Bioinformatic Analysis of Contrasting Expression Patterns and Molecular Interactions of TIMPs in Breast Cancer: Implications for Tumor Progression and Survival

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript systematically analyzes the expression patterns, prognostic value, and molecular interactions of Tissue Inhibitors of Metalloproteinases (TIMPs) in breast cancer using bioinformatics methods. The authors utilized databases such as TCGA and cBioPortal to explore the differential expression of TIMP1-4 across different breast cancer molecular subtypes and stages, finding that TIMP1 is significantly highly expressed in tumor tissues, while other TIMPs show a trend of low expression. Furthermore, the study revealed potential signaling pathways associated with TIMPs, such as the PI3K-Akt and MAPK signaling pathways, through GO and KEGG enrichment analyses, providing clues for understanding the dual role of TIMPs in breast cancer progression. However, there are still some obvious deficiencies in this manuscript that require modification and improvement by the authors.

 

Major Comments

1. The authors mainly rely on public databases for bioinformatics analysis, lacking validation from external datasets or support from wet-lab experimental data, which limits the robustness of the conclusions to a certain extent. The authors should consider using other independent breast cancer datasets from the GEO database to validate the main findings in order to rule out potential biases from a single database. Additionally, although the article describes the correlation between TIMP expression and prognosis, to enhance clinical translational significance, the authors should further utilize immunohistochemistry (IHC) staining images from the Human Protein Atlas (HPA) database to validate the expression differences of TIMP1-4 at the protein level. This will help confirm whether changes at the mRNA level translate into functional changes at the protein level. Regarding statistical methods, although survival analysis is mentioned in the text, the authors should clarify whether multivariate Cox regression analysis was performed to determine whether the prognostic value of TIMPs is independent of clinical-pathological characteristics such as age and stage, which is crucial for establishing their status as independent prognostic biomarkers.
2. The current exploration of the interaction between TIMPs and the tumor microenvironment (TME) is not deep enough, and the analysis regarding immune infiltration appears relatively limited. Considering TIMPs as key regulators of the extracellular matrix, they may have a significant impact on the recruitment and function of immune cells. The authors should use algorithms such as CIBERSORT or ESTIMATE to analyze in detail the correlation between TIMP expression and the infiltration levels of major immune cell subsets (such as macrophages, T cells, etc.). Furthermore, for the key signaling pathways identified in the enrichment analysis, the authors should conduct a deeper mechanistic discussion combining existing literature, rather than just listing pathway names. For example, they should elucidate the specific molecular mechanisms by which TIMPs might regulate the PI3K-Akt pathway to affect cell survival and migration.
3. To further enhance the theoretical depth and cutting-edge nature of the article, it is suggested that the authors expand the discussion in the Introduction or Discussion sections by incorporating recent advances in related fields. Currently, research on breast cancer and pan-cancer has entered a new stage of multi-omics integration. The authors could discuss the application of multi-omics data integration in predicting breast cancer survival rates (doi: 10.1002/imm3.70010), as well as the importance of the immune microenvironment and anti-tumor immunity (doi: 10.1002/mdr2.70007). Additionally, the impact of psychological stress signaling pathways on the breast cancer microenvironment (doi: 10.34133/research.0980) is also an emerging direction worth noting. Finally, from the perspective of drug discovery, a discussion related to target screening and validation using multi-omics technologies (doi: 10.1016/j.cpan.2024.12.001) would help improve the clinical application value of the article.

 

Minor Comments

1. The current English expression in the article contains some grammatical errors and non-idiomatic phrasing, which may affect the reader's experience and accurate understanding of the article's content. It is suggested that the authors seek professional native English editing services to conduct careful language proofreading of the full text.

Author Response

Reviewer's comments 1

 

Major Comments

 

1. The authors mainly rely on public databases for bioinformatics analysis, lacking validation from external datasets or support from wet-lab experimental data, which limits the robustness of the conclusions to a certain extent. The authors should consider using other independent breast cancer datasets from the GEO database to validate the main findings in order to rule out potential biases from a single database. Additionally, although the article describes the correlation between TIMP expression and prognosis, to enhance clinical translational significance, the authors should further utilize immunohistochemistry (IHC) staining images from the Human Protein Atlas (HPA) database to validate the expression differences of TIMP1-4 at the protein level. This will help confirm whether changes at the mRNA level translate into functional changes at the protein level. Regarding statistical methods, although survival analysis is mentioned in the text, the authors should clarify whether multivariate Cox regression analysis was performed to determine whether the prognostic value of TIMPs is independent of clinical-pathological characteristics such as age and stage, which is crucial for establishing their status as independent prognostic biomarkers.

