ArticleBritish journal of cancer2017
Novel immunohistochemistry-based signatures to predict metastatic site of triple-negative breast cancers.
Article in British journal of cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Molecular and Clinicopathological Biomarkers Predicting Brain Metastasis in Triple-Negative Breast Cancer: A Systematic Review.International journal of molecular sciences · 2026Pooled it
- Development and validation of an interpretable ensemble model for predicting androgen receptor status in triple-negative breast cancer: a multi-center study.Frontiers in oncology · 2026Article
- Predictive value of androgen receptor in distant metastasis of triple-negative breast cancer: a retrospective multi-center study.BMC cancer · 2025Article
- Unlocking the epigenetic code: new insights into triple-negative breast cancer.Frontiers in oncology · 2024Review
- ProNGF promotes brain metastasis through TrkA/EphA2 induced Src activation in triple negative breast cancer cells.Experimental hematology & oncology · 2023Article
- Development and external validation of a prediction model for brain metastases in patients with metastatic breast cancer.Journal of cancer research and clinical oncology · 2023Article
- Risk of metastasis in BRCA2 carriers diagnosed with triple-negative breast cancer.Cancer medicine · 2023Article
- Nuclear import of PTPN18 inhibits breast cancer metastasis mediated by MVP and importin β2.Cell death & disease · 2022Article
- Immunotherapy in triple-negative breast cancer: Insights into tumor immune landscape and therapeutic opportunities.Frontiers in molecular biosciences · 2022Review
- Breast cancer-derived DAMPs enhance cell invasion and metastasis, while nucleic acid scavengers mitigate these effects.Molecular therapy. Nucleic acids · 2021Article
- A pre-operative MRI-based brain metastasis risk-prediction model for triple-negative breast cancer.Gland surgery · 2021Article
- An Immune Model to Predict Prognosis of Breast Cancer Patients Receiving Neoadjuvant Chemotherapy Based on Support Vector Machine.Frontiers in oncology · 2021Article
- Review
- Machine learning for tissue diagnostics in oncology: brave new world.British journal of cancer · 2019Article
- Added value of histogram analysis of apparent diffusion coefficient maps for differentiating triple-negative breast cancer from other subtypes of breast cancer on standard MRI.Cancer management and research · 2019Article
- Aberrant miRNAs expressed in HER-2 negative breast cancers patient.Journal of experimental & clinical cancer research : CR · 2018Article
Corrections and comments
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8 authors.
Funding
Abstract
backgroundAlthough distant metastasis (DM) in breast cancer (BC) is the most lethal form of recurrence and the most common underlying cause of cancer related deaths, the outcome following the development of DM is related to the site of metastasis. Triple negative BC (TNBC) is an aggressive form of BC characterised by early recurrences and high mortality. Athough multiple variables can be used to predict the risk of metastasis, few markers can predict the specific site of metastasis. This study aimed at identifying a biomarker signature to predict particular sites of DM in TNBC.
methodsA clinically annotated series of 322 TNBC were immunohistochemically stained with 133 biomarkers relevant to BC, to develop multibiomarker models for predicting metastasis to the bone, liver, lung and brain. Patients who experienced metastasis to each site were compared with those who did not, by gradually filtering the biomarker set via a two-tailed t-test and Cox univariate analyses. Biomarker combinations were finally ranked based on statistical significance, and evaluated in multivariable analyses.
resultsOur final models were able to stratify TNBC patients into high risk groups that showed over 5, 6, 7 and 8 times higher risk of developing metastasis to the bone, liver, lung and brain, respectively, than low-risk subgroups. These models for predicting site-specific metastasis retained significance following adjustment for tumour size, patient age and chemotherapy status.
conclusionsOur novel IHC-based biomarkers signatures, when assessed in primary TNBC tumours, enable prediction of specific sites of metastasis, and potentially unravel biomarkers previously unknown in site tropism.
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