Dataset Information

Proteogenomic subtyping of chronic lymphocytic leukemia identifies subgroups with contrasting clinical outcome and distinct ex-vivo drug response profile – DIA Validation

ABSTRACT: We have performed a comprehensive proteomic analysis of clinical patient samples of chronic lymphocytic leukemia (CLL) alongside genome-, transcriptome- and ex-vivo drug response profiling. Trisomy 12 and IGHV mutation status had the strongest impact on the proteome and transcriptome; and SF3B1 mutations preferentially affected the proteome. Unsupervised clustering of the proteome data partitioned CLL patients into six protein based subgroups (PG) with contrasting clinical behavior. PG1-4 could be explained by the impact of trisomy 12 and IGHV mutation status on protein abundances and another subgroup (PG6), was enriched for TP53 mutations. In addition we uncovered a new subgroup (PG5) only detectable from the proteome, characterized by low expression of central B-cell receptor proteins, altered splicing, metabolic reprogramming and increased sensitivity to proteasomal inhibition. We further validated the existence of this subgroup by conducting DIA based proteomics of an additional 167 patients. This entry contains the DIA-data for 167 patients used to validate the subgroups identified using HiRIEF-LC-MS/MS (see separate accession: PXD017453) as well as DIA data for 36 of the original discovery cohort. https://www.ebi.ac.uk/pride/archive/projects/PXD028936

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): B Cell

DISEASE(S): Chronic Lymphocytic Leukemia

SUBMITTER: Georgios Mermelekas

LAB HEAD: Janne Lehtiö

PROVIDER: PXD024544 | Pride | 2022-10-19

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	CLL_DIA_GMMVRJ_Search_Output.txt	Txt
	GMMVRJ_DIA_20200611_CLL01.raw	Raw
	GMMVRJ_DIA_20200611_CLL02.raw	Raw
	GMMVRJ_DIA_20200611_CLL03.raw	Raw
	GMMVRJ_DIA_20200611_CLL04.raw	Raw

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Publications

Proteogenomics refines the molecular classification of chronic lymphocytic leukemia.

Herbst Sophie A SA Vesterlund Mattias M Helmboldt Alexander J AJ Jafari Rozbeh R Siavelis Ioannis I Stahl Matthias M Schitter Eva C EC Liebers Nora N Brinkmann Berit J BJ Czernilofsky Felix F Roider Tobias T Bruch Peter-Martin PM Iskar Murat M Kittai Adam A Huang Ying Y Lu Junyan J Richter Sarah S Mermelekas Georgios G Umer Husen Muhammad HM Knoll Mareike M Kolb Carolin C Lenze Angela A Cao Xiaofang X Österholm Cecilia C Wahnschaffe Linus L Herling Carmen C Scheinost Sebastian S Ganzinger Matthias M Mansouri Larry L Kriegsmann Katharina K Kriegsmann Mark M Anders Simon S Zapatka Marc M Del Poeta Giovanni G Zucchetto Antonella A Bomben Riccardo R Gattei Valter V Dreger Peter P Woyach Jennifer J Herling Marco M Müller-Tidow Carsten C Rosenquist Richard R Stilgenbauer Stephan S Zenz Thorsten T Huber Wolfgang W Tausch Eugen E Lehtiö Janne J Dietrich Sascha S

Nature communications 20221020 1

Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery coh ...[more]

PMID: 36266272

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Project description:Prospective series of 136 clinical monoclonal B lymphocytosis (cMBL) and 216 chronic lymphocytic leukemia (CLL) Rai 0 patients, were investigated in this study. While the distribution of CD38 and ZAP-70 positivity was similar, IGHV-mutated cases were more frequent among cMBL (P = 0.005). A Cox multivariate analysis on the whole patient cohort showed that cMBL condition was predictive of longer PFS, while CD38 expression and IGHV-unmutated status and CD38 expression correlated significantly with a shorter PFS in cMBL and Rai0-CLL, respectively. Trisomy 12, 11q- and 17p- abnormalities were scanty and of no predictive value in both conditions. Notably, gene and miRNA expression profiling showed no significant differences between cMBL and Rai0-CLL. Furthermore, similar gene and miRNA expression signatures were found in cMBL and Rai0-CLL according to the IGHV gene mutational status: that is, unmutated cases had different signatures from mutated cases, irrespectively of the cMBL or CLL condition. Overall, our study based on a prospective series of patients indicates that no major biological differences exist in cMBL compared to Rai0-CLL, suggesting that this two entities mainly differ for the initial size of the monoclonal cell population which may reflect in the longer time for clonal expansion. This series of microarray experiments contains the microRNA profiles of purified B-cell chronic lymphocytic leukemia (B-CLL) cells obtained from 150 patients (Binet stage A) including 39 cMBL and 111 Rai0-CLL. Peripheral blood mononuclear cells from CLL patients were isolated by Ficoll-Hypaque (Seromed, Biochrom KG, Berlin, Germany) density-gradient centrifugation. For gene and miRNA expression profiling experiments CLL cells were enriched by negative selection with the EasySep-Human B cell enrichment kit without CD43 depletion (Stem Cell Technologies) using the fully automated protocol of immunomagnetic cell separation with RoboSepTM (Stem Cell Technologies). The proportion of CD5/CD19/CD23 triple positive B cells in the suspension was determined by direct immunofluorescence with antibodies for CD19 FITC, CD23 PE and CD5 PC5. 500 nanograms of total RNA was processed in accordance with the manufacturer's protocols (Agilent Technologies) to generate Cy3-labelled RNA, which were purified on chromatography columns (Micro Biospin 6, Bio-Rad, Hercules, CA) and then hybridized on an Agilent microarray (G4470B) at 55C for 17 hr in a rotating oven. Images at 5 um resolution were generated using an Agilent scanner G2505B. The Feature Extraction 10.7.3.1 software (Agilent Technologies) was used to obtain the microarray raw-data. The raw gTotalGeneSignal has been recalculated using the procedures described in Agilent Feature Extraction Software version 10.1 manual. Non-human probes, miRNAs flagged as 'absent' (i.e. expressed below background levels) throughout the whole dataset and miRNAs expired according to Sanger miRBase Release 15 (April 2010) were discarded, and a quantile normalization was applied on raw data using the aroma.light package for Bioconducor. The data were then converted to obtain positive values throughout the dataset, at a minimum value of 1, and log2 transformed.