Race-Associated EGFR and KRAS Mutation Profiles in Lung Adenocarcinoma

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The study is by no means original. The prevalence of EGFR and KRAS mutations in lung adenocarcinoma in different ethnicities and in smokers versus non smokers are widely known. However the study  is formulated in a clear and elegant way and may be of interest for readers. The retrospective results may have significant implications for biomarker – driven therapies based on equity. The paper requires no comments or suggestions.

As I wrote, the manuscript is clearly written and addresses an important topic.
However the observations reported in this study—namely, the associations between EGFR and KRAS mutations,
smoking status, and racial or ethnic background in lung adenocarcinoma—are already well established in the literature,
including analyses based on public databases. The manuscript appears largely to reproduce previously reported findings
without providing a clearly novel hypothesis, independent validation, new methodology, mechanistic insight,
or clinically actionable interpretation. Merely referring to, or reanalyzing findings comparable to, a TCGA series does not establish originality.
The authors should clearly specify what new knowledge this study contributes beyond existing TCGA analyses
and previously published cohorts. However the style of the manuscript , the tables are clear and elegant.

Author Response

Comment: The study is by no means original. The prevalence of EGFR and KRAS mutations in lung 
adenocarcinoma in different ethnicities and in smokers versus nonsmokers are widely known. However, 
the study is formulated in a clear and elegant way and may be of interest for readers. The retrospective 
results may have significant implications for biomarker–driven therapies based on equity. The paper 
requires no comments or suggestions. As I wrote, the manuscript is clearly written and addresses an 
important topic. However, the observations reported in this study—namely, the associations between 
EGFR and KRAS mutations, smoking status, and racial or ethnic background in lung adenocarcinoma—
are already well established in the literature, including analyses based on public databases. The manuscript 
appears largely to reproduce previously reported findings without providing a clearly novel hypothesis, 
independent validation, new methodology, mechanistic insight, or clinically actionable interpretation. 
Merely referring to, or reanalyzing findings comparable to, a TCGA series does not establish originality. 
The authors should clearly specify what new knowledge this study contributes beyond existing TCGA 
analyses and previously published cohorts. However, the style of the manuscript and the tables are clear 
and elegant. 

Response: We sincerely thank the reviewer for their thoughtful evaluation and 
encouraging comments regarding our manuscript. We greatly appreciate their recognition 
of the manuscript's clarity, the importance of the topic, and the potential implications of 
our findings for biomarker-driven precision oncology. We also appreciate the reviewer’s 
perspective regarding the established associations among EGFR and KRAS mutations, 
smoking status, and racial background in lung adenocarcinoma, and we acknowledge 
these findings within the context of the existing literature. We are grateful for the 
reviewer’s time, careful consideration, and positive assessment of our work. The current 
analysis also includes publicly available clinicogenomic data from the MSK Lung 
Adenocarcinoma Met Organotropism cohort; we characterized distinct mutation 
patterns across racial groups and further examined how smoking status influences these 
molecular profiles. Notably, we identify enrichment of EGFR alterations in Asian patients, 
greater KRAS prevalence in White patients, and important smoking-associated 
differences in mutation frequencies across racial cohorts. We have tried to add some 
modifications as per reviewer suggestion. The changes are in red. 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript by de Dios et al. describes a retrospective study evaluating the distribution of EGFR, KRAS, and TP53 mutations among patients with lung adenocarcinoma (LUAD) across different racial and demographic groups. The authors analyzed a Memorial Sloan Kettering dataset available through cBioPortal and further examined mutation prevalence according to smoking status. The study addresses a clinically relevant topic and may provide useful information for understanding demographic differences in LUAD molecular profiles and for guiding the development of mutation-directed treatment strategies.

Although the study is generally well conceived, several discrepancies in the analysis, presentation, and interpretation of the data reduce the overall impact of the manuscript and should be addressed.

1. In Table 1, it is unclear how the percentages of never smokers and ever smokers were calculated because the numbers in these categories do not add up to the total number of patients in each racial cohort. The authors should clearly specify the number of patients with available smoking-history data for each group and indicate the denominator used to calculate each percentage.
2. The information presented in Table 2 appears to duplicate the smoking-status data already provided in Table 1. The authors should clarify how Table 2 differs from Table 1 or consider removing Table 2 to avoid redundancy.
3. The percentage calculations in Table 3 appear to be inconsistent with the reported patient numbers. For example, 190 EGFR-mutated patients among 251 Asian patients would correspond to approximately 75.7%, rather than the reported 64%. Similar inconsistencies appear in other racial groups and mutation categories. The authors should verify all numerators, denominators, and percentage calculations throughout the table. The fact that the percentages of EGFR, KRAS, and TP53 mutations within a racial group exceed 100% is not necessarily an error, because individual tumors may harbor mutations in more than one gene; however, the manuscript should explicitly state that these mutation categories are not mutually exclusive.

The authors should carefully review all statistical calculations, clarify the denominators used in each analysis, correct inconsistencies between the text and tables, and substantially improve the language and grammar throughout the manuscript. A revised manuscript addressing these concerns would be required before the study can be adequately evaluated.

Comments on the Quality of English Language

The quality of language is average and needs to be improved. There are several grammatical errors.

