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- Nordlund, Jessica, et al.
(author)
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DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia
- 2015
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In: Clinical Epigenetics. - : Springer Science and Business Media LLC. - 1868-7083 .- 1868-7075. ; 7
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Journal article (peer-reviewed)abstract
- 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.
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- Ofverholm, Ingegerd, et al.
(author)
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Comprehensive Genomic Profiling Alters Clinical Diagnoses in a Significant Fraction of Tumors Suspicious of Sarcoma
- 2024
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In: Clinical Cancer Research. - : American Association for Cancer Research (AACR). - 1078-0432 .- 1557-3265. ; 30:12, s. 2647-2658
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Journal article (peer-reviewed)abstract
- Purpose: Tumor classification is a key component in personalized cancer care. For soft-tissue and bone tumors, this classification is currently based primarily on morphology assessment and IHC staining. However, these standard-of-care methods can pose challenges for pathologists. We therefore assessed how whole-genome and whole-transcriptome sequencing (WGTS) impacted tumor classification and clinical management when interpreted together with histomorphology.Experimental Design: We prospectively evaluated WGTS in routine diagnostics of 200 soft-tissue and bone tumors suspicious for malignancy, including DNA and RNA isolation from the tumor, and DNA isolation from a peripheral blood sample or any non-tumor tissue.Results: On the basis of specific genomic alterations or absence of presumed findings, WGTS resulted in reclassification of 7% (13/197) of the histopathologic diagnoses. Four cases were downgraded from low-grade sarcomas to benign lesions, and two cases were reclassified as metastatic malignant melanomas. Fusion genes associated with specific tumor entities were found in 30 samples. For malignant soft-tissue and bone tumors, we identified treatment relevant variants in 15% of cases. Germline pathogenic variants associated with a hereditary cancer syndrome were found in 22 participants (11%).Conclusions: WGTS provides an important dimension of data that aids in the classification of soft-tissue and bone tumors, correcting a significant fraction of clinical diagnoses, and identifies molecular targets relevant for precision medicine. However, genetic findings need to be evaluated in their morphopathologic context, just as germline findings need to be evaluated in the context of patient phenotype and family history.
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