"Integrative analysis reveals selective 9p24.1 amplification, increased PD-1 ligand expression, and further induction via JAK2 in nodular sclerosing Hodgkin lymphoma and primary mediastinal large B-cell lymphoma".

Michael R. Green ¹, Stefano Monti ², Scott J. Rodig ³, Przemyslaw Juszczynski ¹, Treeve Currie ³, Evan O'Donnell ¹, Bjoern Chapuy ¹, Kunihiko Takeyama ¹, Donna Neuberg ⁴, Todd R. Golub ², Jeffery L. Kutok ³, and Margaret A. Shipp ^1, *

¹ Department of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, United States;
² Broad Institute, Cambridge, MA, United States;
³ Department of Pathology, Brigham & Women's Hospital, Boston, MA, United States;
⁴ Department of Biostatistics, Dana Farber Cancer Institute, Boston, MA, United States

* Corresponding author; Margaret A. Shipp, Dana-Farber Cancer Institute, Boston, MA,
phone: 617-632-3874, fax: 617-632-4734, email: margaret_shipp@dfci.harvard.edu

Classical Hodgkin Lymphoma (cHL) and Mediastinal Large B-cell Lymphoma (MLBCL) are lymphoid malignancies with certain shared clinical, histological and molecular features. Primary cHLs and MLBCLs include variable numbers of malignant cells within an inflammatory infiltrate suggesting that these tumors escape immune surveillance. Herein, we integrate high-resolution copy number data with transcriptional profiles and identify the immunoregulatory genes, PD-L1 and PD-L2, as key targets at the 9p24.1 amplification peak in HL and MLBCL cell lines. We extend these findings to laser-capture microdissected primary Hodgkin Reed-Sternberg cells and primary MLBCLs and find that PD-1 ligand/9p24.1 amplification is restricted to nodular sclerosing HL, the cHL subtype most closely related to MLBCL. Using quantitative immuno-histo-chemical methods, we document the association between 9p24.1 copy number and PD-1 ligand expression in primary tumors. In cHL and MLBCL, the extended 9p24.1 amplification region also included the JAK2 locus. Of note, JAK2 amplification increased JAK2 protein expression and activity, specifically induced PD-1 ligand transcription and enhanced sensitivity to JAK2 inhibition. Therefore, 9p24.1 amplification is a disease-specific structural alteration that increases both the gene dosage of PD-1 ligands and their induction via JAK2, defining the PD-1 pathway and JAK2 as complementary rational therapeutic targets.

Classical Hodgkin lymphoma (cHL) is a B-cell malignancy that occurs
frequently in Western countries and commonly affects young adults 1. These
tumors are characterised by small numbers of neoplastic Reed-Sternberg
(RS) cells within an extensive inflammatory/immune cell infiltrate. There are
four subtypes of cHL, two of which comprise ~90% of cases -- nodular
sclerosing Hodgkin’s lymphoma (NSHL) (60% of cases) and mixed cellularity
Hodgkin lymphoma (MCHL) (30% of cases). cHLs lack surface-Ig expression
and B-cell receptor (BCR) mediated signals and rely on alternative survival
pathways including aberrant NF-kB signaling 1.

In previous studies, we and others defined shared molecular features of cHL
and a specific subtype of DLBCL, primary mediastinal large B-cell lymphoma
(MLBCL) 2,3. Like cHL, MLBCLs have a Th2-skewed cytokine profile,
decreased expression of BCR signaling pathway components and constitutive
activation of NF-kB 2. MLBCL also exhibits certain clinical and histological
similarities to cHL, particularly the NSHL subtype 4,5. For example, both
diseases are most common in young adults and often present as an anterior
mediastinal or localized nodal mass 2, 4,5. In addition, both MLBCLs and
NSHLs include bands of sclerotic tissue and immune/inflammatory cell
infiltrates 4,5. However, the inflammatory infiltrate is less prominent in
MLBCLs, which have a more diffuse growth pattern 4.

Although cHLs have an extensive polymorphous inflammatory infiltrate, there
is little evidence of an effective host anti-tumor immune response. In fact,
recent studies indicate that Hodgkin RS cells produce certain molecules that
limit the efficacy of T-cell mediated anti-tumor immune responses 1, 6. For
example, Hodgkin RS cells selectively express the immuno-regulatory glycan-binding
protein, galectin-1, which fosters a Th2/T-regulatory cell-skewed tumor
microenvironment 6. Primary HLs RS cells also variably express the PDL1/B7-1
ligand whereas tumor-infiltrating T-cells express the co-inhibitory receptor,
PD-1 7. Similarly, primary MLBCLs are reported to express PD-L2 3.

The natural function of PD-1 signaling is to limit certain T-cell mediated
immune responses 8. Normal antigen presenting cells, dendritic cells and
macrophages express PD-1 ligands which engage PD-1 receptors on
activated T cells 8,9. Upon ligand binding, the PD-1 receptor recruits the SHP2
phosphatase to the immunoreceptor complex resulting in dephosphorylation
of proximal T-cell receptor (TCR) signaling molecules (CD3d, ZAP70 and
PKCq) and attenuation of TCR signaling 8. In addition, PD-L1 inhibits CD28
co-stimulation by competitively binding to the CD28 ligand, CD80 (B7-1) 10.
PD-1 signaling results in “T-cell exhaustion”, a temporary inhibition of
activation and proliferation that can be reversed upon removal of the PD-1
signal. Furthermore, PD-L1 also promotes the induction and maintenance of
PD-1+ T regulatory cells 11.

Emerging data suggests that viruses and tumors have developed
mechanisms that exploit the PD-1 pathway to evade immune detection. In
models of chronic viral infection, engagement of PD-1 receptors triggers T-cell
“exhaustion” and the progressive loss of effector T-cell function and
proliferative capacity 8. In murine cancer models, the tumor cell expression of
PD-1 ligands inhibits T-cell activation and promotes the apoptosis of tumor-specific
T cells 12,13. PD-1 ligands are also expressed and associated with an
unfavorable prognosis in multiple human tumors, including malignant
melanoma, colon, pancreatic, hepatocellular and ovarian carcinoma 14-19.
Despite the prognostic significance of PD-1 ligand expression and the
demonstrated role of PD-1 signaling in tumor immune privilege, structural
genetic mechanisms for deregulated PD-1 ligand expression in cancer have
not been described.

The PD-1 ligand genes, PD-L1 and PD-L2, are located on chromosome
9p24.1 and separated by only 42kb 8. Of interest, 9p copy gain has been
described in both HL and MLBCL with low resolution techniques such as
comparative genomic hybridization 20,21. Several genes residing on 9p have
been postulated to play a role in cHL and MLBCL although the key targets of
this genetic alteration 3, 21-23 remain undefined. Herein, we integrate copy
number data from high density single nucleotide polymorphism (HD SNP)
arrays with paired transcriptional profiles and identify the PD-1 ligands as key
targets of the 9p24.1 amplification in NSHL and MLBCL. In addition, we
characterize a novel regulatory loop in which JAK2, located 322kb upstream
from PD-L1 on 9p24.1, further augments PD-1 ligand expression in these
tumors.

