Neoadjuvant chemotherapy for luminal a breast cancer: Factors predictive of histopathologic response and oncologic outcome

The breast cancer coagulome in the tumor microenvironment and its role in prognosis and treatment response to chemotherapy

BACKGROUND

The procoagulant phenotype in cancer is linked to thrombosis, cancer progression, and immune response. A novel treatment that reduces the risk of both thrombosis and cancer progression without excess bleeding risk remains to be identified.

OBJECTIVES

Here, we aimed to broadly investigate the breast tumor coagulome and its relation to prognosis, treatment response to chemotherapy, and the tumor microenvironment.

METHODS

Key coagulation-related genes (n = 35) were studied in a Norwegian cohort with tumor (n = 134) and normal (n = 189) tissue and in the Cancer Genome Atlas (n = 1052) data set. We performed gene set variation analysis in the Norwegian cohort, and in the Cancer Genome Atlas cohort, associations with the tumor microenvironment and prognosis were evaluated. Analyses were performed with cBioPortal, Estimation of Stromal and Immune cells in Malignant Tumors Using Expression Data, Tumor Immune Estimation Resource, the integrated repository portal for tumor-immune system interactions, Tumor Immune Single-cell Hub 2, and the receiver operating characteristic plotter. Six independent breast cancer cohorts were used to study the tumor coagulome and treatment response to chemotherapy.

RESULTS

Twenty-two differentially expressed coagulation-related genes were identified in breast tumors. Several coagulome factors were correlated with tumor microenvironment characteristics and were expressed by nonmalignant cells in the tumor microenvironment. PLAT and F8 were independent predictors of better overall survival and progression-free survival, respectively. F12 and PLAU were predictors of worse progression-free survival. The PROCR-THBD-PLAT signature showed a promising predictive value (area under the curve, 0.75; 95% CI, 0.69-0.81; P = 3.6 × 10-17) for combination chemotherapy with fluorouracil, epirubicin, and cyclophosphamide.

CONCLUSION

The breast tumor coagulome showed potential in prediction of prognosis and chemotherapy response. Cells within the tumor microenvironment are sources of coagulome factors and may serve as therapeutic targets of coagulation factors.

Neo-adjuvant therapies for ER positive/HER2 negative breast cancers: from chemotherapy to hormonal therapy, CDK inhibitors, and beyond

INTRODUCTION

Chemotherapy has been traditionally used as neo-adjuvant therapy in breast cancer for down-staging of locally advanced disease in all sub-types. In the adjuvant setting, genomic assays have shown that a significant proportion of ER positive/HER2 negative patients do not derive benefit from the addition of chemotherapy to adjuvant endocrine therapy. An interest in hormonal treatments as neo-adjuvant therapies in ER positive/HER2 negative cancers has been borne by their documented success in the adjuvant setting. Moreover, cytotoxic chemotherapy is less effective in ER positive/HER2 negative disease compared with other breast cancer subtypes in obtaining pathologic complete responses.

AREAS COVERED

Neo-adjuvant therapies for ER positive/HER2 negative breast cancers and associated biomarkers are reviewed, using a Medline survey. A focus of discussion is the prediction of patients that are unlikely to derive extra benefit from chemotherapy and have the highest probabilities of benefiting from hormonal and other targeted therapies.

EXPERT OPINION

Predictive biomarkers of response to neo-adjuvant chemotherapy and hormonal therapies are instrumental for selecting ER positive/HER2 negative breast cancer patients for each treatment. Chemotherapy remains the standard of care for many of those patients requiring neo-adjuvant treatment, but other neo-adjuvant therapies are increasingly used.

