Peer review of: SH3RF3 promotes breast cancer stem-like properties via JNK activation and PTX3 (2020)

Reviewer #2 (Remarks to the Author):
 The authors have satisfactorily responded to all my questions and made the necessary changes to
 the manuscript.
With the changes incorporated into the manuscript in answer to the reviewers (this and the others)
comments its quality has been greatly improved.
Where I do not provide an answer for a comment it should be assumed that the answer provided
by the authors is satisfactory.
<i>
We believe the comment was referring to Fig. 1E and agree with the reviewer that more replicates
would have helped the transcriptomic screening. In fact, we used 3 replicates each of CD44H and
CD44L, while one replicate of CD44LS for the transcriptomic analysis. The reason was that our
original plan was to look for CSC-associated genes by comparing the transcriptomes between
CD44L and CD44H cells and in clinical samples, while CD44LS was only used for a confirmation
and backup purpose. Therefore, only one replicate was used for CD44LS though indeed we should
have analyzed more replicates. However, now we already finished the screening and identified
SH3RF3, and further confirmed its association with cancer stemness in clinical samples and in
multiple cell lines including HMLER derivatives (CD44H, CD44L, CD44LS) with qPCR and western
analyses. More importantly, functional analyses showed the role of SH3RF3 in CSCs. Thus we think
it would be pointless to retrospectively add more replicates for transcriptomic screening at this
stage.
</i>
I agree with the authors that this is indeed the case. This reviewer does not argue with the
positive finding derived from the RNAseq analysis, validated with qPCR and followed through with
functional experiments. What is regrettable is that by not adhering to the standards of RNAseq
experiment design and analysis they are most certainly missing out on further relevant results that
could have added to the presented results.
<i>
We apologize for the negligence and have added a section of RNA sequencing in the Methods to
include the detail protocol and relevant information.
</i>
With the new included information in the material and methods section now the bioinformatic
methodology can be evaluated, and while adequate for the most part some issues need to be
addressed:
The authors do not reference how they have dealt with the PCR duplicates.
For the command options specified for STAR, it is understood that they have not performed the
two-pass method for STAR alignment which is the best practices pipeline for said software, do the
authors have an explanation for why not? This may not be an issue since they obtain very high
percentage of aligned reads (mostly thanks to the 150bp long reads as opposed to the more usual
75bp in RNAseq), but any deviation from best practices needs to be explained.
Another best practices point that the authors have neglected is the use of hg38. There are plenty
of reasons why the use of hg19 must be discouraged, especially for RNAseq data. Hg19 is already
an 11-year-old build of the human genome and its use has been deprecated by all the main best
practices pipelines including those of STAR and GATK. Why didn’t the authors use hg38?
The authors state that genes with a fold change greater than 2 were identified. Do they mean
Log2(Fold Change) or this is only for the overexpressed genes since they are not doing the
Log2(fold change)?, how did they identify the underexpressed genes in the analysis? Also, what
statistical test and multiple test correction/level of significance (e.g. FDR corrected P value < 0.05)
were used?
Reviewer #3 (Remarks to the Author):
Authors have responded to all my comments successfully.