Progesterone receptor status and tumor grade predict the 21-gene recurrence score of invasive lobular breast cancer

Enhancing clinical decision support with genomic tools in breast cancer: A Scottish perspective

INTRODUCTION

The Oncotype DX Breast RS test has been adopted in Scotland and has been the subject of a large population-based study by a Scottish Consensus Group to assess the uptake of the recurrence score (RS), evaluate co-variates associated with the RS and to analyse the effect it may have had on clinical practice.

MATERIALS & METHODS

Pan-Scotland study between August 2018-August 2021 evaluating 833 patients who had a RS test performed as part of their diagnostic pathway. Data was extracted retrospectively from electronic records and analysis conducted to describe change in chemotherapy administration (by direct comparison with conventional risk assessment tools), and univariate/multivariate analysis to assess relationship between covariates and the RS.

RESULTS

Chemotherapy treatment was strongly influenced by the RS (p < 0.001). Only 30 % of patients received chemotherapy treatment in the intermediate and high risk PREDICT groups, where chemotherapy is considered. Additionally, 55.5 % of patients with a high risk PREDICT had a low RS and did not receive chemotherapy. There were 17 % of patients with a low risk PREDICT but high RS who received chemotherapy. Multivariate regression analysis showed the progesterone receptor Allred score (PR score) to be a strong independent predictor of the RS, with a negative PR score being associated with high RS (OR 4.49, p < 0.001). Increasing grade was also associated with high RS (OR 3.81, p < 0.001). Classic lobular pathology was associated with a low RS in comparison to other tumour pathology (p < 0.01). Nodal disease was associated with a lower RS (p = 0.012) on univariate analysis, with menopausal status (p = 0.43) not influencing the RS on univariate or multivariate analysis.

CONCLUSIONS

Genomic assays offer the potential for risk-stratified decision making regarding the use of chemotherapy. They can help reduce unnecessary chemotherapy treatment and identify a subgroup of patients with more adverse genomic tumour biology. A recent publication by Health Improvement Scotland (HIS) has updated guidance on use of the RS test for NHS Scotland. It suggests to limit its use to the intermediate risk PREDICT group. Our study shows the impact of the RS test in the low and high risk PREDICT groups. The implementation across Scotland has resulted in a notable shift in practice, leading to a significant reduction in chemotherapy administration in the setting of high risk PREDICT scores returning low risk RS. There has also been utility for the test in the low risk PREDICT group to detect a small subgroup with a high RS. We have found the PR score to have a strong independent association with high risk RS. This finding was not evaluated by the key RS test papers, and the potential prognostic information provided by the PR score as a surrogate biomarker is an outstanding question that requires more research to validate.

Racial/ethnic differences in 21-gene recurrence score and survival among patients with estrogen receptor-positive breast cancer

BACKGROUND

Despite numerous studies on racial/ethnic disparities among patients with breast cancer, there is a paucity of literature evaluating racial/ethnic differences in 21-gene recurrence score (RS) and survival differences stratified by RS risk categories. We thus performed an observational cohort study to examine racial/ethnic disparities in the context of RS.

METHODS

The National Cancer Database (NCDB) was queried for female patients diagnosed between 2006 and 2018 with estrogen receptor (ER)-positive, pT1-3N0-1aM0 breast cancer who received surgery followed by adjuvant endocrine therapy and had RS data available. Logistic multivariable analysis (MVA) was built to evaluate variables associated with RS ≥ 26. Cox MVA was used to evaluate OS. Subgroup analyses were performed to compare the magnitude of racial/ethnic differences stratified by RS. P values less than 0.017 were considered statistically significant based on Bonferroni correction.

RESULTS

A total of 140,133 women were included for analysis. Of these, 115,651 (82.5%), 8,213 (5.9%), 10,814 (7.7%), and 5,455 (3.9%) were NHW, Hispanic, Black, and API women, respectively. Median (IQR) follow up was 66.2 months (48.0-89.8). Logistic MVA showed that, compared with NHW women, Black women were associated with higher RS (≥ 26 vs < 26: adjusted odds ratio [aOR] 1.19, 95% confidence interval [CI] 1.12-1.26, p < 0.001), while HW (aOR 0.93, 95% CI 0.86-1.00, p = 0.04) and API women (aOR 1.03, 95% CI 0.95-1.13, p = 0.45) were not. Cox MVA showed that, compared with NHW women, Black women had worse OS (adjusted hazards ratio [aHR] 1.10, 95% CI 1.02-1.19, p = 0.012), while HW (aHR 0.85, 95% CI 0.77-0.94, p = 0.001) and API (aHR 0.66, 95% CI 0.56-0.77, p < 0.001) women had better OS. In subgroup analysis, similar findings were noted among those with RS < 26, while only API women were associated with improved OS among others with RS ≥ 26.

