Neoadjuvant chemotherapy in triple-negative breast cancer: A multicentric retrospective observational study in real-life setting

H3K27ac-induced RHOXF2 activates Wnt2/β-catenin pathway by binding to HOXC13 to aggravate the malignant progression of triple negative breast cancer

Triple negative breast cancer (TNBC) is insensitive to conventional targeted therapy and endocrine therapy, and is characterized by high invasiveness and high recurrence rate. This study aimed to explore the role and mechanism of RHOXF2 and HOXC13 on the malignant progression of TNBC. RT-qPCR and western blot were used to detect RHOXF2 and HOXC13 expression in TNBC cells. The proliferation, colony formation, invasion, migration, apoptosis and cell cycle of TNBC cells after transfection were analyzed by CCK-8 assay, colony formation assay, transwell assay, wound healing assay and flow cytometry analysis. Co-Immunoprecipitation and GST pull-down assays were used to analyze the combination between RHOXF2 and HOXC13. ChIP-PCR and luciferase reporter gene assay were used to examine the regulation of H3K27ac on RHOXF2. Besides, the expression of Ki67 and cleaved Caspase3 in tumor tissues of nude mice was determined by immunofluorescence. Results revealed that RHOXF2 and HOXC13 expression was increased in TNBC cells. RHOXF2 knockdown suppressed the proliferation, invasion and migration, as well as induced G0/G1 cell cycle arrest and apoptosis of TNBC cells. Besides, RHOXF2 could bind to HOXC13 and RHOXF2 knockdown suppressed HOXC13 expression in TNBC cells. Furthermore, HOXC13 overexpression reversed the impacts of RHOXF2 downregulation on the proliferation, invasion, migration, G0/G1 cell cycle arrest and apoptosis of TNBC cells. In addition, RHOXF2 silencing limited the tumor volume in nude mice, which was reversed by HOXC13 overexpression. Moreover, RHOXF2 knockdown interfered with Wnt2/β-catenin pathway in vitro and in vivo by binding to HOXC13. Importantly, H3K27ac acetylation could activate the expression of RHOXF2 promoter region. In conclusion, RHOXF2 activated by H3K27ac functioned as a tumor promoter in TNBC via mediating Wnt2/β-catenin pathway by binding to HOXC13, which provided promising insight into exploration on TNBC therapy.

Prognostic predictive value of Ki-67 in stage I-II triple-negative breast cancer

Aim: Our research aimed to determine an optimal cutoff value and investigate the prognostic predictive function of Ki-67. Materials & methods: We retrospectively enrolled 1146 patients diagnosed with stage I-II triple-negative breast cancer. Disease-free and overall survival were analyzed using the Kaplan-Meier method and the Cox regression model. Results: We classified Ki-67 >45% as the high group (n = 716). A Ki-67 level of >45% was associated with poorer disease-free survival (p = 0.039) and overall survival (p = 0.029). Lymph node stage, neoadjuvant chemotherapy, and radiotherapy were independent predictive variables of prognosis. Conclusion: Triple-negative breast cancer may be further subcategorized according to the Ki-67 level. Neoadjuvant chemotherapy and postoperative radiotherapy can improve the prognosis of early triple-negative breast cancer.

Digital image analysis and machine learning-assisted prediction of neoadjuvant chemotherapy response in triple-negative breast cancer

BACKGROUND

Pathological complete response (pCR) is associated with favorable prognosis in patients with triple-negative breast cancer (TNBC). However, only 30-40% of TNBC patients treated with neoadjuvant chemotherapy (NAC) show pCR, while the remaining 60-70% show residual disease (RD). The role of the tumor microenvironment in NAC response in patients with TNBC remains unclear. In this study, we developed a machine learning-based two-step pipeline to distinguish between various histological components in hematoxylin and eosin (H&E)-stained whole slide images (WSIs) of TNBC tissue biopsies and to identify histological features that can predict NAC response.

METHODS

H&E-stained WSIs of treatment-naïve biopsies from 85 patients (51 with pCR and 34 with RD) of the model development cohort and 79 patients (41 with pCR and 38 with RD) of the validation cohort were separated through a stratified eightfold cross-validation strategy for the first step and leave-one-out cross-validation strategy for the second step. A tile-level histology label prediction pipeline and four machine-learning classifiers were used to analyze 468,043 tiles of WSIs. The best-trained classifier used 55 texture features from each tile to produce a probability profile during testing. The predicted histology classes were used to generate a histology classification map of the spatial distributions of different tissue regions. A patient-level NAC response prediction pipeline was trained with features derived from paired histology classification maps. The top graph-based features capturing the relevant spatial information across the different histological classes were provided to the radial basis function kernel support vector machine (rbfSVM) classifier for NAC treatment response prediction.

RESULTS

The tile-level prediction pipeline achieved 86.72% accuracy for histology class classification, while the patient-level pipeline achieved 83.53% NAC response (pCR vs. RD) prediction accuracy of the model development cohort. The model was validated with an independent cohort with tile histology validation accuracy of 83.59% and NAC prediction accuracy of 81.01%. The histological class pairs with the strongest NAC response predictive ability were tumor and tumor tumor-infiltrating lymphocytes for pCR and microvessel density and polyploid giant cancer cells for RD.

CONCLUSION

Our machine learning pipeline can robustly identify clinically relevant histological classes that predict NAC response in TNBC patients and may help guide patient selection for NAC treatment.

PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning

BACKGROUND

Invasive breast cancer patients are increasingly being treated with neoadjuvant chemotherapy; however, only a fraction of the patients respond to it completely. To prevent overtreatment, there is an urgent need for biomarkers to predict treatment response before administering the therapy.

METHODS

In this retrospective study, we developed hypothesis-driven interpretable biomarkers based on deep learning, to predict the pathological complete response (pCR, i.e., the absence of tumor cells in the surgical resection specimens) to neoadjuvant chemotherapy solely using digital pathology H&E images of pre-treatment breast biopsies. Our approach consists of two steps: First, we use deep learning to characterize aspects of the tumor micro-environment by detecting mitoses and segmenting tissue into several morphology compartments including tumor, lymphocytes and stroma. Second, we derive computational biomarkers from the segmentation and detection output to encode slide-level relationships of components of the tumor microenvironment, such as tumor and mitoses, stroma, and tumor infiltrating lymphocytes (TILs).

