| 1. |
- Brennan, Donal J., et al.
(författare)
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Tumor-specific HMG-CoA reductase expression in primary premenopausal breast cancer predicts response to tamoxifen
- 2011
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 13:1, s. R12-
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: We previously reported an association between tumor-specific 3-hydroxy-3-methylglutharyl-coenzyme A reductase (HMG-CoAR) expression and a good prognosis in breast cancer. Here, the predictive value of HMG-CoAR expression in relation to tamoxifen response was examined. Methods: HMG-CoAR protein and RNA expression was analyzed in a cell line model of tamoxifen resistance using western blotting and PCR. HMG-CoAR mRNA expression was examined in 155 tamoxifen-treated breast tumors obtained from a previously published gene expression study (Cohort I). HMG-CoAR protein expression was examined in 422 stage II premenopausal breast cancer patients, who had previously participated in a randomized control trial comparing 2 years of tamoxifen with no systemic adjuvant treatment (Cohort II). Kaplan-Meier analysis and Cox proportional hazards modeling were used to estimate the risk of recurrence-free survival (RFS) and the effect of HMG-CoAR expression on tamoxifen response. Results: HMG-CoAR protein and RNA expression were decreased in tamoxifen-resistant MCF7-LCC9 cells compared with their tamoxifen-sensitive parental cell line. HMG-CoAR mRNA expression was decreased in tumors that recurred following tamoxifen treatment (P < 0.001) and was an independent predictor of RFS in Cohort I (hazard ratio = 0.63, P = 0.009). In Cohort II, adjuvant tamoxifen increased RFS in HMG-CoAR-positive tumors (P = 0.008). Multivariate Cox regression analysis demonstrated that HMG-CoAR was an independent predictor of improved RFS in Cohort II (hazard ratio = 0.67, P = 0.010), and subset analysis revealed that this was maintained in estrogen receptor (ER)-positive patients (hazard ratio = 0.65, P = 0.029). Multivariate interaction analysis demonstrated a difference in tamoxifen efficacy relative to HMG-CoAR expression (P = 0.05). Analysis of tamoxifen response revealed that patients with ER-positive/HMG-CoAR tumors had a significant response to tamoxifen (P = 0.010) as well as patients with ER-positive or HMG-CoAR-positive tumors (P = 0.035). Stratification according to ER and HMG-CoAR status demonstrated that ER-positive/HMG-CoAR-positive tumors had an improved RFS compared with ER-positive/HMG-CoAR-negative tumors in the treatment arm (P = 0.033); this effect was lost in the control arm (P = 0.138), however, suggesting that HMG-CoAR predicts tamoxifen response. Conclusions: HMG CoAR expression is a predictor of response to tamoxifen in both ER-positive and ER-negative disease. Premenopausal patients with tumors that express ER or HMG-CoAR respond to adjuvant tamoxifen.
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| 2. |
- Byström, Sanna, et al.
(författare)
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Affinity proteomic profiling of plasma for proteins associated to area-based mammographic breast density
- 2018
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Ingår i: Breast Cancer Research. - : BIOMED CENTRAL LTD. - 1465-5411 .- 1465-542X. ; 20
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Tidskriftsartikel (refereegranskat)abstract
- Background: Mammographic breast density is one of the strongest risk factors for breast cancer, but molecular understanding of how breast density relates to cancer risk is less complete. Studies of proteins in blood plasma, possibly associated with mammographic density, are well-suited as these allow large-scale analyses and might shed light on the association between breast cancer and breast density. Methods: Plasma samples from 1329 women in the Swedish KARMA project, without prior history of breast cancer, were profiled with antibody suspension bead array (SBA) assays. Two sample sets comprising 729 and 600 women were screened by two different SBAs targeting a total number of 357 proteins. Protein targets were selected through searching the literature, for either being related to breast cancer or for being linked to the extracellular matrix. Association between proteins and absolute area-based breast density (AD) was assessed by quantile regression, adjusting for age and body mass index (BMI). Results: Plasma profiling revealed linear association between 20 proteins and AD, concordant in the two sets of samples (p < 0.05). Plasma levels of seven proteins were positively associated and 13 proteins negatively associated with AD. For eleven of these proteins evidence for gene expression in breast tissue existed. Among these, ABCC11, TNFRSF10D, F11R and ERRF were positively associated with AD, and SHC1, CFLAR, ACOX2, ITGB6, RASSF1, FANCD2 and IRX5 were negatively associated with AD. Conclusions: Screening proteins in plasma indicates associations between breast density and processes of tissue homeostasis, DNA repair, cancer development and/or progression in breast cancer. Further validation and follow-up studies of the shortlisted protein candidates in independent cohorts will be needed to infer their role in breast density and its progression in premenopausal and postmenopausal women.
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| 3. |
- Nguyen-Vu, Trang, et al.
