Karaglani et al. BMC Cancer (2015) 15:694
DOI 10.1186/s12885-015-1725-8
RESEARCH ARTICLE
Open Access
Development of novel real-time PCR
methodology for quantification of COL11A1
mRNA variants and evaluation in breast
cancer tissue specimens
Makrina Karaglani1, Ioannis Toumpoulis2, Nikolaos Goutas3, Nikoleta Poumpouridou1,
Dimitrios Vlachodimitropoulos3, Spyridon Vasilaros4, Ioannis Rizos5 and Christos Kroupis1*
Abstract
Background: Collagen XI is a key structural component of the extracellular matrix and consists of three alpha
chains. One of these chains, the α1 (XI), is encoded by the COL11A1 gene and is transcribed to four different
variants at least (A, B, C and E) that differ in the propensity to N-terminal domain proteolysis and potentially in the
way the extracellular matrix is arranged. This could affect the ability of tumor cells to invade the remodeled stroma
and metastasize. No study in the literature has so far investigated the expression of these four variants in breast
cancer nor does a method for their accurate quantitative detection exist.
Methods: We developed a conventional PCR for the general detection of the general COL11A1 transcript and
real-time qPCR methodologies with dual hybridization probes in the LightCycler platform for the quantitative
determination of the variants. Data from 90 breast cancer tissues with known histopathological features were
collected.
Results: The general COL11A1 transcript was detected in all samples. The developed methodologies for each
variant were rapid as well as reproducible, sensitive and specific. Variant A was detected in 30 samples (33 %) and
variant E in 62 samples (69 %). Variants B and C were not detected at all. A statistically significant correlation was
observed between the presence of variant E and lymph nodes involvement (p = 0.037) and metastasis (p = 0.041).
Conclusions: With the newly developed tools, the possibility of inclusion of COL11A1 variants as prognostic
biomarkers in emerging multiparameter technologies examining tissue RNA expression should be further explored.
Key words: COL11A1, Variants, Breast cancer, Real-time qPCR
Background
Breast cancer is the most frequent cancer among women
both in more and in less developed World regions and
the second most commonly occurring form of cancer
globally when both sexes are accounted [1]. The search
for new prognostic and predictive tissue biomarkers is
considered imperative for improving classification of this
* Correspondence: ckroupis@med.uoa.gr
1
Department of Clinical Biochemistry and Molecular Diagnostics, Attikon
University General Hospital, University of Athens Medical School, Rimini 1 St.,
Haidari 12462, Greece
Full list of author information is available at the end of the article
common type of cancer and for avoiding excessive and
unnecessary exposure to toxic and ineffective treatments.
One of such biomarkers could be collagen as it is a
key structural component of the extracellular matrix
(ECM) that also serves as a modulator of diverse signaling
pathways. Collagen XI belongs to the minor fibrillar subcategory in the collagen family and it is responsible for the
proper conformation of collagen II and the formation of
thin fibrils of developing or under remodeling tissues. Its
highest expression values have been found in the articular
cartilage and vitreous humor [2, 3]. It is a heterotrimeric
protein, consisting of three alpha chains (a1, a2 and a3)
that are organized into a triple helix formation. Both
© 2015 Karaglani et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
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(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Karaglani et al. BMC Cancer (2015) 15:694
a1(XI) and a2(XI) chains are unique gene products
however, a3(XI) is a an hyperglycolsylated version of the
collagen a1(II) chain [4, 5]. The a1(XI) chain is encoded by
the gene COL11A1 located at genomic locus 1p21.1. It is
initially synthesized as procollagen XI and then its C and
N termini may be cleaved with proteolysis as soon as they
are secreted from the cell [6]. The molecule of the a1(XI)
chain has a characteristic globular N-terminal domain
(NTD) consisting of a variable region and an aminopropeptide (Npp) that seems responsible for the steric
hindrance exerted by collagen XI to other molecules in
the ECM [7, 8]. Therefore, when collagen a1(XI) protein is
overexpressed -as it has been proven in human ascending
thoracic aortic aneurysms-, it leads to thinner collagen
fibers and decreased tensile strength in the tissue [9].
It has also been demonstrated that expression of collagens alters in neoplasms, a fact that could affect the ability
of tumor cells to break through the basal membrane and
initiate local or distant metastases [10–12]. COL11A1 upregulation in tumor tissue versus normal tissue has been
demonstrated in gastric cancer [13], non-small cell lung
cancer [14, 15], pancreatic cancer [16] and this expression
has been associated with metastasis in oral cavity and oropharynx [17], ovarian [18] and lung cancer [15]. In ovarian
cancer, it leads to a stromal desmoplastic reaction in
cancer-associated fibroblasts, a feature that is associated
with the epithelial-to-mesenchymal transition (EMT)
phenotype [19]. In a significant study for breast cancer, COL11A1 is shown to be significantly upregulated
in infiltrating tumor lesions compared to their in situ
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compartments and adjacent stroma [20]. In another
study though, collagen a1(XI) appears to be downregulated in stroma surrounding breast cancer but also in
metastasized tumors [21]. In addition, COL11A1 is differentially expressed between primary breast cancers
that metastasize and their corresponding lymph node
sites where its expression seems that is no longer needed
[22, 23]. The detection of such quantitative changes in
COL11A1 expression could lead to novel approaches
regarding prognostic and/or predictive tools for breast
cancer.
COL11A1 gene consists of 67 exons and due to alternative splicing of four exons (6, 7, 8 and 9), there exist
possibilities of production of at least eight different variants
during its transcription [24–26]. Four different splicing variants of COL11A1 mRNA termed A, B, C and E, (Fig. 1)
have been deposited in GenBank (Table 1) and are known
to differ in their propensity for NTD proteolysis [27] and
potentially in the way the extracellular matrix is arranged.
No study in the literature has so far investigated the expression of the four known variants in breast cancer (as well as
cancer in general) nor does a method for their accurate
quantitative detection exist.
In our study we validated novel, specific and sensitive
real-time qPCR (quantitative Polymerase Chain Reaction)
methodologies for COL11A1 mRNA variants in the Lightcycler platform and obtained quantitative data for their
distribution in breast tumors. Furthermore, we sought
to determine whether there is a correlation between
differential expression of these COL11A1 splice variants
Fig. 1 Structure of COL11A1 splice variants A, B, C and E and approximate location of primers and set of dual probes in respect to each different
variant in the design of the novel COL11A1 assays: variants A and C employ a common set of probes, variants B and E employ a second different
common set of probes and a common reverse primer
Karaglani et al. BMC Cancer (2015) 15:694
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Table 1 GenBank Accession numbers used for the detection of
the COL11A1 mRNA splice variants and the general transcript
and the sizes of the expected real-time PCR products according
to our design strategy
Name
GenBank
Accession number
Expected PCR
product size
Variant Α
NM_001854
439
Variant Β
NM_080629
379
Variant C
NM_080630
206
Variant Ε
NM_001190709
259
NG_008033.1
132
General transcript
with tumor histopathological parameters and patient
follow-up data in order to explore the possibility of
their inclusion as prognostic biomarkers in emerging
multiparameter technologies examining tissue RNA expression (analogous to Oncotype, MammaPrint, HOXB13:
IL17BR and molecular grade index 8-gene panel, Endopredict and PAM50) [28–32].
