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  • Föregående 123456[7]
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  • Staaf, Johan, et al. (författare)
  • Abstract P1-06-01: Putting multigene signatures to the test: Prognostic assessment in population-based contemporary clinical breast cancer
  • 2018
  • Ingår i: Cancer research. Supplement. - American Association for Cancer Research Inc.. - 1538-7445. ; 78:4
  • Konferensbidrag (refereegranskat)abstract
    • Abstract Background Gene expression signatures hold promise for a molecularly driven division of primary breast cancer with clinical implications. A gap still remains in the application/validation of such signatures in actual clinical treatment groups from unselected, population-based, primary breast cancer receiving current standard of care therapy. We analyzed classification proportions and overall survival (OS) of 14 reported gene expression phenotypes (GEPs) and risk predictors (RPs) in seven clinical treatments groups from an 3273-sample breast cancer cohort representative of population-based disease in the South Swedish healthcare region. Patients and methods Between 2010-09-01 to 2015-03-31, 5101 (87%) of 5892 patients with invasive primary disease in the healthcare region were included in the SCAN-B study (ClinicalTrials.gov ID: NCT02306096). Inclusion criteria included no generalized/prior contralateral disease and known surgery/treatment status (neo- or adjuvant). 3273 tumors were profiled by RNA sequencing and matched to clinicopathological patient data from the National Breast Cancer Register, with distribution of clinicopathological characteristics reflecting proportions in the catchment region. RNA profiles were classified according to 14 reported gene signatures featuring both GEPs (PAM50, IC10, CIT, TNBCtype) and specific risk predictors (e.g. Oncotype Dx, 70-gene, 76-gene, ROR-variants, genomic grade index). Classifications were investigated for association with patient OS by univariate and multivariate analyses in seven adjuvant clinical treatment groups: TNBC-ACT (adjuvant chemotherapy, n=228), TNBC-untreated (n=83), HER2+/ER- with trastuzumab + ACT treatment (n=101), HER2+/ER+ with trastuzumab + ACT + endocrine treatment (n=210), ER+/HER2- with endocrine treatment (n=1477), ER+/HER2- with endocrine + ACT treatment (n=637), and ER+/HER2- untreated (n=216). Results For the majority of signatures, analysis of classification demonstrated prognostic value limited to ER+/HER2- tumors given follow-up time. Several signatures (including Oncotype Dx, 70-gene, ROR-variants) showed strong predictive value in identifying a subset of ER+/HER2- patients receiving a combination of endocrine and ACT therapy with excellent overall survival (>96%), indicating appropriate therapy selection. In addition, for both ER+/HER2- treatment groups signature analysis identified high-risk groups of patients in clear need of additional treatment beyond standard therapeutic regimes, even with less than 5-years of follow-up. Conclusions Our results support the prognostic association of gene expression signatures in large unselected population-based primary breast cancer cohorts even with a short follow-up of OS.Importantly, prognostic associations are limited to specific subgroups for different classifiers and in population-based breast cancer some clinically important subgroups constitute a small proportion of cases. In this context, continued population-based inclusion and broad transcriptional profiling of breast cancer patients provides an opportunity for application to broader patient groups (e.g. TNBC and HER2+), and for consensus classification of individual risk assessments that could potentially provide more stable predictions.
