ArticleBritish journal of cancer2018
An integrative bioinformatics approach reveals coding and non-coding gene variants associated with gene expression profiles and outcome in breast cancer molecular subtypes.
Article in British journal of cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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21 citing papers in PubMed, 32 citations in OpenAlex.
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- Genomic Alterations Affecting Competitive Endogenous RNAs (ceRNAs) and Regulatory Networks (ceRNETs) with Clinical Implications in Triple-Negative Breast Cancer (TNBC).International journal of molecular sciences · 2024Review
- Breast cancers with high proliferation and low ER-related signalling have poor prognosis and unique molecular features with implications for therapy.British journal of cancer · 2023Article
- The mutational landscape of a US Midwestern breast cancer cohort reveals subtype-specific cancer drivers and prognostic markers.Human genomics · 2023Article
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- Gene Expression Profiling in Early Breast Cancer-Patient Stratification Based on Molecular and Tumor Microenvironment Features.Biomedicines · 2022Review
- Non-Coding Variants in Cancer: Mechanistic Insights and Clinical Potential for Personalized Medicine.Non-coding RNA · 2021Review
- 6-lncRNA Assessment Model for Monitoring and Prognosis of HER2-Positive Breast Cancer: Based on Transcriptome Data.Pathology oncology research : POR · 2021Article
- Upregulation of CIP2A in estrogen depletion-resistant breast cancer cells treated with low-dose everolimus.FEBS open bio · 2020Article
- An immune-related prognostic signature for predicting breast cancer recurrence.Cancer medicine · 2020Article
- Differential Allele-Specific Expression Uncovers Breast Cancer Genes Dysregulated by Cis Noncoding Mutations.Cell systems · 2020Article
- Comprehensive Outline of Whole Exome Sequencing Data Analysis Tools Available in Clinical Oncology.Cancers · 2019Review
- GSIAR: gene-subcategory interaction-based improved deep representation learning for breast cancer subcategorical analysis using gene expression, applicable for precision medicine.Medical & biological engineering & computing · 2019Article
- Identification of key genes and pathways downstream of the β-catenin-TCF7L1 complex in pancreatic cancer cells using bioinformatics analysis.Oncology letters · 2019Article
- Transcriptional regulation of normal human mammary cell heterogeneity and its perturbation in breast cancer.The EMBO journal · 2019Review
- Prospective molecular mechanism of COL5A1 in breast cancer based on a microarray, RNA sequencing and immunohistochemistry.Oncology reports · 2019Article
- PopNetD3-A Network-Based Web Resource for Exploring Population Structure.Genome biology and evolution · 2019Article
- Identification of a 4-mRNA metastasis-related prognostic signature for patients with breast cancer.Journal of cellular and molecular medicine · 2019Article
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Authors and funding
9 authors at 5 institutions in 4 countries.
Funding
Abstract
backgroundSequence variations in coding and non-coding regions of the genome can affect gene expression and signalling pathways, which in turn may influence disease outcome.
methodsIn this study, we integrated somatic mutations, gene expression and clinical data from 930 breast cancer patients included in the TCGA database. Genes associated with single mutations in molecular breast cancer subtypes were identified by the Mann-Whitney U-test and their prognostic value was evaluated by Kaplan-Meier and Cox regression analyses. Results were confirmed using gene expression profiles from the Metabric data set (n = 1988) and whole-genome sequencing data from the TCGA cohort (n = 117).
resultsThe overall mutation rate in coding and non-coding regions were significantly higher in ER-negative/HER2-negative tumours (P = 2.8E-03 and P = 2.4E-07, respectively). Recurrent sequence variations were identified in non-coding regulatory regions of several cancer-associated genes, including NBPF1, PIK3CA and TP53. After multivariate regression analysis, gene signatures associated with three coding mutations (CDH1, MAP3K1 and TP53) and two non-coding variants (CRTC3 and STAG2) in cancer-related genes predicted prognosis in ER-positive/HER2-negative tumours.
conclusionsThese findings demonstrate that sequence alterations influence gene expression and oncogenic pathways, possibly affecting the outcome of breast cancer patients. Our data provide potential opportunities to identify non-coding variations with functional and clinical relevance in breast cancer.
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