Biologically-informed regional subset analysis with CatBoost for robust tissue-of-origin prediction

Sungmin Yang; Hong-Gee Kim

doi:10.1371/journal.pone.0337106

Peer Review History

Original SubmissionAugust 4, 2025
28 Sep 2025 Decision Letter - Yogendra Prajapati, Editor PONE-D-25-42292Biologically-Informed Regional Subset Analysis with CatBoost for Robust Tissue-of-Origin PredictionPLOS ONE Dear Dr. Kim, 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 Nov 12 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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The authors are advised to revise the manuscript accordingly. [Note: HTML markup is below. Please do not edit.] 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: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: No Reviewer #2: N/A ****** 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: No Reviewer #2: Yes ****** 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: No Reviewer #2: Yes ****** 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: In this paper reports Biologically-Informed Regional Subset Analysis with CatBoost for Robust Tissue-of Origin Prediction. The concept in general is interesting and the results presented by the authors are interesting and sound. However, before accepting this work for publication, I would like to suggest the authors further revise the paper after taking into account the following comments. 1. Why authors used the only CatBoost machine learning technique only. 2. Much more discussion about the results should be given in this paper, especially the author needs to provide enough physicals mechanism analysis about the results. 3. The authors should clarify the mathematical framework used to the CatBoost model. 4. The figures in the manuscript are blurred and need improvement. 5. In the manuscript, there are grammatical and spelling mistakes. The language is comprehensive and coherent, but there are some mistakes. Manuscript can be accepted if the authors will incorporate the my comments. Reviewer #2: Manuscript Number: PONE-D-25-42292 Reviewer’s Comments: The manuscript titled “Biologically-Informed Regional Subset Analysis with CatBoost for Robust Tissue-of-Origin Prediction” presents a CatBoost prediction model for precision oncology and the diagnosis of cancers. This approach achieved a 4% gain in melanoma accuracy and a 4.4% gain in multiple myeloma and perfect (100%) accuracy in high‑mutation cancers such as esophageal adenocarcinoma and glioblastoma with as few as 50 informative regionals subset. On considering all things, these findings show that biologically guided regional subset 168 selection can improve TOO/COO prediction accuracy by lowering input dimensionality, mitigating data sparsity, and capturing important 169 epigenetic–mutation correlations. I am convinced with the method applied for the analysis. However, before publishing, it requires following minor revision to incorporate the all given suggestions. 1. To enhance the comprehensiveness of your paper, it would be beneficial to include at least five previous studies for comparative analysis, thereby strengthening its position relative to existing literature on the same topic. 2. The novelty of the research work is not clear. The authors are suggested to provide suitable novelty aspects. 3. Can you provide justification for claiming that your work over existing work in literature? 4. Labels of Fig. 3 are not clearly visible. Authors need to revise it. 5. Most of the cited reference work is before 2020. It is suggested to add latest relevant references. ****** 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. 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 #1: No Reviewer #2: Yes: Dr. Sarika Pal ******** [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. Attachments Attachment Submitted filename: Comments PONE-D-25-42292.docx https://doi.org/10.1371/journal.pone.0337106.r001
Revision 1
17 Oct 2025 Author Response Manuscript ID: PONE-D-25-42292 Title: Biologically-Informed Regional Subset Analysis with CatBoost for Robust Tissue-of-Origin Prediction Journal: PLOS ONE Type: Response to Reviewers Date: 15 Oct, 2025 Dear Editor and Reviewers, We sincerely thank the Academic Editor and the reviewers for their constructive comments and valuable suggestions that helped us improve the quality and clarity of our manuscript. We have carefully revised the manuscript in accordance with all comments and suggestions. Below, we provide our detailed responses to each point. All changes have been highlighted in the revised manuscript using track changes. Response to Reviewer 1 Comment 1: Why authors used the only CatBoost machine learning technique only. Response: We thank the reviewer for this important question. In previous studies utilizing tumor mutation and methylation data, algorithms such as Random Forest and XGBoost were commonly applied. These models share the characteristic of being tree-based ensemble methods, primarily aimed at extracting features that can explain model predictions. Moreover, in recent biomedical data analyses, CatBoost has emerged as a widely used interpretable model. Accordingly, we compared the performance of CatBoost with Random Forest and XGBoost in our dataset and observed superior performance. Therefore, we applied our proposed informative regional subset analysis using CatBoost. This explanation has been added to the Introduction section (pages 1, lines 30–36). Comment 2: Much more discussion about the results should be given in this paper, especially the author needs to provide enough physical mechanism analysis about the results. Response: We appreciate the reviewer’s insightful comment. In response, we have substantially expanded the Discussion section to include not only a description of the common regions identified as important in our analysis across cancer types, but also detailed analyses of their chromosomal locations. Furthermore, we identified the transcripts within these regions using the UCSC Genome Browser and incorporated relevant biological information and our interpretations. These