Author Response

1. Comment: In Table 1, it is unclear how the percentages of never smokers and ever smokers were calculated 
   because the numbers in these categories do not add up to the total number of patients in each racial cohort. 
   The authors should clearly specify the number of patients with available smoking-history data for each 
   group and indicate the denominator used to calculate each percentage. 
   Response: We thank the reviewer for identifying this ambiguity. Smoking-status 
   percentages were calculated using only patients with available smoking-history data 
   rather than the total number of patients within each racial cohort. To clarify the 
   denominators used for these calculations, Table 1 has been revised to report the number 
   of patients with available smoking-history data for each racial group. Smoking history was 
   available for 91 Asian, 33 Black, and 601 White patients, and cases with missing or 
   unavailable smoking data were excluded from percentage calculations. Accordingly, 
   never-smoker frequencies are now presented as 72/91 (79%), 11/33 (33%), and 115/601 
   (19%), and ever-smoker frequencies as 19/91 (21%), 22/33 (67%), and 486/601 (81%) 
   for Asian, Black, and White patients, respectively (Table 1, lines 188–196).  The 
   corresponding Results text was also revised to clarify that these proportions are 
   calculated among patients with available smoking-history data (lines 184–187 and 202
   204). The changes are in red so they are apparent. 
   Comment: The information presented in Table 2 appears to duplicate the smoking-status data already 
   provided in Table 1. The authors should clarify how Table 2 differs from Table 1 or consider removing 
   Table 2 to avoid redundancy. 
   Response: We agree with the reviewer that the former Table 2 duplicated the smoking
   status information already presented in Table 1. The former Table 2 has therefore been 
   removed, and the smoking-status information has been retained in Table 1 with the 
   corresponding available-data denominators clearly specified (Table 1, lines 188–196).   
   The Results section was revised accordingly so that the smoking-status findings now refer 
   directly to Table 1 (lines 202–204). Following removal of the former Table 2, the 
   subsequent tables were renumbered: the former Table 3 is now Table 2, and the former 
   Table 4 is now Table 3, with corresponding in-text references updated throughout the 
   Results section (lines 205–217). The changes are in red so they are apparent. 
   Comment: The percentage calculations in Table 3 appear to be inconsistent with the reported patient 
   numbers. For example, 190 EGFR-mutated patients among 251 Asian patients would correspond to 
   approximately 75.7%, rather than the reported 64%. Similar inconsistencies appear in other racial groups 
   and mutation categories. The authors should verify all numerators, denominators, and percentage 
   calculations throughout the table. The fact that the percentages of EGFR, KRAS, and TP53 mutations 
   within a racial group exceed 100% is not necessarily an error, because individual tumors may harbor 
   mutations in more than one gene; however, the manuscript should explicitly state that these mutation 
   categories are not mutually exclusive. 
   Response: We thank the reviewer for identifying this important ambiguity. Upon re
   evaluation of the cBioPortal data, we determined that the discrepancy resulted from the 
   original table displaying patient-level racial cohort counts as the total N, whereas mutation 
   frequencies were calculated at the tumor-sample level. Because individual patients in the 
   Lung Adenocarcinoma Met Organotropism cohort may contribute more than one tumor 
   sample, the genomic sample-level denominator may exceed the number of unique 
   patients.  
   To clarify this distinction throughout the manuscript, the Data Collection section has been 
   revised to explicitly state that genomic analyses were conducted at the tumor-sample 
   level and that sample-level denominators may exceed patient-level counts because 
   individual patients may contribute more than one tumor sample (lines 163–166).   
   The former Table 3, now Table 2, has consequently been revised to report the appropriate 
   genomic sample-level denominators (lines 218–226). For example, the Asian cohort 
   contains 251 unique patients in the patient-level demographic analysis presented in Table 
   1 but 297 tumor samples in the genomic analysis. Thus, the reported EGFR frequency of 
   64% corresponds to 190 of 297 tumor samples, rather than 190 of 251 patients. The 
   revised genomic sample denominators are 297 for Asian, 133 for Black, and 1,988 for 
   White cohorts.   
   The Table 2 caption has also been revised to clarify that mutation frequencies are reported 
   among tumor samples and that sample counts may exceed the number of unique patients 
   reported in Table 1 (lines 219–223). In addition, as suggested by the reviewer, the caption 
   now explicitly states that EGFR, KRAS, and TP53 mutation categories are not mutually 
   exclusive because individual tumor samples may harbor alterations in more than one 
   gene (lines 222–224). Therefore, the summed percentages of these mutations within a 
   racial cohort may exceed 100%.   
   During verification of the genomic denominators, we also identified the same patient
   versus-sample distinction in the smoking-stratified genomic analysis. Table 3 was 
   therefore revised to report the appropriate genomic sample denominators for each race 
   and smoking-status subgroup, rather than unique patient counts (lines 234–241). The 
   caption now explicitly states that N represents tumor samples rather than unique patients 
   and explains why these sample counts may exceed the numbers of patients with available 
   smoking-history data.   
   Finally, Figure 3 and its caption were revised to describe genomic alteration counts at the 
   tumor-sample level rather than the patient level (lines 227–233). The changes are in red 
   so they are apparent.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have done meticulous revision and all of the queries have been appropriately answered.