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  • 1. Ahlén Bergman, Emma
    et al.
    Hartana, Ciputra Adijaya
    Johansson, Markus
    Umeå universitet, Medicinska fakulteten, Institutionen för kirurgisk och perioperativ vetenskap, Urologi och andrologi. Department of Urology, Sundsvall Hospital, Sundsvall, Sweden..
    Linton, Ludvig B
    Berglund, Sofia
    Hyllienmark, Martin
    Lundgren, Christian
    Holmström, Benny
    Palmqvist, Karin
    Umeå universitet, Medicinska fakulteten, Institutionen för kirurgisk och perioperativ vetenskap, Urologi och andrologi. Department of Surgery, Urology Section, Östersund County Hospital, Östersund, Sweden.
    Hansson, Johan
    Alamdari, Farhood
    Huge, Ylva
    Aljabery, Firas
    Riklund, Katrine
    Winerdal, Malin E
    Krantz, David
    Zirakzadeh, Ali A .
    Umeå universitet, Medicinska fakulteten, Institutionen för kirurgisk och perioperativ vetenskap, Urologi och andrologi. Unit of Immunology and Allergy, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
    Marits, Per
    Sjöholm, Louise K
    Sherif, Amir
    Umeå universitet, Medicinska fakulteten, Institutionen för kirurgisk och perioperativ vetenskap, Urologi och andrologi. Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Diagnostisk radiologi.
    Winqvist, Ola
    Increased CD4+ T cell lineage commitment determined by CpG methylation correlates with better prognosis in urinary bladder cancer patients.2018Ingår i: Clinical Epigenetics, E-ISSN 1868-7083, Vol. 10, artikel-id 102Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    BACKGROUND: Urinary bladder cancer is a common malignancy worldwide. Environmental factors and chronic inflammation are correlated with the disease risk. Diagnosis is performed by transurethral resection of the bladder, and patients with muscle invasive disease preferably proceed to radical cystectomy, with or without neoadjuvant chemotherapy. The anti-tumour immune responses, known to be initiated in the tumour and draining lymph nodes, may play a major role in future treatment strategies. Thus, increasing the knowledge of tumour-associated immunological processes is important. Activated CD4+ T cells differentiate into four main separate lineages: Th1, Th2, Th17 and Treg, and they are recognized by their effector molecules IFN-γ, IL-13, IL-17A, and the transcription factor Foxp3, respectively. We have previously demonstrated signature CpG sites predictive for lineage commitment of these four major CD4+ T cell lineages. Here, we investigate the lineage commitment specifically in tumour, lymph nodes and blood and relate them to the disease stage and response to neoadjuvant chemotherapy.

    RESULTS: Blood, tumour and regional lymph nodes were obtained from patients at time of transurethral resection of the bladder and at radical cystectomy. Tumour-infiltrating CD4+ lymphocytes were significantly hypomethylated in all four investigated lineage loci compared to CD4+ lymphocytes in lymph nodes and blood (lymph nodes vs tumour-infiltrating lymphocytes: IFNG -4229 bp p < 0.0001, IL13 -11 bp p < 0.05, IL17A -122 bp p < 0.01 and FOXP3 -77 bp p > 0.05). Examination of individual lymph nodes displayed different methylation signatures, suggesting possible correlation with future survival. More advanced post-cystectomy tumour stages correlated significantly with increased methylation at the IFNG -4229 bp locus. Patients with complete response to neoadjuvant chemotherapy displayed significant hypomethylation in CD4+ T cells for all four investigated loci, most prominently in IFNG p < 0.0001. Neoadjuvant chemotherapy seemed to result in a relocation of Th1-committed CD4+ T cells from blood, presumably to the tumour, indicated by shifts in the methylation patterns, whereas no such shifts were seen for lineages corresponding to IL13, IL17A and FOXP3.

    CONCLUSION: Increased lineage commitment in CD4+ T cells, as determined by demethylation in predictive CpG sites, is associated with lower post-cystectomy tumour stage, complete response to neoadjuvant chemotherapy and overall better outcome, suggesting epigenetic profiling of CD4+ T cell lineages as a useful readout for clinical staging.

