Pathologic Evaluation of Breast Cancer after Neoadjuvant Therapy

Ambiguity-aware breast tumor cellularity estimation via self-ensemble label distribution learning

In this work, we address the task of tumor cellularity (TC) estimation with a novel framework based on the label distribution learning (LDL) paradigm. We propose a self-ensemble label distribution learning framework (SLDL) to resolve the challenges of existing LDL-based methods, including difficulties for inter-rater ambiguity exploitation, proper and flexible label distribution generation, and accurate TC value recovery. The proposed SLDL makes four main contributions which have been demonstrated to be quite effective in numerous experiments. First, we propose an expertness-aware conditional VAE for diversified single-rater modeling and an attention-based multi-rater fusion strategy that enables effective inter-rater ambiguity exploitation. Second, we propose a template-based label distribution generation method that is tailored for the TC estimation task and constructs label distributions based on the annotation priors. Third, we propose a novel restricted distribution loss, significantly improving the TC value estimation by effectively regularizing the learning with unimodal loss and regression loss. Fourth, to the best of our knowledge, we are the first to simultaneously leverage inter-rater and intra-rater variability to address the label ambiguity issue in the breast tumor cellularity estimation tasks. The experimental results on the public BreastPathQ dataset demonstrate that the SLDL outperforms the existing methods by a large margin and achieves new state-of-the-art results in the TC estimation task. The code will be available from https://github.com/PerceptionComputingLab/ULTRA.

The Role of Stromal Tumour Infiltrating Lymphocytes (sTIL) Intensity and Programmed Death Ligand 1 () Expression in Breast Cancer Response to Neoadjuvant Therapy in Cipto Mangunkusumo Hospital (CMH), Indonesia

BACKGROUND

Pathological responses to neoadjuvant therapy were still relatively poor, especially in CMH. Studies had been done to search for predictors of response such as sTIL intensity and  expression, which is known to block sTIL action in killing cancer cells. This research assessed sTIL intensity and  expression as predictors of response to neoadjuvant therapy in breast cancer. The preliminary data might be used to better tailored breast cancer patient therapy, considering the availability of anti-PD-1/ PD- L1 immunotherapy nowadays.

OBJECTIVE

To assess TIL intensity,  expressions, and their roles as pathological predictors of breast cancer response to neoadjuvant therapy in Cipto Mangunkusumo Hospital (CMH).

METHOD

This was an observational analytic retrospective cohort study on breast cancer patients undergoing biopsy/review of biopsy specimens, receiving neoadjuvant therapy and mastectomy in CMH from January 2014 to December 2021. Sixty cases fulfilled the inclusion and exclusion criteria. Total sampling was done.   expression (immunohistochemistry, clone 22C3) and sTIL intensity (histopathology) was examined in the biopsy specimen. Linear regression analysis was done to determine the independent predictors of neoadjuvant therapy response (evaluated in the mastectomy specimen with residual cancer burden/ RCB score).

RESULTS

There were 60 female patients, median age 46 years old. 91,7% had invasive carcinoma of no special type. Median sTIL intensity was 10% (1%-70%). 58,3% patients had low sTIL intensity (≤10%). 28,3% patients had positive  expression (CPS ≥1). Only 8,3% patients had pCR, while 90% patients had RCB class II-III. Every 1% increase in sTIL intensity, no lymphovascular invasion, and taxane chemotherapy were predicted to lower RCB score by 0,058, 0,781, dan 0,594, respectively.  expression associated with pCR-RCB class I (p=0,048), but CPS score was not a predictor of RCB score in linear regression analysis.

CONSLUSION

sTIL intensity was an independent predictor of breast cancer response to neoadjuvant therapy in RSCM.  expression associated with pCR-RCB class I, but CPS score was not a predictor of RCB score.

Compression OCT-elastography combined with speckle-contrast analysis as an approach to the morphological assessment of breast cancer tissue

Currently, optical biopsy technologies are being developed for rapid and label-free visualization of biological tissue with micrometer-level resolution. They can play an important role in breast-conserving surgery guidance, detection of residual cancer cells, and targeted histological analysis. For solving these problems, compression optical coherence elastography (C-OCE) demonstrated impressive results based on differences in the elasticity of different tissue constituents. However, sometimes straightforward C-OCE-based differentiation is insufficient because of the similar stiffness of certain tissue components. We present a new automated approach to the rapid morphological assessment of human breast cancer based on the combined usage of C-OCE and speckle-contrast (SC) analysis. Using the SC analysis of structural OCT images, the threshold value of the SC coefficient was established to enable the separation of areas of adipose cells from necrotic cancer cells, even if they are highly similar in elastic properties. Consequently, the boundaries of the tumor bed can be reliably identified. The joint analysis of structural and elastographic images enables automated morphological segmentation based on the characteristic ranges of stiffness (Young's modulus) and SC coefficient established for four morphological structures of breast-cancer samples from patients post neoadjuvant chemotherapy (residual cancer cells, cancer stroma, necrotic cancer cells, and mammary adipose cells). This enabled precise automated detection of residual cancer-cell zones within the tumor bed for grading cancer response to chemotherapy. The results of C-OCE/SC morphometry highly correlated with the histology-based results (r =0.96-0.98). The combined C-OCE/SC approach has the potential to be used intraoperatively for achieving clean resection margins in breast cancer surgery and for performing targeted histological analysis of samples, including the evaluation of the efficacy of cancer chemotherapy.

