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\begin{document}

\title{Multi-institution analysis of tumor mutational burden and outcomes in
pediatric CNS tumor patients}



\author[1]{Rose Parisi}%
\author[1]{Roshal Patel}%
\author[2]{Gavrielle Rood}%
\author[3]{Acacia Bowden}%
\author[4]{George Turco}%
\author[5]{David Korones}%
\author[5]{Jeffrey Andolina}%
\author[6]{Melanie Comito}%
\author[4]{Matthew Barth}%
\author[7]{Lauren Weintraub}%
\affil[1]{Albany Medical College}%
\affil[2]{SUNY Upstate Medical University College of Medicine}%
\affil[3]{University of Rochester School of Medicine and Dentistry}%
\affil[4]{Roswell Park Comprehensive Cancer Center}%
\affil[5]{University of Rochester Medical Center}%
\affil[6]{SUNY Upstate Medical University Hospital}%
\affil[7]{Albany Medical Center Hospital}%


\vspace{-1em}



  
  \date{May 25, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
\textbf{Background:} Pediatric CNS tumors are the leading cause of
pediatric cancer mortality. Research addressing genomic biomarkers and
clinical outcomes is needed to inform therapeutic decision making.
\textbf{Methods}: We conducted a retrospective analysis of pediatric
patients (age \textless{}21) diagnosed with a primary CNS tumor at four
upstate New York hospitals from 2008 to 2021. Clinical and
histopathologic data were identified from each patient, including
genomic analysis of somatic mutations and tumor mutation burden (TMB)
where available. These variables were each compared with overall
survival using cox-regression analyses. Multivariable analysis was
conducted to identify patient characteristics that may independently
predict survival. \textbf{Results}: We identified 119 patients. Common
tumor types included low-grade glioma (N=51), high-grade glioma (N=29),
and medulloblastoma (N=11). Common driver-mutations included \emph{TP53}
inactivation (N=16), \emph{BRAF-KIAA1549} fusion (N=16), \emph{FGFR1}
amplification (N=12), \emph{BRAF V600E} mutation (N=12), \emph{NF1} loss
(N=12), and \emph{H3F3A K28M} mutation (N=6). Median TMB was 1
mutation/megabase (mut/Mb, range=0-132). Overall survival was 79.9\%.
Variables associated with poorer survival on univariable analysis were
higher TMB (p=0.002, HR 4.97), high grade tumors (p=0.009, HR 84.3), and
high-grade glioma histology (p=0.021, HR 3.14). Multivariable analyses
further identified TMB (p=0.011, HR 4.46) and high-grade histology
(p=0.015, HR 5.28) as independently predictive of worse survival. Tumor
progression was more common in high TMB (N=15, 44\%) than in low TMB
tumors (N=19, 35\%). \textbf{Conclusions}: High TMB is correlated with
higher rates of progression and death as compared to low TMB tumors.
These findings may help identify patients who may benefit from
alternative treatments, such as immunotherapies.%
\end{abstract}%



\sloppy


\textbf{Multi-institution analysis of tumor mutational burden and
outcomes in pediatric CNS tumor patients}

Rose Parisi MBA\textsuperscript{1}, Roshal R. Patel
MD\textsuperscript{1,2}, Gavrielle Rood BS\textsuperscript{3}, Acacia
Bowden BA\textsuperscript{4}, George Turco MD\textsuperscript{5}, David
N. Korones MD\textsuperscript{6}, Jeffrey R. Andolina
MD\textsuperscript{6}, Melanie Comito MD\textsuperscript{7}, Matthew
Barth MD\textsuperscript{5}, Lauren Weintraub MD\textsuperscript{8}

\textsuperscript{1}Albany Medical College, Albany, NY

\textsuperscript{2}Radiation Oncology, Memorial Sloan Kettering Cancer
Center, New York, New York

\textsuperscript{3}Upstate Medical University College of Medicine,
Syracuse, NY

\textsuperscript{4}University of Rochester School of Medicine,
Rochester, NY

\textsuperscript{5}Pediatric Hematology/Oncology, Roswell Park
Comprehensive Cancer Center, Buffalo, NY

