International Journal of
Comprehensive Mutational and Phenotypic
Characterization of New Metastatic Cutaneous
Squamous Cell Carcinoma Cell Lines Reveal Novel
Jay Perry 1,2,3 , Bruce Ashford 1,2,3,4,5 , Amarinder Singh Thind 2,5 , Marie-Emilie Gauthier 6,
Elahe Minaei 1,2,3 , Gretel Major 1, 2, †, Narayanan Gopalakrishna Iyer 7, Ruta Gupta 4,8,
Jonathan Clark 4and Marie Ranson 1,2,3,4,*
1Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong,
Wollongong, NSW 2522, Australia; firstname.lastname@example.org (J.P.); email@example.com (B.A.);
firstname.lastname@example.org (E.M.); email@example.com (G.M.)
2Illawarra Health & Medical Research Institute, Wollongong, NSW 2522, Australia; firstname.lastname@example.org
3CONCERT Translational Cancer Research Centre, Liverpool, NSW 2170, Australia
4Sydney Head and Neck Cancer Institute, Chris O’Brien Lifehouse, Camperdown, NSW 2050, Australia;
email@example.com (R.G.); firstname.lastname@example.org (J.C.)
5School of Medicine, University of Wollongong, Wollongong, NSW 2522, Australia
6Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research,
Darlinghurst, NSW 2010, Australia; email@example.com
7Department of Surgical Oncology, National Cancer Centre Singapore, Singapore 169610, Singapore;
8Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital,
NSW Health Pathology, Camperdown, NSW 2050, Australia
*Correspondence: firstname.lastname@example.org; Tel.: +61-2-4221-3291
†Current address: Department of Orthopaedic Surgery and Musculoskeletal Medicine, University of Otago,
Christchurch 8140, New Zealand.
Received: 3 November 2020; Accepted: 3 December 2020; Published: 15 December 2020
Cutaneous squamous cell carcinoma (cSCC) is a common skin cancer. Most patients who
develop metastases (2–5%) present with advanced disease that requires a combination of radical
surgery and adjuvant radiation therapy. There are few eﬀective therapies for refractory disease.
In this study, we describe novel patient-derived cell lines from cSCC metastases of the head and
neck (designated UW-CSCC1 and UW-CSCC2). The cell lines genotypically and phenotypically
resembled the original patient tumor and were tumorogenic in mice. Diﬀerences in cancer-related
gene expression between the tumor and cell lines after various culturing conditions could be largely
reversed by xenografting and reculturing. The novel drug susceptibilities of UW-CSCC1 and an
irradiated subclone UW-CSCC1-R to drugs targeting cell cycle, PI3K/AKT/mTOR, and DNA damage
pathways were observed using high-throughput anti-cancer and kinase-inhibitor compound libraries,
which correlate with either copy number variations, targetable mutations and/or the upregulation of
gene expression. A secondary screen of top hits in all three cell lines including PIK3CA-targeting drugs
supports the utility of targeting the PI3K/AKT/mTOR pathway in this disease. UW-CSCC cell lines
are thus useful preclinical models for determining targetable pathways and candidate therapeutics.
cSCC; metastasis; skin cancer; PI3K; WGS; ultraviolet; cancer; cell culture; xenograft;
Int. J. Mol. Sci. 2020,21, 9536; doi:10.3390/ijms21249536 www.mdpi.com/journal/ijms
Int. J. Mol. Sci. 2020,21, 9536 2 of 16
Cutaneous squamous cell carcinoma (cSCC) is a common non-melanoma skin cancer and the
most common malignancy worldwide [1,2]. Primary cSCC is typically treatable, although in 2–5% of
cases metastatic spread occurs [
], resulting in the majority of disease-speciﬁc deaths. Other than
surgery and radiotherapy, the only systemic therapy approved for locally advanced and metastatic
cSCC is Cemiplimab immunotherapy, which resulted in a 50% response rate and was associated with
adverse events [9,10].
Recent eﬀorts are helping to identify the biological processes underpinning the tumorigenesis
and metastasis of cSCC [
]. However, candidate biomarkers and therapeutics have seldom been
examined in pre-clinical models of metastatic disease. Cell lines remain powerful pre-clinical tools
to study biological behavior, as well as being amenable to high-throughput drug screening [
Cell lines derived from primary cSCC have been reported [
], but there are few cell lines derived
from metastatic cSCC (Table S1). The metastatic cell lines UT-SCC7, UT-SCC59A, and UT-SCC115 have
not been validated molecularly, nor has evidence of tumorigenicity been published. This is also the
case for an undesignated metastatic cSCC cell line recently developed [
]. MET4 and IC1MET form
tumors in mice but phenotypic comparisons to their originating tumors are limited. The mutational
proﬁle of IC1MET was, however, analyzed by whole-exome sequencing and shown to be comparable to
its originating tumors [
]. Regardless, there is a need for additional high-ﬁdelity models of metastatic
cSCC to cover the mutational spectrum observed between patients.
In this current study, we report the establishment of novel patient-derived cSCC cell cultures from
nodal metastases, designated UW-CSCC1 and UW-CSCC2. The originating tumors and
derivatives underwent whole-genome sequencing (WGS), gene expression analysis, and other
phenotypic analyses to characterize the ﬁdelity of the cell lines and the implications of these ﬁndings
for therapeutic investigations. The beneﬁts of these cell lines are shown through high-throughput
screening of anti-cancer molecules, revealing candidate therapeutics for this disease.
2.1. Phenotypic Validation of Novel Cell Lines from Patients with Metastatic cSCC
Long-term continuous cell lines were established from parotid node metastases from two
patients (Table S2), designated UW-CSCC1 and UW-CSCC2. To model changes that may be
incurred by tumor cells that survive radiation therapy, an irradiated sub-clone was expanded from
passage 13 UW-CSCC1, designated UW-CSCC1-R. The doubling times of UW-CSCC1, UW-CSCC1-R,
and UW-CSCC2 as monolayers were 47, 36, and 82 h, respectively. Morphologically, UW-CSCC1-R
appeared more mesenchymal-like compared to UW-CSCC1 (Figure 1a,b). The UW-CSCC2 were
morphologically dissimilar to UW-CSCC1/1-R, demonstrating rounder borders and a smaller diameter
(Figure 1c). UW-CSCC1 and UW-CSCC2 produced tight spheres in ultralow binding plates within
48 h, whereas UW-CSCC1-R only formed aggregates (Figure 1d–f).
All cell lines stained positive for the epithelial marker CK-5 (Figure 1g–i), but were negative
for the mesenchymal markers
-SMA and vimentin (data not shown), conﬁrming their epithelial
purity. UW-CSCC1 and UW-CSCC1-R demonstrated invasion using an organotypic assay (Figure 1j,k).
UW-CSCC2 was not assessed in this assay. The tumorigenicity of UW-CSCC1 and UW-CSCC2 was
conﬁrmed by xenografting in NOD scid gamma immunocompromised mice. Tumors arose at the site of
inoculation within three months and largely retained the tissue architecture of the clinical specimen
(Figure 1l–o), including unequivocal squamous epithelial cell morphology and malignant cytological
features (Figure 1l inset).
Int. J. Mol. Sci. 2020,21, 9536 3 of 16
Tumor and cell line characterization by microscopy. Photomicrographs (10
cell lines grown in (
) monolayer (2D) culture or (
) spheroid (3D) cultures. Immunocytochemical
) of cell lines stained with CK-5 antibody (green): nuclei stained with RedDot2
(red). Organotypic assays showing UW-CSCC1 (
) and UW-CSCC1-R (
) directional invasion into
ﬁbroblast contracted collagen I matrices at eight days after being placed onto an air–liquid interface.
Representative micrographs of hematoxylin and eosin (H&E)-stained sections (n=3 matrices).
objective. Dotted—Patient 1 and (
) UW-CSCC1 xenotransplant in NSG mouse or
) clinical tumor from Patient 2 and (
) UW-CSCC2 xenotransplant in NSG mouse. Enlarged inset
panel (l) highlights polyploidy. Arrow heads denote papilliform architecture.