CONCLUSION

To our knowledge, this is the largest study using nationwide oncology database to suggest that Black women were associated with higher RS, while HW and API women were not. It also suggested that Black women were associated with worse OS among those with RS < 26, while API women were associated with improved OS regardless of RS when compared to NHW women.

Deep Learning-Based Pathology Image Analysis Enhances Magee Feature Correlation With Oncotype DX Breast Recurrence Score

Background

Oncotype DX Recurrence Score (RS) has been widely used to predict chemotherapy benefits in patients with estrogen receptor-positive breast cancer. Studies showed that the features used in Magee equations correlate with RS. We aimed to examine whether deep learning (DL)-based histology image analyses can enhance such correlations.

Methods

We retrieved 382 cases with RS diagnosed between 2011 and 2015 from the Emory University and the Ohio State University. All patients received surgery. DL models were developed to detect nuclei of tumor cells and tumor-infiltrating lymphocytes (TILs) and segment tumor cell nuclei in hematoxylin and eosin (H&E) stained histopathology whole slide images (WSIs). Based on the DL-based analysis, we derived image features from WSIs, such as tumor cell number, TIL number variance, and nuclear grades. The entire patient cohorts were divided into one training set (125 cases) and two validation sets (82 and 175 cases) based on the data sources and WSI resolutions. The training set was used to train the linear regression models to predict RS. For prediction performance comparison, we used independent variables from Magee features alone or the combination of WSI-derived image and Magee features.

Results

The Pearson's correlation coefficients between the actual RS and predicted RS by DL-based analysis were 0.7058 (p-value = 1.32 × 10-13) and 0.5041 (p-value = 1.15 × 10-12) for the validation sets 1 and 2, respectively. The adjusted R 2 values using Magee features alone are 0.3442 and 0.2167 in the two validation sets, respectively. In contrast, the adjusted R 2 values were enhanced to 0.4431 and 0.2182 when WSI-derived imaging features were jointly used with Magee features.

Conclusion

Our results suggest that DL-based digital pathological features can enhance Magee feature correlation with RS.

Identifying and Validating of an Autophagy-Related Gene Signature for the Prediction of Early Relapse in Breast Cancer

BACKGROUND

Compelling evidence has demonstrated the pivotal role of autophagy in the prognosis of breast cancer. Breast cancer (BC) patients with early relapse consistently exhibited worse survival.

METHODS

The autophagy-related genes were derived from the Human Autophagy Database (HADb) and high-sequencing data were obtained from The Cancer Genome Atlas (TCGA). Discrepantly expressed autophagy genes (DEAGs) between early relapse and long-term survival groups were performed using the Linear Models for Microarray data (LIMMA) method. Lasso Cox regression analysis was conducted for the selection of the 4-gene autophagy-related gene signature. GSE42568 and GSE21653 databases were enrolled in this study for the external validation of the signature. Then patients were divided into high and low-risk groups based on the specific score formula. GSEA was used to discover the related signaling pathway. The Kaplan-Meier curves and the receiver operating characteristic (ROC) curves were used to evaluate the discrimination and accuracy of the 4-gene signature.

RESULTS

A signature composed of four autophagy-related mRNA including APOL1, HSPA8, SIRT1, and TP73, was identified as significantly associated with the early relapse in BC patients. Time-dependent receiver-operating characteristic at 1 year suggested remarkable accuracy of the signature [area under the curve (AUC = 0.748)]. The risk score model based on the autophagy-related signature showed favorable predicting value in 1-, 2-, and 3-year relapse-free survival (RFS) in training and two validating cohorts. The GSEA displayed gene sets were remarkably enriched in carcinogenic activation pathways and autophagy-related pathways. The nomogram involving three variables (progesterone receptor status, T stage, and 4-gene signature) exhibited relatively good discrimination with a C-index of 0.766.

CONCLUSIONS

Our study establishes an autophagy-related 4-gene signature that can effectively stratify the high-risk and low-risk BC patients for early relapse. Combined with the clinicopathological variables, the signature could significantly help oncologists tailor more efficient treatment strategies for BC patients.

Grading of invasive breast carcinoma: the way forward

Histologic grading has been a simple and inexpensive method to assess tumor behavior and prognosis of invasive breast cancer grading, thereby identifying patients at risk for adverse outcomes, who may be eligible for (neo)adjuvant therapies. Histologic grading needs to be performed accurately, on properly fixed specimens, and by adequately trained dedicated pathologists that take the time to diligently follow the protocol methodology. In this paper, we review the history of histologic grading, describe the basics of grading, review prognostic value and reproducibility issues, compare performance of grading to gene expression profiles, and discuss how to move forward to improve reproducibility of grading by training, feedback and artificial intelligence algorithms, and special stains to better recognize mitoses. We conclude that histologic grading, when adequately carried out, remains to be of important prognostic value in breast cancer patients.

