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The lack of tailored therapeutic protocols for breast cancer liver metastasis highlights the need to clarify molecular patterns driving this complication. By comparing differentially expressed genes between primary breast tumors and breast cancer liver metastasis lesions, the study integrates filtering, gene ontology and KEGG pathway analysis, survival analysis, DEG alteration assessment, PPI network visualization, Signor 2.0, immune infiltration, genetic alternation and copy number variant analyses, gene-tomRNA and transcription factor analysis, molecular docking, and potential target identification. 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Identification of Genes Crucial for Biological Processes in Breast Cancer Liver Metastasis Relapse. Int. J. Mol. Sci. 2024, 25, 5439 . [https://doi.org/10.3390/ijms25105439](https://doi.org/10.3390/ijms25105439)  \nAcademic Editor: Caterina Cinti  \nReceived: 8 April 2024  \nRevised: 6 May 2024  \nAccepted: 9 May 2024  \nPublished: 16 May 2024  \nCopyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \nDepartment of Engineering Technology, University of Houston, Sugar Land, TX 77479, USA;  \n[tkwok@cougarnet.uh.edu](tkwok@cougarnet.uh.edu) (T.K.); [syeguvap@central.uh.edu](syeguvap@central.uh.edu) (S.Y.)  \n* Correspondence: [kchitral@central.uh.edu](kchitral@central.uh.edu); Tel.: +1-7137437965  \nAbstract: Breast cancer, when advancing to a metastatic stage, involves the liver, impacting over 50% of cases and significantly diminishing survival rates. Presently, a lack of tailored therapeutic protocols for breast cancer liver metastasis (BCLM) underscores the need for a deeper understanding of molecular patterns governing this complication. Therefore, by analyzing differentially expressed genes (DEGs) between primary breast tumors and BCLM lesions, we aimed to shed light on the diversities of this process. This research investigated breast cancer liver metastasis relapse by employing a comprehensive approach that integrated data filtering, gene ontology and KEGG pathway analysis, overall survival analysis, identification of the alteration in the DEGs, visualization of the protein–protein interaction network, Signor 2.0, identification of positively correlated genes, immune cell infiltration analysis, genetic alternation analysis, copy number variant analysis, gene-tomRNA interaction, transcription factor analysis, molecular docking, and identification of potential treatment targets. This study’s integrative approach unveiled metabolic reprogramming, suggesting altered PCK1 and LPL expression as key in breast cancer metastasis recurrence.  \nKeywords: breast cancer recurrence; breast cancer liver metastasis; bioinformatic analysis  \n1. Introduction  \nMetastasis due to cancer is one of the leading causes of cancer deaths among patients with breast cancer [1] . It is known to be highly complex, involving multiple cellular mechanisms such as tumor invasion, evasion of immune surveillance, and regulation of the tissue microenvironment [2] . Among the metastases, liver metastasis is a common and devastating complication for patients with breast cancer, occurring in over 50% of those with advanced disease. Though early-stage breast cancer has a 5-year survival rate approaching 100%, this prognosis drastically declines by 26% upon diagnosis of distant organ involvement [3] . Unfortunately, there are currently no standardized therapeutic protocols explicitly tailored for BCLM due to an incomplete understanding of the molecular patterns and mechanisms governing this metastatic process. Elucidating the genetic factors that drive BCLM development and relapse following treatment is imperative to determine patient prognosis, identify the highest risk, and develop targeted therapies.  \nA critical first step is to define the landscape of differentially expressed genes (DEGs) between primary breast tumors and matched BCLM lesions. However, uncertainty remains regarding the key molecular biomarkers and functional pathways involved in BCLM pathogenesis. A thorough investigation of DEGs between liver metastases and the original can","cbCaiho65xg8LoHu","https://ap.wps.com/l/cbCaiho65xg8LoHu","pdf",7627055,17,"English","# Abstract\n# Introduction\n# Results\n## Identification of Datasets and Analysis of Differentially Expressed Genes","[{\"question\":\"What clinical gap motivates this research on breast cancer liver metastasis relapse?\",\"answer\":\"The study highlights that there are no standardized therapeutic protocols specifically tailored for breast cancer liver metastasis due to incomplete understanding of the molecular patterns and mechanisms driving the metastatic process and relapse.\"},{\"question\":\"How were differentially expressed genes (DEGs) obtained in this study?\",\"answer\":\"Gene expression profiles from GEO datasets (GSE46141, GSE56493, and GSE175692) were selected. Differential analyses compared primary breast tumors and liver metastasis, including local metastasis versus liver metastasis and relapsed metastatic samples, to derive significant DEGs.\"},{\"question\":\"Which genes showed overlap across the three analyzed datasets?\",\"answer\":\"Venn analysis identified five overlapping genes: PCK1, SHC2, LPL, SFRP2, and KRT6B across the three datasets, suggesting shared biological involvement in the process studied.\"}]","Identification of Genes Crucial for Biological Processes in Breast Cancer Liver Metastasis Relapse - Research Overview | PDF",1789996754,43]