2.2. Genotypic Validation of Novel Cell Lines from Patients with Metastatic cSCC
The genomic characteristics of parent tumors and cell lines analyzed by whole genome sequencing
are summarized in Figure 2a–e. The low levels of variant detection for the Patient 2 tumor (Figure 2d)
were likely a result of the low tumor cellularity of the sample taken for DNA extraction, as conﬁrmed
after WGS (14% by Purple analysis; Table S2), and thus could not be compared genomically to
its corresponding cell line UW-CSCC2. Major structural variation was present in UW-CSCC2,
including deletions, ampliﬁcations, inversions and translocations (Figure 2e), similar to that observed
for the Patient 1 tumor and its derived cell line (Figure 2a–c).
The structural variation patterns (copy number gains and losses and minor allele copy number)
were well conserved between UW-CSCC1/1-R and the originating tumor (Figure 2a–c), with the
exception of some UW-CSCC1-R-speciﬁc reductions in minor allele copy number present in
chromosomes 9 and 11. The UV-associated (C >T) mutational signature was conserved in the
cell lines (Figure 2f), accounting for >70% of small nucleotide variants (SNVs) across all samples.
Some discordance was evident with respect to signature 7c and signature 58 between the various cell
lines and Patient 1 tumor.
The numbers of SNVs in the non-coding regions were similar between the samples, despite some
additional variants in the cell lines (Figure 2g). The up- and down-stream 2 kbp regions were analyzed
more discretely, revealing a similar pattern of ﬁdelity (Figure S1), which has implications for gene
transcription. A detailed analysis of the coding variants in the Patient 1 tumor, its associated cell
lines and UW-CSCC2 identiﬁed 6518 exonic SNVs across 4335 genes (Figure S2a,b). Most of these
mutations functionally relate to poly(A) RNA binding (Figure S2c). In the Patient 1 tumor and related
cell lines, a substantially higher number of variants was observed compared to UW-CSCC2. Of the
2992 genes featuring exonic variants in the Patient 1 tumor, 2924 (97.73%) were shared with matched
cell lines UW-CSCC1 and UW-CSCC1-R (Figure S2d). A further 165 aﬀected genes were identiﬁed and
Int. J. Mol. Sci. 2020,21, 9536 4 of 16
shared between UW-CSCC1 and UW-CSCC1-R only. Either this reﬂects new mutations or, more likely,
it demonstrates the increased purity in the cell lines, facilitating greater variant calling conﬁdence.
There were 35 and 56 genes containing exonic variants exclusive to UW-CSCC1 and UW-CSCC1-R,
respectively. The majority (>97.5%) of the exclusive variants in UW-CSCC1-R were silent or missense
SNVs. Others included a frameshift truncation in PDGFRL and a stop-gained variant in DYNLL1
(Figure S2d). Moreover, the highest SNVs variance was observed in AHNAK2,AHNAK,MUC12,
and KMT2C across the Patient 1 tumor, UW-CSCC1 and UW-CSCC1-R (Figure S2e).
Genomic landscape of cell lines and matched tumors. Circos plots showing overall pattern
of genetic aberrations between (
) the tumor of Patient 1 and matched cell lines, (
) UW-CSCC1 and
) UW-CSCC1-R; or (
) the tumor of Patient 2 and the matched cell line (
) UW-CSCC2. The layers
indicate the following (going from outside in): (i) chromosomes, with the darker shaded areas
representing large gaps in the reference genome due to regions of centromeres, heterochromatin,
and missing short arms; (ii) the purity-adjusted allelic frequency of all observed SNV (including introns
and intergenic regions); (iii) all observed copy number changes; with losses indicated in red and copy
number gain shown in green; (iv) the minor allele copy number (minor allele losses are indicated in
orange, whilst blue shows regions of minor allele gain); (v) the observed structural variants within or
between the chromosomes (translocations are indicated in blue, deletions in red, insertions in yellow,
tandem duplications in green and inversions in black). (
) Mutational signature frequency of cell lines
and tumor from Patient 1. (
) Total number of non-coding variants detected amongst patient 1 tumor,
UW-CSCC1, and UW-CSCC1-R. The unique non-coding SNV speciﬁc to each sample is overlain.
Of the 1309 known oncogenes, tumor suppressor genes or cancer-associated genes previously
examined for somatic variation in a wider group of 15 cSCC lymph node metastases, which included
the parent tumor for UW-CSCC1/1-R [
], 60 genes shared short variants between UW-CSCC1/1-R
and UW-CSCC2 (Table S3). Of these 60 genes, the Patient 1 tumor and its cell lines, along with
UW-CSCC2, showed similar alterations across seven drug-targetable genes (Figure 3). Not surprisingly,
TP53 inactivating mutations were common across these cell lines (and the lymph node metastases,
Table S3), suggesting susceptibility to DNA-damaging drugs. While NOTCH1 mutations often
occur concomitantly with TP53 in cSCC [
], this was not evident in the Patient 1 tumor and its
derivative cell lines (Figure 3). Further, the Patient 1 tumor, its derivative cell lines and UW-CSCC2
all harbored copy number ampliﬁcations in genes of the PI3K/mTOR signaling pathway (Table S4),
Int. J. Mol. Sci. 2020,21, 9536 5 of 16
as well as mutations in AKT3 (Figure 3), supporting this as a key targetable pathway in metastatic
cSCC. Altogether, this suggests that as these cell lines share several targetable alterations in cancer
driver genes, they are thus broadly representative of the metastatic cSCC of the head and neck in the
context of drug susceptibility testing.
Recurrent coding short nucleotide variants of druggable targets shared across Patient 1
tumor, UW-CSCC1/-R and UW-CSCC2. Stop-gained and missense variants are considered high- and
medium-impact, respectively. Synonymous variants are considered low impact. Refer to Supplementary
Dataset 1 for detailed variant information.
2.3. Eﬀect of In Vitro Culture on Cancer Gene Expression Patterns
The unbiased clustering analysis of gene expression from the nCounter panels separated the
Patient 1 tumor-derived
cell lines from
(patient tumor and xenograft) samples (Figure 4).
Of the various
conditions tested, passage number resulted in the most impact, with low
passage number separating UW-CSCC1 away from the cells under the other
(i.e., high passage, irradiated, normoxic and spheroid), which otherwise exhibited very similar pathway
score proﬁles. Indicators of stemness and DNA damage repair were upregulated in UW-CSCC1-R
relative to UW-CSCC1 (Figure S3a,b). Cell adhesion gene set expression was mostly downregulated in
UW-CSCC1-R (Figure S3c), which was reﬂected physiologically in the inability of UW-CSCC1-R to
form tight spheroids compared to UW-CSCC1.
Many pathways’ gene set expressions under
conditions were downregulated relative
samples, with diﬀerences between xenograft samples and the Patient 1 tumor evident
only for a subset of pathways in the PanCancer progression analysis (Figure 4a). In the PanCancer
pathways analysis, the gene set expression in all biological categories was very similar between the
xenograft and the Patient 1 tumor (Figure 4b). A comparison of the overall gene expression of a very
early passage of xenograft-derived UW-CSCC1 (Xenograft 2
UW-CSCC1 cell line) to the xenograft
(Figure 4a) revealed similar pathway score proﬁles.
Int. J. Mol. Sci. 2020,21, 9536 6 of 16
Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 6 of 17
Figure 4. Cancer gene expression analysis. (a) nCounter PanCancer progression and (b) nCounter
Pancancer pathways panel gene expression pathway score profiles for Patient 1 and UW-CSCC1
culture derivatives. Nanostring heatmaps showing how pathway scores (fit using the first principal
component of each gene set’s data) change across samples or culture conditions. Pathway scores
condense each sample’s gene expression profile into a small set of pathway scores. Orange indicates
high scores; blue indicates low scores, i.e., samples that exhibit similar pathway score profiles. Scores
are displayed on the same scale via a Z-transformation. Sample details including passage number are
provided in Table S5.
2.4. High-Throughput and Secondary Drug Screens Reveal Novel Therapeutic Targets in Metastatic cSCC
The novel drug susceptibilities of UW-CSCC1 and UW-CSCC1-R were identified using single-
dose anti-cancer compounds and kinase inhibitor screening libraries. The top 40 most efficacious
drugs for both libraries, along with their respective targets, are listed in Tables S5.1–S5.4. Both
libraries demonstrated a bimodal distribution, partitioning the majority of tested compounds as
either ineffective or highly effective at 1 µM (Figure 5a,b). Between the cell lines there was a strong
and moderate positive correlation for the anti-cancer and anti-kinase drug response, respectively.