Materials and Methods:

Cell Lines

This study was approved by the Institutional Review Board of the Dana-
Farber Cancer Institute and Brigham and Women's Hospital. The HL cell lines
L428, L1236 and KMH2 and the DLBCL cell lines SUDHL4, OCILy1,
KARPAS422, PFEIFFER, SUDHL6 were grown in RPMI medium
supplemented with 10% heat-inactivated fetal bovine serum (FBS). The HL
cell lines L-540 and HD-LM-2 and the MLBCL cell line KARPAS1106P were
maintained in RPMI with 20% heat-inactivated FBS. The HL cell line SUPHD1
was grown in McCoy’s 5A with 20% heat-inactivated FBS. Media for all cell
lines were supplemented with 10mM HEPES buffer, 4 mM L-glutamine, 50
U/mL penicillin and 50 U/mL streptomycin.

Integrative Analysis

Genomic DNAs from 18 DLBCL, 1 MLBCL and 6 HL cell lines and 21
peripheral blood lymphocyte samples from normal donors were extracted as
previously described and profiled using Affymetrix SNP6.0 microarrays 24,
which include over 900,000 SNP probes and ~950,000 additional probes for
copy number.

The inference of DNA copy number from ‘.cel’ files was performed using a
previously described GenePattern pipeline 25. Data is available from the Gene
Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/), accession number
GSE22208. Data was segmented using the Circular Binary Segmentation
(CBS) algorithm 26,27, and naturally occurring copy number variants were
removed prior to assessment of the significance of copy number alterations
across samples with the GISTIC algorithm 28. GISTIC defines regions of
interest with associated FDR q-values below a predefined threshold, and a
smaller peak (or peaks) within each region defined by the set of contiguous
markers with the highest q-values.

Transcriptional profiling was performed for all cell lines using Affymetrix U133
A&B microarrays as previously described 6. Integrative analysis, combining
DNA copy number and gene transcript data, was performed in order to assess
relationships between DNA copy number change and alteration in gene
transcript abundance so as to refine the list of candidate genes within
alteration regions. Genes within the peak (region) of GISTIC-identified
alterations were tested for difference in expression between samples with or
without each lesion by a two-group t-statistic, and significance was assessed
both by permutation test and by asymptotically derived p-values. FDR qvalues
were derived by taking the union of all genes within all the peaks
(regions). Genes were considered positive by integrative analysis if
differences in transcript abundance attained an FDR<0.25 by at least one of
the two procedures (permutation-based or asymptotic). Additional detailed
integrative analysis methodology is included in the Supplementary Data.

Flow Cytometry

Flow cytometry was performed by resuspending 1x10⁶ cells in 100mL of PBS,
incubating with 500mg of antibody for 30 minutes at room temperature,
washing once in PBS and resuspending in a volume of 500mL. Cells were
stained with PE-conjugated antibodies specific for PD-L1 (Clone 29E.2A3),
PD-L2 (Clone 24F.10C12) or the analogous isotype controls (IgG2b k and
IgG2a k, respectively) (BioLegend, San Diego, CA). Following staining,
20,000 cells were analysed using a BD FACSCanto flow cytometer (BD
Biosciences, San Jose, CA). FlowJo software was used for selection of viable
cells by forward and side scatter and subsequent generation of histograms
and median fluorescence intensities. Fluorescence intensities for each
antigen were normalized to their respective isotype controls.

Intracellular phospho-flow was performed by fixing cells with BD CytoFix
fixation buffer (BD Biosciences, San Jose, CA) followed by permeablization
with BD Perm Buffer II (BD Biosciences, San Jose, CA) and staining with a
PE-conjugated antibodies to STAT1(pY701) (BD Biosciences, San Jose, CA).
Phospho-flow was normalized to fixed, permeablized and unstained cells.

Primary Tumor Specimens

Primary tumor specimens included 23 classical Hodgkin lymphomas (cHLs)
and 41 primary MLBCLs. All specimens were identified by clinical criteria and
pathologic features and reviewed by expert hematopatholigists (SR & JK) to
confirm diagnosis. Primary cHLs included 7 of the MCHL subtype and 16 of
the NSHL subtype. Primary MLBCLs included 33 previously described tumors
[Savage et al., 2003] and 8 additional cases.

Laser-Capture Microdissection of Primary Hodgkin Reed Sternberg (RS)
Cells

In order to isolate neoplastic RS cells from primary cHLs, specimens were
sectioned and immunostained for the RS cell marker, CD30. Rapid
immunohistochemistry was performed using 5um thick frozen tissue sections.
Briefly, slides were fixed in -20^oC acetone and air dried for 10 minutes. All
further steps were performed at room temperature in a hydrated chamber.
Slides were pre-treated with Peroxidase Block (DAKO USA, Carpinteria, CA)
for 5 minutes to quench endogenous peroxidase activity. For CD30,
monoclonal mouse anti-human CD30 antibody (DAKO USA, Carpinteria, CA)
was applied ready to use for 10 minutes. Slides were washed in 50-mM Tris-
Cl, pH 7.4, and incubated with anti-mouse Envision+ kit (DAKO) for 5 minutes.
After further washing, immunoperoxidase staining was developed using a
DAB chromogen (DAKO). Slides were then re-dehydrated by passing through
graded alcohols and xylene and are dried prior to use in laser-capture
microdissection. Immediately following staining, between 250-1,000 CD30+
cells per section were laser-capture microdissected from 3 sections per tumor
using a PixCell II (Arcturus, San Diego, CA). Normal tissue, free from CD30+
cells, was also isolated from each section as a control. Caps were placed
immediately into lysis buffer and DNA was isolated using PicoPure DNA
Extraction kits (Arcturus, San Diego, California).

Quantitative PCR Analysis of DNA Copy Number and Transcript
Abundance

PD-L1 DNA copy number was assessed using TaqMan DNA Copy Number
Assay (Hs03704252_cn, Applied Biosystems, Foster City, CA) and TaqMan
Copy Number Reference Assay RNase P (Applied Biosystems). PCR
reactions were performed using TaqMan Universal Genotyping Master Mix
(Applied Biosystems, Foster City, CA) according to the manufacturer’s
protocol on a ABI 7300 real time PCR machine (Applied Biosystems, Foster
City, CA). Prior to interrogation of primary specimens, the assay was validated
using data obtained from HD SNP array analysis of HL cell lines. First, the
RNase P gene was determined not to be in a region of DNA copy number
alteration. Second, qPCR-based DNA copy number calls were found to tightly
correlate with DNA copy number inferences from the HD SNP array analysis
(Pearson correlation coefficient = 0.896; P=0.003). RS cell PD-L1 DNA copy
number was inferred from fold change in DNA with reference to tumor-matched
normal DNA as calculated by the 2^-DDCT method 29. Significant
differences between the DC_T values of RS cells and normal tissue from a
given tumor were determined using a one-tailed paired samples t-test. In
primary MLBCL samples, copy number was inferred by normalization to data
obtained from 5 normal samples.

