Residual specimen cellularity after neoadjuvant chemotherapy for breast cancer

Pathologic response and residual tumor cellularity after neo-adjuvant chemotherapy predict prognosis in breast cancer patients

INTRODUCTION

Residual tumor cellularity (RTC) and pathologic complete response (pCR) after neo-adjuvant chemotherapy (NAC) are prognostic factors associated with improved outcomes in breast cancer (BC). However, the majority of patients achieve partial pathologic response (pPR) and no clear correlation between RTC patterns and outcomes was described. Our aims were to define predictive factors for pCR and compare different outcomes of patients with pCR or pPR and with different RTC patterns.

MATERIALS AND METHODS

Baseline and post-NAC demographics, clinicopathological characteristics, post-operative data, survival and recurrence status were recorded from our institutional database. A multivariable analysis was performed using a logistic regression model to identify independent predictors of pCR. Disease-free survival (DFS), distant disease-free survival (DDFS), and overall survival (OS) analyses were performed using the Kaplan-Meier method.

RESULTS

Overall, of the 495 patients analyzed, 148 (29.9%) achieved pCR, 347 (70.1%) had pPR, and the median RTC was 40%. Multivariable analysis identified 3 independent factors predictive of pCR: tumor stage before NAC (cT1-2 84.5% versus cT3-4 15.5%), BC sub-type (HER2-positive 54.7% versus triple-negative 29.8% versus luminal-like 15.5%), and vascular invasion (absence 98.0% versus presence 2.0%). We found statistically significant longer DFS, DDFS, and OS in patients with pCR and with RTC <40%; no difference was observed in terms of OS between RTC <40% and RTC ≥40% groups.

CONCLUSIONS

Tumor stage before NAC, BC sub-type, and vascular invasion are significant and independent factors associated with pCR. Patients with pCR and with RTC <40% have longer DFS, DDFS, and OS compared with patients with pPR.

Morphological Estimation of Cellularity on Neo-Adjuvant Treated Breast Cancer Histological Images

This paper describes a methodology that extracts key morphological features from histological breast cancer images in order to automatically assess Tumour Cellularity (TC) in Neo-Adjuvant treatment (NAT) patients. The response to NAT gives information on therapy efficacy and it is measured by the residual cancer burden index, which is composed of two metrics: TC and the assessment of lymph nodes. The data consist of whole slide images (WSIs) of breast tissue stained with Hematoxylin and Eosin (H&E) released in the 2019 SPIE Breast Challenge. The methodology proposed is based on traditional computer vision methods (K-means, watershed segmentation, Otsu’s binarisation, and morphological operations), implementing colour separation, segmentation, and feature extraction. Correlation between morphological features and the residual TC after a NAT treatment was examined. Linear regression and statistical methods were used and twenty-two key morphological parameters from the nuclei, epithelial region, and the full image were extracted. Subsequently, an automated TC assessment that was based on Machine Learning (ML) algorithms was implemented and trained with only selected key parameters. The methodology was validated with the score assigned by two pathologists through the intra-class correlation coefficient (ICC). The selection of key morphological parameters improved the results reported over other ML methodologies and it was very close to deep learning methodologies. These results are encouraging, as a traditionally-trained ML algorithm can be useful when limited training data are available preventing the use of deep learning approaches.

Breast specimen handling and reporting in the post-neoadjuvant setting: challenges and advances

Neoadjuvant systemic therapy is becoming more commonly used in patients with earlier stages of breast cancer. To assess tumour response to neoadjuvant chemotherapy, pathological evaluation is the gold standard. Depending on the treatment response, the pathological examination of these specimens can be quite challenging. However, a uniform approach to evaluate post-neoadjuvant-treated breast specimens has been lacking. Furthermore, there is no single universally accepted or endorsed classification system for assessing treatment response in this setting. Recent initiatives have attempted to create a standardised protocol for evaluation of post-neoadjuvant breast specimens. This review outlines the necessary information that should be collected prior to macroscopic examination of these specimens, the recommended and most pragmatic approach to tissue sampling for microscopic examination, describes the macroscopic and microscopic features of post-therapy breast specimens, summarises two commonly used systems for classifying treatment response and outlines the critical variables that should be included in the final pathology report.