The increasing importance of histologic grading in tailoring adjuvant systemic therapy in 30,843 breast cancer patients

Purpose

The large variation in histologic grading of invasive breast cancer (IBC) that has been reported likely influences tailoring adjuvant therapy. The role of grading in therapeutic decision-making in daily practice, was evaluated using the Dutch national guidelines for IBC-management.

Methods

Synoptic reports of IBC resection-specimens, obtained between 2013 and 2016, were extracted from the nationwide Dutch Pathology Registry, and linked to treatment-data from the Netherlands Cancer Registry. The relevance of grading for adjuvant chemotherapy (aCT) was quantified by identifying patients for whom grade was the determinative factor. In addition, the relation between grade and aCT-administration was evaluated by multivariate logistic regression for patients with a guideline-aCT-indication.

Results

30,843 patients were included. Applying the guideline that was valid between 2013 and 2016, grade was the determinative factor for the aCT-indication in 7744 (25.1%) patients, a percentage that even increased according to the current guideline where grade would be decisive for aCT in 10,869 (35.2%) patients. Also in current practice, the indication for adjuvant endocrine therapy (aET) would be based on grade in 9173 (29.7%) patients. Finally, as patients with lower-grade tumors receive aCT significantly less often, grade was also decisive in tailoring aCT de-escalation.

Conclusions

In the largest study published so far we illustrate the increasing importance of histologic grade in tailoring adjuvant systemic breast cancer therapy. Next to playing a key-role in aCT-indication and de-escalation, the role of grading has expanded to the indication for aET. Optimizing histologic grading by pathologists is urgently needed to diminish the risk of worse patient outcome due to non-optimal treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10549-021-06098-7.

Invasive lobular carcinoma of the breast: the increasing importance of this special subtype

Invasive lobular carcinoma (ILC) is the most common of the breast cancer special types, accounting for up to 15% of all breast cancer cases. ILCs are noted for their lack of E-cadherin function, which underpins their characteristic discohesive growth pattern, with cells arranged in single file and dispersed throughout the stroma. Typically, tumours are luminal in molecular subtype, being oestrogen and progesterone receptor positive, and HER2 negative. Since last reviewing the lobular literature (McCart Reed et al., Breast Cancer Res 17:12, 2015), there has been a considerable increase in research output focused on this tumour type, including studies into the pathology and management of disease, a high-resolution definition of the genomic landscape of tumours as well as the evolution of several potential therapeutic avenues. There abounds a huge amount of new data, which we will review herein.

MST1R (RON) expression is a novel prognostic biomarker for metastatic progression in breast cancer patients

PURPOSE

This study evaluates the prognostic significance of MST1R (RON) expression in breast cancer with respect to disease progression, long-term survival, subtype, and association with conventional prognostic factors.

METHODS

The approach includes interrogation of survival and tumor staging with paired MST1R RNA expression from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Protein expression evaluation was performed using immunohistochemistry (IHC) staining of MST1R on breast cancer tissue samples from the Cancer Diagnosis Program Breast Cancer Progression tissue microarray and locally obtained breast tumor tissue samples analyzed with paired survival, metastasis, and subtype.

RESULTS

Data from TCGA (n = 774) show poorer relapse-free survival (RFS) in patients with high MST1R expression (P = 0.32) and no difference in MST1R expression based on tumor stage (P = 0.77) or nodal status (P = 0.94). Patients in the GEO-derived Kaplan-Meier Plotter microarray dataset demonstrate the association of MST1R and poorer overall survival (n = 1402, P = 0.018) and RFS in patients receiving chemotherapy (n = 798, P = 0.041). Patients with high MST1R expression display worse overall survival (P = 0.01) and receiver operator characteristic (ROC) analysis demonstrate the predictive capacity of increased MST1R with early death (P = 0.0017) in IHC-stained samples. Paired IHC-stained breast tumor samples from the primary versus metastatic site show MST1R expression is associated with metastatic progression (P = 0.032), and ROC analysis supports the predictive capacity of MST1R in metastatic progression (P = 0.031). No associations of MST1R with estrogen receptor (ER), progesterone receptor (PR), both ER and PR, HER2 positivity, or triple-negativity were found (P = 0.386, P = 0.766, P = 0.746, P = 0.457, P = 0.947, respectively).

CONCLUSIONS

MST1R expression has prognostic value in breast cancer with respect to survival and metastatic progression. MST1R expression is not associated with tumor stage, nodal status, or subtype.