Androgen receptor expression and response to chemotherapy in breast cancer patients treated in the neoadjuvant TECHNO and PREPARE trial

Androgen receptor: Structure, signaling, function and potential drug discovery biomarker in different breast cancer subtypes

The Androgen Receptor (AR) is emerging as an important factor in the pathogenesis of breast cancer (BC), which is the most common malignancy worldwide. >70 % of AR expression in primary and metastatic breast tumors has been observed which suggests that AR may be a new marker and a potential therapeutic target among AR-positive BC patients. Biological insight into AR-positive breast cancer reveals that AR may cross-talk with several vital signaling pathways, including key molecules and receptors. Downstream signaling of AR might also affect many clinically important pathways that are emerging as clinical targets in BC. AR exhibits different behaviors depending on the breast cancer molecular subtype. Preliminary clinical research using AR-targeted drugs, which have already been FDA-approved for prostate cancer (PC), has given promising results for AR-positive breast cancer patients. However, since AR positivity's prognostic and predictive value remains uncertain, it is difficult to identify and stratify patients who would benefit from AR-targeted therapies alone. Thus, the need of the hour is to target the androgen receptor as a monotherapy or in combination with other conventional therapies which has proven to be an effective clinical strategy for the treatment of prostate cancer patients, and these therapeutic strategies are increasingly being investigated in breast cancer. Therefore, in this manuscript, we review the role of AR in various cellular processes that promote tumorigenesis and aggressiveness, in different subtypes of breast cancer, as well as discuss ongoing efforts to target AR for the more effective treatment and prevention of breast cancer.

Core Needle Biopsy Accuracy for Androgen Receptor Expression in Invasive Breast Cancer

OBJECTIVE

 Breast cancer (BC) biomarkers, such as hormone receptors expression, are crucial to guide therapy in BC patients. Antiandrogens have been studied in BC; however, limited data are available on androgen receptor (AR) expression test methodology. We aim to report the core needle biopsy (CNB) accuracy for AR expression in BC.

METHODS

 Patients diagnosed with stage I-III invasive BC from a single institution were included. Androgen receptor expression was evaluated by immunohistochemistry (IHC) using 1 and 10% cutoff and the AR expression in surgical specimens (SS) was the gold standard. Kappa coefficients were used to evaluate the intraprocedural agreement.

RESULTS

 A total of 72 patients were included, with a mean age of 61 years old and 84% were Luminal A or B tumors. The prevalence of AR expression in all BC samples was 87.5% using a cutoff ≥ 10% in SS. With a cutoff value ≥ 1%, CNB had an accuracy of 95.8% (Kappa value = 0.645; 95% confidence interval [CI]: 0.272-1.000; p < 0.001) and 86.1% (Kappa value = 0.365; 95% CI: 0.052-0.679; p < 0.001) when ≥ 10% cutoff was used for AR positivity. Androgen receptor expression in CNB (cutoff ≥ 1%) had a sensitivity of 98.5%, specificity of 60%, positive predictive value of 97.0%, and a negative predictive value of 76.9% in the detection of AR expression in SS.

CONCLUSION

 Core needle biopsy has good accuracy in evaluating AR expression in BC. The accuracy of CNB decreases with higher cutoff values for AR positivity.

Newly Developed Targeted Therapies Against the Androgen Receptor in Triple-Negative Breast Cancer: A Review

Among different types of breast cancers (BC), triple-negative BC (TNBC) amounts to 15% to 20% of breast malignancies. Three principal characteristics of TNBC cells are (i) extreme aggressiveness, (ii) absence of hormones, and (iii) growth factor receptors. Due to the lack or poor expression of the estrogen receptor, human epidermal growth factor receptor 2, and progesterone receptor, TNBC is resistant to hormones and endocrine therapies. Consequently, chemotherapy is currently used as the primary approach against TNBC. Expression of androgen receptor (AR) in carcinoma cells has been observed in a subset of patients with TNBC; therefore, inhibiting androgen signaling pathways holds promise for TNBC targeting. The new AR inhibitors have opened up new therapy possibilities for BC patients carrying AR-positive TNBC cells. Our group provides a comprehensive review of the structure and function of the AR and clinical evidence for targeting the cell's nuclear receptor in TNBC. We updated AR agonists, inhibitors, and antagonists. We also presented a new era of genetic manipulating CRISPR/Cas9 and nanotechnology as state-of-the-art approaches against AR to promote the efficiency of targeted therapy in TNBC. SIGNIFICANCE STATEMENT: The lack of effective treatment for triple-negative breast cancer is a health challenge. The main disadvantages of existing treatments are their side effects, due to their nonspecific targeting. Molecular targeting of cellular receptors, such as androgen receptors, increased expression in malignant tissues, significantly improving the survival rate of breast cancer patients.