Methods
Patients
Ninety tissue specimens were collected from the Pathologic Anatomy Laboratory of Evgenidio Hospital from
consecutive female breast cancer patients residing mostly
in the Athens Metropolitan area during the period 2007–
2011. Main criteria were the availability of the material,
the presence of >70 % of tumor cells in the frozen section
and the written informed consent of the patients (family
history was not used as a criterion for inclusion in the
study). The study was approved by both bioethics and
scientific committees of the Evgenidio Hospital. Most
of the specimens originated from lumpectomies and
the mean size was 2.0 cm (range: 1.0–5.5 cm). A small
part of the resected specimens at surgery was immediately
stored in RNAlater (Life Technologies Ambion, USA) for
1–2 days at 4 °C and then stored at −80 °C until total RNA
extraction for molecular collagen analysis. The larger part
of the resected specimens was embedded in formalin-fixed
paraffin blocks and used for histopathological examinations.
The majority of the tumors (80 %) were ductal infiltrating
carcinomas (the rest lobular mostly, papillary and mucinous) and were classified according to the BloomRichardson grading system as grade 1 (3 samples), grade 2
(57 samples) and grade 3 (22 samples). Grades 1 and 2
were grouped together because of the small number of
grade 1 tumors. The presence or absence of estrogen and
progesterone hormone receptors was investigated with
routine immunohistochemistry (IHC) and positivity was
defined as a score >1 in IHC. Oncogene HER2 overexpression was examined with IHC and when the score was 2 in
the 0–3 scale, it was further examined with chromogenic
in situ hybridization (CISH). Therefore, we were able to
dichotomize all samples as being either HER2 negative or
positive. Classification into the triple negative breast cancer (TNBC) category was assigned if a tumor was negative
for estrogen and progesterone hormone receptors and
HER2 overexpression. Lymph node involvement was also
noted and the presence of any recurrences or metastasis
was recorded for those patients with follow-up data. The
characteristics of the 90 tissues and patients with breast
cancer are summarized in Table 2.
Total RNA Isolation
Total RNA was extracted with the use of the NucleoSpin
RNA kit (Macherey-Nagel, Germany) after passing the
liquid N2-snap frozen tissues through special filter columns
(shredders) in order to homogenize them and to reduce
Table 2 Clinical characteristics of the 90 tissue samples from
patients with breast cancer
Variable
Value
Age Group, n (%)
< = 50 years
26 (35.6)
> 50 years
47 (64.4)
Tumor Size, n (%)
≤ 2.0 cm
59 (67.0)
> 2.0 cm
29 (33.0)
Histopathological Type, n (%)
Lobular infiltrating & rest
18 (20.0)
Intraductal infiltrating
72 (80.0)
Lymph-node Involvement, n (%)
Negative (Ν0)
55 (67.1)
Positive (Ν+)
27 (32.9)
Metastasis, n (%)
Negative
47 (85.5)
Positive
8 (14.5)
Grade, n (%)
Low (1–2)
60 (73.2)
High (3)
22 (26.8)
Estrogen-receptor Status, n (%)
Negative
21 (23.9)
Positive
67 (76.1)
Progesterone-receptor Status, n (%)
Negative
46 (52.3)
Positive
42 (47.7)
HER2 Overexpression Status, n (%)
Negative
72 (81.8)
Positive
16 (18.2)
TNBC status, n (%)
Yes
17 (19.3)
No
71 (80.7)
Karaglani et al. BMC Cancer (2015) 15:694
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viscosity. DNA was removed by an in-column recombinant DNase treatment. Total RNA was eluted in
RNase-fee water and stored at −80 °C until further use.
The absolute measurement of RNA concentration was
determined by the Quant-iT RNA Assay kit in the
Qubit 1.0 fluorometer (Life Technologies Invitrogen, USA)
that employs a dye specific for RNA and not for DNA.
Complementary DNA Synthesis
cDNA was synthesized from 1 μg of total RNA and random hexamers in a 20 μL total volume, according to the
Transcriptor First Strand cDNA Synthesis kit (Roche
Applied Science, Switzerland) instructions. It was organized in large batches and appropriate controls were
added: a no-RNA blank (RNA−) control, a Reverse
Transcriptase-negative (RT−) control and a 100 ng RNApositive (RNA+) control for Porphobilinogen deaminase
(PBGD) gene provided by the kit. The cDNA samples
were then stored at −20 °C. In order to test the quality and
purity of RNA samples, the resulting cDNA was amplified
in a control PCR method of the actin reference gene as
previously described [33]. cDNA samples that are free of
containing genomic DNA produce a unique fragment of
587 base pairs (bp) (and not the additional fragment of
1122 bp if genomic DNA exists). The efficiency of cDNA
synthesis was also examined with conventional PCR for
the PBGD gene with primers provided by the kit: the same
intensity of a 151 bp band was obtained each time for the
RNA+ control (also many tumor cDNA samples were run
alongside as an additional control of quality and purity of
the RNA samples).
Conventional PCR for the general COL11A1 transcript
In order to detect the presence or not of the general
COL11A1 transcript, a simple conventional PCR was
developed. Suitable primers were designed, common for all
splice variants of COL11A1 gene in a well conserved region,
by using the CLC Free Workbench version 4 software
(Qiagen Bioinformatics, Aarhus, Denmark). The primers
shown in Table 3 are located in the junction of exons 48/
49 and 51, respectively. For each reaction, 1.5 μL of cDNA
was placed in a 23.5 μL reaction mixture containing
12.5 μL of BioMix Red DNA polymerase (Bioline,
Germany), 1.5 μL of the supplied MgCl2 (50 mM), 1 μL of
the primers (final concentration: 0.04 pmol/μL) and
ddH2O. The cycling protocol was consisted of an initial 4min denaturation step at 94 °C, followed by 40 cycles of
denaturation at 94 °C for 30 s, annealing at 57 °C for 30 s,
extension at 72 °C for 30 s and a final 5 min extension step
at 72 °C. Checking for the proper size of 132 bp was performed with electrophoresis of a 10 μL PCR product on
2 % w/v agarose gel along with MW marker (PCR Marker,
New England Biolabs, USA), staining with ethidium bromide and visualization under ultraviolet (UV) light.
Real-time quantitative PCR methodology for the COL11A1
variants detection
For the quantification of COL11A1 transcript variants,
suitable pairs of primers and hybridization sets of dual
probes (labeled with fluorescein donor and LC-Red 640
acceptor dyes) were designed by aligning all four variants
mRNA in the CLC Free Workbench version 4 program in
order to select for non-homologous regions for their binding. The choice of the primers was based on the presence
or absence of exons 6, 7, 8 and 9 which differs in different
variants uniquely. Transcripts A and C employ a common
set of dual probes for their detection but different primers;
the same strategy is used for B and E transcripts (Fig. 1).
The sequences of primers and probes synthesized by TIB
MOLBIOL (Germany) are shown in Table 3.