RESULTS

We developed and evaluated our method on slides from n = 721 patients from three European medical centers with triple-negative and Luminal B breast cancers and performed external independent validation on n = 126 patients from a public dataset. We report the predictive value of the investigated biomarkers for predicting pCR with areas under the receiver operating characteristic curve between 0.66 and 0.88 across the tested cohorts.

CONCLUSION

The proposed computational biomarkers predict pCR, but will require more evaluation and finetuning for clinical application. Our results further corroborate the potential role of deep learning to automate TILs quantification, and their predictive value in breast cancer neoadjuvant treatment planning, along with automated mitoses quantification. We made our method publicly available to extract segmentation-based biomarkers for research purposes.

A Retrospective Exploratory Analysis for Serum Extracellular Vesicles Reveals APRIL (TNFSF13), CXCL13, and VEGF-A as Prognostic Biomarkers for Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

Neoadjuvant chemotherapy (NAC) is widely used as a standard treatment for early-stage triple-negative breast cancer (TNBC). While patients who achieve pathologic complete response (pCR) have a highly favorable outcome, patients who do not achieve pCR have variable prognoses. It is important to identify patients who are most likely to have poor survival outcomes to identify candidates for more aggressive therapeutic approaches after NAC. Many studies have demonstrated that cytokines and growth factors packaged into extracellular vesicles (EVs) have an essential role in tumor progression and drug resistance. In this study, we examined the role of serum-derived EV-associated cytokines as prognostic biomarkers for long-term outcomes in patients who underwent anthracycline-taxane-based NAC. We isolated extracellular vesicles from the serum of 190 TNBC patients who underwent NAC between 2015 and 2018 at Samsung Medical Center. EV-associated cytokine concentrations were measured with ProcartaPlex Immune Monitoring 65-plex panels. The prognostic value of EV-associated cytokines was studied. We found that patients with high EV_APRIL, EV_CXCL13, and EV_VEGF-A levels had shorter overall survival (OS). We further evaluated the role of these selected biomarkers as prognostic factors in patients with residual disease (RD) after NAC. Even in patients with RD, high levels of EV_APRIL, EV_CXCL13, and EV_VEGF-A were correlated with poor OS. In all subgroup analyses, EV_CXCL13 overexpression was significantly associated with poor overall survival. Moreover, multivariate analysis indicated that a high level of EV_CXCL13 was an independent predictor of poor OS. Correlation analysis between biomarker levels in EVs and serum showed that EV_VEGF-A positively correlated with soluble VEGF-A but not CXCL13. An elevated level of soluble VEGF-A was also associated with poor OS. These findings suggest that EV_APRIL, EV_CXCL13, and EV_VEGF-A may be useful in identifying TNBC patients at risk of poor survival outcomes after NAC.

Correlation between Baseline Conventional Ultrasounds, Shear-Wave Elastography Indicators, and Neoadjuvant Therapy Efficacy in Triple-Negative Breast Cancer

In patients with triple-negative breast cancer (TNBC)-the subtype with the poorest prognosis among breast cancers-it is crucial to assess the response to the currently widely employed neoadjuvant treatment (NAT) approaches. This study investigates the correlation between baseline conventional ultrasound (US) and shear-wave elastography (SWE) indicators and the pathological response of TNBC following NAT, with a specific focus on assessing predictive capability in the baseline state. This retrospective analysis was conducted by extracting baseline US features and SWE parameters, categorizing patients based on postoperative pathological grading. A univariate analysis was employed to determine the relationship between ultrasound indicators and pathological reactions. Additionally, we employed a receiver operating characteristic (ROC) curve analysis and multivariate logistic regression methods to evaluate the predictive potential of the baseline US indicators. This study comprised 106 TNBC patients, with 30 (28.30%) in a nonmajor histological response (NMHR) group and 76 (71.70%) in a major histological response (MHR) group. Following the univariate analysis, we found that T staging, dmax values, volumes, margin changes, skin alterations (i.e., thickening and invasion), retromammary space invasions, and supraclavicular lymph node abnormalities were significantly associated with pathological efficacy (p < 0.05). Combining clinical information with either US or SWE independently yielded baseline predictive abilities, with AUCs of 0.816 and 0.734, respectively. Notably, the combined model demonstrated an improved AUC of 0.827, with an accuracy of 76.41%, a sensitivity of 90.47%, a specificity of 55.81%, and statistical significance (p < 0.01). The baseline US and SWE indicators for TNBC exhibited a strong relationship with NAT response, offering predictive insights before treatment initiation, to a considerable extent.

Digital image analysis and machine learning-assisted prediction of neoadjuvant chemotherapy response in triple-negative breast cancer

Background

Pathological complete response (pCR) is associated with favorable prognosis in patients with triple-negative breast cancer (TNBC). However, only 30-40% of TNBC patients treated with neoadjuvant chemotherapy (NAC) show pCR, while the remaining 60-70% show residual disease (RD). The role of the tumor microenvironment (TME) in NAC response in patients with TNBC remains unclear. In this study, we developed a machine learning-based two-step pipeline to distinguish between various histological components in hematoxylin and eosin (H&E)-stained whole slide images (WSIs) of TNBC tissue biopsies and to identify histological features that can predict NAC response.

Methods

H&E-stained WSIs of treatment-naïve biopsies from 85 patients (51 with pCR and 34 with RD) were separated through a stratified 8-fold cross validation strategy for the first step and leave one out cross validation strategy for the second step. A tile-level histology label prediction pipeline and four machine learning classifiers were used to analyze 468,043 tiles of WSIs. The best-trained classifier used 55 texture features from each tile to produce a probability profile during testing. The predicted histology classes were used to generate a histology classification map of the spatial distributions of different tissue regions. A patient-level NAC response prediction pipeline was trained with features derived from paired histology classification maps. The top graph-based features capturing the relevant spatial information across the different histological classes were provided to the radial basis function kernel support vector machine (rbfSVM) classifier for NAC treatment response prediction.

