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Breast Cancer Risk Factors
Breast Cancer Research is presenting our Retrospective Collection on "Breast Cancer Risk Factors." Celebrating 'Breast Cancer Awareness Month (1 October- 31 October)', with this Collection, we aim to gain valuable insights into the multifaceted aspects of breast cancer risk to promote awareness, prevention, and early detection.
Aims and scope
Articles
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Fibroblast growth factor receptor signaling modulates cholesterol storage in a SOAT1-dependent manner to promote mammary tumor cell invasion
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Chemoresistant tumor cell secretome potentiates immune suppression in triple negative breast cancer
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The impact of a mainstream genetic testing pathway and socioeconomic factors on the uptake of germline genetic testing in breast cancer patients: results of the nationwide GENE-SMART study
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The association between body mass index and neoadjuvant chemotherapy response in patients with breast cancer
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Serum thymidine kinase 1 activity as a pharmacodynamic marker of cyclin-dependent kinase 4/6 inhibition in patients with early-stage breast cancer receiving neoadjuvant palbociclib
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Choosing the right cell line for breast cancer research
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Triple-negative breast cancer molecular subtyping and treatment progress
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Breast asymmetry and predisposition to breast cancer
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Critical research gaps and translational priorities for the successful prevention and treatment of breast cancer
Editor-in-Chief
Lewis Chodosh, University of Pennsylvania, USA
Trending in the Media
Click here to see the most popular articles published in Breast Cancer Research in the past three months.
BCR's 20th Anniversary
20 years ago Breast Cancer Research published its first articles with BMC. Well-respected in the field, the journal has continually placed in the first quartile of the ‘Oncology’ category of Journal Citation Reports. Over the past decade, Breast Cancer Research (BCR) has also become the highest ranked breast cancer focused title in the field.
Look back at the journal’s milestone achievements and article highlights.
Featured Review - Artificial intelligence in mammographic phenotyping of breast cancer risk: a narrative review
In this review, we provide a useful reference for AI researchers investigating image-based breast cancer risk assessment while indicating key priorities and challenges that, if properly addressed, could accelerate the implementation of AI-assisted risk stratification to future refine and individualize breast cancer screening strategies.
Springer Nature Oncology Portfolio
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Annual Journal Metrics
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Citation Impact
Journal Impact Factor: 5.6 (2024)
5-year Journal Impact Factor: 7.0 (2024)
Source Normalized Impact per Paper (SNIP): 1.412 (2024)
SCImago Journal Rank (SJR): 2.202 (2024)
Speed
Submission to first editorial decision (median days): 12
Submission to acceptance (median days): 145
Usage 2024
Downloads: 2,971,481
Altmetric mentions: 1,091