Real-time quantitative PCR was performed with the
LightCycler 1.5 platform (Roche Applied Science) in
glass capillaries in a total volume of 10 μL. For transcript
variant A, 1 μL of the sample cDNA was added to 0.3 μL
of the forward primer VARAC F (final concentration: 0.6
pmol/μL), 0.1 μL of the reverse primer VARAEB R (final
Table 3 Sequences of primers and probes of COL11A1 transcript variants
Name
Oligonucleotide Sequence, 5’-3’
Variant A & C Forward Primer
VARAC F
TGTGAGCATTATAGTCCAGACTGTGA
Variant E Forward Primer
VARE F
CAGATAGATGAGGCAAACATCG
Variant B Forward Primer
VARB F
AAGAAGATGAGGACAGTGGCTA
Variant C Reverse Primer
VARC R
CCATGGCCATTTATCTCCGT
Variant A, E & B Reverse Primer
VARAEB R
CATATTCGCCTAAATCTCCATCTAC
Variant A & C Sensor Probe
VARAC FL
TCCTCAGTTACAGTGGGTCCCTCTGTTAC-FL
Variant A & C Anchor Probe
VARAC LC
LC 640-CTTTCAGCCTCTTTATACTCTGCTTCCCCA
Variant E & B Sensor Probe
VAREB FL
GCTCATTTGTCCCAGAAATGCC-FL
Variant E & B Anchor Probe
VAREB LC
LC 640-AGGAGCTTCTGTCTGGTAACTTTCCATTGT
General COL11A1 Forward Primer
F
AATGGAGCTGATGGACCACA
General COL11A1 Reverse Primer
R
TCCTTTGGGACCGCCTAC
Karaglani et al. BMC Cancer (2015) 15:694
concentration: 0.2 pmol/μL), 0.6 μL of the probe VARAC
FL (final concentration: 0.18 μΜ), 0.6 μL of the probe
VARAC LC (final concentration: 0.18 μΜ), 2 μL of
25 mM MgCl2 (Roche, final concentration: 5 mM),
1 μL of the LightCycler FastStart DNA Master HybProbe 10× reagent (Roche Applied Science) and ddH2O
to the final volume (for variant C, the VARC R primer
is used instead of VARAEB R). For transcript variant E,
1 μL of the sample cDNA was added to 0.3 μL of the
forward primer VARE F (final concentration: 0.6 pmol/μL),
0.1 μL of the reverse primer VARAEB R (final concentration: 0.2 pmol/μL), 0.5 μL of the probe VAREB FL (final
concentration: 0.15 μΜ), 0.5 μL of the probe VAREB LC
(final concentration: 0.15 μΜ), 1.2 μL of 25 mM MgCl2
(Roche, final concentration: 3 mM), 0.6 μL of DMSO, 1 μL
of the LightCycler FastStart DNA Master HybProbe 10× reagent and ddH2O to the final volume (for variant B, the
VARB F primer is used instead of VARE F). All reactions
were initiated with a 10-min denaturation at 95 °C and terminated with a 30 s cooling step at 40 °C. The cycling
protocol consisted of denaturation step at 95 °C for 10 s,
annealing at 52 °C for variant A/50 °C for variant E for 30 s
and extension at 72 °C for 30 s and repeated for 42 cycles.
In each preparation, alongside the unknown samples,
standards, blank samples and positive controls samples
(that were confirmed by DNA sequencing analysis)
were included. Fluorescence detection was performed
at the end of each extension step for 0 s at the F1 channel. For quantification, an external standard curve was
obtained by using the transcript variants PCR amplicon
standards (prepared as described below) and plotting
the log number of copies corresponding to each standard
versus the value of their corresponding quantification
cycle (Cq). Real-time qPCR products were additionally
checked: i) for size and purity by inversion of the glass capillaries and electrophoresis on 2 % w/v agarose gels (the
expected PCR product sizes are provided in the last column of Table 1) and ii) for nucleotide composition. The
Sanger DNA sequencing methodology was performed
with a PCR product column clean-up (NucleoSpin Gel
and PCR Clean-up kit, Macherey-Nagel, Germany) and a
cycle sequencing reaction employing the Big Dye 1.1 reagent (Life Technologies Applied Biosystems, USA). The
electrophoregrams in the ΑBI Prism 310 Genetic Analyzer
were manually base-called with the Chromas Lite 2.01
software (Technelysium Pty, Tewantin, Australia) and
compared with the expected sequence with the BLAST
tool of PubMed. Also the Tm’s of the amplicons were
determined immediately after amplification, by melting
curve analysis performed in the LightCycler. The melting curve protocol included raising the temperature at
95 °C, cooling at 55 °C for 15 s and slow heating to 95 °C
at a rate of 0.1 °C/s, during which time fluorescence measurements were continuously collected in the F2 channel
Page 5 of 16
and their first derivate (−d(F2)/dT vs. T) was used for the
determination of Tm.
To establish specific, sensitive and reproducible real-time
quantitative assays, we performed extensive optimization of
primers, probes and MgCl2 concentrations as well as of the
reaction temperatures and cycles. The analytical evaluation
of assays was performed with the prepared standards. For
each splice variant detected in our samples, a calibration
curve was generated from serial dilutions e.g. ranging from
5 × 105 to 5 × 101 copies/μL of variant A and 5 × 106 to 5 ×
101 copies/μL of variant E. The reproducibility (calculated
as coefficients of variation, CVs), the efficiency of the PCR
reaction (expressed as E = 10-1/slope) and the limit of detection for our assays (defined as the concentration detected
in 95 % of trials) were also determined in order to complete
the validation file of the novel methodologies with the
established MIQE guidelines [34].
Preparation of the standards
For the development and analytical evaluation of our assays, we generated and used as standards PCR amplicons
corresponding to the COL11A1 splice variants studied.
For this reason, a significant amount of the amplicons was
produced by many PCR reactions of the same cDNA preparation in a positive sample for each variant. The amplicons
were pooled, purified by columns and quantitated by the
Quant-iT dsDNA Broad-Range Assay kit (Life Technologies Invitrogen, USA) in the Qubit 1.0 fluorometer. The
concentration was converted to copies per microliter by
using the Avogadro constant and the product’s molecular
weight (number of bases of the PCR product multiplied by
the average molecular weight of a pair of nucleic acids,
which is 660), as described elsewhere [35]. Then, serial
dilutions of the above-quantified stock amplicon solutions
were prepared for each variant and kept in aliquots
at −20 °C; they were used throughout the study as external
standards for the absolute quantification of COL11A1
transcript variants.
Normalization
Normalization facilitates experimental problems concerning the inherent variability of RNA level of expression,
variability of extraction protocols and presence of inhibitors [36]. In our assay, we ensured that the starting
tissue material for RNA extraction had similar initial
size and weight (approximately 30 mg) and we performed
normalization against the same amount of total RNA
(1 μg) that was used for cDNA synthesis in all samples as
suggested by previous studies [36–38].
Statistical analysis
The COL11A1 variants were analyzed statistically both
in a qualitative way (presence or absence of the variant)
with either Pearson χ2 or Fischer’s exact test and in a
Karaglani et al. BMC Cancer (2015) 15:694
quantitative way: the positive samples were divided in
two categories (high or low category) depending whether
their copies were above or below a certain percentile
value of copies (e.g. the 25th, 50th or median, the 75th)
and 2 × 2 cross-tabulations were performed. Also the
median copy values of the two low and high categories
were compared in each category of the clinicopathological
characteristics examined (all divided in two categories as
well) with the Mann–Whitney U test for continuous variables that are non-normally distributed (as determined
with the Kolmogorov-Smirnov test). The Spearman correlation coefficient was used as a measurement of correlation
for continuous non-normally distributed variables. Probit
statistical analysis was used for estimation of the limit
of detection in our novel assays. The association of
COL11A1 transcript variants with long-term metastasis
was analyzed with the Kaplan-Meier method and survival curves were compared with the log-rank test. For
all tests performed, a two-sided p value of <0.05 was
considered significant. Data analysis was carried out
with the SPSS version 21.0 statistical software package
for Windows (IBM - SPSS Inc., USA).
Results
Conventional PCR for the general COL11A1 transcript
All extracted RNAs were of adequate quantity -as measured in the fluorometer- and quality as they produced a
single pure actin band in the gels. The general COL11A1
transcript was detected in all samples (Additional file 1:
Figure S1) as revealed from a distinct 132 bp band in all
PCR products.
Development, analytical and clinical evaluation of the
real-time qPCR methodology for the COL11A1 variants
detection
Real-time qPCR methodologies were developed adequately,
were rapid and specific as it can be seen in Additional file
2: Figures S2 and Additional file 3: Figure S3 when the
real-time PCR products from positive cDNA samples
were extracted and run on a 2 % w/v agarose gel: variants A and E produced the expected bands at sizes of
439 and 259 bp. Portions of Sanger DNA Sequencing
electropherograms of these transcripts A and E are shown
in Additional file 4: Figures S4 and Additional file 5: Figure
S5 and are aligned fully with the GenBank deposited variant sequences. Variants B and C were not detected in any
tumor cDNA sample, therefore no further validation
procedures were performed for these two transcripts.
