Enteropathy-associated T cell lymphoma subtypes are characterized by loss of function of SETD2

Enteropathy-associated T cell lymphoma (EATL) is a lethal, and the most common, neoplastic complication of celiac disease. Here, we defined the genetic landscape of EATL through whole-exome sequencing of 69 EATL tumors. SETD2 was the most frequently silenced gene in EATL (32% of cases). The JAK-STAT pathway was the most frequently mutated pathway, with frequent mutations in STAT5B as well as JAK1 , JAK3 , STAT3 , and SOCS1 . We also identified mutations in KRAS , TP53 , and TERT . Type I EATL and type II EATL (monomorphic epitheliotropic intestinal T cell lymphoma) had highly overlapping genetic alterations indicating shared mechanisms underlying their pathogenesis. We modeled the effects of SETD2 loss in vivo by developing a T cell–specific knockout mouse. These mice manifested an expansion of γδ T cells, indicating novel roles for SETD2 in T cell development and lymphomagenesis. Our data render the most comprehensive genetic portrait yet of this uncommon but lethal disease and may inform future classification schemes

Data from: Selective depletion of rRNA enables whole transcriptome profiling of archival fixed tissue

We report a method for Selective Depletion of abundant RNA (SDRNA) species from Human total RNA isolated from formalin-fixed, paraffin-embedded (FFPE) tissue, here demonstrating removal of ribosomal and mitochondrial transcripts from clinical FFPE tissue RNA archived up to 20 years. Importantly, SDRNA removes 98% of targeted RNAs while preserving relative abundance profiles of non-targeted RNAs, enabling routine whole transcriptome analysis of clinically valuable archival tissue specimens by Next-Generation Sequencing

gene_counts

Gene level read counts for the eight libraries reported in the manuscript

Selective Depletion of rRNA Enables Whole Transcriptome Profiling of Archival Fixed Tissue

<div><p>We report a method for <u>S</u>elective <u>D</u>epletion of abundant <u>RNA</u> (<u>SDRNA</u>) species from Human total RNA isolated from formalin-fixed, paraffin-embedded (FFPE) tissue, here demonstrating removal of ribosomal and mitochondrial transcripts from clinical FFPE tissue RNA archived up to 20 years. Importantly, SDRNA removes 98% of targeted RNAs while preserving relative abundance profiles of non-targeted RNAs, enabling routine whole transcriptome analysis of clinically valuable archival tissue specimens by Next-Generation Sequencing.</p> </div

Distribution of uniquely-mapped reads across broad RNA classes. rRNA class includes all reads mapping to the 13 kb transcript shown in Supplementary

<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0042882#pone-0042882-g001" target="_blank"><b>Figure 1a</b></a><b>.</b> Mito class refers to all reads mapping to the mitochondrial genome shown in Supplementary <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0042882#pone-0042882-g001" target="_blank">Figure 1b</a>. The Intergenic class encompasses all remaining reads not mapping to RefSeq annotations or their associated introns. FF – Fresh-frozen; FFPE – Formalin-fixed, paraffin-embedded. (a) polyA+ FF breast RNA.(b) SDRNA2 FF breast RNA. (c) SDRNA2 FFPE RNA pool.</p

Scatterplots of RefSeq transcript abundance: Depleted vs. Undepleted.

<p>Log₁₀ read counts are plotted. Transcripts with zero reads are excluded from analysis. An identity line is shown in each plot for reference. Sub-populations are indicated as follows: Black cross – sno-, sc-, sn- and mir-RNAs from RefSeq; Black and red circles – Genes homologous to SDRNA and SDRNA2 probes, respectively (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0042882#pone.0042882.s007" target="_blank">Table S4</a>); Light blue circles – All other RefSeq transcripts. FF – Fresh-frozen; FFPE – Formalin-fixed, paraffin-embedded. (<b>a</b>) FF Breast RNA: not depleted vs polyA+ (<b>b</b>) FF Breast RNA: not depleted vs SDRNA1 and (<b>c</b>) FF Breast RNA: not depleted vs SDRNA2. (<b>d</b>) FFPE RNA pool: not depleted vs SDRNA1 and (<b>e</b>) FFPE RNA pool: not depleted vs SDRNA2.</p

Scatterplots of RefSeq transcript abundance.

<p>Log₁₀ read counts are plotted. Transcripts with zero reads are excluded from analysis. An identity line is shown in each plot for reference. Sub-populations are indicated as follows: Black cross – sno-, sc-, sn- and mir-RNAs from RefSeq; Black and red circles – Genes homologous to SDRNA and SDRNA2 probes, respectively (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0042882#pone.0042882.s007" target="_blank">Table S4</a>); Light blue circles – All other RefSeq transcripts. FF – Fresh-frozen; FFPE – Formalin-fixed, paraffin-embedded. (<b>a</b>) FFPE RNA Pool: SDRNA1 vs SDRNA2. (<b>b</b>) FF breast RNA : polyA+ vs SDRNA1. (<b>c</b>) FF breast RNA : polyA+ vs SDRNA2.</p

Read density of targeted regions.

<p>Read density plotted across regions targeted for depletion and compared between different depletion methods. Regions targeted for depletion (SDRNA1 = green, SDRNA2 = red and green) are indicated at the bottom of each figure. Density values were computed using igvtools count (<a href="http://www.broadinstitute.org/igv/igvtools" target="_blank">www.broadinstitute.org/igv/igvtools</a>) and plotted using UCSC’s Genome Browser. FF – Fresh-frozen; FFPE – Formalin-fixed, paraffin-embedded.(a) Reads are mapped to chrUn_gl000220, an unplaced genomic contig from hg19 containing the 13 kb rRNA transcript described in Supplementary <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0042882#pone-0042882-g001" target="_blank">Figure 1a</a>. (b) Reads are mapped to the human mitochondrion from hg18 (Supplementary <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0042882#pone-0042882-g001" target="_blank">Figure 1b</a>).</p

Proportion of reads uniquely-mapping to rRNA or non-rRNA categories.

<p>The rRNA category represents all rRNAs encoded in both nuclear and mitochondrial genomes (see Supplementary <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0042882#pone-0042882-g001" target="_blank">Figure 1</a>). Non-rRNA includes all other uniquely-mapping reads.</p