| 21. |
- Chivukula, Indira V, et al.
(författare)
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Decoding breast cancer tissue-stroma interactions using species-specific sequencing.
- 2015
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- Decoding transcriptional effects of experimental tissue-tissue or cell-cell interactions is important; for example, to better understand tumor-stroma interactions after transplantation of human cells into mouse (xenografting). Transcriptome analysis of intermixed human and mouse cells has, however, frequently relied on the need to separate the two cell populations prior to transcriptome analysis, which introduces confounding effects on gene expression.
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| 22. |
- Clendenen, Tess V., et al.
(författare)
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Breast cancer risk prediction in women aged 35-50 years : impact of including sex hormone concentrations in the Gail model
- 2019
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Ingår i: Breast Cancer Research. - : BioMed Central. - 1465-5411 .- 1465-542X. ; 21
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Tidskriftsartikel (refereegranskat)abstract
- Background: Models that accurately predict risk of breast cancer are needed to help younger women make decisions about when to begin screening. Premenopausal concentrations of circulating anti-Mullerian hormone (AMH), a biomarker of ovarian reserve, and testosterone have been positively associated with breast cancer risk in prospective studies. We assessed whether adding AMH and/or testosterone to the Gail model improves its prediction performance for women aged 35-50.Methods: In a nested case-control study including ten prospective cohorts (1762 invasive cases/1890 matched controls) with pre-diagnostic serum/plasma samples, we estimated relative risks (RR) for the biomarkers and Gail risk factors using conditional logistic regression and random-effects meta-analysis. Absolute risk models were developed using these RR estimates, attributable risk fractions calculated using the distributions of the risk factors in the cases from the consortium, and population-based incidence and mortality rates. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory accuracy of the models with and without biomarkers.Results: The AUC for invasive breast cancer including only the Gail risk factor variables was 55.3 (95% CI 53.4, 57.1). The AUC increased moderately with the addition of AMH (AUC 57.6, 95% CI 55.7, 59.5), testosterone (AUC 56.2, 95% CI 54.4, 58.1), or both (AUC 58.1, 95% CI 56.2, 59.9). The largest AUC improvement (4.0) was among women without a family history of breast cancer.Conclusions: AMH and testosterone moderately increase the discriminatory accuracy of the Gail model among women aged 35-50. We observed the largest AUC increase for women without a family history of breast cancer, the group that would benefit most from improved risk prediction because early screening is already recommended for women with a family history.
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| 23. |
- Cox, David G., et al.
(författare)
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A comprehensive analysis of the androgen receptor gene and risk of breast cancer: results from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3)
- 2006
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 8:5
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Tidskriftsartikel (refereegranskat)abstract
- Introduction Androgens have been hypothesised to influence risk of breast cancer through several possible mechanisms, including their conversion to estradiol or their binding to the oestrogen receptor and/ or androgen receptor ( AR) in the breast. Here, we report on the results of a large and comprehensive study of the association between genetic variation in the AR gene and risk of breast cancer in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium ( BPC3). Methods The underlying genetic variation was determined by first sequencing the coding regions of the AR gene in a panel of 95 advanced breast cancer cases. Second, a dense set of markers from the public database was genotyped in a panel of 349 healthy women. The linkage disequilibrium relationships ( blocks) across the gene were then identified, and haplotypetagging single nucleotide polymorphisms ( htSNPs) were selected to capture the common genetic variation across the locus. The htSNPs were then genotyped in the nested breast cancer cases and controls from the Cancer Prevention Study II, European Prospective Investigation into Cancer and Nutrition, Multiethnic Cohort, Nurses' Health Study, and Women's Health Study cohorts ( 5,603 breast cancer cases and 7,480 controls). Results We found no association between any genetic variation ( SNP, haplotype, or the exon 1 CAG repeat) in the AR gene and risk of breast cancer, nor were any statistical interactions with known breast cancer risk factors observed. Conclusion Among postmenopausal Caucasian women, common variants of the AR gene are not associated with risk of breast cancer.
