Importance of Patient-Derived Xenograft Models in Battling Cancer Therapy Resistance

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

In the study entitled “Importance of Patient-Derived Xenograft Models in Battling Cancer Therapy Resistance.

This study investigated the Cancer is one of the most common death factors, taking about ten million lives annually. The majority of the casualties are due to the resistance-driven progression and metastasis. While effective, precise, selective therapeutic options are developed through the last 50 years, the cancer cell capability to flexibly change phenotype and avoid drug effects is still hurdling effectiveness. While classic, simple, repeatable models for drug efficacy studies, like cancer cell line cultures, are still widely used, their common failure to be translated to medicine development urged the evolution of novel model systems. In vitro 3D and complex coculture systems, genetically engineered mouse strains of carcinogenesis are widely used. As one flagship of the model choices, patient-derived xenograft models (PDXs) and their derivatives have quickly become commonly used both for drug development and for evaluating tumor responsiveness upon different therapies, driving towards novel combinations and targets in anticancer therapy, and helping clinical decision-making by pre-testing drug response.

However, there are certain pitfalls/comments which need to be addressed before acceptance of this manuscript.

1. Title has a mistake. Please write Therapy.
2. Abstract looks very vague. Please re-write it to include every detail included in the review as different patient derived models, Co- cultures etc and their pitfalls.
3. Many terms are used for the first time as abbreviations throughout the manuscript. Please expand the terms used of the first time like CAR-T cell (line 63), RECIST-iRECIST criteria, CRISPR-Cas9, TALENs, Nude [84], SCID [85], NOD-SCID [86] and NSG [87] etc. Gene names are not expanded most of the times like BRAF, MET etc.
4. In vitro models of cancer used should be given in a table so that it is easy to differentiate between them and pitfalls among each.
5. Please write about 3D spheroids, organoids, and bio printed tissue constructs in tabulated form as their differences and pitfalls. Also, represent in vivo models in tabulated form so that it is easier to understand and learn for the reader.
6. Authors have used very old references like 2007. Please update all the references to no older than 10 years.
7. Review looks like an unplanned structure of details. Please revise all the sections of manuscript thoroughly and provide pitfalls separately for each model discussed. Also, write in detail about the model systems, then elaborate with examples and discuss mechanism of resistance.
8. Revise each section thoroughly and please check the manuscript by native English speaker for grammatical errors.

 

Comments on the Quality of English Language

Please get the manuscript proof read by a native speaker

Author Response

We are thankful for the reviewer’s help in highlighting the pitfalls of the first version of the manuscript. We believe it benefited substantially from the revision. We answer these points one by one. We attached the revised manuscript.

 

1. Title has a mistake. Please write Therapy.

Agreed, we corrected the fault.

 

2. Abstract looks very vague. Please re-write it to include every detail included in the review as different patient derived models, Co- cultures etc and their pitfalls.

We rewrote the abstract; however, due to word limits, we could not detail all models as we wished. We hope that it still shows what the article is about and gives an overall view of our focus and aim.

 

3. Many terms are used for the first time as abbreviations throughout the manuscript. Please expand the terms used of the first time like CAR-T cell (line 63), RECIST-iRECIST criteria, CRISPR-Cas9, TALENs, Nude [84], SCID [85], NOD-SCID [86] and NSG [87] etc. Gene names are not expanded most of the times like BRAF, MET etc.

We are thankful for the comment, indeed it needed a thorough improvement. Now we added all names at the first occurrence to resolve the abbreviations.

 

4. In vitro models of cancer used should be given in a table so that it is easy to differentiate between them and pitfalls among each.

 

We agree that the table format could help in the comparison of the model properties. We created the extra table; however, due to another reviewer’s request to keep model descriptions proportionally shorter and the PDX/resistance part more elaborate, we kept it for now in the present letter, asking for help from the Editorial Office to decide whether these tables should be edited into the text. Additionally, Figure 4 in the manuscript is intended to serve the same role (summarizing both in vitro and in vivo models in the same table), which might bypass the problem.

