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Aberrant RB-E2F defines molecular phenotypes

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Aberrant RB-E2F Transcriptional Regulation Defines Molecular Phenotypes of Osteosarcoma

Milcah C. Scott1,2,3

, Aaron L. Sarver1,2

, Hirotaka Tomiyasu1,2,3

, Ingrid Cornax1,3,4

, Jamie Van Etten3,5

,

Jyotika Varshney1,5,6

, M. Gerard O'Sullivan1,3,4

, Subbaya Subramanian1,3,5,

Jaime F. Modiano1,2,3,7,8 *

1Animal Cancer Care and Research Program, University of Minnesota, St Paul, MN;

2Department of

Veterinary Clinical Sciences, College of Veterinary Medicine, University of Minnesota, St Paul, MN; 3Masonic Cancer Center, University of Minnesota, Minneapolis, MN;

4Department of Veterinary

Population Medicine, College of Veterinary Medicine, University of Minnesota, St Paul, MN; 5Department of Surgery, School of Medicine, University of Minnesota, Minneapolis, MN;

6Veterinary

Medicine Graduate Program; College of Veterinary Medicine, University of Minnesota, St Paul, MN; 7Stem Cell Institute, University of Minnesota, Minneapolis, MN;

8Center for Immunology, University of

Minnesota, Minneapolis, MN

Running Title: Aberrant RB-E2F defines molecular phenotypes

*Correspondence should be addressed to: Jaime F. Modiano, VMD, PhD. Masonic Cancer Center,

University of Minnesota, 420 Delaware St., SE, MMC 806, Minneapolis, MN 55455. Ph: 612-625-7436.

Fax: 612-626-4915. Email: [email protected]

Keywords: osteosarcoma, retinoblastoma protein (pRb, RB), E2F transcription factor, gene expression,

chromatin remodeling

Background: Gene expression signatures define

prognostically significant osteosarcoma

phenotypes.

Results: Deregulation of the RB-E2F pathway

establishes more aggressive phenotype. Inhibitors

of DNA and chromatin remodeling promote

comparable transcriptional changes as genetic

restoration of RB.

Conclusion: Aberrant RB-E2F pathway alters

epigenetic landscape and biological behavior of

osteosarcoma.

Significance: Epigenetic remodeling regulated by

RB-E2F gives rise to patterns of gene expression

that are associated with different biological

behavior and progression of osteosarcoma.

ABSTRACT

We previously identified two distinct molecular

subtypes of osteosarcoma through gene

expression profiling. These subtypes are

associated with distinct tumor behavior and

clinical outcomes. Here, we describe

mechanisms that give rise to these molecular

subtypes. Using bioinformatic analyses, we

identified a significant association between

deregulation of the RB-E2F pathway and the

molecular subtype with worse clinical

outcomes. Xenotransplantation models

recapitulated the corresponding behavior for

each osteosarcoma subtype; thus, we used cell

lines to validate the role of the RB-E2F

pathway in regulating the prognostic gene

signature. Ectopic RB resets the patterns of

E2F regulated gene expression in cells derived

from tumors with worse clinical outcomes

(Molecular Phenotype-2) to those comparable

to those observed in cells derived from tumors

with less aggressive outcomes (Molecular

Phenotype-1), providing a functional

association between RB-E2F dysfunction and

altered gene expression in osteosarcoma. DNA

methyltransferase and histone deacetylase

inhibitors similarly reset the transcriptional

state of the Molecular Phenotype-2 cells from a

state associated with RB-deficiency to one seen

with RB-sufficiency. Our data indicate that

deregulation of RB-E2F pathway alters the

epigenetic landscape and biological behavior of

osteosarcoma.

Osteosarcoma is a genetically complex,

heterogeneous disease that occurs naturally in

humans and dogs (1-3). In the past decade, the

molecular basis of osteosarcoma has received

significant attention and a number of recurring

chromosomal aberrations and changes in gene

http://www.jbc.org/cgi/doi/10.1074/jbc.M115.679696The latest version is at JBC Papers in Press. Published on September 16, 2015 as Manuscript M115.679696

Copyright 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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expression have been identified (1-5). However,

these findings have not yet translated into

significant improvements in disease prognosis or

outcome (2,6-8), placing osteosarcoma among the

“most wanted” for new and effective therapies (9).

The ability to prospectively identify patients

whose tumors have distinct gene expression

profiles (molecular phenotypes) associated with

clinical outcomes may offer insights to develop

new therapeutic strategies adapted to tumor

behavior. The conservation of disease mechanisms

between canine and human osteosarcoma supports

using the former as a comparative model to

achieve this goal (2,5,10-12). Previously, we

identified a gene signature consisting of

approximately 250 genes that stratified canine

osteosarcoma into sub-groups predictive of patient

outcome (5,13). The gene signature and its

prognostic value were conserved in tumors from

human osteosarcoma patients (5). Tumors from

patients with longer survival (henceforth called

“Molecular Phenotype-1”) were characterized by

decreased expression of genes associated with

G2/M transition and DNA damage-induced cell

cycle checkpoints. Conversely, decreased

expression of genes associated with

microenvironment interactions was observed in

tumors from patients with shorter survival

(henceforth called “Molecular Phenotype-2”). In

the present study, we characterized mechanisms

that are causally related to these distinct molecular

phenotypes. Specifically, we show that

deregulation of the RB-E2F pathway is a major

feature of Molecular Phenotype-2 tumors, and that

restoration of RB in cells from these tumors resets

gene expression to a state comparable to that seen

in tumors from patients with longer survival.

One mechanism of RB-dependent gene regulation

is through changing chromatin structure (14,15).

Thus, we hypothesized that the RB-E2F pathway

might be functionally restored by pharmacologic

alteration of DNA and chromatin structure. We

recently reported that DNA methyltransferase

(DNMT) and histone deacetylase (HDAC)

inhibitors had synergistic and selective

cytotoxicity effects against human and canine

osteosarcoma cells (16). Here, we show that

treatment using DNMT inhibitor (zebularine) with

the HDAC inhibitor (vorinostat) was sufficient to

alter the transcriptional state of Molecular

Phenotype-2 cells to one resembling that seen with

active RB.

EXPERIMENTAL PROCEDURES

Cell Lines and Cell Culture- Canine and human

osteosarcoma cell lines and the Jurkat T-cell

leukemia line were established and maintained as

previously described (5,16,17). OSCA-8, OSCA-

32, and OSCA-40 cells were modified to stably

express green fluorescent protein (GFP) and firefly

luciferase (Luc) for in vivo experiments (18).

Fluorescence in situ hybridization was used to

determine the number of GFP/Luc copies in the

cell lines. Morphologic appearance, doubling time,

and routine viability assays were used to confirm

that growth properties of the derivative cell lines

were comparable to those of the parental cell lines.

Luciferase activity in the parental cell lines and the

GFP/Luc modified cells was measured in vitro

with the dual-luciferase reporter (DLR) Assay

System (Promega, Madison, WI) (19) using a

Wallac 1420 microplate reader (Perkin Elmer;

Turku, Finland). Firefly luciferase was normalized

to Renilla luciferase.

Expression Vectors and Transfections- A pGL3

luciferase reporter encoding Luc downstream from

a 515 bp AURKB promoter was a kind gift of Dr.

Masashi Kimura (Gifu, Japan) (20). The 515 bp

sequence contains full AURKB promoter activity.

Constructs encoding wild type, N-terminal

truncated RB (Wt RB) or a cyclin-dependent

kinase (CDK)-insensitive, N-terminal truncated

mutant (PSM 7-LP) RB were provided by Dr. Erik

S. Knudsen (Dallas, TX and San Diego, CA) (21).

Expression vectors encoding wild type p16 or p21

have been described (19,22). pGL4.73

hRenillaLuc/SV40 vector was purchased from

Promega and Empty CMV-Neo-Bam vector was

purchased from Addgene(Cambridge, MA).