(författare)
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Liver × receptor ligands disrupt breast cancer cell proliferation through an E2F-mediated mechanism
- 2013
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 15:3
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: Liver × receptors (LXRs) are members of the nuclear receptor family of ligand-dependent transcription factors and have established functions as regulators of cholesterol, glucose, and fatty acid metabolism and inflammatory responses. Published reports of anti-proliferative effects of synthetic LXR ligands on breast, prostate, ovarian, lung, skin, and colorectal cancer cells suggest that LXRs are potential targets in cancer prevention and treatment.METHODS: To further determine the effects of LXR ligands and identify their potential mechanisms of action in breast cancer cells, we carried out microarray analysis of gene expression in four breast cancer cell lines following treatments with the synthetic LXR ligand GW3965. Differentially expressed genes were further subjected to gene ontology and pathway analyses, and their expression profiles and associations with disease parameters and outcomes were examined in clinical samples. Response of E2F target genes were validated by real-time PCR, and the posited role of E2F2 in breast cancer cell proliferation was tested by RNA interference experiments.RESULTS: We observed cell line-specific transcriptional responses as well as a set of common responsive genes. In the common responsive gene set, upregulated genes tend to function in the known metabolic effects of LXR ligands and LXRs whereas the downregulated genes mostly include those which function in cell cycle regulation, DNA replication, and other cell proliferation-related processes. Transcription factor binding site analysis of the downregulated genes revealed an enrichment of E2F binding site sequence motifs. Correspondingly, E2F2 transcript levels are downregulated following LXR ligand treatment. Knockdown of E2F2 expression, similar to LXR ligand treatment, resulted in a significant disruption of estrogen receptor positive breast cancer cell proliferation. Ligand treatment also decreased E2F2 binding to cis-regulatory regions of target genes. Hierarchical clustering of breast cancer patients based on the expression profiles of the commonly downregulated LXR ligand-responsive genes showed a strong association of these genes with patient survival.CONCLUSIONS: Taken together, these results indicate that LXR ligands target gene networks, including those regulated by E2F family members, are critical for tumor biology and disease progression and merit further consideration as potential agents in the prevention and treatment of breast cancers.
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| 4. |
- O'Leary, Patrick C., et al.
(författare)
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Peroxiredoxin-1 protects estrogen receptor alpha from oxidative stress-induced suppression and is a protein biomarker of favorable prognosis in breast cancer
- 2014
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 16:4, s. R79-
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Peroxiredoxin-1 (PRDX1) is a multifunctional protein, acting as a hydrogen peroxide (H2O2) scavenger, molecular chaperone and immune modulator. Although differential PRDX1 expression has been described in many tumors, the potential role of PRDX1 in breast cancer remains highly ambiguous. Using a comprehensive antibody-based proteomics approach, we interrogated PRDX1 protein as a putative biomarker in estrogen receptor (ER)-positive breast cancer. Methods: An anti-PRDX1 antibody was validated in breast cancer cell lines using immunoblotting, immunohistochemistry and reverse phase protein array (RPPA) technology. PRDX1 protein expression was evaluated in two independent breast cancer cohorts, represented on a screening RPPA (n = 712) and a validation tissue microarray (n = 498). In vitro assays were performed exploring the functional contribution of PRDX1, with oxidative stress conditions mimicked via treatment with H2O2, peroxynitrite, or adenanthin, a PRDX1/2 inhibitor. Results: In ER-positive cases, high PRDX1 protein expression is a biomarker of improved prognosis across both cohorts. In the validation cohort, high PRDX1 expression was an independent predictor of improved relapse-free survival (hazard ratio (HR) = 0.62, 95% confidence interval (CI) = 0.40 to 0.96, P = 0.032), breast cancer-specific survival (HR = 0.44, 95% CI = 0.24 to 0.79, P = 0.006) and overall survival (HR = 0.61, 95% CI = 0.44 to 0.85, P = 0.004). RPPA screening of cancer signaling proteins showed that ER alpha protein was upregulated in PRDX1 high tumors. Exogenous H2O2 treatment decreased ER alpha protein levels in ER-positive cells. PRDX1 knockdown further sensitized cells to H2O2- and peroxynitrite-mediated effects, whilst PRDX1 overexpression protected against this response. Inhibition of PRDX1/2 antioxidant activity with adenanthin dramatically reduced ER alpha levels in breast cancer cells. Conclusions: PRDX1 is shown to be an independent predictor of improved outcomes in ER-positive breast cancer. Through its antioxidant function, PRDX1 may prevent oxidative stress-mediated ER alpha loss, thereby potentially contributing to maintenance of an ER-positive phenotype in mammary tumors. These results for the first time imply a close connection between biological activity of PRDX1 and regulation of estrogen-mediated signaling in breast cancer.
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| 5. |
- Yoosuf, Niyaz, et al.
(författare)
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Identification and transfer of spatial transcriptomics signatures for cancer diagnosis
- 2020
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Ingår i: Breast Cancer Research. - : BioMed Central. - 1465-5411 .- 1465-542X. ; 22:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Distinguishing ductal carcinoma in situ (DCIS) from invasive ductal carcinoma (IDC) regions in clinical biopsies constitutes a diagnostic challenge. Spatial transcriptomics (ST) is an in situ capturing method, which allows quantification and visualization of transcriptomes in individual tissue sections. In the past, studies have shown that breast cancer samples can be used to study their transcriptomes with spatial resolution in individual tissue sections. Previously, supervised machine learning methods were used in clinical studies to predict the clinical outcomes for cancer types. Methods: We used four publicly available ST breast cancer datasets from breast tissue sections annotated by pathologists as non-malignant, DCIS, or IDC. We trained and tested a machine learning method (support vector machine) based on the expert annotation as well as based on automatic selection of cell types by their transcriptome profiles. Results: We identified expression signatures for expert annotated regions (non-malignant, DCIS, and IDC) and build machine learning models. Classification results for 798 expression signature transcripts showed high coincidence with the expert pathologist annotation for DCIS (100%) and IDC (96%). Extending our analysis to include all 25,179 expressed transcripts resulted in an accuracy of 99% for DCIS and 98% for IDC. Further, classification based on an automatically identified expression signature covering all ST spots of tissue sections resulted in prediction accuracy of 95% for DCIS and 91% for IDC. Conclusions: This concept study suggest that the ST signatures learned from expert selected breast cancer tissue sections can be used to identify breast cancer regions in whole tissue sections including regions not trained on. Furthermore, the identified expression signatures can classify cancer regions in tissue sections not used for training with high accuracy. Expert-generated but even automatically generated cancer signatures from ST data might be able to classify breast cancer regions and provide clinical decision support for pathologists in the future.
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