Results

The tile-level prediction pipeline achieved 86.72% accuracy for histology class classification, while the patient-level pipeline achieved 83.53% NAC response (pCR vs. RD) prediction accuracy. The histological class pairs with the strongest NAC response predictive ability were tumor and tumor tumor-infiltrating lymphocytes for pCR and microvessel density and polyploid giant cancer cells for RD.

Conclusion

Our machine learning pipeline can robustly identify clinically relevant histological classes that predict NAC response in TNBC patients and may help guide patient selection for NAC treatment.

Impact of Pathologic Complete Response on the Prognosis of Triple-Negative Breast Cancer Patients: A Cohort Study

Introduction Triple-negative breast cancer (TNBC) is a molecular subtype in which estrogen (ER)/progesterone receptor (PR) and human epidermal growth receptor 2 (HER2) expression does not occur. The objective of this study was to analyze the impact of pathologic complete response (pCR) after neoadjuvant chemotherapy on the prognosis of triple-negative breast cancer (TNBC) patients. Methods This cohort study was conducted in a private-sector oncology clinic located in the city of Teresina, Brazil. Medical charts of 532 breast cancer patients treated from 2007 to 2020 were analyzed. Of these patients, 83 women with TNBC were selected (10 patients were excluded from the study). Univariate and multivariate analyses (Cox regression) were performed to evaluate the impact on patient survival, comparing patients with or without pCR. A significance level of 5% was set. Overall survival (OS) and disease-free survival (DFS) curves were constructed according to the Kaplan-Meier model. Results Angiolymphatic invasion and positive sentinel lymph node were associated with a lower OS and/or DFS in TNBC (p<0.05). The 10-year OS was 78% and 49%, and the 10-year DFS was 97% and 32% in patients with or without pCR, respectively. Conclusion pCR after neoadjuvant chemotherapy was associated with improvement in OS and DFS in TNBC patients.

Prognostic Factors for Triple-Negative Breast Cancer with Residual Disease after Neoadjuvant Chemotherapy

Valid factors to evaluate the prognosis of triple-negative breast cancer (TNBC) with residual disease after neoadjuvant chemotherapy (NAC) are still lacking. We performed this study to explore prognostic factors focusing on genetic alterations and clinicopathology features in non- pathologic complete response (pCR) TNBC patients. Patients initially diagnosed with early-stage TNBC, treated with NAC, and who had residual disease after primary tumor surgery at the China National Cancer Center during 2016 and 2020 were enrolled. Genomic analyses were performed by targeted sequencing for each tumor sample. Univariable and multivariable analyses were conducted to screen prognostic factors for the survival of patients. Fifty-seven patients were included in our study. Genomic analyses showed that TP53 (41/57, 72%), PIK3CA (12/57, 21%), and MET (7/57, 12%), and PTEN (7/57, 12%) alternations commonly occurred. The clinical TNM (cTNM) stage and PIK3CA status were independent prognostic factors of disease-free survival (DFS) (p < 0.001, p = 0.03). A prognostic stratification indicated that patients with clinical stages I &II possessed the best DFS, followed by those with clinical stage III & wild-type PIK3CA. In contrast, patients with clinical stage III & the PIK3CA mutation had the worst DFS. In TNBC patients with residual disease after NAC, prognostic stratification for DFS was observed by combining the cTNM stage and PIK3CA status.

Breast Magnetic Resonance Imaging Can Predict Ki67 Discordance Between Core Needle Biopsy and Surgical Samples

BACKGROUND

Disagreement in assessments of Ki67 expression based on core-needle biopsy and matched surgical samples complicates decisions in the treatment of breast cancer.

PURPOSE

To examine whether preoperative breast MRI could be useful in predicting Ki67 discordance between core-needle biopsy and surgical samples.

STUDY TYPE

Retrospective.

POPULATION

Three hundred and sixty-five breast cancer patients with MRI scans and having both core-needle biopsy and surgical samples from 2017 to 2019.

FIELD STRENGTH/SEQUENCE

3.0 T, T2-weighted iterative decomposition of water and fat with echo asymmetry and least squares estimation sequence, diffusion-weighted sequence using b-values 0/1000, dynamic contrast enhanced image by volume imaged breast assessme NT.

ASSESSMENT

We collected clinicopathologic variables and preoperative MRI features (tumor size, lesion type, shape of mass, spiculated margin, internal enhancement, peri-tumoral edema, intra-tumoral necrosis, multifocal/multicentric, apparent diffusion coefficient [ADC] minimum, ADC mean, ADC maximum, ADC difference).

STATISTICAL TESTS

K-means clustering, multivariable logistic regression, receiver operating characteristic curve.

RESULTS

Sixty-one patients showed Ki67 discordance and 304 patients show Ki67 concordance according to our definition using K-means clustering. Multivariable regression analysis showed that the following parameters were independently associated with Ki67 discordance: peri-tumoral edema, odds ratio (OR) 2.662, 95% confidence interval (CI) 1.432-4.948; ADCmin ≤ 0.829 × 10^-3  mm² /sec, OR 2.180, 95% CI 1.075-4.418; and ADCdiff > 0.317 × 10^-3  mm² /sec, OR 3.365, 95% CI 1.698-6.669. This multivariable model resulted in an AUC of 0.758 (95% CI 0.711-0.802) with sensitivity and specificity being 0.803 and 0.621, respectively.

CONCLUSION

Presence of peri-tumoral edema, smaller ADCmin and greater ADCdiff in preoperative breast MRI may indicate high risk of Ki67 discordance between core-needle biopsy and surgical samples. For patients with these MRI-based risk factors, clinicians should not rely on Ki67 assessment only from core-needle biopsy.