Neoadjuvant therapy in hormone Receptor-Positive/HER2-Negative breast cancer

Neoadjuvant therapy is commonly used in patients with locally advanced or inoperable breast cancer (BC). Neoadjuvant chemotherapy (NACT) represents an established treatment modality able to downstage tumours, facilitate breast-conserving surgery, yet also achieve considerable pathologic complete response (pCR) rates in HER2-positive and triple-negative BC. For patients with HR+/HER2- BC, the choice between NACT and neoadjuvant endocrine therapy (NET) is still based on clinical and pathological features and not guided by biomarkers of defined clinical utility, differently from the adjuvant setting where gene-expression signatures have been widely adopted to drive decision-making. In this review, we summarize the evidence supporting the choice of NACT vs NET in HR+/HER2- BC, discussing the issues surrounding clinical trial design and proper selection of patients for every treatment. It is time to question the binary paradigm of responder vs non-responders as well as the "one size fits all" approach in luminal BC, supporting the utilization of continuous endpoints and the adoption of tissue and plasma-based biomarkers at multiple timepoints. This will eventually unleash the full potential of neoadjuvant therapy which is to modulate patient treatment based on treatment sensitivity and surgical outcomes. We also reviewed the current landscape of neoadjuvant studies for HR+/HER2- BC, focusing on antibody-drug conjugates (ADCs) and immunotherapy combinations. Finally, we proposed a roadmap for future neoadjuvant approaches in HR+/HER2- BC, which should be based on a staggered biomarker-driven treatment selection aiming at impacting long-term relevant endpoints.

Neoadjuvant chemotherapy in non-metastatic breast cancer: The surgeon's perspective

Breast cancer is the most common non-skin cancer in Australia, affecting 1 in 7 women by the age of 85 years. Current management of early breast cancer is becoming increasingly variable and complex. The typical range of treatments include some combination of surgery, chemotherapy and targeted therapy, immunotherapy, radiotherapy, and endocrine therapy. Neoadjuvant chemotherapy (NACT) in carefully selected patients can facilitate increased rates of breast conservation therapy, and when successful, offers improved cosmesis due to less extensive resection of tissue. A neoadjuvant approach also provides biological insight into a patient's tumour, prognostication based on a patient's response to therapy, as well as enabling their treating oncologist to personalise adjuvant strategies based on the presence or absence of residual cancer at surgery. Neoadjuvant chemotherapy has become an integral element in the provision of breast conserving surgery to selected early-stage breast cancer patients. Appreciating the indications and understanding the likely outcomes from NACT in select situations, can result in significant improvements in patient tailored care.

Neoadjuvant Chemotherapy of Taxanes With or Without Anthracyclines in Different Molecular Subtypes of Breast Cancer: A Propensity Score Matching Study

PURPOSE

To compare the efficacy of taxane (T) based neoadjuvant chemotherapy (NAC) with T and anthracycline (A) based NAC in different molecular types of breast cancer (BC).

METHODS

We retrospectively analyzed the date of NAC for BC from 20 hospitals in China from January 2010 to December 2020, 7870 cases were enrolled. The propensity score matching was used to equalize the baseline characteristics. Pathological complete response (pCR) rate, clinical response rate and breast-conserving rate were analyzed.

RESULTS

The efficacy of 2 regimens were similar in luminal A subtype. The breast-conserving rate was higher in T-based NAC in luminal B subtype (17.9% vs. 10.2%, P = .043).The pCR (T0/isN0M0) and tpCR (T0N0M0) rates in T-based NAC were higher than those in TA-based NAC for triple-negative subtype (pCR: 34.5% vs. 25.8%, P = .041, tpCR: 26.9% vs. 17.1%, P = .008). For HER2+(HR-) subtype, the pCR, and tpCR rates were higher in T-based NAC in insufficient anti-HER2 therapy (P < .05), and those were higher in TA-based NAC in dual-target anti-HER2 therapy (pCR: 69.2% vs. 53.8%, P = .254, tpCR: 61.5% vs. 42.3%, P = .165). For HER2+(HR+) breast cancer, both pCR and tpCR rates were higher in TA group, regardless of the adequacy of anti-HER2 treatment.

CONCLUSIONS

T-based NAC could replace TA-based NAC for luminal A, luminal B, and triple-negative early-stage BC, but anthracyclines cannot be abandoned in HER2+ breast cancer. The development of anthracyclines with lower adverse reactions is one of the directions for the treatment of HER2+ breast cancer.

