Prognostic and predictive value of centrally reviewed expression of estrogen and progesterone receptors in a randomized trial comparing letrozole and tamoxifen adjuvant therapy for postmenopausal early breast cancer: BIG 1-98

Artificial intelligence algorithm accurately assesses oestrogen receptor immunohistochemistry in metastatic breast cancer cytology specimens: A pilot study

OBJECTIVE

The Visiopharm artificial intelligence (AI) algorithm for oestrogen receptor (ER) immunohistochemistry (IHC) in whole slide images (WSIs) has been successfully validated in surgical pathology. This study aimed to assess its efficacy in cytology specimens.

METHODS

The study cohort comprised 105 consecutive cytology specimens with metastatic breast carcinoma. ER IHC WSIs were seamlessly integrated into the Visiopharm platform from the Image Management System (IMS) during our routine digital workflow, and an AI algorithm was employed for analysis. ER AI scores were compared with pathologists' manual consensus scores. Optimization steps were implemented and evaluated to reduce discordance.

RESULTS

The overall concordance between pathologists' scores and AI scores was excellent (99/105, 94.3%). Six cases exhibited discordant results, including two false-negative (FN) cases due to abundant histiocytes incorrectly counted as negatively stained tumour cells by AI, two FN cases owing to weak staining, and two false-positive (FP) cases where pigmented macrophages were erroneously counted as positively stained tumour cells by AI. The Pearson correlation coefficient of ER-positive percentages between pathologists' and AI scores was 0.8483. Optimization steps, such as lowering the cut-off threshold and additional training using higher input magnification, significantly improved accuracy.

CONCLUSIONS

The automated ER AI algorithm demonstrated excellent concordance with pathologists' assessments and accurately differentiated ER-positive from ER-negative metastatic breast carcinoma cytology cases. However, precision in identifying tumour cells in cytology specimens requires further enhancement.

Prognosis and Adjusting Factors in Elderly Patients With Triple-Negative Breast Cancer: Comparing With Young and Middle Age Groups

PURPOSE

Proper breast cancer screening and treatment should be considered in the elderly population; however, some tend to be less proactive. Our study aimed to investigate the impact of old age on treatment and prognosis in triple-negative breast cancer (TNBC).

METHOD

The study included patients with primary TNBC stage I-III diagnosed from 2002 to 2019 in single institution and retrospectively analyzed. We defined young (< 40 years), middle and old (> 70 years) groups. Clinicopathological factors, treatment, and prognosis were analyzed according to age group of TNBC patients.

RESULT

TNBC patients aged 70 and above were 3.3 times more likely (P = .019) to have lymph node metastasis at the time of diagnosis compared to younger patients, but were found to be 0.24 times less likely to receive chemotherapy. (P = .003) Old TNBC patients have an expected likelihood 2.2 times higher of undergoing mastectomy rather than breast-conserving surgery. (P = .042) The 5-year prognosis is poorer in young and old group. (61%, 86%, and 65% in young, middle, and old groups). (P < .001). In subanalysis, old group of stages I and II received fewer chemotherapy compared to youngers (P < .05), but not in stage III. In Cox regression analysis, age and stage had significant impact on prognosis (hazard ratio 2-3), but treatment factors did not. However, in stratified analysis of adjuvant therapy and stage, prognosis of Old TNBC patients in stage II was improved when they underwent neo or adjuvant chemotherapy.

CONCLUSION

TNBC presents challenges in older patients, who receive less aggressive treatment and have poorer outcomes. The primary cause of poor prognosis in old TNBC patients is the high disease stage at diagnosis, underscoring the need for promotion and education on early screening. Additionally, it is suggested that a more proactive approach to adjuvant chemotherapy is necessary for stage II old TNBC patients.

Quantitative expression of oestrogen receptor in breast cancer: Clinical and molecular significance

BACKGROUND

Oestrogen receptor (ER) positive breast cancer (BC) patients are eligible for endocrine therapy (ET), regardless of ER immunohistochemical expression level. There is a wide spectrum of ER expression and the response to ET is not uniform. This study aimed to assess the clinical and molecular consequences of ER heterogeneity with respect to ET-response.