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| 24. |
- Drabsch, Yvette, et al.
(författare)
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Transforming growth factor-β signalling controls human breast cancer metastasis in a zebrafish xenograft model
- 2013
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 15:6, s. R106-
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: The transforming growth factor beta (TGF-β) signalling pathway is known to control human breast cancer invasion and metastasis. We demonstrate that the zebrafish xenograft assay is a robust and dependable animal model for examining the role of pharmacological modulators and genetic perturbation of TGF-β signalling in human breast tumour cells.METHODS: We injected cancer cells into the embryonic circulation (duct of cuvier) and examined their invasion and metastasis into the avascular collagenous tail. Various aspects of the TGF-β signalling pathway were blocked by chemical inhibition, small interfering RNA (siRNA), or small hairpin RNA (shRNA). Analysis was conducted using fluorescent microscopy.RESULTS: Breast cancer cells with different levels of malignancy, according to in vitro and in vivo mouse studies, demonstrated invasive and metastatic properties within the embryonic zebrafish model that nicely correlated with their differential tumourigenicity in mouse models. Interestingly, MCF10A M2 and M4 cells invaded into the caudal hematopoietic tissue and were visible as a cluster of cells, whereas MDA MB 231 cells invaded into the tail fin and were visible as individual cells. Pharmacological inhibition with TGF-β receptor kinase inhibitors or tumour specific Smad4 knockdown disturbed invasion and metastasis in the zebrafish xenograft model and closely mimicked the results we obtained with these cells in a mouse metastasis model. Inhibition of matrix metallo proteinases, which are induced by TGF-β in breast cancer cells, blocked invasion and metastasis of breast cancer cells.CONCLUSIONS: The zebrafish-embryonic breast cancer xenograft model is applicable for the mechanistic understanding, screening and development of anti-TGF-β drugs for the treatment of metastatic breast cancer in a timely and cost-effective manner.
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| 25. |
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| 26. |
- Duffy, S, et al.
(författare)
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Estimates of overdiagnosis from two trials of mammographic screening for breast cancer
- 2005
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 7:6, s. 258-265
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Tidskriftsartikel (refereegranskat)abstract
- Randomised controlled trials have shown that the policy of mammographic screening confers a substantial and significant reduction in breast cancer mortality. This has often been accompanied, however, by an increase in breast cancer incidence, particularly during the early years of a screening programme, which has led to concerns about overdiagnosis, that is to say, the diagnosis of disease that, if left undetected and therefore untreated, would not become symptomatic. We used incidence data from two randomised controlled trials of mammographic screening, the Swedish Two-county Trial and the Gothenburg Trial, to establish the timing and magnitude of any excess incidence of invasive disease and ductal carcinoma in situ (DCIS) in the study groups, to ascertain whether the excess incidence of DCIS reported early in a screening trial is balanced by a later deficit in invasive disease and provide explicit estimates of the rate of 'real' and non-progressive 'overdiagnosed' tumours from the study groups of the trials. We used a multistate model for overdiagnosis and used Markov Chain Monte Carlo methods to estimate the parameters. After taking into account the effect of lead time, we estimated that less than 5% of cases diagnosed at prevalence screen and less than 1 % of cases diagnosed at incidence screens are being overdiagnosed. Overall, we estimate overdiagnosis to be around 1 % of all cases diagnosed in screened populations. These estimates are, however, subject to considerable uncertainty. Our results suggest that overdiagnosis in mammography screening is a minor phenomenon, but further studies with very large numbers are required for more precise estimation. © 2005 BioMed Central Ltd.
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| 27. |
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| 28. |
- Fortner, Renee T., et al.
