biomarkers with prognostic values.

Residual risk stratification of Taiwanese breast cancers following curative therapies with the extended concurrent genes signature

INTRODUCTION

The aim of the study was to perform digital RNA counting to validate a gene expression signature for operable breast cancers initially treated with curative intention, and the risk of recurrence, distant metastasis, and mortality was predicted.

METHODS

Candidate genes were initially discovered from the coherent genomic and transcriptional alternations from microarrays, and the extended concurrent genes were used to build a risk stratification model from archived formalin-fixed paraffin-embedded (FFPE) tissues with the NanoString nCounter.

RESULTS

The extended concurrent genes signature was prognostic in 144 Taiwanese breast cancers (5-year relapse-free survival: 89.8 and 69.4% for low- and high-risk group, log-rank test: P = 0.004). Cross-platform comparability was evidenced from significant and positive correlations for most genes as well as equal covariance matrix across 64 patients assayed for both microarray and digital RNA counting.

DISCUSSION

Archived FFPE samples could be successfully assayed by the NanoString nCounter. The purposed signature was prognostic stratifying breast cancer patients into groups with distinct survival patterns, and clinical applicability of the residual risk model was proved.

The long non-coding RNA EPB41L4A-AS2 inhibits tumor proliferation and is associated with favorable prognoses in breast cancer and other solid tumors

EPB41L4A-AS2 is a novel long non-coding RNA of unknown function. In this study, we investigated the expression of EPB41L4A-AS2 in breast cancer tissues and evaluated its relationship with the clinicopathological features and prognosis of patients with breast cancer. This entailed conducting a meta-analysis and prognosis validation study using two cohorts from the Gene Expression Omnibus (GEO). In addition, we assessed EPB41L4A-AS2 expression and its relationship with the clinicopathological features of renal and lung cancers using the Cancer Genome Atlas cohort and a GEO dataset. We also clarified the role of EPB41L4A-AS2 expression in mediating cancer cell proliferation in breast, renal, and lung cancer cell lines transfected with an EPB41L4A-AS2 expression vector. We found that high EPB41L4A-AS2 expression is associated with favorable disease outcomes. Gene ontology enrichment analysis revealed that EPB41L4A-AS2 may be involved in processes associated with tumor biology. Finally, overexpression of EPB41L4A-AS2 inhibited tumor cell proliferation in breast, renal, and lung cancer cell lines. Our clinical and in vitro results suggest that EPB41L4A-AS2 inhibits solid tumor formation and that evaluation of this long non-coding RNA may have prognostic value in the clinical management of such malignancies.