The majority of the effective drugs (with > 70% inhibition) in the anti-cancer library targeted cell cycle,
cytoskeletal signaling, DNA damage, as well as protease pathways (Tables S6.1–S6.2). Efficacious
compounds included topoisomerase or cyclin-dependent kinase (CDK) inhibitors. The highly
efficacious compounds in the kinase-inhibitor library largely pertained to targeting the cell cycle
(particularly via CDKs), the cytoskeleton, or the PI3K/Akt/mTOR pathways (Tables S6.3–S6.4) in both
Cancer gene expressionanalysis. (
) nCounter PanCancer progression and
(b) nCounter Pancancer
pathways panel gene expression pathway score proﬁles for Patient 1 and UW-CSCC1 culture derivatives.
Nanostring heatmaps showing how pathway scores (ﬁt using the ﬁrst principal component of each
gene set’s data) change across samples or culture conditions. Pathway scores condense each sample’s
gene expression proﬁle into a small set of pathway scores. Orange indicates high scores; blue indicates
low scores, i.e., samples that exhibit similar pathway score proﬁles. Scores are displayed on the same
scale via a Z-transformation. Sample details including passage number are provided in Table S5.
2.4. High-Throughput and Secondary Drug Screens Reveal Novel Therapeutic Targets in Metastatic cSCC
The novel drug susceptibilities of UW-CSCC1 and UW-CSCC1-R were identiﬁed using single-dose
anti-cancer compounds and kinase inhibitor screening libraries. The top 40 most eﬃcacious drugs
for both libraries, along with their respective targets, are listed in Tables S5.1–S5.4. Both libraries
demonstrated a bimodal distribution, partitioning the majority of tested compounds as either ineﬀective
or highly eﬀective at 1
M (Figure 5a,b). Between the cell lines there was a strong and moderate positive
correlation for the anti-cancer and anti-kinase drug response, respectively. The majority of the eﬀective
drugs (with >70% inhibition) in the anti-cancer library targeted cell cycle, cytoskeletal signaling,
DNA damage, as well as protease pathways (Tables S6.1–S6.2). Eﬃcacious compounds included
topoisomerase or cyclin-dependent kinase (CDK) inhibitors. The highly eﬃcacious compounds
in the kinase-inhibitor library largely pertained to targeting the cell cycle (particularly via CDKs),
the cytoskeleton, or the PI3K/Akt/mTOR pathways (Tables S6.3–S6.4) in both cell lines.
Given the response to the PI3K inhibitor PIK-75 and the associated gene alterations in the
PI3K/AKT/mTOR pathway in all three cell lines, a secondary dose-response screen was performed
to elucidate IC
values. The UW-CSCC1 and UW-CSCC1-R sensitivity to PIK-75 did not diﬀer
substantially, with IC
values being 0.122
M and 0.204
M, respectively. PIK-75 was
more potent against UW-CSCC2 compared to the other cell lines, exhibiting an IC
0.026 ±0.012 µM.
The dual PI3K/mTOR-targeting compound dactolisib was also strongly potent against the cell lines.
The inhibition of pAKT was observed with UW-CSCC1 and UW-CSCC1-R in response to IC
concentrations of PIK-75 and dactolisib, and the total AKT expression seemingly reduced in a
time-dependent manner (Figure 5d). IC
values for other common chemotherapeutics against the
cell lines are provided in Table 1for comparison. Of note, UW-CSCC2 appears to be more resistant
than UW-SCC1/1-R to carboplatin, which may reﬂect its dual TP53/NOTCH1 high impact mutations
(refer to Figure 3).
Int. J. Mol. Sci. 2020,21, 9536 7 of 16
Drug screen response of UW-CSSC1/1-R. Overall distribution of percentage inhibition is shown
for the anti-cancer (
) and kinase-inhibitor (
) libraries. Negative inhibition implies a pro-proliferative
event has occurred. Lines of best ﬁt and coeﬃcients of determination are shown. (
) Heatmap showing
the relative viability eﬀect on the cell lines of the topmost eﬀective PI3K/AKT/mTOR inhibitors.
) Western blots demonstrating total AKT and phosphorylated AKT (pAKT) levels in response to
pretreatment with the respective IC
value of the PI3K inhibitors PIK-75 or Dactolosib for the times
shown for both cell lines. The housekeeping gene GAPDH was used as a total protein loading control.
The densitometry analysis shows the ratios of pAKT/total AKT for each treatment.
values of chemotherapeutic agents against UW-CSCC1 and UW-CSCC2. Compounds are
listed in order of lowest IC
presented either as a mean or mean
standard error of the mean (SEM)
from >2 independent experiments each performed in triplicate.
Compound Drug Class UW-CSCC1 UW-CSCC1-R UW-CSCC2
Dactosilib Dual PI3K/mTOR inhibitor 0.022 ±0.003 0.080 ±0.023 0.028 ±0.012
PIK-75 PI3K inhibitor 0.122 ±0.012 0.204 ±0.05 0.026 ±0.012
Antimetabolite 4.47 ±0.4 7.56 ±0.1 -
†Platinum analogue 22.40 22.90 200.00
†Compound not present in HTS drug screen.
This is the ﬁrst study to apply WGS and expression analysis on metastatic cSCC cell lines,
and to correlate those ﬁndings with small molecule drug responsiveness. Our results show that the
predominance of cSCC tumors and UV-associated mutation signature 7 are retained in the
cell lines. UW-CSCC1 almost completely retained the mutational landscape of the clinical tumor,
as has been witnessed in other cell lines [
], suggesting that genetic drift is minimal following 2D
culture. The additional coding and non-coding variants called in UW-CSCC1/1-R are not explicit
evidence of genetic drift, but rather a result of the culture purity enhancing variant detection through
the elimination of the stromal background. Adjustments in copy number were to be expected given
Int. J. Mol. Sci. 2020,21, 9536 8 of 16
that they are generally seen to be in greater numbers in cell lines [
]. The identiﬁcation of SNVs
and CNVs among the cell lines pertaining to the PI3K/AKT/mTOR pathway builds upon previous
], supporting its prognostic utility, as well as being an indicator of therapeutic
responsiveness to corresponding selective inhibitors, as assessed by our compound screening.
The downregulated cancer gene expression proﬁles observed in the cell lines compared to the
original tumor are unsurprising given this eﬀect has been seen in many cell lines of other cancer
]. Contrastingly, Barretina et al. [
] observed a strong positive correlation between
947 cell lines and primary tumors, suggesting cell lines possessed many of the genomic aberrations
found in tumors. They proposed the diﬀerences between cell lines and clinical tumors are a result of
background tumor microenvironment (TME)-related gene expression that could be simply subtracted,
leaving purely tumor cell-associated gene signatures.
High passage cultures were found to downregulate pathways further, highlighting the vulnerability
of high passage commercial cell lines. However, unpublished work from our group has shown
that changes in drug responsiveness over passage numbers were subtle. The spheroid derivative
demonstrated a slight change in expression proﬁle towards the original tumor, although global changes
were found to be negligible, as found with other cell types [
]. It was observed in the normoxic
derivative that the genes involved in metastasis response were inﬂuenced by normoxic-inducible
factors, aligning with previous literature , supporting hypoxic culture conditions.
Cells surviving radiation may acquire new mutations or expose previously undetected mutations
present within the now-expanded subclone. The current study noted an increase in PCNA,MAD2L2,
and FEN1 gene expression in UW-CSCC1-R relative to UW-CSCC1; all of which contribute majorly
to DNA damage repair [
]. In addition, cell adhesion and stem cell-associated genes were also
altered in UW-CSCC1-R, contributing to a more mesenchymal physiology and likely contributing to
the changes observed in proliferation and drug responsiveness. In a clinical context, this may result in
more aggressive local recurrence; therefore, continued investigation into pre-clinical models based on
UW-CSCC1-R that imitate this scenario are warranted.
The cSCC secondary xenograft mostly regained the original tumor phenotype (indicative of
genome stability), with the exception of the following pathways: collagen family, ECM structure,
metastasis response, and regulation of angiogenesis. This may be due to the mouse stroma inhibiting
transcription of the relevant genes in the human cells, or species incompatibility as murine growth
factors do not activate certain human-speciﬁc pathways, e.g., human MET [
]. A similar study
compared cell lines with their successive xenografts and found a number of gene classes becoming
enriched in the xenograft tumors [
]. In contrast, it has been observed for small cell lung cancer that
many of the changes incurred by going onto plastic were irreversible [
]. We infer that this restorative
ability is cell line-dependent.
