| 1. |
- Bjarnadottir, Olöf, et al.
(författare)
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Targeting HMG-CoA reductase with statins in a window-of-opportunity breast cancer trial
- 2013
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Ingår i: Breast Cancer Research and Treatment. - : Springer Science and Business Media LLC. - 0167-6806 .- 1573-7217. ; 138:2, s. 499-508
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Tidskriftsartikel (refereegranskat)abstract
- Lipophilic statins purportedly exert anti-tumoral effects on breast cancer by decreasing proliferation and increasing apoptosis. HMG-CoA reductase (HMGCR), the rate-limiting enzyme of the mevalonate pathway, is the target of statins. However, data on statin-induced effects on HMGCR activity in cancer are limited. Thus, this pre-operative study investigated statin-induced effects on tumor proliferation and HMGCR expression while analyzing HMGCR as a predictive marker for statin response in breast cancer treatment. The study was designed as a window-of-opportunity trial and included 50 patients with primary invasive breast cancer. High-dose atorvastatin (i.e., 80 mg/day) was prescribed to patients for 2 weeks before surgery. Pre- and post-statin paired tumor samples were analyzed for Ki67 and HMGCR immunohistochemical expression. Changes in the Ki67 expression and HMGCR activity following statin treatment were the primary and secondary endpoints, respectively. Up-regulation of HMGCR following atorvastatin treatment was observed in 68 % of the paired samples with evaluable HMGCR expression (P = 0.0005). The average relative decrease in Ki67 expression following atorvastatin treatment was 7.6 % (P = 0.39) in all paired samples, whereas the corresponding decrease in Ki67 expression in tumors expressing HMGCR in the pre-treatment sample was 24 % (P = 0.02). Furthermore, post-treatment Ki67 expression was inversely correlated to post-treatment HMGCR expression (rs = -0.42; P = 0.03). Findings from this study suggest that HMGCR is targeted by statins in breast cancer cells in vivo, and that statins may have an anti-proliferative effect in HMGCR-positive tumors. Future studies are needed to evaluate HMGCR as a predictive marker for the selection of breast cancer patients who may benefit from statin treatment.
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| 2. |
- Brueffer, Christian, et al.
(författare)
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Abstract P4-09-03: On the development and clinical value of RNA-sequencing-based classifiers for prediction of the five conventional breast cancer biomarkers: A report from the population-based multicenter SCAN-B study
- 2018
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Ingår i: Cancer research. Supplement. - 1538-7445. ; 78:4
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Konferensbidrag (refereegranskat)abstract
- Background:In early breast cancer, five histopathological biomarkers are part of current clinical routines and used for determining prognosis and treatment: estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (ERBB2/HER2), Ki67, and Nottingham histological grade (NHG). We aimed to develop classifiers for these biomarkers based on tumor mRNA-sequencing (RNA-seq), compare classification performance to conventional histopathology, and test whether RNA-seq-based predictors could add value for patient risk-stratification.Patients and Methods:In total, 3678 breast tumors were studied. For 405 breast tumors in the training cohort, a comprehensive histopathological biomarker evaluation was performed by three pathology readings to estimate inter-pathologist variability on the original diagnostic slides as well as on repeat immunostains for this study, and the consensus biomarker status for all five conventional biomarkers was determined. Whole transcriptome gene expression profiling was performed by RNA-sequencing on the Illumina platform. Using RNA-seq-derived tumor gene expression data as input, single-gene classifiers (SGC) and multi-gene classifiers (MGC) were trained on the consensus pathology biomarker labels. The trained classifiers were tested on an independent prospective population-based series of 3273 primary breast cancer cases from the multicenter SCAN-B study with median 41 months follow-up (ClinicalTrials.gov identifier NCT02306096), and classifications were evaluated by agreement statistics and by Kaplan-Meier and Cox regression survival analyses.Results:For the histopathological evaluation, pathologist evaluation concordance was high for ER, PgR, and HER2 (average kappa values of .920, .891, and .899, respectively), but moderate for Ki67 and NHG (.734 and .581). Classification concordance between RNA-seq classifiers and histopathology for the independent 3273-cohort was similar to that within histopathology assessments, with SGCs slightly outperforming MGCs. Importantly, patients with discordant results, classified as hormone responsive (HoR+) by histopathology but non-hormone responsive by MGC, presented with significantly inferior overall survival compared to patients with concordant results. These results extended to patients with no adjuvant systemic therapy (hazard ratio, HR, 4.54; 95% confidence interval, CI, 1.42-14.5), endocrine therapy alone (HR 3.46; 95% CI, 2.01-5.95), or receiving chemotherapy (HR 2.57; 95% CI 1.13-5.86). For HoR+ cases receiving endocrine therapy alone, the MGC HoR classifier remained significant after multivariable adjustment (HR 3.14; 95% CI, 1.75-5.65).Conclusions:RNA-seq-based classifiers for the five key early breast cancer biomarkers were generally equivalent to conventional histopathology with regards to classification error rate. However, when benchmarked using overall survival, our RNA-seq classifiers provided added clinical value in particular for cases that are determined by histopathology to be hormone-responsive but by RNA-seq appear hormone-insensitive and have a significantly poorer outcome when treated with endocrine therapy alone
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| 3. |
- Brueffer, Christian, et al.