In primary MLBCLs, complementary DNA was also synthesized by reverse
transcription of 500 ng of total-RNA using the Superscript III First Strand
Synthesis System for RT-PCR (Invitrogen, Carlsbad, CA). Gene transcript
abundance was assessed by quantitative real-time PCR (qRT-PCR) using
commercially available TaqMan Gene Expression Assays (Applied
Biosystems, Foster City, CA) for PD-L1 (Hs01125299_m1) and PD-L2
(Hs01057775_m1) relative to the internal reference gene HPRT1
(Hs99999909_m1). Reactions were prepared with TaqMan Gene Expression
Master Mix (Applied Biosystems, Foster City, CA) according to the
manufacturer’s protocol.

Quantitative Immuno-histo-chemistry

Immuno-histo-chemistry was performed using 4um thick formalin-fixed,
paraffin-embedded tissue sections. Briefly, slides were soaked in xylene,
passed through graded alcohols and put in distilled water. All further steps
were performed at room temperature in a hydrated chamber. Slides were pretreated
with Peroxidase Block (DAKO USA, Carpinteria, CA) for 5 minutes to
quench endogenous peroxidase activity. Slides were washed in 50-mM Tris-
Cl, pH 7.4 and then blocked using an Avidin/Biotin Blocking Kit(Vector,
Burlingame, CA) as per the manufacturer's instructions. For PD-L1,
monoclonal mouse anti-human PD-L1 antibody (BioLengend, San Diego, CA)
was applied 1:1000 in DAKO diluent for 1 hour. For PD-L2, monoclonal
mouse anti-human PD-L2 antibody (BioLegend, San Diego, CA) was applied
at 1:250 in DAKO diluent for 1 hour. Slides were washed and detected with
anti-mouse Envision+ kit (DAKO) as per manufacturer’s instructions. After
another wash, the slides were treated with a Tyramide kit (PerkinElmer,
Boston, MA) at 1:250 for 10 minutes. Slides were then thoroughly washed
and treated with LSAB2 Streptavidin-HRP (DAKO) as per the manufacturer's
instruction. After further washing, immunoperoxidase staining was developed
using a DAB chromogen (DAKO) and counterstained with hematoxylin. For
cHL tumors, PD-L1 protein expression was quantified in 150 individual RS
cells/slide using an Aperio Scan Scope XT workstation, ImageScope software
and the Aperio Color Deconvolution v9 immunohistochemical analysis
algorithm which provided the optical density of DAB staining per RS cell. For
MLBCL tumors, PD-L2 staining was quantified in 10 tumor-involved nonsclerotic
regions per specimen using the same Aperio Color Deconvolution
algorithm and the average optical density per analysed tumor region.

Chemical JAK2 Inhibition

In order to assess the effects of JAK2 inhibition on PD-1 ligand expression,
4x10⁶ cells from representative cHL lines were treated in triplicates with either
dimethylsulfoxide (DMSO, vehicle control) or 2.5-10.0mM of the specific JAK2
inhibitor SD-1029 (Calbiochem, San Diego, CA) 30 for 24h. Thereafter, cells
were harvested to isolate total RNA or to prepare whole-cell extracts for
western blot. Following purification of total-RNA using an RNeasy Mini Kit
(Qiagen, Valencia, CA), PD-L1 and PD-L2 transcript abundance were
assessed by qPCR as described above. Abundance of active phospho-JAK2
and total JAK2 protein were assessed by western blot using antipY1007/
1008-JAK2 (Cell Signaling Technology, Danvers, MA) and anti-JAK2
(Cell Signaling Technology, Danvers, MA) antibodies. Anti-GAPDH (Abcam,
Cambridge, MA) was used as a loading control.

Antiproliferative effects of JAK2 inhibitors were assessed by MTS assay.
Briefly, 5,000 cells per well were exposed to a 2-fold serial dilution series of
the specific JAK2 inhibitors, SD-1029 and Z3 (Calbiochem, San Diego, CA) 31
between the concentrations of 0.625-20.0mM. Following 48 h incubation,
cellular respiration was measured using the CellTiter 96 Aqueous One
Solution Cell Proliferation Assay (Promega, Madison, WI). EC50s were
calculated by fitting sigmoidal dose response to triplicate measurements of
each concentration using GraphPad Prism and averaged over 3 independent
experiments.

PD-L1 Promoter Region Analysis and Luciferase Assays

Computational analysis of PD-L1 genomic sequences was performed using
the USCS Genome Browser (http://www.genome.ucsc.edu), the publicly
available MatInspector module of Genomatix suite (http://www.genomatix.de)
and the open-source TOUCAN software 32. Briefly, putative promoter regions
were identified by high interspecies sequence conservation and high PolI I
binding peaks using the Yale TFBS tracks within the UCSC Genome Browser.
Sequences were then interrogated for transcription factor binding sites and
transcription factor modules using MatInspector and TOUCAN, respectively.

The candidate PD-L1 promoter sequence (-281 bp to +43 bp relative to the
transcription start site) was PCR-amplified from the L428 cHL line and cloned
into the promoterless pGL3 luciferase vector (Promega, Madison, WI). The
cHL cell lines L428 and SUPHD1 were grown to approximately 80%
confluency and 4x10⁶ cells each were co-transfected with 1.0mg/well of pGL3
luciferase construct (empty vector or pGL3-PD-L1p) and 0.5mg/well of pRL-TK
(Promega, Madison, WI). After 24 h of incubation, cells were treated with
10mM of SD-1029 or the equivalent volume of DMSO. Importantly, this
inhibitor maintains specificity for JAK2 at 10mM. After an additional 24 h
incubation, cells were lysed and luciferase activities were determined by
chemiluminescence assay using the Dual Luciferase Assay kit (Promega,
Madison, WI) and Luminoskan Ascent luminometer (Thermo Lab Systems,
Franklin, MA).

Results:

Chromosome 9p24.1 amplification and increased expression of the PD-1 ligands
in cHL and MLBCL cell lines

We first performed genome-wide DNA copy number analyses of a large panel
of cHL and DLBCL cell lines and an additional MLBCL cell line using a high
density SNP array with over 900,000 SNP probes and an additional ~950,000
probes for copy number variation 28. Copy number alterations were assessed
with the GISTIC method which computes separate scores for amplification
and deletion for each probe, taking into account both the frequency and
average amplitude of the observed alteration 28. This approach identified
highly significant amplification of chromosome 9p24.1 (Q-value 0.002) in the
lymphoma cell line panel. The amplified 9p24.1 segment includes 977 genes
within a 22Mbp region (chr9:1-21944952) and 7 genes within the 177Kbp
amplification peak (chr9:5404875-5581849) (Fig. 1A). The 9p24.1
amplification was present in 100% (6/6) of HL cell lines but only 22% (4/18) of
DLBCL lines (p = 0.001, FDR 0.024); notably, the single MLBCL cell line also
had amplification of this region.

