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Combining the tumor-stroma ratio with tumor-infiltrating lymphocytes improves the prediction of pathological complete response in breast cancer patients.
Li, Fengling; Chen, Hong; Lu, Xunxi; Wei, Yani; Zhao, Yuanyuan; Fu, Jing; Xiao, Xiuli; Bu, Hong.
Afiliación
  • Li F; Department of Pathology, West China Hospital, Sichuan University, Chengdu, China.
  • Chen H; Institute of Clinical Pathology, West China Hospital, Sichuan University, Chengdu, China.
  • Lu X; Institute of Clinical Pathology, West China Hospital, Sichuan University, Chengdu, China.
  • Wei Y; Key Laboratory of Transplant Engineering and Immunology of the National Health Commission, West China Hospital, Sichuan University, Chengdu, China.
  • Zhao Y; Department of Pathology, West China Hospital, Sichuan University, Chengdu, China.
  • Fu J; Institute of Clinical Pathology, West China Hospital, Sichuan University, Chengdu, China.
  • Xiao X; Department of Pathology, West China Hospital, Sichuan University, Chengdu, China.
  • Bu H; Institute of Clinical Pathology, West China Hospital, Sichuan University, Chengdu, China.
Breast Cancer Res Treat ; 202(1): 173-183, 2023 Nov.
Article en En | MEDLINE | ID: mdl-37528265
ABSTRACT

PURPOSE:

The tumor-stroma ratio (TSR) is a common histological parameter that measures stromal abundance and is prognostic in breast cancer (BC). However, more evidence is needed on the predictive value of the TSR for the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). The purpose of this study was to determine the importance of the TSR in predicting pCR in NAC settings.

METHOD:

We evaluated the TSR on pretreatment biopsies of 912 BC patients from four independent Chinese hospitals and investigated the potential value of the TSR for predicting pCR. Meanwhile, stromal tumor-infiltrating lymphocytes (sTILs) were assessed, and we evaluated the predictive value of the combination of sTILs and TSR (TSRILs).

RESULTS:

Patients with low stroma showed a higher pCR rate than those with high stroma among the four independent hospitals, and in multivariate analysis, the TSR was proven to be an independent predictor for pCR to NAC with an odds ratio of 1.945 (95% CI 1.230-3.075, P = 0.004). Moreover, we found that TSRILs could improve the area under the curve (AUC) for predicting pCR from 0.750 to 0.785 (P = 0.039); especially in HER2-negative BCs, the inclusion of TSRILs increased the AUC from 0.801 to 0.835 in the discovery dataset (P = 0.048) and 0.734 to 0.801 in the validation dataset (P = 0.003).

CONCLUSION:

TSR and sTILs can be easily measured in pathological routines and provide predictive information without additional cost; with more evidence from clinical trials, TSRILs could be a candidate to better stratify patients in NAC settings.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias de la Mama Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Breast Cancer Res Treat Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias de la Mama Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Breast Cancer Res Treat Año: 2023 Tipo del documento: Article País de afiliación: China