bioRxivCancer Biology
NSMCE2, a Novel Super-Enhancer Regulated Gene, is Linked to Poor Prognosis and Therapy Resistance in Breast Cancer
C. Di Benedetto, J. Oh, Z. Choidhery, W. Shi, G. Valdes, P. Betancur
Abstract
In this study, we identified two novel super-enhancer associated genes: NSMCE2 and MAL2, highly upregulated in breast tumors, for which high RNA levels significantly and specifically correlate with breast cancer patients poor prognosis. To approach this, we took advantage of existing datasets containing super-enhancers associated genes identified in primary breast tumors and public databases comprising gene expression, genomic and clinical outcomes for patients diagnosed with breast cancer. Through in-vitro pharmacological super-enhancer disruption assays in breast cancer cells we confirmed that super-enhancers are involved in NSMCE2 and MAL2 transcript upregulation and through bioinformatics we found that high levels of NSMCE2 strongly associate with poor response to chemotherapy. This was observed especially for patients diagnosed with aggressive triple negative and HER2 positive tumor types. Finally, we showed that treating breast cancer cells with chemotherapeutic agents while simultaneously decreasing NSMCE2 gene expression by super-enhancer blockade or by directly silencing it, reduces cell viability thus increasing the effectiveness of chemotherapy. Our results indicate that moderating the transcript levels of the novel identified super-enhancer associated gene NSMCE2 could improve patients response to standard chemotherapy and, consequently, may improve disease outcome. In summary by mining existing public breast cancer datasets, our work demonstrates that searching for super-enhancer regulated genes and their association to patients survival and response to treatment, could be an effective method for identifying a signature of tumor specific -not frequently mutated, but super-enhancer dysregulated genes. Our approach offers a new avenue to identify novel biomarkers of poor prognosis and potential pharmacological targets for improving cancer treatment.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: drug response / drug discovery
- approach: biophysical modeling
- approach: statistical model
- approach: benchmark study
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