| 1. |
- 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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| 2. |
- Ljungars, A., et al.
(författare)
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A platform for phenotypic discovery of therapeutic antibodies and targets applied on Chronic Lymphocytic Leukemia
- 2018
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Ingår i: JCO Precision Oncology. - : Springer Science and Business Media LLC. - 2473-4284 .- 2397-768X. ; 2:1
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Tidskriftsartikel (refereegranskat)abstract
- Development of antibody drugs against novel targets and pathways offers great opportunities to improve current cancer treatment. We here describe a phenotypic discovery platform enabling efficient identification of therapeutic antibody-target combinations. The platform utilizes primary patient cells throughout the discovery process and includes methods for differential phage display cell panning, high-throughput cell-based specificity screening, phenotypic in vitro screening, target deconvolution, and confirmatory in vivo screening. In this study the platform was applied on cancer cells from patients with Chronic Lymphocytic Leukemia resulting in discovery of antibodies with improved cytotoxicity in vitro compared to the standard of care, the CD20-specific monoclonal antibody rituximab. Isolated antibodies were found to target six different receptors on Chronic Lymphocytic Leukemia cells; CD21, CD23, CD32, CD72, CD200, and HLA-DR of which CD32, CD200, and HLA-DR appeared as the most potent targets for antibody-based cytotoxicity treatment. Enhanced antibody efficacy was confirmed in vivo using a patient-derived xenograft model.
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