COBLL1,LPLandZAP70expression defines prognostic subgroups of chronic lymphocytic leukemia patients with high accuracy and correlates withIGHVmutational status

Abstract

The clinical course of chronic lymphocytic leukemia (CLL) is highly variable. Patients with unmutated IGHV (U-CLL) usually progress rapidly, whereas patients with mutated IGHV (M-CLL) have a more indolent disease. The expression of several genes correlates closely with the IGHV mutational status and could be used to assess prognosis in CLL. We analyzed the prognostic relevance of COBLL1, LPL, and ZAP70 gene expression, which correlated with IGHV mutational status (p < 0.0001), in 117 CLL patients and established a prognostic parameter dividing the tested cohort according to the disease aggressiveness. Our prognostic parameter was validated on an independent cohort of 161 CLL patients and achieved a high accuracy (94%). Patients divided according to the prognostic parameter differ in overall survival and time to first treatment (p < 0.0001, HR = 2.300/5.970, 95% CI: 1.587-3.450/4.621-15.86). Our approach provides a reliable alternative method to prognosis assessment via IGHV mutational status analysis.

Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets

“…At the current resolution, this factor was consistent with three subgroup models such as proposed by Oakes et al () and Queiros et al () (Appendix Fig S11), although there is suggestive evidence for an underlying continuum. MOFA connected this factor to multiple molecular layers (Appendix Figs S12 and S13), including changes in the expression of genes previously linked to IGHV status (Vasconcelos et al , ; Maloum et al , ; Trojani et al , ; Morabito et al , ; Plesingerova et al , ; Fig B and C) and with drugs that target kinases in or downstream of the B‐cell receptor pathway (Fig D and E).…”

“…Plus or minus symbols on the right indicate the sign of the loading. Genes highlighted in orange were previously described as prognostic markers in CLL and associated with IGHV status (Vasconcelos et al , ; Maloum et al , ; Trojani et al , ; Morabito et al , ; Plesingerova et al , ). Heatmap of gene expression values for genes with the largest weights as in (B). Absolute loadings of the drugs with the largest weights, annotated by target category. Drug response curves for two of the drugs with top weights, stratified by the clusters as in (A).…”

COBLL1 modulates cell morphology and facilitates androgen receptor genomic binding in advanced prostate cancer

“…The COBLL1 locus is genetically associated with the development of metabolic diseases (33) and cortical surface (34). High levels of COBLL1 expression are clinically associated with leukemia (35,36). COBLL1 may be involved in the NF-κB signaling in leukemia cells by stabilizing IKKγ (35), although the molecular functions of COBLL1 are unclear.…”

Multi-Omics factor analysis - a framework for unsupervised integration of multi-omic data sets

“…MOFA connected this factor to multiple molecular layers (Appendix Figure S12, S13), including changes in the expression of genes previously linked to IGHV status (Maloum et al, 2009;Morabito 6 et al, 2015;Plesingerova et al, 2017;Trojani et al, 2012;Vasconcelos et al, 2005) (Fig. 3b,c) and with drugs that target kinases in or downstream of the B-cell receptor (Fig.…”

“…For the clustering analysis using SNF and iCluster, the optimal number of clusters was selected using BIC criterion. Genes highlighted in orange were previously described as prognostic markers in CLL and associated with IGHV status (Maloum et al, 2009;Morabito et al, 2015;Plesingerova et al, 2017;Trojani et al, 2012;Vasconcelos et al, 2005). points on each factor were chosen using maximally selected rank statistics (Hothorn & Lausen, 2003), and p-values were calculated using a Log-rank test on the resulting groups.…”