(författare)
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Clinical Value of RNA Sequencing–Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network—Breast Initiative
- 2018
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Ingår i: JCO Precision Oncology. - 2473-4284. ; 2, s. 1-18
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Tidskriftsartikel (refereegranskat)abstract
- PurposeIn early breast cancer (BC), five conventional biomarkers—estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), Ki67, and Nottingham histologic grade (NHG)—are used to determine prognosis and treatment. We aimed to develop classifiers for these biomarkers that were based on tumor mRNA sequencing (RNA-seq), compare classification performance, and test whether such predictors could add value for risk stratification.MethodsIn total, 3,678 patients with BC were studied. For 405 tumors, a comprehensive multi-rater histopathologic evaluation was performed. Using RNA-seq data, single-gene classifiers and multigene classifiers (MGCs) were trained on consensus histopathology labels. Trained classifiers were tested on a prospective population-based series of 3,273 BCs that included a median follow-up of 52 months (Sweden Cancerome Analysis Network—Breast [SCAN-B], ClinicalTrials.gov identifier: NCT02306096), and results were evaluated by agreement statistics and Kaplan-Meier and Cox survival analyses.ResultsPathologist concordance was high for ER, PgR, and HER2 (average κ, 0.920, 0.891, and 0.899, respectively) but moderate for Ki67 and NHG (average κ, 0.734 and 0.581). Concordance between RNA-seq classifiers and histopathology for the independent cohort of 3,273 was similar to interpathologist concordance. Patients with discordant classifications, predicted as hormone responsive by histopathology but non–hormone responsive by MGC, had significantly inferior overall survival compared with patients who had concordant results. This extended to patients who received no adjuvant therapy (hazard ratio [HR], 3.19; 95% CI, 1.19 to 8.57), or endocrine therapy alone (HR, 2.64; 95% CI, 1.55 to 4.51). For cases identified as hormone responsive by histopathology and who received endocrine therapy alone, the MGC hormone-responsive classifier remained significant after multivariable adjustment (HR, 2.45; 95% CI, 1.39 to 4.34).ConclusionClassification error rates for RNA-seq–based classifiers for the five key BC biomarkers generally were equivalent to conventional histopathology. However, RNA-seq classifiers provided added clinical value in particular for tumors determined by histopathology to be hormone responsive but by RNA-seq to be hormone insensitive.
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| 4. |
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| 5. |
- Brueffer, Christian, et al.
