Breast cancer is one of the predominant types of tumors in women worldwide. Despite great progress in the early diagnosis and treatment recently, drug resistance and distal metastasis remain major causes of cancer-related mortality. Despite tremendous progress in understanding breast cancer, gaps remain in our knowledge of the molecular basis underlying the aggressiveness of breast cancer. Breast tumor-initiating cells (BTICs) or breast cancer stem cells (BCSCs) are considered to be responsible for estrogen-induced initiation and aggressive progression of breast tumors.

It is inspiriting and beneficial to analyze the new gene or protein in BTICs or BCSCs and investigate the correlation of the new gene with breast cancer malignant progression. In this manuscript, Dr. Jayanta Kumar Das and colleagues looked at the role of the nuclear respiratory factor 1 protein (NRF1) in BTICs or BCSCs function and prognosis of breast cancer. The study’s conclusion showed that the novel role of NRF1 in the stochastic acquisition of BCSCs and their progression to a malignant phenotype may open an entirely new research direction targeting NRF1 signaling in invasive breast cancer. Although the current study is well and interesting, there are some major concerns that need to be addressed before consideration of publication.

Major points: 1. The title is too ambitious. It should be revised according to the research content to make it more specific. 2. In INTRODUCTION, the presentation of research questions lacks logic, and there is no clear clinical problem or scientific hypothesis. It is suggested that the author be able to generalize scientific hypotheses from clinical problems and then propose clear scientific questions. 3. Statistical analysis methods are presented too simply, lacking, for example, data format, test level, and number of experiments repeated. 4. In the construction of overexpression cell model, the author used transient expression plasmids of cMV-NRF1-GFP. However, in the subsequent studies, especially in vivo experiments, the transient expression model has the defect that it cannot be overexpressed for a long time. Therefore, it is recommended to use the stable expression model. 5. None of the images have enough resolution. Please upload higher resolution pictures. 6. In DISCUSION, however, the limitations of this study are rarely discussed by the authors and are not clearly related to existing clinical problems.

Minor points: 1. The primers of Real-time qRT-PCR analysis are not present. 2. Figure 1C lacks the annotation of standard deviation marker and statistical test. 3. All figure about the micrograph lacks scale. 4. There is obvious deformation in figure 5. Please ensure that the length and width of the picture are scaled to equal proportions.