hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine

Falgreen, Steffen; Bilgrau, Anders Ellern; Brøndum, Rasmus Froberg; Jakobsen, Lasse Hjort; Have, Jonas; Nielsen, Kasper Lindblad; El‐Galaly, Tarec Christoffer; Bødker, Julie Støve; Schmitz, Alexander; Young, Ken H.; Johnsen, Hans Erik; Dybkær, Karen; Bøgsted, Martin

doi:10.1371/journal.pone.0163711

Cited by 7 publications

(7 citation statements)

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“…Therefore, in its current form, "cohort-based" BAGS profiling cannot be applied to individual patients as would be required in the clinical setting. However, in a recent study, this caveat was overcome by inferring a one-by-one microarray normalization scheme, which enabled the classification of individual samples generated on the HG-U133plus2 gene array [ 41 ]. A similar approach is under consideration for the current study.…”

Section: Discussionmentioning

confidence: 99%

Subtype assignment of CLL based on B-cell subset associated gene signatures from normal bone marrow – A proof of concept study

et al. 2018

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Diagnostic and prognostic evaluation of chronic lymphocytic leukemia (CLL) involves blood cell counts, immunophenotyping, IgVH mutation status, and cytogenetic analyses. We generated B-cell associated gene-signatures (BAGS) based on six naturally occurring B-cell subsets within normal bone marrow. Our hypothesis is that by segregating CLL according to BAGS, we can identify subtypes with prognostic implications in support of pathogenetic value of BAGS. Microarray-based gene-expression samples from eight independent CLL cohorts (1,024 untreated patients) were BAGS-stratified into pre-BI, pre-BII, immature, naïve, memory, or plasma cell subtypes; the majority falling within the memory (24.5–45.8%) or naïve (14.5–32.3%) categories. For a subset of CLL patients (n = 296), time to treatment (TTT) was shorter amongst early differentiation subtypes (pre-BI/pre-BII/immature) compared to late subtypes (memory/plasma cell, HR: 0.53 [0.35–0.78]). Particularly, pre-BII subtype patients had the shortest TTT among all subtypes. Correlates derived for BAGS subtype and IgVH mutation (n = 405) revealed an elevated mutation frequency in late vs. early subtypes (71% vs. 45%, P < .001). Predictions for BAGS subtype resistance towards rituximab and cyclophosphamide varied for rituximab, whereas all subtypes were sensitive to cyclophosphamide. This study supports our hypothesis that BAGS-subtyping may be of tangible prognostic and pathogenetic value for CLL patients.

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Section: Discussionmentioning

confidence: 99%

Subtype assignment of CLL based on B-cell subset associated gene signatures from normal bone marrow – A proof of concept study

et al. 2018

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“…The primary and relapse samples were assigned a cell of origin (COO) subtype as described [18] resistance estimate for R-CHOP by REGS [19–21] classifiers following assignment in http://www.hemaClass.org [25]. This tool provides an easy interface for one-by-one microarray based classification based on our preclinical models for BAGS and REGS.…”

Section: Resultsmentioning

confidence: 99%

“…To allow implementation and fast validation of our recent findings in DLBCL [18–21], we have developed an easily accessible web application that permits other users to assign ABC/GCB, B-cell associated gene signature (BAGS) as well as drug specific resistance gene signature (REGS) on their own datasets. The website called hemaClass.org [25] is a new prospect for easy individual subtyping of malignant B cell diseases; in particular for DLBCL and myeloma.…”

Section: Discussionmentioning

confidence: 99%

“…Sensitivity or resistance towards individual drugs can be predicted by the REGS assignment of probability, which ranges from zero to one, respectively. A website (http://www.hemaClass.org) [25] has been generated to grant access to the classification and prediction tools to all researchers by easy upload of .CEL-file data. The.CEL files from the patient case tumors were analyzed and as build-in reference, our collection of lymphoma samples (RetroGene) performed at our laboratory was chosen in the RMA pre-processing normalization step.…”

