Computerized Assessment of the Tumor-stromal Ratio and Proposal of a Novel Nomogram for Predicting Survival in Invasive Breast Cancer

Xu Qian; Feng Xiao; Yuan-Yuan Chen; Jing-Ping Yuan; Xiao-Hong Liu; Lin-Wei Wang; Bin Xiong

doi:10.7150/jca.55750

Computerized Assessment of the Tumor-stromal Ratio and Proposal of a Novel Nomogram for Predicting Survival in Invasive Breast Cancer

J Cancer. 2021 Apr 19;12(12):3427-3438. doi: 10.7150/jca.55750. eCollection 2021.

Authors

Xu Qian^{1

2}, Feng Xiao³, Yuan-Yuan Chen^{1

4}, Jing-Ping Yuan⁵, Xiao-Hong Liu^{1

2}, Lin-Wei Wang^{1

4}, Bin Xiong^{1

2}

Affiliations

¹ Hubei Key Laboratory of Tumor Biological Behaviors, Hubei Cancer Clinical Study Center, Wuhan, China, 430071.
² Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China, 430071.
³ Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China, 430071.
⁴ Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China, 430071.
⁵ Department of Pathology, Renmin Hospital of Wuhan University, 430060 Wuhan, China.

Abstract

Background: Various studies have verified the prognostic significance of the tumor-stromal ratio (TSR) in several types of carcinomas using manually assessed H&E stained histologic sections. This study aimed to establish a computerized method to assess the TSR in invasive breast cancer (BC) using immunohistochemistry (IHC)-stained tissue microarrays (TMAs), and integrate the TSR into a novel nomogram for predicting survival. Methods: IHC-staining of cytokeratin (CK) was performed in 7 prepared TMAs containing 240 patients with 480 invasive BC specimens. The ratio of tumor areas and stromal areas was determined by the computerized method, and categorized as stroma-low and stroma-high groups using the X-tile software. The prognostic value of the TSR at 5-year disease free survival (5-DFS) in each subgroup was analyzed. Univariate and multivariate analyses were performed and a novel nomogram for predicting survival in invasive breast cancer was established and assessed. Results: The newly developed computerized method could accurately recognize CK-labeled tumor areas and non-labeled stromal areas, and automatically calculate the TSR. Stroma-low and stroma-high accounted for 38.8% (n = 93) and 61.2% (n = 147) of the cases, according to the cut-off value of 55.5% for stroma ratio. The Kaplan-Meier analysis showed that patients in the stroma-high group had a worse 5-DFS compared to patients in the stroma-low group (P = 0.031). Multivariable analysis indicated that the T stage, N status, histological grade, ER status, HER-2 gene, and the TSR were potential risk factors of invasive BC patients, which were included into the nomogram (P < 0.10 for all). The nomogram was well calibrated to predict the probability of 5-DFS and the C-index was 0.817, which was higher than any single predictor. A dynamic nomogram was built for convenient use. The area under the curve (AUC) of the nomogram was 0.870, while that of the TNM staging system was 0.723. The Kaplan-Meier analysis showed that the nomogram had a better risk stratification for invasive BC patients than the TNM staging system. Conclusions: Based on IHC staining of CK on TMAs, this study successfully developed a computerized method for TSR assessment and established a novel nomogram for predicting survival in invasive BC patients.

Keywords: Breast cancer; Computerized assessment; Nomogram.; Tumor stromal ratio.