We are grateful to our reviewers for their helpful comments which allowed us to improve the
manuscript. Please find below our responses to their comments.
Reviewer 1: Since only Cav-1, Flot-1, Flot-2 and Stom was investigated, suggest to remove tetraspanins
from the first paragraph of introduction.
Reviewer 2: Why talk about tetraspanins?
We removed the part about tetraspanins from the first paragraph of introduction.
Reviewer 1: The numerous papers investigating expression levels of caveolin-1 in lung cancer or
sarcoma should be covered.
Reviewer 2: There is a vast literature describing the expression of caveolin-1 in lung cancer or sarcoma.
Why not discuss adequately?
A paragraph covering the literature on the subject was added to the Discussion section.
Reviewer 2: Can authors provide P (significance) through-out the manuscript?
P values were provided throughout the text.
Reviewer 1: Flotillin-2 qPCR data would make the study more complete.
Reviewer 2: Can authors carry out Flotillin-2 qPCR?
All our real-time PCR experiments were performed in the same system using the one-time obtained
cDNA stocks which we run out of. Because of the method for generating cDNA (from oligo-dT primers)
and flotillin-2 gene structure, we weren’t able to design primers appropriate for real-time PCR and
performed ordinary semiquantitative PCR. If we will perform a new real-time PCR investigation of
flotillin-2 expression it will be in any case another system, another method for generating cDNA (from
random primers), another frozen tissue pieces. And that is why, in our opinion, we will not be able to
combine obtained results into one statistical analysis with previous data, it will be incorrect. As a result,
such investigation hardly brings new information to our article, and to fill this gap we can include results
of semiquantitative PCR analysis.
Reviewer 2: The quality of Western blot is not optimal. Can authors provide quantification?
The results of western blot quantification are provided in Supplementary Table 1.
Reviewer 1: Use of 1.5 and 0.5 fold as cut-off is not ideal. The authors should perform statistical analysis
on the numerial raw data rather than categorize (Table 2-4).
We agree that the use of cut-off values is not ideal, but this system facilitates the understanding and
interpretation of obtained data. In case of analysis of real-time PCR results, it facilitates data
interpretation for small expression changes which are near 1 fold; it allows distinguishing the group of
paired specimens that demonstrate no significant difference in expression between tumor and normal
tissue taking into account standard errors and error of the method. Such system should prevent readers
from hasty conclusions of reality of decrease or increase of expression in cases where such changes are
meaningless. Furthermore, introducing such cut-off system is not uncommon, especially for microarray
data analysis. We also found similar systems of interpretation of real-time PCR results. In the article of
Freitas et al.: “We determined a gene expression cut-off value of 0.7 (median value) that differentiated
between ADAMTS-1 low expression and high expression in breast tumors” [1]. In the article of
Brabender et al.: “To determine whether there was any prognostic significance attached to quantitative
differences in HER2-neu mRNA expression levels, the maximal x2 method (22, 23) was adapted to
determine which HER2-neu expression level best segregated patients into poor-and good-prognosis
subgroups. This method found that segregation was best achieved by using a T:N HER2-neu expression
ratio of 1.8 as a cutoff value. By this criterion, 29 (34.9%) patients had a high HER2-neu expression and
54 (65.1%) had a low HER2-neu expression” [2]. Their study designs were similar to ours; these authors
also normalized expression in tumor samples to normal ones. But, in our opinion, such systems are not
more appropriate than ours, because they consider relative expression equal to 1 (i.e., equal gene
expression in tumor and normal samples) as high expression in the first article and as low expression in
the second article. Our system has not got drawbacks of this kind.
Densitometric quantification of Western blotting is not ideal itself; it is not a method for obtaining any
new numerical data. All relative expression values obtained by densitometric analysis depend on
particular antibody and particular blot whose picture was captured in specific conditions. Therefore, we
can compare degree of changes in protein expression only for samples of one western blot and cannot
compare samples on different western blots. Similar explanation can be found in the article of Fisher et
al. “Since purified protein standards (which would allow conversion of the measured intensities to molar
concentrations) were not available, comparison between expression levels of the different proteins
using the present methodology was not possible… While comparison of protein expression quantified in
samples on different Western blots is not possible, comparison between samples analysed on the same
membrane is valid” [3]. For instance, if normalized relative expression for sample A from blot1 is equal
to 3 and for sample B from blot2 it is equal to 6, we cannot conclude that in sample B expression is 2
fold higher than in sample A, we can only conclude that expression is up-regulated in both samples. That
is why densitometric quantification can only confirm our conclusions and categorized data are more
objective and it would be incorrect to perform statistical analysis on relative expression values
calculated from densitometric analyses of western blots.
Reviewer 2: Why not perform transfection experiments to examine, if there is a relationship between
cav-1 and Flotillin-2? Why not carry out gene knockdown and re-expression experiments.
First of all, it is not understood clearly why the reviewer chose the relationship between caveolin-1 and
flotillin-2, taking into account that we found strongest common correlation between stomatin and
flotillin-1. In general, it appears as a proposal for future research when we can investigate relationships
between all studied genes by modulating their expression in a panel of cell lines of different origins to
reveal mechanisms in details. We consider our article as a complete study which has enough
unpublished new data (stomatin and flotillin-2 expression changes in NSCLC, simultaneous expression
analysis of different microdomain-forming proteins in NSCLC and STS, correlation relationships, etc.)
and, in our opinion, it deserves to be published without such transfection experiments.
Reviewer 1: Reporting of data is not clear. As table 1, the authors should summarise the data presented
in the supplementary tables in the form of mean expression and standard deviation (or error) for each
grouping.
Reviewer 2: Results are not described clearly. For example, Table 1.
We rewrote the text in Table1 description thoroughly to make its understanding easier. Unfortunately,
the requirements of the first reviewer are no clear enough. We cannot understand what the groupings
we should make a table for are. As a result, the purpose of generating of the proposed table is not also
clear.
Reviewer 1: Quality of written English: Acceptable
Reviewer 2: In some places the text reads well, but in some places, the language is not clear. Perhaps,
the manuscript could benefit from English editorial help.
Quality of written English: Needs some language corrections before being published.
It has been suggested by one of the reviewers that the manuscript should undergo English editing. We
re-edited our manuscript, but will use language editing services, if needed.
References:
[1] Freitas VM, do Amaral JB, Silva TA, Santos ES, et al. Decreased expression of ADAMTS-1 in human
breast tumors stimulates migration and invasion. Mol Cancer. (2013) 12:2, doi: 10.1186/1476-4598-122.
[2] Brabender J, Danenberg KD, Metzger R, Schneider PM, et al. Epidermal growth factor receptor and
HER2-neu mRNA expression in non-small cell lung cancer Is correlated with survival. Clin Cancer Res.
(2001) 7(7): 1850-5.
[3] Fisher RM, Hoffstedt J, Hotamisligil GS, Thörne A et al. Effects of obesity and weight loss on the
expression of proteins involved in fatty acid metabolism in human adipose tissue. Int J Obes Relat Metab
Disord. (2002) 26(10):1379-85.