Assessing the Correlation of Rate of Pathological Complete Response and Outcome in Post Neoadjuvant Chemotherapy Setting and Molecular Subtypes of Breast Cancer

Background Neoadjuvant chemotherapy (NAC) is being widely used in treating breast cancer (BC). This study aimed to analyze the correlation between clinicopathological features, immunohistochemistry (IHC)-based molecular subtypes, and the pathological response to NAC and its relationship with disease-free survival (DFS) and overall survival (OS). Materials and methods A retrospective analysis of 211 breast cancer patients who received NAC between 2008 and 2018 was performed. Tumors were classified by IHC into luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)-enriched, and triple-negative subtypes. The chi-square test was used to assess the association between pathological response and clinicopathological parameters. Cox regression analysis was used to assess factors related to DFS and OS. Results Post NAC, 19.4% of patients achieved a pathologic complete response (pCR). Estrogen receptor (ER), progesterone receptor (PR), HER2 (p<0.001, 0.005, and 0.02), Ki67 (p=0.03), molecular subtypes (p<0.001), T stage (p=0.04), and N stage (p=0.01) were significantly associated with pathological response. The rate of pCR was highest among HER2-enriched and triple-negative tumors (45.2% and 28%, respectively) with OR=0.13 and p<0.001 for the HER2-enriched subtype. Patients with pCR were 61% less likely to develop metastasis (adjusted hazard ratio [aHR]=0.39, p=0.06, 95% CI=0.14-1.06) and were significantly associated with better OS (aHR=0.07, p=0.02, 95% CI=0.01-0.61). Patients who were ≤40 years old (aHR=2.1, p=0.01), with T4 (aHR=3.4, p=0.02), grade 3 (aHR=2.5, p=0.01), and node-positive disease (HR=2.24, p=0.02) were at an increased risk of developing metastasis. High Ki67 was found to be significantly associated with better DFS (p=0.006). Conclusion HER2-enriched and triple-negative BC were associated with a higher rate of pCR. Patients with pCR had significantly better DFS and OS. Younger age, advanced stage, higher grade, and lymph node involvement were risk factors for metastasis.

Good practice: The experiences with the utilization of residual cancer burden-A single institution study

INTRODUCTION

The use of neoadjuvant therapy (NAT) has been showing an incraesing tendency in the treatment of locally advanced breast cancer. The evaluation of residual cancer could be performed by Residual Cancer Burden (RCB) calculator. The prognostic system takes the two largest diameters of the tumor, the cellularity, the amount of in situ carcinoma, the number of metastatic lymph nodes, and the size of the largest metastatic deposit into account. The aim of our study was to examine the reproducibility of RCB in NAT treated patients.

METHODS

Patients who were treated with NAT and had resection specimens between 2018 and 2021 were selected. Histological examination was performed by five pathologists. After assessment of the examined variables, RCB points and RCB classes were defined. For statistical analysis, interclass correlation was used (SPSS Statistics V.22.0 software).

RESULTS

Altogether 100 patients were included in our retrospective, cohort study (average age: 57 years). In two-thirds of the cases, third generation chemotherapy was used, and mastectomy was performed. Significant concordance was found in the two largest diameters of the tumor (coefficients, 0.984 and 0.973), the cellularity (coefficient, 0.970), and the largest metastatic deposit (coefficient, 0.998). Although the amount of in situ carcinoma proved to be the least reproducible factor, it resulted in almost 90% of agreement (coefficient, 0.873). Regarding RCB points and classes, similar results were observed (coefficients, 0.989 and 0.960).

CONCLUSIONS

Significant agreement was observed between examiners based on almost all RCB parameters, points, and classes, reflecting the optimal reproducibility of RCB. Therefore, we recommend the use of the calculator in routine histopathological reports in NAT cases.

Post-Neoadjuvant Treatment Strategies for Patients with Early Breast Cancer

Simple Summary

Treatment strategies for early breast cancer have significantly improved in the last decades. Several new effective agents have proved clinical benefit and have entered the clinics, changing the treatment landscape for this disease and inducing significant prolongation of patient survival. Alongside, there has been an evolution in the design of clinical trials for early breast cancer, with an increasing interest in the pre-surgical treatment approach, which allows a direct evaluation of treatment effect on tumor size and a post-therapy risk stratification. Consequently, the post-neoadjuvant setting has been gaining increasing attention, thanks to the possibility to provide additional treatment for selected patients at higher risk of relapse, namely those who did not respond to neoadjuvant therapy and had residual disease at surgery.

Abstract

Pre-surgical treatments in patients with early breast cancer allows a direct estimation of treatment efficacy, by comparing the tumor and the treatment. Patients who achieve a pathological complete response at surgery have a better prognosis, with lower risk of disease recurrence and death. Hence, clinical research efforts have been focusing on high-risk patients with residual disease at surgery, who may be “salvaged” through additional treatments administered in the post-neoadjuvant setting. In the present review, we aim to illustrate the development and advantages of the post-neoadjuvant setting, and to discuss the available strategies for patients with early breast cancer, either approved or under investigation. This review was written after literature search on main scientific databases (e.g., PubMed) and conference proceedings from major oncology conferences up to 1 August 2022. T-DM1 and capecitabine are currently approved as post-neoadjuvant treatments for patients with HER2-positive and triple-negative breast cancer, respectively, with residual disease at surgery. More recently, other treatment strategies have been approved for patients with high-risk early breast cancer, including the immune checkpoint inhibitor pembrolizumab, the PARP inhibitor olaparib and the CDK 4/6 inhibitor abemaciclib. Novel agents and treatment combinations are currently under investigation as promising post-neoadjuvant treatment strategies.

The prognostic role of lymph node ratio in breast cancer patients received neoadjuvant chemotherapy: A dose-response meta-analysis

BACKGROUND

As neoadjuvant chemotherapy is widely used in breast cancer patients, the lymph node ratio has not been fully validated as a prognostic indicator of breast cancer received neoadjuvant chemotherapy. This study was conducted to investigate the prognostic value of lymph node ratio in breast cancer patients received neoadjuvant chemotherapy.

