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\begin{document}

\title{Prognostic and Therapeutic Utility of Variably Expressed Cell Surface
Receptors in Osteosarcoma}



\author[1]{Yoav Zvi}%
\author[2]{Elif Ugur}%
\author[1]{Brian Batko}%
\author[3]{Jonathan Gill}%
\author[3]{Michael Roth}%
\author[4]{Richard Gorlick}%
\author[5]{David Hall}%
\author[1]{Janet Tingling}%
\author[6]{Donald Barkauskas}%
\author[2]{Jinghang Zhang}%
\author[1]{Rui Yang}%
\author[1]{Bang Hoang}%
\author[1]{David Geller}%
\affil[1]{Montefiore Medical Center}%
\affil[2]{Yeshiva University Albert Einstein College of Medicine}%
\affil[3]{University of Texas MD Anderson Cancer Center Children's Cancer Hospital}%
\affil[4]{University of Texas MD Anderson Cancer Center}%
\affil[5]{Children's Oncology Group}%
\affil[6]{Children’s Oncology Group}%


\vspace{-1em}



  
  \date{May 21, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Background: Six cell surface receptors, human epidermal growth factor
receptor (Her)-2, platelet-derived growth factor receptor (PDGFR)-\selectlanguage{greek}β,
\selectlanguage{english}insulin-like growth factor 1 receptor (IGF-1R), insulin receptor (IR),
c-Met, and vascular endothelial growth factor receptor (VEGFR)-3,
previously demonstrated variable expression across varying osteosarcoma
(OS) cell lines. The current study sought to validate previous
expression patterns and evaluate whether these receptors offer
prognostic and therapeutic value. Methods: Patient-derived OS samples (n
= 52) were labeled with antibodies to Her-2, PDGFR-\selectlanguage{greek}β, \selectlanguage{english}IGF-1R, IR, c-Met,
and VEGFR-3. Expression was characterized using flow cytometry. The
geometric mean fluorescent intensity (geoMFI) for each receptor was
calculated relative to a negative control. The event-free survival (EFS)
and overall survival for patients with positive receptor expression were
estimated by the Kaplan-Meier method. Differences in hazard for EFS
event and overall survival event for patients with positive receptor
expression were assessed using the log-rank test. Results: All 6
receptors were variably expressed in the majority of cell lines. None of
the 6 receptors, were found to be significant predictors of EFS or
overall survival. The sum total number of positive receptors per cell
line also failed to predict EFS or overall survival. Conclusion: The six
cell surface receptors demonstrated variable expression across the
majority of patient-derived OS samples tested. While receptor expression
did not provide prognostic value, their consistent expression makes them
attractive targets for future therapeutic approaches.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Osteosarcoma (OS) is the most common non-hematologic primary bone
malignancy and the fifth most common primary malignancy among
adolescents and young adults {[}1, 2{]}. The overall 5-year survival has
plateaued at roughly 70\% and has not improved in nearly four decades
{[}2-5{]}. Multiple cooperative efforts including the recent EURAMOS-1
trial and studies by the European Osteosarcoma Intergroup {[}6, 7{]}
have repeatedly demonstrated that intensifying conventional chemotherapy
alone is futile, underscoring the need for novel approaches. There
remains an ongoing interest in identifying OS biomarkers for
prognostication and therapeutic targets.

The cell surface receptors expression pattern in OS was previously
studied using patient-derived and standard OS cell lines {[}8{]}.
Insulin-like growth factor receptor 2 (IGF2R) was consistently
overexpressed across all cell lines evaluated, and further investigated
as a potential novel therapeutic target using radioimmunotherapy {[}9,
10{]}. A second group of receptors including Human epidermal growth
factor receptor (HER)-2, platelet-derived growth factor receptor
(PDGFR)-\selectlanguage{greek}β, \selectlanguage{english}IGF-1R, insulin receptor (IR), c-Met, and vascular
endothelial growth factor receptor (VEGFR)-3 were found to be variably
expressed. Consideration was given as to whether expression across these
receptors could yield either prognostic or therapeutic utility for
subsets of OS tumors.

The purpose of this study was to address the following questions: (1)
Does the variable pattern of receptor expression corroborate previously
reported findings? (2) Does the pattern of surface receptor expression
provide prognostic utility?