  • 2.
    Borssén, Magnus
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för medicinsk biovetenskap, Patologi.
    Nordlund, Jessica
    Haider, Zahra
    Umeå universitet, Medicinska fakulteten, Institutionen för medicinsk biovetenskap, Patologi.
    Landfors, Mattias
    Umeå universitet, Medicinska fakulteten, Institutionen för medicinsk biovetenskap, Patologi.
    Larsson, Pär
    Umeå universitet, Medicinska fakulteten, Institutionen för medicinsk biovetenskap, Patologi.
    Kanerva, Jukka
    Schmiegelow, Kjeld
    Flaegstad, Trond
    Jónsson, Ólafur Gísli
    Frost, Britt-Marie
    Palle, Josefine
    Forestier, Erik
    Umeå universitet, Medicinska fakulteten, Institutionen för medicinsk biovetenskap, Medicinsk och klinisk genetik.
    Heyman, Mats
    Hultdin, Magnus
    Umeå universitet, Medicinska fakulteten, Institutionen för medicinsk biovetenskap, Patologi.
    Lönnerholm, Gudmar
    Degerman, Sofie
    Umeå universitet, Medicinska fakulteten, Institutionen för medicinsk biovetenskap, Patologi.
    DNA methylation holds prognostic information in relapsed precursor B-cell acute lymphoblastic leukemia2018Ingår i: Clinical Epigenetics, E-ISSN 1868-7083, Vol. 10, artikel-id 31Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: Few biological markers are associated with survival after relapse of B-cell precursor acute lymphoblastic leukemia (BCP-ALL). In pediatric T-cell ALL, we have identified promoter-associated methylation alterations that correlate with prognosis. Here, the prognostic relevance of CpG island methylation phenotype (CIMP) classification was investigated in pediatric BCP-ALL patients.

    Methods: Six hundred and one BCP-ALL samples from Nordic pediatric patients (age 1-18) were CIMP classified at initial diagnosis and analyzed in relation to clinical data.

    Results: Among the 137 patients that later relapsed, patients with a CIMP-profile (n = 42) at initial diagnosis had an inferior overall survival (pOS(5years) 33%) compared to CIMP+ patients (n = 95, pOS(5years) 65%) (p = 0.001), which remained significant in a Cox proportional hazards model including previously defined risk factors.

    Conclusion: CIMP classification is a strong candidate for improved risk stratification of relapsed BCP-ALL.

  • 3. Nordlund, Jessica
    et al.
    Backlin, Christofer L.
    Zachariadis, Vasilios
    Cavelier, Lucia
    Dahlberg, Johan
    Ofverholm, Ingegerd
    Barbany, Gisela
    Nordgren, Ann
    Overnas, Elin
    Abrahamsson, Jonas
    Flaegstad, Trond
    Heyman, Mats M.
    Jonsson, Olafur G.
    Kanerva, Jukka
    Larsson, Rolf
    Palle, Josefine
    Schmiegelow, Kjeld
    Gustafsson, Mats G.
    Lonnerholm, Gudmar
    Forestier, Erik
    Umeå universitet, Medicinska fakulteten, Institutionen för medicinsk biovetenskap.
    Syvanen, Ann-Christine
    DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia2015Ingår i: Clinical Epigenetics, E-ISSN 1868-7083, Vol. 7, artikel-id 11Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: We present a method that utilizes DNA methylation profiling for prediction of the cytogenetic subtypes of acute lymphoblastic leukemia (ALL) cells from pediatric ALL patients. The primary aim of our study was to improve risk stratification of ALL patients into treatment groups using DNA methylation as a complement to current diagnostic methods. A secondary aim was to gain insight into the functional role of DNA methylation in ALL. Results: We used the methylation status of similar to 450,000 CpG sites in 546 well-characterized patients with T-ALL or seven recurrent B-cell precursor ALL subtypes to design and validate sensitive and accurate DNA methylation classifiers. After repeated cross-validation, a final classifier was derived that consisted of only 246 CpG sites. The mean sensitivity and specificity of the classifier across the known subtypes was 0.90 and 0.99, respectively. We then used DNA methylation classification to screen for subtype membership of 210 patients with undefined karyotype (normal or no result) or non-recurrent cytogenetic aberrations('other' subtype). Nearly half (n = 106) of the patients lacking cytogenetic subgrouping displayed highly similar methylation profiles as the patients in the known recurrent groups. We verified the subtype of 20% of the newly classified patients by examination of diagnostic karyotypes, array-based copy number analysis, and detection of fusion genes by quantitative polymerase chain reaction (PCR) and RNA-sequencing (RNA-seq). Using RNA-seq data from ALL patients where cytogenetic subtype and DNA methylation classification did not agree, we discovered several novel fusion genes involving ETV6, RUNX1, and PAX5. Conclusions: Our findings indicate that DNA methylation profiling contributes to the clarification of the heterogeneity in cytogenetically undefined ALL patient groups and could be implemented as a complementary method for diagnosis of ALL. The results of our study provide clues to the origin and development of leukemic transformation. The methylation status of the CpG sites constituting the classifiers also highlight relevant biological characteristics in otherwise unclassified ALL patients.