METHODS

ER expression, categorised by percentage and staining intensity in a large BC cohort (n = 7559) was correlated with clinicopathological parameters and patient ET response. The Cancer Genome Atlas Data BC cohort (n = 1047) was stratified by ER expression and transcriptomic analysis completed to better understand the molecular basis of ER heterogeneity.

RESULTS

The quantitative proportional increase in ER expression was positively associated with favourable prognostic parameters. Tumours with 1-9% ER expression were characteristically similar to ER-negative (<1%) tumours. Maximum ET-response was observed in tumours with 100% ER expression, with responses significantly different to tumours exhibiting ER at < 100% and significantly decreased survival rates were observed in tumours with 50% and 10% of ER expression. The Histochemical-score (H-score), which considers both staining intensity and percentage, added significant prognostic value over ER percentage alone with significant outcome differences observed at H-scores of 30, 100 and 200. There was a positive correlation between ER expression and ESR1 mRNA expression and expression of ER-regulated genes. Pathway analysis identified differential expression in key cancer-related pathways in different ER-positive groups.

CONCLUSION

ET-response is statistically proportionally related to ER expression with significant differences observed at 10%, 50% and 100%. The H-score adds prognostic and predictive information.

Understanding breast cancer complexity to improve patient outcomes: The St Gallen International Consensus Conference for the Primary Therapy of Individuals with Early Breast Cancer 2023

The 18th St Gallen International Breast Cancer Conference held in March 2023, in Vienna, Austria, assessed significant new findings for local and systemic therapies for early breast cancer with a focus on the evaluation of multimodal treatment options. The emergence of more effective, innovative agents in both the preoperative (primary or neoadjuvant) and post-operative (adjuvant) settings has underscored the pivotal role of a multidisciplinary approach in treatment decision making, particularly when selecting systemic therapy for an individual patient. The importance of multidisciplinary discussions regarding the clinical benefits of interventions was explicitly emphasized by the consensus panel as an integral part of developing an optimal treatment plan with the 'right' degree of intensity and duration. The panelists focused on controversies surrounding the management of common ductal/no special type and lobular breast cancer histology, which account for the vast majority of breast tumors. The expert opinion of the panelists was based on interpretations of available data, as well as current practices in their professional environments, personal and socioeconomic factors affecting patients, and cognizant of varying reimbursement and accessibility constraints around the world. The panelists strongly advocated patient participation in well-designed clinical studies whenever feasible. With these considerations in mind, the St Gallen Consensus Conference aims to offer guidance to clinicians regarding appropriate treatments for early-stage breast cancer and assist in balancing the realistic trade-offs between treatment benefit and toxicity, enabling patients and clinicians to make well-informed choices through a shared decision-making process.

Clinical Behavior, Management, and Treatment Response of Estrogen Receptor Low (1-10%) Breast Cancer

INTRODUCTION

Estrogen receptor (ER) and progesterone receptor (PR) guide management and impact outcomes of breast cancer (BC). This study compares ER-low (1-10%) with ER-negative (< 1%) and ER-positive (>10%) BC and investigates the significance of PR expression within ER-low disease.

PATIENTS AND METHODS

All patients with HER2-negative invasive BC were identified from the National Cancer Database 2018-2019. Treatment and outcomes were compared using chi-squared tests and multivariable logistic regression.

RESULTS

Of 232,762 patients, ER expression was: negative (13.8%), low (2.0%), and > 10% (84.2%). Chemotherapy was given in 83.9% of ER- disease, 82.4% of ER-low/PR- disease, 58.9% of ER-low/PR+ disease, and only in 22.9% of ER+ disease. Within the ER-low subgroup, adjuvant endocrine therapy, recurrence score, and Ki67 varied by PR status (all < 0.01). Patients with ER-low disease selected for neoadjuvant chemotherapy (NAC) were younger and had higher T and N category, tumor grade, and Ki67. With NAC, pathological complete response (pCR) rates were similar between ER-low/PR- and ER-low/PR+ (39.5% and 38.1%, respectively, p = 0.67), and were closer to the ER- group (39.7%) than the ER+ group (8.4%). On multivariable analysis, the adjusted effect of ER status (1-10% versus > 10%) on chemotherapy administration was odds ratio (OR) 8.2 (95% CI 7.3-9.2, p < 0.001) for PR-negative, and OR 3.3 (95% CI 7.3-9.2, p < 0.001) for PR-positive.