Expression vectors were mixed with a 1/100 molar

equivalent of hRenillaLuc/SV40 vector in 20µl of

supplemented SE solution (Lonza, Basel,

Switzerland). These mixtures were added to

200,000 cells, which were then transfected using

the Lonza 4D Nucleofector. Reactions were

optimized to achieve >80% viability and

transfection in all cell lines monitored by GFP

expression. Luciferase activity was measured

using the DLR Assay System.


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Site-directed mutagenesis- PCR site-directed

mutagenesis of the [GGCGGG] E2F binding site

in the AURKB promoter was done using

mutagenic primers reported (20), and the

GENEART site-Directed Mutagenesis System

(Life Technologies, Grand Island, NY).

Western Blotting- Immunoblotting was done as

described (22), with detection and quantification

using the Li-Cor Biosciences (Lincoln, NE)

Odyssey system (Masonic Cancer Center Flow

Cytometry Shared Resources). Anti-RB

monoclonal antibodies (clone G3-245 (catalog no.

554136); BD Sciences, San Jose, CA, and clone

IF8 (catalog no. sc-53566) ; Santa Cruz, Dallas,

TX) were used to detect endogenous canine RB

(23). Human RB (PSM-7LP RB) was detected

with an antibody that recognized the human, but

not the canine C-terminal domain of the protein

(clone LM95.1 (catalog no. OP66-100UG); EMD

Millipore, Brillercia, MA). ß-actin (clone AC-15

(catalog no. A5441); Sigma-Aldrich) was used as a

loading control.

RNA preparation and real-time quantitative

reverse transcriptase PCR (qRT-PCR)- RNAs

were prepared using the miRVANA kit (Life

Technologies) and cDNA was synthesized from

total RNA using a miScript reverse transcription

kit. cDNAs were quantified using the miScript

SYBR Green PCR kit (Qiagen, Valencia, CA) and

the 7500 Real Time PCR system (Applied

BioSystems, Foster City, CA) protocol. Previously

published primer sequences were used (24).

GAPDH was used for normalization and relative

levels of mRNA were established using the delta-

delta Ct method.

Inhibition of DNA methylation and of histone

deacetylation- Canine OSCA-40, OSCA-78, and

OSCA-32 cells were cultured in the presence of

1µM suberoylanilide hydroxamic acid (SAHA/

vorinostat, Cayman Chemical, Ann Arbor, MI)

and 10µM zebularine (Zeb, Sigma-Aldrich, St.

Louis, MO) as previously described (16).

Chromatin Immunoprecipitation (ChIP)- ChIP

assays were performed using the ChIP-IT Express

kit (Active Motif, Carlsbad, CA). Briefly, cells

were cross-linked in culture medium containing

1% formaldehyde, lysed, and then sheared to an

average size of 250-500 bp by sonication in

shearing buffer using the Branson Sonicator

(Thomas Scientific, Swedesboro, NJ). ChIP was

performed by incubating 25 μg chromatin per

reaction with protein G magnetic beads and 5 µg

anti-E2F1 antibody purchased from Abcam

(catalog no. ab112580, Cambridge, MA), anti-

human RB antibody (catalog no. OP66-100UG,

EMD Millipore), or control IgG overnight at 4°C.

Immunoprecipitated chromatin was purified by

magnetic separation, proteins were digested with

proteinase K, and enrichment of E2F1 sequences.

To amplify the GGGCGG (CDE site) sequence of

the human AURKB (AC135178.13) promoter the

following primers were used: 5'

GAGCCAATGGGAACTAGGCA

(F) and

5’- CCCTGGCCAAGGACTTTTCA(R). To

amplify the TTTCCAGCCAAT E2F binding site

in canine AURKB (NC_006587.3) the following

primers were used: 5'-

TTGGGTCCCAAGGTCTACGT (F) and

5’- AGGCCCTTTCAAATCTCCCG (R). To

amplify the CGGCGCTAAA E2F binding site in

canine CHEK1 (NC_006587.3) the following

primers were used: 5'-

TTGGGTCCCAAGGTCTACGT (F) and

5’- AGGCCCTTTCAAATCTCCCG (R).

For all primer pairs, PCR was performed at 60°C,

annealing temperature for 40 cycles. For each

sample, fold enrichment (FE) of target sequence in

ChIP samples versus negative control was

calculated by the delta Ct method. All ChIP

reactions were performed in duplicate. Data

represent mean SD of FE.

Gene Expression Profiling- Hybridization to

canine 4x44, 000 microarray chips (Agilent

Technologies, Santa Clara, CA) was done as

described at the University of Minnesota

Genomics Center (5,18). Probe signal levels were

quantile-normalized and summarized as previously

described (5) (Data archive submitted to GEO).

Two group t-tests were done to determine

differentially expressed genes.

Identification of Transcriptional Regulators-

Ingenuity Pathway Analysis (IPA) Suite (Ingenuity

Systems, Redwood City, CA) was used to identify

potential driver upstream transcriptional regulators


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responsible for gene signatures or differentially

expressed genes. IPA upstream regulator analysis

is based on prior knowledge of predictable effects

between transcriptional regulators and their target

genes stored in the Ingenuity Knowledge Base

IPA provides two statistical measures: the p-value

and regulation Z-score to detect potential upstream

transcriptional regulators. First, the p-value was

calculated based on how many known targets of

each transcriptional regulator were present in the

gene signature. Secondly, the known effect

(repression or activation) of a transcriptional

regulator on each target gene was compared to the

observed changes in gene expression in the

signature. A Z-score was calculated from the

concordance of the known effects of

transcriptional regulators and the observed

changes in gene expression. A Z-score > 2

indicated activation of the transcriptional regulator

while a Z-score of <-2 indicated repression of the

transcriptional regulator” The predicted upstream

regulators were limited to those known to be a

“transcriptional regulator” or “group.

DNA Motif Identification- The hg19_genes_2012-

03-09 GTF file (University of California, Santa

Cruz Genome Browser) was used for retrieval of -

1000 to +1 nucleotide regions relative to the

predicted ATG translation start site for each

ORF(25,26). The 5’ promoter sequences of 143

genes of the G2/M cell cycle transition and DNA

damage cluster and 108 genes of the

microenvironment interactions cluster (5) were

available for motif discovery using the Multiple

Expectation Maximization for Motif Elicitation

(MEME Suite (Version 4.9.0) in the Galaxy

platform (27). Motifs with zero or one occurrence

in each promoter and a length of between 5 – 10

nucleotides were identified.

Orthotopic model of canine osteosarcoma cell

lines- Procedures using laboratory animals were

done according to the guidelines, and under the

supervision, of the University of Minnesota

Institutional Animal Care and Use Committee

(protocol 1207A17293). Six-week old (~20 grams)

female athymic nude mice (NCr-nu/nu; NCI,

Fredrick, MD) anesthetized with xylazine (10

mg/kg) and ketamine (100 mg/kg) were injected

intratibially with OSCA-8, OSCA-32, or OSCA-

40 cells (105 per mouse). Buprenorphine (0.075

mg/kg q.8 hours) was used for pain control over

the first 24 hours and Tylenol administered in the

water was used as needed for pain control

thereafter. Routine tumor endpoints (ill thrift, or a

tumor reaching 1 cm in the largest diameter for

any animal in a group) or the inability to control

pain or discomfort (visible lameness or difficulty

moving in the cage) triggered termination of the

experiment and humane euthanasia of the mice for

that group. Tumor growth was monitored using

caliper measurements and in vivo imaging as

described (18). For histological confirmation,

tumors were collected immediately upon sacrifice,

fixed in 10% neutral buffered formalin and

evaluated grossly and histologically by board-

certified veterinary pathologists (Masonic Cancer

Center Comparative Pathology Shared Resource

Core).

