Introducing effective genes in lymph node metastasis of breast cancer patients using SHAP values based on the mRNA expression data

The prominent identified mRNAs including GDF5, BAHCC1, LCN2, FGF14-AS2, and IDH2, are implicated in lymph node metastasis. This study holds promise in elucidating a thorough insight into key candidate genes that could significantly impact the early detection and tailored therapeutic strategies for lymph node metastasis in patients with breast cancer.

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Publication Details

Journal
PLoS ONE
Published
2024-08-16
DOI
https://doi.org/10.1371/journal.pone.0308531
Citations
3
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
0.86

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article

Introducing effective genes in lymph node metastasis of breast cancer patients using SHAP values based on the mRNA expression data

Farnaz Boostani, Seyed Mahdi Hosseiniyan Khatibi, Sepideh Zununi Vahed, Yalda Rahbar Saadat et al.
3 citations
PLoS ONE
Cancer-related molecular mechanisms research
0.86
article

Introducing effective genes in lymph node metastasis of breast cancer patients using SHAP values based on the mRNA expression data

Farnaz Boostani, Seyed Mahdi Hosseiniyan Khatibi, Sepideh Zununi Vahed, Yalda Rahbar Saadat, Manijeh Emdadi, Saeed Pirmoradi, Solmaz Maleki Dizaj, Mohammad Matin Alishani, Bahareh Khodaei
article en
3 citations

Abstract

The prominent identified mRNAs including GDF5, BAHCC1, LCN2, FGF14-AS2, and IDH2, are implicated in lymph node metastasis. This study holds promise in elucidating a thorough insight into key candidate genes that could significantly impact the early detection and tailored therapeutic strategies for lymph node metastasis in patients with breast cancer.

PLoS ONEVol. 19(8)
Islamic Azad University, Tehran (IR), Tabriz University of Medical Sciences (IR), University of Tabriz (IR), Islamic Azad University, Abadan
Tabriz University of Medical Sciences, University of Tabriz, National Institute for Medical Research Development
Reduced inequalities
Openalex Percentile: Top 26%
Cancer-related molecular mechanisms research
0.86
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