Jan Philippé

Supplementary Data Table S1: general characterisctic of the different cohorts of patients Supplementary Data Table S2: characterisctic of Population A Supplementary Data Table S3: characterisctic of Population B Supplementary Data Table S4: characterisctic of Population C Supplementary Data Table S5: characterisctic of Population D Supplementary Data Table S6: Primer sequences Supplementary Data Table S7: Differentially expressed transcripts between IgLV3-21 + and - patients Supplementary Data Table S8: differentially expressed genes between IgLV3-21 + and - patients Supplementary Data Table S9: differentially expressed genes between IgLV3-21 + and - patients. Restricted to absolute fold-change > 1.5 and protein coding genes only Supplementary Data Table S10 Gene set Enrichment analysis between IgLV3-21 positive and negative patients

Supplementary Data Figure S1. Determination of IgLV3-21 positivity by real-time PCR. Supplementary Data Figure S2: CLL-OS analysis including only CLL-related deaths. Supplementary Data Figure S3. Validation of the poor prognosis associated with IgLV3-21 usage in population C. Supplementary Data Figure S4. Validation of the poor prognosis of IgLV3-21 usage in population D. Supplementary Data Figure S5: prognostic impact of IgLV3-21 usage in the different CLL-IPI subgroups. Supplementary Data Figure S6. Immunogenetic features of IgLV3-21 patients. Supplementary Data Figure S7. CXCR4 surface expression is downregulated in IgLV3-21 patients.

Supplementary Data Figure S1. Determination of IgLV3-21 positivity by real-time PCR. Supplementary Data Figure S2: CLL-OS analysis including only CLL-related deaths. Supplementary Data Figure S3. Validation of the poor prognosis associated with IgLV3-21 usage in population C. Supplementary Data Figure S4. Validation of the poor prognosis of IgLV3-21 usage in population D. Supplementary Data Figure S5: prognostic impact of IgLV3-21 usage in the different CLL-IPI subgroups. Supplementary Data Figure S6. Immunogenetic features of IgLV3-21 patients. Supplementary Data Figure S7. CXCR4 surface expression is downregulated in IgLV3-21 patients.

Supplementary Data Table S1: general characterisctic of the different cohorts of patients Supplementary Data Table S2: characterisctic of Population A Supplementary Data Table S3: characterisctic of Population B Supplementary Data Table S4: characterisctic of Population C Supplementary Data Table S5: characterisctic of Population D Supplementary Data Table S6: Primer sequences Supplementary Data Table S7: Differentially expressed transcripts between IgLV3-21 + and - patients Supplementary Data Table S8: differentially expressed genes between IgLV3-21 + and - patients Supplementary Data Table S9: differentially expressed genes between IgLV3-21 + and - patients. Restricted to absolute fold-change > 1.5 and protein coding genes only Supplementary Data Table S10 Gene set Enrichment analysis between IgLV3-21 positive and negative patients

Purpose: Unmutated (UM) immunoglobulin heavy chain variable region (IgHV) status or IgHV3-21 gene usage is associated with poor prognosis in chronic lymphocytic leukemia (CLL) patients. Interestingly, IgHV3-21 is often co-expressed with light chain IgLV3-21, which is potentially able to trigger cell-autonomous BCR-mediated signaling. However, this light chain has never been characterized independently of the heavy chain IgHV3-21.Experimental Design: We performed total RNA sequencing in 32 patients and investigated IgLV3-21 prognostic impact in terms of treatment-free survival (TFS) and overall survival (OS) in 3 other independent cohorts for a total of 813 patients. IgLV3-21 presence was tested by real-time PCR and confirmed by Sanger sequencing.Results: Using total RNA sequencing to characterize 32 patients with high-risk CLL, we found a high frequency (28%) of IgLV3-21 rearrangements. Gene set enrichment analysis revealed that these patients express higher levels of genes responsible for ribosome biogenesis and translation initiation (P < 0.0001) as well as MYC target genes (P = 0.0003). Patients with IgLV3-21 rearrangements displayed a significantly shorter TFS and OS (P < 0.05), particularly those with IgHV mutation. In each of the three independent validation cohorts, we showed that IgLV3-21 rearrangements—similar to UM IgHV status—conferred poor prognosis compared with mutated IgHV (P < 0.0001). Importantly, we confirmed by multivariate analysis that this was independent of IgHV mutational status or subset #2 stereotyped receptor (P < 0.0001).Conclusions: We have demonstrated for the first time that a light chain can affect CLL prognosis and that IgLV3-21 light chain usage defines a new subgroup of CLL patients with poor prognosis. Clin Cancer Res; 24(20); 5048–57. ©2018 AACR.