The analytical sensitivity and linearity of the proposed
COL11A1 A and E transcript real-time qPCR assays were
determined by using the external standards of each variant
with known concentrations that were prepared as described above. Our standard curves showed linearity over
the entire quantification range (5 × 105 to 5 × 101 variant
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A copies/μL and 5 × 106 to 5 × 101 variant E copies/μL)
while the correlation coefficients were about 0.99 in all
cases, indicating a precise log–linear relationship (Figs. 2
and 3). The mean slope and intercept of the standard
curve of variant A were −3.22 ± 0.19 and 36.81 ± 0.52 respectively (n = 5), while the PCR reaction efficiency was
2.05 ± 0.04 (CV % = 1.97), very close to the ideal value
which is 2.00. About variant E, the mean slope and intercept of the standard curve were −3.66 ± 0.34 and 41.80 ±
2.49 respectively (n = 5), while the efficiency was 1.88 ±
0.10 (CV % = 5.39). The between-run CV’s for the Cq
values of the standards, analyzed in five different experiments over a period of 1 month, ranged from 0.78 to
1.84 % for variant A and from 2.62 to 3.88 % for variant E.
The analytical limit of detection as determined from probit statistical analysis was 19 copies/μL for variant A and
16 copies/μL for variant E. The Tm from all positive variant A amplicons was calculated to be 69.9 (±1.0) °C, while
the corresponding for variant E was 65.3 (±1.2) °C (representative samples in Figs. 4 and 5).
Among the 90 breast cancer tissues investigated, variant A was detected in 30 tumor cDNA samples (33 %)
and variant E in 62 (69 %). Characteristic amplication
plots of tumor cDNA samples for COL11A1 variants A
and E are shown in Figs. 6 and 7. In 28 samples, both A
and E variants were detected (31 %) while in 26 samples,
no variant was detected (29 %). For variant A, the mean
value of copies for the positive samples was 7.58 × 104
copies/μg of total RNA, while the median value was
3.28 × 105 copies/μg of total RNA (range 2.36 × 1026.85 × 105 copies/μg of total RNA). For variant E, the mean
value of copies for the positive samples was 3.56 × 105 copies/μg of total RNA, while the median value was 4.97 × 104
copies/μg total RNA (range 3.51 × 102-3.86 × 106 copies/μg
of total RNA).
COL11A1 transcript variants expression in relation to
clinicopathological features
Statistical results are shown in Tables 4, 5 and 6. In the
qualitative way, a statistically significant correlation was
observed between the presence of variant E and lymph
nodes involvement (p = 0.037) and metastasis (p = 0.041)
(Table 5). No association was detected with the other
classical prognostic factors in breast cancer. When patient
tumors were classified in the higher-copy number group
of the 50th percentile and were also positive for variant A,
they showed correlation with the better prognosis lobular
histopathological type (p = 0.042, Table 4). The two main
findings in the qualitative stats, the lymph-node involvement and the metastasis for the variant E showed a trend
when examined in the 25th percentile subcategories: 0.058
and 0.081 respectively (data not shown).
When examining the simultaneous expression of variant
A and variant E, that was significantly correlated with the
Karaglani et al. BMC Cancer (2015) 15:694
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Fig. 2 Representative standard curve for the real-time qPCR detection of COL11A1 variant A: amplicons ranging from 5 × 105-5 × 101 copies A/μl
serve as standards, the blue line is the blank of the assay
Fig. 3 Representative standard curve for the real-time qPCR detection of COL11A1 variant E: amplicons ranging from 5 × 106-5 × 101 copies E/μl
serve as standards
Karaglani et al. BMC Cancer (2015) 15:694
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Fig. 4 Results from the real-time qPCR assay for COL11A1 variant A in tumor breast cDNA samples: five positive samples, two negative and a blank
(green line)
Fig. 5 Results from the real-time qPCR assay for COL11A1 variant E in tumor breast cDNA samples: four positive samples, one negative and a
blank (gold line)
Karaglani et al. BMC Cancer (2015) 15:694
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Fig. 6 Melting point (Tm) of COL11A1 variant A amplicon: in this –d(F2)/dT vs. temperature graph, it is derived from the mean of two strong
positive and a weak cDNA sample
Fig. 7 Melting point (Tm) of COL11A1 variant E amplicon: in this –d(F2)/dT vs. temperature graph, it is derived from the mean of four positive
cDNA samples
Number of A copies (percentile: 50th) (quantitative)
Presence or absence of variant A (qualitative)
Clinical features
N (%)
Absence
n (%)
Presence
n (%)
Age Group
2
Pearson χ or Fisher’s exact
Ν (%)
p-value
Low
High
n (%)
n (%)
0.060
< =50 years
26 (35.6)
22 (42.3)
4 (19.0)
> 50 years
47 (64.4)
30 (57.7)
17 (81.0)
Tumor Size
4 (19.0)
2 (16.7)
2 (22.2)
17 (81.0)
10 (83.3)
7 (77.8)
0.912
Pearson χ2 or Fisher’s exact
Copies of variant A (for positive samples)
Median
p-value
p-value
1.000
0.420
33,246
99,636
1.000
0.941
≤ 2.0 cm
59 (67.0)
40 (66.7)
19 (67.9)
19 (67.9)
10 (71.4)
9 (67.9)
96,274
> 2.0 cm
29 (33.0)
20 (33.3)
9 (32.1)
9 (32.1)
4 (28.6)
5 (35.7)
38,092
Lobular & rest
18 (20.0)
13 (21.7)
5 (16.7)
5 (16.7)
0 (0.0)
5 (33.3)
Intraductal infiltrating
72 (80.0)
47 (78.3)
25 (83.3)
25 (83.3)
15 (100.0)
10 (66.7)
Histopathological Type
0.576
Lymph-node Involvement
0.042
0.825
0.071
108,055
69,402
0.683
0.500
Negative (Ν0)
55 (67.1)
38 (67.9)
17 (65.4)
17 (65.4)
7 (58.3)
10 (71.4)
106,233
Positive (Ν+)
27 (32.9)
18 (32.1)
9 (34.6)
9 (34.6)
5 (41.7)
4 (28.6)
37,995
Negative M0
47 (85.5)
32 (91.4)
15 (75.0)
15 (75.0)
7 (70.0)
8 (80.0)
Positive M1
8 (14.5)
3 (8.6)
5 (25.0)
5 (25.0)
3 (30.0)
2 (20.0)
Metastasis
0.124
Grade
1.000
0.352
0.570
96,198
78,617
0.683
0.328
Low (1–2)
60 (73.2)
42 (76.4)
18 (66.7)
18 (66.7)
9 (60.0)
9 (75.0)
87,999
High (3)
22 (26.8)
13 (23.6)
9 (33.3)