Section: Methods Sectionmentioning

confidence: 99%

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Molecular classification of tissue from a transformed non-Hogkin’s lymphoma case with unexpected long-time remission

et al. 2017

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BackgroundThe concept of precision medicine in cancer includes individual molecular studies to predict clinical outcomes. In the present N = 1 case we retrospectively have analysed lymphoma tissue by exome sequencing and global gene expression in a patient with unexpected long-term remission following relaps. The goals were to phenotype the diagnostic and relapsed lymphoma tissue and evaluate its pattern. Furthermore, to identify mutations available for targeted therapy and expression of genes to predict specific drug effects by resistance gene signatures (REGS) for R-CHOP as described at http://www.hemaclass.org. We expected that such a study could generate therapeutic information and a frame for future individual evaluation of molecular resistance detected at clinical relapse.Case presentationThe patient was diagnosed with a transformed high-grade non-Hodgkin lymphoma stage III and treated with conventional R-CHOP [rituximab (R), cyclophosphamide (C), doxorubicin (H), vincristine (O) and prednisone (P)]. Unfortunately, she suffered from severe toxicity but recovered during the following 6 months’ remission until biopsy-verified relapse. The patient refused second-line combination chemotherapy, but accepted 3 months’ palliation with R and chlorambucil. Unexpectedly, she obtained continuous complete remission and is at present >9 years after primary diagnosis. Molecular studies and data evaluation by principal component analysis, mutation screening and copy number variations of the primary and relapsed tumor, identified a pattern of branched lymphoma evolution, most likely diverging from an in situ follicular lymphoma. Accordingly, the primary diagnosed transformed lymphoma was classified as a diffuse large B cell lymphoma (DLBCL) of the GCB/centrocytic subtype by “cell of origin BAGS” assignment and R sensitive and C, H, O and P resistant by “drug specific REGS” assignment. The relapsed DLBCL was classified as NC/memory subtype and R, C, H sensitive but O and P resistant.ConclusionsThorough analysis of the tumor DNA and RNA documented a branched evolution of the two clinical diagnosed tFL, most likely transformed from an unknown in situ lymphoma. Classification of the malignant tissue for drug-specific resistance did not explain the unexpected long-term remission and potential cure. However, it is tempting to consider the anti-CD20 immunotherapy as the curative intervention in the two independent tumors of this case.Electronic supplementary materialThe online version of this article (doi:10.1186/s40164-016-0063-0) contains supplementary material, which is available to authorized users.

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“…Patients were classified as activated B-cell like (ABC), germinal center B-cell like (GCB), or unclassified (UC) using CEL files obtained from Affymetrix GeneChip Human Genome U133 Plus 2.0 microarrays and methods implemented in the web-based tool ( https://hemaclass.aau.dk ) providing one-by-one Robust Multichip Average (RMA) normalization of microarrays and subsequent risk stratification of DLBCL into cell-of-origin, as previously described [ 29 , 30 ]. Furthermore, CEL files were used for differential gene expression with the R-package limma [ 31 ] and Cibersort [ 32 ] analysis, using R version 4.0.3.…”

Section: Methodsmentioning

confidence: 99%

The mutational profile of immune surveillance genes in diagnostic and refractory/relapsed DLBCLs

et al. 2021

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Background Diffuse large B-cell lymphoma (DLBCL) is the most frequent lymphoid neoplasm among adults,and approximately 30–40% of patients will experience relapse while 5–10% will suffer from primary refractory disease caused by different mechanisms, including treatment-induced resistance. For refractory and relapsed DLBCL (rrDLBCL) patients, early detection and understanding of the mechanisms controlling treatment resistance are of great importance to guide therapy decisions. Here, we have focused on genetic variations in immune surveillance genes in diagnostic DLBCL (dDLBCL) and rrDLBCL patients to elaborate on the suitability of new promising immunotherapies. Methods Biopsies from 30 dDLBCL patients who did not progress or relapse during follow up and 17 rrDLBCL patients with refractory disease or who relapsed during follow up were analyzed by whole-exome sequencing, including matched individual germline samples to include only somatic genetic variants in downstream analysis of a curated list of 58 genes involved in major immune surveillance pathways. Results More than 70% of both dDLBCLs and rrDLBCLs harbored alterations in immune surveillance genes, but rrDLBCL tumor samples have a lower number of genes affected compared to dDLBCL tumor samples. Increased gene mutation frequencies in rrDLBCLs were observed in more than half of the affected immune surveillance genes than dDLBCLs. Conclusion Genetic variants in the antigen-presenting genes affect a higher number of rrDLBCL patients supporting an important role for these genes in tumor progression and development of refractory disease and relapse.

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hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine

Cited by 7 publications

References 50 publications

Subtype assignment of CLL based on B-cell subset associated gene signatures from normal bone marrow – A proof of concept study

Subtype assignment of CLL based on B-cell subset associated gene signatures from normal bone marrow – A proof of concept study

Molecular classification of tissue from a transformed non-Hogkin’s lymphoma case with unexpected long-time remission

The mutational profile of immune surveillance genes in diagnostic and refractory/relapsed DLBCLs

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