CONCLUSIONS

This study suggests that the tumor features and clinical management of ER-low tumors vary significantly by PR expression. Within ER-low tumors, PR- tumors more closely resemble ER- BC, while PR+ tumors exhibit less aggressive characteristics. In ER-low disease selected for treatment with NAC, response is similar to ER- regardless of PR status.

The Clinical and Biological Significance of Estrogen Receptor-Low Positive Breast Cancer

Estrogen receptor (ER) status in breast cancer (BC) is determined using immunohistochemistry (IHC) with nuclear expression in ≥1% of cells defined as ER-positive. BC with 1%-9% expression (ER-low-positive), is a clinically and biologically unique subgroup. In this study, we hypothesized that ER-low-positive BC represents a heterogeneous group with a mixture of ER-positive and ER-negative tumor, which may explain their divergent clinical behavior. A large BC cohort (n = 8171) was investigated and categorized into 3 groups: ER-low-positive (1%-9%), ER-positive (≥10%), and ER-negative (<1%) where clinicopathological and outcome characteristics were compared. A subset of ER-low-positive cases was further evaluated using IHC, RNAscope, and RT-qPCR. PAM50 subtyping and ESR1 mRNA expression levels were assessed in ER-low-positive cases within The Cancer Genome Atlas data set. The reliability of image analysis software in assessment of ER expression in the ER-low-positive category was also assessed. ER-low-positive tumors constituted <2% of BC cases examined and showed significant clinicopathological similarity to ER-negative tumors. Most of these tumors were nonluminal types showing low ESR1 mRNA expression. Further validation of ER status revealed that 45% of these tumors were ER-negative with repeated IHC staining and confirmed by RNAscope and RT-qPCR. ER-low-positive tumors diagnosed on needle core biopsy were enriched with false-positive ER staining. BCs with 10% ER behaved similar to ER-positive, rather than ER-negative or low-positive BCs. Moderate concordance was found in assessment of ER-low-positive tumors, and this was not improved by image analysis. Routinely diagnosed ER-low-positive BC includes a proportion of ER-negative cases. We recommend repeat testing of BC showing 1%-9% ER expression and using a cutoff ≥10% expression to define ER positivity to help better inform treatment decisions.

Hormone receptors in breast cancer: An update on the uncommon subtypes

Breast cancer is the most common cancer affecting women and is the second leading cause of cancer death among US women. Estrogen receptor (ER) signaling plays a crucial role in mammary gland development and carcinogenesis. Near 80 % of invasive breast cancers are ER-positive (ER+). Endocrine therapies targeting ER have significantly improved the prognostic outcomes in the patients with ER+ breast cancer, and the therapeutic effects are strongly correlated with the levels of the ER expression in tumor cells. Despite being an ER-dependent gene product, PR is not always overexpressed in ER+ tumors, and a small subset of breast cancers demonstrates an ER+/PR- phenotype, and a rare ER-/PR+ subtype also exists. There have been controversies on the biology of these tumor types and the predictive and prognostic power of PR status. Compelling data have shown the distinct biologic characteristics of ER+/PR- and ER-/PR+ tumors. Despite that ER-low breast cancers demonstrate more similarity to ER- tumors, at least a subset of ER-low carcinomas may have a functional ER signaling. Thus, adequate PR expression is essential as its absence indicates impaired ER pathway. Assessment of PR status may not only distinguish the ER+/PR- subset from the ER+ and ER-low tumors, but also differentiate the ER-/PR+ phenotype from the ER- carcinomas, both with therapeutic implications. This article was aimed to provide an up-to-date review focusing on the clinicopathologic characteristics of uncommon subtypes of breast cancer, including ER+/PR-, ER-/PR+, and ER-low breast cancers.

Impact of estrogen receptor expression level on response to neoadjuvant chemotherapy and prognosis in HER2-negative breast cancers

BACKGROUND

Breast cancers with 1-10% cell staining for estrogen receptor (ER) present particular clinical features. The clinical data of estrogen receptor expression level and treatment effect are limited, particularly regarding chemotherapy benefit. We evaluated the pathologic response to neoadjuvant chemotherapy (NAC) in ER low positive tumors (ER staining 1-10%) and compared it with ER > 10% positive tumors (ER staining > 10%) and ER-negative tumors. We further explored the differences in recurrence and survival with respect to the ER expression level.

