Dataset Information

Neural Functions Play Different Roles in Triple Negative Breast Cancer (TNBC) and non-TNBC.

ABSTRACT: Triple negative breast cancer (TNBC) represents the most malignant subtype of breast cancer, and yet our understanding about its unique biology remains elusive. We have conducted a comparative computational analysis of transcriptomic data of TNBC and non-TNBC (NTNBC) tissue samples from the TCGA database, focused on genes involved in neural functions. Our main discoveries are: (1) while both subtypes involve neural functions, TNBC has substantially more up-regulated neural genes than NTNBC, suggesting that TNBC is more complex than NTNBC; (2) non-neural functions related to cell-microenvironment interactions and intracellular damage processing are key inducers of the neural genes in both TNBC and NTNBC, but the inducer-responder relationships are different in the two cancer subtypes; (3) key neural functions such as neural crest formation are predicted to enhance adaptive immunity in TNBC while glia development, along with a few other neural functions, induce both innate and adaptive immunity in NTNBC. These results reveal key differences in the biology between the two cancer subtypes, particularly in terms of the roles that neural functions play. Our findings may open new doors for further investigation of the distinct biology of TNBC vs. NTNBC.

SUBMITTER: Tan R

PROVIDER: S-EPMC7033128 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Neural Functions Play Different Roles in Triple Negative Breast Cancer (TNBC) and non-TNBC.

Tan Renbo R Li Haoyang H Huang Zhenyu Z Zhou Yi Y Tao Mingxin M Gao Xin X Xu Ying Y

Scientific reports 20200220 1

Triple negative breast cancer (TNBC) represents the most malignant subtype of breast cancer, and yet our understanding about its unique biology remains elusive. We have conducted a comparative computational analysis of transcriptomic data of TNBC and non-TNBC (NTNBC) tissue samples from the TCGA database, focused on genes involved in neural functions. Our main discoveries are: (1) while both subtypes involve neural functions, TNBC has substantially more up-regulated neural genes than NTNBC, sugg ...[more]

PMID: 32080331

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Project description:BackgroundTriple Negative Breast Cancers (TNBCs) lack the appropriate targets for currently used breast cancer therapies, conferring an aggressive phenotype, more frequent relapse and poorer survival rates. The biological heterogeneity of TNBC complicates the clinical treatment further. We have explored and compared the biological pathways in TNBC and other subtypes of breast cancers, using an in silico approach and the hypothesis that two opposing effects (Yin and Yang) pathways in cancer cells determine the fate of cancer cells. Identifying breast subgroup specific components of these opposing pathways may aid in selecting potential therapeutic targets as well as further classifying the heterogeneous TNBC subtype.MethodsGene expression and patient clinical data from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) were used for this study. Gene Set Enrichment Analysis (GSEA) was used to identify the more active pathways in cancer (Yin) than in normal and the more active pathways in normal (Yang) than in cancer. The clustering analysis was performed to compare pathways of TNBC with other types of breast cancers. The association of pathway classified TNBC sub-groups to clinical outcomes was tested using Cox regression model.ResultsAmong 4729 curated canonical pathways in GSEA database, 133 Yin pathways (FDR < 0.05) and 71 Yang pathways (p-value <0.05) were discovered in TNBC. The FOXM1 is the top Yin pathway while PPARα is the top Yang pathway in TNBC. The TNBC and other types of breast cancers showed different pathways enrichment significance profiles. Using top Yin and Yang pathways as classifier, the TNBC can be further subtyped into six sub-groups each having different clinical outcomes.ConclusionWe first reported that the FOMX1 pathway is the most upregulated and the PPARα pathway is the most downregulated pathway in TNBC. These two pathways could be simultaneously targeted in further studies. Also the pathway classifier we performed in this study provided insight into the TNBC heterogeneity.

Project description:TGFβ signaling plays crucial role during development and cancer, however the role for TGFβ signaling in regulating the noncoding part of the human genome in triple negative breast cancer (TNBC) is still being unraveled. Herein, we provide the transcriptional landscape of TNBC in response to TGFβ activation and subsequent inhibition employing SB431542, selective TGFβ1 Receptor ALK5 Inhibitor. Our data revealed 72 commonly upregulated [fold change (FC) ≥ 2.0], including PLAU, TPM1, TAGLN, COL1A1, TGFBI, and SNAI1, and 53 downregulated (FC ≤ 2.0) protein coding genes in BT-549 and MDA-MB-231 models in response to TGFβ1 activation. Alignment to the geocode (V33) identified 41 upregulated (FC ≥ 2.0) and 22 downregulated (FC ≤ 2.0) long non-coding RNA (lncRNA) in response to TGFβ1 activation, which were inhibited by concurrent treatment with SB431542. To place our data from the in vitro models into their clinical context, we identified AC015909.1, AC013451.1, CYP1B1-AS1, AC004862.1, LINC01824, AL138828.1, B4GALT1-AS1, AL353751.1, AC090826.3, AC104695.4, ADORA2A-AS1, PTPRG-AS1, LINC01943, AC026954.3, TPM1-AS, ZFPM2-AS1, AC007362.1, AC112721.2, MALAT1, AL513314.2, AC112721.1, AC010343.3, LINC01711, and MAP3K2-DT lncRNA expression to positively correlate with TGFβ1 expression in a cohort of 360 TNBC patients. To provide mechanistic insight into lncRNA regulation by TGFβ signaling, SMAD2/3 ChIp-Seq data from BT-549 TNBC model retrieved from Gene Expression Omnibus (GEO) revealed direct binding of SMAD2/SMAD3 to the promoter of AC112721.1, AC112721.2, MALAT1, HHIP-AS1, LINC00472, and SLC7A11, suggesting their direct regulation by TGFβ1/SMAD2/SMAD3 pathway. Interestingly, AC112721.1, AC112721.2 exhibited higher expression in TNBC compared to normal breast tissue suggesting a possible role for those lncRNA in TNBC biology. Our miRNA analysis in the BT-549 model in response to exogenous TGFB1 revealed several affected miRNAs (2.0 ≤ FC ≤ 2.0), whose expression pattern was reversed in the presence of SB431542, suggesting those miRNA as plausible targets for TGFβ regulation. In particular, we observed hsa-miR-1275 to be downregulated in response to TGFB1 which was highly predicted to regulate PCDH1, FIBCD1, FXYD7, GDNF, STC1, EDN1, ZSWIM4, FGF1, PPP1R9B, NUAK1, PALM2AKAP2, IGFL3, and SPOCK1 whose expression were upregulated in response to TGFβ1 stimulus. On the other hand, hsa-miR-181b-5p was among the top upregulated miRNAs in response to TGFB1, which is also predicted to regulate CDKN1B, TNFRSF11B, SIM1, and ARSJ in the BT-549 model. Taken together, our data is the first to provide such in depth analysis of lncRNA and miRNA epigenetic changes in response to TGFβ signaling in TNBC.

Dataset Information

Neural Functions Play Different Roles in Triple Negative Breast Cancer (TNBC) and non-TNBC.

Publications

Neural Functions Play Different Roles in Triple Negative Breast Cancer (TNBC) and non-TNBC.

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