Whole Transcriptome Analysis of Pre-invasive and Invasive Early Squamous Lung Carcinoma in Archival Laser Microdissected Samples
Koper et al. Respiratory Research
Whole Transcriptome Analysis of Pre- invasive and Invasive Early Squamous Lung Carcinoma in Archival Laser Microdissected Samples
Andre Koper 3
Leo A. H. Zeef 2
Leena Joseph 1
Keith Kerr 6
John Gosney 5
Mark A. Lindsay 4
Richard Booton 0
0 Manchester Thoracic Oncology Centre, University Hospital of South Manchester , Manchester, England M23 9LT , UK
1 Department of Pathology, University Hospital of South Manchester , Manchester, England M23 9LT , UK
2 Faculty of Life Science, University of Manchester , Manchester, England M13 9PT , UK
3 Qiagen GmbH , Hilden 40724 , Germany
4 Department of Pharmacy and Pharmacology, University of Bath , Bath, England BA 7AY , UK
5 Department of Pathology, Royal Liverpool University Hospital , Liverpool, England L7 8XP , UK
6 Department of Pathology, University of Aberdeen , Aberdeen, Scotland AB25 2ZD , UK
Background: Preinvasive squamous cell cancer (PSCC) are local transformations of bronchial epithelia that are frequently observed in current or former smokers. Their different grades and sizes suggest a continuum of dysplastic change with increasing severity, which may culminate in invasive squamous cell carcinoma (ISCC). As a consequence of the difficulty in isolating cancerous cells from biopsies, the molecular pathology that underlies their histological variability remains largely unknown. Method: To address this issue, we have employed microdissection to isolate normal bronchial epithelia and cancerous cells from low- and high-grade PSCC and ISCC, from paraffin embedded (FFPE) biopsies and determined gene expression using Affymetric Human Exon 1.0 ST arrays. Tests for differential gene expression were performed using the Bioconductor package limma followed by functional analyses of differentially expressed genes in IPA. Results: Examination of differential gene expression showed small differences between low- and high-grade PSCC but substantial changes between PSCC and ISCC samples (184 vs 1200 p-value <0.05, fc ±1.75). However, the majority of the differentially expressed PSCC genes (142 genes: 77%) were shared with those in ISCC samples. Pathway analysis showed that these shared genes are associated with DNA damage response, DNA/RNA metabolism and inflammation as major biological themes. Cluster analysis identified 12 distinct patterns of gene expression including progressive up or down-regulation across PSCC and ISCC. Pathway analysis of incrementally up-regulated genes revealed again significant enrichment of terms related to DNA damage response, DNA/RNA metabolism, inflammation, survival and proliferation. Altered expression of selected genes was confirmed using RTPCR, as well as immunohistochemistry in an independent set of 45 ISCCs. Conclusions: Gene expression profiles in PSCC and ISCC differ greatly in terms of numbers of genes with altered transcriptional activity. However, altered gene expression in PSCC affects canonical pathways and cellular and biological processes, such as inflammation and DNA damage response, which are highly consistent with hallmarks of cancer.
Preinvasive squamous cell cancer; Invasive squamous cell cancer; Exon arrays; Gene expression profiling; Microdissection
Lung cancer has been the most common fatal cancer
worldwide in the last 30 years. Its 5-year survival rate is
poor at less than 15% and has not improved significantly
since the 1970’s. However, the prospect of survival in
treated stage I lung cancer are greater than from stage II
lung cancer or worse. Hence, it is suggested that an early
diagnosis is pivotal for successful treatment, and
advancing the means for early diagnosis will reduce mortality
of this disease [1, 2].
About 20% of all lung cancers are ISCC that arise from
epithelia that line the upper airways . Patients at high
risk for ISCC, such as smokers, are susceptible to focal
squamous changes within the upper airway epithelia that
are detectable by sensitive autofluorescence bronchoscopy
techniques [4, 5]. The lesions of PSCC are usually small,
do not disrupt the basement membrane and show a
diverse histological spectrum that suggests a gradual
morphological transformation of bronchial epithelia into
low- and high-grade PSCC that eventually may progress
into ISCC . High-grade lesions in sputum or bronchial
biopsies indicate a higher risk for lung cancer within the
airway and at remote parenchymal sites and are therefore
regarded as important clinical indicators [6, 7]. However,
the prognostic benefit of PSCC is impaired by a
challenging histopathological classification and uncertainty about
their individual malignant potential, which may impair
their clinical relevance [8, 9].
