Dual Biological Role and Clinical Impact of De Novo Chromatin Activation in Chronic Lymphocytic Leukemia
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ABSTRACT: Previous studies have reported that chronic lymphocytic leukemia (CLL) shows a de novo chromatin activation pattern as compared to normal B cells. Here, we explored whether the level of chromatin activation is related to the clinical behavior of CLL. We identified that in some regulatory regions, increased de novo chromatin activation is linked to clinical progression whereas, in other regions, it is associated with an indolent course. We next developed two prognostic scores for progressive and indolent disease, respectively, calculated a single score representing the balance between them, and further generated surrogate scores based on gene and protein expression of the target genes. The balance score outperformed the clinical impact of the two individual scores, as it seemed to capture the prognostic information provided by each of them. Biologically, CLLs with higher balance score showed increased activation of TNF-α/NF-κB and mTOR signaling pathways. Regulatory programs related to progression were predominantly activated in the lymph node microenvironment, whereas those linked to indolent disease appeared to be microenvironment-independent. Finally, we thoroughly validated the balance score as a powerful and independent quantitative prognostic factor for time to first treatment across independent CLL cohorts and data modalities such as chromatin, transcriptome or proteome data. Our findings support the concept that de novo acquisition of chromatin changes in CLL cells plays a dual biological role, and that the balance between pro-progression and pro-indolence is a strong independent determinant of CLL prognosis.
Project description:Chronic lymphocytic leukemia (CLL) is a common and heterogeneous disease. An accurate prediction of outcome is highly relevant for the development of personalized treatment strategies. Microarray technology was shown to be a useful tool for the development of prognostic gene expression scores. However, there are no gene expression scores which are able to predict overall survival in CLL based on the expression of few genes that are better than established prognostic markers. We correlated 151 CLL microarray data sets with overall survival using Cox regression and supervised principal component analysis to derive a prognostic score. This score based on the expression levels of eight genes and was validated in an independent group of 149 CLL patients by quantitative real time PCR. The score was predictive for overall survival and time to treatment in univariate Cox regression in the validation data set (both: p<0.001) and in a multivariate analysis after adjustment for 17p and 11q deletions and the IgVH-status. The score achieved superior prognostic accuracy compared to models based on genomic aberrations and IgVH-status and may support personalized therapy.
Project description:Chronic lymphocytic leukemia (CLL) is a common and heterogeneous disease. An accurate prediction of outcome is highly relevant for the development of personalized treatment strategies. Microarray technology was shown to be a useful tool for the development of prognostic gene expression scores. However, there are no gene expression scores which are able to predict overall survival in CLL based on the expression of few genes that are better than established prognostic markers. We correlated 151 CLL microarray data sets with overall survival using Cox regression and supervised principal component analysis to derive a prognostic score. This score based on the expression levels of eight genes and was validated in an independent group of 149 CLL patients by quantitative real time PCR. The score was predictive for overall survival and time to treatment in univariate Cox regression in the validation data set (both: p<0.001) and in a multivariate analysis after adjustment for 17p and 11q deletions and the IgVH-status. The score achieved superior prognostic accuracy compared to models based on genomic aberrations and IgVH-status and may support personalized therapy. Analysis of 151 samples of peripheral blood mononuclear cells (107 HGU-133plus2; 44 HGU-133A; 44 HGU-133B) from adult patients with chronic lymphocytic leukemia (CLL)
Project description:This study explored resistance functions and their interactions in de novo AML treated with the "7 + 3" induction regimen. We analyzed RNA-sequencing profiles of whole bone marrow samples from 52 de novo AML patients who completed the "7 + 3" regimen and stratified patients into CR (n = 35) and non-CR (n = 17) groups. A systematic gene set analysis revealed significant associations between chemoresistance and mTOR (P < .001), myc (P < .001), mitochondrial oxidative phosphorylation (P < .001), and stemness (P = .002). These functions were independent with regard to gene contents and activity scores. An integration of these four functions showed a prediction of chemoresistance (area under the receiver operating characteristic curve = 0.815) superior to that of each function alone. Moreover, our proposed seven-gene scoring system significantly correlated with the four-function model (r = .97; P < .001) to predict chemoresistance to the "7 + 3" regimen. On multivariate analysis, a seven-gene score of ≥-0.027 (hazard ratio: 11.18; 95% confidence interval: 2.06-60.65; P = .005) was an independent risk factor for induction failure. In summary, Myc, OXPHOS, mTOR, and stemness were responsive for chemoresistance in AML. Treatments other than the "7 + 3" regimen need to be considered for de novo AML patients predicted to be refractory to the "7 + 3" regimen.