Thus, altogether, the WGS and gene expression data indicate that genotype was preserved in
the cell lines and that diﬀerences in gene expression proﬁles due to
culture can be largely
. This property permits the highly reproducible and cost-eﬀective derivation of cell
for eﬃcient biological assays, with the capability of resembling in situ tumor biology,
given the appropriate environment .
The establishment and anti-cancer drug library screening of UW-CSCC1 and its derivatives
also revealed eﬃcacious agents and drug classes that will draw our focus in future investigations.
The moderate correlation in drug sensitivity between UW-CSCC1 and UW-CSCC1-R highlights the
eﬀect that irradiation can have upon drug response. Nonetheless, the cells are still quite responsive to
chemotherapy post-radiation which, for the case
, implies the potential beneﬁt for chemotherapy
in the adjuvant setting or in cases of local recurrence. Drugs targeting cytoskeletal signaling were
particularly eﬃcacious and may be related to mutations in SYNE1 which were notably present in
our cell lines as well as in 14/15 of the clinical samples assessed (Table S3). This gene has a role
in cytoskeletal arrangement and has been proposed as a biomarker of colorectal cancer in liquid
]. Dose-response screening and western blot analysis veriﬁed the sensitivity of the cell lines
Int. J. Mol. Sci. 2020,21, 9536 9 of 16
towards PIK-75, as well as the dual mTOR/PI3K-targeting dactolisib, thus permitting further pre-clinical
studies on the PI3K/AKT/mTOR oncogenic pathway in metastatic cSCC. A recent study similarly
identiﬁed sensitivity to dactolisib for invasive cell lines of cSCC [
]. According to the Genomics
of Drug Sensitivity in Cancer Database (https://www.cancerrxgene.org/; Accessed 1 December 2020)
the mean IC
for head and neck SCC cell lines using dactolisib (PIK-75 data not available) was
notably higher (311 nM) than the range observed with our cell lines (22–80 nM), further supporting the
sensitivity of our cell lines to this drug. Whilst cell cycle and cytoskeleton-targeting drugs were also
unsurprisingly highly eﬃcacious in our study [
], these compounds do not oﬀer the same degree
of speciﬁcity as PI3K/AKT/mTOR-targeting agents. Interestingly, some PI3K inhibitors produced
little to no response against the cell lines, a likely result of isoform speciﬁcity that requires further
]. The anti-EGFR biologic Cetuximab is sometimes given to patients with advanced
cSCC, achieving overall response rates approaching 50% [
]. However, there are multiple mechanisms
by which downstream eﬀectors of EGFR may become activated, including via PI3K [
the continued examination of such pathways in advanced cSCC is necessary.
Not surprisingly, TP53 inactivating mutations were common across these cell lines and the clinical
specimens assessed, which may explain their sensitivity to DNA-damaging drugs. The direct target
of p53, NOTCH1, is also often disrupted in cSCC and generally occurs early in cSCC [
the Patient 1 tumor and its derivative cells lines did not harbor NOTCH1 mutations, suggesting this is
not a universal feature required for metastases. Concomitant NOTCH1 and TP53 stop-gain mutations
(high impact loss of function mutations) in UW-CSCC2 may explain the cell line’s resistance towards
carboplatin relative to UW-CSCC1 and UW-CSCC1-R.
In conclusion, the generation of the UW-CSCC cell lines with detailed genomic characterization
and HTS drug-screen data has provided important new insights into the biology of metastatic cSCC
and revealed new candidate therapeutic targets for this disease. Whilst much of the transcriptomic
diﬀerence noted may prove experimentally and clinically irrelevant, caution must be exercised when
undertaking assays dependent upon the mechanisms provided by any signiﬁcantly altered genes
and/or pathways. However, these diﬀerences may be negated once they are re-established
. It is
hoped that the provision and validation of these novel cell lines will stimulate further investigations in
4. Materials and Methods
4.1. Patient Characteristics and Specimen Selection
An intraparotid lymph-node metastasis of cSCC was resected from a 73-year-old male (
See Table S2
for patient characteristics). Clinical staging of the tumor was performed in accordance with the 8th
edition of the American Joint Committee on Cancer (AJCC) TNM staging manual. An area of the
tumor sample with 70% neoplastic content without necrosis, haemorrhage, high keratin content or
signiﬁcant inﬂammation was selected for cell culture and nucleic acid extraction. A parotid nodal
metastasis from another patient was also processed (86-year-old male), however this sample forwent
extensive genomic and phenotypic analysis for reasons noted below. Tissue and blood were obtained
with written informed patient consent in accordance with the declaration of Helsinki and University of
Wollongong Human Research Ethics Committee’s approval (HE14/397; approval date: 26 May 2015).
4.2. Cell Culture Development and Maintenance
Tumor samples were dissected within 1 h of surgical resection into 1 mm
pieces, with some
fractions of the bulk tumor mass snap-frozen in liquid nitrogen for subsequent nucleic acid extraction.
Samples were either dissociated using the MACS Miltenyi human tumor dissociation kit in conjunction
with the gentleMACS
dissociator (Patient 1), or simply plated as an explant onto the tissue culture
surface (Patient 2). Resultant cultures were designated UW-CSCC1 and UW-CSCC2, respectively.
Dissociated tissue was passed through a 70
m MACS SmartStrainer, the ﬁltrate was centrifuged,
Int. J. Mol. Sci. 2020,21, 9536 10 of 16
and the pellet was re-suspended in Dulbecco’s Modiﬁed Eagle Medium (DMEM), supplemented with
10% heat-inactivated foetal calf serum (FCS), glucose (4500 mg/mL), and penicillin/streptomycin
(50 U/mL). Explant cultures were grown in Advanced DMEM/F12, supplemented with hEGF (20 ng/mL),
1% L-glutamine, 2% FCS, and penicillin/streptomycin (50 U/mL). Cells/explants were placed into tissue
culture ﬂasks according to cell density and incubated at 37 ◦C under a 5% CO2, 3% O2atmosphere.
Diﬀerential trypsinization was employed to deplete the competing ﬁbroblast population [
Pure metastatic cSCC cell cultures were conﬁrmed within 13 (UW-CSCC1) and 4 (UW-CSCC2) passages
and could be frozen and thawed successfully. These cultures were henceforth regarded as low passage,
whilst a high passage culture of UW-CSCC1 was also established (UW-CSCC1-high passage) following
an additional 41 rounds of subculturing. To conﬁrm the cultures as epithelial, antibodies speciﬁc
to cytokeratin 4/5/6/8/10/13/18 (CK223; Abcam, Cambridge, UK, Cat # ab115974) and the epithelial
cell adhesion molecule (EpCAM; Abcam, Cambridge, UK, Cat # ab7504) were used, as well as the
-smooth muscle actin (
-SMA; Abcam, Cambridge, UK, Cat # ab7817) serving
as a negative control.
To obtain spheroid cultures (UW-CSCC1 Spheroid), cells were seeded in Corning
ultra-low binding plates (Sigma-Aldrich, St. Louis, MO, USA) at a density of 375 cells per well
using the aforementioned media formulation. UW-CSCC1 cells at passage 13 were also exposed
to the clinically relevant dose of 2 Gy orthovoltage X-ray radiation (Radiation Oncology Medical
Physics, Prince of Wales Hospital, Sydney, Australia) and surviving radio-resistant cells expanded
(UW-CSCC1-R). A normoxic acclimated population of cells (UW-CSCC1-Normoxic) was also derived
by incubating under standard atmospheric oxygen levels. A list of the cell lines generated along with
experimental derivations is provided in Table S5.
4.3. Generation of Mouse Xenografts
NOD scid gamma (NOD.Cg-Prkdc <scid >IL2rg <tm1Wjl >/SzJAusb) mice (aged 4–5 weeks old,
Australian Bioresources, Australia) were subcutaneously inoculated with cell lines at a density of
cells into the rear ﬂanks. Upon reaching 10
, tumors were harvested from the
sacriﬁced mice for cell culture, RNA extraction, and histological analysis. For culture from xenografts,
tumor tissues were cut into approximately 1 mm pieces and then incubated with tumor dissociation
enzymes (Tumor dissociation kit, Miltenyi Biotec, Bergisch Gladbach, Germany) in culture media,
after which the tumor homogenate was centrifuged, and the pellet was resuspended and plated in
serum-free media and hypoxic conditions as above. All procedures were carried out in accordance
with the Australian Code for the Care and Use of Animal for Scientiﬁc Purposes 8th edition 2013,
and approved by the University of Wollongong’s Animal Ethics Committee (study AE15/17).
