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T-cell-receptor-activity shaped miR-omes of T-PLL
expression for miR-6724-5p. In order to validate our results from small-RNA sequencing, we performed quantitative real-time polymerase chain reaction (qRT-PCR) analyses of three highly deregulated miR (miR-223-3p, miR-200c-3p, miR-141-3p, Online Supplementary Figure S3A to C) in eight T-PLL and four healthy donor T-cell controls. A strong cor- relation between the results from small-RNA sequencing and qRT-PCR (r2=0.84, P<0.0001, Pearson, Online Supplementary Figure S3D) confirmed differential (over)expression of these miR in T-PLL and underlines the robustness of the sequencing data. Using a previously pub- lished independent data set from single nucleotide poly- morphism (SNP) arrays of 83 T-PLL1 (overlap of 23 cases with the cohort presented here), we identified only small fractions of cases to carry genomic losses of significantly downregulated miR: miR-140-3p, miR-196b-5p (both CN<1.5 in 4.82% of cases), miR-339-3p, and miR-589-5p (both CN<1.5 in 8.43%, Online Supplementary Table S2).
Unsupervised clustering by principal component analysis (PCA) based on miR differentially expressed in T-PLL versus healthy donor T cells indicated a homogeneity across T-PLL samples and confirmed the global differences in the miR profiles between T-PLL and healthy controls (Figure 1B). Interestingly, unsupervised hierarchical clustering analysis of miR expression revealed two clusters of T-PLL cases, which were distinguished by expression of miR-200c and miR-141 family members (Figure 1C): 23 T-PLL cases showed low miR-141/-200c expression as compared to CD3+ pan-T cell controls whereas 23 T-PLL samples had higher than normal T-cell expression of miR-141 and -200c. Besides higher serum lactate dehydrogenase (LDH) levels (P=0.03, Mann-Whitney-Wilcoxon test [MWW]) and a lower incidence of TP53 deletions (by fluorescence in situ hybridisation [FISH], P=0.02, Fisher’s exact test) in the miR- 141/-200c high-expressing cohort, we did not find other dif- ferences between these two subsets (Online Supplementary Table S3). Comparing the transcriptomes of cases allocated to these two separate clusters, we identified 356 genes to be differentially expressed (Online Supplementary Table S4). In line with GSEA based on miR141/200c-correlated genes (see following analyses), we identified the HALLMARK pathways E2F TARGETS (normalized enrichment score [NES]=4.38, q<0.0001) and G2M CHECKPOINT (NES=2.68, q<0.0001) as significantly altered between the two clusters of T-PLL. Furthermore, global miR-ome pro- files were not associated with distinct cellular immunophe- notypes, e.g., neither with CD45RA/RO expression (i.e., “memory-like” vs. “naïve-like” T-PLL) nor with CD4/8 expression (Online Supplementary Figures S4A and B).
MicroRNA-profiles of T-cell prolymphocytic leukemia resemble those of T-cell receptor signaling-activated T cells and form regulatory networks around nodes of DNA damage response and prosurvival signaling
In order to align the miR-ome data with those of global transcriptome alterations, polyA-RNA sequencing was per- formed on PB-isolated tumor cells from 41 miR-character- ized T-PLL patients and seven additional T-PLL patients as well as on CD3+ PB pan-T cells from six age-matched healthy donors. In total, we detected 948 protein-encoding mRNA to be differentially expressed (q<0.05, Online Supplementary Figure S5A; Online Supplementary Table S5). Using this set of deregulated genes, PCA corroborated homogeneity among T-PLL cases and a clear distinction to normal T-cell controls (Online Supplementary Figure S5B). In
accordance with published data, TCL1A (fc=1843, q<0.0001) and CTLA4 (fc=0.06, q<0.0001) were among the most differentially expressed genes in T-PLL versus T-cell controls (Online Supplementary Figure S5C). In their tran- scriptome profiles two T-PLL clustered closer to control T cells than the bulk of cases. However, their miR expression signature (Figure 1C) and clinical presentation did not differ from the overall cohort.
GSEA (HALLMARK gene sets27) determined 34 gene sets as upregulated in T-PLL when compared to T-cell controls, of which 19 gene sets were significantly enriched at a FDR of <5%. Sixteen gene sets were downregulated in T-PLL (11 with FDR <0.05, Online Supplementary Table S6). The iden- tified significantly altered pathways associated with cancer and/or immunology are presented in Figure 2A. These included several HALLMARK gene sets reflecting dysregu- lations in DNA damage response pathways (e.g., DNA REPAIR: NES=-2.18, q=0.005; E2F TAGETS: NES=2.05, q=0.01) and prosurvival signaling (e.g., INFLAMMATORY RESPONSE, NES=3.12, q<0.0001; TNFA SIGNALING VIA NFKB, NES=2.44, q=0.001), in line with previously pub- lished data.1
As T-PLL cells generally display a mature, T-cell activated phenotype,1,11 we investigated whether T-PLL cell miR- omes resemble those of TCR-activated healthy donor- derived T cells. For that, PBMC (to avoid direct manipula- tion of T cells) of four healthy donors were cultured for 72 hours with and without stimulation by anti-CD3/CD28 crosslinking, followed by miR sequencing of CD3+-enriched cells. Sample purities and experimental controls are shown in the Online Supplementary Figure S6. We identified 56 miR which are differentially expressed in response to TCR acti- vation (q<0.05, Online Supplementary Figure S7A; Online Supplementary Table S7). PCA indicated homogeneity with- in both groups (T-PLL and normal PBMC) as well as global differences between their TCR-induced miR profiles (Online Supplementary Figure S7B). We identified miR known to be affected by TCR activation (e.g., miR-150-5p)31 as well as previously unreported miR (e.g., miR-18a-5p; Online Supplementary Figure S7C). Integrative PCA based on differentially expressed miR in T-PLL versus healthy controls (Figure 1C) showed that the stimulated (over unstimulated) T cells clustered closer to T-PLL (Figure 2B). Fittingly, unsu- pervised clustering comparing TCR-stimulated T cells to unstimulated controls confirmed that the miR profiles of T- PLL cells resemble the miR-ome of TCR-activated healthy donor-derived T cells (Figure 2C).
We next assessed implicated functional relationships by predicted mRNA targets for each deregulated miR in T-PLL. For that, we (i) ranked mRNA based on their degree of cor- relation with a specific miR and (ii) performed HALLMARK set GSEA on these ranked mRNA. Pathways reflecting dys- regulations of DNA damage response and prosurvival sig- naling emerged as predominantly associated with the alter- ations of miR expression. Exemplary HALLMARK path- ways are shown in Figure 3A, a full list of gene sets is dis- played in Online Supplementary Figure S8. For example, we obtained highly significant NES for the E2F TARGET and the IL2 STAT5 SIGNALING HALLMARK gene sets for (i) the transcriptome of T-PLL as compared to the one of healthy controls (E2F TARGETS: NES=1.92, q=0.02; IL2 STAT5 SIGNALING: NES=-2.86, q<0.0001, Online Supplementary Table S6) and (ii) for most of the miR differ- entially expressed in T-PLL (Figure 3A).
Overall, there was a striking similarity of the miR pro-
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