Loss of transcription factor EB dysregulates the G1/S transition and DNA replication in mammary epithelial cells

Triple-negative breast cancer (TNBC) poses significant challenges for treatment given the lack of targeted therapies and increased probability of relapse. It is pertinent to identify vulnerabilities in TNBC and develop newer treatments. Our prior research demonstrated that transcription factor EB (TFEB) is necessary for TNBC survival by regulating DNA repair, apoptosis signaling, and the cell cycle. However, specific mechanisms by which TFEB targets DNA repair and cell cycle pathways are unclear, and whether these effects dictate TNBC survival is yet to be determined. Here, we show that TFEB knockdown decreased the expression of genes and proteins involved in DNA replication and cell cycle progression in MDA-MB-231 TNBC cells. DNA replication was decreased in cells lacking TFEB, as measured by EdU incorporation. TFEB silencing in MDA-MB-231 and noncancerous MCF10A cells impaired progression through the S-phase following G1/S synchronization; however, this proliferation defect could not be rescued by co-knockdown of suppressor RB1. Instead, TFEB knockdown reduced origin licensing in G1 and early S-phase MDA-MB-231 cells. TFEB silencing was associated with replication stress in MCF10A but not in TNBC cells. Lastly, we identified that TFEB knockdown renders TNBC cells more sensitive to inhibitors of Aurora Kinase A, a protein facilitating mitosis. Thus, inhibition of TFEB impairs cell cycle progress by decreasing origin licensing, leading to delayed entry into the S-phase, while rendering TNBC cells sensitive to Aurora kinase A inhibitors and decreasing cell viability. In contrast, TFEB silencing in noncancerous cells is associated with replication stress and leads to G1/S arrest.

Impact of TP53 mutations in Triple Negative Breast Cancer

Identifying triple negative breast cancer (TNBC) patients expected to have poor outcomes provides an opportunity to enhance clinical management. We applied an Evolutionary Action Score to functionally characterize TP53 mutations (EAp53) in 96 TNBC patients and observed that EAp53 stratification may identify TP53 mutations associated with worse outcomes. These findings merit further exploration in larger TNBC cohorts and in patients treated with neoadjuvant chemotherapy regimens.

Application of Artificial Intelligence to Plasma Metabolomics Profiles to Predict Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

There is a need to identify biomarkers predictive of response to neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). We previously obtained evidence that a polyamine signature in the blood is associated with TNBC development and progression. In this study, we evaluated whether plasma polyamines and other metabolites may identify TNBC patients who are less likely to respond to NACT. Pre-treatment plasma levels of acetylated polyamines were elevated in TNBC patients that had moderate to extensive tumor burden (RCB-II/III) following NACT compared to those that achieved a complete pathological response (pCR/RCB-0) or had minimal residual disease (RCB-I). We further applied artificial intelligence to comprehensive metabolic profiles to identify additional metabolites associated with treatment response. Using a deep learning model (DLM), a metabolite panel consisting of two polyamines as well as nine additional metabolites was developed for improved prediction of RCB-II/III. The DLM has potential clinical value for identifying TNBC patients who are unlikely to respond to NACT and who may benefit from other treatment modalities.

Mapping Intellectual Structures and Research Hotspots of Triple Negative Breast Cancer: A Bibliometric Analysis

Background

Triple negative breast cancer (TNBC) is a highly heterogeneous breast cancer subtype with a poor prognosis due to its extremely aggressive nature and lack of effective treatment options. This study aims to summarize the current hotspots of TNBC research and evaluate the TNBC research trends, both qualitatively and quantitatively.

Methods

Scientific publications of TNBC-related studies from January 1, 2010 to October 17, 2020 were obtained from the Web of Science database. The BICOMB software was used to obtain the high-frequency keywords layout. The gCLUTO was used to produce a biclustering analysis on the binary matrix of word-paper. The co-occurrence and collaboration analysis between authors, countries, institutions, and keywords were performed by VOSviewer software. Keyword burst detection was performed by CiteSpace.

Results

A total of 12,429 articles related to TNBC were identified. During 2010-2020, the most productive country/region and institution in TNBC field was the USA and The University of Texas MD Anderson Cancer Center, respectively. Cancer Research, Journal of Clinical Oncology, and Annals of Oncology were the first three periodicals with maximum publications in TNBC research. Eight research hotspots of TNBC were identified by co-word analysis. In the core hotspots, research on neoadjuvant chemotherapy, paclitaxel therapy, and molecular typing of TNBC is relatively mature. Research on immunotherapy and PARP inhibitor for TNBC is not yet mature but is the current focus of this field. Burst detection of keywords showed that studies on TNBC proteins and receptors, immunotherapy, target, and tumor cell migration showed bursts in recent three years.

Conclusion

The current study revealed that TNBC studies are growing. Attention should be paid to the latest hotspots, such as immunotherapy, PARP inhibitors, target, and TNBC proteins and receptors.

The impact of age group in breast cancer survival outcome according to neoadjuvant treatment response: A matched case-control study

This study aimed to investigate the effectiveness of neoadjuvant chemotherapy in patients with breast cancer in different age groups and evaluate the impact of age group on survival outcome according to different treatment responses. Data were retrospectively collected from the cancer registry database of Kaohsiung Medical University Hospital in Taiwan under an approved protocol. Overall, 96 elder patients (aged >50 years) and 96 younger controls (aged ≤50 years) who received neoadjuvant chemotherapy and breast surgical treatment were examined after 1:1 matching. Logistic regression analysis was used to investigate the effectiveness of treatment response in patients of different age groups. Additionally, the Kaplan-Meier estimator and log-rank test were performed to evaluate the effect of age group and treatment response on disease-free and overall survival (OS). Although no direct significant association was found between age group and treatment response, several significant results were found in treatment response stratification analysis. Among 16 pathological complete response (pCR) patients, elder patients showed significantly greater 5-year disease-free survival (DFS) than younger patients (DFS rate, 85.7% vs. 0%, p = 0.041). However, in 176 non-pCR patients, elder patients showed poor DFS compared to younger patients (DFS rate, 16.6% vs. 32.3%; log-rank test, p = 0.031). With limited sample size and study design, our study results demonstrate that patients aged >50 years who achieved pCR after neoadjuvant chemotherapy could obtain better survival outcome than younger patients. However, the younger patients showed no survival benefits regardless of pCR status.

