Development of a Screening Array for Congenital Melanocytic Nevi
Alexander Valiga1, Daniel Widmer1, Thomas Biedermann2, Phil Cheng1, Reinhard Dummer1,
Mitchell Levesque1
1University
Hospital Zürich, Zürich, Switzerland, 2University Children’s Hospital Zürich, Zürich, Switzerland
Abstract
Methods
Previous studies have revealed a prevalence of mutations within the NRAS gene,
but additional genetic changes attributable to melanoma development from
congenital melanocytic nevi (CMN) remain unknown. Our laboratory has shown that
there exists a set of differentially expressed genes among melanoma and nevus
tissues, which may hold significant implications for understanding the development
of cancer from a previously benign, congenital lesion.
Paired'end)RNA'
sequencing)
Basic&Expression&Measured&via&RT4qPCR&
20&
Analysis)using))
)))))
15&
10&
DESeq)
VOOM)
5&
edgeR)
0&
Candidate)gene)
selec<on)based)
on)fold)change)
In the majority of pairwise comparisons between nevus and melanoma, the RTqPCR data was in concordance with the RNA-seq analysis. Of particular interest
were two validated genes. The first of these is shown to be up regulated in nevus
versus melanoma and is a member of a family of genes known to aid in the
inactivation of tumor suppressors such as p53. The other gene of interest, shown to
be down regulated in melanocyte versus nevus, is important in healthy melanocyte
development and has a well-characterized link with the tumor suppressor, p53.
>5&
>20&
Figure 2. Work flow of entire project from initial RNA sequencing analysis to
validation via RT-qPCR
Reference'
Genome'
Sequence'
Data'
So1ware'
Setup'
Sequence'Quality'
Checks'
2Bgroup'differen6al'
comparison'
like lympho-plasmocytic infiltrate with only a few dermal
melanophages. No atypical melanocytic proliferation was
Figure 1. Clinical manifestations of (A) giant congenital nevus and (B)
cutaneous melanoma as well as (C) Venn diagram depicting the number of
uniquely, differentially expressed genes among different tissue types
determined from initial RNA-seq analysis. While preliminary sequencing
yielded results for melanocyte samples in addition to nevus and melanoma,
variability in genetic expression during RT-qPCR analysis prompted this study to
focus our efforts on only nevus and melanoma samples.
Nevus&
Melanoma&(in&vitro)&
Melanoma&(in&vivo)&
Melanoma&(pa3ent)&
Gene&3&
1&
6.45&
6.99&
727.72&
Gene&6&
>1&
>73.98&
>0.16&
>20.58&
Figure 4. RT-qPCR derived expression for inversely expressed genes within
study. Of note was that validation revealed differences within same gene across
multiple tissue sources. Significant expression (p < 0.05) was seen in patient
melanoma samples when compared to nevus expression for both genes. Error
bars represent standard deviation of basic expression.
Feature'Coun6ng'
GLMBbased'differen6al'
comparisons'
Irina M rg ritescu et al.
638
Through next-generation RNA sequencing technology (RNA-seq), a set of genes
in this flow
part offor
theanalysis
lesion (Figure
3B). data
The final
accepted and
expected
the epidermis overlying Figure
a present
are shown to be differentially expressed across are
melanocyte,
nevus,
andinmelanoma
3. Work
of raw
obtained from paired-end RNA
diagnosis
was
completely
regressed
primary
cutaneous
congenital
melanocytic
nevus.
Step
sections
through
the
tissues. Alternative analysis of this sequencing data using various bioinformatics
sequencing. Adapted from Anders et al. Nature 2013
erythematous
part of the
lesion revealed a hypopigmented melanoma in association with a congenital melanocytic
techniques combined with validation of the acquired
data through
real-time
with loss
of genes
the retewhich
ridges,are
and a scar-like nevus, with nodal and cerebral metastasis (AJCC stage
quantitative PCR (RT-qPCR) analysis allows forepidermis
the selection
of the
fibroplasia
over a profile.
broad zone
theofpapillary and IV disease). The patient was referred to the oncologist
most indicative of a benign melanocytic or malignant
melanoma
This in
type
the reticular
dermis. There was and chemotherapy was initiated. He is still alive five
analysis paves the way for the establishment ofsuperficial
a custom part
array,ofwhich
would allow
vascularity
and a relatively abundant band- months after diagnosis.
for a patient’s tissue sample to be pre-screenedincreased
for cancerous
potential.
C"
>25&
Table 2. Differences across different melanoma tissue sources and their
respective p-values during RT-qPCR validation. Green coloring indicates
statistically significant result (p < 0.05) and red indicates an insignificant result.
Notable results include the differences between significance of gene expression in
in vitro and patient samples in Gene 3, 5, and 7.
Mapping'Reads'
The fact remains that these common mutations are not sufficient for a malignant
transformation, with only 5% of melanomas developing from melanocytic nevi
(Charbel et al., 2013). For example, NRAS and BRAF are frequently mutated within
nevi as well as primary and metastatic melanoma lesions. So far, present studies
have only determined that patients’ age as well as the size of their CMN are factors
that seem to play a part in progression from a benign lesion to melanoma. Thus, it is
clear that additional molecular effects are responsible for aberrant growth and
disease.