Squamous cancers accumulate structural chromosomal
damage that increase in number and size at
wellrecognised genomic positions in high-grade PSCC and
ISCC [10–12]. Moreover, amplifications of the distal part
of chromosome 3q may correlate with progression of
high-grade PSCC to ISCC, and amplifications of this
particular chromosomal area are a significant feature of ISCC
in the lung and the esophagus, which is postulated to lead
to an up-regulation of gene expression of known
oncogenic potential, such as SOX2 or PIK3CA [13, 14].
These findings strongly suggest distinct gene expression
changes that underpin both PSCC and ISCC and which
may offer insights into the mechanism of progression
from a pre-invasive to an invasive tumour and potentially
aid the phenotypic classification of PSCC according to
their malignant potential. However, this has been hindered
by the scarcity of fresh and longitudinally harvested
material and the experimental challenges associated with
analysis of the widely available FFPE biopsies.
In this report, we have examined the changes in gene
expression in PSCC and ISCC using RNA from
microdissected archival biopsies obtained from the
University Hospital of South Manchester. To generate
genome-wide gene expression profiles across a reliable
histological classification of these samples, expert
pathological review of lesions was agreed prior to analysis
with Human Exon 1.0 ST arrays, which demonstrate
greater accuracy of gene expression estimation using
genomic material obtained from FFPE biopsies [15, 16].
Laser capture microscopy (LCM) and RNA extractions
All FFPE biopsies were selected by a specialist thoracic
pathologist, sectioned using a Leica RM2125 microtome
and stained with Hematoxylin and Eosin. PSCC, ISCC
cell clusters and normal epithelia were microdissected as
follows: each FFPE biopsy was used to produce a series
of a single 5μm section, transferred to a standard glass
slide for diagnostic evaluation by specialist thoracic
pathologists, and on average ten 10μm sections were
each placed on 1mm PEN membrane slides (Carl Zeiss,
Germany) for LCM using a Leica LMD6000 (Additional
file 1: Figure S1). RNA was isolated using the Ambion
Recover All Kit. Isolated RNA was quantified using a
Qubit fluorometer (Qubit RNA assay kit) and RNA
integrity was examined using an Agilent Bioanalyser.
Samples with RIN values in the range 2–3 were
employed for microarray analysis. All donors gave
written informed consent and the conducted research was
approved by the South Manchester Ethics Committee
Library preparations and array hybridization
Gene expression was analysed as previously described
. 50ng of total RNA was used for amplification and
reverse transcription of individual samples using the
Nugen Ovation FFPE WTA Kit, followed by biotin
labelling and library fragmentation via the Nugen Encore
Biotin Kit. Affymetrix Human Exon 1.0 ST array
hybridisation, washing, staining and scanning was
performed at the Molecular Biology Core Facility of the
CRUK Manchester Institute.
Real-time PCR (RT-PCR)
Comparative RT-PCR was performed to validate
expression changes of candidate genes between ISCC and
paired normal biopsies by using the delta delta Ct
method . All primers were designed using
PrimerBLAST (see Additional file 2: Table S1). PCR reactions
were setup using Applied Biosystem’s Fast SYBR green
master mix and were run in triplicates on an Applied
Biosystems 7900HT Real-Time PCR system. Primers
targeting 28S were used for the endogenous control in all
Exon array quality control and outlier detection was
performed using dChip (www.dchip.org, ). For
normalization and expression analysis of the array data,
the implementation of the RMA algorithm in Partek GS
6.6 (Copyright 2010, Partek Inc., St. Charles, MO, USA)
using core probesets was used. Differential expression tests
were performed with the Bioconductor package limma
using paired designs . The Bioconductor package
QVALUE was used to calculate the corresponding q-values
. Principal component analysis (PCA) of normalized
expression data from the included exon arrays was
performed using the R package FactoMineR
(https://cran.rproject.org/web/packages/FactoMineR/). Gene Set
Enrichment Analysis was used to calculate positional enrichment
of abnormal transcription using pre-ranked list of
aberrantly expressed genes in all ISCC or all PSCC and
positional gene sets available from MSigDB (http://
www.broadinstitute.org/gsea/msigdb) according to
previously published procedures . RCircos was used to
create the circus plot . For clustering analysis, 1914
differentially expressed genes from the three contrasts, i.e.,
all ISCC versus control samples, all PSCC samples versus
control samples and PSCC high-grade versus PSCC
lowgrade, were selected and filtered for p-value <0.05 and fold
change greater than +/−1.75. For the clustering analysis, 4
data points were used; average controls, average PSCC
low-grade, average PSCC high-grade and average ISCC.