How the variability between computer-assisted analysis procedures evaluating immune markers can influence patients' outcome prediction

Differences between computer-assisted image analysis (CAI) algorithms may cause discrepancies in the identification of immunohistochemically stained immune biomarkers in biopsies of breast cancer patients. These discrepancies have implications for their association with disease outcome. This study aims to compare three CAI procedures (A, B and C) to measure positive marker areas in post-neoadjuvant chemotherapy biopsies of patients with triple-negative breast cancer (TNBC) and to explore the differences in their performance in determining the potential association with relapse in these patients. A total of 3304 digital images of biopsy tissue obtained from 118 TNBC patients were stained for seven immune markers using immunohistochemistry (CD4, CD8, FOXP3, CD21, CD1a, CD83, HLA-DR) and were analyzed with procedures A, B and C. The three methods measure the positive pixel markers in the total tissue areas. The extent of agreement between paired CAI procedures, a principal component analysis (PCA) and Cox multivariate analysis was assessed. Comparisons of paired procedures showed close agreement for most of the immune markers at low concentration. The probability of differences between the paired procedures B/C and B/A was generally higher than those observed in C/A. The principal component analysis, largely based on data from CD8, CD1a and HLA-DR, identified two groups of patients with a significantly lower probability of relapse than the others. The multivariate regression models showed similarities in the factors associated with relapse for procedures A and C, as opposed to those obtained with procedure B. General agreement among the results of CAI procedures would not guarantee that the same predictive breast cancer markers were consistently identified. These results highlight the importance of developing additional strategies to improve the sensitivity of CAI procedures.

Breast-Gynaecological & Immuno-Oncology International Cancer Conference (BGICC) Consensus and Recommendations for the Management of Triple-Negative Breast Cancer

Background: The management of patients with triple-negative breast cancer (TNBC) is challenging with several controversies and unmet needs. During the 12th Breast-Gynaecological & Immuno-oncology International Cancer Conference (BGICC) Egypt, 2020, a panel of 35 breast cancer experts from 13 countries voted on consensus guidelines for the clinical management of TNBC. The consensus was subsequently updated based on the most recent data evolved lately. Methods: A consensus conference approach adapted from the American Society of Clinical Oncology (ASCO) was utilized. The panellists voted anonymously on each question, and a consensus was achieved when ≥75% of voters selected an answer. The final consensus was later circulated to the panellists for critical revision of important intellectual content. Results and conclusion: These recommendations represent the available clinical evidence and expert opinion when evidence is scarce. The percentage of the consensus votes, levels of evidence and grades of recommendation are presented for each statement. The consensus covered all the aspects of TNBC management starting from defining TNBC to the management of metastatic disease and highlighted the rapidly evolving landscape in this field. Consensus was reached in 70% of the statements (35/50). In addition, areas of warranted research were identified to guide future prospective clinical trials.

Impact of Ki-67 Labeling Index on Prognostic Significance of the Chemotherapy Response Score in Women With Tubo-ovarian Cancer Treated With Neoadjuvant Chemotherapy

The chemotherapy response score (CRS) proposed by Bohm and colleagues in 2015 has been validated as a reproducible method for determining histopathologic response of tubo-ovarian carcinoma to neoadjuvant chemotherapy and stratifies tumor response into 3 groups: CRS1 is defined as minimal/no response, CRS2 as moderate response, and CRS3 as marked response. Although described as a 3-tiered system, it essentially works as a 2-tiered system (CRS1/CRS2 vs. CRS3) for assessing prognosis. Here, we analyzed the prognostic value of CRS in a large cohort of tubo-ovarian carcinomas at a tertiary care center and evaluated the potential for Ki-67 labeling index on post-neoadjuvant chemotherapy samples to provide additional prognostic information. We included 170 patients with tubo-ovarian carcinoma treated with neoadjuvant chemotherapy followed by interval debulking surgery. We determined CRS for each case by reviewing slides from the interval debulking surgery resection specimen and calculated progression-free survival and overall survival. For each case with residual disease (CRS1 and CRS2, n=123, 72%), we also performed Ki-67 antibody staining and determined both average and highest Ki-67 labeling index. Consistent with prior studies, patients in our cohort with CRS1 and CRS2 showed significantly shorter progression-free survival and overall survival compared with CRS3. Further, in the subset of cases with CRS1 and CRS2, Ki-67 labeling index was predictive of OS at multiple cutoff points. An average Ki-67 labeling index of 20% (log rank test P-value: 0.0004) or a highest Ki-67 labeling index of 50% (log rank test P-value: 0.0002) could provide a practically useful cutoff. Multivariable cox proportional hazard model showed worse overall survival with both, average Ki-67 >20% (hazard ratios: 2.02, P-value: 0.00422, confidence interval: 1.25-3.28) and highest Ki-67 >50% (hazard ratios: 1.88, P-value: 0.0205, confidence interval: 1.1-3.2). We propose adding Ki-67 labeling index to CRS to provide additional prognostic separation between patients with CRS1 and CRS2.

Early ultrasound evaluation identifies excellent responders to neoadjuvant systemic therapy among patients with triple-negative breast cancer

BACKGROUND

Heterogeneity exists in the response of triple-negative breast cancer (TNBC) to standard anthracycline (AC)/taxane-based neoadjuvant systemic therapy (NAST), with 40% to 50% of patients having a pathologic complete response (pCR) to therapy. Early assessment of the imaging response during NAST may identify a subset of TNBCs that are likely to have a pCR upon completion of treatment. The authors aimed to evaluate the performance of early ultrasound (US) after 2 cycles of neoadjuvant NAST in identifying excellent responders to NAST among patients with TNBC.

METHODS

Two hundred fifteen patients with TNBC were enrolled in the ongoing ARTEMIS (A Robust TNBC Evaluation Framework to Improve Survival) clinical trial. The patients were divided into a discovery cohort (n = 107) and a validation cohort (n = 108). A receiver operating characteristic analysis with 95% confidence intervals (CIs) and a multivariate logistic regression analysis were performed to model the probability of a pCR on the basis of the tumor volume reduction (TVR) percentage by US from the baseline to after 2 cycles of AC.

