| 1. |
- 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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| 2. |
- 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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| 3. |
- 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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| 4. |
- Harbst, Katja, et al.
(författare)
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Molecular profiling reveals low- and high-grade forms of primary melanoma.
- 2012
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Ingår i: Clinical cancer research : an official journal of the American Association for Cancer Research. - 1557-3265. ; 18:15, s. 4026-4036
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Tidskriftsartikel (refereegranskat)abstract
- For primary melanomas, tumor thickness, mitotic rate, and ulceration are well-laid cornerstones of prognostication. However, a molecular exposition of melanoma aggressiveness is critically missing. We recently uncovered a four-class structure in metastatic melanoma, which predicts outcome and informs biology. This raises the possibility that a molecular structure exists even in the early stages of melanoma and that molecular determinants could underlie histophenotype and eventual patient outcome.We subjected 223 archival primary melanomas to a horizontally integrated analysis of RNA expression, oncogenic mutations at 238 lesions, histomorphometry, and survival data.Our previously described four-class structure that was elucidated in metastatic lesions was evident within the expression space of primary melanomas. Because these subclasses converged into two larger prognostic and phenotypic groups, we used the metastatic lesions to develop a binary subtype-based signature capable of distinguishing between "high" and "low" grade forms of the disease. The two-grade signature was subsequently applied to the primary melanomas. Compared with low-grade tumors, high-grade primary melanomas were significantly associated with increased tumor thickness, mitotic rate, ulceration (all P < 0.01), and poorer relapse-free (HR = 4.94; 95% CI, 2.84-8.59), and overall (HR = 3.66; 95% CI, 2.40-5.58) survival. High-grade melanomas exhibited elevated levels of proliferation and BRCA1/DNA damage signaling genes, whereas low-grade lesions harbored higher expression of immune genes. Importantly, the molecular-grade signature was validated in two external gene expression data sets.We provide evidence for a molecular organization within melanomas, which is preserved across all stages of disease.
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| 5. |
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| 6. |
- Lundgren, Christine, et al.
(författare)
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Agreement between molecular subtyping and surrogate subtype classification : a contemporary population-based study of ER-positive/HER2-negative primary breast cancer
- 2019
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Ingår i: Breast Cancer Research and Treatment. - : SPRINGER. - 0167-6806 .- 1573-7217. ; 178:2, s. 459-467
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Oestrogen receptor-positive (ER+) and human epidermal receptor 2-negative (HER2-) breast cancers are classified as Luminal A or B based on gene expression, but immunohistochemical markers are used for surrogate subtyping. The aims of this study were to examine the agreement between molecular subtyping (MS) and surrogate subtyping and to identify subgroups consisting mainly of Luminal A or B tumours.Methods: The cohort consisted of 2063 patients diagnosed between 2013-2017, with primary ER+/HER2- breast cancer, analysed by RNA sequencing. Surrogate subtyping was performed according to three algorithms (St. Gallen 2013, Maisonneuve and our proposed Grade-based classification). Agreement (%) and kappa statistics (kappa) were used as concordance measures and ROC analysis for luminal distinction. Ki67, progesterone receptor (PR) and histological grade (HG) were further investigated as surrogate markers.Results: The agreement rates between the MS and St. Gallen 2013, Maisonneuve and Grade-based classifications were 62% (kappa = 0.30), 66% (kappa = 0.35) and 70% (kappa = 0.41), respectively. PR did not contribute to distinguishing Luminal A from B tumours (auROC = 0.56). By classifying HG1-2 tumours as Luminal A-like and HG3 as Luminal B-like, agreement with MS was 80% (kappa = 0.46). Moreover, by combining HG and Ki67 status, a large subgroup of patients (51% of the cohort) having > 90% Luminal A tumours could be identified.Conclusions: Agreement between MS and surrogate classifications was generally poor. However, a post hoc analysis showed that a combination of HG and Ki67 could identify patients very likely to have Luminal A tumours according to MS.
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| 7. |
- Olsson, Eleonor, et al.
(författare)
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CD44 isoforms are heterogeneously expressed in breast cancer and correlate with tumor subtypes and cancer stem cell markers.
