ERBB2-Mutant Gastrointestinal Tumors Represent Heterogeneous Molecular Biology, Particularly in Microsatellite Instability, Tumor Mutation Burden, and Co-Mutated Genes: An In Silico Study

Round 1

Reviewer 1 Report

in this manuscript the authors creating classification for ERBB2 mutated gastrointestinal (EAC, GC, and CRC) tumors in order to define a better treatment for this small subclasses of tumors. Also correlating the classified groups with different oncogenic signaling pathways like MAPK and PI3K/MTOR. They used available data from Cancer Genome Atlas (TCGA), PanCancer Atlas dataset (EAC), and Memorial Sloan Kettering (MSK) dataset (esophagogastric cancer). They identified three groups based on their analysis that differ in tumor mutation burden and microsatellite instability and clinicopathological features.

The work of trying to subclassify the small percentage of gastrointestinal tumors that has no ERBB2 amplification and to determine the frequency of ERBB2 mutations in each subcategory and this might help in improving the sensitivity to future precision therapeutic.

Overall, the manuscript is well written and understandable to me. The use of publically available datasets and lack of verification of results on actual samples is the weakness I see in this work. Otherwise it is a good work that identified new groups of gastrointestinal tumors based on ERBB2 mutations. And it can be foundation for subsequent investigation. 

I have a very minor comment:

In results figures: the legend states error bars are standard error of the mean. To me the figures seems box-plots so please check if this is correct. 

I have no other concerns.

Thank you to the authors for their work.

Author Response

Thank you very much for taking the time to review this manuscript. As you point out, it is a box-plots. Therefore, we have removed the description of the error bars in Figure 1 and 2.

We are currently working on making figure 3 a sharper image and creating a graphical abstract. I have never created a graphical abstract before and have asked an expert to create one for me. For the other parts, the revision has been complete. According to the expert team, the creation of the graphical abstract is scheduled to be completed on September 9. Image editing for figure 3 is expected to be completed on September 5. Could you please give me a few extra days to make sure everything is in order for me to re-submit the article? We will resubmit as soon as we are ready.

Reviewer 2 Report

I find the study's exploration of activating mutations in the ERBB2 gene in various solid cancers to be of significant importance. The emergence of these mutations and their resemblance to ERBB2 amplifications highlights a potential avenue for targeted therapies in specific cancer types. While effective treatments already exist for some ERBB2-related cancers, there is a notable gap in therapies for ERBB2-mutant esophageal adenocarcinoma (EAC), gastric cancer (GC), and colorectal cancer (CRC). The study's focus on these gastrointestinal tumors and the investigation of potential therapeutic agents that target ERBB2 kinase activity is commendable. However, the study acknowledges the heterogeneity among ERBB2-mutant tumors. Furthermore, the influence of pathways beyond the mutations themselves contributes to the complexity of tumor behavior and treatment response.

The study's objective to categorize diverse ERBB2-mutant tumors based on their biological traits, including clinicopathologic features, MSI, TMB, and co-mutations, using bioinformatics tools is laudable. Such a classification has the potential to guide more tailored treatment strategies, leveraging the unique characteristics of each subgroup to enhance therapeutic outcomes for ERBB2-mutant gastrointestinal cancers.

The "Materials and Methods" section of the article is well-structured, providing a clear overview of the processes, tools, and datasets used in the study. Overall, the study's findings provide valuable insights into the heterogeneous nature of ERBB2-mutant tumors and the potential for tailored treatment strategies. The integration of bioinformatics tools, multi-dataset analysis, and careful classification enhances the validity of the study's conclusions.  I am pleased to offer my recommendation for the publication of this manuscript.

Author Response

Thank you very much for taking the time to review this manuscript. We appreciate your work. We have removed the description of the error bars in Figure 1 and 2.

We are currently working on making figure 3 a sharper image and creating a graphical abstract. I have never created a graphical abstract before and have asked an expert to create one for me. For the other parts, the revision has been complete. According to the expert team, the creation of the graphical abstract is scheduled to be completed on September 9. Image editing for figure 3 is expected to be completed on September 5. Could you please give me a few extra days to make sure everything is in order for me to re-submit the article? We will resubmit as soon as we are ready.