METHODS

Systematic searches were performed in the PubMed, Embase, and Cochrane Library databases until 15 December 2021 for studies on the association between lymph node ratio and the prognosis of breast cancer after neoadjuvant chemotherapy. Overall survival and disease-free survival were used as outcome events, and hazard ratio was chosen as the parameter to evaluate the correlation. The dose-response relationship was assessed by restricted cubic splines. In the subgroup analyses, which were used to explore potential heterogeneity among the included studies according to study region and sample size. Sensitivity analysis was performed to assess the stability of individual studies, and publication bias was determined with funnel plots, Begg's test, and Egger&apos;s test. All statistical analyses were performed using Stata 15.1.

RESULTS

A total of 12 studies with 4,864 patients were included in this meta-analysis. In this study, high lymph node ratio was significantly associated with decreased overall survival (HR: 4.74; 95%CI: 3.36-6.67; P < 0.001) and disease-free survival (HR: 4.77; 95%CI: 3.69-6.17; P < 0.001). Moreover, the dose-response meta-analysis showed a linear association between higher lymph node ratio and shorter overall survival and disease-free survival in breast cancer patients after neoadjuvant chemotherapy.

CONCLUSIONS

The meta-analysis suggested that high lymph node ratio was significantly associated with short overall survival and disease-free survival in breast cancer patients after neoadjuvant chemotherapy. Therefore, lymph node ratio is an independent predictive factor for the prognosis of breast cancer patients after neoadjuvant chemotherapy, which may better refine the cancer staging system.

The Role of miR-375-3p, miR-210-3p and Let-7e-5p in the Pathological Response of Breast Cancer Patients to Neoadjuvant Therapy

Background and Objectives: Prediction of response to therapy remains a continuing challenge in treating breast cancer, especially for identifying molecular tissue markers that best characterize resistant tumours. Microribonucleic acids (miRNA), known as master modulators of tumour phenotype, could be helpful candidates for predicting drug resistance. We aimed to assess the association of miR-375-3p, miR-210-3p and let-7e-5p in breast cancer tissues with pathological response to neoadjuvant therapy (NAT) and clinicopathological data. Material and methods: Sixty female patients diagnosed with invasive breast cancer at The Oncology Institute “Ion Chiricuță”, Cluj-Napoca, Romania (IOCN) were included in this study. Before patients received any treatment, fresh breast tissue biopsies were collected through core biopsy under echographic guidance and processed for total RNA extraction and miRNA quantification. The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) database was used as an independent external validation cohort. Results: miR-375-3p expression was associated with more differentiated tumours, hormone receptor presence and lymphatic invasion. According to the Miller–Payne system, a higher miR-375-3p expression was calculated for patients that presented with intermediate versus (vs.) no pathological response. Higher miR-210-3p expression was associated with an improved response to NAT in both Miller–Payne and RCB evaluation systems. Several druggable mRNA targets were correlated with miR-375-3p and miR-210-3p expression, with upstream analysis using the IPA knowledge base revealing a list of possible chemical and biological targeting drugs. Regarding let-7e-5p, no significant association was noticed with any of the analysed clinicopathological data. Conclusions: Our results suggest that tumours with higher levels of miR-375-3p are more sensitive to neoadjuvant therapy compared to resistant tumours and that higher miR-210-3p expression in responsive tumours could indicate an excellent pathological response.

Predictive Role of Soluble IL-6R, TNF-R1/2, and Cell Adhesion Molecules Serum Levels in the Preoperative and Adjuvant Therapy in Women with Nonmetastatic Breast Cancer: A Preliminary Study

Soluble cell adhesion molecules (sCAMs) are involved in the development of neoplastic diseases. sCAMs can block lymphocytes and promote angiogenesis and migration of breast cancer (BC) cells. Interleukin 6 (IL-6) and tumor necrosis factor α (TNF-α) enhance metastatic potential via upregulation of CAMs. We assessed soluble interleukin-6 receptor subunit alpha (IL-6Ra), TNF-R1, TNF-R2, E-selectin, P-selectin, VCAM-1, ICAM-1, and EpCAM in 89 women with stage I-III BC and 28 healthy women. Blood samples were obtained at the beginning of neoadjuvant/induction (N = 49) or adjuvant treatment (N = 40), and after 2 months. Surgery revealed complete response in 29.4% of patients, partial response in 67%, and stable disease in 5.9%. Achieving a pathological response was 4 times greater for baseline levels of sIL-6Ra >5.63 ng/mL [odds ratio (OR) = 4.1, 95% confidence interval (CI): 0.8-20.4, P = 0.08] and more than 6 times for soluble tumor necrosis factor receptor 1 (sTNF-R1) ≥ 0.97 ng/mL (OR = 6.2, 95% CI: 1.2-32.3, P < 0.05). Compared with the control group, serum sP-selectin, soluble epithelial cell adhesion molecule (sEpCAM), and sTNF-R2 concentrations were significantly higher in patients who started adjuvant therapy (P < 0.05) and preoperative therapy (P < 0.01). Baseline serum sIL-6Ra concentrations were significantly higher in patients before surgery than in patients after tumor resection (P < 0.05), independent of the follow-up time. The baseline serum soluble receptors of IL-6 (sIL-6R) and TNF-α (sTNF-R1) concentrations have a predictive value for preoperative therapy in patients with BC.

Efficacy Evaluation of Neoadjuvant Chemotherapy in Breast Cancer by MRI

Breast cancer is a highly harmful malignancy, which often causes great distress to patients and seriously affects their physical and mental health. Breast cancer causes patients to experience decreased appetite, decreased eating, and indigestion, which in turn leads to malnutrition, body wasting, resistance, immune compromise, progressive anemia, cachexia, and, as a result, severe secondary infections. To investigate the efficacy evaluation of neoadjuvant chemotherapy in breast cancer by MRI, forty-eight subjects treated at the hospital from June 2014 to August 2019 were recruited. After the neoadjuvant chemotherapy, the patients were divided into two groups based on the results of histopathological examination, namely, the ineffective group (n = 14) and the effective group (n = 34). Changes in MRI indicators were compared between the two groups before and after the neoadjuvant chemotherapy. The maximum diameter of lesions decreased significantly after the neoadjuvant chemotherapy than before. The apparent diffusion coefficient (ADC) increased considerably, and the time-intensity curve (TIC) showed a transition from type III to type II/I and from type II to type I. MRI can indicate the maximum diameter of the breast cancer lesion, ADC, and TIC type. Therefore, it can be used to evaluate the efficacy of neoadjuvant chemotherapy for breast cancer and be widely applied in clinical practice.

