We show that their expression is cALL immunophenotype and molecular subtype-specific and correlated with epigenetic modifications on their promoters, much like protein-coding genes. While the biological functions of these vlincRNAs are still unknown, our results suggest they could play a role in cALL etiology or progression.
Childhood ALL is a complex disease comprising multiple molecular subtypes with distinctive somatic genetic alterations such as aneuploidy, chromosomal rearrangements, and point mutations [ 1 ].
Both subtypes are associated with a good prognosis [ 1 , 2 ]. These genetic alterations contribute to leukemogenesis by altering key regulatory processes, subverting normal proliferation control, blocking differentiation, and promoting resistance to death signals [ 2 ].
While these studies primarily focused on the analysis of protein-coding transcripts [ 3 — 6 ], long non-coding RNA lncRNA transcripts have also been shown to have pre-B cALL subtype-specific expression and can modulate cell proliferation, apoptosis, migration, and treatment resistance [ 4 — 7 ].
So far only a few thousand vlincRNAs, whose size ranges from 50kb to 1Mb, have been identified. However, it is known that these transcripts show cell type-specific expression patterns and seem to have biological functions [ 8 — 10 ].
In this study, we described vlincRNA populations expressed in cALL primary samples through whole-transcriptome sequencing, assessed their cALL-subtype specificity, and investigated putative expression regulation mechanisms.
The insight gained from our results on this new class of transcripts will spur further research on their expression and function not only in cALL but also in other cancer types.
We identified a high-confidence subset of vlincRNAs From these, we selected autosomal vlincRNAs having at least reads per sample in a minimum 3 samples to perform differential expression analyses. B Boxplot of vlincRNA transcript sizes. Since it was previously reported that lncRNA expression profiles can accurately classify pre-B cALL molecular subtypes [ 4 , 7 ], we investigated whether this also held true for vlincRNAs. B Hierarchical clustering of discovery samples using Euclidean distance on vlincRNA normalized rld expression values.
C Heatmap of vlincRNA normalized rld expression values in the discovery samples. Some vlincRNAs had expression levels orders of magnitude higher in specific subtypes, suggesting a subtype-specific role e.
Epigenetic tracks of vlincRNAs expressed in specific subtypes. Splicing patterns are more clearly defined with Illumina RNA-seq data. Nearly a third Q4: 7. This experiment showed that the 79 active vlincRNA promoters described above were hypomethylated compared to control cells.
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Motifs from the ETS transcription factor family, with roles in tissue development and cancer progression, were significantly enriched in the t 12;21 subtype, while binding motifs for AP-1 subunits JUN and FOS , implicated in apoptosis, proliferation, and differentiation, were significantly enriched in the HHD subtype. Random regions were generated a thousand times using shuffleBed from bedtools. In this study, we identified and characterized very long intergenic non-coding RNAs vlincRNA expression patterns in 64 primary cALL samples 57 pre-B and 7 pre-T and showed that they are specific to cALL subtypes and that epigenetic modifications correlated with their expression.
The median size and range of the vlincRNA transcripts we identified was of Although it was reported that vlincRNAs are mostly unspliced [ 10 ], we have observed putative splicing patterns in some vlincRNAs Fig 3 , indicating that they could be expressed in both spliced and unspliced forms or less likely be novel pre-mRNAs.
Despite the current cure rate, cALL patients whose disease is refractory to treatment or relapses face a dismal prognosis. In addition, this high cure rate has been achieved through risk-based treatments administered at the expense of considerable toxicity and decreased quality of life.
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Thus, the development of improved risk stratification strategies leading to personalized and targeted treatment is thus essential to improve patient outcome and long-term quality of life.
Previous studies done using microarray technology [ 5 ] or whole-transcriptome sequencing had shown that protein-coding [ 4 , 7 ] or long non-coding RNA transcription profiles [ 4 — 7 ] could be used to discriminate cALL disease subtypes. These results, validated in 35 other primary cALL samples suggest that vlincRNA expression patterns can be used as molecular biomarkers for more accurate disease subtype classification. It would be interesting to see if these results scale with increased cohort size to reach the high cALL subtype classification accuracy demonstrated by Lilljebjorn et al.
This observation is concordant with that of St-Laurent and colleagues [ 9 ] which have reported a wide variation in vlincRNA expression pattern across cancerous and normal cell types. Although these are both acute leukemias, they originate from distinct cell types, play different role, carry specific molecular alterations and thus can be considered as different cancers.
These data and the consistency in expression patterns observed across both our discovery and validation cohorts strongly suggest that they are not transcriptional noise but rather disease-specific and even disease subtype-specific. We further showed that putative vlincRNA promoters are enriched in active chromatin histone marks and had lower DNA methylation levels than healthy cell counterparts.
