Incorporating host genetics and inflammation in myelosuppression risk prediction for triple-negative breast cancer

Dear editor:

We are grateful for the author’s contribution, but there are still several issues that need further discussion. We read with great interest the recent article by Xie et al. describing the development and internal validation of a nomogram to estimate the risk of chemotherapy-induced myelosuppression (CIM) in patients with triple-negative breast cancer (TNBC) (1). The authors retrospectively analyzed 316 TNBC patients and, through least absolute shrinkage and selection operator (LASSO) regression followed by multivariable logistic analysis, identified five independent predictors: bone metastasis, platinum-based regimen, chemotherapy cycle number, pre-existing neutropenia, and the number of concomitant drugs. The resulting model demonstrated excellent discrimination [area under the curve (AUC) =0.886–0.905] and favorable calibration and decision-curve analyses, suggesting potential utility for individualized risk assessment. We commend the authors for this valuable contribution; however, we would like to raise several points that merit further consideration.

First, the current nomogram does not take into account host genetic polymorphisms that have repeatedly been shown to regulate the risk and severity of CIM. Specifically, functional variants such as rs2074292 in the MAP3K14 gene and rs1883832 in the CD40 gene are not only independently associated with breast cancer susceptibility (2), but also associated with gene polymorphisms and the magnitude of neutrophil decline after chemotherapy (3). Integrating these pharmacogenomic markers, together with other variants related to drug metabolism, DNA repair, and inflammatory signal transduction, can significantly improve model calibration and its ability to identify patients at the highest risk of severe or long-term bone marrow suppression.

Secondly, chronic inflammation is not only the starting soil of a variety of malignant tumors, but also constructs a microenvironment rich in inflammatory mediators [such as Interleukin-6 (IL-6)] around the tumor. These molecules significantly accelerate the proliferation, invasion, and distant metastasis of tumor cells by continuously activating pro-survival signals, enhancing angiogenesis, and weakening immune surveillance (4).

In addition, chemotherapy drugs themselves can directly damage the bone marrow hematopoietic microenvironment by triggering systemic inflammatory response, thereby inducing or aggravating bone marrow suppression (5); therefore, it is recommended to include easily available systemic inflammatory markers such as C-reactive protein (CRP) and neutrophil-to-lymphocyte ratio (NLR) in the model to clarify and quantify the independent contribution of inflammatory load to CIM risk.

Finally, there are still some key issues to be clarified: does the potential damage of previous radiotherapy to bone marrow reserve constitute a confounding factor? Whether the independent effects of different chemotherapy regimens, such as taxanes and anthracyclines, on CIM also be quantitatively evaluated and included in the model?

Despite these confusions, we thank the authors for their significant contributions in this field and hope that our explanations and observations will be helpful to readers of this valuable journal.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was a standard submission to the journal. The article did not undergo external peer review.

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1600/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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References

1. Xie H, Zhang R, Wei C, et al. Construction and validation of a nomogram prediction model for predicting the risk of chemotherapy-induced myelosuppression after chemotherapy in patients with triple-negative breast cancer: a single-center retrospective case-control study. Transl Cancer Res 2025;14:2885-99. [Crossref] [PubMed]
2. Savadogo M, Traoré L, Zouré AA, et al. Polymorphisms rs2074292 of the MAP3K14 Gene and rs1883832 of the CD40 Gene and Breast Cancer in Women in Burkina Faso: A Case-Control Study. Health Sci Rep 2025;8:e71027. [Crossref] [PubMed]
3. Zhao X, Wang X, Wu W, et al. Matrix metalloproteinase-2 polymorphisms and clinical outcome of Chinese patients with nonsmall cell lung cancer treated with first-line, platinum-based chemotherapy. Cancer 2012;118:3587-98. [Crossref] [PubMed]
4. Kim ES, Kim SY, Moon A. C-Reactive Protein Signaling Pathways in Tumor Progression. Biomol Ther (Seoul) 2023;31:473-83. [Crossref] [PubMed]
5. Hong M, Chen D, Hong Z, et al. Ex vivo and in vivo chemoprotective activity and potential mechanism of Martynoside against 5-fluorouracil-induced bone marrow cytotoxicity. Biomed Pharmacother 2021;138:111501. [Crossref] [PubMed]