Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning-Reference-Cited by-同舟云学术

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Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning

Published:2024-02-21 Issue: Volume: Page:
ISSN:0006-2928
Container-title:Biochemical Genetics
language:en
Short-container-title:Biochem Genet

Author:

Ma QingLan,Chen Lei,Feng KaiYan,Guo Wei,Huang Tao,Cai Yu-Dong

Funder

National Key R&D Program of China

Strategic Priority Research Program of Chinese Academy of Sciences

Fund of the Key Laboratory of Tissue Microenvironment and Tumor of Chinese Academy of Sciences

Shandong Provincial Natural Science Foundation

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10528-024-10712-w.pdf

Reference134 articles.

1. Abdelzaher E, Mostafa MF (2015) Lysophosphatidylcholine acyltransferase 1 (LPCAT1) upregulation in breast carcinoma contributes to tumor progression and predicts early tumor recurrence. Tumour Biol 36:5473–5483

2. Alexandrou S, George SM, Ormandy CJ, Lim E, Oakes SR, Caldon CE (2019) The proliferative and apoptotic landscape of basal-like breast cancer. Int J Mol Sci 20:667

3. Alfarsi LH, Ansari RE, Craze ML, Toss MS, Masisi B, Ellis IO, Rakha EA, Green AR (2019) CDC20 expression in oestrogen receptor positive breast cancer predicts poor prognosis and lack of response to endocrine therapy. Breast Cancer Res Treat 178:535–544

4. Amiri Souri E, Chenoweth A, Cheung A, Karagiannis SN, Tsoka S (2021) Cancer grade model: a multi-gene machine learning-based risk classification for improving prognosis in breast cancer. Br J Cancer 125:748–758

5. Angus L, Moleirinho S, Herron L, Sinha A, Zhang X, Niestrata M, Dholakia K, Prystowsky MB, Harvey KF, Reynolds PA, Gunn-Moore FJ (2012) Willin/FRMD6 expression activates the Hippo signaling pathway kinases in mammals and antagonizes oncogenic YAP. Oncogene 31:238–250

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