Supplementary Methods
Next generation sequencing (NGS)
Tumor cell rich areas of the DLBCL components were microdissected in patients 1 and 2 and
WGS was accomplished. Non-tumor DNA was obtained from a piece of non-affected lymph
node in patient 1 and peripheral blood in patient 2. DNA was extracted using the QiaAmp
Micro Kit (Qiagen, Hilden, Germany). After library preparation starting from 200 ng of
genomic DNA with the NEBNext Ultra DNA Library Prep Kit (New England Biolabs,
Whitby, Ontario, Canada), WGS was accomplished in 100 bp paired-end mode on an
Illumina HiSeq instrument with a median coverage of 100x (Illumina, San Diego, California)
using v3 sequencing chemistry at Genecore (EMBL, Heidelberg, Germany). For targeted
resequencing of candidate genes, a custom enrichment panel covering the coding exons of 62
genes was created (Suppl. Table 1, HaloPlex Target Enrichment System, Agilent, Santa Clara,
CA, USA) and multiplexed enriched DNA fragments were sequenced as 100 bp paired reads
using an Illumina HiSeq instrument (Illumina, San Diego, California) obtaining a median
coverage of 1000x. For validation, 30 single microdissected tumor cells were pooled for PCR
reaction, digested by proteinase K (Roche, Grenzach-Wyhlen, Germany) and amplified in a
two round seminested PCR as described previously (primers listed in Suppl. Table 2),
followed by Sanger sequencing of the PCR products.1 Genes selected for confirmation were
chosen according to their biological function based on literature research.
WGS data analysis
Sequenced DNA reads were aligned to build hg19 of the human reference genome with bwa
(PMID: 19451168) using default parameters. Alignment post-processing included duplicate
removal and indel realignment using the Genome Analysis Toolkit (GATK) (PMID:
20644199). Somatic single-nucleotide variants (SNVs) were identified using an adapted
version of the EMBL in-house somatic variant analysis pipeline2 and Genomatix software
(Genomatix, Munich, Germany). Specifically, SNVs were initially identified using SAMtools
mpileup (PMID: 19505943) and GATK (PMID: 20644199), and further annotated using
ANNOVAR (PMID: 20601685). To facilitate a fast classification and identification of
candidate driver mutations, all identified coding SNVs were annotated for presence in dbSNP
and for presence in the April 2012 SNV release of the 1000 Genomes Project
(http://1000genomes.org). All nonsynonymous coding changes were annotated with the
corresponding amino acid change, including a computational prediction of the functional
impact on the structure and function of the respective protein using SIFT and PolyPhen-2
(PMID: 19561590, PMID: 2035451).
Targeted deep sequencing data analysis
Raw DNA sequencing reads were preprocessed using cutadapt and Trimmomatic (PMID:
24695404), to remove the Haloplex-specific adapter sequences, to filter and trim low-quality
bases and to crop the first 5 bp biased from the Haloplex restriction enzyme footprint. All
trimmed reads shorter than 36 bp were discarded. The remaining pairs were aligned to build
hg19 of the human reference genome with bwa mem v0.7.7 (PMID: 19451168). Somatic
SNVs were identified using SAMtools mpileup (PMID: 19505943) and VarScan (PMID:
22300766), and filtered for allele frequency based on the estimated tumor cell content. All
remaining somatic candidate SNVs were annotated using ANNOVAR (PMID: 20601685) and
a custom python script.
Western blot, quantitative PCR and immunohistochemistry
Immunohistochemical stainings were performed as described previously.3 For Western blot
analysis, standard conditions were applied. Antibodies, providers and dilutions are listed in
Suppl. Table 3. Quantitative real time PCR (RT-PCR) was performed on an ABI Prism
7900HT Fast Real-Time PCR System (Life Technologies, Darmstadt, Germany) using two
previously published primer pairs for total SGK1 and SGK1 isoform 14 and previously
published primers for GAPDH5 with SYBR green. The following intron-spanning primers for
DUSP2 were created: Forward 5´-GCC GAG ACA AGA GGA CTC C-3´, Reverse 5´-GGA
CAA AAC CAG CCG CTC C-3’. The cycling program consisted of 95°C for 3 min, followed
by 45 cycles of 95°C for 15 s/61°C for 15 s/72°C for 20 s. Fold changes were calculated using
the 2-Ct method. Western blot images were acquired with a Fusion SL (Peqlab, Erlagen,
Germany) and histologic images with a Nikon Eclipse E1000 and Nikon Digital Camera
DXM 1200 (Nikon, Düsseldorf, Germany).
