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Träfflista för sökning "WFRF:(Brueffer Christian) ;pers:(Ehinger Anna)"

Sökning: WFRF:(Brueffer Christian) > Ehinger Anna

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  • Brueffer, Christian, et al. (författare)
  • 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
  • Ingår i: Cancer research. Supplement. - 1538-7445. ; 78:4
  • 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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  • Brueffer, Christian, et al. (författare)
  • 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
  • Ingår i: JCO Precision Oncology. - 2473-4284. ; 2, s. 1-18
  • 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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  • Brueffer, Christian, et al. (författare)
  • The Mutational Landscape of the SCAN-B Real-World Primary Breast Cancer Transcriptome
  • 2020
  • 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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  • Brueffer, Christian, et al. (författare)
  • The mutational landscape of the SCAN‐B real‐world primary breast cancer transcriptome
  • 2020
  • Ingår i: EMBO Molecular Medicine. - : EMBO. - 1757-4684 .- 1757-4676. ; 12:10
  • 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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  • Dahlgren, Malin, et al. (författare)
  • Preexisting Somatic Mutations of Estrogen Receptor Alpha (ESR1) in Early-Stage Primary Breast Cancer
  • 2021
  • Ingår i: JNCI Cancer Spectrum. - : Oxford University Press (OUP). - 2515-5091. ; 5:2
  • 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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  • Loman, Niklas, et al. (författare)
  • Abstract P2-02-09: Breast cancer subtype distribution and circulating tumor DNA in response to neoadjuvant chemotherapy: Experiences from a preoperative cohort within SCAN-B
  • 2018
  • Ingår i: Cancer research. Supplement. - 1538-7445. ; 78:4
  • Konferensbidrag (refereegranskat)abstract
    • Introduction: Preoperative chemotherapy in early breast cancer increases the rate of breast preservation and provides prognostic information. In the case of residual disease, a change in subtypes may be observed. Sensitive and reproducible biomarkers predicting treatment response early during the treatment course are needed in order to better exploit the potential benefit of an individualized preoperative treatment.Material and Methods: In an ongoing prospective study within the population-based SCAN-B project (NCT02306096), patients undergoing preoperative chemotherapy for early or locally recurrent breast cancer have been treated with iv Epirubicin and Cyclophosphamide q3w x 3 in sequence with either Docetaxel q3w x 3 or Paclitaxel q1w x 9 with a preoperative intent. HER2-positive cases also received HER2-directed treatment. At baseline, patients were staged using sentinel node biopsy for clinically node-negative patients and CT scan for cytologically confirmed node-positive cases. A clinical core needle biopsy as well as tissue from the surgical specimen was collected for determination of conventional biomarkers including ER, PgR, HER2 and Ki67. Tumor biopsies for biomolecule-extraction and RNA-sequencing were taken using ultrasound guidance and collected fresh in RNAlater at baseline, after 2 treatment cycles, as well as at surgery. Blood plasma samples were collected at baseline, after one-, three-, and six- 3w treatment cycles, and post-surgery. Using RNA-sequencing data, somatic mutations were identified in the tumor biopsies and personalized analyses for circulating tumor DNA (ctDNA) were performed. A pathological complete remission (pCR) was defined as the complete disappearance of invasive breast cancer in the breast and axilla at time of definitive surgery. Subtyping was performed using modified St Gallen criteria (2013).Results: Thus far, 45 patients aged 24-74 years have been included, of which 34 (76 %) were clinical stage 2 and 11 (24%) were stage 3. The subtype distribution at baseline was five Luminal A-like (11 %), 21 Luminal B-like (HER2 negative) (47 %), 8 HER2-positive (18 %) and 11 Triple-negative (ductal) (24 %). The rates of pCR in 38 operated cases to date were 0/3 Luminal A-like, 3/19 Luminal B-like (HER2 negative), 2/8 HER2-positive, and 4/7 Triple-negative (overall 24 % pCR rate). One patient did not undergo surgery due to clinically progressive disease. In 25 cases with evaluable residual disease at surgery, there was a shift in the subtype in 13 (52 %), the majority of which represented a transition from Luminal B to Luminal A. No Triple-negative cases underwent a change in subtype during treatment. Results of the ctDNA analyses will be presented at the meeting.Discussion: We have established an infrastructure allowing for an extensive evaluation of preoperative chemotherapy in early breast cancer. The goal is to develop methods to refine response-guided treatment in early breast cancer using molecular responses in the tumor as well as in the blood circulation. The patients continue to be prospectively monitored with iterative ctDNA analyses during follow-up.
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  • Meng, Pei, et al. (författare)
  • Digital PCR quantification of ultrahigh ERBB2 copy number identifies poor breast cancer survival after trastuzumab
  • 2024
  • Ingår i: npj Breast Cancer. - 2374-4677. ; 10:1
  • Tidskriftsartikel (refereegranskat)abstract
    • HER2/ERBB2 evaluation is necessary for treatment decision-making in breast cancer (BC), however current methods have limitations and considerable variability exists. DNA copy number (CN) evaluation by droplet digital PCR (ddPCR) has complementary advantages for HER2/ERBB2 diagnostics. In this study, we developed a single-reaction multiplex ddPCR assay for determination of ERBB2 CN in reference to two control regions, CEP17 and a copy-number-stable region of chr. 2p13.1, validated CN estimations to clinical in situ hybridization (ISH) HER2 status, and investigated the association of ERBB2 CN with clinical outcomes. 909 primary BC tissues were evaluated and the area under the curve for concordance to HER2 status was 0.93 and 0.96 for ERBB2 CN using either CEP17 or 2p13.1 as reference, respectively. The accuracy of ddPCR ERBB2 CN was 93.7% and 94.1% in the training and validation groups, respectively. Positive and negative predictive value for the classic HER2 amplification and non-amplification groups was 97.2% and 94.8%, respectively. An identified biological “ultrahigh” ERBB2 ddPCR CN group had significantly worse survival within patients treated with adjuvant trastuzumab for both recurrence-free survival (hazard ratio, HR: 3.3; 95% CI 1.1–9.6; p = 0.031, multivariable Cox regression) and overall survival (HR: 3.6; 95% CI 1.1–12.6; p = 0.041). For validation using RNA-seq data as a surrogate, in a population-based SCAN-B cohort (NCT02306096) of 682 consecutive patients receiving adjuvant trastuzumab, the ultrahigh-ERBB2 mRNA group had significantly worse survival. Multiplex ddPCR is useful for ERBB2 CN estimation and ultrahigh ERBB2 may be a predictive factor for decreased long-term survival after trastuzumab treatment.
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