Diagnostic performance of digital breast tomosynthesis for predicting response to neoadjuvant systemic therapy in breast cancer patients: A comparison with magnetic resonance imaging, ultrasound, and full-field digital mammography

Background

The goals of neoadjuvant systemic therapy (NST) are to reduce tumor volume and to provide a prognostic indicator in assessing treatment response. Digital breast tomosynthesis (DBT) was developed and has increased interest in clinical settings due to its higher sensitivity for breast cancer detection compared to full-field digital mammography (FFDM).

Purpose

To evaluate the accuracy of DBT in assessing response to NST compared to FFDM, ultrasound (US), and magnetic resonance imaging (MRI) in breast cancer patients.

Material and Methods

In this retrospective study, 95 stages II–III breast cancer patients undergoing NST and subsequent surgeries were enrolled. After NST, the longest diameter of residual tumor measured by DBT, FFDM, US, and MRI was compared with pathology. Agreements and correlations of tumor size were assessed, and the diagnostic performance for predicting pathologic complete response (pCR) was evaluated.

Results

Mean residual tumor size after NST was 19.9 mm for DBT, 18.7 mm for FFDM, 16.0 mm for US, and 18.4 mm for MRI, compared with 17.9 mm on pathology. DBT and MRI correlated better with pathology than that of FFDM and US. The ICC values were 0.85, 0.87, 0.74, and 0.77, respectively. Twenty-five patients (26.3%) achieved pCR after NST. For predicting pCR, area under the receiver operating characteristic (ROC) curve for DBT, FFDM, US, and MRI were 0.79, 0.66, 0.68, and 0.77, respectively.

Conclusion

DBT has good correlation with histopathology for measuring residual tumor size after NST. DBT was comparable to MRI in assessing tumor response after completion of NST.

Pathology after neoadjuvant treatment - How to assess residual disease

While systemic therapy for non-metastatic, invasive breast cancer is provided to minimize the risk of recurrence, neoadjuvant therapy (NAT) is given prior to surgery to downstage the tumor and to evaluate treatment response. Downstaging the tumor may allow for less invasive surgery on the breast and axilla, thus avoiding the need for breast reconstruction, improving cosmetic outcomes, and reducing postoperative complications. With the rising number of NAT candidates, it is becoming increasingly important to standardize how tumor response is assessed after surgery. In the post-NAT setting, macroscopic assessment of surgical samples, extent of sampling for histology, and microscopic analysis require a different approach than in the primary surgery setting. In the neo-adjuvant setting, the close collaboration of pathologists, oncologists, surgeons, and radiologists within the multidisciplinary team is essential to ensure the best possible management of breast cancer patients. Here, we provide an update on the suggested procedures for an accurate assessment of tumor response to NAT, including the evaluation of all relevant parameters that correlate with long-term prognosis and inform the subsequent adjuvant interventions.

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Neoadjuvant therapy (NAT) is given to downstage the tumor and evaluate treatment response.

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It is extremely important to standardize how NAT tumor response is assessed after surgery.

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A tailored approach is required for gross examination and microscopic analysis of both tumor and lymph nodes (either sentinel and axillary).

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Changes of biomarkers status (i.e. ER, PgR, Ki67, and HER2) can occur after NAT and biomarkers should always be re-assessed.

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Collaboration of pathologists, oncologists, surgeons, and radiologists is necessary for the appropriate clinical management.

Tumor Microenvironment in Breast Cancer-Updates on Therapeutic Implications and Pathologic Assessment

The tumor microenvironment (TME) in breast cancer comprises local factors, cancer cells, immune cells and stromal cells of the local and distant tissues. The interaction between cancer cells and their microenvironment plays important roles in tumor proliferation, propagation and response to therapies. There is increasing research in exploring and manipulating the non-cancerous components of the TME for breast cancer treatment. As the TME is now increasingly recognized as a treatment target, its pathologic assessment has become a critical component of breast cancer management. The latest WHO classification of tumors of the breast listed stromal response pattern/fibrotic focus as a prognostic factor and includes recommendations on the assessment of tumor infiltrating lymphocytes and PD-1/PD-L1 expression, with therapeutic implications. This review dissects the TME of breast cancer, describes pathologic assessment relevant for prognostication and treatment decision, and details therapeutic options that interacts with and/or exploits the TME in breast cancer.

SPIE-AAPM-NCI BreastPathQ challenge: an image analysis challenge for quantitative tumor cellularity assessment in breast cancer histology images following neoadjuvant treatment

Purpose: The breast pathology quantitative biomarkers (BreastPathQ) challenge was a grand challenge organized jointly by the International Society for Optics and Photonics (SPIE), the American Association of Physicists in Medicine (AAPM), the U.S. National Cancer Institute (NCI), and the U.S. Food and Drug Administration (FDA). The task of the BreastPathQ challenge was computerized estimation of tumor cellularity (TC) in breast cancer histology images following neoadjuvant treatment. Approach: A total of 39 teams developed, validated, and tested their TC estimation algorithms during the challenge. The training, validation, and testing sets consisted of 2394, 185, and 1119 image patches originating from 63, 6, and 27 scanned pathology slides from 33, 4, and 18 patients, respectively. The summary performance metric used for comparing and ranking algorithms was the average prediction probability concordance (PK) using scores from two pathologists as the TC reference standard. Results: Test PK performance ranged from 0.497 to 0.941 across the 100 submitted algorithms. The submitted algorithms generally performed well in estimating TC, with high-performing algorithms obtaining comparable results to the average interrater PK of 0.927 from the two pathologists providing the reference TC scores. Conclusions: The SPIE-AAPM-NCI BreastPathQ challenge was a success, indicating that artificial intelligence/machine learning algorithms may be able to approach human performance for cellularity assessment and may have some utility in clinical practice for improving efficiency and reducing reader variability. The BreastPathQ challenge can be accessed on the Grand Challenge website.