 

Answer: The reviewer's comment is very accurate. For this new version of the manuscript, the authors have added results describing TIMPs expression in breast cancer patients and cell lines, considering molecular subtypes. The analyzed data come from the GEO repository. Furthermore, to increase translational clinical relevance, the authors have added results using immunohistochemical (IHC) staining images from the Human Protein Atlas (HPA) database to validate differences in TIMP1-4 expression at the protein level. It is important to mention that only the frequencies of TIMP1 and TIMP2 expression levels in breast cancer patient samples compared to non-tumor samples were included. Data on TIMP3 and TIMP4 levels at the protein level used are not yet available in the HPA. Nor is there a molecular classification of the samples. The authors have clarified the aforementioned points in the results section of the manuscript and highlighted the limitations of this analysis.

 

Answer: In the survival analyses, the authors performed univariate Cox regression analyses to associate TIMPs expression levels with overall patient survival. Although the reviewer's comment is interesting, the objective of this research was not to identify and determine the prognostic value of TIMPs independently of clinicopathological characteristics such as age and stage. However, in this revised version of the manuscript, the authors have described the type of analysis performed more clearly and concisely in the Materials and Methods section corresponding to these results.

 

2. The current exploration of the interaction between TIMPs and the tumor microenvironment (TME) is not deep enough, and the analysis regarding immune infiltration appears relatively limited. Considering TIMPs as key regulators of the extracellular matrix, they may have a significant impact on the recruitment and function of immune cells. The authors should use algorithms such as CIBERSORT or ESTIMATE to analyze in detail the correlation between TIMP expression and the infiltration levels of major immune cell subsets (such as macrophages, T cells, etc.). Furthermore, for the key signaling pathways identified in the enrichment analysis, the authors should conduct a deeper mechanistic discussion combining existing literature, rather than just listing pathway names. For example, they should elucidate the specific molecular mechanisms by which TIMPs might regulate the PI3K-Akt pathway to affect cell survival and migration.

 

Answer: We thank the reviewer for this valuable suggestion. In response, we performed an extended immune infiltration analysis to systematically evaluate the association between TIMP1, TIMP2, TIMP3, and TIMP4 expression and the tumor immune microenvironment in breast cancer.  Using normalized RNA-seq data from TCGA PanCancer Breast Invasive Carcinoma dataset (n = 1084), immune and stromal cell infiltration was inferred with the EPIC deconvolution algorithm, which estimates the relative proportions of major immune cell populations and cancer-associated fibroblasts. First, we assessed global associations between TIMP expression levels and immune cell fractions by performing Spearman correlation analyses, and the results are summarized in a correlation heatmap. To further validate and complement these findings, samples were subsequently stratified into high- and low-expression groups for each TIMP based on the median expression value. Differences in immune and stromal cell infiltration between groups were evaluated using the Wilcoxon rank-sum test with Benjamini–Hochberg false discovery rate correction. These analyses revealed significant and consistent differences in immune and stromal cell infiltration according to TIMP expression status, particularly involving cancer-associated fibroblasts, endothelial cells, macrophages, and NK cells. Together, these complementary approaches provide a comprehensive assessment of the relationship between TIMP expression and the immune landscape of breast cancer and have now been incorporated into the revised manuscript. Furthermore, in this new version of the manuscript, the authors have added a more in-depth mechanistic discussion section by combining existing literature, which includes the specific molecular mechanisms by which TIMPs could regulate the PI3K-Akt pathway to affect cell survival and migration.

 

3. To further enhance the theoretical depth and cutting-edge nature of the article, it is suggested that the authors expand the discussion in the Introduction or Discussion sections by incorporating recent advances in related fields. Currently, research on breast cancer and pan-cancer has entered a new stage of multi-omics integration. The authors could discuss the application of multi-omics data integration in predicting breast cancer survival rates (doi: 10.1002/imm3.70010), as well as the importance of the immune microenvironment and anti-tumor immunity (doi: 10.1002/mdr2.70007). Additionally, the impact of psychological stress signaling pathways on the breast cancer microenvironment (doi: 10.34133/research.0980) is also an emerging direction worth noting. Finally, from the perspective of drug discovery, a discussion related to target screening and validation using multi-omics technologies (doi: 10.1016/j.cpan.2024.12.001) would help improve the clinical application value of the article.

