Image_1_Comprehensive Analysis of Prognostic Microenvironment-Related Genes in Invasive Breast Cancer.tif
Recent studies reveal that tumor microenvironment contributes to breast cancer (BRCA) development, progression, and therapeutic response. However, the contribution of the tumor microenvironment-related genes in routine diagnostic testing or therapeutic decision making for BRCA remains elusive. Immune/stromal/ESTIMATE scores calculated by the ESTIMATE algorithm quantify immune and stromal components in a tumor, and thus can reflect tumor microenvironment. To investigate the association of the tumor microenvironment-related genes with invasive BRCA prognosis, here we analyzed the immune/stromal/ESTIMATE scores in combination with The Cancer Genome Atlas (TCGA) database in invasive BRCA. We found that immune/stromal/ESTIMATE scores were significantly correlated with the invasive BRCA clinicopathological factors. Based on the immune/stromal/ESTIMATE scores, we extracted a series of differential expression genes (DEGs) related to the tumor microenvironment. Survival analysis was further performed to identify a list of high-frequency DEGs (HF-DEGs), which exhibited prognostic value in invasive BRCA. Importantly, consistent with the results of bioinformatics analysis, immunohistochemistry results showed that high SASH3 expression was associated with a good prognosis in invasive BRCA patients. Our findings suggest that the tumor microenvironment-related HF-DEGs identified in this study have prognostic values and may serve as potential biomarkers and therapeutic targets for invasive BRCA.
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References
- https://doi.org//10.1007/s13304-017-0424-1
- https://doi.org//10.1186/s12859-016-0917-9
- https://doi.org//10.7150/jca.17595
- https://doi.org//10.1002/ijc.31744
- https://doi.org//10.1038/ncomms3612
- https://doi.org//10.3892/ol.2018.7855
- https://doi.org//10.1136/jcp.50.10.801
- https://doi.org//10.1007/s10549-009-0674-9
- https://doi.org//10.12659/MSM.920212
- https://doi.org//10.18632/oncotarget.4470
- https://doi.org//10.4149/neo_2011_03_189
- https://doi.org//10.3892/ol.2017.6844
- https://doi.org//10.4149/neo_2016_017
- https://doi.org//10.3389/fphar.2019.00624
- https://doi.org//10.1016/S0002-9440%2810%2965626-X
- https://doi.org//10.3892/or.2017.5610
- https://doi.org//10.1016/j.bbrc.2013.10.110
- https://doi.org//10.1002/path.4316
- https://doi.org//10.3390/cells8101112
- https://doi.org//10.1002/ijc.21054
- https://doi.org//10.1530/ERC-17-0309
- https://doi.org//10.1007/s00401-018-1806-2
- https://doi.org//10.1002/gcc.22091
- https://doi.org//10.1677/erc.1.01301
- https://doi.org//10.2147/OTT.S200643
- https://doi.org//10.1016/j.prp.2004.09.006
- https://doi.org//10.1038/s41556-019-0346-x
- https://doi.org//10.1158/0008-5472.CAN-12-3526
- https://doi.org//10.3389/fonc.2018.00301
- https://doi.org//10.1371/journal.pone.0099052
- https://doi.org//10.18632/oncotarget.2011
- https://doi.org//10.1158/0008-5472.CAN-13-0967
- https://doi.org//10.18632/oncotarget.9858
- https://doi.org//10.1093/carcin/bgp084
- https://doi.org//10.1186/bcr2114
- https://doi.org//10.1177/0300060518815364
- https://doi.org//10.3892/mmr.2019.10853
- https://doi.org//10.1016/j.biocel.2011.07.012
- https://doi.org//10.1038/sj.onc.1204698
- https://doi.org//10.1038/373573a0
- https://doi.org//10.1182/blood.2020008629
- https://doi.org//10.1016/j.jcmgh.2018.08.007
- https://doi.org//10.1016/j.humpath.2018.01.008
- https://doi.org//10.2147/OTT.S119244