Early prediction of neoadjuvant chemotherapy response for advanced breast cancer using PET/MRI image deep learning

This study aimed to investigate the predictive efficacy of positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) for the pathological response of advanced breast cancer to neoadjuvant chemotherapy (NAC). The breast PET/MRI image deep learning model was introduced and compared with the conventional methods. PET/CT and MRI parameters were evaluated before and after the first NAC cycle in patients with advanced breast cancer [n = 56; all women; median age, 49 (range 26–66) years]. The maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained with the corresponding baseline values (SUV0, MTV0, and TLG0, respectively) and interim PET images (SUV1, MTV1, and TLG1, respectively). Mean apparent diffusion coefficients were obtained from baseline and interim diffusion MR images (ADC0 and ADC1, respectively). The differences between the baseline and interim parameters were measured (ΔSUV, ΔMTV, ΔTLG, and ΔADC). Subgroup analysis was performed for the HER2-negative and triple-negative groups. Datasets for convolutional neural network (CNN), assigned as training (80%) and test datasets (20%), were cropped from the baseline (PET0, MRI0) and interim (PET1, MRI1) images. Histopathologic responses were assessed using the Miller and Payne system, after three cycles of chemotherapy. Receiver operating characteristic curve analysis was used to assess the performance of the differentiating responders and non-responders. There were six responders (11%) and 50 non-responders (89%). The area under the curve (AUC) was the highest for ΔSUV at 0.805 (95% CI 0.677–0.899). The AUC was the highest for ΔSUV at 0.879 (95% CI 0.722–0.965) for the HER2-negative subtype. AUC improved following CNN application (SUV0:PET0 = 0.652:0.886, SUV1:PET1 = 0.687:0.980, and ADC1:MRI1 = 0.537:0.701), except for ADC0 (ADC0:MRI0 = 0.703:0.602). PET/MRI image deep learning model can predict pathological responses to NAC in patients with advanced breast cancer.

Assessing the accuracy of conventional gadolinium-enhanced breast MRI in measuring the nodal response to neoadjuvant chemotherapy (NAC) in breast cancer

Management of the axilla in the era of neoadjuvant chemotherapy for breast cancer is evolving. The aim of this study is to determine if conventional gadolinium-enhanced breast MRI can aid in evaluation of the response to neoadjuvant chemotherapy in the axilla. A retrospective review of a prospectively maintained database of patients undergoing neoadjuvant chemotherapy for breast cancer was performed. Pre and post-neoadjuvant chemotherapy MRI reports for node-positive patients were examined in conjunction with demographic data, treatment type, and final histopathology reports. One-hundred and fourteen patients with breast cancer undergoing neoadjuvant chemotherapy were included in the study. The sensitivity of magnetic resonance imaging in detecting nodal response post-neoadjuvant chemotherapy was 33.93% and the specificity was 82.76%. Magnetic resonance imaging had a positive predictive value of 65.52% and a negative predictive value of 56.47%. MRI was found to be most specific in the detection of triple-negative cancer response. Specificity was 100% in this group and sensitivity was 75%. Magnetic resonance imaging has a relatively high specificity in detecting nodal response post-neoadjuvant chemotherapy but has a low sensitivity. Alone it cannot be relied upon to identify active axillary malignancy post-neoadjuvant chemotherapy. However, given its increased specificity among certain subgroups, it may have a role in super-selecting patients suitable for sentinel lymph node biopsy post-neoadjuvant chemotherapy.

Integrating evolutionary dynamics into cancer therapy

Many effective drugs for metastatic and/or advanced-stage cancers have been developed over the past decade, although the evolution of resistance remains the major barrier to disease control or cure. In large, diverse populations such as the cells that compose metastatic cancers, the emergence of cells that are resistant or that can quickly develop resistance is virtually inevitable and most likely cannot be prevented. However, clinically significant resistance occurs only when the pre-existing resistant phenotypes are able to proliferate extensively, a process governed by eco-evolutionary dynamics. Attempts to disrupt the molecular mechanisms of resistance have generally been unsuccessful in clinical practice. In this Review, we focus on the Darwinian processes driving the eco-evolutionary dynamics of treatment-resistant cancer populations. We describe a variety of evolutionarily informed strategies designed to increase the probability of disease control or cure by anticipating and steering the evolutionary dynamics of acquired resistance.

Examination of Tumor Regression Grading Systems in Breast Cancer Patients Who Received Neoadjuvant Therapy

Neoadjuvant therapy is a common form of treatment in locally advanced breast cancer (LABC) patients. Besides some guidelines for grading regression, a standardized general scheme is not yet available. The aim of our study was to compare the prognostic impact of different regression grading systems, namely the TR/NR, Chevallier, Sataloff, Denkert-Sinn, Miller-Payne, NSABP-B18, Residual Disease in Breast and Nodes and Residual Cancer Burden (RCB) on disease-free (DFS) and overall survival (OS). Data of 746 breast cancer patients treated in neoadjuvant setting between 1999 and 2019 have been included. The different regression grades and follow-up data were collected from medical charts. Statistical analysis included the Kaplan-Meier method, log-rank test and multivariate Cox regression. The average patient age was 55 years. The DFS and OS estimates of patients with complete pathological regression and residual in situ carcinoma have been significantly more favorable than those having partial regression or no signs of regression (pDFS<0.001, pOS < 0.001). Significant differences were found between DFS estimates of classes with partial regression and without regression defined by RCB. Concerning DFS estimates, the RCB classification (p = 0.019), while regarding OS data the y-stage (p = 0.011) and the nodal status (ypN; p = 0.045) were significant prognosticators by multivariate Cox regression. Regression grading systems help the evaluation of regression in LABC patients treated with neoadjuvant therapy. Of the several grading systems compared, the RCB classification makes the best distinction between the outcomes of the different classes, therefore we recommend the inclusion of RCB into the histopathological findings.