4.4. Organotypic Invasion Assay
Contractions of collagen I matrices using dermally derived telomerase induced ﬁbroblasts (TIFs)
were performed as previously described [
]. Brieﬂy, contraction to a 3D matrix was stimulated by
mixing a neutralized collagen I cocktail (8.8% v/v10
minimal essential media (Thermo Scientiﬁc,
Waltham, MA, USA); 75.8% v/v2 mg/mL collagen I; 8% v/v0.22 M NaOH (pH 7.4)) with TIFs
1×106 per 12 matrices
) resuspended in FCS. The TIFs used in this assay are required to be quiescent,
which was achieved by leaving the cells in culture for at least ﬁve days after conﬂuency without a change
of media. Per 35 mm petri dish (Sigma-Aldrich, St. Louis, MO, USA), 2.5 mL of the collagen–ﬁbroblast
cocktail was dispensed and allowed to polymerize for 30 min in an incubator at 37
C. Following this,
the petri dishes were topped with complete media (DMEM/10% FCS/P+S) and matrices permitted to
contract over a period of 5–12 days to give a diameter no smaller than 1 cm. The media was refreshed
every 2–3 days or as required depending on the state of the color indicator present within the media.
Contracted matrices were moved into 24-well plates (Greiner Bio-One, Kremsmunster, Austria)
L of complete media containing 3.0
105 of the cells under investigation was seeded atop
each matrix. After 15 min in the incubator at 37
C to allow the cells to settle to the matrix, a further
Int. J. Mol. Sci. 2020,21, 9536 11 of 16
L of media was added to each well and left to grow until conﬂuent. The matrices were then
transferred onto the top of sterile 40 mm mesh screens in 60 mm petri dishes. Fresh media was added
until surface tension was created between the mesh grid and media, thereby creating an air–liquid
interface to promote invasion across the chemotactic gradient (in this case the underlying media).
After 7–14 days, the matrices were ﬁxed in 4% neutral buﬀered formalin for 24 h followed by another
24 h in 10% formalin. The ﬁxed samples were dehydrated in 70% ethanol and processed overnight in an
ASP200 vacuum tissue processor (Leica Biosystems, Wetzlar, Germany). Each matrix was then sliced in
half dorsoventrally and embedded in paraﬃn using the EG1150 Modular Tissue Embedding Centre and
EG1150 Cold Plate (Leica Biosystems, Germany). The resultant paraﬃn-embedded tissue block was
sectioned at a thickness of 4
m using a RM2255 Fully-Automated Rotary Microtome (Leica Biosystems,
Germany) and transferred onto glass slides by ﬂoating sectioned tissue in a dH
O water-bath at 40
Slides were allowed to dry overnight prior to histological staining. Sectioned tissue was deparaﬃnized
in dipentene (POCD Healthcare, Sydney, NSW, Australia) and rehydrated using graded ethanol washes
(60–100% EtOH). Hematoxylin and eosin (H&E; POCD Sciences, Australia)-staining was performed
on a LeicaST4020 small linear stainer (Leica Biosystems, Germany) and slides mounted with DPX
(Sigma-Aldrich, St. Louis, MO, USA). Following an overnight drying period, the invasion incurred by
the cells was assessed through examination of the slides under a Leica DM4000 bright-ﬁeld microscope
(Leica Biosystems, Germany).
4.5. Nucleic Acid Extraction
Tumor and cell line DNA and RNA were extracted as was previously described (Mueller et al., 2019).
All samples were quantiﬁed using the NanoDrop spectrophotometer (ND1000, ThermoFisher scientiﬁc,
Waltham, MA, USA) and met the purity requirements for downstream applications (A260/280 between
1.7 and 2.3). Samples were further quality controlled prior to WGS by the sequencing facilities.
4.6. Gene Expression Analysis
Gene expression on the NanoString nCounter Sprint platform was assessed using total
RNA (25–50 ng) with two diﬀerent panels (PanCancer Progression and PanCancer Pathways;
each containing 740 target and 30 “housekeeping” genes) as per the manufacturer’s instructions
(NanoString Technologies, Seattle, WA, USA). Table S5 summarizes the samples run, the passage
number from which extracts were made, and the panel used.
Data were analyzed using NanoString’s nSolver Analysis Software v4.0 (https://www.nanostring.
com; NanoString Technologies, Seattle, WA, USA) with raw counts normalized using house-keeping
genes, selected based on a low coeﬃcient of variation between samples and average counts above
negative controls. Diﬀerential gene expression was derived using nCounter default settings and quality
control governed as per manufacturer’s instructions.
4.7. Whole-Genome Sequencing (WGS) and Bioinformatics Analysis Pipeline
WGS was performed on an Illumina HiSeqX instruments (Illumina, San Diego, CA, USA) by
Genome.One Pty Ltd. (Sydney, NSW, Australia) and at Macrogen (Seoul, Korea). Germline DNA
(blood) was sequenced to a depth 30–45X and the experimental samples to 60–90X depending on the
Using a Burrows–Wheeler Aligner (BWA-MEM v0.7.10-r789) [
], paired-end sequencing reads
were aligned to Genome Reference Consortium Human Build 37 (GRCh37/hg19) and improved using
realignment around known indels using the Genome Analyser toolkit (GATK) version 3.3.0. PCR
duplicates were removed using SAMtools v1 and Picard metrics have been used to evaluate the run
quality. Somatic single nucleotide variants (SNVs) were called by Strelka v1.0.15 [
] from tumor-normal
pairs. Calculations of the tumor cellularity, ploidy, and copy number alterations were performed by
Purple and Sequenza 2.1.2 [
]. Major structural variants (SVs) were inferred with Manta 0.27.1 [
The annotation and further ﬁltering of Strelka quality-passed SNVs and indels were done based on
Int. J. Mol. Sci. 2020,21, 9536 12 of 16
two diﬀerent platforms, i.e., OpenCravat [
] and Gemini-Seave pipeline [
]. Mutational signatures
were determined for each specimen as per the method described by
Mueller et al. .
Integrated Genomics Viewer (IGV; Broad Institute, Cambridge, MA, USA) somatic variants of interest
were veriﬁed to ensure coverage and call accuracy. Unique and shared somatic mutation sets were
obtained for each sequenced sample using Bedtools v2.27.0.
4.8. Chemical Compound Library Assays and Analysis
Cells were screened using the CHiP 2G anti-cancer and kinase-inhibitor libraries (SelleckChem,
Houston, TX, USA), at a concentration of 1
M. A total of 1000 cells were seeded per well into 384-well
plates (PerkinElmer, Waltham, MA, USA, Cat. no. 6007558). Cells were cultured at 37
C, 5% CO
treated with anti-cancer (Selleckchem, Houston, TX, USA, Cat. no. L3000) and anti-kinase (Selleckchem,
USA, Cat. no L1200) small molecule libraries 24 h after cell seeding. Cell viability was measured after
72 h using the CellTiter-Glo
Luminescent assay (Promega, Madison, WI, USA, Cat no. G7570) as per
manufacturer’s protocol. Percentage viability was calculated from replicates relative to the average
DMSO control reading.
4.9. Secondary Dose-Response Screening
Based on clinical use and the results of the high-throughput screen, cell lines were screened with a
suite of chemotherapeutic agents including PIK-75 (Selleckchem, USA, Cat no. S1205) at a titrated
range. The metabolic activity of cells was determined using a CellTitre 96
Aqueous One Solution Cell
Proliferation Assay (Promega, USA, Cat no. G3581) according to the manufacturer’s instructions and
as previously described [
]. The raw data of treated cells were normalized against vehicle controls
with background absorbance values subtracted. Half-maximal inhibitory concentration (IC
were derived with GraphPad Prism 6.0 using a logarithmic sigmoidal dose–response curve with the
variable slope parameter. The cell viability of treated cells was normalized against vehicle controls.