Project description:We have previously shown that expression levels of 48 long non-coding RNAs (lncRNAs) can generate a prognostic lncRNA score that independently associates with outcome of older patients (aged ≥ 60 years) with cytogenetically normal acute myeloid leukemia (CN-AML). However, the techniques that were used to identify and measure prognostic lncRNAs are not tailored for real-life clinical testing. Herein we report on an assay (based on the nCounter platform), which is designed to produce targeted measurements of prognostic lncRNAs in a clinically friendly manner. We analyzed an independent cohort of 76 older CN-AML patients and found that the nCounter assay yielded reproducible measurements and that the lncRNA score retained its prognostic value; patients with favorable lncRNA scores were more likely to achieve a complete remission (CR, P=0.009) and have longer diseased-free (DFS, P=0.05), overall (OS, P=0.02) and event-free survival (EFS, P=0.002) than patients with unfavorable lncRNA scores. In multivariable analyses, lncRNA score status independently associated with CR rates (P=0.02), as well as OS (P=0.02) and EFS (P=0.02) duration. To gain biological insights, we examined a dataset of older CN-AML patients, previously analyzed with RNA sequencing. We found genes involved in immune response and B cell receptor signaling (for which targeted inhibitors are currently available) to be enriched in patients with unfavorable lncRNA scores. We conclude that clinically applicable lncRNA profiling is feasible and potentially useful for risk stratification of older CN-AML patients. In addition we identify potentially targetable molecular pathways that are active in the high-risk patients with unfavorable lncRNA scores.
Project description:We analyzed small RNA sequencing data from CD5+/CD19+ B cells of a cohort of indolent and aggressive CLL patients compared with CD19+ B-cells of healthy donors. We identified tsRNA signatures in indolent and aggressive CLL vs. normal B-cells; we also found a drastic dysregulation of the expression of mature tRFs in CLL.
Project description:Gastric cancer is one of the leading causes of cancer mortality worldwide. We compared transcriptomic profiles of gastric cancer with different ferroptosis-related-scores to identify the prognostic significance of ferroptosis-related-score in gastric cancer.
Project description:INTRODUCTION: Progressive muscle-invasive bladder cancer (MIBC) has more aggressive behavior than de novo MIBC. This study aimed to ascertain the differences in gene expression profiles between both MIBC groups and to identify prognostic biomarkers to improve the treatment in these patients. MATERIAL AND METHODS: Retrospective multicentre study in which 212 MIBC patients (104 progressive and 108 de novo) who underwent radical cystectomy in the Hospital Clinic (Barcelona) and Radboud UMC (Nijmegen) were included. Total RNA from formalin-fixed paraffin-embedded tissue samples was obtained. Gene expression profiles of 27,965 coding transcripts were determined in 26 patients using Illumina microarrays. Expression levels of 94 genes selected from microarray data and literature were studied by quantitative PCR in an independent series of 186 de novo and progressive MIBC patients. Survival analysis was performed with the Kaplan-Meier method. R-software and SPSSv23 were used for all calculations. RESULTS: A total of 480 genes were found differently expressed (FDR<0.01) between progressive and de novo MIBC samples. Differential expression of 23 out of the 94 genes selected was validated in an independent set of samples. Survival analysis showed that expression of eight genes were prognostic factors of BCR. CONCLUSION: De novo and progressive MIBC patients show different gene expression profiles. In addition, we have identified eight genes with prognostic value which may contribute to improve BC risk stratification and, consequently, to tailor treatment and surveillance strategies in these patients.
Project description:Gastric cancer is one of the leading causes of cancer mortality worldwide. We compared transcriptomic profiles of advanced gastric cancer with different tumour-stroma-scores to identify the prognostic significance of tumour-stroma-score in advanced gastric cancer.
Project description:The clinical course of patients with chronic lymphocytic leukemia (CLL) is heterogeneous. Several prognostic factors have been identified that can stratify patients into groups that differ in their relative tendency for disease progression and/or survival. Here, we pursued a subnetwork-based analysis of gene expression profiles to discriminate between groups of patients with disparate risks for CLL progression. From an initial cohort of 130 patients, we identified 38 prognostic subnetworks that could predict the relative risk for disease progression requiring therapy from the time of sample collection, more accurately than established markers. The prognostic power of these subnetworks then was validated on two other cohorts of patients. We noted reduced divergence in gene expression between leukemia cells of CLL patients classified at diagnosis with aggressive versus indolent disease over time. The predictive subnetworks vary in levels of expression over time but exhibit increased similarity at later timepoints prior to therapy, suggesting that degenerate pathways apparently converge into common pathways that are associated with disease progression. As such, these results have implications for understanding cancer evolution and for the development of novel treatment strategies for patients with CLL.
Project description:The clinical course of patients with chronic lymphocytic leukemia (CLL) is heterogeneous. Several prognostic factors have been identified that can stratify patients into groups that differ in their relative tendency for disease progression and/or survival. Here, we pursued a subnetwork-based analysis of gene expression profiles to discriminate between groups of patients with disparate risks for CLL progression. From an initial cohort of 130 patients, we identified 38 prognostic subnetworks that could predict the relative risk for disease progression requiring therapy from the time of sample collection, more accurately than established markers. The prognostic power of these subnetworks then was validated on two other cohorts of patients. We noted reduced divergence in gene expression between leukemia cells of CLL patients classified at diagnosis with aggressive versus indolent disease over time. The predictive subnetworks vary in levels of expression over time but exhibit increased similarity at later timepoints prior to therapy, suggesting that degenerate pathways apparently converge into common pathways that are associated with disease progression. As such, these results have implications for understanding cancer evolution and for the development of novel treatment strategies for patients with CLL. Leukemia cells were isolated from blood samples of CLL patients enrolled in the MILE study who had not received prior therapy for CLL, as per the MILE protocol22. Expression data were gathered from samples found to have a CLL cell population with greater than 90% CD5+CD19+, as accessed via flow cytometry. Total RNA was isolated and hybridized to Affymetrix HG-U133+2 GeneChips. This study is about the time to treatment, ie., prognosis instead of diagnosis.