Mammographic density is a potential predictive marker of pathological response after neoadjuvant chemotherapy in breast cancer

Background

Our aim is to study if mammographic density (MD) prior to neoadjuvant chemotherapy is a predictive factor in accomplishing a pathological complete response (pCR) in neoadjuvant-treated breast cancer patients.

Methods

Data on all neoadjuvant treated breast cancer patients in Southern Sweden (2005–2016) were retrospectively identified, with patient and tumor characteristics retrieved from their medical charts. Diagnostic mammograms were used to evaluate and score MD as categorized by breast composition with the Breast Imaging-Reporting and Data System (BI-RADS) 5th edition. Logistic regression was used in complete cases to assess the odds ratios (OR) for pCR compared to BI-RADS categories (a vs b-d), adjusting for patient and pre-treatment tumor characteristics.

Results

A total of 302 patients were included in the study population, of which 57 (18.9%) patients accomplished pCR following neoadjuvant chemotherapy. The number of patients in the BI-RADS category a, b, c, and d were separately 16, 120, 140, and 26, respectively. In comparison to patients with BI-RADS breast composition a, patients with denser breasts had a lower OR of accomplishing pCR: BI-RADS b 0.32 (95%CI 0.07–0.1.5), BI-RADS c 0.30 (95%CI 0.06–1.45), and BI-RADS d 0.06 (95%CI 0.01–0.56). These associations were measured with lower point estimates, but wider confidence interval, in premenopausal patients; OR of accomplishing pCR for BI-RADS d in comparison to BI-RADS a: 0.03 (95%CI 0.00–0.76).

Conclusions

The likelihood of accomplishing pCR is indicated to be lower in breast cancer patients with higher MD, which need to be analysed in future studies for improved clinical decision-making regarding neoadjuvant treatment.

Multimodal image-guided surgery of HER2-positive breast cancer using [111In]In-DTPA-trastuzumab-IRDye800CW in an orthotopic breast tumor model

Background

Combining modalities using dual-labeled antibodies may allow preoperative and intraoperative tumor localization and could be used in image-guided surgery to improve complete tumor resection. Trastuzumab is a monoclonal antibody against the human epidermal growth factor-2 (HER2) receptor and dual-labeled trastuzumab with both a fluorophore (IRDye800CW) and a radioactive label (¹¹¹In) can be used for multimodal imaging of HER2-positive breast cancer. The aim of this study was to demonstrate the feasibility of HER2-targeted multimodal imaging using [¹¹¹In]In-DTPA-trastuzumab-IRDye800CW in an orthotopic breast cancer model.

Methods

Trastuzumab was conjugated with p-isothiocyanatobenzyl (ITC)-diethylenetriaminepentaacetic acid (DTPA) and IRDye800CW-NHS ester and subsequently labeled with ¹¹¹In. In a dose escalation study, the biodistribution of 10, 30, and 100 μg [¹¹¹In]In-DTPA-trastuzumab-IRDye800CW was determined 48 h after injection in BALB/c nude mice with orthotopic high HER2-expressing tumors. Also, a biodistribution study was performed in a low HER2-expressing breast cancer model. In addition, multimodal image-guided surgery was performed in each group. Autoradiography, fluorescence microscopy, and immunohistochemically stained slices of the tumors were compared for co-localization of tumor tissue, HER2 expression, fluorescence, and radiosignal.

Results

Based on the biodistribution data, a 30 μg dose of dual-labeled trastuzumab (tumor-to-blood ratio 13 ± 2) was chosen for all subsequent studies. [¹¹¹In]In-DTPA-trastuzumab-IRDye800CW specifically accumulated in orthotopic HER2-positive BT474 tumors (101 ± 7 %IA/g), whereas uptake in orthotopic low HER2-expressing MCF7 tumor was significantly lower (1.2 ± 0.2 %IA/g, p = 0.007). BT474 tumors could clearly be visualized with both micro-SPECT/CT, fluorescence imaging and subsequently, image-guided resection was performed. Immunohistochemical analyses of BT474 tumors demonstrated correspondence in fluorescence, radiosignal, and high HER2 expression.

Conclusions

Dual-labeled trastuzumab showed specific accumulation in orthotopic HER2-positive BT474 breast tumors with micro-SPECT/CT and fluorescence imaging and enabled image-guided tumor resection. In the clinical setting, [¹¹¹In]In-DTPA-trastuzumab-IRDye800CW could be valuable for preoperative detection of (metastatic) tumors by SPECT/CT imaging, and intraoperative localization by using a gamma probe and fluorescence image-guided surgery to improve radical resection of tumor tissue in patients with HER2-positive tumors.

Higher underestimation of tumour size post-neoadjuvant chemotherapy with breast magnetic resonance imaging (MRI)-A concordance comparison cohort analysis

Objectives

The aim of this study was to evaluate the diagnostic accuracy of breast MRI for detecting residual tumor and the tumor size whether it would be affected after neoadjuvant chemotherapy.

Methods

Total 109 patients with NAC and 682 patients without NAC were included in this retrospective study. Measurement of the largest diameter of tumors at pathology was chosen as gold standard and compared with preoperative breast MRI. A concordance threshold of ±25% of maximal tumor size was used. The accuracy of MRI was graded as concordant, underestimation, or overestimation rate. Further subgroup analysis with tumor stages, histologic subgroups and intrinsic subtypes was performed.

