Comment on “New insight into the risk stratification and treatment priority of breast cancer: TMT scoring system”

Dear Editor, I read with great interest the study by Qi et al titled “New insight into the risk stratification and treatment priority of breast cancer: TMT scoring system” recently published in the International Journal of Surgery, which introduces a novel TMT (Tumor Mitochondrial Transfer) scoring system for breast cancer[1]. The authors elegantly demonstrate how breast cancer cells “hijack” mitochondria from T cells to fuel their own metabolic demands while inducing immune exhaustion. This metabolic “parasitism” provides a fresh perspective on tumor-immune interactions, yet several aspects regarding its application in surgical oncology warrant further consideration. The spatial dynamics of TMT within the tumor microenvironment (TME) are particularly relevant for surgical decision-making[2]. The authors mention that high TMT scores correlate with an aggressive phenotype. From a surgical standpoint, it would be valuable to understand if the TMT process is more pronounced at the “invasive front” of the tumor compared to the core. If mitochondrial hijacking is enriched at the margins, it could imply a more hostile metabolic niche that predisposes patients to local recurrence, potentially necessitating wider surgical margins or more intensive intraoperative margin assessment. The study highlights the potential of TMT scores to predict immunotherapy responses. In the era of neoadjuvant therapy, the ability to stratify patients based on their “metabolic immune status” before surgery is transformative[3]. However, we must consider the impact of surgical stress and wound healing on the TME. Could the systemic inflammatory response induced by major breast surgery further exacerbate mitochondrial depletion in the remaining T-cell pool? Investigating the longitudinal changes in TMT scores – from biopsy to definitive resection – could help surgeons and oncologists optimize the timing of adjuvant immunotherapeutic interventions. While the TMT scoring system is robust, its transition to routine clinical practice requires standardization. We suggest that future studies explore whether these transcriptomic signatures can be simplified into a clinical-grade metabolic assay or integrated with radiomics. This would allow for a non-invasive “metabolic biopsy” to guide surgical planning and personalized treatment priorities. Conclusion In summary, Qi et al have provided a powerful tool for risk stratification in breast cancer. Integrating this metabolic insight with established surgical parameters will undoubtedly refine our approach to the multidisciplinary management of breast cancer patients.