Immunohistochemical surrogate markers of breast cancer molecular classes predicts response to neoadjuvant chemotherapy: a single institutional experience with 359 cases

Public neoantigens in breast cancer immunotherapy (Review)

Among women globally, breast cancer is the most prevalent cancer and the leading cause of cancer‑related death. Interestingly, though genetic mutations contribute to the disease, <15% of women diagnosed with breast cancer have a family history of the disease, suggesting a prevalence of sporadic genetic mutations in breast cancer development. In the rapidly rising field of cancer genomics, neoantigen‑based immunotherapy has come to the fore. The investigation of novel proteins arising from unique somatic mutations or neoantigens have opened a new pathway for both individualized and public cancer treatments. Because they are shared among individuals with similar genetic changes, public neoantigens provide an opportunity for 'off‑the‑shelf' anticancer therapies, potentially extending the benefits to a wider patient group. The present review aimed to highlight the role of shared or public neoantigens as therapeutic targets for patients with breast cancer, emphasizing common hotspot mutations of certain genes identified in breast cancer. The clinical utilization of public neoantigen‑based therapies for breast cancer treatment were also discussed.

Develop and Validate a Nomogram Combining Contrast-Enhanced Spectral Mammography Deep Learning with Clinical-Pathological Features to Predict Neoadjuvant Chemotherapy Response in Patients with ER-Positive/HER2-Negative Breast Cancer

RATIONALE AND OBJECTIVES

To develop and validate a nomogram that combines contrast-enhanced spectral mammography (CESM) deep learning with clinical-pathological features to predict neoadjuvant chemotherapy (NAC) response (either low Miller Payne (MP-L) grades 1-2 or high MP (MP-H) grades 3-5) in patients with ER-positive/HER2-negative breast cancer.

MATERIALS AND METHODS

In this retrospective study, 265 breast cancer patients were randomly allocated into training and test sets (used for models training and testing, respectively) at a 4:1 ratio. Deep learning models, based on the pre-trained ResNet34 model and initially fine-tuned for identifying breast cancer, were trained using low-energy and subtracted CESM images. The predicted results served as deep learning features for the deep learning-based model. Clinical-pathological features, including age, progesterone receptor (PR) status, estrogen receptor (ER) status, Ki67 expression levels, and neutrophil-to-lymphocyte ratio, were used for the clinical model. All these features contributed to the nomogram. Feature selection was performed through univariate analysis. Logistic regression models were developed and chosen using a stepwise selection method. The deep learning-based and clinical models, along with the nomogram, were evaluated using precision-recall curves, receiver operating characteristic (ROC) curves, specificity, recall, accuracy, negative predictive value, positive predictive value (PPV), balanced accuracy, F1-score, and decision curve analysis (DCA).

RESULTS

The nomogram demonstrated considerable predictive ability, with higher area under the ROC curve (0.95, P < 0.05), accuracy (0.94), specificity (0.98), PPV (0.89), and precision (0.89) compared to the deep learning-based and clinical models. In DCA, the nomogram showed substantial clinical value in assisting breast cancer treatment decisions, exhibiting a higher net benefit than the other models.

CONCLUSION

The nomogram, integrating CESM deep learning with clinical-pathological features, proved valuable for predicting NAC response in patients with ER-positive/HER2-negative breast cancer. Nomogram outperformed deep learning-based and clinical models.

Prognostic Importance of Axillary Lymph Node Response to Neoadjuvant Systemic Therapy on Axillary Surgery in Breast Cancer-A Single Center Experience

Neoadjuvant systemic treatment (NST) is the standard treatment for HER2+, triple-negative (TN), and highly proliferative luminal HER2- early breast cancer. Pathologic complete response (pCR) after NST is associated with improved outcomes. We evaluated the predictive factors for axillary-pCR (AXpCR) and its impact on the extent of axillary node surgery. This retrospective study included 92 patients (median age of 50.4 years) with an initially node-positive disease. Patients were treated with molecular subtype-specific NST (4.3% were luminal A-like, 28.3% luminal HER2-, 26.1% luminal HER2+, 18.5% HER2+ non-luminal, and 22.8% TN). Axillary-, breast- and total-pCR were achieved in 52.2%, 48.9%, and 38% of patients, respectively. In a binary logistic regression model for the whole population, the only independent factor significantly associated with AXpCR was breast-pCR (OR 7.4; 95% CI 2.6-20.9; p < 0.001). In patients who achieved breast-pCR, aggressive subtypes (HER2+ and TN; OR 11.24) and clinical tumor stage (OR 0.10) had a significant impact on achieving AXpCR. Axillary lymph node dissection was avoided in 53.3% of patients. In conclusion, in node-positive patients with HER2+ and TN subtypes, who achieved breast-pCR after NST, de-escalation of axillary surgery could be considered in most cases.

Comparison of neoadjuvant chemotherapy response and prognosis between HR-low/HER2-negative BC and TNBC: an exploratory real-world multicentre cohort study

Objective

Hormone receptor (HR)-low/HER2-negative breast cancers (BCs) are more likely to be basal-like BCs, with similar molecular features and gene expression profiles to HR-negative (estrogen receptor <1% or negative and progesterone receptor <1% or negative) BCs. Recently, with the clinical application of adjuvant intensive therapy for triple-negative breast cancer (TNBC), the prognosis of TNBC patients without pathological complete response (pCR) has significantly improved. Therefore, it is necessary to reanalyse the prognostic characteristics of clinically high-risk HR-low/HER2-negative BC.

Methods

According to the inclusion and exclusion standards, 288 patients with HR-low/HER2-negative BC and TNBC who received NAC and were followed up between 2015 and 2022 at three breast centres in Hunan Province, China, were enrolled. Inverse probability of treatment weighting (IPTW) was utilized to mitigate imbalances in baseline characteristics between the HR-low/HER2-negative BC group and TNBC group regarding event-free survival (EFS) and overall survival (OS). The primary clinical endpoints were pCR and EFS, while the secondary endpoints included OS, objective response rate (ORR), and clinical benefit rate (CBR).

Results

The pCR rate (27.1% vs. 28.0%, P = 1.000), ORR rate (76.9% vs. 78.3%, P = 0.827) and CBR rate (89.7% vs. 96.5%, P = 0.113) after NAC were similar between the HR-low/HER2-negative BC and the TNBC group. EFS in patients with non-pCR from the 2 groups was significantly inferior in comparison to patients with pCR (P = 0.001), and the 3-year EFS was 94.74% (95% CI = 85.21% to 100.00%) and 57.39% (95% CI =43.81% to 75.19%) in patients with pCR and non-pCR from the HR-low/HER2-negative BC group, respectively, and 89.70% (95% CI = 82.20% to 97.90%) and 69.73% (95% CI = 62.51% to 77.77%) in the TNBC patients with pCR and non-pCR, respectively.

Conclusions

In the real world, the therapeutic effects of NAC for HR-low/HER2-negative BCs and TNBCs were similar. EFS of patients with non-pCR in the HR-low/HER2-negative BC group was inferior to that of the TNBC group with non-pCR, suggesting that it is necessary to explore new adjuvant intensive therapy strategies for these patients.

Immunoexpression of HER2 pathway related markers in HER2 invasive breast carcinomas treated with trastuzumab

PURPOSE

We evaluated the immunoexpression of potential markers involved in the HER2 pathway in invasive breast carcinoma with HER2 amplification treated with trastuzumab.

METHODS

Samples of ninety patients diagnosed and treated at two public Brazilian hospitals with overexpressed invasive carcinoma between 2009 and 2018 were included. Several markers (Bcl-2, CDK4, cyclin D1, EGFR, IGF1, IGF-1R, MDM2, MUC4, p16, p21, p27, p53, PTEN, RA, TNFα, and VEGF) were immune analyzed in the tumor by immunohistochemistry and then correlated with clinicopathological variables.

RESULTS

Tumor sample expression results determined potential markers of good prognosis with statistically significant values: cyclin D1 with a nuclear grade, and recurrence; IGF-1 with tumor size, and death; p16 with a response after treatment; PTEN with a response after treatment, and death. Markers of poor prognosis: p53 with histological, and nuclear grade; IGF-1R with a compromised lymph node. The treatment resistance rate after trastuzumab was 40%; the overall survival was 4.13 years (95% CI 5.1-12.5) and the disease-free survival was 3.6 years (95% CI 5.1-13.1).

CONCLUSIONS

The tumor samples profile demonstrated that cyclin D1, IGF-1, p16, and PTEN presented the potential for a good prognosis and p53 and IGF-1R for worse.

