ArticleGeburtshilfe und Frauenheilkunde2017
Predicting Triple-Negative Breast Cancer Subtype Using Multiple Single Nucleotide Polymorphisms for Breast Cancer Risk and Several Variable Selection Methods.
Article in Geburtshilfe und Frauenheilkunde, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 22 citations in OpenAlex.
- Predicting mammographic density with linear ultrasound transducers.European journal of medical research · 2023Article
- A novel serum extracellular vesicle protein signature to monitor glioblastoma tumor progression.International journal of cancer · 2023Article
- PD-L1 Gene Polymorphisms rs822336 G>C and rs822337 T>A: Promising Prognostic Markers in Triple Negative Breast Cancer PatientsMedicina (Kaunas, Lithuania) · 2022Article
- Identification of long non‑coding RNA‑mediated transcriptional dysregulation triplets reveals global patterns and prognostic biomarkers for ER+/PR+, HER2‑ and triple negative breast cancer.International journal of molecular medicine · 2019Article
- Diagnosis and Therapy of Triple-Negative Breast Cancer (TNBC) - Recommendations for Daily Routine Practice.Geburtshilfe und Frauenheilkunde · 2019Article
- Update Breast Cancer 2019 Part 3 - Current Developments in Early Breast Cancer: Review and Critical Assessment by an International Expert Panel.Geburtshilfe und Frauenheilkunde · 2019Article
- Update Breast Cancer 2019 Part 1 - Implementation of Study Results of Novel Study Designs in Clinical Practice in Patients with Early Breast Cancer.Geburtshilfe und Frauenheilkunde · 2019Article
- Update Breast Cancer 2018 (Part 4) - Genomics, Individualized Medicine and Immune Therapies - in the Middle of a New Era: Treatment Strategies for Advanced Breast Cancer.Geburtshilfe und Frauenheilkunde · 2018Article
- Update Breast Cancer 2018 (Part 3) - Genomics, Individualized Medicine and Immune Therapies - in the Middle of a New Era: Prevention and Treatment Strategies for Early Breast Cancer.Geburtshilfe und Frauenheilkunde · 2018Article
- Risk, Prediction and Prevention of Hereditary Breast Cancer - Large-Scale Genomic Studies in Times of Big and Smart Data.Geburtshilfe und Frauenheilkunde · 2018Article
- Update Breast Cancer 2018 (Part 2) - Advanced Breast Cancer, Quality of Life and Prevention.Geburtshilfe und Frauenheilkunde · 2018Article
- Using automated texture features to determine the probability for masking of a tumor on mammography, but not ultrasound.European journal of medical research · 2017Observational
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Authors and funding
14 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionStudies of triple-negative breast cancer have recently been extending the inclusion criteria and incorporating additional molecular markers into the selection criteria, opening up scope for targeted therapies. The screening phases required for studies of this type are often prolonged, since the process of determining the molecular subtype and carrying out additional biomarker assessment is time-consuming. Parameters such as germline genotypes capable of predicting the molecular subtype before it becomes available from pathology might be helpful for treatment planning and optimizing the timing and cost of screening phases. This appears to be feasible, as rapid and low-cost genotyping methods are becoming increasingly available. The aim of this study was to identify single nucleotide polymorphisms (SNPs) for breast cancer risk capable of predicting triple negativity, in addition to clinical predictors, in breast cancer patients.
methodsThis cross-sectional observational study included 1271 women with invasive breast cancer who were treated at a university hospital. A total of 76 validated breast cancer risk SNPs were successfully genotyped. Univariate associations between each SNP and triple negativity were explored using logistic regression analyses. Several variable selection and regression techniques were applied to identify a set of SNPs that together improve the prediction of triple negativity in addition to the clinical predictors of age at diagnosis and body mass index (BMI). The most accurate prediction method was determined by cross-validation.
resultsThe SNP rs10069690
conclusionPrediction of triple-negative breast cancer can be improved if SNPs associated with breast cancer risk are added to a prediction rule based on age at diagnosis and BMI. This finding could be used for prescreening purposes in complex molecular therapy studies for triple-negative breast cancer.
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