(författare)
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The Mutational Landscape of the SCAN-B Real-World Primary Breast Cancer Transcriptome
- 2020
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Breast cancer is a disease of genomic alterations, of which the complete panorama of somatic mutations and how these relate to molecular subtypes and therapy response is incompletely understood. Within the Sweden Cancerome Analysis Network–Breast project (SCAN-B; ClinicalTrials.govNCT02306096), an ongoing study elucidating the tumor transcriptomic profiles for thousands of breast cancers prospectively, we developed an optimized pipeline for detection of single nucleotide variants and small insertions and deletions from RNA sequencing (RNA-seq) data, and profiled a large real-world population-based cohort of 3,217 breast tumors. We use it to describe the mutational landscape of primary breast cancer viewed through the transcriptome of a large population-based cohort of patients, and relate it to patient overall survival. We demonstrate that RNA-seq can be used to call mutations in important breast cancer genes such asPIK3CA,TP53, andERBB2, as well as the status of key molecular pathways and tumor mutational burden, and identify potentially druggable genes in 86.8% percent of tumors. To make this rich and growing mutational portraiture of breast cancer available for the wider research community, we developed an open source web-based application, the SCAN-B MutationExplorer, accessible athttp://oncogenomics.bmc.lu.se/MutationExplorer. These results add another dimension to the use of RNA-seq as a potential clinical tool, where both gene expression-based and gene mutation-based biomarkers can be interrogated simultaneously and in real-time within one week of tumor sampling.
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| 6. |
- Brueffer, Christian, et al.
(författare)
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The mutational landscape of the SCAN‐B real‐world primary breast cancer transcriptome
- 2020
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Ingår i: EMBO Molecular Medicine. - : EMBO. - 1757-4684 .- 1757-4676. ; 12:10
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Tidskriftsartikel (refereegranskat)abstract
- Breast cancer is a disease of genomic alterations, of which the panorama of somatic mutations and how these relate to subtypes and therapy response is incompletely understood. Within SCAN‐B (ClinicalTrials.gov: NCT02306096), a prospective study elucidating the transcriptomic profiles for thousands of breast cancers, we developed a RNA‐seq pipeline for detection of SNVs/indels and profiled a real‐world cohort of 3,217 breast tumors. We describe the mutational landscape of primary breast cancer viewed through the transcriptome of a large population‐based cohort and relate it to patient survival. We demonstrate that RNA‐seq can be used to call mutations in genes such as PIK3CA, TP53, and ERBB2, as well as the status of molecular pathways and mutational burden, and identify potentially druggable mutations in 86.8% of tumors. To make this rich dataset available for the research community, we developed an open source web application, the SCAN‐B MutationExplorer (http://oncogenomics.bmc.lu.se/MutationExplorer). These results add another dimension to the use of RNA‐seq as a clinical tool, where both gene expression‐ and mutation‐based biomarkers can be interrogated in real‐time within 1 week of tumor sampling.
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| 7. |
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| 8. |
- Dahlgren, Malin, et al.
(författare)
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Preexisting Somatic Mutations of Estrogen Receptor Alpha (ESR1) in Early-Stage Primary Breast Cancer
- 2021
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Ingår i: JNCI Cancer Spectrum. - : Oxford University Press (OUP). - 2515-5091. ; 5:2
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Tidskriftsartikel (refereegranskat)abstract
- More than three-quarters of primary breast cancers are positive for estrogen receptor alpha (ER; encoded by the gene ESR1), the most important factor for directing anti-estrogenic endocrine therapy (ET). Recently, mutations in ESR1 were identified as acquired mechanisms of resistance to ET, found in 12% to 55% of metastatic breast cancers treated previously with ET. We analyzed 3217 population-based invasive primary (nonmetastatic) breast cancers (within the SCAN-B study, ClinicalTrials.gov NCT02306096), sampled from initial diagnosis prior to any treatment, for the presence of ESR1 mutations using RNA sequencing. Mutations were verified by droplet digital polymerase chain reaction on tumor and normal DNA. Patient outcomes were analyzed using Kaplan-Meier estimation and a series of 2-factor Cox regression multivariable analyses. We identified ESR1 resistance mutations in 30 tumors (0.9%), of which 29 were ER positive (1.1%). In ET-treated disease, presence of ESR1 mutation was associated with poor relapse-free survival and overall survival (2-sided log-rank test P < .001 and P = .008, respectively), with hazard ratios of 3.00 (95% confidence interval = 1.56 to 5.88) and 2.51 (95% confidence interval = 1.24 to 5.07), respectively, which remained statistically significant when adjusted for other prognostic factors. These population-based results indicate that ESR1 mutations at diagnosis of primary breast cancer occur in about 1% of women and identify for the first time in the adjuvant setting that such preexisting mutations are associated to eventual resistance to standard hormone therapy. If replicated, tumor ESR1 screening should be considered in ER-positive primary breast cancer, and for patients with mutated disease, ER degraders such as fulvestrant or other therapeutic options may be considered as more appropriate.
