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Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence
Exploring complex modularization of intracellular signal transduction pathways is critical to understanding aberrant cellular responses during disease development and drug treatment. IMPALA (Inferred Modularization of PAthway LAndscapes) integrates information from high throughput gene expression ex...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801429/ https://www.ncbi.nlm.nih.gov/pubmed/33432018 http://dx.doi.org/10.1038/s41598-020-79603-5 |
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author | Chen, Xi Gu, Jinghua Neuwald, Andrew F. Hilakivi-Clarke, Leena Clarke, Robert Xuan, Jianhua |
author_facet | Chen, Xi Gu, Jinghua Neuwald, Andrew F. Hilakivi-Clarke, Leena Clarke, Robert Xuan, Jianhua |
author_sort | Chen, Xi |
collection | PubMed |
description | Exploring complex modularization of intracellular signal transduction pathways is critical to understanding aberrant cellular responses during disease development and drug treatment. IMPALA (Inferred Modularization of PAthway LAndscapes) integrates information from high throughput gene expression experiments and genome-scale knowledge databases to identify aberrant pathway modules, thereby providing a powerful sampling strategy to reconstruct and explore pathway landscapes. Here IMPALA identifies pathway modules associated with breast cancer recurrence and Tamoxifen resistance. Focusing on estrogen-receptor (ER) signaling, IMPALA identifies alternative pathways from gene expression data of Tamoxifen treated ER positive breast cancer patient samples. These pathways were often interconnected through cytoplasmic genes such as IRS1/2, JAK1, YWHAZ, CSNK2A1, MAPK1 and HSP90AA1 and significantly enriched with ErbB, MAPK, and JAK-STAT signaling components. Characterization of the pathway landscape revealed key modules associated with ER signaling and with cell cycle and apoptosis signaling. We validated IMPALA-identified pathway modules using data from four different breast cancer cell lines including sensitive and resistant models to Tamoxifen. Results showed that a majority of genes in cell cycle/apoptosis modules that were up-regulated in breast cancer patients with short survivals (< 5 years) were also over-expressed in drug resistant cell lines, whereas the transcription factors JUN, FOS, and STAT3 were down-regulated in both patient and drug resistant cell lines. Hence, IMPALA identified pathways were associated with Tamoxifen resistance and an increased risk of breast cancer recurrence. The IMPALA package is available at https://dlrl.ece.vt.edu/software/. |
format | Online Article Text |
id | pubmed-7801429 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78014292021-01-12 Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence Chen, Xi Gu, Jinghua Neuwald, Andrew F. Hilakivi-Clarke, Leena Clarke, Robert Xuan, Jianhua Sci Rep Article Exploring complex modularization of intracellular signal transduction pathways is critical to understanding aberrant cellular responses during disease development and drug treatment. IMPALA (Inferred Modularization of PAthway LAndscapes) integrates information from high throughput gene expression experiments and genome-scale knowledge databases to identify aberrant pathway modules, thereby providing a powerful sampling strategy to reconstruct and explore pathway landscapes. Here IMPALA identifies pathway modules associated with breast cancer recurrence and Tamoxifen resistance. Focusing on estrogen-receptor (ER) signaling, IMPALA identifies alternative pathways from gene expression data of Tamoxifen treated ER positive breast cancer patient samples. These pathways were often interconnected through cytoplasmic genes such as IRS1/2, JAK1, YWHAZ, CSNK2A1, MAPK1 and HSP90AA1 and significantly enriched with ErbB, MAPK, and JAK-STAT signaling components. Characterization of the pathway landscape revealed key modules associated with ER signaling and with cell cycle and apoptosis signaling. We validated IMPALA-identified pathway modules using data from four different breast cancer cell lines including sensitive and resistant models to Tamoxifen. Results showed that a majority of genes in cell cycle/apoptosis modules that were up-regulated in breast cancer patients with short survivals (< 5 years) were also over-expressed in drug resistant cell lines, whereas the transcription factors JUN, FOS, and STAT3 were down-regulated in both patient and drug resistant cell lines. Hence, IMPALA identified pathways were associated with Tamoxifen resistance and an increased risk of breast cancer recurrence. The IMPALA package is available at https://dlrl.ece.vt.edu/software/. Nature Publishing Group UK 2021-01-11 /pmc/articles/PMC7801429/ /pubmed/33432018 http://dx.doi.org/10.1038/s41598-020-79603-5 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Chen, Xi Gu, Jinghua Neuwald, Andrew F. Hilakivi-Clarke, Leena Clarke, Robert Xuan, Jianhua Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence |
title | Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence |
title_full | Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence |
title_fullStr | Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence |
title_full_unstemmed | Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence |
title_short | Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence |
title_sort | identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801429/ https://www.ncbi.nlm.nih.gov/pubmed/33432018 http://dx.doi.org/10.1038/s41598-020-79603-5 |
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