  • Staaf, Johan, et al. (författare)
  • Whole-genome sequencing of triple-negative breast cancers in a population-based clinical study
  • 2019
  • Ingår i: Nature Medicine. - Nature Publishing Group. - 1546-170X. ; 25, s. 1526-1533
  • Tidskriftsartikel (refereegranskat)abstract
    • Whole-genome sequencing (WGS) brings comprehensive insights to cancer genome interpretation. To explore the clinical value of WGS, we sequenced 254 triple-negative breast cancers (TNBCs) for which associated treatment and outcome data were collected between 2010 and 2015 via the population-based Sweden Cancerome Analysis Network-Breast (SCAN-B) project (ClinicalTrials.gov ID:NCT02306096). Applying the HRDetect mutational-signature-based algorithm to classify tumors, 59% were predicted to have homologous-recombination-repair deficiency (HRDetect-high): 67% explained by germline/somatic mutations of BRCA1/BRCA2, BRCA1 promoter hypermethylation, RAD51C hypermethylation or biallelic loss of PALB2. A novel mechanism of BRCA1 abrogation was discovered via germline SINE-VNTR-Alu retrotransposition. HRDetect provided independent prognostic information, with HRDetect-high patients having better outcome on adjuvant chemotherapy for invasive disease-free survival (hazard ratio (HR) = 0.42; 95% confidence interval (CI) = 0.2-0.87) and distant relapse-free interval (HR = 0.31, CI = 0.13-0.76) compared to HRDetect-low, regardless of whether a genetic/epigenetic cause was identified. HRDetect-intermediate, some possessing potentially targetable biological abnormalities, had the poorest outcomes. HRDetect-low cancers also had inadequate outcomes: ~4.7% were mismatch-repair-deficient (another targetable defect, not typically sought) and they were enriched for (but not restricted to) PIK3CA/AKT1 pathway abnormalities. New treatment options need to be considered for now-discernible HRDetect-intermediate and HRDetect-low categories. This population-based study advocates for WGS of TNBC to better inform trial stratification and improve clinical decision-making.
  • Ståhl, Patrik L., et al. (författare)
  • Visualization and analysis of gene expression in tissue sections by spatial transcriptomics
  • 2016
  • Ingår i: Science. - American Association for the Advancement of Science. - 0036-8075. ; 353:6294, s. 78-82
  • Forskningsöversikt (refereegranskat)abstract
    • Analysis of the pattern of proteins or messenger RNAs (mRNAs) in histological tissue sections is a cornerstone in biomedical research and diagnostics.This typically involves the visualization of a few proteins or expressed genes at a time. We have devised a strategy, which we call "spatial transcriptomics," that allows visualization and quantitative analysis of the transcriptome with spatial resolution in individual tissue sections. By positioning histological sections on arrayed reverse transcription primers with unique positional barcodes, we demonstrate high-quality RNA-sequencing data with maintained two-dimensional positional information from the mouse brain and human breast cancer. Spatial transcriptomics provides quantitative gene expression data and visualization of the distribution of mRNAs within tissue sections and enables novel types of bioinformatics analyses, valuable in research and diagnostics.
  • Sökilde, Rolf, et al. (författare)
  • Passenger strand loading in overexpression experiments using microRNA mimics.
  • 2015
  • Ingår i: RNA Biology. - Taylor & Francis. - 1547-6286. ; 12:8, s. 787-791
  • Tidskriftsartikel (refereegranskat)abstract
    • MicroRNAs (miRNAs) are important regulators of gene function and manipulation of miRNAs is a central component of basic research. Modulation of gene expression by miRNA gain-of-function can be based on different approaches including transfection with miRNA mimics; artificial, chemically modified miRNA-like small RNAs. These molecules are intended to mimic the function of a miRNA guide strand while bypassing the maturation steps of endogenous miRNAs. Due to easy accessibility through commercial providers this approach has gained popularity, and accuracy is often assumed without prior independent testing. Our in silico analysis of over-represented sequence motifs in microarray expression data and sequencing of AGO-associated small RNAs indicate, however, that miRNA mimics may be associated with considerable side-effects due to the unwanted activity of the miRNA mimic complementary strand.
  • Søkilde, Rolf, et al. (författare)
  • Refinement of breast cancer molecular classification by miRNA expression profiles
  • 2019
  • Ingår i: BMC Genomics. - BMC Genomics. - 1471-2164. ; 20:1
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Accurate classification of breast cancer using gene expression profiles has contributed to a better understanding of the biological mechanisms behind the disease and has paved the way for better prognostication and treatment prediction.RESULTS: We found that miRNA profiles largely recapitulate intrinsic subtypes. In the case of HER2-enriched tumors a small set of miRNAs including the HER2-encoded mir-4728 identifies the group with very high specificity. We also identified differential expression of the miR-99a/let-7c/miR-125b miRNA cluster as a marker for separation of the Luminal A and B subtypes. High expression of this miRNA cluster is linked to better overall survival among patients with Luminal A tumors. Correlation between the miRNA cluster and their precursor LINC00478 is highly significant suggesting that its expression could help improve the accuracy of present day's signatures.CONCLUSIONS: We show here that miRNA expression can be translated into mRNA profiles and that the inclusion of miRNA information facilitates the molecular diagnosis of specific subtypes, in particular the clinically relevant sub-classification of luminal tumors.