Relationship between pathological response and molecular subtypes in locally advanced breast cancer patients receiving neoadjuvant chemotherapy

Majority of patients with breast cancer were diagnosed with locally advanced stages of the disease (54%). This study aimed to explain the pathological response received to neoadjuvant chemotherapy (NACT) according to the molecular classification of breast cancer in patients with locally advanced tumors. One hundred and one patients with locally advanced breast cancer treated with neoadjuvant chemotherapy were analyzed. Patients were classified into five molecular subtypes based on the profile of the estrogen receptor, progesterone receptor, HER2, and Ki-67. We determined associations between complete pathological response (no invasive tumor after neoadjuvant chemotherapy) and molecular subgroups. Most patients had luminal A tumors (n: 28, 27.7%). The overall rate of complete pathological response (pCR) was 34.7% (n:35). Tumors that presented with the highest rate of pCR were pure HER2-positive, at 60% (n:6; OR, 3.2; 95% CI, 0.8-12.2). According to logistic regression analysis, the factors affecting pCR were HER2 positivity and clinically positive axilla before NACT. Luminal A tumors had a significantly lower pCR rate. (7.1%,p: 0.001). Despite the low pCR rate, Luminal A tumor had the best survival rate in the subgroups (p < 0.001). However, there was no difference between EFS and OS according to pCR in any molecular subgroups. Pathological complete response is directly related to the subtypes of breast cancer. A high complete pathological response rate is observed in the pure HER2-positive group. However, EFS and OS were not statistically significant in patients with and without pCR.

Changes in the tumor oxygenation but not in the tumor volume and tumor vascularization reflect early response of breast cancer to neoadjuvant chemotherapy

BACKGROUND

Breast cancer neoadjuvant chemotherapy (NACT) allows for assessing tumor sensitivity to systemic treatment, planning adjuvant treatment and follow-up. However, a sufficiently large number of patients fail to achieve the desired level of pathological tumor response while optimal early response assessment methods have not been established now. In our study, we simultaneously assessed the early chemotherapy-induced changes in the tumor volume by ultrasound (US), the tumor oxygenation by diffuse optical spectroscopy imaging (DOSI), and the state of the tumor vascular bed by Doppler US to elaborate the predictive criteria of breast tumor response to treatment.

METHODS

A total of 133 patients with a confirmed diagnosis of invasive breast cancer stage II to III admitted to NACT following definitive breast surgery were enrolled, of those 103 were included in the final analysis. Tumor oxygenation by DOSI, tumor volume by US, and tumor vascularization by Doppler US were determined before the first and second cycle of NACT. After NACT completion, patients underwent surgery followed by pathological examination and assessment of the pathological tumor response. On the basis of these, data regression predictive models were created.

RESULTS

We observed changes in all three parameters 3 weeks after the start of the treatment. However, a high predictive potential for early assessment of tumor sensitivity to NACT demonstrated only the level of oxygenation, ΔStO₂, (ρ = 0.802, p ≤ 0.01). The regression model predicts the tumor response with a high probability of a correct conclusion (89.3%). The "Tumor volume" model and the "Vascularization index" model did not accurately predict the absence of a pathological tumor response to treatment (60.9% and 58.7%, respectively), while predicting a positive response to treatment was relatively better (78.9% and 75.4%, respectively).

CONCLUSIONS

Diffuse optical spectroscopy imaging appeared to be a robust tool for early predicting breast cancer response to chemotherapy. It may help identify patients who need additional molecular genetic study of the tumor in order to find the source of resistance to treatment, as well as to correct the treatment regimen.

A framework for deep multitask learning with multiparametric magnetic resonance imaging for the joint prediction of histological characteristics in breast cancer

The clinical management and decision-making process related to breast cancer are based on multiple histological indicators. This study aims to jointly predict the Ki-67 expression level, luminal A subtype and histological grade molecular biomarkers using a new deep multitask learning method with multiparametric magnetic resonance imaging. A multitask learning network structure was proposed by introducing a common-task layer and task-specific layers to learn the high-level features that are common to all tasks and related to a specific task, respectively. A network pretrained with knowledge from the ImageNet dataset was used and fine-tuned with MRI data. Information from multiparametric MR images was fused using the strategy at the feature and decision levels. The area under the receiver operating characteristic curve (AUC) was used to measure model performance. For single-task learning using a single image series, the deep learning model generated AUCs of 0.752, 0.722, and 0.596 for the Ki-67, luminal A and histological grade prediction tasks, respectively. The performance was improved by freezing the first 5 convolutional layers, using 20% shared layers and fusing multiparametric series at the feature level, which achieved AUCs of 0.819, 0.799 and 0.747 for Ki-67, luminal A and histological grade prediction tasks, respectively. Our study showed advantages in jointly predicting correlated clinical biomarkers using a deep multitask learning framework with an appropriate number of fine-tuned convolutional layers by taking full advantage of common and complementary imaging features. Multiparametric image series-based multitask learning could be a promising approach for the multiple clinical indicator-based management of breast cancer.

A deep matrix completion method for imputing missing histological data in breast cancer by integrating DCE-MRI radiomics

PURPOSE

Clinical indicators of histological information are important for breast cancer treatment and operational decision making, but these histological data suffer from frequent missing values due to various experimental/clinical reasons. The limited amount of histological information from breast cancer samples impedes the accuracy of data imputation. The purpose of this study was to impute missing histological data, including Ki-67 expression level, luminal A subtype, and histological grade, by integrating tumor radiomics.

METHODS

To this end, a deep matrix completion (DMC) method was proposed for imputing missing histological data using nonmissing features composed of histological and tumor radiomics (termed radiohistological features). DMC finds a latent nonlinear association between radiohistological features across all samples and samples for all the features. Radiomic features of morphologic, statistical, and texture were extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) inside the tumor. Experiments on missing histological data imputation were performed with a variable number of features and missing data rates. The performance of the DMC method was compared with those of the nonnegative matrix factorization (NMF) and collaborative filtering (MCF)-based data imputation methods. The area under the curve (AUC) was used to assess the performance of missing histological data imputation.

RESULTS

By integrating radiomics from DCE-MRI, the DMC method showed significantly better performance in terms of AUC than that using only histological data. Additionally, DMC using 120 radiomic features showed an optimal prediction performance (AUC = 0.793), which was better than the NMF (AUC = 0.756) and MCF methods (AUC = 0.706; corrected p = 0.001). The DMC method consistently performed better than the NMF and MCF methods with a variable number of radiomic features and missing data rates.

CONCLUSIONS

DMC improves imputation performance by integrating tumor histological and radiomics data. This study transforms latent imaging-scale patterns for interactions with molecular-scale histological information and is promising in the tumor characterization and management of patients.

VGH-TAYLOR: Comprehensive precision medicine study protocol on the heterogeneity of Taiwanese breast cancer patients

Heterogeneity in breast cancer leads to diverse morphological features and different clinical outcomes. There are inherent differences in breast cancer between the populations in Asia and in western countries. The use of immune-based treatment in breast cancer is currently in the developmental stage. The VGH-TAYLOR study is designed to understand the genetic profiling of different subtypes of breast cancer in Taiwan and define the molecular risk factors for breast cancer recurrence. The T-cell receptor repertoire and the potential effects of immunotherapy in breast cancer subjects is evaluated. The favorable biomarkers for early detection of tumor recurrence, diagnosis and prognosis may provide clues for the selection of individualized treatment regimens and improvement in breast cancer therapy.

Evaluation of molecular markers GSTM1 and GSTT1 and clinical factors in breast cancer: case-control study and literature review

The study was conducted to evaluate the frequency of polymorphisms in GSTM1 and GSTT1 genes in patients with breast cancer compared with individuals without history of cancer, and the association of these polymorphisms with clinical/epidemiological parameters.There were evaluated 752 women (219 patients and 533 controls). Molecular analysis was performed by the Polymerase Chain Reaction (PCR). Statistical analysis was used multiple logistic regression and descriptive statistics.Age ≥50 years (OR =3.22, 95% CI =2.30 - 4.51, p <0.001) and alcohol consumption (OR =1.60, 95% CI =1.13 - 2.27, p = 0.008) were associated to the development of breast cancer, while smoking and null genotypes GSTM1 and GSTT1 presented no association. GSTM1 and GSTT1 polymorphisms presented no relationship with the clinical and histopathological parameters or molecular subtypes of breast cancer. Ninety-two percent of tumors were invasive ductal, 66% were grade II, 65% were larger than 2 cm, the stages II (35.3%) and III (31.2%) were the most prevalent, and 47.7% were molecular subtype luminal B.Individuals aged ≥50 years and alcohol consumers have more chance to developing breast cancer. GSTM1 and GSTT1 polymorphisms are not associated to the risk of breast cancer.

Analysis of RPL37A, MTSS1, and HTRA1 expression as potential markers for pathologic complete response and survival

BACKGROUND

Non-metastatic locally advanced breast carcinoma (LABC) treatment involves neoadjuvant chemotherapy (NCT). We evaluated the association of clinical-pathological data and immunoexpression of hormone receptors, HER2 and Ki67, and new biomarkers, RPL37A, MTSS1 and HTRA1, with pathological complete response (PCR) or tumour resistance (stable disease or disease progression), disease-free survival (DFS) and cancer-specific survival (CSS).

