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Your revised manuscript has been re-reviewed by one of the original reviewers (their comments are provided below).
[# PeerJ Staff Note - this decision was reviewed and approved by Paula Soares, a PeerJ Section Editor covering this Section #]
Confirmatory experiments is still lacking in this version of the text. On the other hand, the authors indeed improved the text based on the reviewer's comments.
Many thanks for submitting your interesting manuscript. I have sought independent views on the manuscript and you will see that the reviewers have each made important comments that you will need to respond to by revising your manuscript (not only by responding in a response letter).
Please also ensure that your revised manuscript has been written in correct English language.
The article is clearly written with professional standards.
References are sufficient to justify the state of the art however the authors need to check the formatting once more.
For instance: Line 48-49, references have missed the year. Minor issue, please check the correct positioning of full stop "." at the end of sentence and citation "(XY et al, 2019)." or ".(XY et al, 2019)"
No other comments on writing style.
Line 68 to 71: it is not clear if they have used TPM or FPKM for their downstream analysis. It is suggested to have one metric used throughout the manuscript in order to avoid normalization conflicts or contradictory interpretations.
Line 100 and 105: I am not sure if there is a need for multiple hypothesis testing or FDR cutoff. Authors should include a fdr cutoff if possible.
Line 123: Is it r or r2 value. Please, clear whether the threshold is just a cutoff for an association or related to both positive (+0.6) and negative correlation (-0.6) indices?
Authors have used SpliceSeq software to calculate the PSI values, which later they have implemented in univariate/ COX models to re-investigate the prognostic index. It would be great if they can use another (at least one more) alternative splicing detection tool (if not doing any experimental verification) to authenticate the reproducibility of their best hits (and corresponding risk score) in silico.
The paper is well written and the subject is certainly of interest for both clinic and basic researchers in the fields of oncology and cellular biology.
The research question is well defined, relevant and meaningful, however, my major concern is the fact that this manuscript lacks experimental confirmation. The authors indeed mentioned some important links between literature and its data on some of the top twelve SF genes described, which somehow indicate the robustness of the obtained results, but in my opinion some specific experiments would substantially improve the work presented.
Comments on specific points that should be considered in order to improve the paper:
It would be interesting to see if the relevant Splicing Factors and Alternative Splicing events found could be functionally linked with each other. For instance, have some AS event already been reported as regulated for some of the SF encountered?
Comparison between the prognostic splicing factors obtained with other genes already used in clinics or known as relevant prognostic factors would render an interesting control
Six out of top twelve SF are not in the top twenty SF list presented in Fig 1. Is that correct? Please check the situation of the genes GPATCH3, IGF2BP3, PTBP3, RBM14, SRPK1, XAB2.
Fig 5 was not described in the text.
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