\textsuperscript{6}Pediatric Hematology/Oncology, University of
Rochester Medical Center, Rochester, NY

\textsuperscript{7}Pediatric Hematology/Oncology, Upstate University
Hospital, Syracuse, NY

\textsuperscript{8}Pediatric Hematology/Oncology, Albany Medical Center,
Albany, NY

\textbf{Corresponding Author:}

Rose Parisi MBA

Albany Medical College

47 New Scotland Avenue, Albany, NY

parisir@amc.edu

518-441-9848

Abstract word count: {[} 249 words {]}

Main Text word count: {[} 2165 words {]}

Tables: 2

Figures: 2

Supporting Information Files: 0

Meeting abstract11The abstract for this manuscript was presented at the
International Symposium on Pediatric Neuro-Oncology Meeting 2022 and was
published in Neuro-Oncology 24(Supplement\_1):i153-i153.
DOI:10.1093/neuonc/noac079.566. June 2022.

\textbf{Short Running Title} : TMB as a predictor of outcomes in
pediatric CNS tumor patients

\textbf{Key Words} : Tumor mutational burden, driver mutation, survival,
pediatric, CNS tumors\selectlanguage{english}
\begin{longtable}[]{@{}ll@{}}
\toprule
\textbf{Abbreviation} & \textbf{Full Term}\tabularnewline
\midrule
\endhead
TMB & Tumor mutational burden\tabularnewline
DM & Driver mutation\tabularnewline
HGG & High grade glioma\tabularnewline
LGG & Low grade glioma\tabularnewline
ATRT & Atypical teratoid rhabdoid tumor\tabularnewline
DIPG & Diffuse intrinsic pontine glioma\tabularnewline
COSMIC & Catalogue of somatic mutations In cancer\tabularnewline
ICI & Immune checkpoint inhibitor\tabularnewline
EMR & Electronic medical record\tabularnewline
OS & Overall survival\tabularnewline
TTD & Time to death\tabularnewline
TTP & Time to progression\tabularnewline
\bottomrule
\end{longtable}

\textbf{Abstract:}

\textbf{Background:} Pediatric CNS tumors are the leading cause of
pediatric cancer mortality. Research addressing genomic biomarkers and
clinical outcomes is needed to inform therapeutic decision making.

\textbf{Methods} : We conducted a retrospective analysis of pediatric
patients (age \textless{}21) diagnosed with a primary CNS tumor at four
upstate New York hospitals from 2008 to 2021. Clinical and
histopathologic data were identified from each patient, including
genomic analysis of somatic mutations and tumor mutation burden (TMB)
where available. These variables were each compared with overall
survival using cox-regression analyses. Multivariable analysis was
conducted to identify patient characteristics that may independently
predict survival.

\textbf{Results} : We identified 119 patients. Common tumor types
included low-grade glioma (N=51), high-grade glioma (N=29), and
medulloblastoma (N=11). Common driver-mutations included
\emph{TP53}inactivation (N=16), \emph{BRAF-KIAA1549} fusion (N=16),
\emph{FGFR1}amplification (N=12), \emph{BRAF V600E} mutation (N=12),
\emph{NF1} loss (N=12), and \emph{H3F3A K28M} mutation (N=6). Median TMB
was 1 mutation/megabase (mut/Mb, range=0-132). Overall survival was
79.9\%. Variables associated with poorer survival on univariable
analysis were higher TMB (p=0.002, HR 4.97), high grade tumors (p=0.009,
HR 84.3), and high-grade glioma histology (p=0.021, HR 3.14).
Multivariable analyses further identified TMB (p=0.011, HR 4.46) and
high-grade histology (p=0.015, HR 5.28) as independently predictive of
worse survival. Tumor progression was more common in high TMB (N=15,
44\%) than in low TMB tumors (N=19, 35\%).

