Impact of receptor phenotype on nodal burden in patients with breast cancer who have undergone neoadjuvant chemotherapy

Assessment of the impact of residual tumors at different sites post-neoadjuvant chemotherapy on prognosis in breast cancer patients and development of a disease-free survival prediction model

Background

Residual disease after neoadjuvant chemotherapy (NAC) in breast cancer patients predicts worse outcomes than pathological complete response. Differing prognostic impacts based on the anatomical site of residual tumors are not well studied.

Objectives

The study aims to assess disease-free survival (DFS) in breast cancer patients with different residual tumor sites following NAC and to develop a nomogram for predicting 1- to 3-year DFS in these patients.

Design

A retrospective cohort study.

Methods

Retrospective analysis of 953 lymph node-positive breast cancer patients with residual disease post-NAC. Patients were categorized into three groups: residual disease in breast (RDB), residual disease in lymph nodes (RDN), and residual disease in both (RDBN). DFS compared among groups. Patients were divided into a training set and a validation set in a 7:3 ratio. Prognostic factors for DFS were analyzed to develop a nomogram prediction model.

Results

RDB patients had superior 3-year DFS of 94.6% versus 85.2% for RDN and 81.8% for RDBN (p < 0.0001). Clinical T stage, N stage, molecular subtype, and postoperative pN stage were independently associated with DFS on both univariate and multivariate analyses. Nomogram integrating clinical tumor-node-metastasis (TNM) stage, molecular subtype, pathological response demonstrated good discrimination (C-index 0.748 training, 0.796 validation cohort), and calibration.

Conclusion

The location of residual disease has prognostic implications, with nodal residuals predicting poorer DFS. The validated nomogram enables personalized DFS prediction to guide treatment decisions.

Modern management of the axilla

Surgical management of the axilla has evolved considerably in recent years, with a strong focus on de-escalation to minimise morbidity whilst maintaining oncological outcomes. Current trials will focus on the omission of Sentinel node biopsy in select groups of patients, while axillary lymph node dissection will be reserved for those with more aggressive disease.

A radiomic model to classify response to neoadjuvant chemotherapy in breast cancer

BACKGROUND

Medical image analysis has evolved to facilitate the development of methods for high-throughput extraction of quantitative features that can potentially contribute to the diagnostic and treatment paradigm of cancer. There is a need for further improvement in the accuracy of predictive markers of response to neo-adjuvant chemotherapy (NAC). The aim of this study was to develop a radiomic classifier to enhance current approaches to predicting the response to NAC breast cancer.

METHODS

Data on patients treated for breast cancer with NAC prior to surgery who had a pre-NAC dynamic contrast enhanced breast MRI were included. Response to NAC was assessed using the Miller-Payne system on the excised tumor. Tumor segmentation was carried out manually under the supervision of a consultant breast radiologist. Features were selected using least absolute shrinkage selection operator regression. A support vector machine learning model was used to classify response to NAC.

RESULTS

74 patients were included. Patients were classified as having a poor response to NAC (reduction in cellularity < 90%, n = 44) and an excellent response (> 90% reduction in cellularity, n = 30). 4 radiomics features (discretized kurtosis, NGDLM contrast, GLZLM_SZE and GLZLM_ZP) were identified as pertinent predictors of response to NAC. A SVM model using these features stratified patients into poor and excellent response groups producing an AUC of 0.75. Addition of estrogen receptor status improved the accuracy of the model with an AUC of 0.811.

CONCLUSION

This study identified a radiomic classifier incorporating 4 radiomics features to augment subtype based classification of response to NAC in breast cancer.

The Prognostic Value of Lymph Node Involvement after Neoadjuvant Chemotherapy Is Different among Breast Cancer Subtypes

Simple Summary

Little is known about whether residual axillary disease after neoadjuvant chemotherapy carries a different prognostic value by breast cancer subtype. We retrospectively evaluated the axillary involvement (0, 1 to 3 positive nodes, ≥4 positive nodes) on surgical specimens from a cohort of 1197 patients treated with neoadjuvant chemotherapy, and analyzed its association with survival outcomes. Relapse free survival was significantly associated with the number of positive nodes, but this effect was different by breast cancer subtype (Pinteraction = 0.004). High risk patients were those with 4 or more nodes involved in the luminal subgroup, whereas patients with 1 node or more involved had a decreased prognosis in triple negative and HER2 positive breast cancer subgroups. The prognostic value of residual axillary disease should be interpreted according to breast cancer subtype to accurately stratify patients with a high risk of recurrence after neoadjuvant chemotherapy who should be offered second line therapies.

