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Stephen F. Madden

Researcher at Royal College of Surgeons in Ireland

Publications -  95
Citations -  4187

Stephen F. Madden is an academic researcher from Royal College of Surgeons in Ireland. The author has contributed to research in topics: Breast cancer & Cancer. The author has an hindex of 26, co-authored 85 publications receiving 3447 citations. Previous affiliations of Stephen F. Madden include Ludwig Maximilian University of Munich & German Cancer Research Center.

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Leukocyte Complexity Predicts Breast Cancer Survival and Functionally Regulates Response to Chemotherapy

TL;DR: Blockade of pathways mediating macrophage recruitment, in combination with chemotherapy, significantly decreases primary tumor progression, reduces metastasis, and improves survival by CD8+ T-cell-dependent mechanisms, thus indicating that the immune microenvironment of tumors can be reprogrammed to instead foster antitumor immunity and improve response to cytotoxic therapy.
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Correlating transcriptional networks to breast cancer survival: a large-scale coexpression analysis

TL;DR: Weighted gene coexpression network analysis (WGCNA) is a powerful 'guilt-by-association'-based method to extract coexpressed groups of genes from large heterogeneous messenger RNA expression data sets and a cluster of genes was found to correlate with prognosis exclusively for basal-like breast cancer.
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Proteomic portrait of human breast cancer progression identifies novel prognostic markers.

TL;DR: The findings suggest that global proteomic analysis provides information about the protein changes specific to ER(-) breast tumor progression as well as important prognostic information.
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BreastMark : An Integrated Approach to Mining Publicly Available Transcriptomic Datasets Relating to Breast Cancer Outcome

TL;DR: BreastMark is a powerful tool for examining putative gene/miRNA prognostic markers in breast cancer, and can act as a powerful reductionist approach to these more complex gene signatures, eliminating superfluous genes, potentially reducing the cost and complexity of these multi-index assays.