9 (33.3)
6 (40.0)
3 (25.0)
30,156
Negative
21 (23.9)
12 (20.3)
9 (31.0)
9 (31.0)
7 (46.7)
2 (14.3)
Positive
67 (76.1)
47 (79.7)
20 (69.0)
20 (69.0)
8 (53.3)
12 (85.7)
Estrogen-receptor Status
0.269
Progesterone-receptor Status
0.109
0.403
0.059
20,319
100,602
1.000
0.825
Negative
46 (52.3)
29 (49.2)
17 (58.6)
17 (58.6)
9 (60.0)
8 (57.1)
89,068
Positive
42 (47.7)
30 (50.8)
12 (41.4)
12 (41.4)
6 (40.0)
6 (42.9)
56,729
Negative
72 (81.8)
51 (85.0)
21 (75.0)
21 (75.0)
10 (71.4)
11 (78.6)
Positive
16 (18.2)
9 (15.0)
7 (25.0)
7 (25.0)
4 (28.6)
3 (21.4)
HER2 Overexpression Status
0.257
1.000
0.819
0.254
93,872
31,872
0.169
0.146
Yes
17 (19.3)
11 (18.6)
6 (20.7)
6 (20.3)
5 (33.3)
1 (7.1)
90,085
No
71 (80.7)
48 (81.4)
23 (79.3)
23 (79.3)
10 (66.7)
13 (92.9)
20,493
Page 10 of 16
TNBC, n (%)
Mann–Whitney
Karaglani et al. BMC Cancer (2015) 15:694
Table 4 Association of COL11A1 variant A with clinicopathological characteristics in breast cancer tissues
Number of E copies (percentile: 50th) (quantitative)
Presence or absence of variant E (qualitative)
Clinical features
N (%)
2
Absence
Presence
Pearson χ or Fisher’s exact
n (%)
n (%)
p-value
Age Group
Ν (%)
Low
High
Pearson χ2 or Fisher’s exact
n (%)
n (%)
p-value
0.450
< =50 years
26 (35.6)
10 (41.7)
16 (32.7)
> 50 years
47 (64.4)
14 (58.3)
33 (67.3)
Tumor Size
Copies of variant E (for positive samples)
Median
p-value
0.478
16 (32.7)
9 (37.5)
7 (28.0)
33 (67.3)
15 (62.5)
18 (72.0)
0.912
0.639
579,678
351,707
0.273
0.875
≤ 2.0 cm
59 (67.0)
19 (67.9)
40 (66.7)
40 (66.7)
22 (73.3)
18 (60.0)
493,555
> 2.0 cm
29 (33.0)
9 (32.1)
20 (33.3)
20 (33.3)
8 (26.7)
12 (40.0)
106,231
Lobular & rest
18 (20.0)
6 (21.4)
12 (19.4)
12 (19.4)
7 (22.6)
5 (16.1)
Intraductal infiltrating
72 (80.0)
22 (78.6)
50 (80.6)
50 (80.6)
24 (77.4)
26 (83.9)
Histopathological Type
0.820
Lymph-node Involvement
0.520
0.037
0.498
372,702
352,048
0.435
0.130
Negative (Ν0)
55 (67.1)
23 (82.1)
32 (59.3)
32 (59.3)
14 (53.8)
18 (64.3)
550,330
Positive (Ν+)
27 (32.9)
5 (17.9)
22 (40.7)
22 (40.7)
12 (46.2)
10 (35.7)
145,674
Negative M0
47 (85.5)
20 (100.0)
27 (77.1)
27 (77.1)
15 (78.9)
12 (75.0)
Positive M1
8 (14.5)
0 (0.0)
8 (22.9)
8 (22.9)
4 (21.1)
4 (25.0)
Metastasis
0.041
Grade
1.000
0.601
0.307
259,540
467,861
0.237
0.650
Low (1–2)
60 (73.2)
20 (76.9)
40 (71.4)
40 (71.4)
18 (64.3)
22 (78.6)
401,804
High (3)
22 (26.8)
6 (23.1)
16 (28.6)
16 (28.6)
10 (35.7)
6 (21.4)
119,249
Negative
21 (23.9)
5 (17.9)
16 (26.7)
16 (26.7)
8 (25.8)
8 (27.6)
Positive
67 (76.1)
23 (82.1)
44 (73.3)
44 (73.3)
23 (74.2)
21 (72.4)
Estrogen-receptor Status
0.367
Progesterone-receptor Status
0.876
0.453
0.867
228,414
411,925
0.287
0.174
Negative
46 (52.3)
13 (46.4)
33 (55.0)
33 (55.0)
15 (48.4)
18 (62.1)
305,909
Positive
42 (47.7)
15 (53.6)
27 (45.0)
27 (45.0)
16 (51.6)
11 (37.9)
432,753
Negative
72 (81.8)
24 (85.7)
48 (80.0)
48 (80.0)
24 (80.0)
24 (80.0)
Positive
16 (18.2)
4 (14.3)
12 (20.0)
12 (20.0)
6 (20.0)
6 (20.0)
HER2 Overexpression Status
0.517
1.000
0.732
0.592
430,475
104,271
0.100
0.146
Yes
17 (19.3)
6 (21.4)
11 (18.3)
11 (18.3)
3 (9.7)
8 (27.6)
323,558
No
71 (80.7)
22 (78.6)
49 (81.7)
49 (81.7)
28 (90.3)
21 (72.4)
371,840
Page 11 of 16
TNBC, n (%)
Mann–Whitney
Karaglani et al. BMC Cancer (2015) 15:694
Table 5 Association of COL11A1 variant E with clinicopathological characteristics in breast cancer tissues
Clinical features
Ν (%)
Both Variant A & E
Rest
Pearson χ2 or Fisher’s exact
n (%)
n (%)
p-value
Age Group
N (%)
Either Variant A OR E
No variant
Pearson χ2 or Fisher’s exact
n (%)
n (%)
p-value
0.036
0.535
< =50 years
26 (35.6)
3 (15.8)
23 (42.6)
26 (35.6)
17 (33.3)
9 (40.9)
> 50 years
47 (64.4)
16 (84.2)
31 (57.4)
47 (64.4)
34 (66.7)
13 (59.1)
≤ 2.0 cm
59 (67.0)
18 (69.2)
41 (66.1)
59 (67.0)
41 (66.1)
18 (69.2)
> 2.0 cm
29 (33.0)
8 (30.8)
21 (33.9)
29 (33.0)
21 (33.9)
8 (30.8)
Tumor Size
0.778
Histopathological Type
0.778
0.733
0.642
Lobular & rest
18 (20.0)
5 (17.9)
13 (21.0)
18 (20.0)
12 (18.8)
6 (23.1)
Intraductal infiltrating
72 (80.0)
23 (82.1)
49 (79.0)
72 (80.0)
52 (81.3)
20 (76.9)
Negative (Ν0)
55 (67.1)
15 (62.5)
40 (69.0)
55 (67.1)
34 (60.7)
21 (80.8)
Positive (Ν+)
27 (32.9)
9 (37.5)
18 (31.0)
27 (32.9)
22 (39.3)
5 (19.2)
Lymph-node Involvement
0.571
Metastasis
0.072
0.098
0.043
Negative M0
47 (85.5)
13 (72.2)
34 (91.9)
47 (85.5)
29 (78.4)
18 (100.0)
Positive M1
8 (14.5)
5 (27.8)
3 (8.1)
8 (14.5)
8 (21.6)
0 (0.0)
Low (1–2)
60 (73.2)
16 (64.0)
44 (77.2)
60 (73.2)
42 (72.4)
18 (75.0)
High (3)
22 (26.8)
9 (36.0)
13 (22.8)
22 (26.8)
16 (27.6)
6 (25.0)
Grade
0.215
Estrogen-receptor Status
0.810
0.166
0.509
Negative
21 (23.9)
9 (33.3)
12 (19.7)
21 (23.9)
16 (25.8)
5 (19.2)
Positive
67 (76.1)
18 (66.7)
49 (80.3)
67 (76.1)
46 (74.2)
21 (80.8)
Negative
46 (52.3)
16 (59.3)
30 (49.2)
46 (52.3)
34 (54.8)
12 (46.2)
Positive
42 (47.7)
11 (40.7)
31 (50.8)
42 (47.7)
28 (45.2)
14 (53.8)
Progesterone-receptor Status
0.383
HER2 Overexpression Status
0.457
0.546
0.375
72 (81.8)
20 (76.9)
52 (83.9)
72 (81.8)
49 (79.0)
23 (88.5)
Positive
16 (18.2)
6 (23.1)
10 (16.1)
16 (18.2)
13 (21.0)
3 (11.5)
Yes
17 (19.3)
6 (22.2)
11 (18.0)
17 (19.3)
11 (17.7)
6 (23.1)
No
71 (80.7)
21 (77.8)
50 (82.0)
71 (80.7)
51 (82.3)
20 (76.9)
0.646
0.563
Page 12 of 16
Negative
TNBC, n (%)
Karaglani et al. BMC Cancer (2015) 15:694
Table 6 Association of both or either COL11A1 A and E variants with clinicopathological characteristics in breast cancer tissues
Karaglani et al. BMC Cancer (2015) 15:694
older age group (p = 0.036, Table 6 left). Furthermore,
the qualitative presence of either variant A or either variant E presented a significant correlation with metastasis
(p = 0.043, Table 6 right). There was also a statistically significant positive correlation between copies of variant A
and copies of variant E (rho = 0.368, p = 0.050). We also
examined the association of COL11A1 transcript variants
with metastasis in the 55 patients where follow-up data
was available by using the Kaplan-Meier survival analysis.