Table 1: characteristics of different in vitro models

 

Model	Price	throughput	repeatability	TME	challenges
2D cell lines	$	+++	+++	-	low clinical relevance
2D co-cultures	$$	++	+++	+	lack of 3D heterogeneity
3D spheroids/organoids	$$	++	++	+	low repeatability, cell line based lack of heterogeneity
3D printed organoids/tissues	$$$	+	++	++	limited complexity, cell line based lack of heterogeneity
Patient-derived organoids	$$$	+	++	++	low throughput and repeatability, small scale
PDX-derived organoids	$$$$	+	++	++	low throughput and repeatability, small scale

 

5. Please write about 3D spheroids, organoids, and bio printed tissue constructs in tabulated form as their differences and pitfalls. Also, represent in vivo models in tabulated form so that it is easier to understand and learn for the reader.

 

This issue is partially addressed in the previous answer (in vitro models). For in vivo models, we created the following table.

Table 4: characteristics of in vivo models

 

Model	Price	throughput	immune system	TME	heterogeneity	relevant resistance mechanisms	challenges
Cell derived allografts	$$	++	+++	+	-	-	low clinical relevance, murine cell specificity
cell-derived xenografts	$$$	++	-	+	-	-	low clinical relevance, no immune system
genetically engineered mouse models	$$$$	+	+++	++	++	+	slow, expensive, murine cell specificity
Patient-derived organoid xenografts	$$$$	+	-	+++	+++	++	slow, expensive, no immune system, limited heterogeneity
Patient-derived xenografts	$$$$	+	-	+++	+++	+++	slow, expensive, no immune system, limited heterogeneity
Humanized PDX	$$$$$	+	++	+++	+++	++	expensive, graft versus host disease, short experiments only, limited heterogeneity

 

6. Authors have used very old references like 2007. Please update all the references to no older than 10 years.

We revised the old references. Out of 160 references, 51 were older than 2016. We revised those individually and replaced where applicable with recent literature. In some cases, original descriptions (e.g., mouse strains) are the authentic source and are still requested to be cited.

In the present form, the manuscript has 143 references, of which 28 are from before 2016. The majority of those are historical papers, such as the original description of mouse strains, or the brief history of BRAF V600E treatment and resistance in melanoma throughout the review. If any remaining references need explanation or change, we are flexible.

 

7. Review looks like an unplanned structure of details. Please revise all the sections of manuscript thoroughly and provide pitfalls separately for each model discussed. Also, write in detail about the model systems, then elaborate with examples and discuss mechanism of resistance.

 

We are thankful for that point and reformed all sections of the manuscript. We added challenges of all model types individually, and summarized their role in resistance research, with the utmost focus still on PDX models.

 

8. Revise each section thoroughly and please check the manuscript by native English speaker for grammatical errors.

We revised and corrected the English errors in the manuscript accordingly.

 

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

The title of the review deals with the use of PDX samples in screening for potential therapeutics for cancer patients and does a reasonable job presenting the use of PDX samples.  However the initial 50% of the paper deals with alternative methods cell culture, 2D and 3D , xenografts, GEM models.  This results in almost 50% of the article not dealing with the title of the article.  While one might expect a brief commentary on these other assays devoting almost 50% of the article on these other models is probably excessive.   In contrast a bit further description of how PDX samples are collected and limitations in collecting those samples might be usefrul. 

Comments on the Quality of English Language

In a variety of places the English employed is difficult to understand.  If the editors of the journal are OK with it using AI to check individual sentences for grammar or comprehensibility would be useful.  That is a different question from asking AI to rewrite significant portions of the manuscript. 

Author Response

We are thankful for the reviewer’s work and comments. We believe that the aspects have improved the quality of the article substantially.

1. The title of the review deals with the use of PDX samples in screening for potential therapeutics for cancer patients and does a reasonable job presenting the use of PDX samples.  However the initial 50% of the paper deals with alternative methods cell culture, 2D and 3D , xenografts, GEM models.  This results in almost 50% of the article not dealing with the title of the article.  While one might expect a brief commentary on these other assays devoting almost 50% of the article on these other models is probably excessive.   In contrast a bit further description of how PDX samples are collected and limitations in collecting those samples might be usefrul. 