Integrative analyses identified C9ORF46 (FDR=0.0062), PD-L1
(CD274/B7H1; FDR=0.0399) and PD-L2 (PDCD1LG2/CD273/B7-DC;
FDR=0.0870) 8 as the genes with the most significant association between
DNA copy number and transcript abundance in the amplification peak
(Supplementary Data). Consistent with these findings, PD-L1 and PD-L2
transcripts were significantly more abundant in HL cell lines than in DLBCL
lines and high in the single MLBCL cell line (Fig. 1B).

We next assessed the potential association between PD-1 ligand gene copy
number, transcript abundance and cell surface protein expression in the
lymphoma cell line panel. In flow cytometric analysis, the DLBCL cell lines
largely lacked cell surface expression of PD-1 ligands, PD-L1 and PD-L2 (Fig.
2). In marked contrast, the HL cell lines with increased copies of 9p24.1 had
significantly higher cell surface expression of the PD-L1 and PD-L2 proteins
(Fig. 2). The single MLBCL cell line also had high cell surface PD-1 ligand
expression (Fig. 2). Taken together, these data indicate that 9p24.1
amplification in HL and MLBCL cell lines targets the PD-1 ligand genes and
increases the cell surface expression of PD-L1 and PD-L2 (Figs. 1 and 2).

9p24.1 Amplification and Increased PD-L1 Expression in Primary HL RS cells

Given the identification of PD-1 ligands as key targets of the 9p24.1
amplification in HL cell lines, we next evaluated the frequency of PD-1 ligand
gene amplification and overexpression in primary cHL RS cells. For these
studies, primary Hodgkin RS cells were laser-capture microdissected (LCM)
from a series of primary nodular sclerosing HLs (NSHL; n=16) and mixed
cellularity HLs (MCHL; n=7) (Fig. 3A). Thereafter, PD-L1 gene copy number in
primary HL RS cells was assessed by qPCR relative to matched normal
tissue (Fig. 3B). Of note, LCM Hodgkin RS cell specimens included a small
amount of surrounding normal tissue (Fig. 3A), likely causing an
underestimation of PD-L1 copy number in samples with 9p24.1 amplification
(Fig. 3B). Using the statistically significant differences in DC_T values between
tumor and matched normal cells (corresponding to tumor DNA copy numbers
>2.2), 38% (6/16) of primary NSHLs had PD-L1/9p24.1 amplification. In
marked contrast, none of the primary MCHLs had PD-L1/9p24.1 amplification
(Fig. 3B, NSHL vs MCHL 9p24.1 amplification, p = 0.032). These data
indicate that 9p24.1 amplification is restricted to the cHL subtype, NSHL, most
closely related to MLBCL.

In representative primary NSHLs with known PD-L1 copy numbers, we also
performed quantitative IHC and determined PD-L1 protein expression in 150
RS cells/tumor (Fig. 3C and D). With this sensitive IHC method, PD-L1 copy
number and protein expression were tightly correlated in primary NSHLs (Fig.
3C and D, p <0.001).

PD-1 ligand amplification and overexpression in primary MLBCLs

The previously identified similarities between NSHL and primary MLBCL 2, the
selective amplification of PD-1 ligands in NSHL (Fig. 3) and the observed PD-
1 ligand gene amplification and cell surface expression in a MLBCL cell line
(Figs. 1 and 2) prompted us to assess PD-1 ligand copy numbers in a series
of 41 primary MLBCL by qPCR (Fig. 4). PD-L1 (9p24.1) amplification was
detected in 63% (26/41) of primary MLBCLs (Fig. 4A). Thereafter, PD-1 ligand
transcript abundance was evaluated by qRT-PCR and found to be
significantly higher in primary MLBCLs with the 9p24.1 amplification (Fig. 4B).

Because there were larger changes in PD-L2 than in PD-L1 transcript
abundance in primary MLBCLs with 9p24.1 amplification (Fig. 4B), we
analysed PD-L2 protein expression by quantitative IHC in representative
MLBCLs from this series. In these tumors, 9p24.1 amplification was
associated with increased PD-L2 protein expression (Supplementary Data).
Taken together, these data confirm an association between amplification of
9p24.1 and increased expression of PD-1 ligands, particularly PD-L2, in
primary MLBCLs.

9p24.1 amplification, Janus Kinase 2 (JAK2) overexpression and
increased activity in HL and MLBCL cell lines

In normal immune cells, PD-1 ligands are induced via cytokine-mediated
activation of JAK2/STAT1 signaling. These observations were of particular
interest because JAK2 is located on chromosome 9p24.1 (chr9:4985245-
5128183). In our pilot series of lymphoma cell lines, JAK2 was co-amplified
with the PD-L1 and PD-L2 loci (chr9:5450559-5468477 and chr9:5510545-
5571282, respectively) as part of the broader 9p24.1 amplification region in
HL and MLBCL cell lines (Fig. 5A). Consistent with these findings, HL and
MLBCL cell lines had significantly higher JAK2 transcript levels than DLBCL
cell lines (Fig. 5B). In addition, primary MLBCLs with 9p24.1 (PD-L1)
amplification had significantly higher JAK2 transcript levels than primary
MLBCLs with normal 9p24.1 copy numbers (Fig 4 and Fig. 5B). There was
also a close association between JAK2 copy numbers, transcript abundance
and total and active (phosphorylated) JAK2 in HL and MLBCL cell lines (Fig.
5C).

To evaluate the functional consequences of JAK2 amplification, we assessed
the abundance of phosphorylated STAT1 (pSTAT1) in the HL and MLBCL cell
lines with intracellular phospho-specific flow cytometry. HL and MLBCL cell
lines with increased copies of 9p24.1 and JAK2 had higher levels of
intracellular pSTAT1, directly associating JAK2 amplification with increased
JAK2 activity (Fig. 5D).

JAK2-associated induction of PD-L1 in HLs

Given the increased JAK2/STAT1 activity in HL and MLBCL cell lines with
9p24.1 amplification, we postulated that this genetic alteration would augment
JAK2/STAT1 induction of PD-1 ligands. For this reason, we treated HL cell
lines with low- or high-level 9p24.1 amplification (L428 and SUPHD1,
respectively) with a chemical inhibitor of JAK2, SD-1029, and assessed
associated changes in PD-L1 transcript abundance (Fig. 6 and
Supplementary Data). In both cell lines, SD-1029 treatment resulted in a
dose-dependent decrease in pJAK2 and PD-L1 transcript abundance (Figs.
6A and B). Of note, JAK2 inhibition decreased PD-L1 transcripts to a greater
extent in SUPHD1 which had higher JAK2 copy numbers and activity (Figs.
5C and D and Figs. 6A and B).