  • 4. Perrier, Flavie
    et al.
    Novoloaca, Alexei
    Ambatipudi, Srikant
    Baglietto, Laura
    Ghantous, Akram
    Perduca, Vittorio
    Barrdahl, Myrto
    Harlid, Sophia
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Ong, Ken K.
    Cardona, Alexia
    Polidoro, Silvia
    Haugdahl Nøst, Therese
    Overvad, Kim
    Omichessan, Hanane
    Dollé, Martijn
    Bamia, Christina
    Huerta, José Marìa
    Vineis, Paolo
    Herceg, Zdenko
    Romieu, Isabelle
    Ferrari, Pietro
    Identifying and correcting epigenetics measurements for systematic sources of variation2018Ingår i: Clinical Epigenetics, E-ISSN 1868-7083, Vol. 10, artikel-id 38Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: Methylation measures quantified by microarray techniques can be affected by systematic variation due to the technical processing of samples, which may compromise the accuracy of the measurement process and contribute to bias the estimate of the association under investigation. The quantification of the contribution of the systematic source of variation is challenging in datasets characterized by hundreds of thousands of features.In this study, we introduce a method previously developed for the analysis of metabolomics data to evaluate the performance of existing normalizing techniques to correct for unwanted variation. Illumina Infinium HumanMethylation450K was used to acquire methylation levels in over 421,000 CpG sites for 902 study participants of a case-control study on breast cancer nested within the EPIC cohort. The principal component partial R-square (PC-PR2) analysis was used to identify and quantify the variability attributable to potential systematic sources of variation. Three correcting techniques, namely ComBat, surrogate variables analysis (SVA) and a linear regression model to compute residuals were applied. The impact of each correcting method on the association between smoking status and DNA methylation levels was evaluated, and results were compared with findings from a large meta-analysis.

    Results:  A sizeable proportion of systematic variability due to variables expressing 'batch' and 'sample position' within 'chip' was identified, with values of the partial R-2 statistics equal to 9.5 and 11.4% of total variation, respectively. After application of ComBat or the residuals' methods, the contribution was 1.3 and 0.2%, respectively. The SVA technique resulted in a reduced variability due to 'batch' (1.3%) and 'sample position' (0.6%), and in a diminished variability attributable to 'chip' within a batch (0.9%). After ComBat or the residuals' corrections, a larger number of significant sites (k = 600 and k = 427, respectively) were associated to smoking status than the SVA correction (k = 96).

    Conclusions: The three correction methods removed systematic variation in DNA methylation data, as assessed by the PC-PR2, which lent itself as a useful tool to explore variability in large dimension data. SVA produced more conservative findings than ComBat in the association between smoking and DNA methylation.

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