Correlation between Androgen Receptor Expression in Luminal B (HER-2 Negative) Breast Cancer and Disease Outcomes

(1) Background: Hormone receptor positive breast cancer is a subtype of breast cancer with relatively good prognosis, but luminal B (HER−2 negative) breast cancer has a higher risk of recurrence and metastasis. Patients with endocrine therapy resistance and chemotherapy insensitivity have poor prognosis. Androgen receptor (AR) is widely expressed in breast cancer, but there is no clear conclusion about its function and correlation with prognosis in luminal B breast cancer. Further research is needed to reveal the role of AR in luminal B (HER−2 negative) breast cancer. (2) Methods: Retrospectively analyzed patients with early−stage luminal B breast cancer. The correlation between AR and its associated indexes with long−term survival was determined. (3) Results: A total of 985 patients were included with 143 treated by neoadjuvant therapy. Of these, 83.5% of the patients had AR expression ≥65%. High AR expression was associated with good disease−free survival (DFS) and overall survival (OS). In the neoadjuvant population, AR/estrogen receptor (ER) > 1.06 and residual tumor Ki67 > 23% had significantly worse DFS. (4) Conclusion: Low AR (<65%) expression is associated with poor prognosis in luminal B (HER−2 negative) breast cancer patients. High AR/ER and residual tumor Ki67 were associated with poor DFS in neoadjuvant group with a cutoff value of AR/ER > 1.06 and residual tumor Ki67 > 23%.

Androgen receptor expression and its prognostic value in T1N0 luminal/HER2- breast cancer

Purpose: The authors aimed to evaluate the prognostic and predictive value of androgen receptor (AR) expression in patients with luminal/human EGFR2 negative (HER2-) T1N0 breast cancer. Methods: The cohort in this retrospective study comprised 471 patients with luminal/HER2- T1N0 breast cancer who had undergone surgery between 2013 and 2017 in the authors' center. Results: Androgen receptor (AR)+ tumors were associated with favorable characteristics. AR+ patients had better 5-year recurrence-free survival rates and the risk of recurrence was greater for AR- than for AR+ patients. AR- status predicted the failure of adjuvant endocrine therapy with aromatase inhibitors and of adjuvant chemotherapy with docetaxel plus cyclophosphamide. Conclusion: AR+ expression is significantly related to a better prognosis. AR expression may be an additional biomarker for both endocrine and chemotherapy responsiveness.

Development and validation of a nomogram based on pretreatment dynamic contrast-enhanced MRI for the prediction of pathologic response after neoadjuvant chemotherapy for triple-negative breast cancer

OBJECTIVES

To develop a nomogram based on pretreatment dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in patients with triple-negative breast cancer (TNBC).

METHODS

A total of 108 female patients with TNBC treated with neoadjuvant chemotherapy followed by surgery between January 2017 and October 2020 were enrolled. The patients were randomly divided into the primary cohort (n = 87) and validation cohort (n = 21) at a ratio of 4:1. The pretreatment DCE-MRI and clinicopathological features were reviewed and recorded. Univariate analysis and multivariate logistic regression analyses were used to determine the independent predictors of pCR in the primary cohort. A nomogram was developed based on the predictors, and the predictive performance of the nomogram was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). The validation cohort was used to test the predictive model.

RESULTS

Tumor volume measured on DCE-MRI, time to peak (TTP), and androgen receptor (AR) status were identified as independent predictors of pCR. The AUCs of the nomogram were 0.84 (95% CI: 0.75-0.93) and 0.79 (95% CI: 0.59-0.99) in the primary cohort and validation cohort, respectively.

CONCLUSIONS

Pretreatment DCE-MRI could predict pCR after NAC in patients with TNBC. The nomogram can be used to predict the probability of pCR and may help individualize treatment.