\textbf{Conclusions} : High TMB is correlated with higher rates of
progression and death as compared to low TMB tumors. These findings may
help identify patients who may benefit from alternative treatments, such
as immunotherapies.



\textbf{Introduction:}

Pediatric central nervous system (CNS) tumors are the leading cause of
pediatric cancer mortality.\textsuperscript{1} Historically, pediatric
CNS tumors were characterized by tumor location and histologic features.
With advances in next-generation sequencing, these data may better
inform tumor diagnosis and clinical decision
making.\textsuperscript{1,2}

Tumor mutational burden (TMB) is the total number of mutations per
megabase (mut/Mb) in a tumor's genetic coding
region.\textsuperscript{3}Driver mutations (DM) are specific mutations
that are thought to enable oncogenicity.\textsuperscript{4} TMB and DMs
have been studied across numerous cancer types as a means of risk
stratification.\textsuperscript{5} High TMB has been associated with
poor outcomes in adult diffuse glioma
patients.\textsuperscript{6}Multiple types of high TMB tumors have
demonstrated improved responses to immunotherapy.\textsuperscript{7}
More research is needed, especially in pediatric populations, to
identify ways in which TMB and DMs may be used as prognostic and
therapeutic determinants.\textsuperscript{8}

Patel et al. were among the first investigators to analyze TMB and DMs
in a large cohort of pediatric brain tumors patients. They provided
evidence that a high TMB subsets exists in pediatric brain tumor
patients and demonstrated a clear relationship between TMB and certain
types of DMs. For example, low TMB tumors had a higher incidence
of\emph{BRAF} alterations, whereas high TMB tumors had a higher
incidence of \emph{TP53} mutations.\textsuperscript{9}

The aim of this study is to identify specific patient and genomic
variables that may be associated with outcomes in pediatric brain
tumors. Specifically, we aim to determine the prognostic relevance of
TMB and identify potential populations that may benefit from the
addition of immunotherapy agents, including immune checkpoint inhibitors
(ICI).

\textbf{Methods:}

We conducted a multi-institutional retrospective analysis of all
pediatric patients \textless{}21 years with a primary diagnosis of a CNS
tumor, who had available histopathology data from 2008 to 2021 at 4
upstate New York hospitals. Institutional Review Board approval was
obtained from each respective institution; only de-identified data were
shared across institutions. Tumors were classified based on molecular
genetics and clinical features. DMs were determined based on Catalogue
Of Somatic Mutations In Cancer (COSMIC) database Tier 1 genes (genes
that are definitively implicated in cancer
development).\textsuperscript{10} Using COSMIC, the following mutations
were identified in our subset of patients as DMs:
\emph{TP53}inactivation, \emph{BRAF-KIAA1549} fusion, \emph{FGFR1}
amplification,\emph{BRAF V600E} mutation, \emph{NF1} loss and
\emph{H3F3A K28M}mutation. Patient demographics, clinical history, tumor
histopathology and genomics, treatments, and outcomes were obtained from
the electronic medical record (EMR). Specific genomic alterations and
TMB were identified using FoundationOne sequencing.

The prespecified primary analysis of this study was to compare TMB with
survival outcomes. High TMB ([?]3 mut/Mb) and low TMB (\textless{}3
mut/Mb) were stratified based on patient TMB distribution in our study
and also based on prior literature.\textsuperscript{11} Time to
progression (TTP) was defined as the days from date of diagnosis to
first clinical documentation of progression. Time to death (TTD) was
defined as the days from date of diagnosis to date of death. A cutoff
date of July 1, 2021, was used for survival calculations. Secondarily,
we sought to further characterize the genomics of pediatric patients
with CNS tumors.

Frequencies, means, medians and confidence intervals were used to
describe the patients, treatments, and genomics. Univariable
cox-regression analyses were conducted to assess the relationship
between patient/tumor characteristics and survival. Variables with
p\textless{}0.05 on univariable analysis were included in a
multi-variable cox-regression model. All analyses were performed via
SPSS Statistics, Version 28.0.1.1 (IBM Corp., Armonk, NY).

