| 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. |
- Ehinger, Anna, et al.
(författare)
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Myoepithelium assessment with p63 immunostaining in formalinfixed paraffin-embedded breast cancer tissue pre-treated with RNA-later
- 2017
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Ingår i: Virchows Archiv. - : Springer Science and Business Media LLC. - 1432-2307 .- 0945-6317. ; 471:Supplement 1, s. 299-299
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Konferensbidrag (refereegranskat)abstract
- Objective: To assessmyoepithelium with p63 in fresh breast cancer (BC)tissue samples collected in RNA later for further analysis with NextGeneration Sequencing (NGS) technique. For a better understanding ofthe NGS bulk-analysis, a central part of the sample in RNA-later isformalin-fixed paraffin-embedded to score relative cellularity in % onhematoxylin-eosin (HE) staining (% of invasive cancer, cancer in situ,benign epithelium, lymphocytes and fat). Our aim is hence to test p63immunohistochemistry (IHC) to highlight myoepithelium and to facilitatethe evaluation of the relative cellularity on BC-tissue pre-treated withRNA-later.Method: Two-hundred and twenty-four selected samples of fresh BCtissue collected in RNA-later. A 10 mg central piece from each samplewas FFPE and assembled in a tissue-microarray (TMA) and sectioned toHE and p63 IHC.Results: All samples (n = 224) had internal control for myoepitheliumsurrounding in situ cancer or benign epithelium. p63 showed positivenuclear staining in myoepithelial cells in 92 % (206/224) of samplesand false negative p63 staining in 8 % (18/224).Conclusion: p63 IHC is assessable in samples of FFPE BC-tissue pretreatedwith RNA-later.
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| 5. |
- Häkkinen, Jari, et al.
(författare)
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Implementation of an Open Source Software solution for Laboratory Information Management and automated RNAseq data analysis in a large-scale Cancer Genomics initiative using BASE with extension package Reggie.
- 2016
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- BackgroundLarge-scale cancer genomics initiatives and next-generation sequencing for transcriptome profiling allow for detailed molecular characterization of tumors, and provide opportunities for clinical tools to improve diagnosis, prognosis, and treatment decisions. Laboratory information, data management, and data sharing in large-scale genomics projects is a challenge. Aiming to introduce such technologies in a clinical setting offer additional challenges associated with requirements of short lead-times and specialized tracking of biomaterials, data, and analysis results.ResultsUsing the free open-source BioArray Software Environment (BASE) and extension package Reggie we have implemented a laboratory information management system and an automated RNAseq data analysis pipeline that successfully manage a large regional cancer genomics initiative. The system manages enrolled cancer patients, tumor biopsies, extraction of nucleic acid, and whole transcriptome RNA-sequencing through to data analysis and quality control. The implementation offers integration of laboratory equipment and operating procedures, and information tracking in a module based fashion enabling efficient and flexible use of personnel resources. The system provides two-factor authentication and transaction control and seamless integration of freely available software for RNAseq analysis such as Tophat, Cufflinks, and Picard. As of February 2016 more than 8000 patients and over 6000 tumor biopsies have been successfully processed. Lead-time from biopsy arrival to summarized reports based on RNAseq data is less than 5 days, in line with regional clinical requirements. BASE and Reggie are freely available and released as open-source under the GNU General Public License and GNU Affero General Public License, respectively.ConclusionUsing free open-source software together with BASE and a customized extension package, Reggie, we have implemented a system capable of managing large collections of quality controlled and curated material for use in research and development and tailored to meet requirements for clinical use. Featuring high degree of automation and interactivity the system allows for resource efficient laboratory procedures and short lead-times with demonstrated use of RNAseq data analyses in a clinical setting.
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| 6. |
- Loman, Niklas, et al.
(författare)
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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
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Ingår i: Cancer research. Supplement. - 1538-7445. ; 78:4
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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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| 7. |
- 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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| 8. |
- Morgan, G, et al.