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| 9. |
- Dihge, Looket, et al.
(författare)
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Prediction of lymph node metastasis in breast cancer by gene expression and clinicopathological models: Development and validation within a population based cohort.
- 2019
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Ingår i: Clinical Cancer Research. - 1078-0432. ; 25:21, s. 6368-6381
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: More than 70% of patients with breast cancer present with node-negative disease, yet all undergo surgical axillary staging. We aimed to define predictors of nodal metastasis using clinicopathological characteristics (CLINICAL), gene expression data (GEX), and mixed features (MIXED) and to identify patients at low risk of metastasis who might be spared sentinel lymph node biopsy (SLNB).Experimental Design: Breast tumors (n = 3,023) from the population-based Sweden Cancerome Analysis Network–Breast initiative were profiled by RNA sequencing and linked to clinicopathologic characteristics. Seven machine-learning models present the discriminative ability of N0/N+ in development (n = 2,278) and independent validation cohorts (n = 745) stratified as ER+HER2−, HER2+, and TNBC. Possible SLNB reduction rates are proposed by applying CLINICAL and MIXED predictors.Results: In the validation cohort, the MIXED predictor showed the highest area under ROC curves to assess nodal metastasis; AUC = 0.72. For the subgroups, the AUCs for MIXED, CLINICAL, and GEX predictors ranged from 0.66 to 0.72, 0.65 to 0.73, and 0.58 to 0.67, respectively. Enriched proliferation metagene and luminal B features were noticed in node-positive ER+HER2− and HER2+ tumors, while upregulated basal-like features were observed in node-negative TNBC tumors. The SLNB reduction rates in patients with ER+HER2− tumors were 6% to 7% higher for the MIXED predictor compared with the CLINICAL predictor accepting false negative rates of 5% to 10%.Conclusions: Although CLINICAL and MIXED predictors of nodal metastasis had comparable accuracy, the MIXED predictor identified more node-negative patients. This translational approach holds promise for development of classifiers to reduce the rates of SLNB for patients at low risk of nodal involvement.
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| 10. |
- Förnvik, Daniel, et al.
(författare)
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Detection of circulating tumor cells and circulating tumor DNA before and after mammographic breast compression in a cohort of breast cancer patients scheduled for neoadjuvant treatment
- 2019
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Ingår i: Breast Cancer Research and Treatment. - : Springer Science and Business Media LLC. - 1573-7217 .- 0167-6806. ; 177:2, s. 447-455
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Tidskriftsartikel (refereegranskat)abstract
- PurposeIt is not known if mammographic breast compression of a primary tumor causes shedding of tumor cells into the circulatory system. Little is known about how the detection of circulating biomarkers such as circulating tumor cells (CTCs) or circulating tumor DNA (ctDNA) is affected by breast compression intervention.MethodsCTCs and ctDNA were analyzed in blood samples collected before and after breast compression in 31 patients with primary breast cancer scheduled for neoadjuvant therapy. All patients had a central venous access to allow administration of intravenous neoadjuvant chemotherapy, which enabled blood collection from superior vena cava, draining the breasts, in addition to sampling from a peripheral vein.ResultsCTC and ctDNA positivity was seen in 26% and 65% of the patients, respectively. There was a significant increase of ctDNA after breast compression in central blood (p = 0.01), not observed in peripheral testing. No increase related with breast compression was observed for CTC. ctDNA positivity was associated with older age (p = 0.05), and ctDNA increase after breast compression was associated with high Ki67 proliferating tumors (p = 0.04). CTCs were more abundant in central compared to peripheral blood samples (p = 0.04).ConclusionsThere was no significant release of CTCs after mammographic breast compression but more CTCs were present in central compared to peripheral blood. No significant difference between central and peripheral levels of ctDNA was observed. The small average increase in ctDNA after breast compression is unlikely to be clinically relevant. The results give support for mammography as a safe procedure from the point of view of CTC and ctDNA shedding to the blood circulation. The results may have implications for the standardization of sampling procedures for circulating tumor markers.
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