 

Answer: The reviewer's suggestion is certainly very accurate and relevant. In this new version of the manuscript, the authors have expanded the discussion in the Introduction and Discussion sections, incorporating recent advances in related fields. In these sections, the authors discuss the application of multi-omics data integration in predicting breast cancer survival rates, as well as the importance of the immune microenvironment and antitumor immunity, the impact of psychological stress signaling pathways on the breast cancer microenvironment, and the prospect of drug discovery, including target selection and validation using multi-omics technologies. In this current version of the discussion, the authors have considered the following references suggested by the reviewer: (doi: 10.1002/imm3.70010), (doi: 10.1002/mdr2.70007), (doi: 10.34133/research.0980), (doi: 10.1016/j.cpan.2024.12.001).

 

Minor Comments

 

The current English expression in the article contains some grammatical errors and non-idiomatic phrasing, which may affect the reader's experience and accurate understanding of the article's content. It is suggested that the authors seek professional native English editing services to conduct careful language proofreading of the full text.

 

Response: We appreciate the reviewer's suggestion. For this new version of the manuscript, we have contracted MDPI's English editing service for the authors. The English editing adjustments are displayed using tracked changes. The authors have attached the certificate below for your verification.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript shows the re-analysis of expressional profiling with TIMP family using TCGA-BRCA datasets. Standard analyses are performed, but it's just basic and not very interesting. However, due to the lack of similar studies, this study certainly provides some important information. This reviewer have some important concerns that can be addressed with some clarification and text revision.

1. There is no information of sample number in the survival analyses.

2. Not only MMPs but also proteases such as ADAMs should be checked in the correlational analysis.

3. TIMPs also play important roles in the tumor microenvironment, particularly in immune cells and fibroblasts, and this should be considered and described in the introduction and discussion sections.

Author Response

Reviewer's comments 2

Comments and Suggestions for Authors

This manuscript shows the re-analysis of expressional profiling with TIMP family using TCGA-BRCA datasets. Standard analyses are performed, but it's just basic and not very interesting. However, due to the lack of similar studies, this study certainly provides some important information. This reviewer have some important concerns that can be addressed with some clarification and text revision.

1. There is no information of sample number in the survival analyses.

Answer: The authors thank the reviewer for their valuable comment; in this new version of the manuscript we have added the number of samples in the materials and methods section that describes the survival analyses.

2. Not only MMPs but also proteases such as ADAMs should be checked in the correlational analysis.

Answer: The reviewer's suggestion is very accurate and valuable. In this new version of the manuscript, the authors have added and verified the correlational analysis of TIMPs with ADAMs proteases. The results were interesting and precise in justifying the relationship of TIMPs and ADAMs in the progression and prognosis of BRCA. The authors thank the reviewer for this important suggestion.

3. TIMPs also play important roles in the tumor microenvironment, particularly in immune cells and fibroblasts, and this should be considered and described in the introduction and discussion sections.

Answer: The authors are grateful for the reviewer's insightful suggestion. In this revised version of the manuscript, the authors have analyzed the relationship between TIMP expression (high and low) and immune cell infiltration using normalized RNA-seq data from the TCGA PanCancer Breast Invasive Carcinoma dataset (n = 1084) and the EPIC deconvolution algorithm. Furthermore, the results obtained are described in the introduction and interpreted in the discussion section.

 

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I have carefully reviewed the revised manuscript titled "Bioinformatic Analysis of Contrasting Expression Patterns and Molecular Interactions of TIMPs in Breast Cancer: Implications for Tumor Progression and Survival." While I acknowledge the authors' efforts to modify the text and address certain points raised in the previous round of review, I regret to inform you that the fundamental limitations of the study have not been adequately resolved.

The modifications in this version appear to be largely textual or cosmetic, rather than substantive improvements to the scientific content. The study remains a descriptive bioinformatic analysis relying heavily on public database mining (TCGA, GEO, cBioPortal) without sufficient experimental validation (wet lab) or deep mechanistic exploration to support the correlational findings. Given that the role of TIMPs in breast cancer is a well-established area of research, a purely in silico study requires significant novelty or robust clinical validation to warrant publication. Unfortunately, this revision does not provide new biological insights or overcome the lack of experimental rigor noted previously. As the essential disadvantages regarding the study's depth and novelty persist, I cannot recommend this manuscript for publication.

Author Response

Comments for reviewer 1

The authors would like to thank the reviewer for all comments and suggestions. Each of their comments has been very helpful in giving greater impact and rigor to our research. Thank you very much.

Reviewer 2 Report

Comments and Suggestions for Authors

The authors addressed all my concerns.

Author Response

Comments for reviewer 2

The authors appreciate the time the reviewer dedicated to reviewing this manuscript. Their comments and suggestions have been very helpful in giving this research greater focus and rigor.

Thank you very much.