(författare)
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Abstract P3-02-02: Concordance between immunohistochemical and gene-expression based subtyping of early breast cancer using core needle biopsies and surgical specimens - experices from SCAN-B
- 2018
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Ingår i: Cancer research. Supplement. - 1538-7445. ; 78:4
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Konferensbidrag (refereegranskat)abstract
- Introduction: Preoperative chemotherapy in early breast cancer increases the rate of breast preservation and provides prognostic information. Treatment decisions in these cases rely on biomarker assessments and subtyping from tissue acquired through core needle biopsies. Tumor heterogeneity and representativity are pit-falls when limited tissue is available. Biomarker expression may change considerably as a result of preoperative chemotherapy, and in a subset of cases a complete pathological response at time of surgery may even preclude any further assessment. Therefore, the reliability and reproducibility of biomarkers in base-line core biopsies are of utmost importance for patients treated with preoperative chemotherapy.Material and Methods: In an ongoing population-based study of early breast cancer, the SCAN-B (NCT02306096), patients were identified for whom an ultra-sound guided core needle biopsy was analyzed for biomarkers during primary clinical work-up and the patient was offered primary surgery as initial treatment. Clinical biomarker profiles including immunohistochemical (IHC) determinations of ER, PgR, HER2 and Ki67 were translated to subtypes according to modified St Gallen criteria (2013) and compared with paired samples from surgical specimens. In addition, tumor specimens for biomolecule extraction and RNA sequencing were collected fresh in RNAlater.Results: IHC data was available from 51 paired samples. The subtype distribution in core needle biopsies was DCIS in 1 case (2 %), LCIS in 1 case (2 %) Luminal A-like in 16 cases (31 %), Luminal B-like (HER2 negative) in 26 cases (51 %), Luminal B-HER2-like (HER2 positive) in 4 cases (8 %), HER2-positive (non-luminal) in 1 case (2 %) and triple negative (ductal) breast cancer in 2 cases (4 %). The subtype distribution in surgical specimens was DCIS in 0 case (0 %), LCIS in 1 case (2 %) Luminal A-like in 18 cases (35 %), Luminal B-like (HER2negative) in 23 cases (45 %), Luminal B--like (HER2 positive) in 6 cases (12 %), HER2-positive (non-luminal) in 1 case (2 %) and triple negative (ductal) breast cancer in 2 cases (4 %). Notably, 5/16 cases classified as Luminal A-like in the core needle biopsy were reclassified as Luminal B-like (HER2-negative) in the surgical specimen, whereas 9/26 cases classified as Luminal B-like (HER2-negative) in the core needle biopsy were reclassified as either Luminal A-like (7 cases) or Luminal B-like (HER2 positive) (2 cases) in the surgical specimen. In all instances, except one, transition between Luminal A-like and Luminal B-like was due to recorded Ki67 expression. One case that was classified as a DCIS in the core needle was reclassified as Luminal B-like (HER2 negative) at time of surgery.Discussion: In this limited material, discordance between evaluations regarding Luminal A-like and Luminal B-like was considerable. Especially the misclassification of primary HER2-positive breast cancer needs further evaluation. These findings may be caused by tumor heterogeneity, and highlight the risk of both over- and under-treatment upon biomarker assessment from core needle biopsies. Data from gene expression based subtype classifications will be presented during the meeting.
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| 9. |
- Persson, Helena, et al.
(författare)
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Frequent miRNA-convergent fusion gene events in breast cancer
- 2017
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Studies of fusion genes have mainly focused on the formation of fusions that result in the production of hybrid proteins or, alternatively, on promoter-switching events that put a gene under the control of aberrant signals. However, gene fusions may also disrupt the transcriptional control of genes that are encoded in introns downstream of the breakpoint. By ignoring structural constraints of the transcribed fusions, we highlight the importance of a largely unexplored function of fusion genes. Here, we show, using breast cancer as an example, that miRNA host genes are specifically enriched in fusion genes and that many different, low-frequency, 5 partners may deregulate the same miRNA irrespective of the coding potential of the fusion transcript. These results indicate that the concept of recurrence, defined by the rate of functionally important aberrations, needs to be revised to encompass convergent fusions that affect a miRNA independently of transcript structure and protein-coding potential.
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| 10. |
- Phung, Bengt, et al.
(författare)
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The X-Linked DDX3X RNA Helicase Dictates Translation Reprogramming and Metastasis in Melanoma
- 2019
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Ingår i: Cell Reports. - : Elsevier BV. - 2211-1247. ; 27:12, s. 7-3586
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Tidskriftsartikel (refereegranskat)abstract
- The X-linked DDX3X gene encodes an ATP-dependent DEAD-box RNA helicase frequently altered in various human cancers, including melanomas. Despite its important roles in translation and splicing, how DDX3X dysfunction specifically rewires gene expression in melanoma remains completely unknown. Here, we uncover a DDX3X-driven post-transcriptional program that dictates melanoma phenotype and poor disease prognosis. Through an unbiased analysis of translating ribosomes, we identified the microphthalmia-associated transcription factor, MITF, as a key DDX3X translational target that directs a proliferative-to-metastatic phenotypic switch in melanoma cells. Mechanistically, DDX3X controls MITF mRNA translation via an internal ribosome entry site (IRES) embedded within the 5' UTR. Through this exquisite translation-based regulatory mechanism, DDX3X steers MITF protein levels dictating melanoma metastatic potential in vivo and response to targeted therapy. Together, these findings unravel a post-transcriptional layer of gene regulation that may provide a unique therapeutic vulnerability in aggressive male melanomas.
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