4.10. Cell Lysate Preparation and Western Blot Analysis
Near-conﬂuent UW-CSCC1 and UW-CSCC1-R were treated with IC
concentrations of PIK-75
(120 nM or 200 nM, respectively) or dactolisib (22 nM or 80 nM, respectively) for 3 and 6 h, along with
a 6 h DMSO vehicle control treatment. Lysates were prepared by washing the cells in PBS, followed by
a 20 min incubation with RIPA buﬀer (50 mM Tris-HCl (pH =7.4), 150 mM NaCl, 1% Triton-x100,
5 mM EDTA, 1 mM PMSF, 1 mM sodium orthovandate) on ice. The crude lysate was transferred
to a microfuge tube and centrifuged at 12,000
gfor 5 min at 4
C to pellet debris and genomic
DNA. The proteinaceous supernatant was subsequently aliquoted for long-term storage at
The protein concentration of lysates was determined using a Pierce Bicinchoninic Acid (BCA) Protein
Assay Kit (ThemoFisher Scientiﬁc, Waltham, MA, USA) according to the manufacturer’s protocol.
Protein extracts (20
g) were resolved on a 4–20% gradient SDS-polyacrylamide gel (Invitrogen,
Carlsbad, CA, USA, Cat no. NP0324BOX) under reducing conditions. Proteins were transferred
to a PVDF membrane and blocked in 5% skim milk powder containing Tris-buﬀered saline with
0.2% tween (TBST) for one hour at room temperature. Membranes were rinsed with TBST and
then incubated overnight at 4
C with primary antibodies from Cell Signalling (Danvers, MA, USA),
including: rabbit anti-human AKT ([11E7] 1:1000, Cat no. 46855), rabbit anti-human phospho-AKT
(Ser473; D9E, 1:1000, Cat no. 4060S), and the housekeeping mouse anti-human GAPDH (D4C6R,
1:2000, Cat no. 97166S) diluted in TBST containing 2% skim milk powder. After three rinses with TBST,
membranes were incubated for 90 min at room temperature with horseradish peroxidase-conjugated
anti-rabbit (Cell Signalling, Danvers, MA, USA, Cat no. 7074), and anti-mouse (Abcam, Cambridge, UK,
Cat no. ab205719) IgG secondary antibodies at a dilution of 1:2000 in TBST containing 2% skim
milk powder. Chemiluminescence was generated using Pierce
ECL Western Blotting Substrate
(ThermoFisher Scientiﬁc, Waltham, MA, USA, Cat no. 32109) and visualized on the Amersham
Imager 600 (GE Healthcare, Chicago, IL, USA). Captured blots were subsequently analyzed using
Int. J. Mol. Sci. 2020,21, 9536 13 of 16
ImageJ (version 1.53) to obtain densitometry. The resulting densitometry units were then graphically
interpreted using GraphPad Prism5 v6.0.
4.11. Data Repository
The variant call format ﬁles have been deposited at the European Genome-Phenome
Archive (https://ega-archive.org/), which is hosted by the EMBL-European Bioinformatics Institute
(Cambridgeshire, UK) and the Center for Genomic Regulation (Barcelona, Spain), under accession
Supplementary Materials: The following are available online at http://www.mdpi.com/1422- 0067/21/24/9536/s1.
Conceptualization: M.R., B.A., J.P., N.G.I.; formal analysis: J.P., M.R., B.A., A.S.T.,
M.-E.G.; methodology: J.P., E.M., G.M., M.R., A.S.T., M.-E.G., N.G.I.; investigation: J.P., E.M., G.M., A.S.T.;
funding acquisition: M.R., B.A., J.C.; supervision: M.R., B.A., N.G.I., J.C., R.G.; writing—original draft preparation:
J.P., M.R.; writing—review and editing: All; project administration: M.R. All authors have read and agreed to the
published version of the manuscript.
This research received ﬁnancial support from the Illawarra Cancer Carers and NHMRC Ideas Grant
We thank the Kinghorn Centre for Clinical Genomics for assistance with production and
processing of whole-genome sequencing data and the Illawarra Cancer Carers for ﬁnancial support.
Conﬂicts of Interest: The authors declare no conﬂict of interest.
cSCC Cutaneous squamous cell carcinoma
NER Nuclear excision repair
SNV Small nucleotide variant
UV Ultraviolet radiation
WGS Whole genome sequencing
Vasconcelos, L.; Melo, J.C.; Miot, H.A.; Marques, M.E.A.; Abbade, L.P.F. Invasive head and neck cutaneous
squamous cell carcinoma: Clinical and histopathological characteristics, frequency of local recurrence and
metastasis. An. Bras. Dermatol. 2014,89, 562–568. [CrossRef] [PubMed]
Stratigos, A.; Garbe, C.; Lebbe, C.; Malvehy, J.; del Marmol, V.; Pehamberger, H.; Peris, K.; Becker, J.C.;
Zalaudek, I.; Saiag, P.; et al. Diagnosis and treatment of invasive squamous cell carcinoma of the skin:
European consensus-based interdisciplinary guideline. Eur. J. Cancer
,51, 1989–2007. [CrossRef]
Brougham, N.D.; Dennett, E.R.; Cameron, R.; Tan, S.T. The incidence of metastasis from cutaneous squamous
cell carcinoma and the impact of its risk factors. J. Surg. Oncol. 2012,106, 811–815. [CrossRef] [PubMed]
Makki, F.M.; Mendez, A.I.; Taylor, S.M.; Trites, J.; Bullock, M.; Flowerdew, G.; Hart, R.D. Prognostic factors
for metastatic cutaneous squamous cell carcinoma of the parotid. J. Otolaryngol. Head Neck Surg.
Burton, K.A.; Ashack, K.A.; Khachemoune, A. Cutaneous Squamous Cell Carcinoma: A Review of High-Risk
and Metastatic Disease. Am. J. Clin. Dermatol. 2016,17, 491–508. [CrossRef]
Karia, P.S.; Han, J.; Schmults, C.D. Cutaneous squamous cell carcinoma: Estimated incidence of disease,
nodal metastasis, and deaths from disease in the United States, 2012. J. Am. Acad. Dermatol.
Nelson, T.G.; Ashton, R.E. Low incidence of metastasis and recurrence from cutaneous squamous cell
carcinoma found in a UK population: Do we need to adjust our thinking on this rare but potentially fatal
event? J. Surg. Oncol. 2017,116, 783–788. [CrossRef]
Venables, Z.; Autier, P.; Nijsten, T.; Wong, K.F.; Langan, S.M.; Rous, B.; Broggio, J.; Harwood, C.; Henson, K.;
Proby, C.M.; et al. Nationwide Incidence of Metastatic Cutaneous Squamous Cell Carcinoma in England.
JAMA Dermatol. 2018,155, 298–306. [CrossRef]
Int. J. Mol. Sci. 2020,21, 9536 14 of 16
Migden, M.R.; Khushalani, N.I.; Chang, A.L.S.; Lewis, K.D.; Schmults, C.D.; Hernandez-Aya, L.; Meier, F.;
Schadendorf, D.; Guminski, A.; Hauschild, A.; et al. Cemiplimab in locally advanced cutaneous squamous
cell carcinoma: Results from an open-label, phase 2, single-arm trial. Lancet Oncol.