Magnetic resonance imaging patterns of tumor regression in breast cancer patients after neo-adjuvant chemotherapy, and an analysis of the influencing factors

The objective of this study was to analyze the patterns of breast tumor shrinkage in patients after neo-adjuvant chemotherapy (NAC) based on magnetic resonance imaging (MRI), and to evaluate the influential factors. Preoperative breast dynamic contrast-enhanced MRI was performed on 88 patients before NAC, every 2 weeks during their chemotherapy treatment, and the week before their surgery. The MRI enhancement pattern of the primary tumors was classified into one of four categories based on BI-RADS-MRI: type I (postcontrast mass image), II (multiple small masses image), III (postcontrast mass image with peripheral non-mass enhancement image), and IV (nonmass enhancement image). Multivariate regression and χ² test analyses were employed to establish significant associations. Two kinds of tumor regression patterns were observed: concentric shrinkage was observed in 39 lesions of 88 patients (44.3%), and nests or dendritic shrinkage was observed for the other 49 lesions (55.7%). ER+/HER2-, HER2+, and type I lesions were observed in 23 (62.2%), 21 (63.6%), and 29 (60.0%) patients, respectively, out of 49 nest or dendritic shrinkage pattern lesions. Triple negative breast cancer lesions, and type II, III, and IV lesions were observed in 13 (72.2%), 9 (81.8%), 10 (62.5%), and 10 (76.9%) patients, respectively, out of 39 lesions with a concentric shrinkage pattern. Molecular subtypes (χ² =7.171, P<.05) and the MRI schedule of enhancement (χ² =11.244, P<.05) were significantly associated with the tumor regression patterns. Multivariate analysis showed molecular subtypes (P<.05) and MRI pattern enhancement (P<.05) were significant predictive factors. Molecular subtypes and the MRI enhancement patterns of the primary tumors were significant predictive factors for tumor regression patterns of breast cancer after NAC.

Neoadjuvant trials in early breast cancer: pathological response at surgery and correlation to longer term outcomes - what does it all mean?

BACKGROUND

Neoadjuvant breast cancer trials are important for speeding up the introduction of new treatments for patients with early breast cancer and for the highly productive translational research which they facilitate. Meta-analysis of trial data shows clear correlation between pathological response at surgery after neoadjuvant chemotherapy and longer-term outcomes at an individual patient level. However, this does not appear to be present on individual trial level analysis, when correlating improved outcome for the investigational arm for the primary endpoint (pathological response) with longer-term outcomes.

DISCUSSION

The correlation between pathological response and longer-term outcomes in trials is dependent on many factors. These include definitions of pathological response, both complete and partial; assessment methods for pathological response at surgery; subtype and prognosis of breast cancer at diagnosis; number of patients recruited; adjuvant treatments; the mechanism of action of the investigational drug; the length of follow-up at the time of reporting; the definitions used in longer-term outcomes analysis; clonal heterogeneity; and new adaptive trial designs with additional neo/adjuvant treatments. Future developments of neoadjuvant breast cancer trials are discussed. With so many factors influencing the correlation of longer-term outcomes for trial-level data, we conclude that the main focus of neoadjuvant trials should remain the primary endpoint of pathological response. Neoadjuvant breast cancer trials are very important investigational studies that will continue to increase our understanding of the disease and offer the potential of more rapid introduction of new treatments for women with high-risk early breast cancer. In the future, we are likely to see both novel trial designs adopted in the neoadjuvant context and modifications of neo/adjuvant treatments for pathological non-responders within clinical trials. Both of these have the intention of improving longer-term outcomes for patients who do not have a good pathological response to first-line neoadjuvant treatment. If successful, these developments are likely to reduce further any positive correlation between pathological response and longer-term outcomes.