Purpose: Unmutated (UM) immunoglobulin heavy chain variable region (IgHV) status or IgHV3-21 gene usage is associated with poor prognosis in chronic lymphocytic leukemia (CLL) patients. Interestingly, IgHV3-21 is often co-expressed with light chain IgLV3-21, which is potentially able to trigger cell-autonomous BCR-mediated signaling. However, this light chain has never been characterized independently of the heavy chain IgHV3-21.Experimental Design: We performed total RNA sequencing in 32 patients and investigated IgLV3-21 prognostic impact in terms of treatment-free survival (TFS) and overall survival (OS) in 3 other independent cohorts for a total of 813 patients. IgLV3-21 presence was tested by real-time PCR and confirmed by Sanger sequencing.Results: Using total RNA sequencing to characterize 32 patients with high-risk CLL, we found a high frequency (28%) of IgLV3-21 rearrangements. Gene set enrichment analysis revealed that these patients express higher levels of genes responsible for ribosome biogenesis and translation initiation (P < 0.0001) as well as MYC target genes (P = 0.0003). Patients with IgLV3-21 rearrangements displayed a significantly shorter TFS and OS (P < 0.05), particularly those with IgHV mutation. In each of the three independent validation cohorts, we showed that IgLV3-21 rearrangements—similar to UM IgHV status—conferred poor prognosis compared with mutated IgHV (P < 0.0001). Importantly, we confirmed by multivariate analysis that this was independent of IgHV mutational status or subset #2 stereotyped receptor (P < 0.0001).Conclusions: We have demonstrated for the first time that a light chain can affect CLL prognosis and that IgLV3-21 light chain usage defines a new subgroup of CLL patients with poor prognosis. Clin Cancer Res; 24(20); 5048–57. ©2018 AACR.

Pediatric acute myeloid leukemia (pedAML) is a heterogeneous blood cancer that affects children. Although survival rates have significantly improved over the past few decades, 20–30% of children will succumb due to treatment-related toxicity or relapse. The molecular characterization of the leukemic stem cell, shown to be responsible for relapse, is needed to improve treatment options and survival. Recently, it has become clear that non-coding RNAs, including long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), play a role in the development of human diseases, including pediatric cancer. Nevertheless, non-coding RNA expression data in pedAML are scarce. Here, we explored lncRNA (n = 30,168) and miRNA (n = 627) expression in pedAML subpopulations (leukemic stem cells (LSCs) and leukemic blasts (L-blasts)) and their normal counterparts (hematopoietic stem cells and control myeloblasts). The potential regulatory activity of differentially expressed lncRNAs in LSCs (unique or shared with the L-blast comparison) on miRNAs was assessed. Moreover, pre-ranked gene set enrichment analyses of (anti-) correlated protein-coding genes were performed to predict the functional relevance of the differentially upregulated lncRNAs in LSCs (unique or shared with the L-blast comparison). In conclusion, this study provides a catalog of non-coding RNAs with a potential role in the pathogenesis of pedAML, paving the way for further translational research studies.

Flowcytometric analysis allows for detailed identification and characterization of large numbers of cells in blood, bone marrow, and other body fluids and tissue samples and therefore contributes to the diagnostics of hematological malignancies. Novel data analysis tools allow for multidimensional analysis and comparison of patient samples with reference databases of normal, reactive, and/or leukemia/lymphoma patient samples. Building such reference databases requires strict quality assessment (QA) procedures. Here, we compiled a dataset and developed a QA methodology of the EuroFlow Acute Myeloid Leukemia (AML) database, based on the eight-color EuroFlow AML panel consisting of six different antibody combinations, including four backbone markers. In total, 1142 AML cases and 42 normal bone marrow samples were included in this analysis. QA was performed on 803 AML cases using multidimensional analysis of backbone markers, as well as tube-specific markers, and data were compared using classical analysis employing median and peak expression values. Validation of the QA procedure was performed by re-analysis of >300 cases and by running an independent cohort of 339 AML cases. Initial evaluation of the final cohort confirmed specific immunophenotypic patterns in AML subgroups; the dataset therefore can reliably be used for more detailed exploration of the immunophenotypic variability of AML. Our data show the potential pitfalls and provide possible solutions for constructing large flowcytometric databases. In addition, the provided approach may facilitate the building of other databases and thereby support the development of novel tools for (semi)automated QA and subsequent data analysis.

The aim of this study was to explore the relationship of iron and zinc deficiencies and anemia in children aged under 5 years living in malaria endemic area of South Kivu/DRC. We conducted a cross-sectional study in the health zone of Miti Murhesa in South Kivu/DRC. A total of 1088 children in good general health were included in this study. Almost 40% of children were anemic. The prevalence of iron deficiency (ID) was found in 34.9% and 49.1% children based on ferritin or free erythrocyte protoporphyrin (FEP), respectively. If anemia is present, we found iron deficiency anemia (IDA) according to the WHO-criteria (ferritin) in 31%, and according to FEP in 66% of children. The overall prevalence of zinc deficiency was 17.6%. If anemia is present, zinc deficiency was found in 24.4% of children. Inflammation/infection, based upon CRP, was present in 39.7% children. The independent factors associated with anemia were recent illness, middle upper arm circumference, weight-for-height, ID according to FEP, zinc deficiency, and submicroscopic Plasmodium infection. A high prevalence of ID was observed in children in South Kivu according to FEP. Ferritin as acute phase protein was less suited in this population due to a high frequency of infection/inflammation. Iron and zinc deficiencies were found to be significantly associated with anemia in this population.