\textbf{Materials \& Methods}

\emph{Cell lines}

Ninety-nine OS cells lines were obtained from the Children's Oncology
Group (COG) biorepository. All samples originated from patients with
high-grade localized OS and were banked following informed written
patient consent and Institutional Review Board (IRB) approval. Clinical
outcomes for each sample were blinded to the investigators and only
associated at the time of analysis. Of these 99 patients, 50 patients
survived, and 49 patients had died. Eighteen samples did not grow in
culture, leaving 81 samples available for analysis. Fifty-two samples
yielded a sufficient number of cells for data analysis. Forty-eight
patients had survival data. One patient had 2 observations that were
treated as independent observations. The survival analysis was performed
using these 49 observations.

\emph{Flow Cytometry Analysis}

Cells were thawed and centrifuged to remove their freezing medium. After
re-suspension with MEM-\selectlanguage{greek}α \selectlanguage{english}media and 10\% fetal bovine serum, cells were
counted to determine the number of live cells per sample. As close to 1
million live cells were stained and assessed using flow cytometry.

Cell staining was done using commercially available anti-human
antibodies to Her-2, IGF-1R, IR, VEGFR-3, c-MET, and PDGFR- \selectlanguage{greek}β \selectlanguage{english}receptors
in accordance with manufacture instructions (Table 1). Each antibody was
conjugated to one of three fluorophores -- phycoerythrin (PE),
fluorescein-isothiocyanate (FITC) or allophycocyanin (APC) (Table 1).
Control tubes were prepared using isotype-matched antibodies.

Flow cytometry analysis was performed using a Becton Dickinson LSRII
digital bench top flow cytometer (Becton Dickinson, Mountain View, CA).
To gate for single live cells, standard forward and side scatter gating
protocols with DAPI staining, were employed as follows: FSC-A/SSC-A,
FSC-A/FSC-H, SSC-A/SSC-H, SSC-A/DAPI. A minimum of 1,000 single live
cells was required for analysis. Data was analyzed using FlowJo software
(BD Biosciences).

\emph{Receptor Characterization}

Receptor expression was plotted across all assayed cell lines, and
expressed relative to a negative control. The negative controls used for
Her-2-PE and PDGFR- \selectlanguage{greek}β -\selectlanguage{english}PE were their respective isotype-matched
controls, while the C243 cell line was used as the negative control for
IGF-1R-FITC, IR-FITC, c-Met-APC, and VEGFR3-APC. Cell line C243 yielded
no meaningful expression for these four receptors, and statistically
deemed to be a robust negative control.

Limited samples precluded the use of Fluorescent Minus One (FMO) tubes;
however, the C243 line was felt to provide a better negative control,
accounting for any auto-fluorescence. Additional negative control Molt4
cell line was used as validation for Her-2 receptor characterization.
For each cell line, triplicate samples were analyzed in order to
diminish the likelihood that the results were due to a technical error.
The geometric mean fluorescent intensity (geoMFI) and negative control
geoMFI for each receptor across all cell lines were calculated.

The geoMFI for each receptor was recorded and expressed relative to the
respective negative control as a fold change and defined as
(geoMFI\textsubscript{positive}/geoMFI\textsubscript{negative}). A
receptor was considered positive if the fold change in geoMFI was above
the 50\textsuperscript{th} percentile of cell lines. Binary variables
were assigned for Her-2, PDGFR- \selectlanguage{greek}β, \selectlanguage{english}IGF-1R, IR, cMet, and VEGFR3 in every
cell line, indicating their presence or absence.

\emph{Statistical Analysis}

For each COG cell line, seven variables were analyzed. The first six
were binary variables representing the presence or absence of: Her-2,
PDGFR- \selectlanguage{greek}β, \selectlanguage{english}IGF-1R, IR, c-Met, and VEGFR-3. The seventh variable was the
total number of positive receptors for a given cell line.

Each demographic characteristic of interest plus the COG study that was
the source of follow-up data was checked for association with inclusion
in the analytic population and each pair of characteristics was checked
for association within the analytic population by the exact conditional
test of proportions. Age at enrollment was checked in this manner as a
categorical variable (0-9, [?]10 years) and also as a continuous variable
using the \emph{t} -test or a one-way analysis of variance (ANOVA), as
appropriate.

The outcome in terms of event free survival (EFS) and overall survival
were compared among the groups defined by the demographic variables.
Event free survival was defined as days from enrollment to either an
event (relapse, progression, or death) or to last contact. For EFS,
patients were considered censored at last contact if they did not
experience an event. Overall survival was defined as days from
enrollment until either death or last contact. Osteosarcoma patients
were considered censored at last contact if they were alive at that
time.