Recommendations for standardized pathological characterization of residual disease for neoadjuvant clinical trials of breast cancer by the BIG-NABCG collaboration

Neoadjuvant systemic therapy (NAST) provides the unique opportunity to assess response to treatment after months rather than years of follow-up. However, significant variability exists in methods of pathologic assessment of response to NAST, and thus its interpretation for subsequent clinical decisions. Our international multidisciplinary working group was convened by the Breast International Group-North American Breast Cancer Group (BIG-NABCG) collaboration and tasked to recommend practical methods for standardized evaluation of the post-NAST surgical breast cancer specimen for clinical trials that promote accurate and reliable designation of pathologic complete response (pCR) and meaningful characterization of residual disease. Recommendations include multidisciplinary communication; clinical marking of the tumor site (clips); and radiologic, photographic, or pictorial imaging of the sliced specimen, to map the tissue sections and reconcile macroscopic and microscopic findings. The information required to define pCR (ypT0/is ypN0 or ypT0 yp N0), residual ypT and ypN stage using the current AJCC/UICC system, and the Residual Cancer Burden system were recommended for quantification of residual disease in clinical trials.

Shrink pattern of breast cancer after neoadjuvant chemotherapy and its correlation with clinical pathological factors

Background

Breast conservation therapy (BCS) after neoadjuvant chemotherapy (NCT) can improve patients’ quality of life. Currently used intraoperative examination for negative margins may not be sufficient to detect microresidual foci, which are a risk factor for local recurrence. This study was conducted to investigate the shrinking pattern of breast cancer and residual tumors as a risk factor for BCS after NCT.

Methods

Ninety women with stage II or III invasive ductal carcinoma who achieved partial response after NCT with paclitaxel and epirubicin were enrolled. All patients had undergone modified radical mastectomy. One-half of the surgical specimens were subjected to subserial sectioning. Pathological changes of tumor bed and pericancerous tissues were examined with an optical microscope. The levels of estrogen receptors, progesterone receptors and HER2 were analyzed by immnohistochemical staining.

Results

The residual tumors were classified into three types according to their microscopic morphology: solitary lesion, multifocal and patchlike lesions, and main residual tumor with satellite lesions. Type I residual tumors were found in 55 patients (61%), type II in 30 patients (33%) and type III in 5 patients (6%). Types II and III were often associated with larger primary tumors. The types of residual tumors were not correlated with the status of hormone receptors or HER2.

Conclusion

Three types of residual tumors were observed after NCT. The solitary residual tumor is most common, but main residual tumors with satellite lesions are most likely to cause local recurrence after BCS. Subserial sectioning would improve the identification of microfoci and patient survival after BCS.

Diagnostic performance of magnetic resonance imaging for assessing tumor response in patients with HER2-negative breast cancer receiving neoadjuvant chemotherapy is associated with molecular biomarker profile

BACKGROUND

This study aimed to evaluate the influence of hormone receptor (HR) and Ki-67 proliferation markers in predicting the accuracy of magnetic resonance imaging (MRI) for measuring residual tumor size in patients with HER2-negative (HER2(-)) breast cancer receiving neoadjuvant chemotherapy (NAC).

PATIENTS AND METHODS

Fifty-four women were studied. Patients received AC (doxorubicin (Adriamycin)/cyclophosphamide) and/or taxane-based regimens. The accuracy of MR-determined clinical complete response (CCR) was compared to pathological complete response (pCR). The size of detectable residual tumor on MRI was correlated with pathologically diagnosed tumor size using the Pearson correlation.

RESULTS

MRI correctly diagnosed 16 of the 17 cases of pCR. There were 8 false-negative diagnoses: 7 HR(+) and 1 HR(-). The overall sensitivity, specificity, and accuracy of MRI were 78%, 94%, and 83%, respectively. The positive predictive value was 97% and the negative predictive value was 67%. For MRI vs. pathologically determined tumor size correlation, HR(-) cancers showed a higher correlation (R = 0.79) than did HR(+) cancers (R = 0.58). A worse MRI/pathology size discrepancy was found in HR(+) cancer than in HR(-)cancer (1.6 ± 2.8 cm vs. 0.56 ± 0.9 cm; P = .05). Tumors with low Ki-67 proliferation (< 40%) showed a larger size discrepancy than did those with high Ki-67 proliferation (≥ 40%) (1.2 ± 2.0 cm vs. 0.4 ± 0.8 cm; P = .05).

