Gene expression profiling identifies ARSD as a new marker of disease progression and the sphingolipid metabolism as a potential novel metabolism in chronic lymphocytic leukemia

Trojani, Alessandra; Camillo, Barbara Di; Tedeschi, Alessandra; Lodola, Milena; Montesano, Simona; Ricci, Francesca; Vismara, Eleonora; Greco, Antonio; Veronese, Silvio; Orlacchio, Aldo; Martino, Sabata; Colombo, Chiara; Mura, Mariangela; Nichelatti, Michele; Colosimo, Anna; Scarpati, Barbara; Montillo, Marco; Morra, Enrica

doi:10.3233/cbm-2012-0259

Cited by 22 publications

(25 citation statements)

References 39 publications

(52 reference statements)

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“…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).…”

Section: Resultsmentioning

confidence: 96%

“…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).…”

Section: Resultsmentioning

confidence: 99%

“…Vasconcelos et al, 2005;Maloum et al, 2009;Trojani et al, 2012;Morabito et al, 2015;Plesingerova et al, 2017). C Heatmap of gene expression values for genes with the largest weights as in (B).…”

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confidence: 99%

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

Argelaguet

Velten

Arnol

et al. 2018

Molecular Systems Biology

787

804

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Multi‐omics studies promise the improved characterization of biological processes across molecular layers. However, methods for the unsupervised integration of the resulting heterogeneous data sets are lacking. We present Multi‐Omics Factor Analysis (MOFA), a computational method for discovering the principal sources of variation in multi‐omics data sets. MOFA infers a set of (hidden) factors that capture biological and technical sources of variability. It disentangles axes of heterogeneity that are shared across multiple modalities and those specific to individual data modalities. The learnt factors enable a variety of downstream analyses, including identification of sample subgroups, data imputation and the detection of outlier samples. We applied MOFA to a cohort of 200 patient samples of chronic lymphocytic leukaemia, profiled for somatic mutations, RNA expression, DNA methylation and ex vivo drug responses. MOFA identified major dimensions of disease heterogeneity, including immunoglobulin heavy‐chain variable region status, trisomy of chromosome 12 and previously underappreciated drivers, such as response to oxidative stress. In a second application, we used MOFA to analyse single‐cell multi‐omics data, identifying coordinated transcriptional and epigenetic changes along cell differentiation.

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Section: Resultsmentioning

confidence: 96%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

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

Argelaguet

Velten

Arnol

et al. 2018

Molecular Systems Biology

787

804

View full text Add to dashboard Cite

show abstract

“…The SNP was determined to lie within a histone mark of intron 6 using the UCSC Genome Browser (http://genome.ucsc.edu/) and could potentially play a role in regulation of expression. The ARSD was associated with bone and cartilage development and was identified previously as having involvement in sphingolipid metabolism and as a potential biomarker for chronic lymphocytic leukemia [32]. The SNP is in Hardy-Weinberg Equilibrium (HWE p>1×10 −4 ) in the 1000 Genomes controls and the ARDS population and subgroups.…”

Section: Resultsmentioning

confidence: 95%

“…The molecular mechanisms underlying these associations are presently unknown. The ARSD gene encodes a sulfatase that is associated with bone and cartilage development and has been identified previously as having involvement in sphingolipid metabolism (involved in signal transmission and cellular recognition) and as a potential biomarker for chronic lymphocytic leukemia [32]. ARSD protein isoforms have a highly conserved catalytic peptide domain when compared with other arylsulfatases [36], [37].…”

Section: Discussionmentioning

confidence: 99%

Identification of Novel Single Nucleotide Polymorphisms Associated with Acute Respiratory Distress Syndrome by Exome-Seq

et al. 2014

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Acute respiratory distress syndrome (ARDS) is a lung condition characterized by impaired gas exchange with systemic release of inflammatory mediators, causing pulmonary inflammation, vascular leak and hypoxemia. Existing biomarkers have limited effectiveness as diagnostic and therapeutic targets. To identify disease-associating variants in ARDS patients, whole-exome sequencing was performed on 96 ARDS patients, detecting 1,382,399 SNPs. By comparing these exome data to those of the 1000 Genomes Project, we identified a number of single nucleotide polymorphisms (SNP) which are potentially associated with ARDS. 50,190SNPs were found in all case subgroups and controls, of which89 SNPs were associated with susceptibility. We validated three SNPs (rs78142040, rs9605146 and rs3848719) in additional ARDS patients to substantiate their associations with susceptibility, severity and outcome of ARDS. rs78142040 (C>T) occurs within a histone mark (intron 6) of the Arylsulfatase D gene. rs9605146 (G>A) causes a deleterious coding change (proline to leucine) in the XK, Kell blood group complex subunit-related family, member 3 gene. rs3848719 (G>A) is a synonymous SNP in the Zinc-Finger/Leucine-Zipper Co-Transducer NIF1 gene. rs78142040, rs9605146, and rs3848719 are associated significantly with susceptibility to ARDS. rs3848719 is associated with APACHE II score quartile. rs78142040 is associated with 60-day mortality in the overall ARDS patient population. Exome-seq is a powerful tool to identify potential new biomarkers for ARDS. We selectively validated three SNPs which have not been previously associated with ARDS and represent potential new genetic biomarkers for ARDS. Additional validation in larger patient populations and further exploration of underlying molecular mechanisms are warranted.

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Differential DNA methylome profiling of nonfunctioning pituitary adenomas suggesting tumour invasion is correlated with cell adhesion

Zhou

et al. 2016

J Neurooncol

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Global and gene-specific changes to the epigenome are hallmarks of most tumours including those of pituitary origin, and this fact might offer important clues about diagnostic and therapeutic applications. We performed global DNA methylation screening with 6 invasive and 6 noninvasive nonfunctioning pituitary adenomas (PA) to investigate whether DNA methylation was associated with the invasion of nonfunctioning pituitary adenomas. An additional seven PAs were included as an independent cohort to validate the initial results. Five thousand nine hundred thirty-one CpGs were selected (△β ≥0.15 and p value ≤0.01) as differentially methylated sites (DMSs). The hypomethylated DMSs in the invasive PAs were significantly more than the hypermethylated sites. Cluster analysis of 339 CpGs (△β ≥0.25 and p value ≤0.001) demonstrated a complete distinction between the invasive and noninvasive nonfunctioning groups. GO analysis of the three hundred seven corresponding genes shown they were involved in homophilic cell adhesion, cell-cell adhesion, cell adhesion and biological adhesion. The mRNA expression of GALNT9 which contain a validated DMS was significantly downregulated in invasive group. Our findings indicate that the differential DNA methylome profiling of invasive and noninvasive nonfunctioning PAs suggesting tumour invasion is correlated with cell adhesion.

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Gene expression profiling identifies ARSD as a new marker of disease progression and the sphingolipid metabolism as a potential novel metabolism in chronic lymphocytic leukemia

Abstract: ARSD is a novel prognostic factor as the time to start therapy is shorter in patients with high levels of ARSD protein and sphingolipid metabolism could represent a new biological mechanism in CLL.

Cited by 22 publications

References 39 publications

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

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

Identification of Novel Single Nucleotide Polymorphisms Associated with Acute Respiratory Distress Syndrome by Exome-Seq

Differential DNA methylome profiling of nonfunctioning pituitary adenomas suggesting tumour invasion is correlated with cell adhesion

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