\textbf{Results:}

One hundred and nineteen patients (60 male, 59 female) with a median age
of 9 years (range 2 months-20 years) were diagnosed with a primary CNS
tumor at 4 upstate New York hospitals between 2008 and 2021 and had
FoundationOne testing (Table 1). There were 25 deaths observed (21\%),
median age at death was 13 years old (range 1.4 - 22 years). All death
events were in high-grade tumor patients. Overall survival was 79.9\%.

Tumor types included LGG (N=51, 43\%), HGG (N=29, 24\%), medulloblastoma
(N=11, 9\%), ependymoma (N=7, 6\%), ganglioglioma (N=4, 3\%), ATRT (N=4,
3\%), embryonal tumor (N=3, 3\%), choroid plexus (N=2, 3\%), DIPG (N=1,
1\%), and other CNS tumor types (N=7, 6\%). Seventy patients had DMs,
including \emph{TP53} inactivation (n=16, 13\%),
\emph{BRAF-KIAA1549}fusion (N=16, 13\%), \emph{FGFR1} amplification
(N=12, 10\%), \emph{BRAF V600E} mutation (N=12, 10\%), \emph{NF1} loss
(N=12, 10\%), and\emph{H3F3A K28M} mutation (N=6, 5\%).

TMB data was available for most patients (N=89, 75\%); median TMB was 1
mut/Mb (range=0-132). Low TMB was defined as \textless{}3 mut/Mb (N=55,
62\% of tumors with TMB available); high TMB was defined as [?]3 mut/Mb
(N=34, 38\% of tumors with TMB available) (Table 1). Two tumors (2\%),
HGG and medulloblastoma, had DNA methylation data. Patient outcomes were
categorized as progression (N=47, 40\%), stable disease or cure (N=45,
38\%), recurrence (N=29, 24\%), or death (N=25, 21\%) (Table 1).

High TMB tumors were most commonly HGG (N=11, 32\% of patients with high
TMB) and medulloblastomas (N=7, 21\%). Low TMB tumors were most commonly
LGG (N=30, 55\% of patients with low TMB), however also prevalent in
HGGs (N=11, 20\%) (Table 1). High TMB tumors were more commonly
identified in high-grade (N=26, 77\%) than low-grade (N=8, 24\%)
histologies. High TMB tumors were more likely to have a
\emph{TP53}inactivation (N=10, 29\%) as compared to low TMB tumors (N=3,
6\%).\emph{NF1} loss was similar amongst high TMB tumors (N=4, 12\%) and
low TMB tumors (N=5, 9\%). All other DMs were more likely to be in low
TMB tumors (Figure 1).

Patients with high TMB tumors were more likely to have a death event
(N=14, 41\%) as compared to patients with low TMB (N=5, 9\%) (Figure 2).
For patients with a death event and TMB data, the mean TTD was 25.8
months (range 3.27 months-15.5 years); patients with high TMB tumors had
a shorter TTD (mean=20.7 months) as compared to those with low TMB
(mean=3.3 years). Tumor progression was more common in high TMB (N=15,
44\%) than in low TMB tumors (N=19, 35\%) (Table 1). Mean TTP was 28.3
months (range 22 days-15.0 years). TTP was shorter in high TMB tumors
(mean=17.6 months) as compared to low TMB tumors (mean=30.3 months).

The majority of patients were treated with surgery (N=99, 83.2\%).
Patients were also treated with chemotherapy (N=77, 64.7\%), radiation
(N=56, 47.1\%), and/or targeted therapy (N=32, 26.9\%). Few patients
were treated with immunotherapy (N=3, 2.5\%), types included were
pembrolizumab, dendritic cell-based immunotherapy, and nivolumab; all
were used as second-line therapy following progression. High TMB tumors
were more frequently treated with systemic therapy (N=29, 85\%) compared
to low TMB tumors (N=38, 69\%) (Table 1). Most patients who were treated
with systemic therapy were treated initially at the time of diagnosis
(N=75, 87\%) rather than after tumor progression (N=11, 13\%).