Averages are calculated in log base 2 and were
standardised (standard deviation normalised to 1 and mean to 0).
Genes were clustered according to these standardised
expression levels by k-means into 12 clusters
followed by ranking by hierarchical clustering using
maxdView software "Super Grouper" plugin (available
from http://bioinf.man.ac.uk/microarray/maxd/). The
functional analyses of differentially expressed genes
were generated through the use of QIAGEN’s
Ingenuity Pathway Analysis (IPA®, QIAGEN Redwood
ingenuity-pathway-analysis/). Microarray data has
been uploaded to the ArrayExpress database
(www.ebi.ac.uk/arrayexpress) under accession number
Immunohistochemistry on FFPE lung biopsies was
performed on the Leica Bond platform, which included
standard procedures for the removal of paraffin wax,
section rehydration, epitope retrieval (Leica Bond
Epitope Retrieval Solution 2, 20 min, Leica Biosystems,
Germany), blocking of endogenous peroxidases for 5
min and blocking with 10% casein for 10 min. The
primary antibody (Anti-PTTG1, Sigma-Aldrich HPA008890,
produced in rabbit) was used at 5 μg/ml for 15 min
followed by treatment with the Leica Bond Refine Kit (8
min, Leica Biosystems, Germany), Leica Bond DAB (10
mins, Leica Biosystems, Germany) and a counterstaining
with hematoxylin prior to rehydration, clearing and
coverslipping. Images were taken on a Leica SCN 400.
Classification of the biopsy samples
FFPE biopsies used in this study originate from the
Manchester Cancer Research Centre Biobank and
sample interpretation was undertaken by three specialist
thoracic pathologists who classified areas of normal
bronchial epithelium, PSCC and ISCC. Pathologists also
subdivided PSCC into low- or high-grade lesions,
according to mild and moderate squamous dysplasia (low
grade dysplasia) and severe squamous dysplasia and
carcinoma in-situ (CIS) (high grade dysplasia). Final
sample classifications were based on two concordant
reviews; those without a majority agreement or technically
uninterpretable were excluded. Using this approach, we
obtained 15 ISCC regions (from surgical specimens) and
20 PSCC regions (from bronchial biopsies) from 25
patients (Fig. 1a, Additional file 2: Table S2). ISCC samples
include 10 primary tumours (5 lymph node-negative
(TN0), 5 lymph node-positive (TNx)) and 5 paired
lymph node metastases (Nx) to the primary TNx
samples. PSCC samples were composed of 8 high-grade and
12 low-grade lesions. The median age of the 17 male
(68%) and 8 female (32%) donors at the time of sampling
was 65years (range 45-79years). 72% (18/25) where
treated for ISCC, 8% (2/25) for head and neck squamous
cell carcinoma and another 8% (2/25) for CIS. Three
patients (12%) had no treatment. A history of smoking
was recorded in 52% (13/25) of the donors.