Results

The post-NAC MRI was associated with 92.5% sensitivity, 55.2% specificity, 85.1% positive predictive value, 72.7% negative predictive value, and overall 82.6% accuracy for detecting residual tumor. In determining tumor size, the overall concordance rates of the non-NAC group and the NAC group were 43.5% and 41.3%, respectively (p = 0.678). But the overestimation rate and underestimation rate were 26.6% and 32.1% for NAC group, and 52.9% and 3.5% for the non-NAC group (p<0.001). While in the subgroups analysis, the concordance rate of the NAC group (26.7%) was lower than that of the non-NAC group (82.1%) at T3 stage (p<0.001). There were no statistically significant differences between different tumor histologic subgroups and intrinsic subtypes.

Conclusions

The overall accuracy of MRI in predicting tumor size was not affected by NAC; however, it tends to underestimate tumor size after NAC, especially in patients with T3 lesions and above.

The Role of Neutrophil-lymphocyte Ratio and Platelet-lymphocyte Ratio in Predicting Neoadjuvant Chemotherapy Response in Breast Cancer

Purpose

The role of the host immunologic environment is crucial in cancer progression. Recent studies revealed that neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR), are possible surrogate markers of outcome in various cancers. In breast cancer, the therapeutic effect of neoadjuvant chemotherapy (NAC) differs in patients, and higher response rate reflects better outcomes. This study aimed to determine the predictive value of peripheral blood NLR and PLR for NAC response along with their prognostic role in breast cancer.

Method

A total of 105 patients with breast cancer treated with NAC between 2009 and 2017 were analyzed retrospectively. NAC response and prognosis (disease-free-survival [DFS], progression-free-survival [PFS] and overall survival [OS]) according to NLR and PLR were evaluated. According to the optimal cut-off values for NAC response obtained from receiver operating characteristic (ROC) curves, patients satisfying both low NLR and PLR levels (low-ratio group) were compared to those who did not (high-ratio group).

Results

The NLR cut-off value was ≤ 2.21 (area under the ROC curve [AUC], 0.617; 95% confidence interval [CI], 0.517–0.710; p=0.030) with 94.1% sensitivity and 38.0% specificity. The PLR cut-off value was ≤ 143.36 (AUC, 0.618; 95% CI, 0.518–0.711; p = 0.040) with 85.3% sensitivity and 39.4% specificity. The low-ratio group demonstrated a better NAC response (p = 0.006) in multivariate analysis than the high-ratio group. The low-ratio group showed better DFS and PFS (p = 0.046 and p = 0.040, respectively) and longer OS (p = 0.078) in univariate survival analysis than the high-ratio group. In multivariate analysis, the low-ratio group had significantly better PFS (p = 0.049) and higher DFS (p = 0.054) than the high-ratio group.

Conclusions

The combination of NLR and PLR showed improved prediction of NAC response, revealing their potential as screening tools, significant prognostic role in breast cancer patients who receive NAC. Further studies with subgroup analysis, larger population and longer follow up duration are required.

Neoadjuvant chemotherapy in non-metastatic breast cancer: a study on practice trends in a regional cancer treatment service

BACKGROUND

Neoadjuvant chemotherapy (NACT) is increasingly used for managing locally advanced and high risk non-metastatic breast cancer.

AIMS

To describe trends in NACT use, assess compliance to best practice recommendations and determine treatment response rates in a regional cancer treatment service.

METHODS

In this retrospective cross- sectional study, electronic records of patients who underwent NACT in centres covered by the MidCentral Regional Cancer Treatment Service in 2013 and 2017 were reviewed. Data pertaining to patient demographics, disease status, compliance to best practice recommendations and treatment outcomes were extracted and analysed.

RESULTS

Of a total of 502 referrals for non-metastatic breast cancer, 34 underwent NACT with the estimated NACT rate rising from 3.85% (2013) to 9.92% (2017). Compliance to practice recommendations improved in all domains (pre-treatment tumour and axillary evaluation, marker placement, multidisciplinary discussion). Overall, NACT was well tolerated with only three patients experiencing treatment limiting toxicity. Response rates mirror published data (complete response: 29.4%, partial: 61.8%) with higher responses registered in HER2 positive and triple negative subtypes. Discordance between radiological and pathological response was 28%, with imaging overestimating response in five out of seven cases. Of the 11 (32%) patients who initially underwent breast conserving surgery, six required a second surgery.

CONCLUSION

NACT is increasingly used in the Regional Cancer Treatment Service, with improving compliance to practice recommendations. These results are reassuring and can be used to help patients develop a realistic expectation towards NACT.

Early Prediction of Response to Neoadjuvant Chemotherapy Using Dynamic Contrast-Enhanced MRI and Ultrasound in Breast Cancer

Objective

To determine the diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and DCE ultrasound (DCE-US) for predicting response to neoadjuvant chemotherapy (NAC) in breast cancer patients.

Materials and Methods

This Institutional Review Board-approved prospective study was performed between 2014 and 2016. Thirty-nine women with breast cancer underwent DCE-US and DCE-MRI before the NAC, follow-up DCE-US after the first cycle of NAC, and follow-up DCE-MRI after the second cycle of NAC. DCE-MRI parameters (transfer constant [K_trans], reverse constant [k_ep], and leakage space [V_e]) were assessed with histograms. From DCE-US, peak-enhancement, the area under the curve, wash-in rate, wash-out rate, time to peak, and rise time (RT) were obtained. After surgery, all the imaging parameters and their changes were compared with histopathologic response using the Miller-Payne Grading (MPG) system. Data from minor and good responders were compared using Wilcoxon rank sum test, chi-square test, or Fisher's exact test. Receiver operating characteristic curve analysis was used for assessing diagnostic performance to predict good response.