Association of SLC12A1 and GLUR4 Ion Transporters with Neoadjuvant Chemoresistance in Luminal Locally Advanced Breast Cancer

Chemoresistance to standard neoadjuvant treatment commonly occurs in locally advanced breast cancer, particularly in the luminal subtype, which is hormone receptor-positive and represents the most common subtype of breast cancer associated with the worst outcomes. Identifying the genes associated with chemoresistance is crucial for understanding the underlying mechanisms and discovering effective treatments. In this study, we aimed to identify genes linked to neoadjuvant chemotherapy resistance in 62 retrospectively included patients with luminal breast cancer. Whole RNA sequencing of 12 patient biopsies revealed 269 differentially expressed genes in chemoresistant patients. We further validated eight highly correlated genes associated with resistance. Among these, solute carrier family 12 member 1 (SLC12A1) and glutamate ionotropic AMPA type subunit 4 (GRIA4), both implicated in ion transport, showed the strongest association with chemoresistance. Notably, SLC12A1 expression was downregulated, while protein levels of glutamate receptor 4 (GLUR4), encoded by GRIA4, were elevated in patients with a worse prognosis. Our results suggest a potential link between SLC12A1 gene expression and GLUR4 protein levels with chemoresistance in luminal breast cancer. In particular, GLUR4 protein could serve as a potential target for drug intervention to overcome chemoresistance.

GATA3 mediates doxorubicin resistance by inhibiting CYB5R2-catalyzed iron reduction in breast cancer cells

AIMS

Neoadjuvant chemotherapy (NAC) is the primary preoperative therapy for breast cancer. The luminal subtype of breast cancer shows less NAC response than the basal subtype, with an inefficient NAC treatment effect. Understanding of the molecular and cellular mechanisms responsible for this chemoresistance is an important issue when determining optimal treatment.

METHODS

Doxorubicin-induced apoptosis and ferroptosis was investigated using cytotoxicity, western blotting, and flow cytometry assays. The role of GATA3 in modulating doxorubicin-induced cell death was investigated both in vitro and in vivo. RNA-seq, qPCR, ChIP, and luciferase assay and association analyses were performed to investigate the regulation of CYB5R2 by GATA3. The function of GATA3 and CYB5R2 in regulating doxorubicin-induced ferroptosis was evaluated with iron, ROS, and lipid peroxidation detection assays. Immunohistochemistry was performed for results validation.

RESULTS

Doxorubicin-induced basal breast cancer cell death is dependent on iron-mediated ferroptosis. Overexpression of the luminal signature transcriptional factor GATA3 mediates doxorubicin resistance. GATA3 promotes cell viability by decreasing ferroptosis-related gene CYB5R2 expression and by maintaining iron homeostasis. Analyzing data from the public and our cohorts demonstrates that GATA3 and CYB5R2 are associated with NAC response.

CONCLUSIONS

GATA3 promotes doxorubicin resistance by inhibiting CYB5R2-mediated iron metabolism and ferroptosis. Therefore, patients with breast cancer who display high GATA3 expression do not benefit from doxorubicin-based NAC regimens.

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.

A logarithmic model for hormone receptor-positive and breast cancer patients treated with neoadjuvant chemotherapy

OBJECTIVE

The aim of this study was to investigate the predictive importance of the previously validated log(ER)*log(PgR)/Ki-67 predictive model in a larger patient population.

METHODS

Patients with hormone receptor positive/HER-2 negative and clinical node positive before chemotherapy were included. Log(ER)*log(PgR)/Ki-67 values of the patients were determined, and the ideal cutoff value was calculated using a receiver operating characteristic curve analysis. It was analyzed with a logistic regression model along with other clinical and pathological characteristics.