KEY POINTS

• Pretreatment DCE-MRI findings can predict pathologic complete response (pCR) after neoadjuvant chemotherapy in patients with triple-negative breast cancer. • A nomogram based on the independent predictors of tumor volume measured on DCE-MRI, time to peak, and androgen receptor status could help personalized cancer treatment in TNBC patients.

Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer

Objective

To investigate whether radiomics features extracted from multi-parametric MRI combining machine learning approach can predict molecular subtype and androgen receptor (AR) expression of breast cancer in a non-invasive way.

Materials and Methods

Patients diagnosed with clinical T2–4 stage breast cancer from March 2016 to July 2020 were retrospectively enrolled. The molecular subtypes and AR expression in pre-treatment biopsy specimens were assessed. A total of 4,198 radiomics features were extracted from the pre-biopsy multi-parametric MRI (including dynamic contrast-enhancement T1-weighted images, fat-suppressed T2-weighted images, and apparent diffusion coefficient map) of each patient. We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). The performances of binary classification models were assessed via the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). And the performances of multiclass classification models were assessed via AUC, overall accuracy, precision, recall rate, and F1-score.

Results

A total of 162 patients (mean age, 46.91 ± 10.08 years) were enrolled in this study; 30 were low-AR expression and 132 were high-AR expression. HR+/HER2− cancers were diagnosed in 56 cases (34.6%), HER2+ cancers in 81 cases (50.0%), and TNBC in 25 patients (15.4%). There was no significant difference in clinicopathologic characteristics between low-AR and high-AR groups (P > 0.05), except the menopausal status, ER, PR, HER2, and Ki-67 index (P = 0.043, <0.001, <0.001, 0.015, and 0.006, respectively). No significant difference in clinicopathologic characteristics was observed among three molecular subtypes except the AR status and Ki-67 (P = <0.001 and 0.012, respectively). The Multilayer Perceptron (MLP) showed the best performance in discriminating AR expression, with an AUC of 0.907 and an accuracy of 85.8% in the testing dataset. The highest performances were obtained for discriminating TNBC vs. non-TNBC (AUC: 0.965, accuracy: 92.6%), HER2+ vs. HER2− (AUC: 0.840, accuracy: 79.0%), and HR+/HER2− vs. others (AUC: 0.860, accuracy: 82.1%) using MLP as well. The micro-AUC of MLP multiclass classification model was 0.896, and the overall accuracy was 0.735.

Conclusions

Multi-parametric MRI-based radiomics combining with machine learning approaches provide a promising method to predict the molecular subtype and AR expression of breast cancer non-invasively.

Prognostic value of androgen receptor expression and molecular alterations in metastatic triple-negative or low hormone receptor breast carcinomas

Metastatic breast carcinomas (BCs) with phenotype of triple-negative (TNBC) or low hormonal receptor levels [estrogen receptor (ER)/progesterone receptor (PR) < 10% and HER2-] are mainly treated with cytotoxic chemotherapy. Targeting androgen receptor (AR) pathway may represent a potential new therapeutic strategy in such group of BCs. We evaluated AR expression by immunohistochemistry and genetic alterations by next-generation sequencing. Among 114 metastatic BCs, 37 (32.5%) cases showed AR expression and 77 (67.5%) lacked AR expression. Statistical analysis revealed that AR expression is associated with older age, lobular carcinoma, positive ER and positive PR in primary tumors, and lymph node metastasis. Patients with AR-positive tumors had significantly longer metastatic intervals and overall survivals. In addition, AR-positive tumors had significantly higher rate of PI3CA mutation. Our results demonstrated that AR expression has prognostic value in this subgroup of metastatic BCs and tumors with AR expression had different molecular alterations compared with those without AR expression.

