ArticleScientific reports2017
Molecular Classification of Lobular Carcinoma of the Breast.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- Article
- BC-predict: mining of signal biomarkers and production of models for early-stage breast cancer subtyping and prognosis.Frontiers in bioinformatics · 2025Article
- Daidzein Inhibits Non-small Cell Lung Cancer Growth by Pyroptosis.Current pharmaceutical design · 2025Article
- The combined signatures of the tumour microenvironment and nucleotide metabolism-related genes provide a prognostic and therapeutic biomarker for gastric cancer.Scientific reports · 2023Article
- Uterine metastasis of lobular breast carcinoma under tamoxifen therapy: A case report.Molecular and clinical oncology · 2021Article
- A nomogram for determining the disease-specific survival in invasive lobular carcinoma of the breast: A population study.Medicine · 2020Article
- Applications of single cell RNA sequencing to research of stem cells.World journal of stem cells · 2019Article
- Feature Selection for Longitudinal Data by Using Sign Averages to Summarize Gene Expression Values over Time.BioMed research international · 2019Article
- Invasive lobular and ductal breast carcinoma differ in immune response, protein translation efficiency and metabolism.Scientific reports · 2018Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The morphology of breast tumors is complicated and diagnosis can be difficult. We present here a novel diagnostic model which we validate on both array-based and RNA sequencing platforms which reliably distinguishes this tumor type across multiple cohorts. We also examine how this molecular classification predicts sensitivity to common chemotherapeutics in cell-line based assays. A total of 1845 invasive breast cancer cases in six cohorts were collected, split into discovery and validation cohorts, and a classifier was created and compared to pathological diagnosis, grade and survival. In the validation cohorts the concordance of predicted diagnosis with a pathological diagnosis was 92%, and 97% when inconclusively classified cases were excluded. Tumor-derived cell lines were classified with the model as having predominantly ductal or lobular-like molecular physiologies, and sensitivity of these lines to relevant compounds was analyzed. A diagnostic tool can be created that reliably distinguishes lobular from ductal carcinoma and allows the classification of cell lines on the basis of molecular profiles associated with these tumor types. This tool may assist in improved diagnosis and aid in explorations of the response of lobular type breast tumor models to different compounds.
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