Statistical Analysis- Graphs were created using

Prism (GraphPad Software, Inc. version 5.0, La

Jolla, CA). Results are presented as means ± SD.

Student’s two-tailed t-test was used to assess

significance. p-values < 0.05 were considered

significant.

RESULTS

Deregulation of the RB-E2F pathway is associated

with molecular phenotype that predicts worse

clinical outcomes- We anticipated that one or few

upstream transcriptional regulators were likely

responsible for the previously published, observed

expression changes that segregate osteosarcoma

samples into two distinct molecular phenotypes

predictive of tumor behavior and outcome (Fig.

1A) (5). To identify potential candidates, we used

the Upstream Regulator Analysis within the IPA

Suite. The direction of gene expression changes in

the Molecular Phenotype-2 samples (shorter

median survival times) was consistent with

inactive RB and p53 tumor suppressor genes

(Table 1, activation Z-scores of -3.801 and -3.791,

respectively). Other significant, predicted altered

regulators included E2F transcription factors and

chromatin remodelers: E2F-1, E2F-2, E2F-3,

E2F4, E2F6, SMARCB1, KDM5B, and HDAC1.

E2F4 was the most significantly altered

transcriptional regulator of the gene signature

(Table 1). However, since E2F4 up-regulates some

of these genes and down-regulates others, a

direction of activity (Z-score) could not be


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determined.

An important role for E2F-regulation of the target

genes in the gene signature became more evident

when we searched for conserved DNA response

elements in 5’ upstream promoter sequences. More

than 70% of the 5’ upstream promoter sequences

of the genes comprising the prognostic signature

contained the E2F consensus binding motif

sequence, CCAGGCTGG (data not shown). The

CCAGGCTGG sequence was present in 106 of

143 promoters of genes in the G2/M cluster (E

value 8.1E-105) and in 80 of 108 promoters of the

genes associated with microenvironment

interactions (E value 5.0E-32) (5). Importantly, the

9 base-pair dyad sequence also is one of the most

common sequence motifs in promoters of E2F4

target genes (28).

Orthotopic xenografts using cell lines derived

from Molecular Phenotype-1 and Molecular

Phenotype-2 osteosarcomas recapitulate their

clinical behavior- To test the tumorigenic potential

and outcome of cells from tumors from each

molecular phenotype and to establish suitable cell

lines for downstream functional studies, we

evaluated tumor growth in orthotopic xenografts.

The pattern of outcomes and tumor behavior was

maintained in vivo: the OSCA-32 cell line, which

was derived from a Molecular Phenotype-1 tumor

progressed more slowly and generated less local

bone destruction than the OSCA-40 and OSCA-8

cell lines, which were derived from dogs with

Molecular Phenotype-2 (shorter median survival

times) tumors (Fig 1B.). Microscopic findings for

these tumors were consistent with clinical

outcome. The OSCA-32 tumor cells showed

relatively well differentiated tumor cells laying

down osteoid seams in an orderly fashion (Fig.

2A, C); in contrast, OSCA-40 had highly

anaplastic cells embedded in a poorly organized

osteoid matrix, and extensive areas of necrosis

(Fig. 2B, D)

Characterization of representative cell lines of

each osteosarcoma phenotype- The results from

the orthotopic xenografts supported the use of

these cell lines to elucidate pathogenetic

mechanisms responsible for the biological

behavior of the two molecular phenotypes of

osteosarcoma. Deregulation of E2F transcriptional

activity could result from direct or indirect

mechanisms upon loss-of or reduced RB function.

This loss-of or reduced RB function, in turn, might

be due to mutations that decrease or eliminate RB-

1 expression or that render the RB protein

inactive; however, RB is a component of a

complex pathway and its activity can be

influenced by several regulatory factors (29). The

steady state levels of RB protein were

reproducibly lower in cell lines derived from

Molecular Phenotype-2 tumors (OSCA-40,

OSCA-78, OSCA-8) as compared to those seen in

the cell line derived from a Molecular Phenotype-

1 tumor (OSCA-32) (Fig. 3A).

To test the hypothesis that functional deregulation

of RB-E2F transcriptional regulation was causally

related to the osteosarcoma molecular phenotypes,

we measured the effect of RB protein abundance

on expression levels of Aurora Kinase B

(AURKB), a target gene that was among those

most highly expressed in Molecular Phenotype-2

samples (5). As shown in Fig. 3B, differential

expression of AURKB between the Molecular

Phenotypes 1 and 2 was maintained; Molecular

Phenotype-1 cells had lower expression levels of

AURKB while Molecular Phenotype-2 cells had

higher expression levels, providing the rationale to

next assess the activity of a AURKB-Luc reporter

construct (20). The AURKB 515 base pair

minimal promoter alone showed basal activity in

all four osteosarcoma cell lines that was consistent

with observed endogenous AURKB transcript

abundance (Fig. 3C). Reporter activity was not

further enhanced when we used an AURKB

promoter that included 1000 base pairs upstream

from the transcriptional start site (20), indicating

that the full complement of activity for this

promoter in osteosarcoma cells was contained

within the minimal promoter sequence.

Ectopic RB partially rescues the effects of RB-E2F

deregulation in vitro- The minimal AURKB

promoter reporter does not contain the

CCAGGCTGG sequence or the canonical E2F

binding DNA motif (TTTCCCGC). However, it

contains the cell cycle dependent element (CDE;

GGGCGG) that is responsive to E2F-mediated

transcriptional activation (20,30). In order to

evaluate the role of RB-E2F1 we used both the


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AURKB-Luc reporter and a CDE-mutant

AURKB-Luc reporter.

Canine osteosarcoma cell lines were co-

transfected with AURKB reporter and an N-

terminally truncated, RB pocket protein domain

(Wt RB), or the same construct containing seven

mutations that render the protein insensitive to

CDK inactivation (PSM-7LP RB). Introduction of

a CMV empty vector control (21) did not alter the

activity of the AURKB reporter, whereas ectopic

expression of RB inhibited AURKB promoter

activity in the four cell lines (Fig. 4A-B).

However, only the CDK-insensitive RB construct

decreased the activity of the AURKB reporter in

OSCA-32 cells, and the effect was modest when

compared to that observed in the OSCA-40,

OSCA-78, and OSCA-8 cell lines, where both RB

plasmids showed approximately equal repression

(Fig. 4B).

Repression by ectopic PSM-7LP RB was

significantly attenuated in each of the four cell

lines when we used a CDE-mutant AURKB

promoter, although partial repression was still

observed in the Molecular Phenotype-2 cell lines

(Fig. 4C). ChIP analysis confirmed that

endogenous canine E2F1 binds to the CDE in the

AURKB reporter, and that E2F1 had lower affinity

for the mutant CDE site (Fig. 4C).

The effect of ectopic PSM-7LP RB to suppress the

AURKB reporter also was rapidly saturable in

OSCA-32 cells, consistent with the presence of

active endogenous RB (Fig. 4D). In contrast,

ectopic PSM-7LP RB showed dose-dependent

suppression in OSCA-40, OSCA-78, and OSCA-8

cells (Fig. 4D), as would be predicted by absence

of endogenous functional RB.

