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

Reviewers' comments: 

Reviewer #1 (Remarks to the Author); expert in expert in JNK signalling: 

The paper by Zhang et al. describes that the scaffold protein POSH2 is upregulated in cancer stem-
like cells (CSCs) promoting breast cancer stem-like properties. It seems that these effects are 
mediated by JNK activation and PTX3 upregulation. 
As it was already published that POSH mediates JNK activation (Xu et al., 2003) while the third 
member of the same family, POSHER, induces its degradation (Wilhelm et al., 2013) the authors 
would need to study the molecular mechanism of these differences. To really result in a significant 
increase of our knowledge of this pathway, it would be necessary to clarify which SH3 domain is 
involved and if the biding is to JNK, MKK or JIP. 

There are several points that need to improve in order to be published: 

• The authors make clear that previous reports firmly established the role of PTX3 in cancer. For 
this reason, the authors need to check whether it could be a target for cancer treatment. They 
need to carry on experiments to see if the lack/reduction of PTX3 reduce the tumor size, similarly 
to their data in Figure 3 targeting POSH2. 
• Evaluate the interaction between the component of the signaling network (JIP, JNK, POSH2, 
MKK) 
• The use of Ponceau S staining of the nitrocellulose membranes is not acceptable as loading 
control for the western blots. Antibodies such us tubulin, GAPDH or similar must be employed. 
• It is important to demonstrate reduced activity of JNK when the interaction between POSH2 and 
JNK is impaired due to JIP3 knockdown (Fig. 6H). This can be done by showing Jun 
phosphorylation or the expression of Jun-target genes. 
• Tumor incidence in animal studies should be determined by observing lack of tumors after 
opening the mice. If this is only determined by external palpation, some very small tumors would 
not be taken into consideration, and incidence would be underestimated. 
• For the flow cytometry analysis of ALDH+ population, the negative control of DEAB+ (ALDH 
inhibitor) should be included, if not, how do the authors really now that the positive population is 
the real one? 
• Authors sort HMLER cells in 2 populations in function of their CD44 expression levels. However, 
the plots in figure1D show that the level of CD44 in both populations are almost the same. Does 
CD44LS population increase the levels of CD44 over time? 
• Authors directly relate POSH2 levels with CD44high in HMLE and MCF10AT cell lines and ALDH+ 
expression in MDA-MB-231. Did the authors measure ALDH+ expression in HMLE and MCF10AT 
and CD44 in MDA-MB-231? 
• Did the authors perform limiting dilution assays in POSH2 overexpressing-HMLE cell line? Why 
did the authors specifically use MDA-MB-231 cell line for this experiment? These ex-periments 
need to be done also in HMLE cell. 
• In the siRNA-POSH2 experiments, did the authors check the siRNA-POSH2 in the MDA-MB-231 
cell line? 
• Previously it has been shown that PI3K signalling target pentraxin-3 to promote stemness in 
basal-like breast cancer (Thomas et al. 2017 Sci Signal. 21;10 (467)). Does POSH2 exert its 
functions, at least in part, through the PI3K pathway? Authors should investigate this possi-bility. 
• The information about the details in tumorsphere experiment is very deficient. The author should 
include the cell concentration at the begging and in the passages. 
Minor points 
• The authors indicate that one band of p-JNK Western blot corresponds to p-JNK1, while the other 
one corresponds to p-JNK2 (Fig. 6C). However, each band is p-JNK1/2 (two different splice 
variants of JNK1 and JNK2. 
• In Figures 2 & 3, the tubulin western blot control is clearly overexposed. A shorter exposition (or 
less protein loaded) must be presented. 

• The authors should show total JNK and Jun protein levels in Fig. 6C. 
• In the MMTs assays (Figure1C) authors used paclitaxel amounts between 0-200ng per well, but 
which volume was used per well? Inhibitors might be indicated by concentration in order to allow 
reproductivity of the experiments 
• The number of replicates is only included in some experiments. Without sample size the pre-
sented results don't mean anything. I suggest authors to include this information in their fig-ures. 

Some of the figures are too small and there are some spelling errors. 
• “Tumoresphere” should be “tumorsphere” in line of page 5. 
• “Overxpression” should be “overexpression” in line 7 of Figure legend 5. 
• Line 12 of Methods section lacks the word “in” before “this study”. 

Reviewer #2 (Remarks to the Author); expert in cancer bioinformatics: 