METHOD

Patients with stages II and III HER2-negative primary breast cancer who received neoadjuvant chemotherapy followed by definitive surgery were categorized according to their ER percentages into three groups: ER-negative, ER low positive, and ER > 10% positive. Logistic regression models were used to assess the association between each variable and pathologic complete response (pCR). Kaplan‒Meier analysis was used to estimate survival outcomes. Cox models were used to adjust for patient and tumor characteristics.

RESULTS

A total of 241 patients were analyzed. Of all patients included, 22 (9.1%) had ER low positive tumors, 159 (66.0%) had ER > 10% positive tumors, and 60 (24.9%) were ER-negative. Low ER positivity was significantly associated with a higher pCR rate than ER > 10% positivity (OR, 0.249; 95% CI, 0.067-0.923; P = 0.038). After a median follow-up time of 32 months, the disease-free survival (DFS) and overall survival (OS) of the patients with ER low positive tumors were significantly worse than those of the patients with ER > 10% positive tumors but similar to those with ER-negative tumors. After adjustment for covariates, ER low positive tumors were significantly associated with worse DFS than ER > 10% positive tumors.

CONCLUSION

Our results indicated that ER low positive breast cancer presents a better response to neoadjuvant chemotherapy and significantly worse prognosis for patients than those with ER > 10% positive tumors, but similar to the ER-negative group. These data support that this category of patients behaves clinically like patients with ER-negative breast cancer and should be treated differently from patients with ER > 10% positive tumors. Further prospective study is needed.

Applications of Artificial Intelligence in Breast Pathology

CONTEXT.—

Increasing implementation of whole slide imaging together with digital workflow and advances in computing capacity enable the use of artificial intelligence (AI) in pathology, including breast pathology. Breast pathologists often face a significant workload, with diagnosis complexity, tedious repetitive tasks, and semiquantitative evaluation of biomarkers. Recent advances in developing AI algorithms have provided promising approaches to meet the demand in breast pathology.

OBJECTIVE.—

To provide an updated review of AI in breast pathology. We examined the success and challenges of current and potential AI applications in diagnosing and grading breast carcinomas and other pathologic changes, detecting lymph node metastasis, quantifying breast cancer biomarkers, predicting prognosis and therapy response, and predicting potential molecular changes.

DATA SOURCES.—

We obtained data and information by searching and reviewing literature on AI in breast pathology from PubMed and based our own experience.

CONCLUSIONS.—

With the increasing application in breast pathology, AI not only assists in pathology diagnosis to improve accuracy and reduce pathologists' workload, but also provides new information in predicting prognosis and therapy response.

Advancing Breast Cancer Heterogeneity Analysis: Insights from Genomics, Transcriptomics and Proteomics at Bulk and Single-Cell Levels

Breast cancer continues to pose a significant healthcare challenge worldwide for its inherent molecular heterogeneity. This review offers an in-depth assessment of the molecular profiling undertaken to understand this heterogeneity, focusing on multi-omics strategies applied both in traditional bulk and single-cell levels. Genomic investigations have profoundly informed our comprehension of breast cancer, enabling its categorization into six intrinsic molecular subtypes. Beyond genomics, transcriptomics has rendered deeper insights into the gene expression landscape of breast cancer cells. It has also facilitated the formulation of more precise predictive and prognostic models, thereby enriching the field of personalized medicine in breast cancer. The comparison between traditional and single-cell transcriptomics has identified unique gene expression patterns and facilitated the understanding of cell-to-cell variability. Proteomics provides further insights into breast cancer subtypes by illuminating intricate protein expression patterns and their post-translational modifications. The adoption of single-cell proteomics has been instrumental in this regard, revealing the complex dynamics of protein regulation and interaction. Despite these advancements, this review underscores the need for a holistic integration of multiple 'omics' strategies to fully decipher breast cancer heterogeneity. Such integration not only ensures a comprehensive understanding of breast cancer's molecular complexities, but also promotes the development of personalized treatment strategies.