Abstract

Introduction: The three different breast cancer subtypes (Luminal, HER2-positive, and triple negative (TNBCs) display different natural history and sensitivity to treatment, but little is known about whether residual axillary disease after neoadjuvant chemotherapy (NAC) carries a different prognostic value by BC subtype. Methods: We retrospectively evaluated the axillary involvement (0, 1 to 3 positive nodes, ≥4 positive nodes) on surgical specimens from a cohort of T1-T3NxM0 BC patients treated with NAC between 2002 and 2012. We analyzed the association between nodal involvement (ypN) binned into three classes (0; 1 to 3; 4 or more), relapse-free survival (RFS) and overall survival (OS) among the global population, and according to BC subtypes. Results: 1197 patients were included in the analysis (luminal (n = 526, 43.9%), TNBCs (n = 376, 31.4%), HER2-positive BCs (n = 295, 24.6%)). After a median follow-up of 110.5 months, ypN was significantly associated with RFS, but this effect was different by BC subtype (P_interaction = 0.004), and this effect was nonlinear. In the luminal subgroup, RFS was impaired in patients with 4 or more nodes involved (HR 2.8; 95% CI [1.93; 4.06], p < 0.001) when compared with ypN0, while it was not in patients with 1 to 3 nodes (HR = 1.24, 95% CI = [0.86; 1.79]). In patients with TNBC, both 1-3N+ and ≥4 N+ classes were associated with a decreased RFS (HR = 3.19, 95% CI = [2.05; 4.98] and HR = 4.83, 95% CI = [3.06; 7.63], respectively versus ypN0, p < 0.001). Similar decreased prognosis were observed among patients with HER2-positive BC (1-3N +: HR = 2.7, 95% CI = [1.64; 4.43] and ≥4 N +: HR = 2.69, 95% CI = [1.24; 5.8] respectively, p = 0.003). Conclusion: The prognostic value of residual axillary disease should be considered differently in the 3 BC subtypes to accurately stratify patients with a high risk of recurrence after NAC who should be offered second line therapies.

Impact of Breast Cancer Pretreatment Nodal Burden and Disease Subtype on Axillary Surgical Management

BACKGROUND

The management of clinically node-positive breast cancer after neoadjuvant chemotherapy (NAC) has progressed with the potential to avoid the morbidity of axillary lymph node dissection in patients with complete response to therapy. This study addresses the impact of pretreatment nodal burden and tumor subtype on axillary pathologic complete response (AXpCR) in patients treated with NAC to better inform axillary surgical management.

METHODS

A prospective database was reviewed to identify clinically node-positive patients who underwent NAC followed by axillary lymph node dissection. Patients were stratified in accordance with abnormal nodal burden on pretreatment axillary imaging defined as low (1-2 nodes) or high (≥3 nodes), and biologic subtype defined by hormone receptor (HR+, HR-) and HER2 (human epidermal growth factor receptor 2) status. The primary outcome was AXpCR.

RESULTS

AXpCR was 43% in the study population. There was no difference in AXpCR between low and high nodal burden groups (44% versus 42%, P = 0.87). Subtype correlated to AXpCR (P < 0.001) with the highest rate (78%) in the HR-/HER2+ group. Overall, HER2+ patients had a significantly higher AXpCR than HER2- subtypes (66% versus 28% P < 0.001). HR and HER2 status were also predictive of AXpCR when comparing patient, tumor, and treatment variables.

CONCLUSIONS

Biologic subtype better correlated with rates of AXpCR than nodal burden alone with the highest rates of AXpCR in HER2+ patients. Consideration of tumor biology is more informative than nodal burden when evaluating options for axillary management after NAC.

Impact of progesterone receptor status on response to neoadjuvant chemotherapy in estrogen receptor-positive breast cancer patients

INTRODUCTION

Breast cancer patients respond differently to neoadjuvant chemotherapy(NAC) based on receptor subtype. The aim of this study was to assess the impact of progesterone receptor (PgR) status on response to neoadjuvant chemotherapy (NAC) in estrogen receptor (ER)+, human epidermal growth factor receptor (HER)- breast cancer patients.

