| 11. |
- Zanti, Maria, et al.
(author)
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A Likelihood Ratio Approach for Utilizing Case-Control Data in the Clinical Classification of Rare Sequence Variants : Application to BRCA1 and BRCA2
- 2023
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In: Human Mutation. - : John Wiley & Sons. - 1059-7794 .- 1098-1004. ; 2023
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Journal article (peer-reviewed)abstract
- A large number of variants identified through clinical genetic testing in disease susceptibility genes are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion) can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analysis of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC) and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity-findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.
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| 12. |
- Bjørklund, Sunniva Stordal, et al.
(author)
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Subtype and cell type specific expression of lncRNAs provide insight into breast cancer
- 2022
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In: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 5:1
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Journal article (peer-reviewed)abstract
- Long non-coding RNAs (lncRNAs) are involved in breast cancer pathogenesis through chromatin remodeling, transcriptional and post-transcriptional gene regulation. We report robust associations between lncRNA expression and breast cancer clinicopathological features in two population-based cohorts: SCAN-B and TCGA. Using co-expression analysis of lncRNAs with protein coding genes, we discovered three distinct clusters of lncRNAs. In silico cell type deconvolution coupled with single-cell RNA-seq analyses revealed that these three clusters were driven by cell type specific expression of lncRNAs. In one cluster lncRNAs were expressed by cancer cells and were mostly associated with the estrogen signaling pathways. In the two other clusters, lncRNAs were expressed either by immune cells or fibroblasts of the tumor microenvironment. To further investigate the cis-regulatory regions driving lncRNA expression in breast cancer, we identified subtype-specific transcription factor (TF) occupancy at lncRNA promoters. We also integrated lncRNA expression with DNA methylation data to identify long-range regulatory regions for lncRNA which were validated using ChiA-Pet-Pol2 loops. lncRNAs play an important role in shaping the gene regulatory landscape in breast cancer. We provide a detailed subtype and cell type-specific expression of lncRNA, which improves the understanding of underlying transcriptional regulation in breast cancer.
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| 13. |
- Edvardsen, Hege, et al.
(author)
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Experimental validation of data mined single nucleotide polymorphisms from several databases and consecutive dbSNP builds
- 2006
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In: Pharmacogenetics & Genomics. - : Ovid Technologies (Wolters Kluwer Health). - 1744-6872 .- 1744-6880. ; 16:3, s. 207-217
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Journal article (peer-reviewed)abstract
- Rapid development in the annotation of human genetic variation has increased the numbers of single nucleotide polymorphisms (SNPs) in candidate genes by several orders of magnitude. The selection of both useful target SNPs; for disease-gene association studies and SNPs associated with the treatment response is therefore an increasingly challenging task. We describe a workflow for selecting SNPs based on their putative function and frequency in candidate genes extracted from PubMed resources. The annotation of each SNP and its frequency in a Caucasian population was assessed in several databases. Approximately 4000 SNPs were identified from an initial 233 candidate genes. In a case study, we performed actual genotyping of 1030 of these SNPs in 213 genes and obtained 710 successfully genotyped SNPs. Using the flow-chart outlined here, only 87 SNPs were monomorphic (approximately 12%). This study reports the frequency of SNPs in a Caucasian population, selected in silico, using a candidate gene approach and validated by actually genotyping 193 individuals. The selected genotypes represent a valuable set of verified candidate SNPs for pharmacogenetic studies in Caucasian populations.
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| 14. |
- Edvardsen, Hege, et al.
(author)
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SNP in TXNRD2 Associated With Radiation-Induced Fibrosis : A Study of Genetic Variation in Reactive Oxygen Species Metabolism and Signaling.