The EFS and overall survival for the 6 receptors, as well as the total
number of positive receptors per cell line, were estimated by the Kaplan
Meier method. Differences in hazard for EFS event and overall survival
event for positive and negative patients in each of the 6 receptors, as
well as the total number of positive receptors per cell line, were
assessed using the log-rank test. Analyses were done in SAS9.4 using
PROC LIFETEST and PROC FREQ.

\textbf{Results}

The geoMFI and negative control geoMFI for each cell line and the
respective receptors are summarized in Table 2. In Figure 1, the fold
change (geoMFI\textsubscript{positive}/geoMFI\textsubscript{negative})
for each receptor across all cell lines is shown. The majority of cell
lines were found to express the receptors of interest relative to their
negative control; Her-2 was expressed in 98\% of cell lines, c-MET in
76.5\%, IGF-1R in 76.5\%, PDGFR- \selectlanguage{greek}β \selectlanguage{english}in 70.5\%, IR in 66.7\%, and VEGFR-3
in 62.7\%. Outliers included cell lines C232 and C331, which exhibited
no or very low expression for all 6 receptors. Her-2 and PDGFR- \selectlanguage{greek}β
\selectlanguage{english}expression demonstrated more variability across all cell lines, compared
to IGF-1R, IR, VEGFR-3, and c-MET, which demonstrate less variability
(Figures 1 \& 2). The majority of cell lines were noted to be positive
for 2 of 6 receptors, while only 3 cell lines demonstrated positive
expression for all 6 receptors (Figure 3, Table 3).

Metastatic status at diagnosis (p = 0.0192) was found to be
significantly associated with overall survival. Tables 4 and 5 summarize
those patients with EFS and overall survival events with relation to the
respective receptors expressed. Hazard ratio analyses for each of the 6
receptors and total number of positive receptors per cell line did not
find them to be significant predictors of EFS or overall survival
(Tables 6 \& 7).

\textbf{Discussion}

In this study Her-2, PDGFR-\selectlanguage{greek}β, \selectlanguage{english}IGF-1R, IR, c-Met, and VEGFR-3 were
variably expressed, reaffirming previously reported results {[}8{]}.
Hassan et al. reported a mean and standard deviation
geoMFI\textsubscript{positive}/geoMFI\textsubscript{negative} for the
six receptors across all cell lines much different in absolute value
than those reported in the current study. However when calculating the
coefficient of variation to account for these differences, variable
expression clearly exists across all receptors in both studies
(Supplementary Table 1). Despite corroborating these initially reported
findings, expression failed to achieve statistical significance in
predicting EFS or overall survival.

The prognostic value of Her-2 in OS has been debated in the past and
remains controversial. Akatsuka et al. analyzed immunohistochemical
expression of Her-2 in 81 tumor samples from patients with
non-metastatic OS treated with surgery and chemotherapy {[}11{]}. They
found that Her-2 over-expression was associated with both significantly
increased EFS (72.2\% vs. 45.6\% at 5 years, p = 0.03) and overall
survival (79.7\% vs. 58.2\% at 5 years, p = 0.03). Additionally,
decreased levels of Her-2 increased the risk of adverse events and death
(rate ratio: 2.24 and 2.54; 95\% CI, 1.07-4.72 and 1.09-5.67,
respectively). In contrast, Zhang et al. performed a meta-analysis
evaluating the relationship between Her-2 expression and overall
survival {[}12{]}. They identified 16 OS studies that provided survival
outcomes and identified samples as being Her-2 positive or negative.
Overexpression of Her-2 was associated with decreased overall survival
in both biopsy and surgically removed specimens (HR = 2.07, 95\% CI:
1.16-3.72, p = 0.014; and HR = 2.02, 95\% CI: 1.10-3.71, P = 0.024).
Finally, the COG conducted a large prospective study of 149 patients
with newly diagnosed OS to determine the prognostic value of Her-2
{[}13{]}. They were unable to demonstrate that Her-2 status was
associated with EFS or overall survival in patients with localized
disease, concluding Her-2 expression was not prognostic.