Patients with the presence of variant E in their tumor
showed a reduced disease-free interval compared to those
not expressing it (p = 0.060, log-rank test, Fig. 8).
Discussion
The first goal of this study was the development and
validation of new and reliable quantitative assays for all reported COL11A1 mRNA splice variants (A, B, C and E) by
using real-time qPCR methods. With another simple
conventional PCR technique -in a common genomic
area for all transcripts- we would still being able to determine the presence or not of the COL11A1 gene transcript,
in general. Furthermore, we applied these techniques in
breast cancer tissues in order to use the obtained quantitative data to determine any existing significant correlation
between the differential expression of COL11A1 variants
and clinicopathological features of these patients.
When 90 breast cancer tissues were studied, only A and
E variants were encountered while the general COL11A1
transcript was present in all samples. Variant A was detected in 30 samples (33 %) and variant E in 62 (69 %).
In 28 samples, both A and E variants were detected
(31 %) while in 26 samples, no variant was detected
Page 13 of 16
(29 %). Variants B and C were not detected in our series
of samples and hence, we were not able to validate the
methodologies with the proposed combination of primers
and probes. The quantification of variants A and E was
performed with a real-time qPCR methodology on the
LightCycler 1.5 thermocycler using dual hybridization
probes and melting curve analysis at the end of each reaction. We performed optimization experiments by using
isolated and quantified amplicons as external standards of
the developed real-time qPCR assays for the A and E variants. The assays were developed satisfactorily, were rapid
and reliable, demonstrating excellent efficiencies (2.05 ±
0.04 for variant A and 1.88 ± 0.10 variant E), very good reproducibilities (CV ≤1.3 % for variant A and CV ≤3.2 %
for variant E) and low detection limits (~19 copies/μL
for variant A and ~16 copies /μL for variant E). The
specificity of the real-time qPCR assays was tested by
melting curve analysis (Tm of variant A amplicon was
69.9 (±1.0) °C while that of variant E was 65.3 (±1.0) °C),
by the presence of specific bands of the proper size during
electrophoresis of the real-time PCR products and finally,
by DNA sequencing of the amplicons obtained. The determination was easy and rapid (within ~ 50 min) after the
synthesis of the cDNA and it was possible to analyze up to
32 samples simultaneously. However, there is the possibility of higher throughput in larger platforms such as the
LightCycler 480/1630, wherein the determinations that are
performed in microtiter plates lead to a much greater
number of samples that can be processed together.
Statistical analysis of the data was carried out in order
to detect any existing significant correlation between the
differential expression of the variants A and E (presence
Fig. 8 Figure 8 Kaplan-Meier survival analysis with respect to long-term metastasis in 55 of 90 breast cancer patients (35 patients with variant E
expression vs. 20 without variant E expression), where follow-up data was available
Karaglani et al. BMC Cancer (2015) 15:694
or not, low or high number of copies) with clinicopathological characteristics of the samples and the patients
(such as age group, tumor size, histopathological type
of tumor, lymph nodes involvement, grade, metastasis,
hormone receptors status, HER2 oncogene overexpression,
TNBC status). The copy numbers of variants A and
were E showed some positive correlation between them
(rho = 0.368, p = 0.050) and the simultaneous expression
of them was significantly correlated with the older age
group (p = 0.036). We cannot exclude that this might reflect a more generalized defect in the splicing machinery
with increased aging. The most important finding was the
observed statistically significant correlation between
the presence of variant E and lymph nodes involvement
(p = 0.037) and metastasis (p = 0.041) which was corroborated by a trend in Kaplan-Meir analysis where the
patients with variant E in their tissue show reduced
disease-free interval (p = 0.060). Furthermore, the qualitative presence of either variant A or variant E showed
a significant correlation with metastasis (p = 0.043). Results could be probably reinforced if follow-up data was
available for all 90 patients with quantitative data on
variants A and E and not only for 55 patients. No other
association with established histopathological prognostic parameters was detected in our results. A working
hypothesis therefore, would be that the shorter isoform,
produced from the translation of variant E mRNA,
would be more resistant in proteolytic actions by enzymes such as BMP-1 [27]- and it could retain the
bulky NTD domain for a longer time. This could lead to a
“thinner” collagenous stroma, more attractive to adhesion
molecules and metalloproteinases (as NTD contains
thrombospondin-1 like and heparin binding regions [39])
and thus, could pave the way for tumor cells motility and
metastasis.
A limitation of our study is that we could not investigate
quantitatively whether the breast tumor cells showed
upregulation of the expression of variants compared to
normal epithelial breast tissues. Also, we could not dissect
the expression to either the epithelial or the stromal
compartment as the specimens obtained were a mixture
of these. Finally, regarding the group of breast tumor tissues examined, the tumors studied were relatively small
(~2.0 cm) because they originated from well-monitored
patients in a metropolitan area. During the total RNA isolation procedure, although the samples were placed directly into an appropriate material for the RNA stability
(RNAlater), the presence of inhibitors in our fresh-frozen
biopsy RNA preparations and their integrity were not
assessed by assays such as the SPUD [40] and the 5:3 ratio
GAPDH (GlycerAldehyde 3-Phosphate DeHydrogenase)
mRNA integrity tests [36]. However, the RNA quality was
tested with the actin reference gene and measured with
absolute accuracy with the Quant-It RNA Assay kit on
Page 14 of 16
Qubit. Differences in cDNA synthesis efficiency due to
tumor variability could not be assessed since the absolute
quantification and normalization to total RNA strategy was
selected for analysis of data (and not relative quantification
and normalization to expression of one or an average of
three reference genes as is the trend nowadays).
Conclusions
This study was the first to assess the differential expression
of COL11A1 A and E splice variants in breast cancer tissues
and in cancer in general. We attempted also to detect B
and C variants but with no clear indication whether our assays failed or these transcripts weren’t present, since we
didn’t possess any positive control. The existence of other
variants is speculated: the fact that in 29 % of the cDNA
samples no COL11A1 variant were detected -despite the
presence of the general transcript- warrants a new research
effort in the future for the quest and identification of novel
variants. Additionally, the general COL11A1 transcript
could also be quantitated in a novel assay (e.g. multiplexed
with A and/or E variants) in order to identify samples that
although they are positive for A and/or E variants don’t
sum up to the total COL11A1 transcript and therefore one
could hypothesize that they contain additional aberrant
transcripts.