A prospective cohort study of clinical characteristics and outcomes in Chinese patients with estrogen receptor-negative/progesterone receptor-positive early breast cancer

PURPOSE

This study aimed to examine the clinical characteristics and outcomes of patients with estrogen receptor-negative (ER-)/progesterone receptor-positive (PR+) early breast cancer. We also aimed to investigate the benefits of adjuvant endocrine therapy (ET) in this patient population.

METHODS

Patients with early breast cancer diagnosed at West China Hospital were divided into the ER-/PR+, ER+, and ER-/PR- groups. The chi-square test was used to analyze differences in clinical and pathological features among the groups. Multivariable Cox and Fine-Gray regression models were used to compare mortality and locoregional recurrence (LRR)/distant recurrence (DR), respectively. We performed a subgroup analysis to determine which ER-/PR+ patients can benefit more from ET.

RESULTS

From 2008 to 2020, we enrolled 443, 7104, and 2892 patients into the ER-/PR+, ER+, and ER-/PR- groups, respectively. The ER-/PR+ group showed more unfavorable clinical features and aggressive pathological characteristics than the ER+ group. The mortality, LRR, and DR rates were higher in the ER-/PR+ than in the ER+ group. Most clinical features and pathological characteristics were similar between the ER-/PR+ and ER-/PR- group and their outcomes were comparable. In the ER-/PR+ group, patients who received ET showed significantly lower LRR and mortality rates than those who did not; however, no difference was observed in DR. Subgroup analysis suggested that ER-/PR+ patients age ≥ 55 years, and postmenopausal status can benefit from ET.

CONCLUSION

ER-/PR+ tumors have more aggressive pathological characteristics and more unfavorable clinical features than ER+ tumors. ET can reduce the LRR and mortality rates in ER-/PR+ patients. Postmenopausal and age ≥ 55 years ER-/PR+ patients can benefit from ET.

A Review of Endocrine Therapy in Early-stage Breast Cancer: The Journey From Crudeness to Precision

Endocrine therapy (ET) is the standard of care for hormone receptor-positive early-stage breast cancer in the adjuvant setting. However, response to ET can vary across patient subgroups. Historically, hormone receptor expression and clinical stage are the main predictors of the benefit of ET. A "window of opportunity" trials has raised significant interest in recent years as a means of assessing the sensitivity of a patient's cancer to short-term neoadjuvant ET, which provides important prognostic information, and helps in decision-making regarding treatment options in a time-efficient and cost-efficient manner. In the era of genomics, molecular profiling has led to the discovery and evaluation of the prognostic and predictive abilities of new molecular profiles. To realize the goal of personalized medicine, we are in urgent need to explore reliable biomarkers or genomic signatures to accurately predict the clinical response and long-term outcomes associated with ET. Validation of these biomarkers as reliable surrogate endpoints can also lead to a revolution in the clinical trial designs, and potentially avoid the need for repeated tissue biopsies in the surveillance of disease response. The clinical potential of tumor genomic profiling marks the beginning of a new era of precision medicine in breast cancer treatment.

The clinical value of progesterone receptor expression in luminal breast cancer: A study of a large cohort with long-term follow-up

BACKGROUND

The routine assessment of progesterone receptor (PR) expression in breast cancer (BC) remains controversial. This study aimed to evaluate the role of PR expression in luminal BC, with emphasis on the definition of positivity and its prognostic significance as compared to Ki67 expression.

METHODS

A large cohort (n = 1924) of estrogen receptor (ER)-positive/HER2-negative BC was included. PR was immunohistochemically (IHC) stained on full face sections and core needle biopsies (CNB) where the optimal scoring cutoff was evaluated. In addition, the association of PR with other clinicopathological factors, cellular proliferation, disease outcome, and response to adjuvant therapy were analyzed.

RESULTS

Although several cutoffs showed prognostic significance, the optimal cutoff to categorize PR expression into two clinically distinct prognostic groups on CNB was 10%. PR negativity showed a significant association with features of aggressive tumor behavior and poor outcome. Multivariate analyses indicated that the association between PR negativity and poor outcome was independent of tumor grade, size, node stage, and Ki67. PR negativity showed independent association with shorter survival in patients who received endocrine therapy whereas Ki67did not.

CONCLUSION

PR IHC expression provides independent prognostic value superior to Ki67. Routine assessment of PR expression in BC using 10% cutoff in the clinical setting is recommended.

