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dc.contributor.authorChen, Xi
dc.contributor.authorGu, Jinghua
dc.contributor.authorNeuwald, Andrew F
dc.contributor.authorHilakivi-Clarke, Leena
dc.contributor.authorClarke, Robert
dc.contributor.authorXuan, Jianhua
dc.date.accessioned2021-01-21T20:20:59Z
dc.date.available2021-01-21T20:20:59Z
dc.date.issued2021-01-11
dc.identifier.urihttp://hdl.handle.net/10713/14396
dc.description.abstractExploring 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/. © 2021, The Author(s).en_US
dc.description.urihttps://doi.org/10.1038/s41598-020-79603-5en_US
dc.language.isoenen_US
dc.publisherSpringer Natureen_US
dc.relation.ispartofScientific Reportsen_US
dc.subjectInferred Signal Modularization PAthway LAndscapes (IMPALA)en_US
dc.subject.lcshBreast--Canceren_US
dc.subject.meshDrug Resistanceen_US
dc.subject.meshSignal Transduction--geneticsen_US
dc.titleIdentifying intracellular signaling modules and exploring pathways associated with breast cancer recurrenceen_US
dc.typeArticleen_US
dc.identifier.doi10.1038/s41598-020-79603-5
dc.identifier.pmid33432018
dc.source.volume11
dc.source.issue1
dc.source.beginpage385
dc.source.endpage
dc.source.countryUnited States
dc.source.countryEngland


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