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- Andersson-Evelönn, Emma, 1983-, et al.
(författare)
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Combining epigenetic and clinicopathological variables improves specificity in prognostic prediction in clear cell renal cell carcinoma
- 2020
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Ingår i: Journal of Translational Medicine. - : Springer Science and Business Media LLC. - 1479-5876. ; 18:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Metastasized clear cell renal cell carcinoma (ccRCC) is associated with a poor prognosis. Almost one-third of patients with non-metastatic tumors at diagnosis will later progress with metastatic disease. These patients need to be identified already at diagnosis, to undertake closer follow up and/or adjuvant treatment. Today, clinicopathological variables are used to risk classify patients, but molecular biomarkers are needed to improve risk classification to identify the high-risk patients which will benefit most from modern adjuvant therapies. Interestingly, DNA methylation profiling has emerged as a promising prognostic biomarker in ccRCC. This study aimed to derive a model for prediction of tumor progression after nephrectomy in non-metastatic ccRCC by combining DNA methylation profiling with clinicopathological variables.Methods: A novel cluster analysis approach (Directed Cluster Analysis) was used to identify molecular biomarkers from genome-wide methylation array data. These novel DNA methylation biomarkers, together with previously identified CpG-site biomarkers and clinicopathological variables, were used to derive predictive classifiers for tumor progression.Results: The “triple classifier” which included both novel and previously identified DNA methylation biomarkers together with clinicopathological variables predicted tumor progression more accurately than the currently used Mayo scoring system, by increasing the specificity from 50% in Mayo to 64% in our triple classifier at 85% fixed sensitivity. The cumulative incidence of progress (pCIP5yr) was 7.5% in low-risk vs 44.7% in high-risk in M0 patients classified by the triple classifier at diagnosis.Conclusions: The triple classifier panel that combines clinicopathological variables with genome-wide methylation data has the potential to improve specificity in prognosis prediction for patients with non-metastatic ccRCC.
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- Andersson-Evelönn, Emma, 1983-
(författare)
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DNA methylation as a prognostic marker in clear cell Renal Cell Carcinoma
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cell carcinoma worldwide. Metastatic ccRCC is correlated to poor prognosis whereas non-metastatic disease has a 5-year survival rate up to 90%. Due to increased accessibility to different types of diagnostic imaging the frequency of metastatic ccRCC at diagnosis has decreased since the beginning of the 21st century. This has led to an earlier detection of primary tumors before patients present symptoms. However, 20-30% of the non-metastatic patients at diagnosis will progress and metastasize within five years of primary nephrectomy. Identifying patients at high risk of tumor progression at an early stage after diagnosis is of importance to improve outcome and survival. Currently, in Sweden, the Mayo scoring system is used to divide tumors into low, intermediate or high risk for tumor progression.DNA methylation has been associated with tumor development and progression in different malignancies. In this thesis, Illumina Infinium HumanMeth27 BeadChip Arrays and Human Meth450K BeadChip Arrays have been used to evaluate the relationship between methylation and clinicopathological variables as well as ccRCC outcome in 45 and 115 patients.Our studies identified an association between higher level of promoter-associated DNA methylation and clinicopathological variables in ccRCC. There was a significant stepwise increase of average methylation from tumor-free tissue, via non-metastatic tumors to metastatic disease. Cluster analysis divided patients into two distinct groups that differed in average methylation levels, TNM stage, Fuhrman nuclear grade, tumor size, survival and tumor progression. We also presented two prognostic classifiers for non-metastatic tumors; the promoter methylation classifier (PMC) panel and the triple classifier. The PMC panel divided tumors depending on the methylation level, PMC low or PMC high, with significantly worse prognosis in the PMC high group. This data was verified in an independent, publically available cohort. The triple classifier was created using a combination of clinicopathological variables, previously identified CpGs biomarkers and a novel cluster analysis approach (Directed Cluster Analysis). The triple classifier had a higher specificity compared to the clinically used Mayo scoring system and predicted tumor progression with higher accuracy at a fixed sensitivity.The identification of two epigenetic classifiers that predicted outcome in non-metastatic ccRCC further establishes the role of DNA methylation as a prognostic marker. This knowledge can contribute to identification of patients with a high risk of tumor progression and can be of importance in the decision regarding adjuvant treatment post-nephrectomy.