  • Tang, Man-Hung Eric, et al. (författare)
  • Remarkable similarities of chromosomal rearrangements between primary human breast cancers and matched distant metastases as revealed by whole-genome sequencing.
  • 2015
  • Ingår i: Oncotarget. - Impact Journals, LLC. - 1949-2553. ; 6:35, s. 37169-37184
  • Tidskriftsartikel (refereegranskat)abstract
    • To better understand and characterize chromosomal structural variation during breast cancer progression, we enumerated chromosomal rearrangements for 11 patients by performing low-coverage whole-genome sequencing of 11 primary breast tumors and their 13 matched distant metastases. The tumor genomes harbored a median of 85 (range 18-404) rearrangements per tumor, with a median of 82 (26-310) in primaries compared to 87 (18-404) in distant metastases. Concordance between paired tumors from the same patient was high with a median of 89% of rearrangements shared (range 61-100%), whereas little overlap was found when comparing all possible pairings of tumors from different patients (median 3%). The tumors exhibited diverse genomic patterns of rearrangements: some carried events distributed throughout the genome while others had events mostly within densely clustered chromothripsis-like foci at a few chromosomal locations. Irrespectively, the patterns were highly conserved between the primary tumor and metastases from the same patient. Rearrangements occurred more frequently in genic areas than expected by chance and among the genes affected there was significant enrichment for cancer-associated genes including disruption of TP53, RB1, PTEN, and ESR1, likely contributing to tumor development. Our findings are most consistent with chromosomal rearrangements being early events in breast cancer progression that remain stable during the development from primary tumor to distant metastasis.
  • Vallon-Christersson, Johan, et al. (författare)
  • Cross comparison and prognostic assessment of breast cancer multigene signatures in a large population-based contemporary clinical series
  • 2019
  • Ingår i: Scientific Reports. - Nature Publishing Group. - 2045-2322. ; 9
  • Tidskriftsartikel (refereegranskat)abstract
    • Multigene expression signatures provide a molecular subdivision of early breast cancer associated with patient outcome. A gap remains in the validation of such signatures in clinical treatment groups of patients within population-based cohorts of unselected primary breast cancer representing contemporary disease stages and current treatments. A cohort of 3520 resectable breast cancers with RNA sequencing data included in the population-based SCAN-B initiative (ClinicalTrials.gov ID NCT02306096) were selected from a healthcare background population of 8587 patients diagnosed within the years 2010-2015. RNA profiles were classified according to 19 reported gene signatures including both gene expression subtypes (e.g. PAM50, IC10, CIT) and risk predictors (e.g. Oncotype DX, 70-gene, ROR). Classifications were analyzed in nine adjuvant clinical assessment groups: TNBC-ACT (adjuvant chemotherapy, n = 239), TNBC-untreated (n = 82), HER2+/ER- with anti-HER2+ ACT treatment (n = 110), HER2+/ER+ with anti-HER2 + ACT + endocrine treatment (n = 239), ER+/HER2-/LN- with endocrine treatment (n = 1113), ER+/HER2-/LN- with endocrine + ACT treatment (n = 243), ER+/HER2-/LN+ with endocrine treatment (n = 423), ER+/HER2-/LN+ with endocrine + ACT treatment (n = 433), and ER+/HER2-/LN- untreated (n = 200). Gene signature classification (e.g., proportion low-, high-risk) was generally well aligned with stratification based on current immunohistochemistry-based clinical practice. Most signatures did not provide any further risk stratification in TNBC and HER2+/ER- disease. Risk classifier agreement (low-, medium/intermediate-, high-risk groups) in ER+ assessment groups was on average 50-60% with occasional pair-wise comparisons having <30% agreement. Disregarding the intermediate-risk groups, the exact agreement between low- and high-risk groups was on average ~80-95%, for risk prediction signatures across all assessment groups. Outcome analyses were restricted to assessment groups of TNBC-ACT and endocrine treated ER+/HER2-/LN- and ER+/HER2-/LN+ cases. For ER+/HER2- disease, gene signatures appear to contribute additional prognostic value even at a relatively short follow-up time. Less apparent prognostic value was observed in the other groups for the tested signatures. The current study supports the usage of gene expression signatures in specific clinical treatment groups within population-based breast cancer. It also stresses the need of further development to reach higher consensus in individual patient classifications, especially for intermediate-risk patients, and the targeting of patients where current gene signatures and prognostic variables provide little support in clinical decision-making.