Variables significantly associated with reduced OS on univariable
analysis were high TMB (p=0.002, HR=4.97, 95\% CI: 1.79-13.83), high
grade tumor (p=0.009, HR=84.3, 95\% CI: 3.05-2333), and HGG (p=0.021,
HR=3.14, 95\% CI: 1.19-8.26). Including these factors in a multivariable
model, high TMB (p=0.011, HR=4.46, 95\% CI: 1.40-14.15) and HGG
(p=0.015, HR=5.28, 95\% CI: 1.38-20.27) remained significantly
associated with reduced OS (Table 2).

There were no statistically significant differences in OS with respect
to age, gender, treatment modality (chemotherapy, surgery, radiation,
targeted therapy, or immunotherapy), the presence of an oncogenic DM, or
non-high-grade glioma histology (Table 2).

\textbf{Discussion:}

Previous studies have demonstrated a clear correlation between TMB and
DM in pediatric brain tumors.\textsuperscript{9} This
multi-institutional analysis assessed whether higher TMB tumors
correlate with outcomes in children with a broad range of brain tumors.
We summarized genomic characteristics of pediatric CNS tumors and
outcome data in 119 pediatric patients across 4 academic medical
institutions between 2008-2021. We report a clear link between higher
TMB and worse outcome. Higher TMB was a significant and independent
predictor of reduced OS. Death events and tumor progression were more
common in high TMB tumors as compared to low TMB tumors; high TMB tumors
also had shorter TTD and TTP. These represent novel findings in
understanding the genomics as they relate to outcomes in pediatric CNS
tumors.

TMB and outcomes have previously been studied in many adult, and some
pediatric, tumors. TMB has not always correlated to OS; there are wide
ranges of solid tumor types and data has been
inconsistent.\textsuperscript{5} TMB has been associated with shorter OS
in adult patients with gliomas, BRCA1 or BRCA2 mutated high-grade serous
ovarian cancer, and lung cancer. Worse outcomes in high TMB tumors are
likely attributed to mutations that inhibit cell cycle checkpoints and
DNA repair mechanisms, leading to high proliferative
activity.\textsuperscript{6,9,12,13} These mutations contribute to more
severe and rapid metastatic disease in high TMB
tumors.\textsuperscript{6} Our data further demonstrates poor
prognostication of TMB.\textsuperscript{6,14,15} Poorer outcomes may
also be indicative of inadequate treatment options for this high-risk
pediatric CNS tumor patient subset.

Similar to data presented by Patel et al., high TMB tumors in this
analysis were more likely to have a \emph{TP53} inactivation and low TMB
tumors were more likely to have a
\emph{BRAF}mutation.\textsuperscript{9} Patel et al., postulated this
was because\emph{TP53} inactivation causes an inability to repair DNA
mutations and\emph{BRAF} has a minimal effect on DNA
repair.\textsuperscript{9}\emph{TP53} inactivation is likely associated
with high TMB tumors given its facilitation of a multi-step malignant
progression.\textsuperscript{16} The current data further demonstrates
that high TMB tumors often do not have driver mutations that can be
therapeutically targeted; identifying a need for alternative therapies.

Although most high TMB tumors in our dataset were treated with systemic
therapy, only a small fraction of patients were treated with targeted or
immunotherapy. Targeted and immunotherapy may not have had a significant
association with survival because such therapies were most commonly used
second-line, post-tumor recurrence or progression; this is true for all
three patients who received immunotherapy in our study. Literature
supports that first-line immunotherapy may have better outcomes than
when immunotherapy is used as second-line; the hypothesis being that
upfront chemotherapy may destroy the host immune system, decreasing the
efficacy of subsequent immunotherapy.\textsuperscript{17} A lack of
statistical significance may also be due to low sample size. The use of
ICIs may be indicated for such patients, given our findings that high
TMB tumors are more likely to be associated with loss of tumor
suppressor genes and less likely to be associated with oncogene
mutations.