- 2013
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In: International journal of radiation oncology, biology, physics. - : Elsevier BV. - 1879-355X .- 0360-3016. ; 86:4, s. 791-9
-
Journal article (peer-reviewed)abstract
- PURPOSE: The aim of the study was to identify noninvasive markers of treatment-induced side effects. Reactive oxygen species (ROS) are generated after irradiation, and genetic variation in genes related to ROS metabolism might influence the level of radiation-induced adverse effects (AEs).METHODS AND MATERIALS: 92 breast cancer (BC) survivors previously treated with hypofractionated radiation therapy were assessed for the AEs subcutaneous atrophy and fibrosis, costal fractures, lung fibrosis, pleural thickening, and telangiectasias (median follow-up time 17.1 years). Single-nucleotide polymorphisms (SNPs) in 203 genes were analyzed for association to AE grade. SNPs associated with subcutaneous fibrosis were validated in an independent BC survivor material (n=283). The influence of the studied genetic variation on messenger ribonucleic acid (mRNA) expression level of 18 genes previously associated with fibrosis was assessed in fibroblast cell lines from BC patients.RESULTS: Subcutaneous fibrosis and atrophy had the highest correlation (r=0.76) of all assessed AEs. The nonsynonymous SNP rs1139793 in TXNRD2 was associated with grade of subcutaneous fibrosis, the reference T-allele being more prevalent in the group experiencing severe levels of fibrosis. This was confirmed in another sample cohort of 283 BC survivors, and rs1139793 was found significantly associated with mRNA expression level of TXNRD2 in blood. Genetic variation in 24 ROS-related genes, including EGFR, CENPE, APEX1, and GSTP1, was associated with mRNA expression of 14 genes previously linked to fibrosis (P≤.005).CONCLUSION: Development of subcutaneous fibrosis can be associated with genetic variation in the mitochondrial enzyme TXNRD2, critically involved in removal of ROS, and maintenance of the intracellular redox balance.
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| 15. |
- Escala-Garcia, Maria, et al.
(author)
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A network analysis to identify mediators of germline-driven differences in breast cancer prognosis
- 2020
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In: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 11:1
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Journal article (peer-reviewed)abstract
- Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies similar to 7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.
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| 16. |
- Fleischer, Thomas, et al.
(author)
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An integrated omics approach highlights how epigenetic events can explain and predict response to neoadjuvant chemotherapy and bevacizumab in breast cancer
- 2024
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In: Molecular Oncology. - 1574-7891. ; 18:8, s. 2042-2059
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Journal article (peer-reviewed)abstract
- Treatment with the anti-angiogenic drug bevacizumab in addition to chemotherapy has shown efficacy for breast cancer in some clinical trials, but better biomarkers are needed to optimally select patients for treatment. Here, we present an omics approach where DNA methylation profiles are integrated with gene expression and results from proteomic data in breast cancer patients to predict response to therapy and pinpoint response-related epigenetic events. Fresh-frozen tumor biopsies taken before, during, and after treatment from human epidermal growth factor receptor 2 negative non-metastatic patients receiving neoadjuvant chemotherapy with or without bevacizumab were subjected to molecular profiling. Here, we report that DNA methylation at enhancer CpGs related to cell cycle regulation can predict response to chemotherapy and bevacizumab for the estrogen receptor positive subset of patients (AUC = 0.874), and we validated this observation in an independent patient cohort with a similar treatment regimen (AUC = 0.762). Combining the DNA methylation scores with the scores from a previously published protein signature resulted in a slight increase in the prediction performance (AUC = 0.784). We also show that tumors receiving the combination treatment underwent more extensive epigenetic alterations. Finally, we performed an integrative expression–methylation quantitative trait loci analysis on alterations in DNA methylation and gene expression levels, showing that the epigenetic alterations that occur during treatment are different between responders and non-responders and that these differences may be explained by the proliferation–epithelial-to-mesenchymal transition axis through the activity of grainyhead like transcription factor 2. Using tumor purity computed from copy number data, we developed a method for estimating cancer cell-specific methylation to confirm that the association to response reflects DNA methylation in cancer cells. Taken together, these results support the potential for clinical benefit of the addition of bevacizumab to chemotherapy when administered to the correct patients.
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| 17. |
- Fleischer, Thomas, et al.
(author)
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Genome-wide DNA methylation profiles in progression to in situ and invasive carcinoma of the breast with impact on gene transcription and prognosis
- 2014
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In: Genome Biology. - : Springer Science and Business Media LLC. - 1465-6906 .- 1474-760X. ; 15:8, s. 435-
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Journal article (peer-reviewed)abstract
- Background: Ductal carcinoma in situ (DCIS) of the breast is a precursor of invasive breast carcinoma. DNA methylation alterations are thought to be an early event in progression of cancer, and may prove valuable as a tool in clinical decision making and for understanding neoplastic development. Results: We generate genome-wide DNA methylation profiles of 285 breast tissue samples representing progression of cancer, and validate methylation changes between normal and DCIS in an independent dataset of 15 normal and 40 DCIS samples. We also validate a prognostic signature on 583 breast cancer samples from The Cancer Genome Atlas. Our analysis reveals that DNA methylation profiles of DCIS are radically altered compared to normal breast tissue, involving more than 5,000 genes. Changes between DCIS and invasive breast carcinoma involve around 1,000 genes. In tumors, DNA methylation is associated with gene expression of almost 3,000 genes, including both negative and positive correlations. A prognostic signature based on methylation level of 18 CpGs is associated with survival of breast cancer patients with invasive tumors, as well as with survival of patients with DCIS and mixed lesions of DCIS and invasive breast carcinoma. Conclusions: This work demonstrates that changes in the epigenome occur early in the neoplastic progression, provides evidence for the possible utilization of DNA methylation-based markers of progression in the clinic, and highlights the importance of epigenetic changes in carcinogenesis.