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- Andersson Evelönn, Emma, 1983-, et al.
(författare)
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DNA methylation associates with survival in non-metastatic clear cell renal cell carcinoma
- 2019
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Ingår i: BMC Cancer. - : BioMed Central. - 1471-2407. ; 19
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Tidskriftsartikel (refereegranskat)abstract
- Background: Clear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cancer and is associated with poor prognosis if metastasized. Up to one third of patients with local disease at diagnosis will develop metastasis after nephrectomy, and there is a need for new molecular markers to identify patients with high risk of tumor progression. In the present study, we performed genome-wide promoter DNA methylation analysis at diagnosis to identify DNA methylation profiles associated with risk for progress.Method: Diagnostic tissue samples from 115 ccRCC patients were analysed by Illumina HumanMethylation450K arrays and methylation status of 155,931 promoter associated CpGs were related to genetic aberrations, gene expression and clinicopathological parameters.Results: The ccRCC samples separated into two clusters (cluster A/B) based on genome-wide promoter methylation status. The samples in these clusters differed in tumor diameter (p < 0.001), TNM stage (p < 0.001), morphological grade (p < 0.001), and patients outcome (5 year cancer specific survival (pCSS5yr) p < 0.001 and cumulative incidence of progress (pCIP5yr) p < 0.001. An integrated genomic and epigenomic analysis in the ccRCCs, revealed significant correlations between the total number of genetic aberrations and total number of hypermethylated CpGs (R = 0.435, p < 0.001), and predicted mitotic age (R = 0.407, p < 0.001). We identified a promoter methylation classifier (PMC) panel consisting of 172 differently methylated CpGs accompanying progress of disease. Classifying non-metastatic patients using the PMC panel showed that PMC high tumors had a worse prognosis compared with the PMC low tumors (pCIP5yr 38% vs. 8%, p = 0.001), which was confirmed in non-metastatic ccRCCs in the publically available TCGA-KIRC dataset (pCIP5yr 39% vs. 16%, p < 0.001).Conclusion: DNA methylation analysis at diagnosis in ccRCC has the potential to improve outcome-prediction in non-metastatic patients at diagnosis.
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- Andersson Evelönn, Emma, 1983-, et al.
(författare)
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DNA methylation status defines clinicopathological parameters including survival for patients with clear cell renal cell carcinoma (ccRCC)
- 2016
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Ingår i: Tumor Biology. - : Springer Science and Business Media LLC. - 1010-4283 .- 1423-0380. ; 37:8, s. 10219-10228
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Tidskriftsartikel (refereegranskat)abstract
- Epigenetic alterations in the methylome have been associated with tumor development and progression in renal cell carcinoma (RCC). In this study, 45 tumor samples, 12 tumor-free kidney cortex tissues, and 24 peripheral blood samples from patients with clear cell RCC (ccRCC) were analyzed by genome-wide promoter-directed methylation arrays and related to clinicopathological parameters. Unsupervised hierarchical clustering separated the tumors into two distinct methylation groups (clusters A and B), where cluster B had higher average methylation and increased number of hypermethylated CpG sites (CpGs). Furthermore, tumors in cluster B had, compared with cluster A, a larger tumor diameter (p = 0.033), a higher morphologic grade (p < 0.001), a higher tumor-node-metastasis (TNM) stage (p < 0.001), and a worse prognosis (p = 0.005). Higher TNM stage was correlated to an increase in average methylation level (p = 0.003) and number of hypermethylated CpGs (p = 0.003), whereas a number of hypomethylated CpGs were mainly unchanged. However, the predicted age of the tumors based on methylation profile did not correlate with TNM stage, morphological grade, or methylation cluster. Differently methylated (DM) genes (n = 840) in ccRCC samples compared with tumor-free kidney cortex samples were predominantly hypermethylated and a high proportion were identified as polycomb target genes. The DM genes were overrepresented by transcription factors, ligands, and receptors, indicating functional alterations of significance for ccRCC progression. To conclude, increased number of hypermethylated genes was associated with increased TNM stage of the tumors. DNA methylation classification of ccRCC tumor samples at diagnosis can serve as a clinically applicable prognostic marker in ccRCC.
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