METHODS

This is a retrospective study of 333 patients with LABC who underwent NCT. Expression of MTSS1, RPL37A and HTRA1/PRSS11 was evaluated by immunohistochemistry in TMA slides. Cutoff values were established for low and high tumour expression. ROC plotter evaluated response to NCT. Chi-square test for factors related to PCR, and Kaplan-Meier test and Cox model for factors related to DFS and CSS were prformed.

RESULTS

The mean follow-up was 70.0 months and PCR rate was 15.6%. At 120 months, DFS rate was 32.5% and CSS rate was 67.1%. In multivariate analysis, there was an association between: (1) necrosis presence, intense inflammatory infiltrate, ER absence, HER2 molecular subtype and high RPL3A expression with increased odds of PCR; (2) lymph node involvement (LNI), high Ki67, low RPL37A and high HTRA1 expression with increased risk for NCT non-response; (3) LNI, high proliferation, necrosis absence, low RPL37A and high HTRA1 expression with increased recurrence risk; (4) advanced LNI, ER negative tumours, high HTRA1, low RPL37A expression and desmoplasia presence with higher risk of cancer death.

CONCLUSION

RPL37A is a potential biomarker for response to NCT and for prognosis. Additional studies evaluating HTRA1 and MTSS1 prognostic value are needed.

Utility of 18F-FDG PET/CT for predicting pathologic complete response in hormone receptor-positive, HER2-negative breast cancer patients receiving neoadjuvant chemotherapy

Background

Pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) is a predictor of improved outcomes in breast cancer. In patients with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2) -negative breast cancer, the response to NAC is variable and mostly limited. This study was an investigation of the predictive relevance of parameters of ¹⁸F-FDG PET/CT for the pCR to NAC in patients with HR-positive, HER2–negative breast cancer. Methods: AH total of 109 consecutive HR-positive and HER2-negative breast cancer patients who were treated with NAC were enrolled in this prospective cohort study. The relationships between pretreatment ¹⁸F-FDG PET/CT and clinical outcomes including pathologic response to NAC were evaluated. Results: All patients finished their planned NAC cycles and eight patients (7.3%) achieved pCR. In the receiver operating characteristic (ROC) curve analysis, pSUVmax exhibited high sensitivity and specificity for predicting pCR. Furthermore, multivariate logistic regression analysis revealed pSUVmax as a predictive factor for pCR (hazard ratio = 17.452; 95% CI = 1.847–164.892; p = 0.013).

Conclusion

The results of this study suggest that ¹⁸F-FDG PET/CT pSUVmax is a predictive factor for pCR of HR-positive, HER2-negative breast cancer to NAC.

Current Landscape of Breast Cancer Imaging and Potential Quantitative Imaging Markers of Response in ER-Positive Breast Cancers Treated with Neoadjuvant Therapy

In recent years, neoadjuvant treatment trials have shown that breast cancer subtypes identified on the basis of genomic and/or molecular signatures exhibit different response rates and recurrence outcomes, with the implication that subtype-specific treatment approaches are needed. Estrogen receptor-positive (ER+) breast cancers present a unique set of challenges for determining optimal neoadjuvant treatment approaches. There is increased recognition that not all ER+ breast cancers benefit from chemotherapy, and that there may be a subset of ER+ breast cancers that can be treated effectively using endocrine therapies alone. With this uncertainty, there is a need to improve the assessment and to optimize the treatment of ER+ breast cancers. While pathology-based markers offer a snapshot of tumor response to neoadjuvant therapy, non-invasive imaging of the ER disease in response to treatment would provide broader insights into tumor heterogeneity, ER biology, and the timing of surrogate endpoint measurements. In this review, we provide an overview of the current landscape of breast imaging in neoadjuvant studies and highlight the technological advances in each imaging modality. We then further examine some potential imaging markers for neoadjuvant treatment response in ER+ breast cancers.

CAIX is a predictor of pathological complete response and is associated with higher survival in locally advanced breast cancer submitted to neoadjuvant chemotherapy

BACKGROUND

Locally advanced breast cancer often undergoes neoadjuvant chemotherapy (NAC), which allows in vivo evaluation of the therapeutic response. The determination of the pathological complete response (pCR) is one way to evaluate the response to neoadjuvant chemotherapy. However, the rate of pCR differs significantly between molecular subtypes and the cause is not yet determined. Recently, the metabolic reprogramming of cancer cells and its implications for tumor growth and dissemination has gained increasing prominence and could contribute to a better understanding of NAC. Thus, this study proposed to evaluate the expression of metabolism-related proteins and its association with pCR and survival rates.

METHODS

The expression of monocarboxylate transporters 1 and 4 (MCT1 and MCT4, respectively), cluster of differentiation 147 (CD147), glucose transporter-1 (GLUT1) and carbonic anhydrase IX (CAIX) was analyzed in 196 locally advanced breast cancer samples prior to NAC. The results were associated with clinical-pathological characteristics, occurrence of pCR, disease-free survival (DFS), disease-specific survival (DSS) and overall survival (OS).

RESULTS

The occurrence of pCR was higher in the group of patients whith tumors expressing GLUT1 and CAIX than in the group without expression (27.8% versus 13.1%, p = 0.030 and 46.2% versus 13.5%, p = 0.007, respectively). Together with regional lymph nodes staging and mitotic staging, CAIX expression was considered an independent predictor of pCR. In addition, CAIX expression was associated with DFS and DSS (p = 0.005 and p = 0.012, respectively).

CONCLUSIONS

CAIX expression was a predictor of pCR and was associated with higher DFS and DSS in locally advanced breast cancer patients subjected to NAC.

Risk stratification of triple-negative breast cancer with core gene signatures associated with chemoresponse and prognosis

PURPOSE

Neoadjuvant chemotherapy studies have consistently reported a strong correlation between pathologic response and long-term outcome in triple-negative breast cancer (TNBC). We aimed to define minimal gene signatures for predicting chemoresponse by a three-step approach and to further develop a risk-stratification method of TNBC.

METHODS

The first step involved the detection of genes associated with resistance to docetaxel in eight TNBC cell lines, leading to identification of thousands of candidate genes. Through subsequent second and third step analyses with gene set enrichment analysis and survival analysis using public expression profiles, the candidate gene list was reduced to prognostic core gene signatures comprising ten or four genes.

RESULTS

The prognostic core gene signatures include three up-regulated (CEBPD, MMP20, and WLS) and seven down-regulated genes (ASF1A, ASPSCR1, CHAF1B, DNMT1, GINS2, GOLGA2P5, and SKA1). We further develop a simple risk-stratification method based on expression profiles of the core genes. Relative expression values of the up-regulated and down-regulated core genes were averaged into two scores, Up and Down scores, respectively; then samples were stratified by a diagonal line in a xy plot of the Up and Down scores. Based on this method, the patients were successfully divided into subgroups with distinct chemoresponse and prognosis. The prognostic power of the method was validated in three independent public datasets containing 230, 141, and 117 TNBC patients with chemotherapy. In multivariable Cox regression analysis, the core gene signatures were significantly associated with prognosis independent of tumor stage and age at diagnosis. In meta-analysis, we found that five core genes (CEBPD, WLS, CHAF1B, GINS2, and SKA1) play opposing roles, either tumor promoter or suppressor, in TNBC and non-TNBC tumors respectively, depending on estrogen receptor status.

CONCLUSIONS

The results may provide a promising prognostic tool for predicting chemotherapy responders among TNBC patients prior to initiation of chemotherapeutic treatment.

Association of ki67 and tumor marker p53 in locally advanced breast cancer patients and evaluation of response to neoadjuvant chemotherapy: a survey in South Iran

Purpose

Heterogeneity of breast cancer, the most common cancer in women, complicates approach to its treatment. Neoadjuvant chemotherapy (NAC) in the treatment of locally advanced breast cancer (LABC) with the endpoint of achieving pathologic complete response (pCR) is not always successful. The purpose of this study was to evaluate the clinicopathologic characteristics, biomarker status and response of LABCs to NAC.

Patients and methods

Core biopsies and post-surgical specimens of LABC patients were evaluated after receiving NAC. Their lymph node involvement, tumor staging, grading, size, tumoral and stromal lymphocytic infiltration (TLI, SLI), hormonal status, ki67, p53 and HER2 expression were evaluated. Response to NAC was assessed using pCR, Miller-Payne grading and residual cancer burden.

Results

In a total of 71 patients, pCR rate was 5.6%. Strong association was observed between ki67 positivity and p53 expression (P-value˂0.001). Also ki67, TLI and SLI showed association with triple negative tumor subtype (P-value 0.011, 0.002 and 0.014). Good response to NAC was associated with p53 expression. Nodal metastatic residue was also associated with primary tumor’s nuclear grade.

Conclusion

Strong correlation of ki67 and p53 can suggest probable interchangeability of both markers in the prognosis of LABC. In this study p53 even showed superiority to ki67 having association with good response. Strong association of ki67, TLI and SLI with triple negative tumor subtype can be parallel to an overall better response rate of this subtype. We can also propose the effectiveness of defining nuclear grade as a prognostic factor towards residual lymph node involvement post NAC.