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| 18. |
- Johansson, Henrik J., et al.
(author)
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Breast cancer quantitative proteome and proteogenomic landscape
- 2019
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In: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 10
-
Journal article (peer-reviewed)abstract
- In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets.
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| 19. |
- Klajic, Jovana, et al.
(author)
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Quantitative DNA methylation analyses reveal stage dependent DNA methylation and association to clinico-pathological factors in breast tumors
- 2013
-
In: BMC Cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 13, s. 456-
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Journal article (peer-reviewed)abstract
- Background: Aberrant DNA methylation of regulatory genes has frequently been found in human breast cancers and correlated to clinical outcome. In the present study we investigate stage specific changes in the DNA methylation patterns in order to identify valuable markers to understand how these changes affect breast cancer progression. Methods: Quantitative DNA methylation analyses of 12 candidate genes ABCB1, BRCCA1, CDKN2A, ESR1, GSTP1, IGF2, MGMT, HMLH1, PPP2R2B, PTEN, RASSF1A and FOXC1 was performed by pyrosequencing a series of 238 breast cancer tissue samples from DCIS to invasive tumors stage I to IV. Results: Significant differences in methylation levels between the DCIS and invasive stage II tumors were observed for six genes RASSF1A, CDKN2A, MGMT, ABCB1, GSTP1 and FOXC1. RASSF1A, ABCB1 and GSTP1 showed significantly higher methylation levels in late stage compared to the early stage breast carcinoma. Z-score analysis revealed significantly lower methylation levels in DCIS and stage I tumors compared with stage II, III and IV tumors. Methylation levels of PTEN, PPP2R2B, FOXC1, ABCB1 and BRCA1 were lower in tumors harboring TP53 mutations then in tumors with wild type TP53. Z-score analysis showed that TP53 mutated tumors had significantly lower overall methylation levels compared to tumors with wild type TP53. Methylation levels of RASSF1A, PPP2R2B, GSTP1 and FOXC1 were higher in ER positive vs. ER negative tumors and methylation levels of PTEN and CDKN2A were higher in HER2 positive vs. HER2 negative tumors. Z-score analysis also showed that HER2 positive tumors had significantly higher z-scores of methylation compared to the HER2 negative tumors. Univariate survival analysis identifies methylation status of PPP2R2B as significant predictor of overall survival and breast cancer specific survival. Conclusions: In the present study we report that the level of aberrant DNA methylation is higher in late stage compared with early stage of invasive breast cancers and DCIS for genes mentioned above.
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| 20. |
- Kristensen, Vessela N, et al.
(author)
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Genetic variation in putative regulatory loci controlling gene expression in breast cancer
- 2006
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In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 103:20, s. 7735-7740
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Journal article (other academic/artistic)abstract
- Candidate single-nucleotide polymorphisms (SNPs) were analyzed for associations to an unselected whole genome pool of tumor mRNA transcripts in 50 unrelated patients with breast cancer. SNPs were selected from 203 candidate genes of the reactive oxygen species pathway. We describe a general statistical framework for the simultaneous analysis of gene expression data and SNP genotype data measured for the same cohort, which revealed significant associations between subsets of SNPs and transcripts, shedding light on the underlying biology. We identified SNPs in EGF, IL1A, MAPK8, XPC, SOD2, and ALOX12 that are associated with the expression patterns of a significant number of transcripts, indicating the presence of regulatory SNPs in these genes. SNPs were found to act in trans in a total of 115 genes. SNPs in 43 of these 115 genes were found to act both in cis and in trans. Finally, subsets of SNPs that share significantly many common associations with a set of transcripts (biclusters) were identified. The subsets of transcripts that are significantly associated with the same set of SNPs or to a single SNP were shown to be functionally coherent in Gene Ontology and pathway analyses and coexpressed in other independent data sets, suggesting that many of the observed associations are within the same functional pathways. To our knowledge, this article is the first study to correlate SNP genotype data in the germ line with somatic gene expression data in breast tumors. It provides the statistical framework for further genotype expression correlation studies in cancer data sets.
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