The study Zhang et al present uses a wide array of techniques to investigate the biology of CSCs 
in breast cancer specifically and cancer more broadly. While most of what is presented in the 
present manuscript is correct, and conclusions are solid, the manuscript has a severe deficit in 
some techniques in explaining the methods used. The authors need to be aware that any other 
scientist that would want to replicate their results need to have the VERY DETAILED and FULL 
methodology used to produce the presented results, which is not the case. This is reflected in the 
specific comments below, but not restricted to these: 
Throughout all the text: 
Minor: Official symbol of the gene is SH3RF3, not POSH2. This needs to be reversed throughout 
the text (including the title). All other mentioned genes in the manuscript should be also revised to 
ensure that official gene symbols are used, and not any aliases or old names. 
Minor: The authors make several statements like “These results demonstrated”, where “These 
results suggested” would be more appropriate, since other explanations beyond the scope of this 
study could explain the changes. 
Introduction 
Minor: Page 3 line 12: change testified to tested 
Minor: Rephrase the PTX3 sentences, just jumps into it, but needs to start saying first why are 
they talking about it. 
Results 
Major: 3 replicas of CD44L (control) and 2 replicas of CD44H and CD44LS. At least 3 replicas of 
each treatment need to be done. 
Minor: In the mice injected with 40 control cells, were the injection of tumorigenic cells also 40? 
Furthermore, the increase is “only” 20%, have they controlled in their analysis for the expression 
of the other already known over or under-expressed cancer genes? Is there a specific gene 
expression environment in which the overexpression of SH3RF3 is more tumorigenic? 
Minor: The 24 genes resulting from the overlap of HMLER and MCF10AT does not imply that they 
are controlled by SH3RF3, only that they are co-up- or co-down-regulated together with SH3RF3. 
Not causality, just co-occurrence. As they verify by knockdown, PTX3 seems to be the case, but 
not necessarily the other 23 genes, rephrase. 
Methods 
Major: For their own RNAseq data (SH3RF3 and PTX3 over-expressing cell lines), they do not 
mention absolutely anything about who the data was analysed. They need to state which algorithm 
was used for reads alignment, how they controlled and/or how they addressed for multimapping of 
reads, what kind of normalisation they used prior to differential expression analyses, which 
software/packages they used for all this processed (with references) and which default parameters 
of these software/packages were changed (if any). Also, which kind of RNAseq was performed? 
Whole transcriptome or something else? Was the RNAseq paired end or single end? What length of 
read? How many millions of read per sample they obtained (both raw and after QC)? Which were 

the QC criteria to remove reads after alignment to reference? Mapping quality? Multimapping? PCR 
duplicates? Also, were the reads aligned to the hg19 or hg38 of the reference? 
Major: Once all this is cleared, they also need to assess how this RNAseq analysis correlates 
technically with other external analyses considered for the study (e.g. TCGA). Is the RNAseq 
analysis performed by the authors comparable and compatible with that of the TCGA and others? 
Major: SH3RF3 has genes with similar sequences and implicated in the same processes SH3RF1 
and SH3RF2 (as the authors clearly discuss). What is the rate of multimap between the reads that 
mapped to each of the three genes? How was read multimapping addressed between these 3 
genes? 

Reviewer #3 (Remarks to the Author); expert in CSC and breast cancer: 

In the submitted manuscript, authors show that POSH2, a scaffold protein increases CSC 
properties of breast cancer cells through activation of JNK-JUN pathway and Pentaxrin 3. Authors 
through in vitro tumorsphere formation assay and in vivo experiments coupled with clinical cohort 
data show the relevance of POSH3 in CSC properties of breast cancer. The manuscript is very well 
written and communicates the idea convincingly. The role of POSH2 in breast cancer CSC is novel. 
Given the need to target CSCs to overcome chemo and radio resistant in patients, this study 
possess clinical relevance. 

However, I would like to suggest few corrections before publication of the article: 
Major corrections: 
1. Throughout the manuscript, authors have used orthotropic mice models to show the role of 
POSH2 in CSC maintenance. It would interesting to show if POSH2 expression correlates with CSC 
numbers and function in spontaneous breast cancer models. 
2. Authors show that inhibition of PTX3 in control and POSH2 over expressing MDA-MB-231 and 
HMLE cells inhibit the POSH2 promoted tumorsphere formation. However, no in vivo experiment 
has been provided to show that inhibiting PTX3 hampers CSC properties of breast cancer cells. It 
would be good if authors could compare the tumor initiation capability of PTX3 knockdown cells to 
that of POSH2 knockdown cells. 
3. In Figure 7, authors have used 3 patient samples, to study the correlation between POSH2 
expression and CD44 expression. The sample number is very low to state that there is a positive 
correlation between the two. Also, in experiments involving patient derived organoids, n=3 which 
is very less to convincingly demonstrate the positive relationship between POSH2 expression and 
organoid number. 
Minor corrections: 
1. In Figure 2A, authors show over expression of POSH2 in HMLE, MCF10AT and MDA-MB-231. 
Over expression in MCF10AT is minimal while in the other two, tubulin looks saturated. Authors 
can repeat these blots for better quality. Also, please specify if it is beta tubulin. 
2. Figure 2B, upon over expression of POSH2 in HMLE and MCF10AT, authors show increase in 
CD44+CD24- population, while in MDA-MB-231, ALDH+ population is increased. What happens to 
CD44+CD24- population in MDA-MB-231? 
3. In Figure 4B, authors show relative expression of PTX3 between control and POSH2 over 
expression. Control bars are not showing unit “1”, so what is the baseline for “relative 
expression”? 
4. Blot for PTX3 in MCF10AT in Figure 4B is not convincing. 
5. In Figure 7I, authors show a positive correlation between POSH2 expression and decreased 
overall survival. Is that relationship true with high PTX3 expression?