Despite conflicting evidence regarding the prognostic utility of Her-2,
its role as a therapeutic target has been pursued. \emph{In
vitro}studies by Long et al. investigated the role of Lapatinib, an
inhibitor of Her-2 phosphorylation, in standard OS cell lines {[}14{]}.
They found a dose- and time-dependent inhibition of cellular
proliferation, higher apoptotic rates, and inhibition of
migratory/invasive abilities. Rainusso et al. utilized Her-2-specific
CAR T-cells to target tumor-initiating cells (TICs) in OS within an
orthotopic xenograft model {[}15{]}. \emph{In vivo} administration of
the Her-2-specific T cells significantly reduced TICs, as evidenced by a
reduction in sarcosphere forming efficiency in the explanted tumors. A
phase II clinical trial, involving 96 patients with newly diagnosed
metastatic OS, sought to determine the safety and feasibility of
Trastuzumab as an adjunct to chemotherapy in patients whose tumors
overexpressed Her-2 {[}16{]}. The 30-month EFS and overall survival for
patients with Her-2 overexpression treated with chemotherapy and
trastuzumab were 32\% and 59\%, respectively. Patients without Her-2
overexpression treated with chemotherapy alone demonstrated EFS and
overall survival of 32\% and 50\%, respectively. These results failed to
demonstrate significant improvement in survival by the addition of
Trastuzumab. While Her-2 remains a feasible target, further
investigation into its clinical value is needed.

There are numerous reports that have characterized the role of the
IR/IGF-1R signaling pathway in the tumorigenesis and metastasis of
various cancers {[}17, 18{]}. Li et al. showed that over-expression of
IGF-1R promotes cellular proliferation, survival, and drug resistance,
subsequently leading to OS metastasis {[}19{]}. Wang et al. compared
expression levels of IGF-1R mRNA and proteins in 26 OS versus
non-cancerous bone samples; both mRNA and proteins levels were found to
be significantly higher within the OS samples {[}20{]}. Using 84 OS
samples, IGF-1R expression was correlated to survival. High IGF-1R
expression was associated with poorer survival, with multivariate Cox
analyses demonstrating it to be an independent prognostic marker.

Both IR and IGF-1R have been investigated as therapeutic targets. A
number of preclinical \emph{in vitro} studies using OS cell lines have
successfully suppressed cell proliferation, migration and invasion by
inhibiting the IR/IGF-1R signaling pathway using miRNA, siRNA, and
inhibitory antibodies {[}18, 21-25{]}. Kolb et al. used R1507, an
anti-IGF-1R antibody, in OS xenograft tumor models to delay tumor growth
in 4 of 6 OS xenografts with significant improvement in EFS {[}26{]}.
Anderson et al. conducted a multi-institutional phase 2 clinical study
using robatumumab in patients with relapsed OS and Ewing sarcoma
{[}27{]}. In OS patients with resectable tumors the median overall
survival was 20 months, while OS patients with unresectable tumors had a
median overall survival of 8.2 months. The authors concluded that IGF-1R
was targetable, though additional investigation was needed.

Platelet derived growth factor has been implicated in the tumorigenesis
and metastasis of several solid tumors, and shown to portend a poor
prognosis {[}28, 29{]}. Its role in the progression and prognosis of OS
has been investigated as well {[}30, 31{]}. Kubo et al. examined
surgical specimens from 54 OS patients, comparing the level of PDGF
(-AA, -\selectlanguage{greek}α, -\selectlanguage{english}BB, -\selectlanguage{greek}β\selectlanguage{english}) receptor expression through immunohistochemistry to
patient prognosis. They found PDGF-AA and PDGF-\selectlanguage{greek}α \selectlanguage{english}receptors were
correlated with inferior EFS (p \textless{} 0.05), while PDGF-BB and
PDGF-\selectlanguage{greek}β \selectlanguage{english}did not correlate to inferior EFS (p = 0.15). They also evaluated
imatinib mesylate as a therapeutic agent for OS. However, excessively
high doses were required to achieve cytotoxicity and pathway inhibition,
making this therapeutic approach unfeasible.

Imatinib has been utilized in both pre-clinical and early phase clinical
studies. Yamaguchi et al. evaluated the \emph{in vivo} anti-tumor
effects of imatinib versus imatinib and doxorubicin in mice with
heterotopically injected OS tumors. They demonstrated that combination
therapy yielded synergistic effects, inhibiting cell proliferation
{[}32{]}. The COG conducted a phase 2 clinical study looking at the
effects of imatinib in children with refractory or relapsed solid tumors
{[}33{]}. None of their OS patients demonstrated response according to
Response Evaluation Criteria in Solid Tumors (RECIST). They were
unsuccessful in showing imatinib was an effective, single-agent
treatment.