We are thankful for the comment, indeed, excessive description was pushing the focus away from the exact topic. Therefore we revised and shortened the explanatory parts, while added some more details to the PDX part, believing that not only this makes it useful, but also more unique among reviews in the topic. Since another reviewer asked more detailed analysis on the other models, we suggested those details in the review letter / supplementary data form, letting the Editorial office to decide in this question.

 

 

2. In a variety of places the English employed is difficult to understand.  If the editors of the journal are OK with it using AI to check individual sentences for grammar or comprehensibility would be useful.  That is a different question from asking AI to rewrite significant portions of the manuscript. 

We revised the text and in many places we switched to more simple sentence structures. We avoided the use of AI doing this, while the checkup was run also on large language model, any changes were only made personally by the authors.

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript presents a narrative review on the use of patient-derived xenograft (PDX) models in the study of therapeutic resistance in cancer. Although the topic is relevant and of interest to translational oncology, the manuscript has significant limitations in terms of originality, conceptual depth, and innovative contribution to the field. In its current state, the work does not reach the level of novelty expected for a high-impact journal.

The article adequately summarizes well-established concepts related to:

• therapeutic resistance,
• 2D and 3D models,
• organoids,
• GEMMs,
• PDXs
• humanized models.

 

 

 

Major concerns.

1. The review is predominantly descriptive and reproduces information previously published in multiple recent reviews on PDX models and therapeutic resistance.
2. The manuscript lacks an innovative conceptual approach, in-depth critical analysis, or mechanistic integration that would enable identification of a distinctive contribution to the field.
3. Although the authors mention some methodological limitations, the discussion is insufficient. The true clinical predictive value of PDXs compared to other emerging models is also not critically discussed.
4. Several excessively long and redundant sentences make reading difficult.
5. There are many typographical errors.
6. It's recommended to rewrite the review and remark on the novelty regarding many other similar published reviews.

Author Response

We are grateful for the reviewer’s work and comments, which helped us a lot to improve the manuscript, we hope that the novel focus is more emphasized in the new version.

The manuscript presents a narrative review on the use of patient-derived xenograft (PDX) models in the study of therapeutic resistance in cancer. Although the topic is relevant and of interest to translational oncology, the manuscript has significant limitations in terms of originality, conceptual depth, and innovative contribution to the field. In its current state, the work does not reach the level of novelty expected for a high-impact journal. The article adequately summarizes well-established concepts related to therapeutic resistance, 2D and 3D models, organoids, GEMMs, PDXs humanized models.

We agree that reproduction of former reviews is not a work worthy to do. Our aim was – and still is – to show how the field of cancer therapy resistance can exploit the possibilities of PDX (or other) models. The large number of recent reviews are mainly focusing on different models, their advantages in primary drug screening or co-clinical trials (screening primary therapy response). Our manuscript also contains such parts, as it is almost unavoidable to omit that. However, we went further than that. We summarized the progress of therapy resistance research using PDX models in numerous major cancer types, emphasizing the wider focus of the use of modern experimental models. As cancer resistance and consequent progression and metastasis is likely the biggest hurdle in cancer management, and we did not find general reviews about resistance research by advanced models, we believe our manuscript could help open discussion about this topic and start projects in PDX research centers.

 

Major concerns.

1. The review is predominantly descriptive and reproduces information previously published in multiple recent reviews on PDX models and therapeutic resistance.

Our aim was to bring novelty by introducing the impact of PDX models in resistaance research. Obviously, it needed introduction of many model choices, resistance mechanisms, and history of good and vague results. In our experience, resistance-related topic was collected in reviews only regarding one certain tumor type, its significance or abundance among a variety of cancer types was not collected.