Ectopic RB displaces E2F1 from endogenous

promoters - Given the repressive effect of ectopic

PSM-7LP RB on the ectopic AURKB vector in

cells representing the two molecular phenotypes of

osteosarcoma, we investigated whether these

effects were relevant and reproducible in the

endogenous context. Ectopic PSM-7LP RB protein

was detectable in all of the cell lines (Fig. 5A),

and the presence of ectopic RB consistently

reduced transcript abundance of AURKB and three

other genes (AURKA, BUB1B, and TOP2A) that

were part of the signature that identified

osteosarcoma molecular phenotypes (5) GAPDH

transcript abundance was not affected by the

presence of ectopic PSM-7LP RB (Fig. 5B).

To further validate the importance of the E2F-

dependent interactions in the study context, we

next confirmed that E2F1 was bound to the

endogenous TTTCCAGCCAAT motif in the

canine AURKB promoter, and that its presence on

the promoter contributed to transcription of

AURKB. ChIP assays (Fig. 6A) showed greater

enrichment for E2F1 bound to endogenous

AURKB promoter in OSCA-8 cells (Molecular

Phenotype-2) than in OSCA-32 cells (Molecular

Phenotype-1). Furthermore, E2F1 binding to the

promoter in both molecular phenotypes was

reduced in the presence of ectopic PSM-7LP RB.

Quantitative assessment of AURKB transcript

abundance by qRT-PCR was consistent with what

was observed in our ChIP data, showing that

ectopic PSM-7LP RB caused a greater magnitude

of reduction of AURKB transcript in OSCA-8 cells

versus OSCA-32 cells (data not shown). We

observed a similar effect upon analysis of E2F1

binding to the CGGCGCTAAA motif of the

endogenous CHEK1 promoter (Fig. 6B),

illustrating that ectopic PSM-7LP RB was

repressing the binding of E2F1 protein to genes

associated with G2/M progression and the DNA

damage checkpoint.

Importantly, we did not see any difference in E2F1

protein abundance in the cells transfected with

either the ectopic PSM-7LP RB or CMV plasmids

suggesting that ectopic RB was not simply

reducing E2F1 protein levels. PSM-7LP RB also

was not found in complexes bound to the E2F1-

response elements in the endogenous AURKB

promoter as determined by ChIP in OSCA-8 cells

using an antibody that specifically recognized the

ectopic human RB protein (data not shown). We

similarly did not find evidence of complex

formation between ectopic PSM-7LP RB and

endogenous E2F1 in co-immunoprecipitation

assays; yet, we also did not see a quantitative

difference in the amount of immunoprecipitated

E2F1 protein in cells from either molecular

phenotype transfected with PSM-7LP RB or with

the CMV empty vector, suggesting that ectopic

PSM-7LP RB did not compete with or sterically


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hinder binding of the anti-E2F1 antibody (data not

shown). Thus, we favor the interpretation that

displacement of E2F1 from the AURKB promoter

was an indirect effect of RB.

Ectopic RB alters the transcriptional landscape of

Molecular Phenotype-2 osteosarcoma cells

towards one resembling Molecular Phenotype-1-

The selective effects of RB on Molecular

Phenotype-2 osteosarcoma cells led us to

hypothesize that restoration of RB in these cells

would shift the genome-wide transcriptional state

in these cells to one resembling that of Molecular

Phenotype-1 cells. Genome-wide expression

profiling highlighted 78 genes that were

differentially expressed in OSCA-78 cells

transfected with PSM-7LP RB versus the CMV

control: these genes were significantly associated

with functions of DNA replication, metabolism of

DNA, and binding of chromatin (Table 2). The

most significant canonical pathway identified by

IPA was cell cycle control (data not shown).

Importantly, active RB, and inactive E2F1 and

E2F1 were among the most significant predicted

transcriptional regulators associated with the

differential expression of these 78 genes (Table 3).

In addition, IPA yielded a number of predicted

inactivated oncogenes, which have been shown to

be aberrantly expressed in osteosarcoma, including

MYC (31), as well as transcriptional regulators

associated with DNA damage repair and the

mitotic checkpoint, including TBX2 (32) (Table

3). Intriguingly, the gene expression profiles

resulting from restored RB activity in these cells

reflected an apparent recovery of activity for the

TP53 tumor suppressor gene (Table 3).

Regulation of AURKB by RB does not require p16-

Whereas, human U2-OS cells retain wild type

functional RB, human SAOS-2 cells have a

mutated RB (33,34). As shown in Figure 5A,

consistent with observations from canine samples,

RB-replete U2-OS cells had lower basal AURKB

luciferase activity in comparison to RB-deficient

SAOS-2 cells (average AURKB-

Luciferase/Renilla RLU: 0.43 and 41.01,

respectively) (Fig. 7A). Ectopic PSM-7LP RB did

not significantly repress expression of the AURKB

reporter in U2-OS cells after 6 hours (p=0.150),

whereas AURKB reporter activity was

significantly (p=0.002) reduced (~30%) in SAOS-

2 cells after 6 hours (Fig. 7B).

In U2-OS cells, p16 protein is silenced by

methylation of the promoter (33). Loss of p16 can

lead to unrestrained activation of Cdk4/6 and may

impair function of RB at the G0/G1 transition

checkpoint, during G1 progression and at cell

cycle exit (re-entry to G0). We hypothesized that

p16 deficiency would not be equivalent to

complete loss of RB, as other mechanisms of

control are operative during progression through

the S-phase and the G2/M phase (35,36).

Therefore, we tested whether CDK inhibition

occurred in p16-deficient U2-OS cells upon RB

activation. First, we confirmed that U2-OS cells

do not express p16 protein by Western blot (Fig.

7C). We then determined if RB was completely

inactivated in U2-OS cells by culturing them

under conditions of serum deprivation, which

leads to growth arrest. Within 72 hours of serum

withdrawal, RB was predominantly present in the

active, faster migrating (hypophosphorylated)

form, indicating that, despite silencing of p16,

CDKs can still be inhibited in U2-OS cells (Fig.

7D).

As we observed in canine OSCA-32 cells,

transfection of U2-OS cells with the CDK-

insensitive PSM-7LP RB led to modest repression

(30-40%; p = 0.047) of the AURKB reporter after

24 hours (Fig. 7E). Ectopic expression of the

CMV Empty Vector or p21 (CDKN1A) pan-CDK

inhibitor did not significantly reduce AURKB Luc

activity (p = 0.261, and p = 0.128, respectively).

Similarly, ectopic expression of the p16

(CDKN2A) CDK4/6 inhibitor had no effect (p =

0.484) (Fig. 7E).

HDAC and DNMT inhibitors alter genome wide

gene expression in Molecular Phenotype-2 cells to

a status associated with a functional RB-E2F

regulatory network (Molecular Phenotype-1)- RB

protein is known to associate with HDACs and

DNMTs (14,15). We reasoned that the absence of

functional RB would hinder the function of these

chromatin-remodeling enzymes, and that RB

activity might be restored through

pharmacological modulation. To assess the effects

on transcription due to treatment with DNMT and


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HDAC inhibitors, we did genome-wide expression

profiling of Molecular Phenotype-2 cells treated

with Zeb and SAHA. Figs. 8A and 8B show that

in Molecular Phenotype-2 cells (OSCA-78) cells

the transcriptional state of the defining prognostic

signature shifted to a state that resembled

Molecular Phenotype-1 (OSCA-32) after treatment

with Zeb and SAHA (5). Next, we examined if the

observed effect was associated with displacement

of E2F1 from relevant promoters. ChIP showed

that the amount of E2F1 bound to the endogenous

AURKB (Fig. 8C) promoter was decreased by

approximately 90% in Molecular Phenotype-1

cells, and 95% in Molecular Phenotype-2 cells,

after treatment with these drugs. Similarly, the

amount of E2F1 bound to the endogenous CHEK1

promoter decreased by approximately 80% in both

Molecular Phenotype-1 and Molecular Phenotype-

2 cells after treatment (Fig. 8C).