Cell culture and inhibitor experiments
Cell lines DEV, Daudi, Namalwa, OCI-Ly3, Farage, BJAB, MOLP-8, L1236, L428, HDLM2 and KM-H2 were cultured in RPMI-1640 medium with stable glutamine supplemented with
10 or 20% fetal calf serum (Biochrom AG, Berlin, Germany). Cell lines were obtained from
the German Collection of Microorganisms and cell cultures (DSMZ, Braunschweig,
Germany). For the SGK1 inhibitor experiments 105 cells were seeded per well in 1 ml
medium into 24-well plates 6 hours prior to inhibitor administration. The SGK1 inhibitor
EMD638683 was administered for 48 hours at a concentration of 150, 225 or 300 µM. For
comparison, cells were treated with the solvent control (3 µl DMSO). After 48 hours cells
were either analyzed or supplied with fresh medium with either inhibitor or solvent control
and analyzed after 120 hours. Cell viability was assessed using propidium iodide staining, and
analysis was performed on MACSQuant using the MACSQuantify software (Miltenyi
Biotech, Bergisch Gladbach, Germany) and FlowJo software (version 7.6.1). All experiments
were run at least two times in triplicates.
Overexpression of SGK1 wild type protein in the GCB-type DLBCL cell line SU-DHL-8
Mutations described by Zhang et al.6 were confirmed in the SU-DHL-8 cell line by Sanger
sequencing. Since SGK1 transcript variant 1 was the most strongly expressed SGK1 isoform
in the DEV cell line, the cDNA sequence of SGK1 transcript variant 1 was cloned into a
retroviral vector. In addition, the retroviral vector co-expressed the green fluorescent protein
(GFP) as a marker gene via an internal ribosome entry site (IRES) to enable flow cytometric
analysis of gene modified cells. The retroviral vector, the production of GALV-envelope
pseudotyped retroviral vector particles and the transduction procedure are described
elsewhere.7 Transduction efficacy for both, the SGK1-encoding and the control vector was
limited to 5-15%, to ensure low vector copy numbers per cell and thereby minimizing the risk
of undesired retroviral integration-associated side effects. To enrich SGK1-overexpressing
cells and empty vector (solely GFP-encoding) transduced cells, SU-DHL-8 cells were
subjected to fluorescence-activated cell sorting (FACSAria, Becton-Dickinson, Heidelberg,
Germany) and a purity of > 95% was achieved. Eight days after transduction and expansion of
sorted gene-modified cells, Western blot analysis confirmed SGK1 protein overexpression in
SGK1-transduced cells. Proliferation assays and apoptotic cell staining were performed with
SGK1-, GFP- and Mock-transduced SU-DHL-8 cells according to the manufacturer´s
protocol (CellTraceTM Violet, Thermo Fisher, Waltham, MA USA; Annexin V, BectonDickinson).
References
1.
Mottok A, Renne C, Willenbrock K, Hansmann ML, Brauninger A. Somatic
hypermutation of SOCS1 in lymphocyte-predominant Hodgkin lymphoma is accompanied by
high JAK2 expression and activation of STAT6. Blood. 2007;110:3387-3390.
2.
Rausch T, Jones DT, Zapatka M, et al. Genome sequencing of pediatric
medulloblastoma links catastrophic DNA rearrangements with TP53 mutations. Cell.
2012;148:59-71.
3.
Hartmann S, Agostinelli C, Klapper W, et al. Revising the historical collection of
epithelioid cell-rich lymphomas of the Kiel Lymph Node Registry: what is Lennert's
lymphoma nowadays? Histopathology. 2011;59:1173-1182.
4.
Fagerli UM, Ullrich K, Stuhmer T, et al. Serum/glucocorticoid-regulated kinase 1
(SGK1) is a prominent target gene of the transcriptional response to cytokines in multiple
myeloma and supports the growth of myeloma cells. Oncogene. 2011;30:3198-3206.
5.
Bohle V, Doring C, Hansmann ML, Küppers R. Role of early B-cell factor 1 (EBF1)
in Hodgkin lymphoma. Leukemia. 2013;27:671-679.
6.
Zhang J, Grubor V, Love CL, et al. Genetic heterogeneity of diffuse large B-cell
lymphoma. Proc Natl Acad Sci U S A. 2013;110:1398-1403.
7.
Newrzela S, Cornils K, Li Z, et al. Resistance of mature T cells to oncogene
transformation. Blood. 2008;112:2278-2286.