A Quantitative Centrosomal Amplification Score Predicts Local Recurrence of Ductal Carcinoma In Situ

PURPOSE

The purpose of this study is to predict risk of local recurrence (LR) in ductal carcinoma in situ (DCIS) with a new visualization and quantification approach using centrosome amplification (CA), a cancer cell-specific trait widely associated with aggressiveness.

EXPERIMENTAL DESIGN

This first-of-its-kind methodology evaluates the severity and frequency of numerical and structural CA present within DCIS and assigns a quantitative centrosomal amplification score (CAS) to each sample. Analyses were performed in a discovery cohort (DC, n = 133) and a validation cohort (VC, n = 119).

RESULTS

DCIS cases with LR exhibited significantly higher CAS than recurrence-free cases. Higher CAS was associated with a greater risk of developing LR (HR, 6.3 and 4.8 for DC and VC, respectively; P < 0.001). CAS remained an independent predictor of relapse-free survival (HR, 7.4 and 4.5 for DC and VC, respectively; P < 0.001) even after accounting for potentially confounding factors [grade, age, comedo necrosis, and radiotherapy (RT)]. Patient stratification using CAS (P < 0.0001) was superior to that by Van Nuys Prognostic Index (VNPI; HR for CAS = 6.2 vs. HR for VNPI = 1.1). Among patients treated with breast-conserving surgery alone, CAS identified patients likely to benefit from adjuvant RT.

CONCLUSIONS

CAS predicted 10-year LR risk for patients who underwent surgical management alone and identified patients who may be at low risk of recurrence, and for whom adjuvant RT may not be required. CAS demonstrated the highest concordance among the known prognostic models such as VNPI and clinicopathologic variables such as grade, age, and comedo necrosis.

Machine learning-based prediction of breast cancer growth rate in vivo

Background

Determining the rate of breast cancer (BC) growth in vivo, which can predict prognosis, has remained elusive despite its relevance for treatment, screening recommendations and medicolegal practice. We developed a model that predicts the rate of in vivo tumour growth using a unique study cohort of BC patients who had two serial mammograms wherein the tumour, visible in the diagnostic mammogram, was missed in the first screen.

Methods

A serial mammography-derived in vivo growth rate (SM-INVIGOR) index was developed using tumour volumes from two serial mammograms and time interval between measurements. We then developed a machine learning-based surrogate model called Surr-INVIGOR using routinely assessed biomarkers to predict in vivo rate of tumour growth and extend the utility of this approach to a larger patient population. Surr-INVIGOR was validated using an independent cohort.

Results

SM-INVIGOR stratified discovery cohort patients into fast-growing versus slow-growing tumour subgroups, wherein patients with fast-growing tumours experienced poorer BC-specific survival. Our clinically relevant Surr-INVIGOR stratified tumours in the discovery cohort and was concordant with SM-INVIGOR. In the validation cohort, Surr-INVIGOR uncovered significant survival differences between patients with fast-growing and slow-growing tumours.

Conclusion

Our Surr-INVIGOR model predicts in vivo BC growth rate during the pre-diagnostic stage and offers several useful applications.

Abstract P5-18-02: A quantitative centrosomal amplification score (CAS) predicts local recurrence in ductal carcinoma in situ

Background: About 60-80% of ductal carcinoma in situ (DCIS) cases are high-grade (HG) DCIS with an elevated risk of local recurrence (LR) even after a lumpectomy. Patients are often under or over treated due to the lack of accurate recurrence risk prediction models. Current prognostic models such as OncotypeDX and Van Nuys Prognostic Index (VNPI) lack consistency and are limited to a specific subset of patients. Here in this study, we show that the extent of centrosome amplification (CA) in a DCIS lesion can predict the risk of LR after lumpectomy. CA refers to presence of supernumerary or large centrosomes and is a characteristic of pre-invasive lesions, and breast tumors, and promotes erroneous mitoses and chromosomal instability.

Methods: We have pioneered a semi-automated pipeline that integrates immunofluorescence confocal microscopy with digital image analysis and yields a quantitative Centrosomal Amplification Score (CAS) for each patients' tumor sample by evaluating severity and frequency of centrosomal aberrations therein. To this end, we first immunofluorescently stained centrosomes in formalin fixed paraffin embedded resection samples from DCIS patients (discovery cohort n=133 and a validation cohort n=119) using an antibody against γ-tubulin, and co-stained nuclei with DAPI. Next, we imaged the slides and processed the raw 3D image data using IMARIS Biplane 8.2 3D volume rendering software. Finally, we calculated centrosome numbers and volume in ˜250 cells from each patient sample. Using a mathematical algorithm, we generated a composite CAS score for each patient sample by integrating the numerical (CASi) and structural (CASm) aberrations.

Results: We found that DCIS patients with recurrence exhibited higher CAS. Intriguingly, higher CAS was also associated with greater risk of developing ipsilateral breast events [Hazard ratio (HR) =7.58 for discovery cohort and HR=5.8 for validation cohort, p&lt;0.0001] which remained significant (HR=8.5 for discovery and HR=3.39, p&lt;0.0001) after accounting for the confounding factors like age, tumor size, comedo necrosis and radiotherapy. Kaplan Meir survival analysis indicated that high CAS was associated with poor recurrence-free survival (RFS) (p&lt;0.001). For the high and low CAS groups, the 5-year risk of recurrence was 87.5% and 12.5% respectively (p&lt;0.001). In our discovery cohort, a head-to-head comparison of the ability of VNPI and CAS to predict recurrence illuminated that CAS was able to stratify the DCIS group in recurrence and recurrence-free group with much higher significance (p&lt;0.0001) than the Van Nuys Prognostic Index (VNPI) (HRs for CAS- 8.8 vs. VNPI 0.959). Finally, the Harrell's concordance index using SAS PROC PHREG tests yielded that the probability of a patient with poorer/lower RFS to be in the high CAS group is 76.2%.

Conclusion: Our data compellingly show that CAS quantifies the risk of recurrence in DCIS patients with the highest concordance and provides a novel and innovative tool to tailor their treatment based on their risk profile.

Citation Format: Mittal K, Kaur J, Wei G, Toss MS, Osan RM, Janssen EA, Søiland H, Rakha EA, Rida PC, Aneja R. A quantitative centrosomal amplification score (CAS) predicts local recurrence in ductal carcinoma in situ [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-18-02.