In addition, we identified 1047 statistically

significant differentially expressed genes (p< 0.05

and average fold-change of 2.0) in untreated and

treated OSCA-78 cells. These genes clustered into

two groups (data not shown). The first group of

genes, which was significantly associated with

functions of cell cycle progression and

proliferation, was down regulated in treated cells.

The second group, which was significantly

associated with functions of cellular organization,

maintenance, and cell-cell interactions, was up

regulated in treated cells. As a single group, these

genes were significantly associated with functions

related to cell cycle, proliferation, and cancer

functions (data not shown).

The IPA transcription factor module was used to

predict upstream regulators of the 1047 genes that

were differentially expressed between cells treated

with DNMT and HDAC inhibitors and those that

were not. RB was a predicted upstream

transcriptional regulator (Table 4) and was

predicted as being active in treated cells. The

predicted activity of other upstream transcriptional

regulators for these 1047 genes paralleled that

observed in Molecular Phenotype-1 cells (Table 1)

as well as that seen upon ectopic reintroduction of

RB into Molecular Phenotype-2 cells (Table 2).

SMARCB1 was predicted as being activated in

treated cells while E2F1, MYC, and FOXM1 were

predicted as being inactivated (Table 4).

DISCUSSION

Here we provide insight into mechanisms that

account for a prognostic gene signature that

reduces the heterogeneity associated with

osteosarcoma. As shown in our model Fig. 9, the

signature allowed us to group the disease into two

subgroups (Molecular Phenotype-1 and Molecular

Phenotype-2) that differ in their biological

behavior; i.e., time to progression and clinical

outcomes (5).

We observed that Molecular Phenotype-1 and

Molecular Phenotype-2 derived xenograft tumors

recapitulated the gross and histologic features of

spontaneous canine osteosarcoma. More

importantly, we show that Molecular Phenotype-2

xenograft tumors appeared to be phenotypically

more aggressive than Molecular Phenotype-1,

exhibiting more rapid growth at the primary tumor

site and a greater propensity for pulmonary

metastasis.

We determined that critical transcriptional

regulators of this evolutionary conserved signature

responsible for these two osteosarcoma

phenotypes are in the RB-E2F regulatory pathway.

In Molecular Phenotype-2 osteosarcoma (which

represents tumors from patients with worse

prognosis), the RB-E2F pathway is dysfunctional.

As a consequence, E2F-regulated genes including

those involved in G2/M transition and DNA

damage-induced cell cycle checkpoints are up

regulated and microenvironment-interacting genes

are down regulated.

Our results show that Molecular Phenotype-2 cells

are more responsive to RB restoration than

Molecular Phenotype-1 cells. The observation that

ectopic expression of constitutively active RB

resulted in transcriptional repression of E2F

targets and other genes associated with cell cycle

control and DNA replication is consistent with

previously defined mechanisms (15). However,

assessments of individual components of the RB

pathway have not always correlated with event

free or overall survival (37,38). Loss of

heterozygosity of RB has been proposed as an

indicator of poor prognosis in human

osteosarcoma patients (39), but our work is the

first to establish a direct link between a conserved,


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prognostic genome-wide gene expression

signature and deregulation of the RB-E2F pathway

in osteosarcoma (5). More specifically, current

models of the RB-E2F pathway do not

consistently account for expression levels of genes

during the G2/M phase of cell cycle (40,41); yet,

many of the genes that are overexpressed in

Molecular Phenotype-2 osteosarcoma, including

AURKB, are associated with the G2/M transition.

Recent data suggest that, unlike canonical E2F

response elements that operate primarily in G1/S,

the binding of E2F to the CDE is stronger in G2/M

(30).

One interesting finding from our study was that

restoration of RB compensated for other common

genetic alterations (e.g., TP53 and MYC)

associated with osteosarcoma. The finding

suggests that RB loss or deregulation can modify

tumor behavior and disease progression

downstream of oncogenes that are often altered in

osteosarcoma. While some of these effects could

be due to direct modulation of E2F activity, it also

is likely that indirect changes in the epigenetic

landscape that are established by functional RB

contribute to these effects. The interpretation that

functional RB utilizes mechanisms that are

independent of E2F binding is consistent with the

observation that mutating the CDE sequence did

not completely abrogate reduced AURKB activity

upon re-introduction of a functional RB gene to

Molecular Phenotype-2 cells. Additional support

for our interpretation was the observation that

mutating the CDE sequence also did not

completely abolish E2F1 binding, and that we

did not see evidence of RB binding to the E2F-

responsive elements in the AURKB promoter.

An important finding from our study was that

treatment with DNMT and HDAC inhibitors was

sufficient to supplant RB-E2F pathway function in

Molecular Phenotype-2 cells. Treatment with these

inhibitors altered genome wide gene expression in

Molecular Phenotype-2 cells to a status associated

with a functional RB-E2F regulatory network (as

seen in Molecular Phenotype-1). Moreover, we

show that treatment with DNMT and HDAC

inhibitors achieved comparable transcriptional

changes as genetic restoration of RB, albeit

through regulation of somewhat different gene

sets. Still, these gene sets were concentrated in or

near control nodes for overlapping biochemical

pathways, which is not entirely unexpected, given

the expectation that chromatin-remodeling

enzymes would have a broader effect to modulate

gene expression.

The observation that p16-deficient U2-OS cells

maintained at least a partially functional RB,

possibly through compensation of other CDK

inhibitors like p21, indicates that by itself, the

status of p16 cannot explain the RB-dependent

heterogeneity of osteosarcoma. Specifically, our

findings show that RB-E2F pathway are still able

to regulate genes associated with the G2/M

transition in U2-OS cells, probably through

inhibition of the S-phase and G2/M CDKs.

Nevertheless, CDKN2A deletion or silencing could

contribute to deregulation of the E2F pathway in

osteosarcoma (42). Not surprisingly, CDKN2A

was a predicted transcriptional regulator of the

prognostic gene signature. The CDKN2A locus

was recently linked to osteosarcoma risk in dogs,

and that the risk allele is “fixed” in certain breeds

like Rottweilers and Irish Wolfhounds (43). This

finding illuminates the need to investigate an

explanation for why canine osteosarcoma is so

often a highly aggressive disease (5).

It is widely accepted that RB inactivation is not

necessary for the development of osteosarcoma,

but rather accelerates its development and

progression (44,45). Here, we show that the

integrity of the RB-E2F pathway is

mechanistically associated with the biological

behavior of tumor cells derived from spontaneous

canine osteosarcoma in vitro and in vivo, and that

the RB-E2F molecular regulatory network extends

to human osteosarcoma cells. Specifically, our

data suggest that alternative treatment options that

create a state analogous to that seen with

functional RB could improve outcomes in

osteosarcoma patients, especially those with the

worst prognoses. Our data provide support for

further evaluation of the mechanistic role of RB-

E2F pathway in chromatin remodeling and the

contribution of the epigenetic landscape in

osteosarcoma pathogenesis.


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RESEARCH SUPPORT

Grant support for the project was provided by Morris Animal Foundation (D13CA-032), the American

Cancer Society (RSG-13-381-01), the Karen Wyckoff Rein in Sarcoma Foundation (2011-1), the Zach

Sobiech Fund for Osteosarcoma Research of the Children’s Cancer Research Fund, and the Comparative

Medicine Signature Program of the College of Veterinary Medicine, University of Minnesota. The NIH

Comprehensive Cancer Center Support Grant to the Masonic Cancer Center (P30 CA077598) provided

support for bioinformatics, genomics, flow cytometry, bioimaging, cytogenetics, and comparative

pathology services. Jamie Van Etten was supported by grant T32 CA09138, Cancer Biology Training

Grant from the National Institutes of Health, and Jaime F. Modiano is supported by the Alvin and June

Perlman Chair in Animal Oncology. The authors also gratefully acknowledge support from donors to the

Animal Cancer Care and Research Program of the University of Minnesota that helped support of the

project.