Schlafen-11 expression is associated with immune signatures and basal-like phenotype in breast cancer

PURPOSE

Breast cancer (BC) is a heterogeneous disorder, with variable response to systemic chemotherapy. Likewise, BC shows highly complex immune activation patterns, only in part reflecting classical histopathological subtyping. Schlafen-11 (SLFN11) is a nuclear protein we independently described as causal factor of sensitivity to DNA damaging agents (DDA) in cancer cell line models. SLFN11 has been reported as a predictive biomarker for DDA and PARP inhibitors in human neoplasms. SLFN11 has been implicated in several immune processes such as thymocyte maturation and antiviral response through the activation of interferon signaling pathway, suggesting its potential relevance as a link between immunity and cancer. In the present work, we investigated the transcriptional landscape of SLFN11, its potential prognostic value, and the clinico-pathological associations with its variability in BC.

METHODS

We assessed SLFN11 determinants in a gene expression meta-set of 5061 breast cancer patients annotated with clinical data and multigene signatures.

RESULTS

We found that 537 transcripts are highly correlated with SLFN11, identifying "immune response", "lymphocyte activation", and "T cell activation" as top Gene Ontology processes. We established a strong association of SLFN11 with stromal signatures of basal-like phenotype and response to chemotherapy in estrogen receptor negative (ER-) BC. We identified a distinct subgroup of patients, characterized by high SLFN11 levels, ER- status, basal-like phenotype, immune activation, and younger age. Finally, we observed an independent positive predictive role for SLFN11 in BC.

CONCLUSIONS

Our findings are suggestive of a relevant role for SLFN11 in BC and its immune and molecular variability.

Machine Learning-Based Analysis of MR Multiparametric Radiomics for the Subtype Classification of Breast Cancer

Objective: To investigate whether machine learning analysis of multiparametric MR radiomics can help classify immunohistochemical (IHC) subtypes of breast cancer.

Study design: One hundred and thirty-four consecutive patients with pathologically-proven invasive ductal carcinoma were retrospectively analyzed. A total of 2,498 features were extracted from the DCE and DWI images, together with the new calculated images, including DCE images changing over six time points (DCE_sequential) and DWI images changing over three b-values (DWI_sequential). We proposed a novel two-stage feature selection method combining traditional statistics and machine learning-based methods. The accuracies of the 4-IHC classification and triple negative (TN) vs. non-TN cancers were assessed.

Results: For the 4-IHC classification task, the best accuracy of 72.4% was achieved based on linear discriminant analysis (LDA) or subspace discrimination of assembled learning in conjunction with 20 selected features, and only small dependent emphasis of Kendall-tau-b for sequential features, based on the DWI_sequential with the LDA model, yielding an accuracy of 53.7%. The linear support vector machine (SVM) and medium k-nearest neighbor using eight features yielded the highest accuracy of 91.0% for comparing TN to non-TN cancers, and the maximum variance for DWI_sequential alone, together with a linear SVM model, achieved an accuracy of 83.6%.

Conclusions: Whole-tumor radiomics on MR multiparametric images, DCE images changing over time points, and DWI images changing over different b-values provide a non-invasive analytical approach for breast cancer subtype classification and TN cancer identification.

Differential response to neoadjuvant hormonal therapy in prostate cancer: Predictive morphological parameters and molecular markers

OBJECTIVES

The predictive value of the histological parameters and molecular markers for neoadjuvant hormonal therapy (NHT) in prostate cancer (PCa) has not been well established. The aim of this study is to determine pathological variables that can predict differences in response to NHT in PCa.

METHODS

A total of 85 locally high risk PCa patients with matched preoperative needle biopsies and radical prostatectomy (RP) specimens were included. All patients were treated with NHT for at least 3 months. We quantified the response to NHT using a new proposed pathological grading system. The system classified tumors into five groups (grades 0-4) according to the severity of histological response. We then categorized the PCa patients into drug-sensitive (DS) group (Grades 2-4) and drug-resistant (DR) group (Grades 0-1). Two pathologists assessed each pretreated tumors for presence or absence of nine morphological features. The expression of androgen receptor (AR), ERG, and PTEN were evaluated by immunohistochemistry (IHC) as well. Statistical analysis was performed to identify significant associations between differentially histological response to NHT and morphological features as well as molecular aberrations. We evaluated different prediction models using receiver operating characteristic (ROC) curves and area under the ROC curve (AUC) analysis.

RESULTS

73% (n = 62/85) of tumors in our cohort belonged to DS group, whereas 27% (n = 23/85) of tumors were DR. Univariate logistic analysis suggested four pathological variables, cribriform growth pattern, macronucleoli, ductal adenocarcinoma differentiation, and PTEN loss in needle biopsies were significantly associated with DR effect, all with P-value < 0.05. Multivariate logistic regression analysis revealed that the three parameters as significant predictive factors for predicting DR effect. These were macronucleoli (RR = 4.008, P = 0.002), ductal adenocarcinoma differentiation (RR = 11.659, P = 0.009) and PTEN loss expression (RR = 7.275, P = 0.015). The AUC of three integrated indicators model was 0.781.

CONCLUSIONS

Our study suggested that the presence of tumor cribriform growth pattern, macronucleoli, ductal adenocarcinoma differentiation, and PTEN loss in needle biopsies are of value in predicting tumor response to NHT regimen. Multivariate logistic regression analysis revealed the performance of combined pathological indicators in predicting DR response was better than that of model based on individual factor alone.

Intraoperative Assessment of Sentinel Lymph Nodes in Breast Cancer Patients Post-Neoadjuvant Therapy

BACKGROUND

Shift toward minimizing axillary lymph node dissection in patients with breast cancer post neoadjuvant therapy has led to the assessment of sentinel lymph nodes by frozen section intraoperatively to determine the need for axillary lymph node dissection. However, few studies have examined the accuracy of sentinel lymph node frozen section after neoadjuvant therapy. Our objective is to compare the accuracy of sentinel lymph node frozen section in patients with breast cancer with and without neoadjuvant therapy and to identify features that may influence accuracy.

DESIGN

We identified 161 sentinel lymph node frozen section from 77 neoadjuvant therapy patients and 255 sentinel lymph node frozen section from 88 non-neoadjuvant therapy patients diagnosed between 2010 and 2016 in 2 institutions. The frozen section diagnoses were compared to the final diagnoses, and clinicopathologic data were analyzed.

RESULTS

The sensitivity, specificity, and accuracy of frozen section analysis were comparable between neoadjuvant therapy patients and non-neoadjuvant therapy patients (71.9% vs 50%, 100% vs 100%, and 88.3% vs 81.8%). Nine (11.7%) of 77 neoadjuvant therapy patients had discordant results, most often due to undersampling (tumor absent on frozen section slide). Four of these patients subsequently underwent axillary lymph node dissection. Discordant results (all false negatives) were significantly more likely in neoadjuvant therapy patients with Estrogen Receptor-positive/HER2-negative status, and in sentinel lymph node with pN1mic and pN0i+ deposits; age, preneoadjuvant therapy lymph node status, histotype, nuclear grade, tumor size, and response to neoadjuvant therapy showed no significant differences. For non-neoadjuvant therapy cases, large tumor size, lobular histotype, and sentinel lymph node with pN1mic and pN0i+ were associated with false-negative frozen section assessment.

CONCLUSION

Sentinel lymph node frozen section diagnosis post-neoadjuvant therapy has comparable sensitivity, specificity, and accuracy to the sentinel lymph node frozen section diagnosis in the non-neoadjuvant therapy setting.

Significance of intrinsic breast cancer subtypes on the long-term prognosis after neoadjuvant chemotherapy

BACKGROUND

The prognosis of breast cancer and the treatment response to neoadjuvant chemotherapy (NAC) differ depending on the intrinsic molecular subtypes. We evaluated the prognostic significance of immunohistological subtypes in patients with recurrent breast cancer after treatment with NAC and surgery.

METHODS

A total of 237 patients with breast cancer treated with NAC and subsequent curative surgery between 2007 and 2015 were analyzed. The correlation between intrinsic molecular subtypes and clinicopathological features, prognosis, and pathological complete response (pCR) rate of NAC were investigated retrospectively.

RESULTS

There were 55 (23.2%) patients with recurrence after surgery. No significant difference in post-recurrence survival (PRS) was noted among the subtypes (p = 0.397). In patients with estrogen receptor-positive human epidermal growth factor receptor (HER) 2-negative (luminal) malignancy, PRS was significantly better in the pCR group than in the non-pCR group (p = 0.031). Conversely, pCR was not a significant predictor of improved PRS in patients with triple-negative breast cancer (TNBC; p = 0.329). Multivariate analysis revealed that the efficacy of NAC [hazard ratio (HR) 300.204, p < 0.001] and the initial metastasis site (HR 15.037, p = 0.005) were independent predictors for PRS in patients with luminal breast cancer, while Ki-67 (HR 51.171, p = 0.020) and the initial metastasis site (HR 13.318, p = 0.048) were independent predictors for PRS in patients with TNBC.