2. The manuscript lacks an innovative conceptual approach, in-depth critical analysis, or mechanistic integration that would enable identification of a distinctive contribution to the

 

We emphasized more in the discussion of the article: our main message that PDX-based research techniques (involving PDXO, PDO, or PDOX) are invaluable in successfully mapping and tackling resistance in cancer. As it was shown in a recent review (Jian et al, Mol. Cancer, 2026, PMID: 41699647), PDX is not the holy grail in itself, indeed it needs to be integrated with other models. However, we keep it an important point that the use of proper preclinical methods can lead us to clinically relevant resistance mechanisms, which contributes targeting the disease more efficiently.

 

3. Although the authors mention some methodological limitations, the discussion is insufficient. The true clinical predictive value of PDXs compared to other emerging models is also not critically discussed.

 

We extended the section on limitations and discussed possible escape routes to overcome these challenges. Clinical predictive value of PDX, PDO, or other models is still being evaluated, and their reliability proven to be higher than cell-line-based experimental science; however, their use is context-dependent. We built the evaluation into the discussion.

 

4. Several excessively long and redundant sentences make reading difficult.

 

We went through the manuscript, and separated unpleasantly complex sentences to more sentences. Also, we screened and cleaned the manuscript of redundant information.

 

5. There are many typographical errors.

 

We revised the manuscript thoroughly to correct the typos. We are sorry for the inconvenience.

 

6. It's recommended to rewrite the review and remark on the novelty regarding many other similar published reviews.

 

We changed and extended the summary and discussion parts in order to clarify our statements about the topic. Our points are mainly the focus on the reasons of therapy failure instead of continuously screening for new compounds, and the importance of the existence of such studies, emphasizing PDX-centers to evaluate emerging resistance mechanisms on their PDX systems, and predicting potential therapies that can avoid or at least delay the failure of anticancer effects. In our view, while general use and characterization of PDX models were reviewed many times before, the focus on resistance research makes our review novel and different from previously published material.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

References need to be updated. Authors have just deleted the references and not updated any. Please update further.

English editing needs to be done by a native speaker throughout the manuscript.

Comments on the Quality of English Language

Please get the manuscript proof read by a native speaker

Author Response

We are thankful for the reviewer’s help in highlighting the pitfalls of the last version of the manuscript. We attached the revised form of the manuscript. We believe it benefited substantially from the revision.  We answer these points one by one.

 

1. References need to be updated. Authors have just deleted the references and not updated any. Please update further.

 

Again, we revised all references particularly dated before 2016. The refreshment and reasoning is found in the following table:

 

 

Reference number	Year	Replaced?	If not, reasoning
7	1977	no	historical data
9	2008	PMID: 37442207
27	2013	no	historical data
36	2013	PMID: 35822563
40	2012	no	historical BRAF data
41	2015	no	historical BRAF data
51	2014	PMID: 36280768
55	2010	no	historical BRAF data
70	1993	no	original mouse model data
71	1995	no	original mouse model data
72	2005	no	original mouse model data
73	2002	no	original mouse model data
74	1998	no	original mouse model data
76	2009	PMID: 34011964
77	2011	PMID: 27616293
78	2012	PMID: 37277206
81	2015	no	original NCI PDX database citation
90	2004	no	historical pioneer targeted therapy
100	2014	no	Relevant PDX CRC research
101	2015	no	Relevant PDX CRC research
102	2015	no	Relevant PDX CRC research
104	2013	no	Relevant PDX CRC research
124	2014	no	original BRAFi MEKi data
135	2015	no	first important PDX article in the topic
139	2012	PMID: 38821942
144	2012	no	Relevant PDX RCC research

 

 

2. English editing needs to be done by a native speaker throughout the manuscript.

 

We implemented full revision of grammar with native speaker and improved grammar issues.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

I appreciate the efforts made by the authors to revise the manuscript. However, after carefully evaluating the revised version, I conclude that the major concerns raised during the initial review have not been adequately addressed. The manuscript still lacks sufficient novelty, critical depth, and a distinctive scientific contribution to justify publication. The principal limitations identified in the first evaluation remain largely unchanged.