PCA of expression data and assessment of differential
RNA expression in pre-invasive and invasive squamous
RNA libraries isolated from 15 ISCC (and 10 paired
samples of control normal bronchial epithelia) and 20
PSCC (and 15 paired samples of control normal
bronchial epithelia) using micro-dissection were
amplified and converted into cDNA for hybridisation using
Exon 1.0 ST arrays. Principal Component Analysis
(PCA) was performed in order to visualize variability of
the entire normalized expression data from all arrays
included in this study (Fig. 1b). In this PCA, ISCC and
PSCC data points show a clear tendency of being
separated from each other by mainly the first principal
component (explains 28.13% of the observed variability in
gene expression), which suggests that the general gene
expression in ISCC and PSCC is strikingly different
(Fig. 1b and 95% confidence intervals therein). Controls
paired to ISCC or PSCC were widely distributed across
the PCA plot but did not show any significant clustering
according to sample origin (surgical or bronchial
biopsies) or their various locations (see Additional file 2:
Table S2) (Fig. 1b). However, a PCA of low-grade and
high-grade PSCC showed widely spread low-grade PSCC
data points that overlap with high-grade PSCC data points
Fig. 1 Sample classification, general variability of normalized gene expression and differential gene expression in the selected FFPE PSCC and ISCC
samples. a Sample classification according to independent reviews by three expert histopathologists. Each of the first three columns in the heatmap
corresponds to one of the three involved pathologists (R1, R2 and R3) and rows to the selected samples. The color of each heatmap cell indicates the
corresponding sample classification (see legend, white = no review for technical reasons). The FC column represents the final classification based on
two concordant reviews. b Plot shows the result of a Principal component analysis (PCA) of normalized gene expression data obtained from all the
included samples. ISCC and PSCC samples are clearly separated. Ellipses delineate 95% confidence level for each sample class respectively. c PCA plot
of normalized gene expression data from low- and high-grade PSCC. Samples are widespread and show no clear separation. d PCA plot of normalized
gene expression data from ISCC and high-grade PSCC. TN0, TNx and Nx ISCC samples are widespread and do not show recognizable differences.
High-grade PSCC are clearly separated from ISCC samples. e Venn diagram illustrate the numbers of differentially expressed genes in ISCC and PSCC,
including the intersection between both. f The Venn diagram represents the numbers of differentially expressed genes in high-grade and low-grade
PSCC, including the intersection between both
(Fig. 1c), and similarly, no clear clusters of TN0, TNx or
Nx ISCC data points were observed in a PCA (Fig. 1d),
which suggests that the observed variability of gene
expression changes in these samples do not differentiate
these distinct histological categories. Furthermore, the
observed gene expression was clearly different between
ISCC and high-grade PSCC, which were previously
reported with similar changes to chromosomal structures
and which were suggested to be more prone to malignant
transformations (Fig. 1d) [13, 24, 25].
Following comparison with matched normal epithelium,
1200 RNAs were differentially expressed in ISCC samples
(p < 0.05 and fold change ±1.75, Additional file 2: Table S3).
As might be expected, a considerably smaller number of
184 RNAs were differentially expressed in PSCC samples
(Additional file 2: Table S4). However, 142 (77%) of these
RNAs were abnormally expressed in both PSCC and ISCC
(Fig. 1e, Additional file 2: Table S5). Further comparative
analysis of the high-grade and low-grade preinvasive
samples and their controls confirmed differential expression of
243 (Additional file 2: Table S6) and 183 RNAs (Additional
file 2: Table S7) respectively, of which 99 RNAs (40% and
54% respectively) were differentially expressed in both
lowgrade and high-grade groups (Fig. 1e, Additional file 2:
Table S8). Hence, the obvious difference in the amount of
abnormal gene expression between ISCC and PSCC
suggests a substantial molecular difference between these two
conditions, but no such dramatic changes were found
between low-grade and high-grade PSCC, which in the case
of PSCC reasons against a process of gradually added
modifications to gene transcription. Nevertheless our analysis
identified abnormal gene expression shared between ISCC
and PSCC that supports the assumption of a common
ancestry and the possibility of molecular events that could
drive the progression of squamous lesions.
Genome-wide assessment of coordinately regulated
chromosomal regions in ISCC and PSCC
We used Gene Set Enrichment Analyses (GSEA) with
pre-ranked lists of differently expressed genes derived
from all ISCC or PSCC samples versus paired controls
using the positional gene sets provided by MSigDB in
order to correlate aberrant transcription to chromosomal
positions as previously reported for PSCC and ISCC [22,
24]. Significantly enriched gene up-regulation in ISCC was
found for chromosomes 2p25, 3q21, 3q24, 3q26-28, 6p22,
15q11 and 18q12 (Fig. 2a). Similarly, gene
downregulation in ISCC was significantly enriched at 2q35,
9p13, 10q11, 11p14, 11q12, 12q14 and 18q21 (Fig. 2a).
