Version 1
: Received: 9 April 2024 / Approved: 10 April 2024 / Online: 11 April 2024 (04:09:05 CEST)
How to cite:
Kwok, T.; Yeguvapalli, S.; Chitrala, K.N. Integrated Bioinformatics Analysis for the Screening of Hub Genes in Breast Cancer Metastasis Recurrence at Liver. Preprints2024, 2024040721. https://doi.org/10.20944/preprints202404.0721.v1
Kwok, T.; Yeguvapalli, S.; Chitrala, K.N. Integrated Bioinformatics Analysis for the Screening of Hub Genes in Breast Cancer Metastasis Recurrence at Liver. Preprints 2024, 2024040721. https://doi.org/10.20944/preprints202404.0721.v1
Kwok, T.; Yeguvapalli, S.; Chitrala, K.N. Integrated Bioinformatics Analysis for the Screening of Hub Genes in Breast Cancer Metastasis Recurrence at Liver. Preprints2024, 2024040721. https://doi.org/10.20944/preprints202404.0721.v1
APA Style
Kwok, T., Yeguvapalli, S., & Chitrala, K.N. (2024). Integrated Bioinformatics Analysis for the Screening of Hub Genes in Breast Cancer Metastasis Recurrence at Liver. Preprints. https://doi.org/10.20944/preprints202404.0721.v1
Chicago/Turabian Style
Kwok, T., Suneetha Yeguvapalli and Kumaraswamy Naidu Chitrala. 2024 "Integrated Bioinformatics Analysis for the Screening of Hub Genes in Breast Cancer Metastasis Recurrence at Liver" Preprints. https://doi.org/10.20944/preprints202404.0721.v1
Abstract
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, it aimed to shed light on the diversities of this process. This research investigates Breast cancer liver metastasis relapse by employing a comprehensive approach that integrates data filtering, Gene Ontology and KEGG Pathway Analysis, Overall Survival analysis, identification of the Alteration in the DEGs, Visualization of Protein-Protein Interaction Network, Signor 2.0, identification of positively correlated genes, screening results of the function of hub genes, immune cell infiltration analysis, genetic alternation analysis, Copy number variant analysis, Gene to mRNA interaction, transcription factor analysis , autodocking and identification of Potential Treatment Target. This study’s integrative approach unveils metabolic reprogramming, suggesting altered PCK1 and LPL expression as key in breast cancer metastasis recurrence.
Keywords
Breast cancer recurrence; Breast Cancer Liver Metastasis; Bioinformatic analysis
Subject
Biology and Life Sciences, Life Sciences
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