CONCLUSIONS

The results showed that the diagnostic performance of MRI for patients with breast cancer undergoing NAC is associated with a molecular biomarker profile. Among HER2(-)tumors, the accuracy of MRI was worse in HR(+)cancers than in HR(-)cancers and was also worse in low-proliferation tumors than in high-proliferation tumors. These findings may help in surgical planning.

Breast cancer: evaluation of response to neoadjuvant chemotherapy with 3.0-T MR imaging

PURPOSE

To assess how the molecular biomarker status of a breast cancer, including human epidermal growth factor receptor 2 (HER2), hormone receptors, and the proliferation marker Ki-67 status, affects the diagnosis at 3.0-T magnetic resonance (MR) imaging.

MATERIALS AND METHODS

This study was approved by the institutional review board and was HIPAA compliant. Fifty patients (age range, 28-82 years; mean age, 49 years) receiving neoadjuvant chemotherapy were monitored with 3.0-T MR imaging. The longest dimension of the residual cancer was measured at MR imaging and correlated with pathologic findings. Patients were further divided into subgroups on the basis of HER2, hormone receptor, and Ki-67 status. Pathologic complete response (pCR) was defined as when there were no residual invasive cancer cells. The Pearson correlation was used to correlate MR imaging-determined and pathologic tumor size, and the unpaired t test was used to compare MR imaging-pathologic size discrepancies.

RESULTS

Of the 50 women, 14 achieved pCR. There were seven false-negative diagnoses at MR imaging. The overall sensitivity, specificity, and accuracy for diagnosing invasive residual disease at MR imaging were 81%, 93%, and 84%, respectively. The mean MR imaging-pathologic size discrepancy was 0.5 cm ± 0.9 (standard deviation) for HER2-positive cancer and 2.3 cm ± 3.5 for HER2-negative cancer (P = .009). In the HER2-negative group, the size discrepancy was smaller for hormone receptor-negative than for hormone receptor-positive cancers (1.0 cm ± 1.1 vs 3.0 cm ± 4.0, P = .04). The size discrepancy was smaller in patients with 40% or greater Ki-67 expression (0.8 cm ± 1.1) than in patients with 10% or less Ki-67 expression (3.9 cm ± 5.1, P = .06).

CONCLUSION

The diagnostic accuracy of breast MR imaging is better in more aggressive than in less aggressive cancers. When MR imaging is used for surgical planning, caution should be taken with HER2-negative hormone receptor-positive cancers.

Neoadjuvant chemotherapy for early breast cancer

BACKGROUND

Neoadjuvant chemotherapy defines the preoperative administration of systemic therapy in order to downstage the primary tumor and affected lymph nodes to improve the surgical approach. Neoadjuvant chemotherapy is increasingly being used in the treatment of early operable breast cancer.

OBJECTIVE

We reviewed the available data of neoadjuvant chemotherapy with emphasis on tumor response assessment and prediction, and locoregional management.

METHODS

We searched the databases of MEDLINE and EMBASE using the search terms breast cancer, neoadjuvant or preoperative or primary or induction, and chemotherapy from 1950 to 1 March 2009.

RESULTS/CONCLUSION

Compared with adjuvant chemotherapy, neoadjuvant chemotherapy increases breast conservation with equal survival and locoregional control. Tumor response assessment during neoadjuvant chemotherapy allows identification of in vivo tumor sensitivity to different agents which will help determine predictive factors for improved selection criteria. Randomized trials assessing the timing of sentinel lymph node biopsy in initially lymph node positive patients are warranted. In the near future, intraoperative fluorescent imaging and targeting of cancer stem cells will become important avenues of research.