RESULTS

Overall, 39.3% of the patients (42 of 107) achieved a pCR. A positive predictive value (PPV) analysis identified a cutoff point of 80% TVR after 2 cycles; the pCR rate was 77% (17 of 22) in patients with a TVR ≥ 80%, and the area under the curve (AUC) was 0.84 (95% CI, 0.77-0.92; P < .0001). In the validation cohort, the pCR rate was 44%. The PPV for pCR with a TVR ≥ 80% after 2 cycles was 76% (95% CI, 55%-91%), and the AUC was 0.79 (95% CI, 0.70-0.87; P < .0001).

CONCLUSIONS

The TVR percentage by US evaluation after 2 cycles of NAST may be a cost-effective early imaging biomarker for a pCR to AC/taxane-based NAST.

Phosphatidylserine-exposing tumor-derived microparticles exacerbate coagulation and cancer cell transendothelial migration in triple-negative breast cancer

Background: Neoadjuvant chemotherapy is relevant to the formation of thromboembolism and secondary neoplasms in triple-negative breast cancer (TNBC). Chemotherapy-induced breast cancer cell-derived microparticles (BCMPs) may have important thrombogenic and pro-metastatic effects on platelets and endothelium, which may be related to the expression and distribution of phosphatidylserine (PS). However, investigating these interactions is challenging due to technical limitations. Methods: A study was conducted in 20 healthy individuals and 18 patients who had been recently diagnosed with TNBC and were undergoing neoadjuvant chemotherapy with doxorubicin and cyclophosphamide. BCMPs were isolated from patient blood samples and doxorubicin-treated breast cancer cell lines. Their structure and morphology were studied by electron microscopy and antigen levels were measured by fluorescence-activated cell sorting. In an inhibition assay, isolated BCMPs were pretreated with lactadherin or tissue factor antibodies. Platelets isolated from healthy subjects were treated with BCMPs and coagulation time, fibrin formation, and expression of intrinsic/extrinsic factor Xase (FXa) and thrombin were evaluated. The effects of BCMPs on endothelial thrombogenicity and integrity were assessed by confocal microscopy, electron microscopy, measurement of intrinsic/extrinsic FXa, prothrombinase assay, and transwell permeability assay. Results: Neoadjuvant chemotherapy significantly increased the expression of PS+ BCMPs in patient plasma. Its expression was associated with a rapid increase in procoagulant activity. Treatment with lactadherin, a PS-binding scavenging molecule, markedly reduced the adhesion of BCMPs and abolished their procoagulant activity, but this was not observed with tissue factor antibody treatment. Intravenous injection of BCMPs in mice induced a significant hypercoagulable state, reducing the extent of plasma fibrinogen and promoting the appearance of new thrombus. Cancer cells incubated with doxorubicin released large numbers of PS+ BCMPs, which stimulated and transformed endothelial cells into a procoagulant phenotype and increased the aggregation and activation of platelets. Moreover, cancer cells exploited this BCMP-induced endothelial leakiness and showed promoted metastasis. Pretreatment with lactadherin increased uptake of both PS+ BCMPs and cancer cells by endothelial cells and limited the transendothelial migration of cancer cells. Conclusion: Lactadherin, a biosensor that we developed, was used to study the extracellular vesicle distribution of PS, which revealed a novel PS+ BCMPs administrative axis that initiated a local coagulation cascade and facilitated metastatic colonization of circulating cancer cells.

Neoadjuvant Chemotherapy of Triple-Negative Breast Cancer: Evaluation of Early Clinical Response, Pathological Complete Response Rates, and Addition of Platinum Salts Benefit Based on Real-World Evidence

Simple Summary

Neoadjuvant chemotherapy (NACT) is the standard treatment for early-stage triple-negative breast cancer (TNBC). Achieving pathological complete response (pCR) is considered an essential prognostic factor with favorable long-term outcomes. The administration of NACT regimens with platinum salts is associated with a higher pCR rate. However, with unclear treatment guidelines and at the expense of a higher incidence of adverse events. Identifying patients and circumstances in which the benefits of platinum NACT outweigh inconveniences is still an ongoing challenge. Considering early clinical response (ECR) after the initial standard NACT cycles together with other suitable predictors could be useful to decide about the administration of platinum salts in clinical practice. The results of this large single institutional retrospective study of consecutive patients showed the significant role of adding platinum salts in older patients with high-proliferative early responded tumors and persisted lymph nodes involvement regardless of BRCA1/2 status.

Abstract

Pathological complete response (pCR) achievement is undoubtedly the essential goal of neoadjuvant therapy for breast cancer, directly affecting survival endpoints. This retrospective study of 237 triple-negative breast cancer (TNBC) patients with a median follow-up of 36 months evaluated the role of adding platinum salts into standard neoadjuvant chemotherapy (NACT). After the initial four standard NACT cycles, early clinical response (ECR) was assessed and used to identify tumors and patients generally sensitive to NACT. BRCA1/2 mutation, smaller unifocal tumors, and Ki-67 ≥ 65% were independent predictors of ECR. The total pCR rate was 41%, the achievement of pCR was strongly associated with ECR (OR = 15.1, p < 0.001). According to multivariable analysis, the significant benefit of platinum NACT was observed in early responders ≥45 years, Ki-67 ≥ 65% and persisted lymph node involvement regardless of BRCA1/2 status. Early responders with pCR had a longer time to death (HR = 0.28, p < 0.001) and relapse (HR = 0.26, p < 0.001). The pCR was achieved in only 7% of non-responders. However, platinum salts favored non-responders’ survival outcomes without statistical significance. Toxicity was significantly often observed in patients with platinum NACT (p = 0.003) but not for grade 3/4 (p = 0.155). These results based on real-world evidence point to the usability of ECR in NACT management, especially focusing on the benefit of platinum salts.

Combinational Treatment of Doxorubicin With Neoadjuvant Docetaxel for Different Subtypes of Patients With Breast Cancer

Aim:

The aim of this study is to characterize the effect of chemotherapy drug doxorubicin with neoadjuvant drug docetaxel for different molecular subtypes.

Methods:

A total of 83 patients with late-stage breast cancer were chosen to undergo treatment and compared to these patients to the combinational treatment to identify the molecular characteristics that can predict the responses.

