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Prognostic features of signal transducer and activator of transcription 3 in an ER(+) breast cancer model system.

Liu LY, Chang LY, Kuo WH, Hwa HL, Lin YS, Jeng MH, Roth DA, Chang KJ, Hsieh FJ - Cancer Inform (2014)

Bottom Line: These data predict malignant events, treatment responses and a novel enhancer of tamoxifen resistance.Taken together, we identify a poor prognosis relevant gene set within the STAT3 network and a robust one in a subset of patients.VEGFA, ABL1, LYN, IGF2R and STAT3 are suggested therapeutic targets for further study based upon the degree of differential expression in our model.

View Article: PubMed Central - PubMed

Affiliation: Department of Agronomy, Biometry Division, National Taiwan University, Taipei, Taiwan.

ABSTRACT
The aberrantly expressed signal transducer and activator of transcription 3 (STAT3) predicts poor prognosis, primarily in estrogen receptor positive (ER(+)) breast cancers. Activated STAT3 is overexpressed in luminal A subtype cells. The mechanisms contributing to the prognosis and/or subtype relevant features of STAT3 in ER(+) breast cancers are through multiple interacting regulatory pathways, including STAT3-MYC, STAT3-ERα, and STAT3-MYC-ERα interactions, as well as the direct action of activated STAT3. These data predict malignant events, treatment responses and a novel enhancer of tamoxifen resistance. The inferred crosstalk between ERα and STAT3 in regulating their shared target gene-METAP2 is partially validated in the luminal B breast cancer cell line-MCF7. Taken together, we identify a poor prognosis relevant gene set within the STAT3 network and a robust one in a subset of patients. VEGFA, ABL1, LYN, IGF2R and STAT3 are suggested therapeutic targets for further study based upon the degree of differential expression in our model.

No MeSH data available.


Related in: MedlinePlus

Heatmaps for the subnetworks of MYC and STAT3 in different subtypes of the ER(+) IDCs. Non-tumor components (NT) serve as the controls. Left panel shows the heatmaps for 90 A cohort, which were generated from 61 group IE, and 29 group IIE breast cancer subtypes. Right panel shows the heatmaps for 72 A cohort which were generated from 42 luminal A and 32 luminal B breast cancer subtypes. The hierarchically clustered gene expression patterns were based on the similar expression levels among genes in the subnetworks of four altered biological events—cell proliferation (upper panel of A), sustained angiogenesis (lower panel of A), Warburg effect (B) and ES-like phenotype (C). A FOXC1 subnetwork (D) contains a gene list to be a part of the FOXC1 subnetwork in the ER(−) IDCs.9 4E stands for heatmaps of 2 cohorts (90 A, 72 A) for the prognostic factors (17 probes) identified in the STAT3 subnetworks (4A–D and Fig. 7B) of 90 A cohort. We located 3 subcohorts based on their similarity in gene expression patterns for a prognosis signature (17 probes) indicated by feature color bars underneath of the heatmap for Figure 4E. Light red color bar stands for subcohort 1 (N = 14). Light green color bar stands for subcohort 3 (N = 17). Light blue color bar stands for subcohort 2 (N = 59).
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f4-cin-13-2014-021: Heatmaps for the subnetworks of MYC and STAT3 in different subtypes of the ER(+) IDCs. Non-tumor components (NT) serve as the controls. Left panel shows the heatmaps for 90 A cohort, which were generated from 61 group IE, and 29 group IIE breast cancer subtypes. Right panel shows the heatmaps for 72 A cohort which were generated from 42 luminal A and 32 luminal B breast cancer subtypes. The hierarchically clustered gene expression patterns were based on the similar expression levels among genes in the subnetworks of four altered biological events—cell proliferation (upper panel of A), sustained angiogenesis (lower panel of A), Warburg effect (B) and ES-like phenotype (C). A FOXC1 subnetwork (D) contains a gene list to be a part of the FOXC1 subnetwork in the ER(−) IDCs.9 4E stands for heatmaps of 2 cohorts (90 A, 72 A) for the prognostic factors (17 probes) identified in the STAT3 subnetworks (4A–D and Fig. 7B) of 90 A cohort. We located 3 subcohorts based on their similarity in gene expression patterns for a prognosis signature (17 probes) indicated by feature color bars underneath of the heatmap for Figure 4E. Light red color bar stands for subcohort 1 (N = 14). Light green color bar stands for subcohort 3 (N = 17). Light blue color bar stands for subcohort 2 (N = 59).

Mentions: OGDH, PC, IDH3G, SDHA, SDHC, and GLS are predicted to be up-regulated by STAT3 coupled with MYC in the 72 A cohort. The 90 A cohort has the same regulatory subnetwork except GLS is predicted to be regulated by STAT3 alone (Fig. 3C). LDHA and LDHB appear to be down-regulated by STAT3 and MYC in both 90 A and 72 A cohorts and low LDHB mRNA levels in 90 A cohort are a predictor of favorable prognosis (Table 2). High levels of IDH3G are a favorable prognosis predictor in 72 A cohort (Table 3). ESRRG, PC, a transcript variant of MYC, SDHD, and LDHB are highly expressed in the non-tumor component (Fig. 4B).