Interestingly, significant positional gene expression
changes at the positions 2q35, 10q11, 11q12, 12q14
(down-regulation) as well as 3q21 and 18q12
(upFig. 2 Positional enrichment and cluster analysis differentially expressed
genes in PSCC and ISCC. a Genome wide positional enrichment of
aberrant transcription in PSCC and ISCC. Tracks of the circos plot from
outside to inside: chromosome ideogram (except Y chromosome), in
which red lines demarcates the centromere; heatmap of enriched
aberrant transcription in ISCC; heatmap of enriched aberrant transcription
in ISCC. In both heatmaps gene up-regulation is coded in red and gene
down-regulation in blue. b Cluster analysis of genes differentially
expressed in low-grade PSCC, high-grade PSCC or ISCC; (i) heatmap of
standardized gene expression; (ii) z-scores and (iii) histograms of
standardized expression of the selected genes across normal bronchial
epithelia (C), low-grade PSCC (L), high-grade PSCC (H) and ISCC (I); (iv)
profiles of aberrant gene expression for the 12 identified clusters. The
value in brackets represents the number of genes assigned to each of
the 12 clusters
regulation) were detected in both ISCC and PSCC (Fig. 2a).
As reported previously, this analysis confirms elevated
levels of gene expression in ISCC and, to a lesser extent,
PSCC at the distal part of chromosome 3q (Fig. 2a).
Conversely, chromosome 3p confirmed a moderate degree of
down-regulation, most evident in ISCC (Fig. 2a). This data
supports and extends previous observations of structural
changes to chromosomes in PSCC that are thought be
important in the phenotypic transformation to invasive
malignancies and further suggests the propagation of
aberrant transcriptional activity during squamous
carcinogenesis [11, 13, 22].
Pathway analysis of differentially expressed mRNA in
preinvasive and invasive squamous carcinomas confirms a
Ingenuity pathway analysis (IPA) was employed to
identify canonical pathways linked to genes that were
differentially expressed in ISCC, total PSCC, high-grade
PSCC and low grade PSCC (Fig. 3 and Additional file 2:
Table S9). The widespread changes in genes expression
in ISCC samples were associated with 40 significantly
affected pathways (P: <=0.05) including those
characteristic for invasive malignancies such as ‘Cell Cycle: G2/M
DNA Checkpoint Regulation’ (p-value: 2.18e-6, z-score:
−1.414), ‘ATM signaling’ (p-value: 0.00173, z-score:
−1.134), ‘p53 Signaling’ (p-value: 5.75e-5, z-score:
−0.905) and ‘GADD45 Signaling’ (p-value: 9.12e-6) [25–
27]. IPA further suggested ‘Cell Cycle: G2/M DNA
Checkpoint Regulation’, pathways concerned with DNA
and RNA metabolism and inflammation-related
processes to be affected in all contrasts, which is line with
the finding of differential gene expression shared
between ISCC and PSCC. Overall, this pathway analysis
further supports the existence of shared aberrant gene
expression in the analysed samples with potential to
affect cellular functions that may drive squamous
carcinogenesis across pre-invasive and invasive stages.