We further characterized the role of JAK2/STAT1 signaling in PD-1 ligand
induction by directly evaluating the PD-L1 upstream regulatory region. The 5’
PD-L1 sequence (-281 bp upstream to + 43 bp downstream of the
transcription start site) includes an ISRE/IRF1 module (-125bp to -188bp) and
several degenerate STAT binding sites (Fig. 6C). To assess the effect of
JAK2 on transcription mediated by this regulatory element, the 5’ PD-L1
sequence was cloned into the pGL3 luciferase vector and transfected into HL
cell lines with low (L428) or high (SUPHD1) 9p24.1 copy numbers. PD-L1
promoter-driven luciferase activity was increased in both L428 and SUPHD1
(Fig. 6D, empty vector [control] vs pGL3-PD-L1 [control]). Of note, SUPHD1
exhibited significantly higher PD-L1 promoter-driven luciferase expression
than L428 (Fig. 6D, SUPHD1 pGL-3PD-L1p [control], compare y-axes). In
addition, treatment with the specific chemical JAK2 inhibitor, SD-1029,
resulted in a highly significant decrease in PD-L1 driven luciferase expression
in SUPHD1 and a more modest decrease in L428 (Fig. 6D, compare pGL3-
PD-L1p [control] vs pg3-PD-L1;[SD-1029]). Similar, more modest, results
were observed following siRNA-mediated knock-down of JAK2
(Supplementary Data). Taken together, these studies confirm a direct
association between 9p24.1 amplification, JAK2 abundance and activity and
PD-L1 upregulation in HL (Figs. 5 and 6).

We also investigated the role of JAK2 in PD-L2 induction. Like PD-L1, the PDL2
5’ regulatory region includes an ISRE/IRF1 module and degenerate STAT
binding sites (Supplementary Data). However, the spacing of ISRE and IRF1
elements in the predicted module was larger than that seen in other
transcription regulatory elements 33, including the 5’ PD-L1 sequence, and
there were fewer degenerate STAT binding sites (Supplementary Data).
Consistent with these findings, JAK2 inhibition decreased PD-L2 transcript
abundance and PD-L2 promoter-driven luciferase expression less than PD-L1
(Supplementary Data).

Together, these results implicate JAK2 in the induction of PD-L1 and, to a
lesser extent, PD-L2 gene expression. Therefore, co-amplification of JAK2
and PD-1 ligand genes increases both PD-1 ligand gene-dosage and the
abundance and activity of the PD-1 ligand inducer, JAK2.

JAK2 inhibition and HL cellular proliferation

Given the pleiotropic effects of JAK2/STAT1 signaling and the additional
known STAT1 targets, we also assessed the effects of 2 different chemical
inhibitors of JAK2 (SD1029 and Z3) on HL and MLBCL cell lines proliferation
at 48 hours. Both of the JAK2 chemical inhibitors decreased the proliferation
of HL and MLBCL lines with similar EC50s. In addition, there was an inverse
correlation between JAK2 (9p24.1) copy number and the EC50 of both JAK2
inhibitors in HL cells (Table 1).

Discussion:

By integrating high-resolution copy number data with transcriptional profiles,
we identified the immunoregulatory genes, PD-L1 and PD-L2, as key targets
of the 9p24.1 amplification in HL and MLBCL cell lines. We also extended
these findings to primary tumors and found that PD-1 ligand/9p24.1
amplification was restricted to the HL subtype most closely related to primary
MLBCL, NSHL. Using quantitative immuno-histo-chemical methods, we
demonstrated that PD-1 ligand gene amplification was associated with
increased protein expression in primary tumors. In HLs and MLBCLs, the
extended 9p24.1 amplification region included the JAK2 locus. JAK2
amplification increased JAK2 protein expression and activity, specifically
induced PD-1 ligand transcription and enhanced sensitivity to JAK2 inhibition.
These findings define 9p24.1 amplification as a disease-specific structural
alteration that increases both the gene dosage of PD-1 ligands and their
induction via JAK2 (Fig. 7).

With high resolution HD SNP array data and GISTIC analysis, it was possible
to define the boundaries of the 9p24.1 amplification (13Mbp, 799 genes) and
further delineate the amplification peak (177 Kbp, 7 genes). By integrating
these data with concurrent transcriptional profiles, we identified the genes with
the closest association between transcript abundance and copy number. With
this approach, we built upon the prior observations of 9p gain in HL and
MLBCL, localized the PD-1 ligand genes to the 9p24.1 amplification peak and
confirmed the highly significant association between PD-L1 and PD-L2 copy
number and transcript abundance.

Recent studies highlight the emerging role of PD-1 ligand/receptor-mediated
immune escape in cancer 8. Although PD-1 ligand expression is associated
with adverse outcomes in multiple solid tumors, the genetic mechanisms for
PD-1 ligand overexpression and/or induction are largely undefined. In
previous in vitro analyses of multiple myeloma or lung cancer cell lines, IFNg
treatment induced PD-1 ligand expression 34,35. More recently, loss of the
PTEN tumor suppressor was associated with increased PD-L1 expression in
malignant gliomas 36 but not in other solid tumors 35, 37. In additional studies of
anaplastic large cell lymphomas, the chimeric fusion protein, nucleophosmin
(NPM)/anaplastic lymphoma kinase (ALK), was reported to induce PD-L1
expression via a STAT3-dependent mechanism 37.

Herein, we demonstrate that structural amplification of chromosome 9p24.1
increases the abundance of both PD-1 ligands and their inducer, JAK2, in the
related diseases of NSHL and MLBCL. In HL cell lines with 9p24.1
amplification, cell surface PD-1 ligand expression was greater than would be
predicted by a simple gene-dosage effect. Furthermore, PD-L1 promoter-driven
luciferase activity was significantly higher than predicted by gene copy
number alone in HL cell lines. Consistent with these findings, JAK2 signaling
further augmented PD-1 ligand expression in cell lines with 9p24.1
amplification. In addition, JAK2 inhibition had a greater effect on PD-L1-driven
luciferase activity in the HLs with high-level 9p24.1 amplification. There was a
similar, although less striking association between 9p24.1 copy number and
PD-L2 transcript abundance in HL.

The relative differences in JAK2/STAT induction of PD-L1 and PD-L2 may be
due, in part, to features of the genes’ 5’ regulatory regions, including spacing
of the ISRE/IRF1 module and numbers of candidate STAT binding sites. Of
note, PD-L1 was more abundant than PD-L2 in HL cell lines with 9p24.1
amplification; in contrast, MLBCLs with 9p24.1 had greater induction of PD-L2
than PD-L1. Previous studies highlight subtle differences in the expression,
regulation and potential function of the two PD-1 ligands 10, 38,39.