  • Wadt, Karin A W, et al. (författare)
  • Molecular characterization of melanoma cases in denmark suspected of genetic predisposition.
  • 2015
  • Ingår i: PLoS ONE. - Public Library of Science. - 1932-6203. ; 10:3
  • Tidskriftsartikel (refereegranskat)abstract
    • Both environmental and host factors influence risk of cutaneous melanoma (CM), and worldwide, the incidence varies depending on constitutional determinants of skin type and pigmentation, latitude, and patterns of sun exposure. We performed genetic analysis of CDKN2A, CDK4, BAP1, MC1R, and MITFp.E318K in Danish high-risk melanoma cases and found CDKN2A germline mutations in 11.3% of CM families with three or more affected individuals, including four previously undescribed mutations. Rare mutations were also seen in CDK4 and BAP1, while MC1R variants were common, occurring at more than twice the frequency compared to Danish controls. The MITF p.E318K variant similarly occurred at an approximately three-fold higher frequency in melanoma cases than controls. To conclude, we propose that mutation screening of CDKN2A and CDK4 in Denmark should predominantly be performed in families with at least 3 cases of CM. In addition, we recommend that testing of BAP1 should not be conducted routinely in CM families but should be reserved for families with CM and uveal melanoma, or mesothelioma.
  • Waldemarson, Sofia, et al. (författare)
  • Proteomic analysis of breast tumors confirms the mRNA intrinsic molecular subtypes using different classifiers : A large-scale analysis of fresh frozen tissue samples
  • 2016
  • Ingår i: Breast Cancer Research. - BioMed Central. - 1465-5411. ; 18:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Breast cancer is a complex and heterogeneous disease that is usually characterized by histological parameters such as tumor size, cellular arrangements/rearrangments, necrosis, nuclear grade and the mitotic index, leading to a set of around twenty subtypes. Together with clinical markers such as hormone receptor status, this classification has considerable prognostic value but there is a large variation in patient response to therapy. Gene expression profiling has provided molecular profiles characteristic of distinct subtypes of breast cancer that reflect the divergent cellular origins and degree of progression. Methods: Here we present a large-scale proteomic and transcriptomic profiling study of 477 sporadic and hereditary breast cancer tumors with matching mRNA expression analysis. Unsupervised hierarchal clustering was performed and selected proteins from large-scale tandem mass spectrometry (MS/MS) analysis were transferred into a highly multiplexed targeted selected reaction monitoring assay to classify tumors using a hierarchal cluster and support vector machine with leave one out cross-validation. Results: The subgroups formed upon unsupervised clustering agree very well with groups found at transcriptional level; however, the classifiers (genes or their respective protein products) differ almost entirely between the two datasets. In-depth analysis shows clear differences in pathways unique to each type, which may lie behind their different clinical outcomes. Targeted mass spectrometry analysis and supervised clustering correlate very well with subgroups determined by RNA classification and show convincing agreement with clinical parameters. Conclusions: This work demonstrates the merits of protein expression profiling for breast cancer stratification. These findings have important implications for the use of genomics and expression analysis for the prediction of protein expression, such as receptor status and drug target expression. The highly multiplexed MS assay is easily implemented in standard clinical chemistry practice, allowing rapid and cheap characterization of tumor tissue suitable for directing the choice of treatment.
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  • Föregående 123456[7]
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