Prognostic features of signal transducer and activator of transcription 3 in an ER(+) breast cancer model system.

Liu LY, Chang LY, Kuo WH, Hwa HL, Lin YS, Jeng MH, Roth DA, Chang KJ, Hsieh FJ - Cancer Inform (2014)

Heatmaps for the subnetworks of MYC and STAT3 in different subtypes of the ER(+) IDCs. Non-tumor components (NT) serve as the controls. Left panel shows the heatmaps for 90 A cohort, which were generated from 61 group IE, and 29 group IIE breast cancer subtypes. Right panel shows the heatmaps for 72 A cohort which were generated from 42 luminal A and 32 luminal B breast cancer subtypes. The hierarchically clustered gene expression patterns were based on the similar expression levels among genes in the subnetworks of four altered biological events—cell proliferation (upper panel of A), sustained angiogenesis (lower panel of A), Warburg effect (B) and ES-like phenotype (C). A FOXC1 subnetwork (D) contains a gene list to be a part of the FOXC1 subnetwork in the ER(−) IDCs.9 4E stands for heatmaps of 2 cohorts (90 A, 72 A) for the prognostic factors (17 probes) identified in the STAT3 subnetworks (4A–D and Fig. 7B) of 90 A cohort. We located 3 subcohorts based on their similarity in gene expression patterns for a prognosis signature (17 probes) indicated by feature color bars underneath of the heatmap for Figure 4E. Light red color bar stands for subcohort 1 (N = 14). Light green color bar stands for subcohort 3 (N = 17). Light blue color bar stands for subcohort 2 (N = 59).
© Copyright Policy - open-access
Related In: Results  -  Collection

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f4-cin-13-2014-021: Heatmaps for the subnetworks of MYC and STAT3 in different subtypes of the ER(+) IDCs. Non-tumor components (NT) serve as the controls. Left panel shows the heatmaps for 90 A cohort, which were generated from 61 group IE, and 29 group IIE breast cancer subtypes. Right panel shows the heatmaps for 72 A cohort which were generated from 42 luminal A and 32 luminal B breast cancer subtypes. The hierarchically clustered gene expression patterns were based on the similar expression levels among genes in the subnetworks of four altered biological events—cell proliferation (upper panel of A), sustained angiogenesis (lower panel of A), Warburg effect (B) and ES-like phenotype (C). A FOXC1 subnetwork (D) contains a gene list to be a part of the FOXC1 subnetwork in the ER(−) IDCs.9 4E stands for heatmaps of 2 cohorts (90 A, 72 A) for the prognostic factors (17 probes) identified in the STAT3 subnetworks (4A–D and Fig. 7B) of 90 A cohort. We located 3 subcohorts based on their similarity in gene expression patterns for a prognosis signature (17 probes) indicated by feature color bars underneath of the heatmap for Figure 4E. Light red color bar stands for subcohort 1 (N = 14). Light green color bar stands for subcohort 3 (N = 17). Light blue color bar stands for subcohort 2 (N = 59).
Mentions: OGDH, PC, IDH3G, SDHA, SDHC, and GLS are predicted to be up-regulated by STAT3 coupled with MYC in the 72 A cohort. The 90 A cohort has the same regulatory subnetwork except GLS is predicted to be regulated by STAT3 alone (Fig. 3C). LDHA and LDHB appear to be down-regulated by STAT3 and MYC in both 90 A and 72 A cohorts and low LDHB mRNA levels in 90 A cohort are a predictor of favorable prognosis (Table 2). High levels of IDH3G are a favorable prognosis predictor in 72 A cohort (Table 3). ESRRG, PC, a transcript variant of MYC, SDHD, and LDHB are highly expressed in the non-tumor component (Fig. 4B).

Bottom Line: These data predict malignant events, treatment responses and a novel enhancer of tamoxifen resistance.Taken together, we identify a poor prognosis relevant gene set within the STAT3 network and a robust one in a subset of patients.VEGFA, ABL1, LYN, IGF2R and STAT3 are suggested therapeutic targets for further study based upon the degree of differential expression in our model.

View Article: PubMed Central - PubMed

Affiliation: Department of Agronomy, Biometry Division, National Taiwan University, Taipei, Taiwan.

ABSTRACT
The aberrantly expressed signal transducer and activator of transcription 3 (STAT3) predicts poor prognosis, primarily in estrogen receptor positive (ER(+)) breast cancers. Activated STAT3 is overexpressed in luminal A subtype cells. The mechanisms contributing to the prognosis and/or subtype relevant features of STAT3 in ER(+) breast cancers are through multiple interacting regulatory pathways, including STAT3-MYC, STAT3-ERα, and STAT3-MYC-ERα interactions, as well as the direct action of activated STAT3. These data predict malignant events, treatment responses and a novel enhancer of tamoxifen resistance. The inferred crosstalk between ERα and STAT3 in regulating their shared target gene-METAP2 is partially validated in the luminal B breast cancer cell line-MCF7. Taken together, we identify a poor prognosis relevant gene set within the STAT3 network and a robust one in a subset of patients. VEGFA, ABL1, LYN, IGF2R and STAT3 are suggested therapeutic targets for further study based upon the degree of differential expression in our model.

No MeSH data available.


Related in: MedlinePlus