These data support St-Laurent et al. Together these data strongly suggest that subtype-specific vlincRNA expression is regulated by epigenetic changes. We demonstrated that vlincRNA expression is cALL subtype-specific, but the question remains about the function of these molecules in normal cells and their role in cancer etiology and progression.
Silencing experiments performed on vlincRNAs expressed in K chronic myeloid leukemia cells resulted in an increase in apoptosis, particularly for transcripts that were more broadly expressed across cell types, suggesting that cell type-specific vlincRNAs have more specialized roles [ 9 ]. Others have shown that vlincRNAs are involved in senescence control [ 10 ].
Although further experiments would be required to confirm this, we speculate that cALL subtype-specific vlincRNAs could have distinct biological roles between subtypes. Other cALL vlincRNAs that are more broadly expressed across cALL subtypes or other cancer cell types could also play a role in proliferation or apoptosis; again, additional work is required to assess their roles.
In conclusion, we have identified cALL subtype-specific vlincRNAs transcripts whose expression is controlled by well-known epigenetic mechanisms and modulators. Patients 50 females and 52 males aged from 1—17 years median 5. The Sainte-Justine Institutional Review Board approved the research protocol, and written informed consent was obtained from all participating individuals or their parents. Total RNA was extracted from white blood cell pellets obtained from bone marrow or peripheral blood tissue, followed by a DNase treatment to remove possible genomic DNA contamination.
Replication samples and the Reh cell line were sequenced on the Illumina platform. Reads were aligned to the human genome hg19 using STAR v2. Remaining covered bases were merged if less than bp apart and the resulting segments were merged if less than 10kb apart.
Expression cluster purity was calculated on eight clusters for the discovery cohort and five clusters for the replication cohort cluster numbers returned by mclust [ 29 ]. ChIP-sequencing was performed on bone marrow aspirates or peripheral blood mononuclear cells of a pool of two t 12;21 cases using the previously described procedure [ 30 ].
Reads were aligned with bwa v. Regions separated by less than 1kb were merged and those longer or equal to bp were retained. The longest active regions overlapping candidate promoter regions were retained and reassigned as being active promoters Figs S3 and 6A and 6C. Read density plots and heatmaps of chromatin marks around putative and active vlincRNA promoters were obtained using ngsplot v2.
Reads were aligned to a bisulfite-converted reference genome using bwa and methylation calls were obtained using nxtgen-utils [ 35 ]. IDAT Files were processed using minfi [ 36 ] with funnorm normalization [ 37 ].
Beta values were used as estimates of methylation levels. Methylation values of covered CpGs overlapping the bins were averaged. Boxplots and hierarchical clustering of promoter methylation levels were obtained by averaging methylation values of covered CpGs across the promoters. A third For each promoter, methylation levels were obtained by averaging the values of all overlapping K probes. Circle size increases as Pearson correlation decreases.
The authors are indebted to the patients and their parents for participating in this study. We thank Joseph L. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
National Center for Biotechnology Information , U. PLoS One. Published online Nov Obul Reddy Bandapalli, Editor. Author information Article notes Copyright and License information Disclaimer. Competing Interests: The authors have declared that no competing interests exist.
Received Jun 7; Accepted Oct This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. S4 Fig: Pearson correlations of K methylation levels of t 12;21 active promoters in four normal B cell stages and three cALL subtypes. S1 Table: Study samples. Open in a separate window.
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Fig 3. Fig 4. Fig 5. Methylation regulation of t 12;21 active vlincRNA promoters. Fig 6. Histone mark ChIP-seq read density plots of candidate t 12;21 active promoters. Discussion In this study, we identified and characterized very long intergenic non-coding RNAs vlincRNA expression patterns in 64 primary cALL samples 57 pre-B and 7 pre-T and showed that they are specific to cALL subtypes and that epigenetic modifications correlated with their expression.
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Chromatin immunoprecipitation ChIP sequencing ChIP-sequencing was performed on bone marrow aspirates or peripheral blood mononuclear cells of a pool of two t 12;21 cases using the previously described procedure [ 30 ]. TIF Click here for additional data file. S4 Fig Pearson correlations of K methylation levels of t 12;21 active promoters in four normal B cell stages and three cALL subtypes. S1 Table Study samples. XLSX Click here for additional data file. Acknowledgments The authors are indebted to the patients and their parents for participating in this study.
References 1. Childhood B-acute lymphoblastic leukemia: a genetic update. Exp Hematol Oncol. Mullighan CG. Molecular genetics of B-precursor acute lymphoblastic leukemia.