Furthermore, TMB is a biomarker for ICI enrollment; TMB has been found
to predict ICI response in 20-60\% of
patients.\textsuperscript{3,7,18-21} High TMB (\textgreater{}3 mut/Mb)
has also been demonstrated to predict improved progression-free survival
in patients on ICI.\textsuperscript{11} Although TMB has been associated
with worse survival, tumors with high TMB tumors are often extremely
responsive to ICI therapy. Additionally, high TMB tumors associated with
poor OS were found to have improved OS with ICI when compared to low TMB
tumors. These responses have been demonstrated in non-small cell lung
cancer, malignant melanoma, cervical cancer, breast cancer, gastric,
esophageal and head and neck cancers.\textsuperscript{18,19,22-24} In
pediatrics, however, responses have been inconsistent, possibly because
of the relatively low TMB of pediatric cancers.\textsuperscript{25,26}

There are over 2,000 clinical trials investigating ICI in patients of
all ages and with all tumor types (accessed June 2022). Of the 141
trials investigating ICI in pediatric patients, five of which have or
are currently investigating ICI in pediatric CNS tumor
patients.\textsuperscript{27-31} Only one trial, specifically recruits
pediatric patients with high TMB CNS and solid tumors to analyze the
effect of ICI.\textsuperscript{28} Pembrolizumab has been approved for
high TMB solid tumors, including pediatric CNS tumors with PD-L1
expression.\textsuperscript{32} In a post-hoc analysis of the HERBY
trial, hypermutated pediatric HGGs treated with bevacizumab (anti-VEGF)
had significantly more CD8+ tumor-infiltrating lymphocytes and improved
OS as compared to non-hypermutated types.\textsuperscript{33} This
analysis supports that bevacizumab may be a treatment option for
pediatric CNS tumor patients with high TMB and poor outcomes in need of
more effective treatment regimens. It also emphasizes the importance of
understanding tumor microenvironment as a means of further stratifying
patients, which may be a future direction for
studies.\textsuperscript{34}

Our multi-institutional analysis shows a clear correlation between
higher TMB and poor outcomes for children with brain
tumors\textbf{.}Although variables were standardized, discrepancies may
exist in data collection amongst institutions. Additionally, DNA
methylation profiling has increasingly been used for pediatric CNS tumor
classification.\textsuperscript{2,35,36} Only two patients in our
dataset had DNA methylation profiling and only 75\% of patients had TMB
data. In addition, the brain tumor tissue obtained at these institutions
was not routinely sent to FoundationOne for TMB testing for all children
so it is possible our sample is not representative of all children with
brain tumors. We recommend an increase in TMB and DNA methylation
testing, as both may be applicable toward stratifying treatments and
also used to improve research and treatment developments in the
future.\textsuperscript{2} Lastly, although our analyses were
pre-determined prior to data collection, results should be interpreted
in the context of the retrospective nature of this study.

We identify pediatric CNS high TMB tumor patients as a unique high-risk
patient subset that has poor outcomes: higher progression rates and
poorer overall survival. Our data may help in identifying such patients
who may require alternative treatments, such as ICI.

\textbf{Conflict of Interest Statement:} All authors have no conflicts
of interest to disclose.

\textbf{Acknowledgements} : This study was supported in part by Albany
Medical Center Children's Hospital Grant, Albany, NY, 2021.



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\textbf{Figure Legends:}

\textbf{Figure 1.} Driver mutations in pediatric CNS tumor patients
characterized by proportion of high vs. low tumor mutational burden
(TMB) tumors.

\textbf{Figure 2.} Overall survival of pediatric CNS tumor patients
reported as time from diagnosis to last follow-up or death event with
the last date of data collection being July 1 2021 (p=0.002) .\selectlanguage{english}
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\includegraphics[width=0.70\columnwidth]{figures/Figure2/Figure2}

\end{center}
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\textbf{Hosted file}

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