The MET signaling pathway has been well described and implicated in the
epithelial-mesenchymal transition (EMT) of tumor cells {[}34{]}. Thus,
c-Met has been investigated as a potential target to inhibit tumor
progression and metastasis. \emph{In vitro} studies utilizing miRNA to
inhibit c-Met have been successful in preventing cell proliferation,
migration and invasion {[}35, 36{]}. Cabozantinib, an inhibitor of
c-Met, has been investigated both in pre-clinical and clinical settings.
Fioramonti et al. showed that cabozantinib decreased OS cell
proliferation and migration through its effects on OS cells and their
microenvironment {[}37{]}. The French Sarcoma Group conducted a phase 2
combined clinical trial using cabozantinib in patients with advanced
Ewing sarcoma or OS, to assess efficacy both histologically and
radiographically {[}38{]}. Five of 42 patients (12\%; 95\% CI 4-26) with
OS had objective responses by 6 months; 14 of 42 patients (33\%; 95\% CI
20-50) had 6-month non-progression. They concluded that cabozantinib was
well tolerated and demonstrated anti-tumor effects, warranting further
investigation.

Vascular endothelial growth factor has been extensively reported in the
literature to be associated with poor prognosis in OS due to its
promotion of angiogenesis and metastasis {[}39-42{]}. Similar to the
previously discussed receptors, VEGF has been investigated as a
therapeutic target both \emph{in vitro} and clinically. Studies have
utilized a variety of miRNAs to inhibit the VEGF pathway and
successfully suppressed cell proliferation, invasion and angiogenesis in
standard OS cell lines {[}43-45{]}.

Grignani et al. conducted a non-randomized, phase 2 clinical trial
assessing the efficacy of sorafenib, an anti-VEGF antibody, and
everolimus in patients with unresectable high-grade OS that had
progressed despite standard chemotherapy treatment {[}46{]}. Of the 38
patients enrolled, 17 were progression free at six months (45\%; 95\% CI
28-61). They failed to demonstrate that treatment with sorafenib and
everolimus improved disease progression at six months, despite having a
small proportion of patients who were progression free. Navid et al.
completed phase 2 clinical trials to evaluate the role of bevacizumab as
an adjunct to standard OS treatment {[}47{]}. Thirty-one patients with
localized OS received bevacizumab and chemotherapy both pre- and
post-operatively. The estimated 4-year EFS and overall survival rate
were 57.5 +/- 10\% and 83.4 +/- 7.8 \%, respectively. They concluded
that while bevacizumab is a tolerable adjunctive therapy, the histologic
tumor responses and EFS did not support further investigation..

It is valuable to distinguish inhibiting a receptor and its associated
pathway from using a receptor as a means of targeting the expressing
cell. The former approach needs the pathway to be functional and
critical if the therapeutic measure is to have an impact. The latter
approach is pathway-independent and uses the receptor solely for
directing the therapeutic agent to the cell of interest. Targeting can
be accomplished using a variety of means, including radioimmunotherapy
and antibody-drug conjugates, both of which have been of interest in the
setting of OS. IGF2-R targeted radioimmunotherapy has been explored in
the preclinical arena and DS-8201 (trastuzumab deruxtecan), a HER-2
targeting antibody-drug conjugate, is currently being pursued by the
COG. While uniquely expressed receptors or receptor patterns are ideal,
consistent expression and overexpression may offer targeting
opportunities, independent of associated intracellular pathways. A
comprehensive understanding of a given osteosarcoma's surfaceome may
prove increasingly useful.

In this study, we validated the variable expression of six cell surface
receptors across a wide panel of patient-derived OS samples. We also
sought to establish what prognostic value these receptors could offer.
While our findings corroborate previous surface receptor expression
results, they do not appear to offer obvious prognostic utility.
Nevertheless, the frequent expression of most receptors across most
tumors raises the possibility that one or more could serve as a
therapeutic target.

This study is limited by several factors. The experimental environment
does not adequately recapitulate the human experience. \emph{In
vitro}tumors do not entirely reflect the \emph{in vivo} state. Moreover,
receptor expression was tested at a single point in time, assuming that
expression is stable over time. We utilized the
50\textsuperscript{th}percentile as a threshold for positivity,
recognizing that varying this cutoff could impact statistical results.
Lastly, we analyzed a small sample from a larger tumor that is known to
be genomically heterogeneous. Findings may be limited by sampling error,
yielding results that may not be representative of the whole tumor.

In summary, although the evaluated six cell surface receptors fail to
provide prognostic utility, they demonstrated variable expression across
a panel of patient-derived OS samples. This finding, taken together with
many prior publications, highlights the possibility of using one or more
of these receptors in a targeted therapeutic manner. Osteosarcoma's
genomic variability and high mutational burden makes it unlikely that a
single treatment will adequately address all relapsed, metastatic,
and/or chemo-resistant cases. One, or a combination, of the receptors
discussed may prove useful in future targeted approaches and further
investigation into such strategies is warranted.