Results:

Total response rate is 81.9% (68/83 patients). Among them, 7 patients show pathological complete response of 8.4%, 12 patients show clinical complete response of 14.5%, 49 patients show partial response of 59%, and 15 patients show stable disease of 18.1%. The comparison among different subtypes of breast cancer, including luminal A, luminal B, basal-like, and ERBB2⁺ subtypes, did not show statistical significant differences to the treatment of combinational treatment for the complete response rate, including pathological complete response and clinical complete response. Comparing with luminal A and luminal B subtypes, the ERBB2⁺ and basal-like subtypes have better complete response and response rate rates. The disease-free survival rate and overall survival rate at 29 months after treatment did not show statistical significant differences among different subtypes of patients with breast cancer.

Conclusion:

The molecular subtypes of breast cancer can predict responses to the combinational treatment of doxorubicin with docetaxel, and ERBB2⁺ and basal-like subtypes have better response rate and complete response rate. There is correlation of estrogen receptor and KI-67 level changes with response rate as well, where KI-67 high patients are more sensitive to the treatment.

Novel biomarkers and prediction model for the pathological complete response to neoadjuvant treatment of triple-negative breast cancer

Objective: To develop and validate a prediction model for the pathological complete response (pCR) to neoadjuvant chemotherapy (NCT) of triple-negative breast cancer (TNBC). Methods: We systematically searched Gene Expression Omnibus, ArrayExpress, and PubMed for the gene expression profiles of operable TNBC accessible to NCT. Molecular heterogeneity was detected with hierarchical clustering method, and the biological profiles of differentially expressed genes were investigated by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analyses, and Gene Set Enrichment Analysis (GSEA). Next, machine-learning algorithms including random-forest analysis and least absolute shrinkage and selection operator (LASSO) analysis were synchronously performed and, then, the intersected proportion of significant genes was undergone binary logistic regression to fulfill variables selection. The predictive response score (pRS) system was built as the product of the gene expression and coefficient obtained from the logistic analysis. Last, the cohorts were randomly divided in a 7:3 ratio into training cohort and validation cohort for the introduction of a robust model, and a nomogram was constructed with the independent predictors for pCR rate. Results: A total of 217 individuals from four cohort datasets (GSE32646, GSE25065, GSE25055, GSE21974) with complete clinicopathological information were included. Based on the microarray data, a six-gene panel (ATP4B, FBXO22, FCN2, RRP8, SMERK2, TET3) was identified. A robust nomogram, adopting pRS and clinical tumor size stage, was established and the performance was successively validated by calibration curves and receiver operating characteristic curves with the area under curve 0.704 and 0.756, respectively. Results of GSEA revealed that the biological processes including apoptosis, hypoxia, mTORC1 signaling and myogenesis, and oncogenic features of EGFR and RAF were in proactivity to attribute to an inferior response. Conclusions: This study provided a robust prediction model for pCR rate and revealed potential mechanisms of distinct response to NCT in TNBC, which were promising and warranted to further validate in the perspective.

Downregulation of miR-205 contributes to epithelial-mesenchymal transition and invasion in triple-negative breast cancer by targeting HMGB1-RAGE signaling pathway

Our aim was to study the regulatory molecule networks involved in the epithelial-to-mesenchymal transition and thus promoting the early onset of metastasis in triple-negative breast cancer (TNBC). Forty pairs of human TNBC and their adjacent normal breast tissues were analyzed by real-time PCR and immunochemistry to demonstrate the correlation between the miR-205 expression and clinicopathological characteristics. In vitro, 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide assay, cell migration, and invasion assay were used to detect the cell growth and invasive ability of TNBC cells after upregulation or downregulation of miR-205 expression. Luciferase reporter assay was used to confirm the potential target directly influenced by miR-205. Our results showed that miR-205 abnormal expression may be involved and associated with the biological traits of TNBC. Ectopic expression of miR-205 not only inhibited cell growth, but also suppressed migration and invasion of mesenchymal-like TNBC cells. In addition, we found that overexpression of miR-205 significantly suppressed HMGB1 by binding its 3′-untranslated region, and that miR-205 was inversely correlated with the expression of HMGB1 and RAGE in cell lines and clinical samples. Our study illustrated that miR-205 was a tumor suppressor in TNBC, which attenuated the viability and the acquisition of the epithelial-to-mesenchymal transition phenotype TNBC cells at least partially exerted through targeting of HMGB1–RAGE signaling pathway.

Neoadjuvant Treatment for Triple Negative Breast Cancer: Recent Progresses and Challenges

Triple negative breast cancer (TNBC) is an aggressive breast cancer with historically poor outcomes, primarily due to the lack of effective targeted therapies. The tumor molecular heterogeneity of TNBC has been well recognized, yet molecular subtype driven therapy remains lacking. While neoadjuvant anthracycline and taxane-based chemotherapy remains the standard of care for early stage TNBC, the optimal chemotherapy regimen is debatable. The addition of carboplatin to anthracycline, cyclophosphamide, and taxane (ACT) regimen is associated with improved complete pathologic response (pCR). Immune checkpoint inhibitor (ICI) combinations significantly increase pCR in TNBC. Increased tumor infiltrating lymphocyte (TILs) or the presence of DNA repair deficiency (DRD) mutation is associated with increased pCR. Other targets, such as poly-ADP-ribosyl polymerase inhibitors (PARPi) and Phosphatidylinositol-3-kinase/Protein Kinase B/mammalian target of rapamycin (PI3K-AKT-mTOR) pathway inhibitors, are being evaluated in the neoadjuvant setting. This review examines recent progress in neoadjuvant therapy of TNBC, including platinum, ICI, PARPi, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) pathway targeted therapies, and novel tumor microenvironment (TME) targeted therapy, in addition to biomarkers for the prediction of pCR.

Prognostic Value of Ki-67 in Patients With Resected Triple-Negative Breast Cancer: A Meta-Analysis

Background: Ki-67 is a widely used marker of tumor proliferation, but the prognostic value of ki-67 in triple-negative breast cancer (TNBC) has not been comprehensively reviewed. This meta-analysis was conducted to evaluate the association between ki-67 expression and survival of patients with resected TNBC.

Materials and Methods: Relevant studies, evaluating the prognostic impact of pretreatment ki-67 in resected TNBC patients, were identified from PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and Cochrane Library until March 14, 2019. Hazard ratios (HRs) with 95% confidence intervals (CI) were calculated as effect values for disease-free survival (DFS) and overall survival (OS).

