Clinical validation of an immunohistochemistry-based CanAssist-Breast test for distant recurrence prediction in hormone receptor-positive breast cancer patients

Abstract

CanAssist-Breast (CAB) is an immunohistochemistry (IHC)-based prognostic test for early-stage Hormone Receptor (HR+)-positive breast cancer patients. CAB uses a Support Vector Machine (SVM) trained algorithm which utilizes expression levels of five biomarkers (CD44, ABCC4, ABCC11, N-Cadherin, and Pan-Cadherin) and three clinical parameters such as tumor size, grade, and node status as inputs to generate a risk score and categorizes patients as low- or high-risk for distant recurrence within 5 years of diagnosis. In this study, we present clinical validation of CAB. CAB was validated using a retrospective cohort of 857 patients. All patients were treated either with endocrine therapy or chemoendocrine therapy. Risk categorization by CAB was analyzed by calculating Distant Metastasis-Free Survival (DMFS) and recurrence rates using Kaplan-Meier survival curves. Multivariate analysis was performed to calculate Hazard ratios (HR) for CAB high-risk vs low-risk patients. The results showed that Distant Metastasis-Free Survival (DMFS) was significantly different (P-0.002) between low- (DMFS: 95%) and high-risk (DMFS: 80%) categories in the endocrine therapy treated alone subgroup (n = 195) as well as in the total cohort (n = 857, low-risk DMFS: 95%, high-risk DMFS: 84%, P < 0.0001). In addition, the segregation of the risk categories was significant (P = 0.0005) in node-positive patients, with a difference in DMFS of 12%. In multivariate analysis, CAB risk score was the most significant predictor of distant recurrence with hazard ratio of 3.2048 (P < 0.0001). CAB stratified patients into discrete risk categories with high statistical significance compared to Ki-67 and IHC4 score-based stratification. CAB stratified a higher percentage of the cohort (82%) as low-risk than IHC4 score (41.6%) and could re-stratify >74% of high Ki-67 and IHC4 score intermediate-risk zone patients into low-risk category. Overall the data suggest that CAB can effectively predict risk of distant recurrence with clear dichotomous high- or low-risk categorization.

Keywords: CanAssist-Breast; distant recurrence; early-stage breast cancer; immunohistochemistry; prognostication; support vector machine.

Figure 1

Rationale of biomarker selection: Role and cross talk between the biomarkers chosen for test development during cancer progression. Five selected biomarkers for CanAssist‐Breast (CD44, Pan‐Cadherin, N‐Cadherin, ABCC4, and ABCC11) participate in various steps of cancer progression and are also involved in the cross talk (shown by dotted line)

Figure 2

Risk classification by CanAssist‐Breast (CAB): Kaplan‐Meier plot of distant recurrence: stratified by CAB into low‐risk or high‐risk categories in the total validation cohort (n = 857) (A) subgroup of patients treated with endocrine therapy alone (n = 195) (B); endocrine therapy vs chemoendocrine therapy in CAB low‐risk category (C); endocrine therapy vs chemoendocrine in CAB high‐risk category (D)

Figure 3

Kaplan‐Meier survival analysis of distant recurrence in the validation cohort by node status (A), low‐ and high‐risk groups by CanAssist‐Breast (CAB) in node‐negative (B), and node‐positive patients (C)

Figure 4

Comparison of CanAssist‐Breast (CAB) with Ki‐67 and IHC4 score: Kaplan‐Meier survival analysis of distant recurrence in the subset of validation cohort by Ki‐67 (n = 715) (A); CAB in the 715 cohort (B); CAB re‐stratification of low Ki‐67 patients (C); CAB re‐stratification of high Ki‐67 patients (D); IHC4 score (n = 543) (E); CAB in 543 cohort (F); CAB re‐stratification of IHC4 score intermediate‐risk category (n = 179) into low‐and high‐risk groups (G)