Fig. 3 Ingenuity pathway analysis (IPA) of aberrant transcription in PSCC and ISCC. (i) The first heatmap column shows all IPA pathways that
are significantly affected in ISCC (p-value < =0.05). The remaining 3 columns indicate the association of these IPA pathways with differentially
expressed genes in all PSCC, high-grade PSCC or low-grade PSCC. (ii) This heatmap summarise the connection between IPA pathways
significantly related to gene expression changes in ISCC (p-value < =0.05) and genes sorted by cluster analysis. Note that genes from cluster 8
were not linked to any IPA pathways associated with ISCC
Cluster analysis refines gene expression profiles across
PSCC and ISCC
A cluster analysis was performed using 1914 genes that
are differentially expressed in either of the low-grade
PSCC, high-grade PSCC or ISCC samples in order to
identify genes that share a particular expression pattern
across these samples. Among the 12 identified clusters,
three (clusters 4, 6 and 12) showed a gradual increase of
expression of 702 genes (36.7% of 1914 genes) across
controls, PSCC and ISCC (Fig. 2b). Signalling pathways
associated with these genes by IPA cover functional
themes of DNA damage response and cell cycle
regulation, including ‘cell cycle: G2/M DNA checkpoint
regulation’ (z-score: −0.447), ‘p53 signaling’, ‘GADD45 signaling’
and ‘mitotic roles of Polo-like kinases’, and other pathways
associated with tumor development, such as ‘Rac
signaling’ (z-score: 2.449), ‘RhoA signaling’, ‘ERK/MAPK
signaling’ (z-score: 2.236) and ‘PI3K/AKT signaling’ (z-score:
2.449) (Fig. 2b and Fig. 3, see Additional file 2: Table S10
for full details) . Two clusters (3 and 5) of 596 genes
(31.1% of 1914 genes) were found gradually down regulated
from control to PSCC and then ISCC. These included
several cytochrome P450 genes (CYP4B1, CYP2B6, CYP4Z1)
that indicates a reduced metabolism of potential carcinogens
(see Additional file 2: Table S10). In addition, we identified
243 RNAs in cluster 11 (12.7% of 1914 genes) that
demonstrated an increase in expression levels only in ISCC that
were linked to changes in the extracellular matrix and an
increase in inflammation-related processes (‘IL-17 signaling,’
‘IL-8 signaling,’ ‘agranulocyte/granulocyte adhesion and
diapedesis,’ see Additional file 2: Table S10). Hence, using
cluster analysis and IPA we were able to sort genes with similar
expression profiles across PSCC and ISCC (see Additional
file 2: Table S11) and to identify biological themes associated
with these profiles, which refines our understanding of the
molecular pathology that underlies squamous
carcinogenesis. As summarised in Fig. 3, IPA pathways associated with
ISCC are mainly, but not exclusively, linked to a gene
Validation of gene expression data in ISCC samples
To validate the microarray data, we undertook
RTPCR to confirm changes in gene expression of four
candidate genes, PTTG1, FN1, HIF1alpha and ITGAV
that have been reported to drive tumorigenesis. As a
result of the availability of independent samples, this
could only be performed in ISCC samples. As with the
microarray data, RNA expression of these four genes
was found to gradually increase across the tested
histology and to peak in ISCC samples. Thus, the
observed upregulation of these four genes was confirmed
by RT-PCR: PTTG1 (P: 0.0015), FN1 (P: 0.0011),
HIF1α (P: 0.0017) and ITGAV (P: 0.0082) in ISCC
samples with fold changes comparable to the results
obtained from the Human Exon arrays (Fig. 4a). In
addition, we performed cross-validation of PTTG1
upregulation using FFPE tissue microarrays of 45
unrelated ISCC and paired normal bronchial epithelia by
immunohistochemistry. The obtained antibody
stainings were quantified by an experienced pathologist
using the H-score system, which revealed a significant
up-regulation of PTTG1 in the cytoplasmic (mean in
tumor: 124.1, mean in control: 79.78, P: 3.97e-08) and
nuclear (mean in tumor: 125.4, mean in control: 30.66,
P: 4.35e-16) compartments of tumor cells in
comparison to cells in paired pseudo stratified epithelia that
were used as controls. As suggested by the H-scores, a
prevalent nuclear localization of PTTG1 protein was
noted in ISCC (Fig. 4b and c). Hence, we detected a
significant up-regulation of PTTG1 in malignant
squamous cells from an independent set of ISCC that
confirms the obtained array data and is in line with
previously published PTTG1 expression in lung and
other cancers .
Understanding the molecular alteration that underpins
malignant squamous transformations within the airway
epithelia is pivotal for the development of novel means of
early detection or treatments of squamous cell carcinomas
at a non-lethal stage [30, 31]. Recently published studies
utilized different grades of FFPE PSCC samples that
revealed incremental increase of chromosomal
rearrangements to occur during the proposed model of squamous
carcinogenesis, and although these findings imply
changing transcriptional profiles, the available knowledge of
genes or pathways with altered transcriptional profiles in
these conditions remains sparse [6, 32]. Only a few studies
so far have successfully addressed this shortcoming and
uncovered a number of genes, e.g., SOX2, CEACAM5 or
SLC2A1, with the potential of inducing malignant traits in
PSCC by amplification or up-regulation in fresh samples
of PSCC and ISCC [13, 22, 33].