Results: In present meta-analysis, 35 studies with 7,716 enrolled patients were eligible for inclusion. Pooled results showed that a high ki-67 expression was significantly associated with poor DFS (HR = 1.73, 95% CI: 1.45–2.07, p < 0.001) and poor OS (HR = 1.65, 95% CI: 1.27–2.14, p < 0.001) in resected TNBC. In the subgroup analysis, when a cutoff of Ki-67 staining ≥40% was applied, the pooled HR for DFS and OS was 2.30 (95% CI 1.54–3.44, p < 0.001) and 2.95 (95% CI 1.67–5.19, p < 0.001), respectively.

Conclusion: A high Ki-67 expression is a poor prognostic factor of resected TNBC. The cut-off of ki-67 ≥40% is associated with a greater risk of recurrence and death compared with lower expression rates, despite the Ki-67 threshold with the greatest prognostic significance is as yet unknown.

The predictive and prognostic value of Foxp3+/CD25+ regulatory T cells and PD-L1 expression in triple negative breast cancer

Recent significant developments in cancer immunotherapy have led to important breakthroughs and paradigm shifts in the treatment of malignancy. Although breast cancer traditionally has been considered less immunogenic, triple-negative breast cancer (TNBC) is the most immunogenic subtype with more stromal tumor-infiltrating lymphocytes (TILs) and higher programmed death-ligand 1 (PD-L1) expression. The goal of this study is to evaluate regulatory T cells (Tregs) and PD-L1 expression in TNBC, as well as their associations with clinicopathologic features and the outcomes. Tissue microarrays (TMA) of biopsy and resection specimens of 43 TNBC patients who underwent breast biopsy, neoadjuvant chemotherapy, and mastectomy were prepared. The number of Foxp3+ Tregs, Foxp3+/CD25+ Tregs, and expression of PD-L1 in tumor cells (PD-L1 TCs) and TILs (PD-L1 TILs) were assessed by immunohistochemistry. PD-L1 expression combined positive score (PD-L1 CPS) was calculated according to the manufacturer's guidelines. PD-L1 expression was detected in 72% of the cases, and it expressed in a higher percentage and higher intensity in TILs than TCs in TNBC (p = 0.006 and 0.0005, respectively). PD-L1 TCs, PD-L1 TILs, and PD-L1 CPS were all positively associated with pathologic complete response (pCR) (p = 0.04, 0.03, and 0.02, respectively). PD-L1 TILs and PD-L1 CPS also correlated with TILs and tumor infiltrating lymphocyte volume (TILV). Foxp3+ Tregs and Foxp3+/CD25+ Tregs had strong positive correlation (r = 0.89), and they were positively associated with TILs, TILV, and PD-L1 expression. Foxp3+/CD25+ Tregs, PD-L1 TCs, and PD-L1 CPS were positively correlated with better overall survival (p = 0.04, 0.04 and 0.01, respectively).

A two-gene epigenetic signature for the prediction of response to neoadjuvant chemotherapy in triple-negative breast cancer patients

Background

Pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) varies between 30 and 40% approximately. To provide further insight into the prediction of pCR, we evaluated the role of an epigenetic methylation-based signature.

Methods

Epigenetic assessment of DNA extracted from biopsy archived samples previous to NAC from TNBC patients was performed. Patients included were categorized according to previous response to NAC in responder (pCR or residual cancer burden, RCB = 0) or non-responder (non-pCR or RCB > 0) patients. A methyloma study was performed in a discovery cohort by the Infinium HumanMethylation450 BeadChip (450K array) from Illumina. The epigenetic silencing of those methylated genes in the discovery cohort were validated by bisulfite pyrosequencing (PyroMark Q96 System version 2.0.6, Qiagen) and qRT-PCR in an independent cohort of TN patients and in TN cell lines.

Results

Twenty-four and 30 patients were included in the discovery and validation cohorts, respectively. In the discovery cohort, nine genes were differentially methylated: six presented higher methylation in non-responder patients (LOC641519, LEF1, HOXA5, EVC2, TLX3, CDKL2) and three greater methylation in responder patients (FERD3L, CHL1, and TRIP10). After validation, a two-gene (FER3L and TRIP10) epigenetic score predicted RCB = 0 with an area under the ROC curve (AUC) = 0.905 (95% CI = 0.805–1.000). Patients with a positive epigenetic two-gene score showed 78.6% RCB = 0 versus only 10.7% RCB = 0 if signature were negative.

Conclusions

These results suggest that pCR in TNBC could be accurately predicted with an epigenetic signature of FERD3L and TRIP10 genes. Further prospective validation of these findings is warranted.

Electronic supplementary material

The online version of this article (10.1186/s13148-019-0626-0) contains supplementary material, which is available to authorized users.

PD-L1 Expression in TNBC: A Predictive Biomarker of Response to Neoadjuvant Chemotherapy?

Triple negative breast cancer (TNBC) has an aggressive clinical behaviour, with a poorer prognosis compared to other subtypes. Recently, tumor-infiltrating lymphocytes (TILs) have been proposed as a predictive biomarker for a better clinical outcome and pathological response (pR) after neoadjuvant chemotherapy (NACT) in TNBC. These data confirm the role of the immune system in the neoplastic progression and in the response to therapy. We performed a retrospective analysis of 54 pre-NACT biopsies of TNBC and compared both the percentage of stromal TILs and the degree of PD-L1 expression with the extent of pR to standard NACT. A pathological complete response (pCR) was achieved in 35% of cases. Univariate analysis showed (i) a significant association between PD-L1 expression in ≥25% of neoplastic cells and the achievement of a pCR (p = 0.024); (ii) a significantly higher frequency of pCR in cases showing ≥50% stromal TILs (p < 0.001). However in the multivariate analysis only PD-L1 expression on tumor cells remained significantly associated with pCR (OR = 1,13; 95% CI 1,01–1,27), suggesting that the expression of this biomarker could be associated with a subpopulation of TNBC more likely to respond to chemotherapy. These data need to be confirmed by larger studies.