The study also could be extended to a larger number
of breast cancer tissues and a significant number of normal
tissues so that it could verify the results of earlier studies in
relation to increased or no expression of COL11A1 mRNA
and its variants in breast cancer. In this case, it may be possible to include COL11A1 gene and/or its variants in new
improved prognostic multiparameter expression arrays for
predicting metastasis. This information would be useful for
20–30 % of lymph node positive breast cancer patients that
remain free of distant metastasis in 15–30 years but
still receive toxic chemotherapy [22]. It is expected that
new tools such as deep RNA Sequencing with Next
Generation Sequencing (NGS) platforms could assist in
the discovery of such new aberrant transcripts in tumor
RNA samples.
By employing polyclonal antibodies against various
epitopes in the NTD domain -that are available now at
a research level [21, 41]-, it should be possible to further
validate our assays of COL11A1 RNA variants and to
evaluate findings on the differential proteolysis of the Nterminal regions of the protein chain of collagen a1(XI) in
breast cancer and their involvement in tissue remodeling
through stereochemistry. The combined use of laboratory
tools such as qPCR and Western Blot would lead to
validation of antibodies suitable for use in routine IHC
in paraffin-embedded tissues. Also it would be useful to
evaluate the expression of COL11A1 variants in other
cancers such as oropharynx [17], ovarian [18] and lung
Karaglani et al. BMC Cancer (2015) 15:694
cancer [15], wherein the expression of COL11A1 has
been shown to be associated with disease progression.
Additional files
Additional file 1: Figure S1. Conventional PCR products for the
general COL11A1 transcript run on a 2 % w/v agarose gel: in lane 1 PCR
MW Marker (50-150-300-500-766 bp), lanes 2–5 positive cDNA samples
for the general transcript (132 bp), lane 6 blank. (JPEG 43 kb)
Additional file 2: Figure S2. PCR products from inverted capillaries of
positive tumor samples for COL11A1 splice variant A run on a 2 % w/v
agarose gel: in lane 1 PCR MW Marker (50-150-300-500-766 bp), lane 2
blank, lanes 3–7 positive cDNA samples (439 bp). (JPEG 13 kb)
Additional file 3: Figure S3. PCR products from inverted capillaries of
positive tumor samples for COL11A1 splice variant E run on a 2 % w/v
agarose gel: in lane 1 PCR MW Marker (50-150-300-500-766 bp), lane 2
blank, lanes 3–7 positive cDNA samples (259 bp). (JPEG 15 kb)
Additional file 4: Figure S4. Sanger DNA Sequencing electropherogram
from a positive amplicon for COL11A1 transcript variant A in a tumor cDNA
sample. (JPEG 133 kb)
Additional file 5: Figure S5. Sanger DNA Sequencing electropherogram
from a positive amplicon for COL11A1 transcript variant E in a tumor cDNA
sample. (JPEG 125 kb)
Abbreviations
CISH: Chromogenic in situ hybridization; Cq: Quantification cycle;
CV: Coefficient of variation; ECM: Extracellular matrix; EMT: Epithelial-tomesenchymal transition; IHC: Immunohistochemistry; NTD: N-terminal
domain; qPCR: Quantitative Polymerase Chain Reaction; Tm: Melting point
temperature; TNBC: Triple negative breast cancer.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
MK participated in the conception and design of the study, carried out the
assays, collected and assembled the data, performed the statistical analysis
and drafted the manuscript. IT participated in the conception and design of
the study, provided study material and edited the manuscript. NG, DV and
SV provided study patients and material. NP participated in the assays and
the collection of the data. IR provided study material. CK participated in the
conception and design of the study, provided study material, performed the
statistical analysis, interpreted the data, drafted and edited the manuscript.
All authors have read and approved the final manuscript.
Acknowledgements
We would like to express our gratitude to Ms. Tatiana Rizou for reading and
commenting on our manuscript, Assoc. Prof. Kleanthi Dima for equipment
provision, Prof. Evi Lianidou for critically reviewing the manuscript and for
the decision to submit to BMC Cancer and finally, all the patients that
participated in the study. NP is supported from Grant NSRF HRAKLEITOS 70/
3/10973 from the European Social fund 2007–2013 (but with no role in
study design, data collection and analysis, decision to publish, or preparation
of the manuscript).
Author details
1
Department of Clinical Biochemistry and Molecular Diagnostics, Attikon
University General Hospital, University of Athens Medical School, Rimini 1 St.,
Haidari 12462, Greece. 2Department of Cardiothoracic Surgery, Attikon
University General Hospital, University of Athens Medical School, Athens,
Greece. 3Pathologic Anatomy Laboratory, Evgenidio Hospital, University of
Athens Medical School, Athens, Greece. 4Prolipsis Breast Cancer Clinic,
Athens, Greece. 5Department of Cardiology, Attikon University General
Hospital, University of Athens Medical School, Athens, Greece.
Received: 17 December 2014 Accepted: 8 October 2015
Page 15 of 16
References
1. Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, et al.
Cancer incidence and mortality worldwide: sources, methods and major
patterns in GLOBOCAN 2012. Int J Cancer. 2015;136(5):359–86.
2. Mendler M, Eich-Bender SG, Vaughan L, Winterhalter KH, Bruckner P.
Cartilage contains mixed fibrils of collagen types II, IX, and XI. J Cell Biol.
1989;108(1):191–7.
3. Bernard M, Yoshioka H, Rodriguez E, Van der Rest M, Kimura T, Ninomiya Y,
et al. Cloning and sequencing of pro-alpha 1 (XI) collagen cDNA
demonstrates that type XI belongs to the fibrillar class of collagens and
reveals that the expression of the gene is not restricted to cartilagenous
tissue. J Biol Chem. 1988;263(32):17159–66.
4. Morris NP, Bachinger HP. Type XI collagen is a heterotrimer with the
composition (1 alpha, 2 alpha, 3 alpha) retaining non-triple-helical domains.
J Biol Chem. 1987;262(23):11345–50.
5. Burgeson RE, Hollister DW. Collagen heterogeneity in human cartilage:
identification of several new collagen chains. Biochem Biophys Res
Commun. 1979;87(4):1124–31.
6. Thom JR, Morris NP. Biosynthesis and proteolytic processing of type XI
collagen in embryonic chick sterna. J Biol Chem. 1991;266(11):7262–9.
7. Fallahi A, Kroll B, Warner LR, Oxford RJ, Irwin KM, Mercer LM, et al. Structural
model of the amino propeptide of collagen XI alpha1 chain with similarity
to the LNS domains. Protein Sci. 2005;14(6):1526–37.
8. Oxford JT, DeScala J, Morris N, Gregory K, Medeck R, Irwin K, et al.
Interaction between amino propeptides of type XI procollagen alpha1
chains. J Biol Chem. 2004;279(12):10939–45.
9. Toumpoulis IK, Oxford JT, Cowan DB, Anagnostopoulos CE, Rokkas CK,
Chamogeorgakis TP, et al. Differential expression of collagen type V and XI
alpha-1 in human ascending thoracic aortic aneurysms. Ann Thorac Surg.
2009;88(2):506–13.
10. Fischer H, Stenling R, Rubio C, Lindblom A. Colorectal carcinogenesis is
associated with stromal expression of COL11A1 and COL5A2.
Carcinogenesis. 2001;22(6):875–8.
11. Banyard J, Bao L, Hofer MD, Zurakowski D, Spivey KA, Feldman AS, et al.
Collagen XXIII expression is associated with prostate cancer recurrence and
distant metastases. Clin Cancer Res. 2007;13(9):2634–42.