Surprisingly, the results from the array data presented
here suggest a massive surge of significantly altered
transcription in ISCC in comparison to PSCC, while levels
between low-grade and high-grade PSCC or the different
stages of ISCC, i.e., TN0, TNx and Nx ISCC, remain rather
indistinguishable. This seems to point to a great leap of
significantly changed gene expression at or after the transition
of PSCC to ISCC rather than a gradual change in gene
expression that would match the previously described stepwise
accumulation of chromosome instability in PSCC and ISCC.
Nevertheless, despite these obvious molecular differences
found between PSCC and ISCC, we were able to identify
abnormal gene expression shared between both. Moreover,
cluster analysis of this shared abnormal gene expression
revealed that the majority of these genes are either
incrementally changed across PSCC and ISCC or exclusively altered
The pathways identified by IPA for genes gradually up
regulated across PSCC and ISCC encompass changes to
biological functions that are reminiscent of malignant cells.
‘G2/M cell cycle checkpoint regulation,’ ‘p53 signaling,’
‘GADD signaling’ or ‘Polo-like kinase signaling’ can be
associated with DNA damage and stress reactions in response to
a chronic exposure to tobacco fumes or other volatile
carcinogens [25, 27, 34–36]. The observed activations of
‘ERK/MAPK Signaling’ (z-score: 2.236) or ‘PI3K/AKT
Signaling’ (z-score: 2.449) are common in many different
cancers and may gradually enhance survival and proliferation of
preinvasive and invasive cells in the included samples .
In addition, the incremental down regulation of the
cytochrome P450 genes CYP2B6 and CYP4B1 in PSCC and
ISCC suggest a reduced catabolism of inhaled carcinogens,
such as those from tobacco fumes, which might in turn
accelerate their detrimental effects in bronchial epithelia and
preinvasive squamous tumors . Hence, the combination
of increased genetic injury, modifications of the G2/M
Fig. 4 Validation of the array data obtained from FFPE PSCC and ISCC
samples. a The bar plot compares the fold changes of mRNA levels for
four individual genes in ISCC tumours and paired controls obtained either
by Human Exon arrays or RT-PCR. b Anti-PTTG1 staining in FFPE ISCC
(Tumour) and paired bronchial mucosa (Normal). In ISCC anti-PTTG1
appears moderately in the cytoplasm and strongly in about ~70% of
nuclei. The used ISCC is unrelated to the samples for the gene expression
study. c H-scores of anti-PTTG1 immunostaining in a set of 45
independent ISCC (Tumour) and paired bronchial epithelia
(Normal). Cytoplasmic and nuclear PTTG1 levels are significantly
raised in ISCC and therefore cross-validate the gene expression
data. Nuclear staining is increased 4x in ISCC whereas the
cytoplasmic was raised 1.5x
checkpoint regulation and early changes of signalling
cascades that underpin cell survival and proliferation could
provide a possible explanation for the occurrence and
propagation of chromosomal rearrangements in PSCC.
PTTG1, which is a known proto-oncogene that under
normal conditions acts as a securin to regulate chromatid
separation during mitosis, has been found up-regulated in
colorectal, thyroid and skin cancer where it is suggested to
cause genetic instability and an increase in aneuploidy .
Hence, the observed increase of PTTG1 on the mRNA and
protein level suggests a similar function of this protein in
invasive squamous carcinomas. Moreover, the observed shift
to a pronounced nuclear localization in ISCC confirms a
previous observation in aggressive-invasive subtypes of
pituitary tumors (prolactin) that suggest a crucial role for
PTTG1 during squamous carcinogenesis .