CONCLUSIONS

The prognostic factors for each intrinsic subtype should be evaluated separately in patients with recurrent breast cancer following NAC and surgery.

Retrospective analysis of concurrent docetaxel and epirubicin neoadjuvant versus adjuvant chemotherapy: Which leads to better outcomes for different subtype breast cancer patients?

Different biological subtype breast cancers respond differently to neoadjuvant chemotherapy, but it is unknown whether neoadjuvant or adjuvant chemotherapy leads to different long-term survival in each specific subtype although equal outcomes have been reported in general population. This study sought to clarify whether the selection of either neoadjuvant or adjuvant chemotherapy was linked to a differential survival benefit based on breast cancer subtypes.A prospectively maintained breast cancer database was queried from 2000 to 2008. All patients with a diagnosis of stage II and III breast cancer who received neoadjuvant or adjuvant chemotherapy were identified, only patients receiving docetaxel and epirubicin (TA) regimen were included. Patients were divided according to the administration of neoadjuvant or adjuvant chemotherapy. The biological subtypes were determined by immunohistochemical tests. The outcomes between neoadjuvant and adjuvant chemotherapy were compared in each different subtype. Kaplan-Meier curves were generated, and the Cox model was used to estimate the association between death risk and chemotherapy timing while adjusting for potentially confounding factors. P values < .05 were considered statistically significant.Of the 406 patients included, 201 (49.5%) received neoadjuvant chemotherapy, and 205 (50.5%) received an adjuvant TA regimen. Patients with the HER2+ and TNBC subtypes showed significantly higher pCR rates than patients with luminal types (P < .05). In general population, the neoadjuvant and adjuvant chemotherapy groups showed little survival variance (HR=1.15, 95% confidence interval (CI) .69-1.91, P=.60). In luminal B-like patients, neoadjuvant chemotherapy led to worse overall survival (OS) than adjuvant therapy (HR=2.92, 95%CI 1.20 to 8.31, P = .02). In patients with the HER2+ subtype, neoadjuvant treatment corresponded to better OS (HR = .10, 95%CI .02-.58, P = .01). In contrast, patients with luminal A-like (HR = 1.14, 95%CI .53-2.43, P = .74) and TNBC disease (HR = 1.00, 95%CI .27-3.73, P = >.99) who underwent neoadjuvant chemotherapy showed equivalent OS when compared to patients undergoing adjuvant therapy.Neoadjuvant versus adjuvant chemotherapy results in a disparate impact on overall survival among patients with variant subtype breast cancer. When neoadjuvant chemotherapy was given, luminal B-like patients showed worse outcome, while patients with HER2+ disease had better OS. Prospective studies are necessary to determine and optimize the timing of chemotherapy for breast cancers with different molecular backgrounds.

Prognostic Significance of Modified Residual Disease in Breast and Nodes (mRDBN) Algorithm After Neoadjuvant Chemotherapy for Breast Cancer

OBJECTIVES

We hypothesized that prognostic accuracy of the residual disease in breast and lymph nodes (RDBN) method, which is calculated using residual tumor size, nodal involvement, and tumor grade, may be improved by incorporating residual tumor cellularity.

METHODS

Cases included 614 patients who underwent neoadjuvant therapy for breast cancer. Tumor size was adjusted for residual cellularity of invasive carcinoma and used to calculate modified RDBN (mRDBN) and compared with unmodified gross tumor size (gRDBN).

RESULTS

RDBN could be calculated in 428 cases. Relative risks of recurrence and death were significantly higher for RDBN-3 and RDBN-4 compared with RDBN-1. Kaplan-Meier analysis showed significant differences in disease-free survival and overall survival for estrogen receptor (ER)-negative/human epidermal growth factor receptor 2 (HER2)-negative and ER-positive/HER2-negative subgroups (P < .0001).

CONCLUSIONS

Both mRDBN and gRDBN provide prognostic information, particularly in HER2-negative carcinoma; however, mRDBN showed better stratification of RDBN-3 and RDBN-4 patients.

Diagnostic performance of breast ultrasonography and MRI in the prediction of lymph node status after neoadjuvant chemotherapy for breast cancer

Background Neoadjuvant chemotherapy (NAC) is widely used to treat breast cancer. Sentinel lymph node biopsy has replaced axillary lymph node dissection in patients who convert to node-negative status after NAC. However, few studies have evaluated the diagnostic performance of ultrasonography and magnetic resonance imaging (MRI) in determining axillary lymph node status after NAC. Purpose To evaluate the diagnostic performance of breast ultrasonography and MRI in determining residual metastatic axillary lymph node status after NAC for breast cancer and to identify histopathological factors affecting radiological performance. Material and Methods This study included 157 patients who underwent initial and follow-up preoperative breast ultrasonography and MRI before NAC between January and December 2010. The sensitivity, specificity, negative and positive predictive values, and accuracy of ultrasonography, MRI, and their combinations were evaluated. Results The sensitivity of ultrasonography, MRI, and their combination in post-NAC axillary imaging was 60.00%, 57.33%, and 65.33%, respectively; the specificity was 60.47%, 72.09%, and 60.47%, respectively. The positive predictive value was highest with MRI (78.18%). On univariate analysis, positive estrogen receptor status was associated with misdiagnosis by ultrasonography ( P = 0.002), MRI ( P = 0.002), and their combination ( P = 0.001). When residual metastatic lymph nodes were present, lymph nodes with macrometastasis (>2.0 mm) were associated with correct ultrasonography-based diagnosis ( P = 0.0027). Conclusion Imaging assists in predicting axillary lymph node status in patients undergoing NAC; however, is imprudent to omit sentinel lymph node biopsy or axillary lymph node dissection for staging in women determined to be node-positive.

Breast-conserving surgery in locally advanced breast cancer submitted to neoadjuvant chemotherapy. Safety and effectiveness based on ipsilateral breast tumor recurrence and long-term follow-up

OBJECTIVE:

To evaluate ipsilateral breast tumor recurrence after breast-conserving surgery for locally advanced breast cancer.

METHODS:

A retrospective observational cohort study was performed in patients with locally advanced breast cancer submitted to breast-conserving surgery after neoadjuvant chemotherapy based on an adriamycin-cyclophosphamide-paclitaxel regimen. We evaluated the clinical, pathologic, immunohistochemistry, and surgical factors that contribute to ipsilateral breast tumor recurrence and locoregional recurrence. A Kaplan-Meier analysis and Cox model were used to evaluate the main factors related to disease-free survival.

RESULTS:

Of the 449 patients who received neoadjuvant chemotherapy, 98 underwent breast-conserving surgery. The average diameter of the tumors was 5.3 cm, and 87.2% reached a size of up to 3 cm. Moreover, 86.7% were classified as clinical stage III, 74.5% had T3-T4 tumors, 80.5% had N1-N2 axilla, and 89.8% had invasive ductal carcinoma. A pathologic complete response was observed in 27.6% of the tumors, and 100.0% of samples had free margins. The 5-year actuarial overall survival rate was 81.2%, and the mean follow-up was 72.8 months. The rates of ipsilateral breast tumor recurrence and locoregional recurrence were 11.2% and 15.3%, respectively. Multifocal morphology response was the only factor related to ipsilateral breast tumor recurrence disease-free survival (p=0.04). A multivariate analysis showed that the pathologic response evaluation criteria in solid tumors (RECIST)-breast cutoff was the only factor related to locoregional recurrence disease-free survival (p=0.01).

CONCLUSIONS:

Breast-conserving surgery is a safe and effective therapy for selected locally advanced breast tumors.

Identifying relations between imaging phenotypes and molecular subtypes of breast cancer: Model discovery and external validation

PURPOSE

To determine whether dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) characteristics of the breast tumor and background parenchyma can distinguish molecular subtypes (ie, luminal A/B or basal) of breast cancer.

MATERIALS AND METHODS

In all, 84 patients from one institution and 126 patients from The Cancer Genome Atlas (TCGA) were used for discovery and external validation, respectively. Thirty-five quantitative image features were extracted from DCE-MRI (1.5 or 3T) including morphology, texture, and volumetric features, which capture both tumor and background parenchymal enhancement (BPE) characteristics. Multiple testing was corrected using the Benjamini-Hochberg method to control the false-discovery rate (FDR). Sparse logistic regression models were built using the discovery cohort to distinguish each of the three studied molecular subtypes versus the rest, and the models were evaluated in the validation cohort.

RESULTS

On univariate analysis in discovery and validation cohorts, two features characterizing tumor and two characterizing BPE were statistically significant in separating luminal A versus nonluminal A cancers; two features characterizing tumor were statistically significant for separating luminal B; one feature characterizing tumor and one characterizing BPE reached statistical significance for distinguishing basal (Wilcoxon P < 0.05, FDR < 0.25). In discovery and validation cohorts, multivariate logistic regression models achieved an area under the receiver operator characteristic curve (AUC) of 0.71 and 0.73 for luminal A cancer, 0.67 and 0.69 for luminal B cancer, and 0.66 and 0.79 for basal cancer, respectively.

