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BACKGROUND: Tumor-associated collagen signature (TACS) is an independent prognostic factor for breast cancer. However, it is unclear whether the complete collagen signature, including TACS, the TACS-based collagen microscopic features (TCMF1), and the TACS-based nuclear features (TCMF2), can provide additional prognostic information for the current tumor-node-metastasis (TNM) staging system. PATIENTS AND METHODS: We included 941 patients with breast cancer from three cohorts: the training (n = 355), internal (n = 334), and external validation cohorts (n = 252). TACS and TCMF1 were obtained by multiphoton microscopy (MPM). TCMF2 was extracted on the hematoxylin and eosin images colocated with MPM images. They were linearly combined to establish a complete collagen signature score for reclassifying current TNM staging into stage Ⅰ (II and Ⅲ)/low risk and stage Ⅰ (II and Ⅲ)/high risk. RESULTS: The low-risk collagen signatures 'downstaged' patients in stage II or Ⅲ, while the high-risk collagen signatures 'upstaged' patients with stage Ⅰ tumors. After incorporating the complete collagen signature into the current TNM staging system, the modified staging system had a higher ability to stratify patients referent, Ⅰ-new; Ⅱ-new, hazard ratio (HR) 8.655, 6.136, and 4.699 in the training, internal validation, and external validation cohorts, respectively; Ⅲ-new, HR 14.855, 11.201, and 13.245 in the corresponding three cohorts, respectively than the current TNM staging system (referent, Ⅰ; Ⅱ, HR 1.642, 1.853, and 1.371 in the corresponding three cohorts, respectively; Ⅲ, HR 4.131, 4.283, and 3.711 in the corresponding three cohorts, respectively). Furthermore, the modified staging system showed a higher area under the curve than the current TNM staging system (training cohort: 0.843 versus 0.683; internal validation cohort: 0.792 versus 0.661; and external validation cohort: 0.793 versus 0.646). CONCLUSIONS: The complete collagen signature is an independent predictor of survival outcomes in breast cancer. It adds significant information about the biological behavior of the disease to staging for breast cancer.
Li et al. (Thu,) studied this question.