AKNOWLEDGEMENTS

We thank the Minnesota Supercomputing Institute for computational resources, and especially Dr. Ying

Zhang, for providing support and advice. We thank Dr. Aric Frantz for generation of OSCA-40-G/L cells,

Dr. Ramesh Kovi for assistance with pathological analyses and Mitzi Lewellen for assistance with in vivo

experiments, and LeAnn Oseth and the MCC cytogenetics core for assistance with FISH. We also thank

Rachit Gupta and Frances Phan for technical assistance and Drs. Dai Ito, Ali Khammanivong, and Siu

Chiu Chan for technical advice. We also thank Drs. Eric Knudsen and Masashi Kimura for providing

constructs and Drs. David Largaespada, Logan Spector, Scott Dehm, Tim Hallstrom, and Richard Gorlick

for helpful discussions and for review of the manuscript.

CONFLICT OF INTEREST

None.

AUTHOR CONTRIBUTIONS

MCS generated data, led the analysis and interpretation of data, prepared manuscript figures, and wrote

the paper. ALS generated data, contributed to bioinformatics data analysis and interpretation, and

performed a critical analysis of the manuscript. HT conducted xenograft and co-immunoprecipitation

experiments, provided technical assistance, and contributed to the preparation of the xenograft figures and

text. JLVE and JV conducted qRT-PCR analysis and revised the manuscript. IC and MGO did

histopathology of xenograft tumors and prepared the histopathology figure and text. SS and JFM

conceived and designed the study. SS offered advice on interpretation of data and gave a critical analysis

of the manuscript during its preparation. JFM supervised laboratory experiments, and assisted in writing

the manuscript. All authors reviewed the results and approved the final version of the manuscript.


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FIGURE LEGENDS

Fig. 1. Osteosarcoma in vivo models recapitulates the biological behavior of two distinct molecular

phenotypes. A, Sample dendrogram from previously published gene expression profiling of canine

osteosarcoma showing two molecularly distinct sample clusters, denoted as Molecular Phenotype-1 and

Molecular Phenotype-2, which have significantly different survival times 14 month and 2.83 months

respectively (5). Representative cell lines from each phenotype (OSCA-32, OSCA-40, OSCA-78, OSCA-

8) were used to identify mechanisms driving sample stratification. B, Serial in vivo imaging of athymic

nude mice harboring intratibial xenografts of OSCA-32 cells (Molecular Phenotype-1) or OSCA-40 or

OSCA-8 cells (Molecular Phenotype-2).

Fig. 2. Histopathology findings. Panels A and B show low magnification photomicrographs of OSCA-32

and OS-40 tumors, respectively. Note orderly deposition of osteoid seams (indicated by asterisk) in an

OSCA-32 tumor (Panel A) in contrast to the poorly organized osteoid matrix in an OSCA-40 tumor

(Panel B); also note area of necrosis (indicated by asterisk). Bars = 200 µm.

Panels C and D show high magnification photomicrographs of OSCA-32 and OS-40 tumors, respectively.

Relatively well-differentiated osteoblastic cells lay down osteoid (indicated by asterisk) in an OSCA-32

tumor (Panel C). In contrast, note proliferating spindle cells with numerous mitotic figures (arrowheads)

within poorly organized matrix (osteoid) of an OSCA-40 tumor (Panel D). Bars = 50 µm.

Fig. 3. Expression of AURKB in osteosarcoma phenotypes is inversely related to endogenous RB

protein and cells from tumors derived from dogs with shorter median survival times (Molecular

Phenotype-2) behave aggressively in vivo. A, Steady state levels of RB protein as determined by Western

blotting (ß-actin, loading control). B, Average value (SD) for AURKB expression from two Affymetrix

probes (GEO accession number GSE27217) (5). C, AURKB minimal promoter as determined by dual

luciferase assays in the four cell lines (means SD of duplicate experiments).

Fig. 4. Ectopic expression of RB represses activity of the AURKB minimal reporter through binding of

E2F1 to the cell cycle–dependent element (CDE). A, OSCA-32 (Molecular Phenotype-1), and OSCA-

40, OSCA-78, and OSCA-8 (Molecular Phenotype-2) cell lines were transiently transfected with CDK-

insensitive RB (PSM-7LP RB), or with CMV empty vector (Empty CMV) in combination with the

AURKB minimal reporter (AURKB) or the CDE site mutant AURKB reporter (Mut AURKB). All

reactions were done with a 1/100 molar equivalent of Renilla luciferase plasmid. Data show normalized

luciferase activity (Firefly/Renilla). Bars, represent inter-experimental means SD of two or more

independent experiments for each cell line. B, Cells were transiently transfected with RB constructs

encoding the wild type pocket protein sequence with an N-terminal truncation (Wt RB) or a CDK-

insensitive RB (PSM-7LP RB), in combination with the AURKB minimal reporter (AURKB) and a 1/100

molar equivalent of Renilla-Luc plasmid. Bars represent means SD of five independent experiments. C,

ChIP was performed using anti-E2F1 antibody or control IgG in cells transfected with the AURKB

reporter or the Mut AURKB reporter followed by PCR amplification of the CDE site of these reporters.

Bars show the mean fold enrichment SD of endogenous canine E2F1 normalized to IgG control in two

independent experiments. D, The experimental set-up described in (A) was used to determine the dose

response relationships of CDK-insensitive RB (PSM-7LP RB), or empty vector control (0- 0.25 µg per

2E5 cells) on the AURKB minimal reporter (AURKB-Luc).

Fig. 5. Ectopic RB decreases the abundance of prototypical E2F targets. A, Western blot (ß-actin,

loading control) showing steady state protein levels of ectopic PSM-7LP RB in cells transfected with

CDK-insensitive RB (PSM-7LP RB), or CMV empty vector. B, Transcript abundance of AURKB,

AURKA, BUB1B, TOP2A, and GAPDH in transfected cells was determined by qRT-PCR and normalized


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to RPL19. Results are shown as fold change in cells transfected with PSM-7LP RB relative to levels in

cells transfected with CMV control (CMV). Data represent means SD of two independent experiments.

Fig. 6. RB-mediated repression of endogenous AURKB associated with displacement of E2F1. A, ChIP

was performed using anti-E2F1 antibody or control IgG and enrichment of the E2F1 DNA binding motif

TTTCCAGCCAAT in the endogenous canine AURKB promoter in Molecular Phenotype-1 (OSCA-32,

left) and Molecular Phenotype-2 (OSCA-8, right) cells transfected with the CDK-insensitive RB (PSM-

7LP RB) or empty vector control was determined by qRT-PCR. Bars represent means SD of duplicate

reactions from one of six experiments done with similar results. B, ChIP to determine enrichment of E2F1

DNA binding to the endogenous CHEK1 promoter in OSCA-32 cells (left) and OSCA-8 cells (right)

transfected with CMV empty vector or with the CDK-insensitive RB (PSM-7LP RB).