Genes up regulated in ISCC (cluster 11 in Fig. 2b) are
enriched with a subset of IPA pathways, e.g., ‘leukocyte
extravasation signaling’ (z-score: 1.265), ‘granulocyte
adhesion and diapedesis’, or ‘IL-8 Signaling’ (z-score: 1)
that suggest inflammation-related, microenvironmental
processes such as the infiltration of immune cells,
rearrangements of the connective tissue by metalloproteases
or chemokine signaling in invasive squamous tumors
(Fig. 3 and Additional file 2: Table S10). It is understood
that such a local inflammation may contribute to tumor
growth by the initiation of tumor vascularization, the
local supply of growth stimuli, modifications of the
immune response towards tumor cells and might
eventually facilitate tumor metastasis [39, 40]. Interestingly,
abnormal up regulation of chemokine genes such as
CXCL1, CXCL8, CXCL9 or CXCL10 is also frequently
detected in pre-invasive tumors, which might be
indicative of a response to microbiological infections or an
earlier onset of the inflammation-related processes
observed in ISCC samples.
Despite the known challenges to molecular studies that
come with the use of FFPE material, we believe that our
transcriptome analysis of preinvasive and invasive
squamous FFPE tumor samples from the lower airways
provides valuable insights into the genomic changes that
occur during squamous carcinogenesis. The analysis of
our Human Exon 1.0 ST array data confirms the
previously published prevalence of segmental amplifications
on chromosome 3q through enrichment analysis of
abnormal transcription in PSCC and ISCC, and extends
this analysis to all chromosomes (apart Y), which
suggests further changes to chromosomal structures and
consequently changes to gene expression being present
in PSCC and ISCC. In addition, the functional analysis
of this array data by IPA revealed alterations of
biological functions in PSCC that confirm and extend
recent findings [11, 22, 33]. The included PSCC and
ISCC samples were not longitudinally harvested from
the same bronchial lesion and are therefore unlikely to
be clonally related. Nevertheless, we were able to
identify common patterns of aberrant transcription during
squamous carcinogenesis by sorting genes according to
their abnormal expression profiles in PSCC and ISCC
and associate these genes with biological functions
related to developing malignancies. Consequently, we can
propose alterations to cell cycle checkpoint regulation,
DNA damage response and, among other signal
transduction cascades, PI3K/AKT signaling as early events
during squamous carcinogenesis, and suggest the
upregulations and nuclear localization of PTTG1 as a novel
biomarker for ISCC.
Additional file 2: Table S1. RT-PCR primer. Table S2. Patient and
sample information. Table S3. Differential RNA expression in ISCC versus
paired controls (normal histology). Table S4. Differential RNA expression
in PSCC versus paired controls. Table S5. Differential RNA expression in
PSCC and ISCC. Table S6. Differential RNA expression in high-grade PSCC
versus paired controls. Table S7. Differential RNA expression in low-grade
PSCC versus paired controls. Table S8. Differential RNA expression in
high-grade PSCC and low-grade PSCC. Table S9. Ingenuity Pathway
Analysis. Table S10. IPA results for genes associated with Clusters 1-12.
Table S11. RNA expression profiles across PSCC and ISCC.
(DOC 5260 kb)
cDNA: Complementary DNA; CIS: Carcinoma in-situ; DNA: Deoxyribonucleic
acid; FFPE: Formalin fixed and paraffin embedded; GSEA: Gene set
enrichment analysis; IPA: Ingenuity pathways analysis; ISCC: Invasive
squamous cell carcinoma; LCM: Laser capture microscopy; lncRNA: Long
non-coding RNA; Nx: Lymph node metastasis; PCA: Principal component
analysis; PSCC: Preinvasive squamous cell carcinoma; RNA: Ribonucleic acid;
RT-PCR: Real-time PCR; TN0: Lymph node-negative; TNx: Lymph
Availability of data and material
Microarray data has been uploaded to the ArrayExpress database
(www.ebi.ac.uk/arrayexpress) under accession number E-MTAB-3950.
AK designed and conducted the experiments, analysed the obtained data
and wrote the manuscript. LZ processed the array data, and designed and
conducted all data analyses together with AK. LJ, KK and JG performed
histopathological reviews of all included samples. ML and RB designed the
study and wrote the manuscript together with AK. All authors have given
their approval for the publication of this manuscript.
Richard Booton received research grants from Astra-Zeneca and Lilly Oncology
UK, advisory board fees from Astra-Zeneca, Lilly Oncology UK, MSD and Chiesi,
and speaker honoraria from Lilly Oncology UK, Astra-Zeneca and Chiesi. The
other authors declare that they have no competing interest.
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