\textbf{References}

1. Mirabello, L., R.J. Troisi, and S.A. Savage, \emph{International
osteosarcoma incidence patterns in children and adolescents, middle ages
and elderly persons.} Int J Cancer, 2009. \textbf{125} (1): p. 229-34.

2. Kaatsch, P., \emph{Epidemiology of childhood cancer.} Cancer Treat
Rev, 2010. \textbf{36} (4): p. 277-85.

3. Mirabello, L., R.J. Troisi, and S.A. Savage, \emph{Osteosarcoma
incidence and survival rates from 1973 to 2004: data from the
Surveillance, Epidemiology, and End Results Program.} Cancer,
2009.\textbf{115} (7): p. 1531-43.

4. Ferrari, S., et al., \emph{Neoadjuvant chemotherapy with high-dose
Ifosfamide, high-dose methotrexate, cisplatin, and doxorubicin for
patients with localized osteosarcoma of the extremity: a joint study by
the Italian and Scandinavian Sarcoma Groups.} J Clin Oncol,
2005.\textbf{23} (34): p. 8845-52.

5. Meyers, P.A., et al., \emph{Osteosarcoma: a randomized, prospective
trial of the addition of ifosfamide and/or muramyl tripeptide to
cisplatin, doxorubicin, and high-dose methotrexate.} J Clin Oncol,
2005.\textbf{23} (9): p. 2004-11.

6. Whelan, J.S., et al., \emph{EURAMOS-1, an international randomised
study for osteosarcoma: results from pre-randomisation treatment.} Ann
Oncol, 2015. \textbf{26} (2): p. 407-14.

7. Smeland, S., et al., \emph{Survival and prognosis with osteosarcoma:
outcomes in more than 2000 patients in the EURAMOS-1 (European and
American Osteosarcoma Study) cohort.} Eur J Cancer, 2019. \textbf{109} :
p. 36-50.

8. Hassan, S.E., et al., \emph{Cell surface receptor expression patterns
in osteosarcoma.} Cancer, 2012. \textbf{118} (3): p. 740-9.

9. Geller, D.S., et al., \emph{Targeted therapy of osteosarcoma with
radiolabeled monoclonal antibody to an insulin-like growth factor-2
receptor (IGF2R).} Nucl Med Biol, 2016. \textbf{43} (12): p. 812-817.

10. Karkare, S., et al., \emph{Detection and targeting insulin growth
factor receptor type 2 (IGF2R) in osteosarcoma PDX in mouse models and
in canine osteosarcoma tumors.} Sci Rep, 2019. \textbf{9} (1): p. 11476.

11. Akatsuka, T., et al., \emph{ErbB2 expression is correlated with
increased survival of patients with osteosarcoma.} Cancer,
2002.\textbf{94} (5): p. 1397-404.

12. Zhang, Q., et al., \emph{HER-2 expression in biopsy and surgical
specimen on prognosis of osteosarcoma: A systematic review and
meta-analysis of 16 studies.} Medicine (Baltimore), 2016.\textbf{95}
(23): p. e3661.

13. Gorlick, S., et al., \emph{HER-2 expression is not prognostic in
osteosarcoma; a Children's Oncology Group prospective biology
study.}Pediatr Blood Cancer, 2014. \textbf{61} (9): p. 1558-64.

14. Long, X.H., et al., \emph{Lapatinib alters the malignant phenotype
of osteosarcoma cells via downregulation of the activity of the
HER2-PI3K/AKT-FASN axis in vitro.} Oncol Rep, 2014. \textbf{31} (1): p.
328-34.

15. Rainusso, N., et al., \emph{Immunotherapy targeting HER2 with
genetically modified T cells eliminates tumor-initiating cells in
osteosarcoma.} Cancer Gene Ther, 2012. \textbf{19} (3): p. 212-7.

16. Ebb, D., et al., \emph{Phase II trial of trastuzumab in combination
with cytotoxic chemotherapy for treatment of metastatic osteosarcoma
with human epidermal growth factor receptor 2 overexpression: a report
from the children's oncology group.} J Clin Oncol, 2012.\textbf{30}
(20): p. 2545-51.

17. Pollak, M., \emph{The insulin and insulin-like growth factor
receptor family in neoplasia: an update.} Nat Rev Cancer,
2012.\textbf{12} (3): p. 159-69.

