ArticleOncotarget2015
Genome and transcriptome delineation of two major oncogenic pathways governing invasive ductal breast cancer development.
Article in Oncotarget, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 45 citations in OpenAlex.
- Article
- Exploring the molecular mechanisms of comorbidity between thyroid cancer and breast cancer through multi-omics data.Scientific reports · 2025Article
- KDM7A-DT induces genotoxic stress, tumorigenesis, and progression of p53 missense mutation-associated invasive breast cancer.Frontiers in oncology · 2024Article
- The clinical and genetic features in patients coexisting primary breast and thyroid cancers.Frontiers in endocrinology · 2023Article
- Understanding Breast Cancers through Spatial and High-Resolution Visualization Using Imaging Technologies.Cancers · 2022Review
- Article
- ABI1-based expression signature predicts breast cancer metastasis and survival.Molecular oncology · 2022Article
- Decision Theory versus Conventional Statistics for Personalized Therapy of Breast Cancer.Journal of personalized medicine · 2022Article
- Decision theory for precision therapy of breast cancer.Scientific reports · 2021Article
- Lipidomics investigations into the tissue phospholipidomic landscape of invasive ductal carcinoma of the breast.RSC advances · 2020Article
- Elevated mRNA expression levels of DLGAP5 are associated with poor prognosis in breast cancer.Oncology letters · 2020Article
- A qualitative transcriptional signature to reclassify histological grade of ER-positive breast cancer patients.BMC genomics · 2020Article
- Screening of core genes and pathways in breast cancer development via comprehensive analysis of multi gene expression datasets.Oncology letters · 2019Article
- Decreased methylation in the SNAI2 and ADAM23 genes associated with de-differentiation and haematogenous dissemination in breast cancers.BMC cancer · 2018Article
- Comprehensive integrated analysis of gene expression datasets identifies key anti-cancer targets in different stages of breast cancer.Experimental and therapeutic medicine · 2018Article
- Gene expression information improves reliability of receptor status in breast cancer patients.Oncotarget · 2017Article
- Transposon insertional mutagenesis in mice identifies human breast cancer susceptibility genes and signatures for stratification.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
- Comprehensive tissue-specific gene set enrichment analysis and transcription factor analysis of breast cancer by integrating 14 gene expression datasets.Oncotarget · 2017Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Invasive ductal carcinoma (IDC) is a major histo-morphologic type of breast cancer. Histological grading (HG) of IDC is widely adopted by oncologists as a prognostic factor. However, HG evaluation is highly subjective with only 50%-85% inter-observer agreements. Specifically, the subjectivity in the assignment of the intermediate grade (histologic grade 2, HG2) breast cancers (comprising ~50% of IDC cases) results in uncertain disease outcome prediction and sub-optimal systemic therapy. Despite several attempts to identify the mechanisms underlying the HG classification, their molecular bases are poorly understood.We performed integrative bioinformatics analysis of TCGA and several other cohorts (total 1246 patients). We identified a 22-gene tumor aggressiveness grading classifier (22g-TAG) that reflects global bifurcation in the IDC transcriptomes and reclassified patients with HG2 tumors into two genetically and clinically distinct subclasses: histological grade 1-like (HG1-like) and histological grade 3-like (HG3-like). The expression profiles and clinical outcomes of these subclasses were similar to the HG1 and HG3 tumors, respectively. We further reclassified IDC into low genetic grade (LGG = HG1+HG1-like) and high genetic grade (HGG = HG3-like+HG3) subclasses. For the HG1-like and HG3-like IDCs we found subclass-specific DNA alterations, somatic mutations, oncogenic pathways, cell cycle/mitosis and stem cell-like expression signatures that discriminate between these tumors. We found similar molecular patterns in the LGG and HGG tumor classes respectively.Our results suggest the existence of two genetically-predefined IDC classes, LGG and HGG, driven by distinct oncogenic pathways. They provide novel prognostic and therapeutic biomarkers and could open unique opportunities for personalized systemic therapies of IDC patients.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.