Results

Twelve patients (30.8%) showed a good response (MPG 4 or 5) and 27 (69.2%) showed a minor response (MPG 1–3). The mean, 25th, 50th, and 75th percentiles of K_trans and K_ep of post-NAC DCE-MRI differed between the two groups. These parameters showed fair to good diagnostic performance for the prediction of response to NAC (AUC 0.76–0.81, p ≤ 0.007). Among DCE-US parameters, the percentage change in RT showed fair prediction (AUC 0.71, p = 0.023).

Conclusion

Quantitative analysis of DCE-MRI and DCE-US was helpful for early prediction of response to NAC.

Outcomes of neoadjuvant and adjuvant chemotherapy in stage 2 and 3 non-small cell lung cancer: an analysis of the National Cancer Database

Introduction

The current recommendation for the treatment of stage II and III NSCLC is surgery with chemotherapy. While the convention is to administer chemotherapy postoperatively (adjuvant chemotherapy), inconsistent results have been reported regarding the administration of chemotherapy preoperatively (neoadjuvant chemotherapy). Therefore, a comprehensive analysis of neoadjuvant chemotherapy use in NSCLC is needed.

Results

Of the 35,134 NSCLC patients identified, 18,684 received surgery alone, 1,154 received surgery with neoadjuvant chemotherapy, and 15,296 received surgery with adjuvant chemotherapy. Race, Charlson-Deyo score, facility type, insurance type and stage of disease are associated with the use of neoadjuvant chemotherapy. In the case of stage II disease, adjuvant chemotherapy showed improved survival (median OS = 80.8 months) over neoadjuvant chemotherapy (OS = 67.0 months) and surgery alone (OS = 51.0 months). For stage III disease, adjuvant chemotherapy (OS = 49.0 months) showed improved survival over surgery alone (OS = 24.3 months), followed by neoadjuvant chemotherapy (OS = 42.0 months). After propensity score matching, adjuvant chemotherapy was found to provide a survival advantage over neoadjuvant in both stage II (HR = 0.70; p = 5.8e-3) and stage III (HR = 0.77; p = 0.011) NSCLC.

Conclusions

Our analysis finds a survival advantage for neoadjuvant chemotherapy when compared to surgery alone, but no advantage compared to adjuvant chemotherapy in the treatment of resectable stage II and III NSCLC.

Methods

The National Cancer Database (NCDB) was queried for all cases of stage II and III NSCLC from 2006 to 2012. These patients were stratified by stage, and the factors affecting use of neoadjuvant chemotherapy and the effects of neoadjuvant versus adjuvant chemotherapy on overall survival (OS) were investigated.

Automatic cellularity assessment from post-treated breast surgical specimens

Neoadjuvant treatment (NAT) of breast cancer (BCa) is an option for patients with the locally advanced disease. It has been compared with standard adjuvant therapy with the aim of improving prognosis and surgical outcome. Moreover, the response of the tumor to the therapy provides useful information for patient management. The pathological examination of the tissue sections after surgery is the gold-standard to estimate the residual tumor and the assessment of cellularity is an important component of tumor burden assessment. In the current clinical practice, tumor cellularity is manually estimated by pathologists on hematoxylin and eosin (H&E) stained slides, the quality, and reliability of which might be impaired by inter-observer variability which potentially affects prognostic power assessment in NAT trials. This procedure is also qualitative and time-consuming. In this paper, we describe a method of automatically assessing cellularity. A pipeline to automatically segment nuclei figures and estimate residual cancer cellularity from within patches and whole slide images (WSIs) of BCa was developed. We have compared the performance of our proposed pipeline in estimating residual cancer cellularity with that of two expert pathologists. We found an intra-class agreement coefficient (ICC) of 0.89 (95% CI of [0.70, 0.95]) between pathologists, 0.74 (95% CI of [0.70, 0.77]) between pathologist #1 and proposed method, and 0.75 (95% CI of [0.71, 0.79]) between pathologist #2 and proposed method. We have also successfully applied our proposed technique on a WSI to locate areas with high concentration of residual cancer. The main advantage of our approach is that it is fully automatic and can be used to find areas with high cellularity in WSIs. This provides a first step in developing an automatic technique for post-NAT tumor response assessment from pathology slides. © 2017 International Society for Advancement of Cytometry.

The importance of tissue confirmation of metastatic disease in patients with breast cancer: lesson from a brain metastasis case

Background

The discrepancy of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) statuses in breast cancers has been reported. Available systemic therapy for patients with breast cancer is based on the molecular subtypes as identified by IHC and/or FISH. However, these biomarkers may change throughout tumor progression.

Case presentation

We report a relatively uncommon case of a 39-year-old Chinese woman with local advanced breast cancer (LABC) treated with 6 cycles of docetaxel, doxorubicin and cyclophosphamide (TAC) regimen neoadjuvant chemotherapy, and subsequently mastectomy, intensity-modulated radiation therapy (IMRT) and tamoxifen followed as regularly. Brain metastatic event appeared in 6 months after mastectomy. Treatment for brain metastasis was surgical resection and followed by whole brain radiotherapy (WBRT) approved by multidisciplinary team (MDT). Initial pathological diagnosis was IDC, cT4N1M0, luminal B (ER+ 90%, PR+90%, HER2 0, Ki67+ 70%) based on ultrasound-guided core needle biopsy. Surgical pathology revealed IDC, pT2N3M0 luminal B (ER+ 20%, PR+20%, HER2 0, Ki67+ 20%). Histological response to neoadjuvant chemotherapy is grade 3 according to the Miller/Payne grading system. Final pathology of brain metastasis showed a HER2 overexpression metastatic breast cancer luminal B (ER+ 70%, PR+ 70%, HER2 2+, Ki67+ 30%), FISH confirmed HER2 overexpression. Weekly paclitaxel plus trastuzumab was given for 12 weeks, then trastuzumab every 3 weeks for a whole year. Patient follow-up is still ongoing, no new events appear yet.

Conclusions

The determination of hormone receptors and HER2 status should be routinely performed in all involved tissues, if possible, and systemic therapy should be tailored following the latest finding.