Rischin, D.; Migden, M.R.; Lim, A.M.; Schmults, C.D.; Khushalani, N.I.; Hughes, B.G.M.; Schadendorf, D.;
Dunn, L.A.; Hernandez-Aya, L.; Chang, A.L.S.; et al. Phase 2 study of cemiplimab in patients with metastatic
cutaneous squamous cell carcinoma: Primary analysis of ﬁxed-dosing, long-term outcome of weight-based
dosing. J. Immunother. Cancer 2020,8, e000775. [CrossRef]
Al-Rohil, R.N.; Tarasen, A.J.; Carlson, J.A.; Wang, K.; Johnson, A.; Yelensky, R.; Lipson, D.; Elvin, J.A.;
Vergilio, J.A.; Ali, S.M.; et al. Evaluation of 122 advanced-stage cutaneous squamous cell carcinomas
by comprehensive genomic proﬁling opens the door for new routes to targeted therapies. Cancer
122, 249–257. [CrossRef] [PubMed]
Inman, G.J.; Wang, J.; Nagano, A.; Alexandrov, L.B.; Purdie, K.J.; Taylor, R.G.; Sherwood, V.; Thomson, J.;
Hogan, S.; Spender, L.C.; et al. The genomic landscape of cutaneous SCC reveals drivers and a novel
azathioprine associated mutational signature. Nat. Commun. 2018,9, 3667. [CrossRef] [PubMed]
Li, Y.Y.; Hanna, G.J.; Laga, A.C.; Haddad, R.I.; Lorch, J.H.; Hammerman, P.S. Genomic Analysis of Metastatic
Cutaneous Squamous Cell Carcinoma. Clin. Cancer Res. 2015,21, 1447–1456. [CrossRef] [PubMed]
Zilberg, C.; Lee, M.W.; Yu, B.; Ashford, B.; Kraitsek, S.; Ranson, M.; Shannon, K.; Cowley, M.; Iyer, N.G.;
Palme, C.E.; et al. Analysis of clinically relevant somatic mutations in high-risk head and neck cutaneous
squamous cell carcinoma. Mod. Pathol. 2017,31, 275–287. [CrossRef]
Pickering, C.R.; Zhou, J.H.; Lee, J.J.; Drummond, J.A.; Peng, S.A.; Saade, R.E.; Tsai, K.Y.; Curry, J.L.;
Tetzlaﬀ, M.T.; Lai, S.Y.; et al. Mutational Landscape of Aggressive Cutaneous Squamous Cell Carcinoma.
Clin. Cancer Res. 2014,20, 6582–6592. [CrossRef]
Badlani, J.; Gupta, R.; Smith, J.; Ashford, B.; Ch’ng, S.; Veness, M.; Clark, J. Metastases to the parotid gland
—A review of the clinicopathological evolution, molecular mechanisms and management. Surg. Oncol.
27, 44–53. [CrossRef]
Mitsui, H.; Su
rez-Fariñas, M.; Gulati, N.; Shah, K.R.; Cannizzaro, M.V.; Coats, I.; Felsen, D.; Krueger, J.G.;
Carucci, J.A. Gene expression proﬁling of the leading edge of cutaneous squamous cell carcinoma:
IL-24-driven MMP-7. J. Investig. Dermatol. 2014,134, 1418–1427. [CrossRef]
Mueller, S.A.; Gauthier, M.-E.A.; Ashford, B.; Gupta, R.; Gayevskiy, V.; Ch’ng, S.; Palme, C.E.; Shannon, K.;
Clark, J.R.; Ranson, M.; et al. Mutational Patterns in Metastatic Cutaneous Squamous Cell Carcinoma.
J. Investig. Dermatol. 2019,139, 1449–1458. [CrossRef]
Lobl, M.B.; Clarey, D.; Higgins, S.; Sutton, A.; Hansen, L.; Wysong, A. Targeted next-generation sequencing
of matched localized and metastatic primary high-risk SCCs identiﬁes driver and co-occurring mutations
and novel therapeutic targets. J. Dermatol. Sci. 2020,99, 30–43. [CrossRef]
Goodspeed, A.; Heiser, L.M.; Gray, J.W.; Costello, J.C. Tumor-Derived Cell Lines as Molecular Models of
Cancer Pharmacogenomics. Mol. Cancer Res. 2016,14, 3–13. [CrossRef] [PubMed]
21. Weinstein, J.N. Cell lines battle cancer. Nature 2012,483, 544. [CrossRef] [PubMed]
Wilding, J.L.; Bodmer, W.F. Cancer Cell Lines for Drug Discovery and Development. Cancer Res.
74, 2377–2384. [CrossRef] [PubMed]
Lin, C.J.; Grandis, J.R.; Carey, T.E.; Gollin, S.M.; Whiteside, T.L.; Koch, W.M.; Ferris, R.L.; Lai, S.Y. Head and
neck squamous cell carcinoma cell lines: Established models and rationale for selection. Head Neck
29, 163–188. [CrossRef] [PubMed]
Kondo, S.; Aso, K. Establishment of a cell line of human skin squamous cell carcinoma
.Br. J. Dermatol.
1981,105, 125–132. [CrossRef]
Farshchian, M.; Kivisaari, A.; Ala-aho, R.; Riihilä, P.; Kallajoki, M.; Gr
nman, R.; Peltonen, J.; Pihlajaniemi, T.;
Heljasvaara, R.; Kähäri, V.-M. Serpin Peptidase Inhibitor Clade A Member 1 (SerpinA1) Is a Novel Biomarker
for Progression of Cutaneous Squamous Cell Carcinoma. Am. J. Pathol. 2011,179, 1110–1119. [CrossRef]
Proby, C.M.; Purdie, K.J.; Sexton, C.J.; Purkis, P.; Navsaria, H.A.; Stables, J.N.; Leigh, I.M. Spontaneous
keratinocyte cell lines representing early and advanced stages of malignant transformation of the epidermis.
Exp. Dermatol. 2000,9, 104–117. [CrossRef] [PubMed]
Int. J. Mol. Sci. 2020,21, 9536 15 of 16
Hassan, S.; Purdie, K.J.; Wang, J.; Harwood, C.A.; Proby, C.M.; Pourreyron, C.; Mladkova, N.; Nagano, A.;
Dhayade, S.; Athineos, D.; et al. A Unique Panel of Patient-Derived Cutaneous Squamous Cell Carcinoma Cell
Lines Provides a Preclinical Pathway for Therapeutic Testing. Int. J. Mol. Sci.
,20, 3428. [CrossRef] [PubMed]
Rheinwald, J.G.; Beckett, M.A. Tumorigenic Keratinocyte Lines Requiring Anchorage and Fibroblast Support
Cultured from Human Squamous Cell Carcinomas. Cancer Res. 1981,41, 1657–1663.
Anderson, A.N.; McClanahan, D.; Jacobs, J.; Jeng, S.; Vigoda, M.; Blucher, A.S.; Zheng, C.; Yoo, Y.J.; Hale, C.;
Ouyang, X.; et al. Functional genomic analysis identiﬁes drug targetable pathways in invasive and metastatic
cutaneous squamous cell carcinoma. Cold Spring Harb. Mol. Case Stud. 2020,6, a005439. [CrossRef]
Cañueto, J.; Cardeñoso, E.; Garc
a, J.L.; Santos-Briz,
n, A.; Fern
mez, A.; P
rez-Losada, J.; Rom
n-Curto, C. Epidermal growth factor receptor expression is associated
with poor outcome in cutaneous squamous cell carcinoma. Br. J. Dermatol. 2017,176, 1279–1287. [CrossRef]
Ashford, B.G.; Clark, J.; Gupta, R.; Iyer, N.G.; Yu, B.; Ranson, M. Reviewing the genetic alterations in high-risk
cutaneous squamous cell carcinoma: A search for prognostic markers and therapeutic targets. Head Neck
2017,39, 1462–1469. [CrossRef]
Gazdar, A.F.; Gao, B.; Minna, J.D. Lung cancer cell lines: Useless artifacts or invaluable tools for medical
science? Lung Cancer 2010,68, 309–318. [CrossRef]
Janus, J.M.; O’Shaughnessy, R.F.L.; Harwood, C.A.; Maﬀucci, T. Phosphoinositide 3-Kinase-Dependent
Signalling Pathways in Cutaneous Squamous Cell Carcinomas. Cancers 2017,9, 86. [CrossRef] [PubMed]
Chamcheu, J.C.; Roy, T.; Uddin, M.B.; Banang-Mbeumi, S.; Chamcheu, R.-C.N.; Walker, A.L.; Liu, Y.-Y.;
Huang, S. Role and Therapeutic Targeting of the PI3K/Akt/mTOR Signaling Pathway in Skin Cancer: A
Review of Current Status and Future Trends on Natural and Synthetic Agents Therapy. Cells
Hoxhaj, G.; Manning, B.D. The PI3K–AKT network at the interface of oncogenic signalling and cancer
metabolism. Nat. Rev. Cancer 2020,20, 74–88. [CrossRef] [PubMed]
Gillet, J.-P.; Calcagno, A.M.; Varma, S.; Marino, M.; Green, L.J.; Vora, M.I.; Patel, C.; Orina, J.N.; Eliseeva, T.A.;
Singal, V.; et al. Redeﬁning the relevance of established cancer cell lines to the study of mechanisms of
clinical anti-cancer drug resistance. Proc. Natl. Acad. Sci. USA 2011,108, 18708–18713. [CrossRef]
Lukk, M.; Kapushesky, M.; Nikkilä, J.; Parkinson, H.; Goncalves, A.; Huber, W.; Ukkonen, E.; Brazma, A.