18. Buck, E., et al., \emph{Compensatory insulin receptor (IR)
activation on inhibition of insulin-like growth factor-1 receptor
(IGF-1R): rationale for cotargeting IGF-1R and IR in cancer.} Mol Cancer
Ther, 2010. \textbf{9} (10): p. 2652-64.

19. Li, Y.S., et al., \emph{The possible role of insulin-like growth
factor-1 in osteosarcoma.} Curr Probl Cancer, 2019. \textbf{43} (3): p.
228-235.

20. Wang, Y.H., et al., \emph{Increased expression of insulin-like
growth factor-1 receptor is correlated with tumor metastasis and
prognosis in patients with osteosarcoma.} J Surg Oncol,
2012.\textbf{105} (3): p. 235-43.

21. Zheng, S.W., et al., \emph{Leptocarpin Suppresses Proliferation,
Migration, and Invasion of Human Osteosarcoma by Targeting Type-1
Insulin-Like Growth Factor Receptor (IGF-1R).} Med Sci Monit,
2017.\textbf{23} : p. 4132-4140.

22. Chen, G., et al., \emph{MicroRNA-133a Inhibits Osteosarcoma Cells
Proliferation and Invasion via Targeting IGF-1R.} Cell Physiol Biochem,
2016. \textbf{38} (2): p. 598-608.

23. Liu, Y., et al., \emph{MiR-100 Inhibits Osteosarcoma Cell
Proliferation, Migration, and Invasion and Enhances Chemosensitivity by
Targeting IGFIR.} Technol Cancer Res Treat, 2016. \textbf{15} (5): p.
NP40-8.

24. Kuijjer, M.L., et al., \emph{IR/IGF1R signaling as potential target
for treatment of high-grade osteosarcoma.} BMC Cancer, 2013.\textbf{13}
: p. 245.

25. Avnet, S., et al., \emph{Insulin receptor isoform A and insulin-like
growth factor II as additional treatment targets in human
osteosarcoma.}Cancer Res, 2009. \textbf{69} (6): p. 2443-52.

26. Kolb, E.A., et al., \emph{R1507, a fully human monoclonal antibody
targeting IGF-1R, is effective alone and in combination with rapamycin
in inhibiting growth of osteosarcoma xenografts.} Pediatr Blood Cancer,
2010. \textbf{55} (1): p. 67-75.

27. Anderson, P.M., et al., \emph{A phase II study of clinical activity
of SCH 717454 (robatumumab) in patients with relapsed osteosarcoma and
Ewing sarcoma.} Pediatr Blood Cancer, 2016. \textbf{63} (10): p.
1761-70.

28. Uren, A., et al., \emph{Beta-platelet-derived growth factor receptor
mediates motility and growth of Ewing's sarcoma cells.} Oncogene,
2003.\textbf{22} (15): p. 2334-42.

29. Sulzbacher, I., et al., \emph{Platelet-derived growth factor-alpha
receptor expression supports the growth of conventional chondrosarcoma
and is associated with adverse outcome.} Am J Surg Pathol,
2001.\textbf{25} (12): p. 1520-7.

30. Sulzbacher, I., et al., \emph{Platelet-derived growth factor-AA and
-alpha receptor expression suggests an autocrine and/or paracrine loop
in osteosarcoma.} Mod Pathol, 2000. \textbf{13} (6): p. 632-7.

31. Kubo, T., et al., \emph{Platelet-derived growth factor receptor as a
prognostic marker and a therapeutic target for imatinib mesylate therapy
in osteosarcoma.} Cancer, 2008. \textbf{112} (10): p. 2119-29.

32. Yamaguchi, S.I., et al., \emph{Synergistic antiproliferative effect
of imatinib and adriamycin in platelet-derived growth factor
receptor-expressing osteosarcoma cells.} Cancer Sci, 2015.\textbf{106}
(7): p. 875-82.

33. Bond, M., et al., \emph{A phase II study of imatinib mesylate in
children with refractory or relapsed solid tumors: a Children's Oncology
Group study.} Pediatr Blood Cancer, 2008. \textbf{50} (2): p. 254-8.

34. Jeon, H.M. and J. Lee, \emph{MET: roles in epithelial-mesenchymal
transition and cancer stemness.} Ann Transl Med, 2017. \textbf{5} (1):
p. 5.

35. Li, Q., et al., \emph{MicroRNA-449b-5p Suppresses Proliferation,
Migration, and Invasion of Osteosarcoma by Targeting c-Met.} Med Sci
Monit, 2019. \textbf{25} : p. 6236-6243.