Fig. 7. Differential RB-E2F activity associated with Molecular Phenotypes-1 and 2 is independent of

p16. A, The transcriptional activity of the AURKB minimal promoter in human U2-OS osteosarcoma

cells (RBwt

) and SAOS-2 osteosarcoma cells (RB mutant

) was determined using dual luciferase assays as

described in Figure 1D. B, Activity of the AURKB minimal reporter in cells transiently transfected with

RB constructs encoding the wild type pocket protein sequence with an N-terminal truncation (Wt RB) or

PSM-7LP RB in combination with a 1/100 molar equivalent of Renilla plasmid. Bars represent inter-

experimental means SD of two independent experiments. C, Western blot showing steady state levels of

p16 in U2-OS and SAOS-2 cells. ß-actin was used as a loading control. D, Western blot analysis of U2-

OS cells under conditions of serum deprivation. Electrophoretic mobility of total RB was used as an

indicator of phosphorylation status (faster mobility, lower band represents active, hypophosphorylated

RB; slower mobility, upper band represents inactive, hyperphosphorylated RB). ß-actin was used as

loading control. E, The effects of ectopic CDK-insensitive RB (PSM-7LP RB), p16, p21, empty vector

control on the activity of the AURKB minimal reporter (AURKB) Bars represent means SD of

duplicates from one experiment of four done with similar results.

Fig. 8. Treatment of Molecular Phenotype-2 osteosarcoma cells with HDAC and DNMT inhibitors

shifts their transcriptional state to resemble that of Molecular Phenotype-1 osteosarcoma cells. A,

Genome-wide microarray transcriptional profiling was used to define the effects of treatment with DNMT

and HDAC inhibitors (Zeb and SAHA) in Molecular Phenotype-2 cells (OSCA-78) and to compare these

transcriptional changes to the basal state of Molecular Phenotype-1 cells (OSCA-32). Left: Expression

levels of evolutionary conserved prognostic gene signature genes (n =255) in Molecular Phenotype-1

cells (OSCA-32) and Molecular Phenotype-2 cells (OSCA-78) (GEO accession number GSE27217);

right: Expression levels in replicates of Zeb + SAHA-treated and untreated OSCA-78 cells (5). Up

regulated genes are in red and down regulated genes are in green. B, Subset of G2/M transition and DNA

damage genes, including AURKB, from previously reported prognostic signature. C, ChIP was done as in

Figure 3A to determine enrichment of the E2F1 DNA binding motif (TTTCCAGCCAAT) in the

endogenous canine AURKB promoter in untreated and Zeb + SAHA-treated Molecular Phenotype-1 cells

(OSCA-32, left) and Molecular Phenotype-2 cells (OSCA-8, right).

Fig. 9. Working model of RB-E2F regulated gene expression in the two molecular phenotypes of

osteosarcoma. In Molecular Phenotype-1 osteosarcoma (left), functional RB down-regulates E2F activity

and restricts expression of genes associated with cell cycle progression through its interaction with the

E2F DNA binding sequences. In Molecular Phenotype-2 osteosarcoma (right), RB is absent or non-

functional and cannot form stable RB-E2F complexes, leading to deregulation of E2F-responsive targets

(indicated by black shapes in figure). Restoration of RB or treatment with DNMT and HDAC inhibitors

shifts the transcriptional state of genes associated with Molecular Phenotype-2 osteosarcoma (rapid

progression and worse prognosis) to a transcriptional state associated with functional RB and Molecular

Phenotype-1 osteosarcoma (less rapid progression and better prognosis).


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Table 1: Regulators of the gene signature that identifies two osteosarcoma phenotypes. IPA was

applied to identify upstream transcriptional regulators of the gene signature consisting of approximately

250 genes (5). A Z-score >2 indicates activation, while a Z-score < -2 indicates inactivation.

Upstream

Regulator Molecule Type

Predicted Activation State

in samples with worse

patient outcomes

Activation

z-score

p-value of

overlap

E2F4 transcription regulator NA NA 7.86E-39

Vegf group Activated 5.751 2.79E-30

E2F1 transcription regulator Activated 5.032 1.18E-31

TBX2 transcription regulator Activated 4.583 9.26E-27

FOXM1 transcription regulator Activated 4.127 3.70E-20

CCND1 transcription regulator Activated 3.755 6.74E-28

MED1 transcription regulator Activated 3.550 2.88E-09

FOXO1 transcription regulator Activated 3.503 4.12E-09

E2f group Activated 3.382 3.61E-19

MYC transcription regulator Activated 3.309 3.18E-10

STAT3 transcription regulator Activated 3.239 2.24E-04


NFKBIA transcription regulator Activated 3.011 2.16E-09


NRIP1 transcription regulator Inhibited -2.219 2.32E-06

SMARCB1 transcription regulator Inhibited -2.393 2.73E-16

TOB1 transcription regulator Inhibited -2.449 5.86E-06

ATF3 transcription regulator Inhibited -2.577 3.17E-07

HOXA10 transcription regulator Inhibited -2.588 2.20E-03

HDAC1 transcription regulator Inhibited -2.611 2.24E-11

E2F6 transcription regulator Inhibited -2.828 1.27E-11

TCF3 transcription regulator Inhibited -3.317 3.95E-08

Rb group Inhibited -3.348 2.94E-19

RBL1 transcription regulator Inhibited -3.379 8.36E-15

KDM5B transcription regulator Inhibited -3.734 9.06E-17

TP53 transcription regulator Inhibited -3.791 2.03E-38

RB1 transcription regulator Inhibited -3.801 2.51E-23

CDKN2A transcription regulator Inhibited -4.358 2.27E-16

NUPR1 transcription regulator Inhibited -4.849 6.56E-17


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Table 2: Gene function enrichment analysis after RB is ectopically restored in Molecular Phenotype-2

cells. Genome-wide expression profiling was used to compare OSCA-78 cells transfected with CDK-

insensitive RB (PSM-7LP RB) to OSCA-78 cells transfected with CMV empty vector. Genes with a p-

value < 0.05 and average fold-change of 1.53 were identified for further analysis. IPA was applied to

identify biological functions associated with differentially expressed genes in Molecular Phenotype-2

osteosarcoma, RB restored cells.

Functions Annotation p-Value

metabolism of DNA 6.95E-14

DNA replication 7.76E-14

synthesis of DNA 3.22E-12

initiation of replication of DNA 1.13E-09

interphase 1.52E-08

binding of chromatin 2.33E-08

checkpoint control 3.98E-08

S phase 5.79E-08

repair of DNA 1.11E-07

proliferation of tumor cell lines 1.73E-07

Table 3: Upstream Regulator analysis of genes whose expression changes in Molecular Phenotype-2

osteosarcoma cells after RB is ectopically restored. Genome-wide expression profiling was used to

compare OSCA-78 cells transfected with CDK-insensitive RB (PSM-7LP RB) to OSCA-78 cells

transfected with CMV empty vector. Genes with a p-value < 0.05 and average fold-change of 1.53 were

identified for further analysis. IPA was applied to identify upstream transcriptional regulators specific to

restoration of RB. A Z-score >2 indicates activation, while a Z-score < -2 indicates inactivation.

Upstream


Predicted Activation

State after RB is

ectopically restored

Activation

z-score

p-value of

overlap

NUPR1 transcription regulator Activated 3.464 1.08E-02

CDKN2A transcription regulator Activated 3.06 1.26E-08

RB1 transcription regulator Activated 2.93 1.76E-13

TP53 transcription regulator Activated 2.852 7.09E-12

Rb group Activated 2.425 1.31E-06

CDKN1A transcription regulator Activated 2 5.41E-10

IRGM transcription regulator Activated 2 1.66E-03


JUN transcription regulator Inhibited 2.412 1.44E-01

CCND1 transcription regulator Inhibited -2.555 3.34E-07

MYC transcription regulator Inhibited -3.082 8.38E-02

TBX2 transcription regulator Inhibited -3.44 6.00E-11



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Table 4: Regulators of genes whose expression significantly changes in Molecular Phenotype-2

osteosarcoma cells after treatment with DNMT and HDAC inhibitors. Genome-wide expression

profiling was used to compare OSCA-78 cells treated with DNMT and HDAC inhibitors to untreated

OSCA-78 cells. Genes with a p-value < 0.05 and average fold-change of 1.53 were identified for further

analysis. IPA was applied to identify upstream transcriptional regulators specific to treatment with DNMT

and HDAC inhibitors. A Z-score >2 indicates activation, while a Z-score < -2 indicates inactivation.