RESULTS

A total of 181 patients were included in the study. The ideal cutoff value for pathological response was 0.12 (area under the curve=0.585, p=0.032). In the univariate analysis, no statistical correlation was observed between luminal subtype (p=0.294), histological type (p=0.238), clinical t-stage (p=0.927), progesterone receptor level (p=0.261), Ki-67 cutoff value (p=0.425), and pathological complete response. There was a positive relationship between numerical increase in age and residual disease. As the grade of the patients increased, the probability of residual disease decreased. Patients with log(ER)*log(PgR)/Ki-67 above 0.12 had an approximately threefold increased risk of residual disease when compared to patients with 0.12 and below (odds ratio: 3.17, 95% confidence interval: 1.48-6.75, p=0.003). When age, grade, and logarithmic formula were assessed together, the logarithmic formula maintained its statistical significance (odds ratio: 2.47, 95% confidence interval: 1.07-5.69, p=0.034).

CONCLUSION

In hormone receptor-positive breast cancer patients receiving neoadjuvant chemotherapy, the logarithmic model has been shown in a larger patient population to be an inexpensive, easy, and rapidly applicable predictive marker that can be used to predict response.

A radiomic model to classify response to neoadjuvant chemotherapy in breast cancer

BACKGROUND

Medical image analysis has evolved to facilitate the development of methods for high-throughput extraction of quantitative features that can potentially contribute to the diagnostic and treatment paradigm of cancer. There is a need for further improvement in the accuracy of predictive markers of response to neo-adjuvant chemotherapy (NAC). The aim of this study was to develop a radiomic classifier to enhance current approaches to predicting the response to NAC breast cancer.

METHODS

Data on patients treated for breast cancer with NAC prior to surgery who had a pre-NAC dynamic contrast enhanced breast MRI were included. Response to NAC was assessed using the Miller-Payne system on the excised tumor. Tumor segmentation was carried out manually under the supervision of a consultant breast radiologist. Features were selected using least absolute shrinkage selection operator regression. A support vector machine learning model was used to classify response to NAC.

RESULTS

74 patients were included. Patients were classified as having a poor response to NAC (reduction in cellularity < 90%, n = 44) and an excellent response (> 90% reduction in cellularity, n = 30). 4 radiomics features (discretized kurtosis, NGDLM contrast, GLZLM_SZE and GLZLM_ZP) were identified as pertinent predictors of response to NAC. A SVM model using these features stratified patients into poor and excellent response groups producing an AUC of 0.75. Addition of estrogen receptor status improved the accuracy of the model with an AUC of 0.811.

CONCLUSION

This study identified a radiomic classifier incorporating 4 radiomics features to augment subtype based classification of response to NAC in breast cancer.

Epigenetic oncogenesis, biomarkers and emerging chemotherapeutics for breast cancer

Breast cancer remains one of the leading causes of cancer-related deaths globally and the most prominent among females, yet with limited effective therapeutic options. Most of the current medications are challenged by various factors including low efficacy, incessant resistance, immune evasion and frequent recurrence of the disease. Further understanding of the prognosis and identification of plausible therapeutic channels thus requires multimodal approaches. In this review, epigenetics studies of several pathways to BC oncogenesis via the inducement of oncogenic changes on relevant markers have been overviewed. Similarly, the counter-epigenetic mechanisms to reverse such changes as effective therapeutic strategies were surveyed. The epigenetic oncogenesis occurs through several pathways, notably, DNMT-mediated hypermethylation of DNA, dysregulated expression for ERα, HER2/ERBB and PR, histone modification, overexpression of transcription factors including the CDK9-cyclin T1 complex and suppression of tumour suppressor genes. Scientifically, the regulatory reversal of the mechanisms constitutes effective epigenetic approaches for mitigating BC initiation, progression and metastasis. These were exhibited at various experimental levels by classical chemotherapeutic agents including some repurposable drugs, endocrine inhibitors, monoclonal antibodies and miRNAs, natural products, metal complexes and nanoparticles. Dozens of the potential candidates are currently in clinical trials while others are still at preclinical experimental stages showing promising anti-BC efficacy. The review presents a model for a wider understanding of epigenetic oncogenic pathways to BC and reveals plausible channels for reversing the unpleasant changes through epigenetic modifications. It advances the science of therapeutic designs for ameliorating the global burden of BC upon further translational studies.