(författare)
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Early pregnancy sex steroids during primiparous pregnancies and maternal breast cancer : a nested case-control study in the Northern Sweden Maternity Cohort
- 2017
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 19
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Tidskriftsartikel (refereegranskat)abstract
- Background: Pregnancy and parity are associated with subsequent breast cancer risk. Experimental and epidemiologic data suggest a role for pregnancy sex steroid hormones.Methods: We conducted a nested case–control study in the Northern Sweden Maternity Cohort (1975–2007). Eligible women had provided a blood sample in the first 20 weeks of gestation during a primiparous pregnancy leading to a term delivery. The current study includes 223 cases and 417 matched controls (matching factors: age at and date of blood collection). Estrogen receptor (ER) and progesterone receptor (PR) status was available for all cases; androgen receptor (AR) data were available for 41% of cases (n = 92). Sex steroids were quantified by high-performance liquid chromatography tandem mass spectrometry. Odds ratios (ORs) and 95% confidence intervals were estimated using conditional logistic regression.Results: Higher concentrations of circulating progesterone in early pregnancy were inversely associated with ER+/PR+ breast cancer risk (ORlog2: 0.64 (0.41–1.00)). Higher testosterone was positively associated with ER+/PR+ disease risk (ORlog2: 1.57 (1.13–2.18)). Early pregnancy estrogens were not associated with risk, except for relatively high estradiol in the context of low progesterone (split at median, relative to low concentrations of both; OR: 1.87 (1.11–3.16)). None of the investigated hormones were associated with ER–/PR– disease, or with AR+ or AR+/ER+/PR+ disease.Conclusions: Consistent with experimental models, high progesterone in early pregnancy was associated with lower risk of ER+/PR+ breast cancer in the mother. High circulating testosterone in early pregnancy, which likely reflects nonpregnant premenopausal exposure, was associated with higher risk of ER+/PR+ disease.
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| 29. |
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| 30. |
- Fredlund, Erik, et al.
(författare)
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The gene expression landscape of breast cancer is shaped by tumor protein p53 status and epithelial-mesenchymal transition
- 2012
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 14:4
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Gene expression data derived from clinical cancer specimens provide an opportunity to characterize cancer-specific transcriptional programs. Here, we present an analysis delineating a correlation-based gene expression landscape of breast cancer that identifies modules with strong associations to breast cancer-specific and general tumor biology. Methods: Modules of highly connected genes were extracted from a gene co-expression network that was constructed based on Pearson correlation, and module activities were then calculated using a pathway activity score. Functional annotations of modules were experimentally validated with an siRNA cell spot microarray system using the KPL-4 breast cancer cell line, and by using gene expression data from functional studies. Modules were derived using gene expression data representing 1,608 breast cancer samples and validated in data sets representing 971 independent breast cancer samples as well as 1,231 samples from other cancer forms. Results: The initial co-expression network analysis resulted in the characterization of eight tightly regulated gene modules. Cell cycle genes were divided into two transcriptional programs, and experimental validation using an siRNA screen showed different functional roles for these programs during proliferation. The division of the two programs was found to act as a marker for tumor protein p53 (TP53) gene status in luminal breast cancer, with the two programs being separated only in luminal tumors with functional p53 (encoded by TP53). Moreover, a module containing fibroblast and stroma-related genes was highly expressed in fibroblasts, but was also up-regulated by overexpression of epithelial-mesenchymal transition factors such as transforming growth factor beta 1 (TGF-beta1) and Snail in immortalized human mammary epithelial cells. Strikingly, the stroma transcriptional program related to less malignant tumors for luminal disease and aggressive lymph node positive disease among basal-like tumors. Conclusions: We have derived a robust gene expression landscape of breast cancer that reflects known subtypes as well as heterogeneity within these subtypes. By applying the modules to TP53-mutated samples we shed light on the biological consequences of non-functional p53 in otherwise low-proliferating luminal breast cancer. Furthermore, as in the case of the stroma module, we show that the biological and clinical interpretation of a set of co-regulated genes is subtype-dependent.
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