Therefore, I am unable to recommend publication in its current form.

Major Concerns

1. Limited novelty and innovation

The revised manuscript continues to present a predominantly descriptive overview of patient-derived xenograft (PDX) models and their applications in therapeutic resistance research. While the topic remains relevant, the review does not offer a novel conceptual framework, innovative perspective, or unique synthesis that advances current understanding of the field.

The content largely reiterates information already available in numerous recent reviews addressing PDX models, therapeutic resistance, organoids, genetically engineered mouse models (GEMMs), and humanized systems. The revisions do not substantially increase the originality of the manuscript.

2. Limited coverage of the literature

The manuscript relies on a relatively small number of studies considering the breadth and complexity of the topic. The literature coverage remains insufficient to support a comprehensive state-of-the-art review. Several recent advances in PDX-based precision oncology, humanized PDX platforms, multi-omics integration, and next-generation translational models are not discussed in adequate depth.

3. Lack of mechanistic depth

The central theme of therapeutic resistance requires deeper mechanistic exploration. The manuscript still focuses primarily on descriptive aspects of model systems rather than on analyzing the biological mechanisms driving resistance and how PDX models contribute to their investigation.

Author Response

We are grateful for the reviewer’s comments, which helped us a lot to improve the manuscript, we emphasized the novel focus in the new version. We attached the revised manuscript, highlighting the changes.

Major Concerns

 

Limited novelty and innovation

The revised manuscript continues to present a predominantly descriptive overview of patient-derived xenograft (PDX) models and their applications in therapeutic resistance research. While the topic remains relevant, the review does not offer a novel conceptual framework, innovative perspective, or unique synthesis that advances current understanding of the field.

 

We agree that reproduction of former reviews is not a work worthy to do. We presented the progress of Cancer resistance research (novel mechanisms, overcoming resistance) using PDX models, a topic that was not yet discussed in previous reviews.

 

The content largely reiterates information already available in numerous recent reviews addressing PDX models, therapeutic resistance, organoids, genetically engineered mouse models (GEMMs), and humanized systems. The revisions do not substantially increase the originality of the manuscript.

 

We meticulously reviewed the literature and picked all important data from previous literature. Our manuscript is pioneer in discussing PDX and cancer resistance in general.

 

Limited coverage of the literature

The manuscript relies on a relatively small number of studies considering the breadth and complexity of the topic. The literature coverage remains insufficient to support a comprehensive state-of-the-art review. Several recent advances in PDX-based precision oncology, humanized PDX platforms, multi-omics integration, and next-generation translational models are not discussed in adequate depth.

 

We screened again the literature and added fourteen new articles which are important in the field. Additionally, mirroring the latest news, we incorporated data about pancreatic cancer resistance research, and all the modern platforms and models.

 

Lack of mechanistic depth

The central theme of therapeutic resistance requires deeper mechanistic exploration. The manuscript still focuses primarily on descriptive aspects of model systems rather than on analyzing the biological mechanisms driving resistance and how PDX models contribute to their investigation.

As therapy resistance is a complex and yet largely unveiled field, we focused on data already obtained, mechanisms and strategies already proved experimentally. This includes the biological mechanisms in each cancer types that were so far explored.

Author Response File: Author Response.docx

Round 3

Reviewer 3 Report

Comments and Suggestions for Authors

I thank the authors for addressing most of the observations made in previous versions of the manuscript. After reviewing the new version, I believe the work has undergone a substantial improvement in both its structure and scientific content.

There is a significant improvement in the contextualization of the mechanisms of therapeutic resistance, significantly strengthening the manuscript's conceptual foundation.

Furthermore, although the addition of new bibliography is limited to 14 additional references, the authors successfully integrated these references with the restructuring of the manuscript's narrative, resulting in a more solid and coherent scientific context.

This is reflected in the shift from a descriptive narrative to a more critical discussion, increasing the manuscript's academic value.

Therefore, I recommend publishing the current manuscript after correcting minor editorial errors.