- 2011
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Ingår i: BMC Cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The CD44 cell adhesion molecule is aberrantly expressed in many breast tumors and has been implicated in the metastatic process as well as in the putative cancer stem cell (CSC) compartment. We aimed to investigate potential associations between alternatively spliced isoforms of CD44 and CSCs as well as to various breast cancer biomarkers and molecular subtypes. METHODS: We used q-RT-PCR and exon-exon spanning assays to analyze the expression of four alternatively spliced CD44 isoforms as well as the total expression of CD44 in 187 breast tumors and 13 cell lines. ALDH1 protein expression was determined by IHC on TMA. RESULTS: Breast cancer cell lines showed a heterogeneous expression pattern of the CD44 isoforms, which shifted considerably when cells were grown as mammospheres. Tumors characterized as positive for the CD44+/CD24- phenotype by immunohistochemistry were associated to all isoforms except the CD44 standard (CD44S) isoform, which lacks all variant exons. Conversely, tumors with strong expression of the CSC marker ALDH1 had elevated expression of CD44S. A high expression of the CD44v2-v10 isoform, which retain all variant exons, was correlated to positive steroid receptor status, low proliferation and luminal A subtype. The CD44v3-v10 isoform showed similar correlations, while high expression of CD44v8-v10 was correlated to positive EGFR, negative/low HER2 status and basal-like subtype. High expression of CD44S was associated with strong HER2 staining and also a subgroup of basal-like tumors. Unsupervised hierarchical cluster analysis of CD44 isoform expression data divided tumors into four main clusters, which showed significant correlations to molecular subtypes and differences in 10-year overall survival. CONCLUSIONS: We demonstrate that individual CD44 isoforms can be associated to different breast cancer subtypes and clinical markers such as HER2, ER and PgR, which suggests involvement of CD44 splice variants in specific oncogenic signaling pathways. Efforts to link CD44 to CSCs and tumor progression should consider the expression of various CD44 isoforms.
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| 8. |
- Staaf, Johan, et al.
(författare)
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Identification of Subtypes in Human Epidermal Growth Factor Receptor 2-Positive Breast Cancer Reveals a Gene Signature Prognostic of Outcome.
- 2010
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Ingår i: Journal of Clinical Oncology. - 1527-7755. ; 28:11, s. 1813-1820
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: Human epidermal growth factor receptor 2 (HER2) gene amplification or protein overexpression (HER2 positivity) defines a clinically challenging subgroup of patients with breast cancer (BC) with variable prognosis and response to therapy. We aimed to investigate the heterogeneous biologic appearance and clinical behavior of HER2-positive tumors using molecular profiling. PATIENTS AND METHODS: Hierarchical clustering of gene expression data from 58 HER2-amplified tumors of various stage, histologic grade, and estrogen receptor (ER) status was used to construct a HER2-derived prognostic predictor that was further evaluated in several large independent BC data sets. RESULTS: Unsupervised analysis identified three subtypes of HER2-positive tumors with mixed stage, histologic grade, and ER status. One subtype had a significantly worse clinical outcome. A prognostic predictor was created based on differentially expressed genes between the subtype with worse outcome and the other subtypes. The predictor was able to define patient groups with better and worse outcome in HER2-positive BC across multiple independent BC data sets and identify a sizable HER2-positive group with long disease-free survival and low mortality. Significant correlation to prognosis was also observed in basal-like, ER-negative, lymph node-positive, and high-grade tumors, irrespective of HER2 status. The predictor included genes associated with immune response, tumor invasion, and metastasis. CONCLUSION: The HER2-derived prognostic predictor provides further insight into the heterogeneous biology of HER2-positive tumors and may become useful for improved selection of patients who need additional treatment with new drugs targeting the HER2 pathway.
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| 9. |
- Staaf, Johan, et al.
(författare)
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RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer
- 2022
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Ingår i: npj Breast Cancer. - : Nature Publishing Group. - 2374-4677. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Multigene assays for molecular subtypes and biomarkers can aid management of early invasive breast cancer. Using RNA-sequencing we aimed to develop single-sample predictor (SSP) models for clinical markers, subtypes, and risk of recurrence (ROR). A cohort of 7743 patients was divided into training and test set. We trained SSPs for subtypes and ROR assigned by nearest-centroid (NC) methods and SSPs for biomarkers from histopathology. Classifications were compared with Prosigna in two external cohorts (ABiM, n = 100 and OSLO2-EMIT0, n = 103). Prognostic value was assessed using distant recurrence-free interval. Agreement between SSP and NC for PAM50 {five subtypes) was high (85%, Kappa = 0.78) for Subtype (four subtypes) very high {90%, Kappa = 0.84) and for ROR risk category high (84%, Kappa = 0.75, weighted Kappa = 0.90). Prognostic value was assessed as equivalent and clinically relevant. Agreement with histopathology was very high or high for receptor status, while moderate for Ki67 status and poor for Nottingham histological grade. SSP and Prosigna concordance was high for subtype (OSLO-EMIT0 83%, Kappa = 0.73 and ABiM 80%, Kappa = 0.72) and moderate and high for ROR risk category (68 and 84%, Kappa = 0.50 and 0.70, weighted Kappa = 0.70 and 0.78). Pooled concordance for emulated treatment recommendation dichotomized for chemotherapy was high (85%, Kappa = 0.66). Retrospective evaluation suggested that SSP application could change chemotherapy recommendations for up to 17% of postmenopausal ER+/HER2-/N0 patients with balanced escalation and de-escalation. Results suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level and that SSP models can be derived to closely match clinical tests.
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