additions provide a more comprehensive discussion of the potential biological mechanisms underlying our findings (Discussion section, pages 11–12, lines 243–297). Comment 3: The authors should clarify the mathematical framework used to the CatBoost model. Response: Following the reviewer’s suggestion, we have added a detailed explanation of the mathematical framework underlying the CatBoost model. This includes the fundamental principles of gradient boosting and the base model formulation. This new subsection has been incorporated into the Methods section of the revised manuscript. (pages 3–4, lines 120–144) Comment 4: The figures in the manuscript are blurred and need improvement. Response: We have replaced all blurred figures with high-resolution versions and ensured that the axis labels, legends, and annotations are clearly visible in the revised manuscript. In particular, Figure 3, which appeared noticeably less clear than the others, has been replaced with a high-resolution version to improve visual quality. (Result section, page 8, Figure 3) Comment 5: In the manuscript, there are grammatical and spelling mistakes. The language is comprehensive and coherent, but there are some mistakes. Response: We have carefully proofread the entire manuscript and corrected all grammatical and typographical errors. The revised text has also been checked by a professional English editing service. Response to Reviewer 2 Comment 1: To enhance the comprehensiveness of your paper, it would be beneficial to include at least five previous studies for comparative analysis, thereby strengthening its position relative to existing literature on the same topic. Response: We thank the reviewer for this important suggestion. To enhance the comprehensiveness of our manuscript, we have now compared the datasets, analysis methods, and results of recent related studies. We also summarized the limitations of prior work to highlight the novelty and necessity of our study. These revisions have been added to the Introduction section (pages 1–2, lines 30–63). Comment 2: The novelty of the research work is not clear. The authors are suggested to provide suitable novelty aspects. Response: We thank the reviewer for this constructive comment. To clarify the novelty of our study, we have explicitly highlighted the main contributions of our work, including a concise description of the novel aspects of our approach and an expanded literature review to contextualize our findings relative to existing studies. These revisions are included in the Introduction section (pages 2, lines 64–88). (pages 2, lines 64–88) Comment 3: Can you provide justification for claiming that your work over existing work in literature? Response: We appreciate the reviewer’s suggestion. To emphasize the advantages of our study over existing work, we have added a discussion highlighting the limitations of previous studies and the biological and computational strengths of our approach in the Introduction section.(pages 2, lines 48–63) Comment 4: Labels of Fig. 3 are not clearly visible. Authors need to revise it. Response: We have revised Figure 3 to improve label clarity, font size, and contrast for better readability. (Result section, page 8, Figure 3) Comment 5: Most of the cited reference work is before 2020. It is suggested to add latest relevant references. Response: We thank the reviewer for this valuable suggestion. In response, we have added more than 10 recent relevant studies to the manuscript. These additions help to highlight the novelty of our work, differentiate it from existing studies, and clarify the limitations of prior research, thereby emphasizing the advantages of our approach. These revisions are included in the Introduction section. (pages 1–2, lines 30–63) Conclusion We thank the reviewers and editor once again for their time and constructive feedback. We believe that the revised version has been significantly improved and hope that it now meets PLOS ONE’s publication standards. Sincerely, [Sungmin Yang / Professor Hong-Gee Kim] Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0337106.r002
4 Nov 2025 Decision Letter - Yogendra Prajapati, Editor Biologically-Informed Regional Subset Analysis with CatBoost for Robust Tissue-of-Origin Prediction PONE-D-25-42292R1 Dear Dr.Hong-Gee Kim, 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, Yogendra Kumar Prajapati, Ph.D. Academic Editor PLOS ONE Additional Editor Comments (optional): Based on the reviewer's decision, the manuscript may be accepted for publication. 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 #1: All comments have been addressed Reviewer #2: All comments have been addressed ******** 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 #1: Yes Reviewer #2: Partly ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: I Don't Know Reviewer #2: N/A ****** 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 #1: No Reviewer #2: Yes ****** 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 #1: Yes Reviewer #2: Yes ****** 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 #1: Authors are successfully incorporated the my comments. Manuscript can be accepted for the publication. Reviewer #2: (No Response) ****** 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 #1: No Reviewer #2: No ******** https://doi.org/10.1371/journal.pone.0337106.r003
Formally Accepted
Acceptance Letter - Yogendra Prajapati, Editor PONE-D-25-42292R1 PLOS ONE Dear Dr. Kim, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. 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. You will receive an invoice from PLOS for your publication fee after your manuscript has reached the completed accept phase. If you receive an email requesting payment before acceptance or for any other service, this may be a phishing scheme. Learn how to identify phishing emails and protect your accounts at https://explore.plos.org/phishing. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Yogendra Kumar Prajapati Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0337106.r004

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