Given the association between PD-1 ligand expression and outcome in other
cancers, we speculate that 9p24.1 amplification may be an important genetic
prognostic factor in HL and MLBCL. Furthermore, the basal and
amplification-associated PD-1 ligand expression in NSHL and MLBCLs
suggests that these tumors may be particularly responsive to PD-1 ligand/PD-
1 receptor blockade (Fig. 7). In recent studies, tumor-infiltrating T cells from
primary HLs expressed PD-1 and responded to PD-1 blockade in vitro 7, 40,41.
Because both PD-L1 and PD-L2 engage the PD-1 receptor, PD-1 receptor
blockade may represent a promising therapeutic strategy in HL and, possibly,
MLBCL. Of note, humanized PD-1 receptor-blocking monoclonal antibodies
augment anti-tumor activities of effector T cells and NK cells and increase
anti-cancer immune responses in murine tumor models 42. In addition, PD-1
neutralizing antibodies appear to be well tolerated in initial phase I clinical
trials 42.

Given the copy-number dependent JAK2 activity in HLs, JAK2 may be
another rational therapeutic target alone or in combination with PD-1 blockade
(Fig. 7). In our in vitro assays using the commercially available JAK2
inhibitors, SD1029 and Z3 30,31, there was an excellent correlation between
the doses required to inhibit phosphoJAK2, decrease PD-L1 transcription and
reduce the proliferation of HL cell lines. Of note, these SD1029 and Z3 doses
were comparable to those required to inhibit phosphoJAK2 and cellular
proliferation in hematologic malignancies with activating JAK2 mutations
(JAK2-V617F or TEL-JAK2) 30,31. These observations suggest that additional
clinical evaluation of more potent clinical-grade JAK2 inhibitors 43 is
warranted in HL and MLBCL. Consistent with the likely importance of JAK2
amplification in HL and MLBCL, additional genetic mechanisms including
SOCS-1 mutation and miR135a loss also increase JAK2 activity 44-47.

The current studies, which highlight the role of 9p24.1-driven PD-1 ligand
expression in HL and MLBCL, add to emerging data regarding
complementary mechanisms of tumor immune privilege in these diseases 6. In
addition to the PD-1 ligand, cHL RS cells also produce the immunoregulatory
protein, galectin-1, and the immuno-suppressive cytokine, IL-10  6, 48. IL-10
suppresses the activation of naive T-cells and PD-L1 inhibits the TCR
signalling of activated T-cells 48. Furthermore, IL-10 and PD-L1 promote the
differentiation of immuno-suppressive T-regulatory cells via different
mechanisms 49, and galectin-1 supports the expansion of T-regulatory cells
and the selective deletion of Th1 and Th17 cells 50. These mechanisms of
immune escape likely act in concert within the tumor microenvironment in
order to foster immune privilege.

In summary, our current studies define a disease-specific genetic abnormality,
9p24.1 amplification, with likely prognostic significance and associated
complementary rational therapeutic targets, PD-1 ligand and JAK2 (Fig. 7).
Furthermore, we describe a quantitative method for determining PD-1 ligand
expression in primary tumors, an important adjunct to personalized
approaches to therapy. These data support further evaluation of PD-1
blockade and JAK2 inhibition, alone and in combination, in HL and MLBCL
patients characterized for 9p24.1 and the associated targets.

Authorship Contributions:
MRG: designed research, performed research, analyzed data, and wrote the
paper
SM: performed research, analysed data.
SJR: performed research, analysed data.
PJ: performed research, analysed data.
TC: performed research.
EO: performed research.
BC: analysed data.
KT: performed research.
DN: analysed data.
TG: analysed data.
JLK: designed research, analysed data.
MAS: designed research, analysed data and wrote the paper.

Disclosure of Conflicts of Interest:

We declare that no author has any financial conflict of interest.

1. Frenster JH, Papalian MM, Masek MA and Frenster JA,
"Electron Microscopic Analysis of Lymph Node Cellular Activity in Hodgkin's Disease",
Journal of the National Cancer Institute, Vol. 63, pp. 331-335, Aug. 1979.

2. Frenster JH,.
"Hodgkin Lymphoma Immuno-Pathology".
A brief history of the biology.

Fig. 1 Chromosome 9p24.1 amplification and increased expression of PD-1 ligands in HL and MLBCL cell lines.

Fig. 1 Chromosome 9p24.1 amplification and increased expression of PD-1 ligands in HL and MLBCL cell lines.

A) Left panel) Smoothed chromosome 9p gene copy number estimates for each DLBCL, MLBCL and HL cell line. The color scale ranges from blue (deletion) to red (amplification). Right panel) GISTIC q values (for all cell lines) for the 9p24.1 amplification which includes the PD-L1/PD-L2 loci.

B) PD-L1 and PD-L2 transcript abundance in the DLBCL, MLBCL and HL cell lines was assessed by transcriptional profiling and represented in box plots.

Fig. 2: 9p24.1 amplification and PD-1 ligand cell surface expression in HL and MLBCL cell lines.

Flow cytometric analysis of cell surface PD-1 ligand (PD-L1 and PD-L2) expression in DLBCL, MLBCL and HL cell lines (PD-L1 or PD-L2, open black lines; isotype controls, solid grey histograms). DLBCL and HL cell lines are arranged according to PD-1 ligand copy number (normal to high, left to right).

Fig. 3 PD-1 ligand amplification and over-expression in primary HL.

A) Laser-capture microdissection (LCM) of primary HL Reed-Sternberg RS cells. (i) RS cells were identified by CD30 staining, (ii) selected by laser (Arcturus PixCell II) (iii) removed from surrounding nonneoplastic tissue, resulting in (iv) highly enriched RS cell specimens.

B) qPCR-based DNA copy number analysis of PD-L1 in LCM primary RS cells isolated from 7 MCHLs and 16 NSHLs. Data are means (+/- SD) of triplicate qPCR reactions performed on pooled DNA samples from RS cells or normal tissue from each slide, repeated for 3 slides per sample.

C) Left panel) Quantitative IHC of PD-L1 in 3 representative cases (#8, 15 and 22) from B. Right panel)
Quantitative analysis of PD-L immunostaining in 150 individual RS cells from each of these cases (#8, 15 and 22) (see Methods).

Fig. 4 PD-1 ligand amplification and overexpression in primary MLBCL.

A) qPCR-based DNA copy number analysis of PD-L1 in 41 primary MLBCLs. B) RT-qPCR analysis of PD-L1 and PD-L2 transcript abundance in the same series of primary MLBCLs. Transcript abundance in tumors with normal or increased 9p24.1 is represented in box blots.

Fig. 5: JAK2 amplification, expression and activity.

A) GISTIC analysis (for all cell lines) of 9p24.1 – PD-L1 and PD-L2 in the amplification
peak and JAK2 in the broader amplification region.

B) JAK2 transcript abundance in HL and DLBCL cell lines and the single MLBCL cell line
(left panel) and primary MLBCLs with 9p24.1 (PD-L1) amplification or normal copy number (right panel).

C) Western blot analysis of phospho- and total JAK2 in HL cell lines arranged according to 9p24.1 copy number (normal to high, left to right, as in Fig. 2) and the single MLBCL cell line.

D) Intracellular phosphoflow cytometric analysis of pSTAT1 in HL and MLBCL cell lines in C.

Fig. 6: Chemical inhibition of JAK2 decreases PD-1 ligand transcription.