CONCLUSION

DCE-MRI characteristics of breast cancer and BPE may potentially be used to distinguish among molecular subtypes of breast cancer.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1017-1027.

Breast Cancer Immunology and Immunotherapy: Current Status and Future Perspectives

Cancer immunology has gained renewed interest in the past few years due to emerging findings on mechanisms involved in tumoral immune evasion. Indisputably, immune edition is currently considered a critical hallmark of cancer. Basic research has revealed new targets which can be modulated in the clinical setting with new compounds and strategies. As recent evidence confirms, breast cancer (BC) is a complex and heterogeneous disease in which host immune responses play a substantial role. T-infiltrating lymphocytes measurement is suggested as a powerful new tool necessary to predict early BC evolution, especially in HER2-positive and triple negative subtypes. However, T-infiltrating lymphocytes, genomic platforms, and many other biomarkers in tissue and peripheral blood (e.g., regulatory T cells and myeloid-derived suppressor cells) are not the only factors being evaluated regarding their potential role as prognostic and/or predictive factors. Many ongoing clinical trials are exploring the activity of immune checkpoint modulators in BC treatment, both in the advanced and neoadjuvant setting. Although this field is expanding with exciting new discoveries and promising clinical results-and creating great expectations-there remain many uncertainties yet to be addressed satisfactorily before this long awaited therapeutic promise can come to fruition.

How interacting pathways are regulated by miRNAs in breast cancer subtypes

BACKGROUND

An important challenge in cancer biology is to understand the complex aspects of the disease. It is increasingly evident that genes are not isolated from each other and the comprehension of how different genes are related to each other could explain biological mechanisms causing diseases. Biological pathways are important tools to reveal gene interaction and reduce the large number of genes to be studied by partitioning it into smaller paths. Furthermore, recent scientific evidence has proven that a combination of pathways, instead than a single element of the pathway or a single pathway, could be responsible for pathological changes in a cell.

RESULTS

In this paper we develop a new method that can reveal miRNAs able to regulate, in a coordinated way, networks of gene pathways. We applied the method to subtypes of breast cancer. The basic idea is the identification of pathways significantly enriched with differentially expressed genes among the different breast cancer subtypes and normal tissue. Looking at the pairs of pathways that were found to be functionally related, we created a network of dependent pathways and we focused on identifying miRNAs that could act as miRNA drivers in a coordinated regulation process.

CONCLUSIONS

Our approach enables miRNAs identification that could have an important role in the development of breast cancer.

Long-term outcome in young women with breast cancer: a population-based study

Purpose

Whether young age at diagnosis of breast cancer is an independent risk factor for death remains controversial, and the question whether young age should be considered in treatment decisions is still to be answered.

Methods

From a population-based cohort of 22,017 women with breast cancer, all women <35 years (n = 471) were compared to a random sample of 700 women aged 35–69 years from the same cohort. Information on patient and tumor characteristics, treatment, and follow-up was collected from the medical records. Tissue microarrays were produced for analysis of classical biomarkers. Breast cancer-specific survival (BCSS), distant disease-free survival (DDFS), and locoregional recurrence-free survival (LRFS) by age were compared using women 50–69 years as reference.

Results

At 10 years follow-up, women <35 years and 35–39 years had a worse BCSS [age <35 years 69 % (HR 2.75, 95 % CI 1.93–3.94), age 35–39 years 76 % (HR 2.33, 95 % CI 1.54–3.52), age 40–49 years 84 % (HR 1.53, 95 % CI 0.97–2.39), and age 50–69 years 89 % (reference)]. The worse BCSS was statistically significant in stages I–IIa and Luminal B tumors. At multivariate analysis age <35 years and 35–39 years confined a risk in LRFS (HR 2.13, 95 % CI 1.21–3.76 and HR 1.97, 95 % CI 1.06–3.68) but not in DDFS and BCSS. In the subgroup of women <40 years with luminal tumors stage I–IIa, low age remained an independent risk factor also in DDFS (HR 1.87, 95 % CI 1.03–3.44).

Conclusion

Young women have a high risk of systemic disease even when diagnosed in an early stage. The excess risk of relapse is most pronounced in Luminal B tumors, where low age is an independent prognostic factor of DDFS and LRFS.

Electronic supplementary material

The online version of this article (doi:10.1007/s10549-016-3983-9) contains supplementary material, which is available to authorized users.

Neoadjuvant chemotherapy in breast cancers

With advances in science and technology, there are more innovations in the approach to management of patients with breast cancer. Neoadjuvant chemotherapy that is designed to be used prior to surgical removal of a tumor has received significant attention. Currently, neoadjuvant chemotherapy is offered to patients with locally advanced breast cancer and also those breast cancer patients who may benefit from size reduction before conservation therapy. There is now sufficient evidence that if neoadjuvant chemotherapy leads to complete pathologic response, the patient will enjoy a better outcome. Therefore, assessment of the degree of response to neoadjuvant chemotherapy has a major impact on patient selection and the follow-up management of each patient and defines patient outcome.

Anthracycline-Free Neoadjuvant Chemotherapy Ensures Higher Rates of Pathologic Complete Response in Breast Cancer

PURPOSE

Neoadjuvant chemotherapy (NCT) is a standard of care for locally advanced and initially inoperable breast cancer. NCT can test chemotherapy efficacy and can be followed by breast-conserving surgery. Considering taxanes as one of the most effective agents, we analyzed the efficacy of a neoadjuvant schedule without anthracyclines and based only on taxanes and carboplatin, trying to avoid cardiotoxicity, which is the most serious side effect correlated with anthracyclines.

PATIENTS AND METHODS

We enrolled 61 patients with breast cancer, belonging to 4 subgroups, according to molecular phenotypes: 24 triple-negative/basal-like, 13 HER2-like, 20 luminal B, and 4 luminal A. All patients underwent weekly chemotherapy with carboplatin AUC2, paclitaxel 80 mg/m², with trastuzumab (in case of HER2 positivity) 2 mg/kg, except for luminal A patients, who underwent only hormonal therapy. Among 61 patients, 26 (43%) received modified radical mastectomy and 35 (57%) received breast-conserving surgery.

RESULTS

The patients obtaining pathologic complete response (pCR) were 20 (83%) of 24 triple-negative/basal-like, 10 (76%) of 13 HER2-like, 6 (30%) of 20 luminal B, and 3 (75%) of 4 luminal A. All the patients were evaluated for toxicity: no grade 4 was detected, 5 patients experienced grade 3 neuropathy, then reverted to G2 after chemotherapy discontinuation. At a minimum follow-up of 5 years, median overall survival was 48 months.

CONCLUSION

Taxane/carboplatin-based/anthracycline-free NCT is the best treatment for inoperable breast cancer in terms of efficacy and toxicity, because this approach avoids cardiotoxicity and obtains an optimal rate (64%) of pCR, with an important impact on survival.

Adjuvant chemotherapy: which patient? What regimen?

In the past, treatment decisions regarding adjuvant chemotherapy in early breast cancer (EBC) were made solely based on clinicopathologic factors. However, with increased awareness of the importance of underlying tumor biology, we are now able to use genomic analyses to determine molecular breast cancer subtype and thus identify patients with tumors that are chemotherapy resistant and unlikely to benefit from the addition of chemotherapy. Although genomics has allowed some patients to avoid chemotherapy-specifically those with luminal A-like breast cancer-these assays do not indicate which regimen is most appropriate. For this, consideration must be given to the combination of underlying tumor biology, tumor stage, and patient characteristics, such as age and tolerability of side effects.

Impact of immunohistological subtypes on the long-term prognosis of patients with metastatic breast cancer

PURPOSE

Although improved long-term prognoses for patients with metastatic breast cancer (MBC) have been demonstrated, few reports address overall survival (OS) with sufficient follow-up. Furthermore, the relevance of immunohistological subtypes to OS in MBC has not been clarified.

METHODS

We evaluated, retrospectively, the OS of patients who had been initiated on systemic therapy for MBC between 2000 and 2008.

RESULTS

The subjects of this study were 527 patients with MBC treated by systemic therapy. The median survival time (MST) was 55.5 months. The MST for each immunohistological subtype was as follows: luminal, 59.9 months; luminal-HER2, not reached; triple-negative, 18.6 months; and HER2-enriched, 49.9 months. According to multivariate analysis, metastasis-free intervals of ≥2 years and treatment with anthracycline for MBC were predictive of better OS. The predictors of shorter OS included disease progression after first-line treatment for MBC, triple-negative, and all histological factors, except papillotubular carcinoma, with liver metastasis, and having three or more initial metastatic sites.

CONCLUSIONS

The prognosis of the patients with MBC in this series was better than that reported before 2000, which is probably attributable to the use of novel, improved pharmacological agents. For example, luminal-HER2 tumors can be treated using both aromatase inhibitors and trastuzumab. Because of the lower toxicities, it is now possible to administer these agents for longer periods, resulting in better prognoses.