36. Xie, W., et al., \emph{MicroRNA-876-5p inhibits cell proliferation,
migration and invasion by targeting c-Met in osteosarcoma.} J Cell Mol
Med, 2019. \textbf{23} (5): p. 3293-3301.

37. Fioramonti, M., et al., \emph{Cabozantinib Affects Osteosarcoma
Growth Through A Direct Effect On Tumor Cells and Modifications In Bone
Microenvironment.} Sci Rep, 2018. \textbf{8} (1): p. 4177.

38. Italiano, A., et al., \emph{Cabozantinib in patients with advanced
Ewing sarcoma or osteosarcoma (CABONE): a multicentre, single-arm, phase
2 trial.} Lancet Oncol, 2020. \textbf{21} (3): p. 446-455.

39. Abdullah, S.E. and R. Perez-Soler, \emph{Mechanisms of resistance to
vascular endothelial growth factor blockade.} Cancer, 2012.\textbf{118}
(14): p. 3455-67.

40. Liu, Y., et al., \emph{High expression levels of Cyr61 and VEGF are
associated with poor prognosis in osteosarcoma.} Pathol Res Pract,
2017.\textbf{213} (8): p. 895-899.

41. Mohamed, F.E.A., E.Z.I. Khalil, and N.D.M. Toni, \emph{Caveolin-1
Expression Together with VEGF can be a Predictor for Lung Metastasis and
Poor Prognosis in Osteosarcoma.} Pathol Oncol Res, 2019.

42. Han, G., et al., \emph{Effects of vascular endothelial growth factor
expression on pathological characteristics and prognosis of
osteosarcoma.} Clin Exp Med, 2016. \textbf{16} (4): p. 577-584.

43. Lv, T., et al., \emph{miR-503 is down-regulated in osteosarcoma and
suppressed MG63 proliferation and invasion by targeting
VEGFA/Rictor.}Cancer Biomark, 2018. \textbf{23} (3): p. 315-322.

44. Yan, T., et al., \emph{MicroRNA944 targets vascular endothelial
growth factor to inhibit cell proliferation and invasion in
osteosarcoma.} Mol Med Rep, 2018. \textbf{18} (6): p. 5221-5228.

45. Zhang, L., et al., \emph{MicroRNA-134 inhibits osteosarcoma
angiogenesis and proliferation by targeting the VEGFA/VEGFR1
pathway.}FEBS J, 2018. \textbf{285} (7): p. 1359-1371.

46. Grignani, G., et al., \emph{Sorafenib and everolimus for patients
with unresectable high-grade osteosarcoma progressing after standard
treatment: a non-randomised phase 2 clinical trial.} Lancet Oncol,
2015.\textbf{16} (1): p. 98-107.

47. Navid, F., et al., \emph{A phase II trial evaluating the feasibility
of adding bevacizumab to standard osteosarcoma therapy.} Int J Cancer,
2017. \textbf{141} (7): p. 1469-1477.

\textbf{Legend}

\textbf{Table 1.} Summary of Antibodies and Their Respective Isotype
Antibodies (Autofluorescence)

\textbf{Table 2.} Raw Flow Cytometry Expression Data expressed in
Geometric Mean Fluorescent Intensity (MFI).

\textbf{Table 3.} Cell lines that are positive or negative for each
receptor.

\textbf{Table 4.} Number of Event Free Survival (EFS) events per patient
with respect to positive or negative receptors

\textbf{Table 5.} Number of Overall Survival events per patient with
respect to positive or negative receptors

\textbf{Table 6.} Hazard ratio analysis for EFS per cell surface
receptor

\textbf{Table 7.} Hazard ratio analysis for overall survival per cell
surface receptor

\textbf{Figure 1.} Fold change in receptor expression defined as
relative increase in expression relative to the corresponding negative
control

\textbf{Figure 2.} Receptor expression patterns assigned by geometric
mean fluorescent intensity (A) low expression pattern group (B) medium
expression pattern group (C) high expression pattern group

\textbf{Figure 3.} Total number of positive receptors per cell line
using the 50\textsuperscript{th} percentile as a cutoff for positivity.

\textbf{Supplementary Table 1.} Comparison between Hassan et al. and the
current study, demonstrating mean
geoMFI\textsubscript{positive}/geoMFI\textsubscript{negative} and
coefficient of variation (defined as standard deviation/mean) across all
six surface receptors.\selectlanguage{english}
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