PONE-D-25-09189Development of a Prostate Cancer Biochemical Recurrence Risk Signature Using Machine Learning and Motor Protein-Related GenesPLOS ONE

Dear Dr. Wang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by May 09 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

Elnaz Pashaei, Ph.D

Academic Editor

PLOS ONE

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1.  Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

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3. In the online submission form, you indicated that [The data that support the findings of this study are available from the corresponding author upon reasonable request].

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4. Please include your tables as part of your main manuscript and remove the individual files. Please note that supplementary tables (should remain/ be uploaded) as separate "supporting information" files

Additional Editor Comments:

1.The model performs well in TCGA-PRAD (AUC = 0.966) but poorly in MSKCC2010 (AUC = 0.739–0.684), suggesting potential dataset bias. Please address this issue.

2.The nomogram is developed using TCGA-PRAD but lacks external validation, which is essential to assess its reliability in broader populations.

3.While pathway enrichment analysis is performed, the study does not discuss how these pathways relate to prostate cancer progression or treatment response.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Nice in silico exploratory study of motor protein transcriptomic signature and its correlation to biochemical recurrence in prostate cancer. Please if you could add additional paragraph to discussion section where you state certain limitations of the study, mainly that it is in silico and that as in any in silico study depending where you cut off the statistical significance in pathways enrichment analysis you get a different biological conclusions.

Reviewer #2: Thanks for the chance to review your work. This paper aimed to construct a risk signature of biochemical recurrence for prostate cancer, by using the methods of machine learning and the data from TCGA, KEGG, and MSKCC2010. Overall, this paper is solid and provided valuable insights for the understanding of Motor proteins and PCa progression. I have some minor suggestions for authors to refer to.

1) There are so many figures included in the paper, and please consider to conprehensively rearrange and reduce the number of all the figures. I think some figures should be merged into one.

2) Please consider to add a table to summarize all the related studies.

3) Some sentences are confusing to follow, and authors should carefully check all the typos and grammar.

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6. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files.

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy .

Reviewer #1: Yes:  Benjamin Benzon

Reviewer #2: No

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PONE-D-25-09189R1Development of a Prostate Cancer Biochemical Recurrence Risk Signature Using Machine Learning and Motor Protein-Related GenesPLOS ONE

Dear Dr. Wang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Aug 21 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Elnaz Pashaei, Ph.D

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

Please address my requests below in addition to the reviewer comments:

1) While external cohorts were included, the conclusions rely entirely on bioinformatics analyses. Experimental or clinical validation would substantially strengthen the findings. Please update your manuscript to include further validation of your findings, and ensure that cohort matching on clinical covariates is fully addressed. 

2) Although key clinical variables such as T and N stages were analyzed, important factors like PSA levels, treatment history, and comorbidities were not included or discussed. Please incorporate these to improve the robustness of the prognostic model.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #3: (No Response)

Reviewer #4: All comments have been addressed

Reviewer #5: All comments have been addressed

Reviewer #6: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: No

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: No

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #3: (No Response)

Reviewer #4: This second version of the paper is a great improvement, the authors are to be commended.

The manuscript has been much improved and is in a nice condition now.

Reviewer #5: All suggestions have been addressed. The statistical analysis has been conducted appropriately and rigorously and any biases have been highlighted.

Reviewer #6: The Manuscript presented by Weixing Wang et al entitled: "Development of a Prostate Cancer Biochemical Recurrence Risk Signature Using Machine Learning and Motor Protein-Related Genes" is technically sound and presents a comprehensive bioinformatics and machine learning pipeline to develop a prognostic model for biochemical recurrence (BCR) in prostate cancer based on motor protein-related genes (MPRGs).

1. Technical soundness:

The use of two independent cohorts (TCGA-PRAD and MSKCC2010) for training and validation strengthens the reliability of the findings. the study's conclusions are generally well-supported by the presented data, including differential gene expression, survival analysis, ROC curves, immune cell infiltration correlations, and drug sensitivity predictions. However, the biological interpretation of some genes within the 8-MPRG signature could benefit from more mechanistic explanation or references, especially for less characterized genes in prostate cancer context.

2. statistical analysis:

The statistical approach is appropriately rigorous, especially with the incorporation of 10 machine learning algorithms and 101 model combinations. The authors applied uninvariate Cox regression, leave-one-out cross-validation (LOOCV), and evaluated performance using Harrel's index and ROC/AUC analysis- all of which are acceptable and correctly used.