Evaluation of lymph node status after neoadjuvant chemotherapy in breast cancer patients: comparison of diagnostic performance of ultrasound, MRI and ¹⁸F-FDG PET/CT

Objective:

To evaluate the diagnostic performance of ultrasound, MRI and fluorine-18 fludeoxyglucose positron emission tomography (¹⁸F-FDG PET)/CT for the diagnosis of metastatic axillary lymph node (ALN) after neoadjuvant chemotherapy (NAC) and to find out histopathological factors affecting the diagnostic performance of these imaging modalities.

Methods:

From January 2012 to November 2014, 191 consecutive patients with breast cancer who underwent NAC before surgery were retrospectively reviewed. We included 139 patients with ALN metastasis that was confirmed on fine needle aspiration or core needle biopsy at initial diagnosis.

Results:

After NAC, 39 (28%) patients showed negative conversion of ALN on surgical specimens of sentinel lymph node (LN) or ALN. The sensitivity of ultrasound, MRI and PET/CT was 50% (48/96), 72% (70/97) and 22% (16/73), respectively. The specificity of ultrasound, MRI and PET/CT was 77% (30/39), 54% (21/39) and 85% (22/26), respectively. The Az value of combination of ultrasound and PET/CT was the highest (0.634) followed by ultrasound (0.626) and combination of ultrasound, MRI and PET/CT (0.617). The size of tumour deposit in LN and oestrogen receptor was significantly associated with the diagnostic performance of ultrasound (p < 0.001 and p = 0.009, respectively) and MRI (p = 0.045 and p = 0.036, respectively). The percentage diameter decrease, size of tumour deposit in LN, progesterone receptor, HER2 and histological grade were significantly associated with the diagnostic performance of PET/CT (p = 0.023, p = 0.002, p = 0.036, p = 0.044 and p = 0.008, respectively). On multivariate logistic regression analysis, size of tumour deposit within LN was identified as being independently associated with diagnostic performance of ultrasound [odds ratio, 13.07; 95% confidence interval (CI), 2.95–57.96] and PET/CT (odds ratio, 6.47; 95% CI, 1.407–29.737).

Conclusion:

Combination of three imaging modalities showed the highest sensitivity, and PET/CT showed the highest specificity for the evaluation of ALN metastasis after NAC. Ultrasound alone or combination of ultrasound and PET/CT showed the highest positive-predictive value. The size of tumour deposit within ALN was significantly associated with diagnostic performance of ultrasound and PET/CT.

Advances in knowledge:

This study is about the diagnostic performance of ultrasound, MRI, PET/CT and combination of each imaging modality for the evaluation of metastatic ALN after NAC. Of many histopathological factors, only the size of tumour deposit within ALN was an independent factor associated with the diagnostic performance of ultrasound and PET/CT.

ER, PgR, Ki67, p27(Kip1), and histological grade as predictors of pathological complete response in patients with HER2-positive breast cancer receiving neoadjuvant chemotherapy using taxanes followed by fluorouracil, epirubicin, and cyclophosphamide concomitant with trastuzumab

Background

Neoadjuvant chemotherapy (NAC) with taxanes followed by fluorouracil, epirubicin, and cyclophosphamide (FEC), and concurrent trastuzumab is a potent regimen for HER2 over-expressing breast cancer. A high pathological complete response (pCR) rate has been achieved using this regimen; however, the predictive factors and prognostic effects of pCR currently remain unclear. In the present study, we determined whether pCR was related to histological grade (HG) and several biological factors including p27^Kip1. We also assessed the prognosis of the pCR and non-pCR groups, and expected differences between those positive and negative for lymph node metastasis after chemotherapy.

Methods

A total of 129 Japanese women with HER2-positive invasive breast cancer received either paclitaxel or docetaxel followed by FEC, with the concomitant administration of trastuzumab. The statuses of HG, ER, PgR, Ki67, and p27^Kip1 were evaluated to determine their relationship with pCR. Relapse-free survival (RFS) and overall survival (OS) were also analyzed for their relationship with pCR and pathological nodal involvement.

Results

pCR was obtained in 84 out of 129 patients and the pCR rate was 65.1 %. The pCR rates related to 5 factors were as follows: HG (grade 3, 70.0 % vs. grades 1–2, 36.8 %), ER (negative, 78.6 % vs. positive, 40.0 %), PgR (negative, 75.3 % vs. positive, 38.9 %), Ki67 (high, 72.0 % vs. low, 47.2 %), and p27^Kip1 (low, 71.0 % vs. high, 50.0 %). RFS was significantly better in the pCR group than in the non-pCR group (p = 0.018). Patients with remaining nodal disease in the pCR group had worse OS (p = 0.0002).

Conclusions

High-HG, low-ER, low-PgR, high-Ki67, and low-p27^Kip1 were identified as predictive factors of pCR in NAC with trastuzumab, while pCR and negative nodes were predictive of better survivals.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1641-y) contains supplementary material, which is available to authorized users.

How to use magnetic resonance imaging following neoadjuvant chemotherapy in locally advanced breast cancer

Magnetic resonance imaging (MRI) is highly sensitive in identifying residual breast cancer following neoadjuvant chemotherapy (NAC), and consequently is a commonly used imaging modality in locally advanced breast cancer patients. In these patients, tumor response is an important prognostic indicator. However, discrepancies between MRI findings and surgical pathology are well documented. Overestimation of residual disease by MRI may result in greater surgery than is actually required while underestimation may result in insufficient surgery. Thus, it is important to understand when MRI findings are reliable and when they are less accurate. MRI most accurately predicts pathology in triple negative, Her2 positive and hormone receptor negative tumors, especially if they are of a solid imaging phenotype. In these cases, post-NAC MRI is highly reliable for surgical planning. Hormone receptor positive cancers and those demonstrating non mass enhancement show lower concordance with surgical pathology, making surgical guidance more nebulous in these cases. Radiologists and surgeons must assess MRI response to NAC in the context of tumor subtype. Indiscriminate interpretations will prevent MRI from achieving its maximum potential in the pre-operative setting.

Evaluation of the pathological response and prognosis following neoadjuvant chemotherapy in molecular subtypes of breast cancer

BACKGROUND

The pathological complete response of neoadjuvant chemotherapy for breast cancer correlates with the prognosis for survival. Tumors may have different prognoses according to their molecular subtypes. This study was performed to evaluate the relevance of the pathological response and prognosis following neoadjuvant chemotherapy in the molecular subtypes of breast cancer.

METHODS

A consecutive series of 88 patients with operable breast cancer treated with neoadjuvant chemotherapy was analyzed. Patients were classified into four molecular subtypes based on the immunohistochemistry profile of the estrogen receptor, progesterone receptor, HER2, and Ki-67. The histological response was assessed according to Miller-Payne grading (MPG) and Residual Disease in Breast and Nodes (RDBN).

RESULTS

Ten patients (11.4%) achieved a pathological complete response, assessed according to RDBN. The pathological complete response rate was 13.6% according to MPG. Patients with the triple-negative subtype were more likely to achieve a pathological complete response than those with luminal A breast cancer (P=0.03). MPG and RDBN are independent predictors of distant disease-free survival and local recurrence-free survival, but do not predict overall survival. Ki-67, size of invasive carcinoma, lymph nodes, molecular subtypes, MPG, and RDBN are important predictors of distant disease-free survival, local recurrence-free survival, and overall survival.

CONCLUSION

MPG and RDBN were similarly related to the patient's prognosis. MPG was more suitable for evaluation of distant disease-free survival, and RDBN was more suitable for evaluation of local recurrence-free survival. Survival following neoadjuvant chemotherapy correlated with the pathological reaction rather than the molecular subtype of breast cancer. The molecular subtype of breast cancer was not correlated with pathological response in patients who did not achieve a pathological complete response.

Sentinel lymph node biopsy alone after neoadjuvant chemotherapy in patients with initial cytology-proven axillary node metastasis

Purpose

Neoadjuvant chemotherapy (NAC) has been recently used to downstage breast cancer. However, in patients with initial axillary lymph node (ALN) metastasis, ALN dissection regardless of the NAC response remains the standard treatment. The purpose of this study was to identify the feasibility and accuracy of sentinel lymph node biopsy (SLNB) after NAC in patients with ALN metastasis at diagnosis.

Methods

From January 2007 to August 2013, data of patients who were diagnosed with invasive breast cancer and ALN metastasis and treated with NAC followed by definitive surgery in two centers were collected retrospectively. A total of 386 patients were enrolled and classified into five groups according to surgical procedure for the ALNs and pathologic results.

Results

At SLNB after NAC, sentinel lymph nodes (SLNs) that stained blue or were hot, including suspicious nodes, were identified; the SLN identification and false-negative rates was 96% and 10%, respectively. There was no difference in the overall survival among the groups. For patients who revealed a pathologic complete node response, there was a significant difference in the disease-free survival rate between the SLNB only and complete ALN dissection groups (p=0.031). However, the rate of axillary recurrence demonstrated no significant differences among the groups (p>0.050).