12. Misawa K, Kanazawa T, Imai A, Endo S, Mochizuki D, Fukushima H, et al.
Prognostic value of type XXII and XXIV collagen mRNA expression in head
and neck cancer patients. Mol Clin Oncol. 2014;2(2):285–91.
13. Zhao Y, Zhou T, Li A, Yao H, He F, Wang L, et al. A potential role of
collagens expression in distinguishing between premalignant and
malignant lesions in stomach. Anat Rec. 2009;292(5):692–700.
14. Wang KK, Liu N, Radulovich N, Wigle DA, Johnston MR, Shepherd FA, et al.
Novel candidate tumor marker genes for lung adenocarcinoma. Oncogene.
2002;21(49):7598–604.
15. Chong IW, Chang MY, Chang HC, Yu YP, Sheu CC, Tsai JR, et al. Great
potential of a panel of multiple hMTH1, SPD, ITGA11 and COL11A1 markers
for diagnosis of patients with non-small cell lung cancer. Oncol Rep.
2006;16(5):981–8.
16. Garcia-Pravia C, Galvan JA, Gutierrez-Corral N, Solar-Garcia L, Garcia-Perez E,
Garcia-Ocana M, et al. Overexpression of COL11A1 by cancer-associated
fibroblasts: clinical relevance of a stromal marker in pancreatic cancer. PLoS
One. 2013;8(10):e78327.
17. Schmalbach CE, Chepeha DB, Giordano TJ, Rubin MA, Teknos TN, Bradford
CR, et al. Molecular profiling and the identification of genes associated with
metastatic oral cavity/pharynx squamous cell carcinoma. Arch Otolaryngol
Head Neck Surg. 2004;130(3):295–302.
18. Wu YH, Chang TH, Huang YF, Huang HD, Chou CY. COL11A1 promotes
tumor progression and predicts poor clinical outcome in ovarian cancer.
Oncogene. 2013;33(26):3432–40.
19. Kim H, Watkinson J, Varadan V, Anastassiou D. Multi-cancer computational
analysis reveals invasion-associated variant of desmoplastic reaction
involving INHBA, THBS2 and COL11A1. BMC Med Genet. 2010;3:51.
20. Vargas AC, McCart Reed AE, Waddell N, Lane A, Reid LE, Smart CE, et al.
Gene expression profiling of tumour epithelial and stromal compartments
during breast cancer progression. Breast Cancer Res Treat. 2012;135(1):153–65.
21. Halsted KC, Bowen KB, Bond L, Luman SE, Jorcyk CL, Fyffe WE, et al.
Collagen alpha1(XI) in normal and malignant breast tissue. Mod Pathol.
2008;21(10):1246–54.
22. Feng Y, Sun B, Li X, Zhang L, Niu Y, Xiao C, et al. Differentially expressed
genes between primary cancer and paired lymph node metastases predict
Karaglani et al. BMC Cancer (2015) 15:694
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
clinical outcome of node-positive breast cancer patients. Breast Cancer Res
Treat. 2007;103(3):319–29.
Ellsworth RE, Seebach J, Field LA, Heckman C, Kane J, Hooke JA, et al. A
gene expression signature that defines breast cancer metastases. Clin Exp
Metastasis. 2009;26(3):205–13.
Yoshioka H, Inoguchi K, Khaleduzzaman M, Ninomiya Y, Andrikopoulos K,
Ramirez F. Coding sequence and alternative splicing of the mouse alpha
1(XI) collagen gene (Col11a1). Genomics. 1995;28(2):337–40.
Zhidkova NI, Justice SK, Mayne R. Alternative mRNA processing occurs in
the variable region of the pro-alpha 1(XI) and pro-alpha 2(XI) collagen
chains. J Biol Chem. 1995;270(16):9486–93.
Oxford JT, Doege KJ, Morris NP. Alternative exon splicing within the
amino-terminal nontriple-helical domain of the rat pro-alpha 1(XI)
collagen chain generates multiple forms of the mRNA transcript which
exhibit tissue-dependent variation. J Biol Chem. 1995;270(16):9478–85.
Medeck RJ, Sosa S, Morris N, Oxford JT. BMP-1-mediated proteolytic
processing of alternatively spliced isoforms of collagen type XI. Biochem J.
2003;376(Pt 2):361–8.
Sinn P, Aulmann S, Wirtz R, Schott S, Marme F, Varga Z, et al. Multigene
Assays for Classification, Prognosis, and Prediction in Breast Cancer: a Critical
Review on the Background and Clinical Utility. Geburtshilfe Frauenheilkd.
2013;73(9):932–40.
Habel LA, Sakoda LC, Achacoso N, Ma XJ, Erlander MG, Sgroi DC, et al.
HOXB13:IL17BR and molecular grade index and risk of breast cancer death
among patients with lymph node-negative invasive disease. Breast Cancer
Res. 2013;15(2):R24.
Caan BJ, Sweeney C, Habel LA, Kwan ML, Kroenke CH, Weltzien EK, et al.
Intrinsic subtypes from the PAM50 gene expression assay in a population-based
breast cancer survivor cohort: prognostication of short- and long-term outcomes.
Cancer Epidemiol Biomarkers Prev. 2014;23(5):725–34.
Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, et al. A multigene assay to
predict recurrence of tamoxifen-treated, node-negative breast cancer.
N Engl J Med. 2004;351(27):2817–26.
Poumpouridou N, Kroupis C. Hereditary breast cancer: beyond BRCA
genetic analysis; PALB2 emerges. Clin Chem Lab Med. 2012;50(3):423–34.
Pavlidou A, Kroupis C, Goutas N, Dalamaga M, Dimas K. Validation of a Real-Time
Quantitative Polymerase Chain Reaction Method for the Quantification of 3
Survivin Transcripts and Evaluation in Breast Cancer Tissues. Clin Breast Cancer.
2014;14(2):122–31.
Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, et al. The
MIQE guidelines: minimum information for publication of quantitative real-time
PCR experiments. Clin Chem. 2009;55(4):611–22.
Kroupis C, Stathopoulou A, Zygalaki E, Ferekidou L, Talieri M, Lianidou ES.
Development and applications of a real-time quantitative RT-PCR method
(QRT-PCR) for BRCA1 mRNA. Clin Biochem. 2005;38(1):50–7.
Nolan T, Hands RE, Bustin SA. Quantification of mRNA using real-time RT-PCR.
Nat Protoc. 2006;1(3):1559–82.
Tricarico C, Pinzani P, Bianchi S, Paglierani M, Distante V, Pazzagli M, et al.
Quantitative real-time reverse transcription polymerase chain reaction:
normalization to rRNA or single housekeeping genes is inappropriate for
human tissue biopsies. Anal Biochem. 2002;309(2):293–300.
Zygalaki E, Tsaroucha EG, Kaklamanis L, Lianidou ES. Quantitative real-time
reverse transcription PCR study of the expression of vascular endothelial
growth factor (VEGF) splice variants and VEGF receptors (VEGFR-1 and
VEGFR-2) in non small cell lung cancer. Clin Chem. 2007;53(8):1433–9.
Warner LR, Brown RJ, Yingst SMC, Oxford JT. Isoform-specific Heparan
Sulfate Binding within the Amino-terminal Noncollagenous Domain of
Collagen α1(XI). J Biol Chem. 2006;281(51):39507–16.
Nolan T, Hands RE, Ogunkolade W, Bustin SA. SPUD: a quantitative PCR
assay for the detection of inhibitors in nucleic acid preparations. Anal
Biochem. 2006;351(2):308–10.
Bowen KB, Reimers AP, Luman S, Kronz JD, Fyffe WE, Oxford JT.
Immunohistochemical localization of collagen type XI alpha1 and alpha2
chains in human colon tissue. J Histochem Cytochem. 2008;56(3):275–83.
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