A global map of human gene expression. Nat. Biotechnol. 2010,28, 322. [CrossRef]
Ertel, A.; Verghese, A.; Byers, S.W.; Ochs, M.; Tozeren, A. Pathway-speciﬁc diﬀerences between tumor cell
lines and normal and tumor tissue cells. Mol. Cancer 2006,5, 55. [CrossRef]
Barretina, J.; Caponigro, G.; Stransky, N.; Venkatesan, K.; Margolin, A.A.; Kim, S.; Wilson, C.J.; Lehar, J.;
Kryukov, G.V.; Sonkin, D.; et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer
drug sensitivity. Nature 2012,483, 603–607. [CrossRef]
Kenny, P.A.; Lee, G.Y.; Myers, C.A.; Neve, R.M.; Semeiks, J.R.; Spellman, P.T.; Lorenz, K.; Lee, E.H.;
Barcellos-Hoﬀ, M.H.; Petersen, O.W.; et al. The morphologies of breast cancer cell lines in three-dimensional
assays correlate with their proﬁles of gene expression. Mol. Oncol. 2007,1, 84–96. [CrossRef]
Geraghty, R.J.; Capes-Davis, A.; Davis, J.M.; Downward, J.; Freshney, R.I.; Knezevic, I.; Lovell-Badge, R.;
Masters, J.R.; Meredith, J.; Stacey, G.N.; et al. Guidelines for the use of cell lines in biomedical research.
Br. J. Cancer 2014,111, 1021–1046. [CrossRef] [PubMed]
Boehm, E.M.; Gildenberg, M.S.; Washington, M.T. The Many Roles of PCNA in Eukaryotic DNA Replication.
Enzymes 2016,39, 231–254. [CrossRef] [PubMed]
Boersma, V.; Moatti, N.; Segura-Bayona, S.; Peuscher, M.H.; van der Torre, J.; Wevers, B.A.; Orthwein, A.;
Durocher, D.; Jacobs, J.J.L. MAD2L2 controls DNA repair at telomeres and DNA breaks by inhibiting 5’ end
resection. Nature 2015,521, 537–540. [CrossRef] [PubMed]
Gomes, X.V.; Burgers, P.M. Two modes of FEN1 binding to PCNA regulated by DNA. EMBO J.
19, 3811–3821. [CrossRef]
Creighton, C.; Kuick, R.; Misek, D.E.; Rickman, D.S.; Brichory, F.M.; Rouillard, J.-M.; Omenn, G.S.; Hanash, S.
Proﬁling of pathway-speciﬁc changes in gene expression following growth of human cancer cell lines
transplanted into mice. Genome Biol. 2003,4, R46. [CrossRef]
Daniel, V.C.; Marchionni, L.; Hierman, J.S.; Rhodes, J.T.; Devereux, W.L.; Rudin, C.M.; Yung, R.; Parmigani, G.;
Dorsch, M.; Peacock, C.D.; et al. A Primary Xenograft Model of Small Cell Lung Cancer Reveals Irreversible
Changes in Gene Expression Imposed by Culture In-Vitro. Cancer Res. 2009,69, 3364. [CrossRef]
Int. J. Mol. Sci. 2020,21, 9536 16 of 16
Melotte, V.; Yi, J.M.; Lentjes, M.H.F.M.; Smits, K.M.; Van Neste, L.; Niessen, H.E.C.; Wouters, K.A.D.;
Louwagie, J.; Schuebel, K.E.; Herman, J.G.; et al. Spectrin repeat containing nuclear envelope 1 and forkhead
box protein E1 are promising markers for the detection of colorectal cancer in blood. Cancer Prev. Res.
8, 157–164. [CrossRef]
Ong, M.S.; Deng, S.; Halim, C.E.; Cai, W.; Tan, T.Z.; Huang, R.Y.-J.; Sethi, G.; Hooi, S.C.; Kumar, A.P.; Yap, C.T.
Cytoskeletal Proteins in Cancer and Intracellular Stress: A Therapeutic Perspective. Cancers
, H.; Viotti, J.; Combemale, P.; Dutriaux, C.; Dupin, N.; Robert, C.; Mortier, L.; Kaphan, R.;
Duval-Modeste, A.-B.; Dalle, S.; et al. Cetuximab is eﬃcient and safe in patients with advanced cutaneous
squamous cell carcinoma: A retrospective, multicentre study. Oncotarget 2020,11, 378–385. [CrossRef]
Zhang, J.; Jia, J.; Zhu, F.; Ma, X.; Han, B.; Wei, X.; Tan, C.; Jiang, Y.; Chen, Y. Analysis of bypass signaling in
EGFR pathway and proﬁling of bypass genes for predicting response to anticancer EGFR tyrosine kinase
inhibitors. Mol. Biosyst. 2012,8, 2645–2656. [CrossRef]
Corchado-Cobos, R.; Garc
a-Sancha, N.; Gonz
lez-Sarmiento, R.; P
rez-Losada, J.; Cañueto, J. Cutaneous
Squamous Cell Carcinoma: From Biology to Therapy. Int. J. Mol. Sci. 2020,21, 2956. [CrossRef] [PubMed]
Jones, J.C.R. Reduction of Contamination of Epithelial Cultures by Fibroblasts. Cold Spring Harb. Protoc.
2008,2008, pdb.prot4478. [CrossRef]
Timpson, P.; McGhee, E.J.; Erami, Z.; Nobis, M.; Quinn, J.A.; Edward, M.; Anderson, K.I. Organotypic
Collagen I Assay: A Malleable Platform to Assess Cell Behaviour in a 3-Dimensional Context. J. Vis. Exp.
2011,56, e3089. [CrossRef] [PubMed]
Li, H.; Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics
2009,25, 1754–1760. [CrossRef]
Saunders, C.T.; Wong, W.S.W.; Swamy, S.; Becq, J.; Murray, L.J.; Cheetham, R.K. Strelka: Accurate somatic
small-variant calling from sequenced tumor–normal sample pairs. Bioinformatics
Priestley, P.; Baber, J.; Lolkema, M.P.; Steeghs, N.; de Bruijn, E.; Shale, C.; Duyvesteyn, K.; Haidari, S.;
van Hoeck, A.; Onstenk, W.; et al. Pan-cancer whole genome analyses of metastatic solid tumors. Nature
2019,575, 210–216. [CrossRef] [PubMed]
Favero, F.; Joshi, T.; Marquard, A.M.; Birkbak, N.J.; Krzystanek, M.; Li, Q.; Szallasi, Z.; Eklund, A.C. Sequenza:
Allele-speciﬁc copy number and mutation proﬁles from tumor sequencing data. Ann. Oncol. Oﬀ. J. Eur. Soc.
Med. Oncol. 2015,26, 64–70. [CrossRef]
Chen, X.; Schulz-Trieglaﬀ, O.; Shaw, R.; Barnes, B.; Schlesinger, F.; Källberg, M.; Cox, A.J.; Kruglyak, S.;
Saunders, C.T. Manta: Rapid detection of structural variants and indels for germline and cancer sequencing
applications. Bioinformatics 2015,32, 1220–1222. [CrossRef]
Pagel, K.A.; Kim, R.; Moad, K.; Busby, B.; Zheng, L.; Tokheim, C.; Ryan, M.; Karchin, R. Integrated Informatics
Analysis of Cancer-Related Variants. JCO Clin. Cancer Inform. 2020,4, 310–317. [CrossRef]
Gayevskiy, V.; Roscioli, T.; Dinger, M.E.; Cowley, M.J. Seave: A comprehensive web platform for storing and
interrogating human genomic variation. Bioinformatics 2018,35, 122–125. [CrossRef]
Brungs, D.; Minaei, E.; Piper, A.K.; Perry, J.; Splitt, A.; Carolan, M.; Ryan, S.; Wu, X.J.; Corde, S.; Tehei, M.; et al.
Establishment of novel long-term cultures from EpCAM positive and negative circulating tumour cells from
patients with metastatic gastroesophageal cancer. Sci. Rep. 2020,10, 539. [CrossRef]
MDPI stays neutral with regard to jurisdictional claims in published maps and institutional
2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).