Conclusion

SLNB after NAC in breast cancer patients with initial ALN metastasis may help identify downstaging to negative nodal status and thereby reduce the surgical morbidity by avoiding standard ALN dissection.

Can pathologic complete response (pCR) be used as a surrogate marker of survival after neoadjuvant therapy for breast cancer?

Breast cancer is heterogeneous in clinical, morphological, immunohistochemical and biological features, as reflected by several different prognostic subgroups. Neoadjuvant approaches are currently used for the "in vivo" efficacy assessment of treatments. Pathological complete response (pCR) has been reported as a reliable predictive factor of survival in that setting. However, pCR remains a subject of controversy in terms of definition and its evaluation methods. In addition, its predictive value for patient outcome in various breast cancer biological subtypes has been under debate. In this review, we will present the existing definitions of pCR, the impact of its evaluation methods on its rate and the assessment of its predictive value for patient outcome in the molecular subtypes of breast cancer (luminal A and B, Triple Negative and HER2-positive).

Role of positron emission tomography for the monitoring of response to therapy in breast cancer

This review considers the potential utility of positron emission tomography (PET) tracers in the setting of response monitoring in breast cancer, with a special emphasis on glucose metabolic changes assessed with (18)F-fluorodeoxyglucose (FDG). In the neoadjuvant setting of breast cancer, the metabolic response can predict the final complete pathologic response after the first cycles of chemotherapy. Because tumor metabolic behavior highly depends on cancer subtype, studies are ongoing to define the optimal metabolic criteria of tumor response in each subtype. The recent multicentric randomized AVATAXHER trial has suggested, in the human epidermal growth factor 2-positive subtype, a clinical benefit of early tailoring the neoadjuvant treatment in women with poor metabolic response after the first course of treatment. In the bone-dominant metastatic setting, there is increasing clinical evidence that FDG-PET/computed tomography (CT) is the most accurate imaging modality for assessment of the tumor response to treatment when both metabolic information and morphologic information are considered. Nevertheless, there is a need to define standardized metabolic criteria of response, including the heterogeneity of response among metastases, and to evaluate the costs and health outcome of FDG-PET/CT compared with conventional imaging. New non-FDG radiotracers highlighting specific molecular hallmarks of breast cancer cells have recently emerged in preclinical and clinical studies. These biomarkers can take into account the heterogeneity of tumor biology in metastatic lesions. They may provide valuable clinical information for physicians to select and monitor the effectiveness of novel therapeutics targeting the same molecular pathways of breast tumor.

The value of tumor infiltrating lymphocytes (TILs) for predicting response to neoadjuvant chemotherapy in breast cancer: a systematic review and meta-analysis

Background

We carried out a systematic review and meta-analysis to evaluate the predictive roles of tumor infiltrating lymphocytes (TILs) in response to neoadjuvant chemotherapy (NAC) in breast cancer.

Method

A PubMed and Web of Science literature search was designed. Random or fixed effect models were adopted to estimate the summary odds ratio (OR). Heterogeneity and sensitivity analyses were performed to explore heterogeneity among studies and to assess the effects of study quality. Publication bias was evaluated using a funnel plot, Egger's test and Begg's test. We included studies where the predictive significance of TILs, and/or TILs subset on the pathologic complete response (pCR) were determined in NAC of breast cancer.

Results

A total of 13 published studies (including 3251 patients) were eligible. In pooled analysis, the detection of higher TILs numbers in pre-treatment biopsy was correlated with better pCR to NAC (OR = 3.93, 95% CI, 3.26–4.73). Moreover, TILs predicted higher pCR rates in triple negative (OR = 2.49, 95% CI: 1.61–3.83), HER2 positive (OR = 5.05, 95% CI: 2.86–8.92) breast cancer, but not in estrogen receptor (ER) positive (OR = 6.21, 95%CI: 0.86–45.15) patients. In multivariate analysis, TILs were still an independent marker for high pCR rate (OR = 1.41, 95% CI: 1.19–1.66). For TILs subset, higher levels of CD8+ and FOXP3+ T-lymphocytes in pre-treatment biopsy respectively predicted better pathological response to NAC (OR = 6.44, 95% CI: 2.52–16.46; OR = 2.94, 95% CI: 1.05–8.26). Only FOXP3+ lymphocytes in post-NAC breast tissue were a predictive marker for low pCR rate in univariate (OR = 0.41, 95% CI: 0.21–0.80) and multivariate (OR = 0.36, 95% CI: 0.13–0.95) analysis.

Conclusion

Higher TILs levels in pre-treatment biopsy indicated higher pCR rates for NAC. TILs subset played different roles in predicting response to NAC.

The genomic map of breast cancer: which roads lead to better targeted therapies?

Recent advances in whole-genome technologies have supplied the field of cancer research with an overwhelming amount of molecular data. Improvements in massively parallel sequencing approaches have led to logarithmic decreases in costs, and so these methods are becoming almost commonplace in the analysis of clinical trials and other cohorts of interest. Furthermore, whole-transcriptome quantification by RNA sequencing is quickly replacing microarrays. However, older chip-based methodologies such as comparative genomic hybridization and single-nucleotide polymorphism arrays have benefited from this technological explosion and are now so accessible that they can be employed in increasingly larger cohorts of patients. The study of breast cancer lends itself particularly well to these technologies. It is the most commonly diagnosed neoplasm in women, giving rise to nearly 230,000 new cases each year. Many patients are given a diagnosis of early-stage disease, for which surgery is the standard of care. These attributes result in excellent availability of tissues for whole-genome/transcriptome analysis. The Cancer Genome Atlas project has generated comprehensive catalogs of publically available genomic breast cancer data. In addition, other studies employing the power of genomic technologies in medium to large cohorts were recently published. These data are now publically available for the generation of novel hypotheses. However, these studies differed in the methods, patient cohorts, and analytical techniques employed and represent complementary snapshots of the molecular underpinnings of breast cancer. Here, we will discuss the convergences and divergences of these reports as well as the scientific and clinical implications of their findings.

Progesterone receptor status and Ki-67 index may predict early relapse in luminal B/HER2 negative breast cancer patients: a retrospective study

PURPOSE

Few studies has documented early relapse in luminal B/HER2-negative breast cancer. We examined prognostic factors for early relapse among these patients to improve treatment decision-making.

PATIENTS AND METHODS

A total 398 patients with luminal B/HER2-negative breast cancer were included. Kaplan-Meier curves were applied to estimate disease-free survival and Cox regression to identify prognostic factors.

RESULTS

Progesterone receptor (PR) negative expression was associated with higher tumor grade (p<.001) and higher Ki-67 index (p = .010). PR-negative patients received more chemotherapy than the PR-positive group (p = .009). After a median follow-up of 28 months, 17 patients (4.3%) had early relapses and 8 patients (2.0%) died of breast cancer. The 2-year disease-free survival was 97.7% in the PR-positive and 90.4% in the PR-negative groups (Log-rank p = .002). Also, patients with a high Ki-67 index (defined as >30%) had a reduced disease-free survival (DFS) when compared with low Ki-67 index group (≤30%) (98.0% vs 92.4%, respectively, Log-rank p = .013). In multivariate analysis, PR negativity was significantly associated with a reduced DFS (HR = 3.91, 95% CI 1.29-11.88, p = .016).

CONCLUSION

In this study, PR negativity was a prognostic factor for early relapse in luminal B/HER2-negative breast cancer, while a high Ki-67 index suggested a higher risk of early relapse.

Circulating miR-19a and miR-205 in serum may predict the sensitivity of luminal A subtype of breast cancer patients to neoadjuvant chemotherapy with epirubicin plus paclitaxel

Background

The luminal A subtype of breast cancer has a good prognosis and is sensitive to endocrine therapy but is less sensitive to chemotherapy. It is necessary to identify biomarkers to predict chemosensitivity and avoid over-treatment. We hypothesized that miRNAs in the serum might be associated with chemosensitivity.

Methods

Sixty-eight breast cancer patients received neoadjuvant chemotherapy with epirubicin plus paclitaxel. The serum of the patients was collected before chemotherapy and stored at −80°C. The samples were classified into two groups in term of the chemosensitivity. We identified the differential expression patterns of miRNAs between the chemotherapy sensitive and resistant groups using microRNA profiling. Four miRNAs that were differentially expressed between the two groups were further validated in another 56 samples. We created a model fitting formula and a receiver operating characteristics (ROC) curve using logistic regression analysis to evaluate the prediction potency.

Results

We identified 8 miRNAs differentially expressed between the two groups: 6 miRNAs were up-regulated, and 2 miRNAs were down-regulated in the resistant group compared with the sensitive group. The expression of miR-19a and miR-205 were determined to have significant differences between the two groups (P<0.05). A predictive model of these two miRNAs was created by the logistic regression analysis. The probability of this model was 89.71%. Based on the ROC curve, the specificity was 75.00%, and the sensitivity was 81.25%.

Conclusions

The combination of miR-19a and miR-205 in the serum may predict the chemosensitivity of luminal A subtype of breast cancer to epirubicin plus paclitaxel neoadjuvant chemotherapy.