METHODS

ER+ and HER- patients receiving NAC over a 7-year period (2011-2017) were identified. The primary outcome was breast complete pathological response (pCR) rate. Secondary outcomes included axillary pCR, axillary/breast pCR and complete radiological response (cRR).

RESULTS

A total of 203 patients were identified (149 in the ER+, PgR+, and HER- group and 54 in the ER+, PgR-, and HER- group). Compared with the PgR+ group, PgR- patients were significantly associated with breast pCR (31.5% vs 7.4%; χ² test; P < .01). In multivariable analysis, PgR- status (odds ratio [OR], 4.58; 95% confidence interval [CI]: 1.58,13.28; P = .005), radiological size >50 mm (OR, 5.38; 95% CI: 1.07,27.04; P = .04) and grade (OR, 3.52;95% CI: 1.21,10.23;P = .02) were significant predictors of breast pCR. Only PgR- status was a significant predictor of cRR (OR, 6.234; 95% CI: 2.531, 15.355; P < .001). In node positive patients, PgR negativity was associated with a trend towards breast/axillary nodal pCR (22% vs 12.7%; χ² test; P = .055).

CONCLUSION

Over 30% of ER+, PgR-, and HER- patients will have a breast pCR after NAC. PgR- is the only significant predictor of breast pCR/cRR in this tumor subtype. ER+, PgR-, and HER- patients should be considered for NAC.

Meta-analysis of the impact of progesterone receptor status on oncological outcomes in oestrogen receptor-positive breast cancer

BACKGROUND

Assessment of the oestrogen receptor (ER) provides important prognostic information in breast cancer. The impact of progesterone receptor (PgR) status is less clear. Standardization of immunohistochemical analysis of these receptors has reduced interstudy heterogeneity. The aim of this meta-analysis was to evaluate the impact of PgR negativity on outcomes in ER-positive (ER+) breast cancer.

METHODS

This study was performed according to PRISMA and MOOSE guidelines. PubMed, Embase and the Cochrane Library were searched systematically to identify studies comparing disease-free survival as the primary outcome and overall survival as secondary outcome between PgR-positive (PgR+) and PgR-negative (PgR-) status in ER+ breast cancer. A meta-analysis of time-to-effect measures from included studies was undertaken.

RESULTS

Eight studies including 13 667 patients, 11 838 in the ER+PgR+ group and 1829 in the ER+PgR- group, met the inclusion criteria. Treatment characteristics did not differ significantly between the two groups. Patients in the ER+PgR- group had a higher risk of disease recurrence than those who had ER+PgR+ disease (hazard ratio (HR) 1·57, 95 per cent c.i. 1·38 to 1·79; P < 0·001). This hazard was increased in patients with human epidermal growth factor receptor 2-negative tumours (HR 1·62, 1·37 to 1·93; P < 0·001). A similar result was observed for overall survival (HR 1·69, 1·33 to 2·14; P < 0·001).

CONCLUSION

PgR negativity is associated with significant reductions in disease-free and overall survival in ER+ breast cancer. Treatment and surveillance strategies in these patients should be tailored accordingly.

Heterogeneous Responses of Axillary Lymph Node Metastases to Neoadjuvant Chemotherapy are Common and Depend on Breast Cancer Subtype

BACKGROUND

The objective of this study was to analyze heterogeneous responses of axillary lymph node metastasis to neoadjuvant chemotherapy and to determine to what extent they differ between tumor subtypes (TN, HER2+, HR+/HER2-).

METHODS

This retrospective, monocenter study included 72 consecutive, histologically node-positive breast cancers (cT1-4 cN1-3 cM0) diagnosed in the period from January 2015 to December 2016, who had received axillary lymph node dissection following neoadjuvant chemotherapy. All individual lymph node specimens were re-evaluated for the presence of tumor cells and chemotherapy effects to assess their response to neoadjuvant chemotherapy on an individual lymph node level according to the Sataloff classification.

RESULTS

Heterogeneous axillary responses to neoadjuvant chemotherapy occurred in 47.2% of the included 72 patients. The partial response rate was significantly higher in HR+/HER2- tumors (74.2%) than in TN (28.6%) and HER2+ tumors (25.0%) (p < 0.001). The presence of at least one negative, completely responding lymph node in the axillary lymph node dissection specimen had a false-negative rate of 48.8% in predicting ypN0. It dropped below 10% if at least four completely responding negative lymph nodes were identified.

CONCLUSIONS

Our study shows that axillary heterogeneous response rates differ significantly between tumor subtypes.