Conclusions and Future
Directions
>15&
Valida<on)by)384)
well)RT'qPCR)
array)
Congenital melanocytic nevi (CMN) are benign melanocytic tumors that exist at
birth. While not fully understood, it is believed that melanocytes, driven by cAMP
activity, proliferate to form these pigmented lesions (Setaluri and Rodriguez, 2014).
Furthermore, over 70% of medium to large CMN, developed in utero, possess
NRAS mutations, a genetic aberration that has been previously implicated in
melanoma development (Charbel et al., 2013). Through a series of genetic and
phenotypic changes, the cancer can then progress to a metastatic state at which
point typical survival is only 6-8 months after diagnosis (Hodi, 2010).
B"
Figure 6. Pathway analysis for genes found to be up-regulated in nevus
when compared to melanoma. Pathways related to both the immune response
as well as tumor suppressors were found to be most significant. All pathways
shown are significant (p < 0.05).
>10&
Introduction
A"
Results Cont.
25&
Preliminary experiments assessed gene expression of each tissue type though
RNA-sequencing (RNA-seq) and analyzing the resulting data by combining several
software packages in R. Validation of the differentially expressed genes was
confirmed via SYBR Green based RT- qPCR array. To allow for the most
representative validation, the same RNA samples used in the previous RNA-seq
study were used in the validation stage: nevus (n=4), melanoma (n=3). Also, an
additional number of nevus and melanoma RNA samples were harvested from both
solid tissue and cell culture sources, which allowed added confidence to the
validation result: nevus (n=8), melanoma (n=6).
Combinations of such genes would be excellent candidates to assess the overall
malignant potential of patients’ nevus tissue within the context of a future diagnostic
array.
Results Cont.
Results
The clinical features and histopathological findings
are summarized in Tables 1 and 2.
Target
Gene$1
Gene$2
Gene$3
Gene$4
Gene$5
Gene$6
Gene$7
Gene$8
p(value,from,RT(qPCR,Validation
in#vitro
in#vivo
patient
0.004
0.001
0.010
0.028
0.014
0.006
0.205
0.097
0.001
0.183
0.012
0.400
0.412
0.019
0.023
0.002
0.066
0.005
0.474
0.192
0.010
0.022
0.011
0.031
This study has shown that RT-qPCR is capable of acting as a validation platform
for preliminary results gathered via next generation, paired-end RNA-sequencing.
Analysis of RNA from different tissue sources (in vitro, in vivo, and patient)
demonstrate that gene expression differences can arise based on source of RNA.
Additional applications for RNA-sequencing data could be directed towards
examining single nucleotide variants among tissue types in order to create a better
diagnostic tool.
Future studies would involve growing fully human artificial skin on the back of
immunocompromised rats and induce nevi and melanoma growth, after which
gene knockdown could be used to determine a gene of interests’ biological
importance in transformation from nevus to melanoma.
Implications
This work demonstrates the importance of utilizing RT-qPCR to validate RNAsequencing results and solidifies the practice as an important step in the
interpretation of differentially expressed genes.
The seven genes currently validated during this study paves the way for future
validation of genes for use in a custom array that could be used to assess the
cancerous potential of skin lesions in a clinical setting.
References
Setaluri V and Rodriguez Cl. Arch Biochem Biophys. 2014 [Epub ahead of
print]
Charbel C et al. J Invest Dermatol. 2013. 134(4): 1067-74
Table 1. Comparison between selected target gene expression patterns
across tissue types as seen from RNA seq and RT-qPCR approaches.
Melanocytes were included during RNA sequencing but were abandoned during
RT-qPCR validation in favor of more clinically relevant nevus and melanoma
tissues.
Hodi FS et al. N Engl J Med. 2010 8(7): 645-654
Holderfield M et al. Nat Rev Cancer 2014 14(7): 455-467
Widmer DS et al. Pigment Cell Melanoma Res 2012 25(3): 343-353
Target
Gene$1
Gene$2
Gene$3
Gene$4
Gene$5
Gene$6
Gene$7
Gene$8
RNA*Sequencing*Result
Melanoma$>$Nevus$>$Melanocyte
Melanoma$>$Nevus$>$Melanocyte
Melanoma$>$Nevus$>$Melanocyte
Melanocyte$>$Nevus$>$Melanoma
Melanocyte$>$Nevus$>$Melanoma
Melanocyte$>$Nevus$>$Melanoma
Melanocyte$>$Nevus$>$Melanoma
Melanocyte$>$Nevus$>$Melanoma
RT3qPCR*Result
SAME
SAME
SAME
SAME
SAME
SAME
SAME
OPPOSITE
Anders S et al. Nat Protoc 2013 8(9): 1765-1786
Acknowledgements
This work was supported by grants from Drexel University as well as the
Whitaker International Program, which is a subsidiary of the Institute of
International Education
Figure 5. Pathway analysis for genes found to be up-regulated in melanoma
when compared to nevus. Several pathways vital to melanoma oncogenesis and
progression are listed above such as NRAS and those involved in EMT. All
pathways shown are significant (p < 0.05).