Cancer stem cells in TNBC

Triple-negative breast cancer (TNBC) is a broad collection of breast cancer that tests negative for estrogen receptors (ER), progesterone receptors (PR), and excess human epidermal growth factor receptor 2 (HER2) protein. TNBC is considered to have poorer prognosis than other types of breast cancer because of a lack of effective therapeutic targets. The success of precision cancer therapies relies on the clarification of key molecular mechanisms that drive tumor growth and metastasis; however, TNBC is highly heterogeneous in terms of their cellular lineage composition and the molecular nature within each individual case. In particular, the rare and sometimes slow cycling cancer stem cells (CSCs) can provide effective means for TNBC to resist various treatments. Single cell analysis technologies, including single-cell RNA-seq (scRNA-seq) and proteomics, provide an avenue to unravel patient-level intratumoral heterogeneity by identifying CSCs populations, CSC biomarkers and the range of tumor microenvironment cellular constituents that contribute to tumor growth. This review discusses the emerging evidence for the role of CSCs in driving TNBC incidence and the therapeutic implications in manipulating molecular signaling against this rare cell population for the control of this deadly disease.

Identifying High-Risk Triple-Negative Breast Cancer Patients by Molecular Subtyping

<b><i>Introduction:</i></b> Triple-negative breast cancer (TNBC) is considered the most aggressive type of breast cancer (BC) with limited options for therapy. TNBC is a heterogeneous disease and tumors have been classified into TNBC subtypes using gene expression profiling to distinguish basal-like 1, basal-like 2, immunomodulatory, mesenchymal, mesenchymal stem-like, luminal androgen receptor (LAR), and one nonclassifiable group (called unstable). <b><i>Objectives:</i></b> The aim of this study was to verify the clinical relevance of molecular subtyping of TNBCs to improve the individual indication of systemic therapy. <b><i>Patients and Methods:</i></b> Molecular subtyping was performed in 124 (82%) of 152 TNBC tumors that were obtained from a prospective, multicenter cohort including 1,270 histopathologically confirmed invasive, nonmetastatic BCs (NCT 01592825). Treatment was guideline-based. TNBC subtypes were correlated with recurrence-free interval (RFI) and overall survival (OS) after 5 years of observation. <b><i>Results:</i></b> Using PAM50 analysis, 87% of the tumors were typed as basal with an inferior clinical outcome compared to patients with nonbasal tumors. Using the TNBCtype-6 classifier, we identified 23 (15%) of TNBCs as LAR subtype. After standard adjuvant or neoadjuvant chemotherapy, patients with LAR subtype showed the most events for 5-year RFI (66.7 vs. 80.6%) and the poorest probability of 5-year OS (60.0 vs. 84.4%) compared to patients with non-LAR disease (RFI: adjusted hazard ratio [aHR] = 1.87, 95% confidence interval [CI] 0.69–5.05, <i>p</i> = 0.211; OS: aHR = 2.74, 95% CI 1.06–7.10, <i>p</i> = 0.037). <b><i>Conclusion:</i></b> Molecular analysis and subtyping of TNBC may be relevant to identify patients with LAR subtype. These cancers seem to be less sensitive to conventional chemotherapy, and new treatment options, including androgen receptor-blocking agents and immune checkpoint inhibitors, have to be explored.

Role of androgen receptor expression in early stage ER+/PgR-/HER2- breast cancer

BACKGROUND

Progesterone receptor (PgR) negative breast cancer (BC) is an aggressive subtype with poor prognosis and reduced response to endocrine treatments. Several studies have suggested that androgen receptor (AR) expression is associated with a favorable tumor biology, longer recurrence free survival (RFS), and overall survival. In the literature no data exist regarding the role of AR expression in early stage estrogen receptor (ER)+/PgR- BCs. The aim of this study was to evaluate the prognostic role of AR expression in this setting.

PATIENTS AND METHODS

This is a monocentric retrospective study in which 208 patients who underwent surgical intervention for ER+/PgR-/Human Epidermal growth factor Receptor 2 (HER2)- BC were included. The primary objective was to analyze the relationship between AR expression and RFS.

RESULTS

At a median follow-up of 77 months, 75 patients (36%) had a disease relapse (all sites included). AR expression was significantly higher in patients who did not relapse compared with those who relapsed with an impact on RFS (hazard ratio [HR] = 0.99, p = 0.025). Patients with AR expression ⩾80% had a lower risk of relapse compared with those with AR <80% (HR = 0.53, p = 0.008). In addition, breast tumors with higher AR expression had good biological features (low ki67 and nuclear grade) compared with BCs with lower AR expression, at least partly explaining the different outcome.

CONCLUSIONS

The results of this study support the potential prognostic role of AR in patients with ER+/PgR- BCs and may contribute to the identification of subgroups of high-risk patients.