A) Western analysis of phosphoJAK2 in HL cell lines (L428 and SUPHD1) treated with the increasing doses (2.5-10?m) of the specific JAK2 inhibitor, SD-1029.

B) RT-qPCR analysis of PD-L1 transcript abundance in the cell lines treated with SD-1029. Data are
means (+/-SD) of triplicate measurements from the representative experiment shown in A.

C) The PD-L1 promoter regulatory module. STAT-responsive (ISRE) element and additional degenerate STAT
binding sites are indicated. This region was cloned into a pGLluciferase vector (pGL3-PD-L1p).

D) Analysis of pGL3-PD-L1p luciferase activity in L428 and SUPHD1 HL cells treated with SD-1029 or vehicle. Data are means (+/-SD) of triplicate measurements from a representative experiment. Experiments in B and D were performed 3 times.

Fig. 7: 9p24.1 amplification targets, consequences and associated treatment options.

9p24.1 amplification increases PD-1 ligand (PDL1 and PD-L2) and JAK2 copy numbers, augments JAK2/STAT1
activity, induces PD-1 ligand expression and stimulates HL proliferation.

Integrative analysis of copy-number and expression data

Genomic DNAs from 18 DLBCL (SUDHL4, SUDHL6, SUDHL7, SUDHL8, SUDHL10,
OCILy1, OCILy3, OCILy8, OCILy10, OCILy18, OCILy19, DB, FARAGE, Pfeiffer, Toledo,
HT, KARPAS-422, WSUNHL), 1 MLBCL (KARPAS11106P) and 6 HL (L428, KMH2, L540,
L1236, SUPHD1, HDLM2) cell lines and 21 peripheral blood lymphocyte samples from normal
donors were extracted as previously described and profiled using Affymetrix SNP6.0
microarrays.1 The above-mentioned high density (HD) SNP array includes over 900,000 SNP
probes and ~950,000 additional probes for copy number variation resulting in substantially
improved whole genome coverage.

The inference of DNA copy number from ‘.cel’ files was performed using a GenePattern
pipeline that runs the following modules: SNPFileCreator, CopyNumberInference,
RemoveCopyNumberOutliers, DivideByNormals, and Quality Control. 2 Normalized log2-ratios
were segmented using the Circular Binary Segmentation (CBS) algorithm (v1.12.0) using 10,000
permutations, a=0.01, and undo splits (undo.sd=1).3,4 Significance of copy number alterations
across samples was assessed by the GISTIC algorithm 5, applied using the GenePattern platform
and thresholds corresponding to t_amp=2.178 for amplifications and t_del=1.820 for deletions. These
thresholds were determined based on an empirical analysis of the distribution of copy numbers
(CNs) in known regions of amplification (and deletion), and by selecting the mid-point between
the modes corresponding to two and three CNs (and two and one CNs). The chromosome-wide
amplification in chromosome 7 and the chromosome arm-wide deletion in chromosome 6 were
used for this purpose.

GISTIC defines peaks of interest with associated FDR q-values determined by multiple
hypothesis testing (MHT) correction, with regions obtaining q-values below 0.25 being
considered significant. Within each region a smaller peak (or peaks) is identified as the set of
contiguous markers with the highest q-values. Naturally occurring copy number variants (CNVs)
were removed before running GISTIC. These CNVs were compiled from SNP6.0 analysis of
HapMap normals 6 the Database of Genomic Variants (DGV, http://projects.tcag.ca/variation) 7
and an automated search of profiled normals.

Transcriptional profiling was performed for all cell lines using Affymetrix U133 A&B
microarrays as previously described. 8 Integrative analysis, combining DNA copy number and
gene transcript data, was performed in order to assess relationships between DNA copy number
change and alteration in gene transcript abundance so as to refine the list of candidate genes
within alteration regions. Genes within the peak (region) of GISTIC-identified alterations were
tested for difference in expression between samples with or without each lesion by a two-group
t-statistic, and significance was assessed both by a permutation test procedure and by
asymptotically derived p-values (using a Student’s t distribution). The permutation-based pvalues
were “smoothed” by the Laplace rule of succession, i.e., by adding 1 to the numerator and
2 to the denominator of the ratio used to compute the empirical p-value. 9 Q-values were derived
by MHT correction of nominal p-values using the FDR method applied to the union of all genes
within all the peaks (regions). Genes were considered positive by integrative analysis if
differences in transcript abundance attained an FDR<0.25 by at least one of the two procedures
(permutation-based or asymptotic).

Supplementary REFERENCES:

1 Takeyama, K. et al. Integrative analysis reveals 53BP1 copy loss and decreased expression in a
subset of human diffuse large B-cell lymphomas. Oncogene 27, 318–322 (2007).

2 Network, C. G. A. R. Comprehensive genomic characterization defines human glioblastoma
genes and core pathways. Nature 455, 1061–1068 (2008).

3 Olshen, A., Venkatraman, E., Lucito, R. & Wigler, M. Circular binary segmentation for the
analysis of array based DNA copy number data. Biostat 5, 557–572 (2004).

4 Venkatraman, E. & Olshen, A. A faster circular binary segmentation algorithm for the analysis
of array CGH data. Bioinformatics 23, 657–663 (2007).

5 Beroukhim, R. et al. Assessing the significance of chromosomal aberrations in cancer:
methodology and application in glioma. . Proc Natl Acad Sci U S A 104, 20007–20012 (2007).

6 McCarroll, S. et al. Integrated detection and population-genetic analysis of SNPs and copy
number variation. Nat Genet 40, 1166–1174 (2008).

7 Iafrate, A. et al. Detection of large-scale variation in the human genome. Nat Genet 36, 949–
951 (2004).

8 Juszczynski, P. et al. The AP1-dependent secretion of galectin-1 by Reed Sternberg cells
fosters immune privilege in classical Hodgkin lymphoma. Proc Natl Acad Sci U S A 104, 13134–
13139 (2007).

9 Gould, J., Getz, G., Monti, S., Reich, M. & Mesirov, J. P. Comparative gene marker selection
suite. Bioinformatics 22, 1924–1925, doi:10.1093/bioinformatics/btl196 (2006).

Table S1. Integrative analysis of DNA copy number and transcript abundance of genes
within the 9p24 amplification peak:

C90RF46, CD274 (PD-L1) and PDCD1LG2 (PD-L2) have most significant association between
DNA copy number and transcript abundance.

Figure S1. PD-L2 expression in HL and MLBCL cell lines

– comparison of cell surface immunostaining by flow cytometry (as in Fig. 2, main manuscript) (top panel) and
quantitative immunohistochemistry (bottom panel)

PD-L2 levels measured by quantitative immunohistochemistry are in line with those determined
by flow cytometry. After confirming that PD-L2 quantitative IHC and flow cytometry gave
comparable results in the above-mentioned cell lines, we evaluated PD-L2 expression in primary
MLBCLs by quantitative IHC (Fig. S2).