Upstream


Predicted Activation

Status after treatment

with DNMT and HDAC

inhibitors

Activation

z-score

p-value of

overlap

FOXO3 transcription regulator Activated 2.224 6.58E-06

RB1 transcription regulator Activated 2.200 1.19E-05

HNF4A transcription regulator Activated 2.114 1.17E-04

EPAS1 transcription regulator Activated 2.362 6.75E-04

Rb group Activated 2.528 4.46E-03

SMARCB1 transcription regulator Activated 2.877 1.89E-02

HIF1A transcription regulator Activated 2.063 2.19E-02

TBX2 transcription regulator Inhibited -3.053 4.34E-06

Vegf group Inhibited -2.882 1.23E-05

MYC transcription regulator Inhibited -3.386 3.16E-04

FOXM1 transcription regulator Inhibited -3.082 4.13E-04


EIF4E translation regulator Inhibited -2.517 5.61E-03

ZNF217 transcription regulator Inhibited -2.000 5.78E-03

Ras group Inhibited -2.150 1.59E-02

KLF5 transcription regulator Inhibited -2.197 3.19E-02

JUN transcription regulator Inhibited -2.013 5.03E-02

Hdac group Inhibited -2.345 7.14E-02

ETS1 transcription regulator Inhibited -2.076 8.35E-02


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OSC

A-3

2

OSC

A-7

8 O

SCA

-8

OSC

A-4

0

Molecular Phenotype-1


OSCA-32

Day1

Day35

OSCA-40 OSCA-8

Day56

Luminescence 5.0 4.0 3.0 2.0 1.0 × 109 Radiance (p/sec/cm2/sr) Color Scale Min = 5.00e7 Max = 5.00e9

B

Figure 1A


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Figure 2


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RB

B-actin

OSCA-32 OSCA-40 OSCA-78 OSCA-8

100200300

1000

1500

2000

AU

RK

B e

xpre

ssio

n (A

ffym

etrix

_Can

ine

2.0)


2

4

6

AU

RK

B F

irefly

/Ren

illa

RLU


B

C

A



Figure 3


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Molecular Phenotype-1 (OSCA-32)

0.0

0.5

1.0

1.5R

LU (L

ucife

rase

/Ren

illa)

PSM 7LP RB:Empty CMV:

AURKB:Mut AURKB:

- - + - - +

+ + + - - -- - - + + +

- + - - + -

p > 0.05p = 0.05


RLU

(Luc

ifera

se/R

enill

a)

0.0

0.5

1.0

1.5 p = 0.03p < 0.001


AURKB:Mut AURKB:

- - + - - +

+ + + - - -- - - + + +

- + - - + -

Molecular Phenotype-1(OSCA-32)

0.0

0.5

1.0

1.5

RLU

(Luc

ifera

se/R

enill

a)

Con Plasmid


0.0

0.5

1.0

1.5

Con Plasmid

Molecular Phenotype-2(OSCA-8) Ectopic AURKB

0

5

10

15

20

Fold

Enr

ichm

ent IgG

E2F1

AURKB:Mut AURKB:

+ + - -- - + +


0.0

0.5

1.0

1.5

RLU

(Luc

ifera

se/R

enill

a) p > 0.05p < 0.0001


AURKB:Mut AURKB:

- - + - - +

+ + + - - -- - - + + +

- + - - + -


RLU

(Luc

ifera

se/R

enill

a)

0.0

0.5

1.0

1.5 p = 0.01p < 0.0001


AURKB:Mut AURKB:

- - + - - +

+ + + - - -- - - + + +

- + - - + -


0.0

0.5

1.0

1.5

Con Plasmid


0.0

0.5

1.0

1.5 CMV EmptyPSM 7LP RB

Con Plasmid

A

D

B

Figure 4R

LU (L

ucife

rase

/Ren

illa)

OSCA-32

OSCA-40

OSCA-78

OSCA-80.0

0.5

1.0

1.5AURKB-Luc AURKB-Luc+ PSM 7LP RB

AURKB-Luc+wt RB

C


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Molecular Phenotype-1Endogenous AURKB

012345

Fold

Enr

ichm

ent

IgGE2F1

Empty CVM: PSM 7LP RB:

+ + - -- - + +

Molecular Phenotype-1Endogenous CHEK1

012345

Fold

Enr

ichm

ent

IgGE2F1


+ + - -- - + +


012345

Fold

Enr

ichm

ent

IgGE2F1


+ + - -- - + +

Molecular Phenotype-2Endogenous CHEK1

012345

Fold

Enr

ichm

ent

IgGE2F1


+ + - -- - + +

A

B

Figure 6


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0.0

0.5

1.0

1.5

RLU

(Luc

ifera

se/R

enill

a) U2-OS

U2-OS - serum

48 hr 72 hr

Jurkat + serum

U2-OS + serum

RB

B-actin

U2-OS SAOS-20.1

1

10

100

AU

RK

B L

ucife

rase

/Ren

illa

RLU

U2-OS (6 hrs) SAOS-2 (6 hrs)0.0

0.5

1.0

1.5

2.0

RLU

(Luc

ifera

se/R

enill

a)

AURKB-Luc AURKB-Luc + PSM 7LP RB

AURKB-Luc + wt RB

p > 0.05

p = 0.002

0.0

0.5

1.0

1.5

2.0

RLU

(Luc

ifera

se/R

enill

a) U2-OS (24 hrs)

p > 0.05

AURKB:Empty CMV:

PSM-7LP RB:p16:p21:

+ + + + +- + - - -- - + - -+ + + + +- - - - +

A C

D E

Figure 7

B-actin

p16

U2-OS SAOS-2

B-actin

p16

U2-OS SAOS-2

B


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Mol

ecul

ar P

heno

type

-1

Mol

ecul

ar P

heno

type

-2

Bla

nk

SAH

A+Z

eb

SAH

A+Z

eb

Unt

reat

ed

Unt

reat

ed

G2/

M tr

ansi

tion

an

d D

NA

dam

age

gene

s M

icro

envi

ronm

ent

gene

s


Subs

et o

f G2/

M tr

ansi

tion

and

DN

A d

amag

e ge

nes

Mol

ecul

ar P

heno

type

-1

Mol

ecul

ar P

heno

type

-2

Bla

nk

SAH

A+Z

eb

SAH

A+Z

eb

Unt

reat

ed

Unt

reat

ed

A B

C

Figure 8


01234

Fold

Enr

ichm

ent

SAHA + Zeb

- - + +


01234

Fold

Enr

ichm

ent

IgGE2F1

- - + +SAHA + Zeb


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Figure 9

RB regulated E2F-responsive genes

Molecular Phenotype-1 (Better Prognosis)

Molecular Phenotype-2 (Worse Prognosis)

GGCGGG

RB RB

GGCGGG E2F

+ functional RB

+ DNA and chromatin modifying drugs

E2F

Jyotika Varshney, M. Gerard O'Sullivan, Subbaya Subramanian and Jaime F. ModianoMilcah Carol Scott, Aaron L. Sarver, Hirotaka Tomiyasu, Ingrid Cornax, Jamie Van Etten,

OsteosarcomaAberrant RB-E2F Transcriptional Regulation Defines Molecular Phenotypes of

published online September 16, 2015J. Biol. Chem.

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