That said, some aspects could be strengthened:

- the model calibration could be described more clearly. Were the calibration curves statistically evaluated?

- Multivariate Cox regression was performed, but the interpretation that riskscore is the only independent predictor (Table 1) requires further context (e.g., confidence intervals, hazard ratios).

3. Manuscript presentation and language:

The manuscript is generally intelligible and logically structured, with standard scientific English. However, there are numerous grammatical and typographical issues that should be addresssed to improve clarity. Some sentences are overly long and awkwardly constructed.

Examples:

- Line 13: "but their involvement in the biochemical recurrence (BCR) of prostate cancer is not well understood" can be improved as " but their role in biochemical recurrence (BCR) of prostate cancer remains unclear."

- Line 183: Age was observed to be positively associated with the riskscores (r=0.16, p=0,0053, Figure 4D), indicating that older patients had significantly higher risk scores compared to younger patients (Figure 4E)." can be improved as " Age was positively correlated with risk scores (r=0.16, p=0.0053; Figure 4D), suggesting that older patients tend to have higher riskscores than younger individuals (Figure 4E)."

- Line 23: Consider revising "with 8 significantly associated with BCR" to "of which 8 were significantly associated with BCR."

- Figure Legends are repetitive; consider condensing for example:

Figure 3 legend: this legend restates what each panel obviously shows, without adding interpretive value or clarification. it's descriptive but nor insightful. it can be improved as " Performance of the MPRG-based RSF model in predicting BCR. Risk score distributions, Kaplan-Meier survival curves, and ROC analyses for 1-, 3-, and 5-year BCR prediction are shown for the TCGA-PRAD (A-C) and MSKCC2010 (D-F) cohorts. Please consider same condensing to other legends as well.

- Data availability:

Refer to (Line328-330): "The data that support the findings of this study are available from the corresponding author upon request." However, earlier in the form-based metadata (near the beginning of the PDF), the authors checked "Yes- all data are fully available without restriction." this is inconsistent and contradicts PLOS ONE's open data policy. As the data appear to be sourced from public databases (e.g., TCGA, cBioPortal), the authors should revise statement to include direct links or accession numbers to these sources and clearly indicate that no restrictions apply.

- Novelty and impact:

The manuscript offers techical novelty through its use of motor protein-related genes in a machine learning framework to predict biochemical recurrence in prostate cancer. while the computational framework id rigorous and the biological rationale is sound, the novelty would be strengthened by comparing this model against existing BCR signatures and discussing its added clinical value over current available tools. Moreover, the lack of experimental validation or prospective cohort analyses limits the immediate applicability of the model in clinical settings.

In summary, this manuscript presents a technically sound and biologically motivated approach to predicting biochemical recurrence in prostate cancer using machine learning and motor protein-related genes. while the study is methodologically rigorous and offers meaningful insights, it would benefit from improved language clarity, enhanced biological interpretation, and alignment with open data standards. I recommend minor to moderate revision before acceptance.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy .

Reviewer #3: Yes:  In my opinion, the article contains all possible ways of developing the topic and can be published in its original version.

Reviewer #4: No

Reviewer #5: No

Reviewer #6: Yes:  Shayan Maleknia

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[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step.

Development of a Prostate Cancer Biochemical Recurrence Risk Signature Using Machine Learning and Motor Protein-Related Genes

PONE-D-25-09189R2

Dear Dr. Wang,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager®  and clicking the ‘Update My Information' link at the top of the page. For questions related to billing, please contact billing support .

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Elnaz Pashaei, Ph.D

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewer #6:

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #6: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #6: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #6: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #6: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #6: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #6: Dear Authors,

I would like to thank you for your careful revisions and thoughtful responses to all reviewer comments. the manuscript has beensubstantially improved in terms of clarity, language, and presentation. the statistical analysis are now much clear, the figures and legends are more concise, and the discussion better contextualizes the biological significance of the findings.

The revised data availability statement also now meets PLOS ONE's open-data requirements.

Overall, the study is technically sound, well presented, and makes a meaningful contribution by developing a machine learning-based signiture of motor protein-related genes for predicting biochemical recurrence in prostate cancer.I have no further concerns and support publication of this work.

Best regards,

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy .

Reviewer #6: Yes:  Shayan Maleknia

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