Figure S2. Quantitative immunohistochemistry of PD-L2 in representative primary MLBCLs with known 9p24.1 copy numbers

(Top panel) qPCR analysis of PD-1 ligand (PD-L1)/9p24.1 copy numbers in a series of 41 primary MLBCLs (as in Fig. 4A, main manuscript).

(Bottom panel) PD-L2 quantitative immuno-histo-chemistry in representative primary MLBCLs from this series.

(Left) PD-L2 quantitative immuno-histo-chemistry.

(Right) Quantitative analysis of PD-L2 immuno-staining in 10 tumor-involved non-sclerotic regions of each tumor.

Figure S3. Chemical inhibition and siRNA-mediated knockdown of JAK2 decrease PD-1
ligand transcription

(A) Western analysis of phosphoJAK2 in HL cell lines (L428 and SUPHD1) treated with the
increasing doses (2.5–10 µm) of the specific JAK2 inhibitor, SD-1029, or control or siRNA
JAK2. siRNA-mediated knockdown of JAK2 was obtained by transfecting cells with 75 mol of
JAK2 ON-TARGETplus SMARTpool siRNA (Dharmacon) or corresponding scrambled
oligonucleotides. Transfections were performed as described for luciferase constructs (main
manuscript).

(B) RT-qPCR analysis of PD-L1 transcript abundance in the cell lines treated with
SD-1029, or control or siRNA JAK2 in A. Data are means (+/- SD) of triplicate RT-qPCR
reactions from a representative experiment (experiment performed 3 times). Although siRNAmediated
JAK2 knockdown was less effective at decreasing JAK2 activity (phosphoJAK2) than
chemical inhibition, JAK2 depletion also decreased PD-L1 expression in the HL cell lines.
Similar to JAK2 chemical inhibition, JAK2 knockdown was more effective at inhibiting PD-L1
expression in SUPHD1 (which has high-level 9p24.1 amplification).

Figure S4. Chemical inhibition of JAK2 decreases PD-L2 ligand transcription

(A) RT-qPCR analysis of PD-L2 transcript abundance in HL cell lines treated with increasing
doses (2.5–10 µM) of the JAK2 inhibitor, SD-1029 (as in Fig. 6A, main manuscript or Fig. S3).
Data are means (+/- SD) of triplicate RT-qPCR reactions from a representative experiment.

(B) The PD-L2 promoter regulatory module including a predicted ISRE/IRF module and other
degenerate STAT-binding sites. The spacing of the ISRE and IRF1 elements in the predicted PDL2
module was larger than that in other known ISRE/IRF1 modules (<100bp) and the PD-L1
module (63bp, Fig. 6C, main manuscript). The ISRE/IRF1 spacing and lower numbers of
degenerate STAT-binding sites in the PD-L2 5? regulatory region likely explain the more
moderate effect of chemical JAK2 inhibition on PD-L2 transcript abundance (compared with
PD-L1).

(C) Analysis of pGL3-PD-L2p luciferase activity in L428 and SUHD1 HL cells treated
with SD-1029 or vehicle. To assess the effect of JAK2 on transcription mediated by the 5' PD-L2
regulatory element, this sequence was cloned into the pGL3 luciferase vector and transfected into
HL cell lines with low (L428) or high (SUPHD1) 9p24.1 copy numbers. PD-L2 promoter-driven
luciferase activity was increased in both L428 and SUPHD1 (empty vector [control] vs pGL3-
PD-L2 [control]). Of note, SUPHD1 exhibited much higher PD-L2 promoter-driven luciferase
expression than L428 (SUPHD1 vs. L428 pGL-3PD-L1p [control], compare y-axes). In addition,
treatment with the specific chemical JAK2 inhibitor, SD-1029, resulted in a marked decrease in
PD-L2 driven luciferase expression in SUPHD1 and a more modest decrease in L428 (compare
pGL3-PD-L2p [control] vs pGL3-PD-L2 [SD-1029]). Data are means (+/- SD) of triplicate
measurements from a representative experiment. The experiments in A and B were performed 3
times.

In this detailed integrative study of  Hodgkin lymphoma and Large B-cell lymphoma by Michael Green, Stefano Monti, Scott Rodig, Przemyslaw Juszczynski, Treeve Currie, Evan O'Donnell, Bjoern Chapuy, Kunihiko Takeyama, Donna Neuberg, Todd Golub, Jeffery Kutok, and Margaret Shipp, we find successful attempts to compare two types of Hodgkin lymphoma, two types of large B-cell lymphoma, several chromosomal gene sites, several gene products, and several gene therapeutic agents, in 64 patients, during, and after their disease. This is truly ambitious, desirable, and perhaps conclusive. Caveats arise, of course, as they must in so large an enterprise. None are fatal, but some are persistant, and perhaps useful.

Neoplastic cells within patients are the reality, and when freshly biopsied as the primary neoplasm, perhaps reflect the in vivo state. When placed in vitro in cultured cell lines over some or many generations, changes occur, in chromosomes, genes, DNA, proteins, even RNAs. These reflect the adaptation of human cells to laboratory life. When fully analyzed, these biological structures enter the abstract world of silicon models, predictive mathematics, and geometric drug design. And, in the happiest of all conclusions, this journey aids the patient, the physician, and, really, all of us.

That said, this study often succeeds, and perhaps even more than its authors realize, because we are now getting closer to reality, within lymphoma patients, present, future, and even past. But we need to keep our fields of inquiry active, and work to keep the resulting integrations real, successful, and available.

So far, so good.

1. Frenster JH, Papalian MM, Masek MA and Frenster JA,
"Electron Microscopic Analysis of Lymph Node Cellular Activity in Hodgkin's Disease",
Journal of the National Cancer Institute, Vol. 63, pp. 331-335, Aug. 1979.

2. Frenster JH,.
"Hodgkin Lymphoma Immuno-Pathology".
A brief history of the biology.

1. Each cell retains all of its embryonic genes for a lifetime.

2. Controls for embryonic genes are often absent in adults.

3. Uncontrolled embryonic genes can replicate wildly.

4.  Replicating genes participate in  intra-cellular competition.

5.  The basis for gene competition is selective transcription.

6.  MicroRNAs can reprogram embryomic transcription.

7.  Gene reprogramming can produce normal phenotypes.

8.  Normal phenotypes can by-pass chromosomal lesions.

9.  MicroRNA therapy may need to be permanent.

10. Transplantation of microRNAs could be preferred.

http://www.embryomas.net/

1. Pathways within cell genomes involve a flow of information.

2. Information can flow by direct contact or by third parties.

3. Direct contact within whole genomes is difficult to regulate.

4. DNA-DNA direct contects are influenced by agents.

5. Nuclear agents include hydrophilic ionic and hydrophobic conforming ligands.

6. Third parties within genomes involve RNAs and proteins.

7.  RNAs and proteins are easy to regulate or reverse.

8.  Information can be shared, lost, or transformed.

9. System information can be hidden during system isolation.

10.  Local information can be permanently lost during system entropy.

http://www.embryomas.net/

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