PLAIN LANGUAGE SUMMARY

In this study, we have established an optimal approach to determine the prognostic value of progesterone receptor expression in estrogen receptor-positive breast cancer patients. To do this, the levels of progesterone receptor were measured in a large cohort of estrogen receptor-positive breast cancer patients. We have refined the definition of progesterone receptor positivity in estrogen receptor-positive breast cancer. We show that progesterone receptor expression adds prognostic and predictive value of endocrine therapy in estrogen receptor-positive breast cancer patients, and our results show that the absence of progesterone receptor is associated with poorer outcomes independent of tumor grade, size, node stage, and Ki67 expression.

Correlative studies of the Breast Cancer Index (HOXB13/IL17BR) and ER, PR, AR, AR/ER ratio and Ki67 for prediction of extended endocrine therapy benefit: a Trans-aTTom study

BACKGROUND

Multiple clinical trials demonstrate consistent but modest benefit of adjuvant extended endocrine therapy (EET) in HR + breast cancer patients. Predictive biomarkers to identify patients that benefit from EET are critical to balance modest reductions in risk against potential side effects of EET. This study compares the performance of the Breast Cancer Index, BCI (HOXB13/IL17BR, H/I), with expression of estrogen (ER), progesterone (PR), and androgen receptors (AR), and Ki67, for prediction of EET benefit.

METHODS

Node-positive (N+) patients from the Trans-aTTom study with available tissue specimen and BCI results (N = 789) were included. Expression of ER, PR, AR, and Ki67 was assessed by quantitative immunohistochemistry. BCI (H/I) gene expression analysis was conducted by quantitative RT-PCR. Statistical significance of the treatment by biomarker interaction was evaluated by likelihood ratio tests based on multivariate Cox proportional models, adjusting for age, tumor size, grade, and HER2 status. Pearson's correlation coefficients were calculated to evaluate correlations between BCI (H/I) versus ER, PR, AR, Ki67 and AR/ER ratio.

RESULTS

EET benefit, measured by the difference in risk of recurrence between patients treated with tamoxifen for 10 versus 5 years, is significantly associated with increasing values of BCI (H/I) (interaction P = 0.01). In contrast, expression of ER (P = 0.83), PR (P = 0.66), AR (P = 0.78), Ki67 (P = 0.87) and AR/ER ratio (P = 0.84) exhibited no significant relationship with EET benefit. BCI (H/I) showed a very weak negative correlation with ER (r = - 0.18), PR (r = - 0.25), and AR (r = - 0.14) expression, but no correlation with either Ki67 (r = 0.04) or AR/ER ratio (r = 0.02).

CONCLUSION

These findings are consistent with the growing body of evidence that BCI (H/I) is significantly predictive of response to EET and outcome. Results from this direct comparison demonstrate that expression of ER, PR, AR, Ki67 or AR/ER ratio are not predictive of benefit from EET. BCI (H/I) is the only clinically validated biomarker that predicts EET benefit.

[Endocrine Treatments in Breast Cancer]

Endocrine Treatments in Breast Cancer Abstract. Breast cancer, the most common cancer in women, expresses estrogen and/or progesterone receptors in about 75% of patients. This allows for the use of endocrine treatments. Adjuvant therapy with tamoxifen for 5 years reduces the mortality by about 33%; the residual risk can be lowered by using aromatase inhibitors and by prolonging the treatment. In patients with advanced disease, the median duration of response to first-line therapy is about twelve months, and the median survival time is 20 to 40 months. The use of the various substances differs in terms of duration, sequence, and combinations, particularly with CDK4/6-inhibitors, depending on the clinical situation. Endocrine therapies are prescribed over a long period of time. Treatment adherence is improved by optimal control of side effects.

3D and 4D Printing in the Fight against Breast Cancer

Breast cancer is the second most common cancer worldwide, characterized by a high incidence and mortality rate. Despite the advances achieved in cancer management, improvements in the quality of life of breast cancer survivors are urgent. Moreover, considering the heterogeneity that characterizes tumors and patients, focusing on individuality is fundamental. In this context, 3D printing (3DP) and 4D printing (4DP) techniques allow for a patient-centered approach. At present, 3DP applications against breast cancer are focused on three main aspects: treatment, tissue regeneration, and recovery of the physical appearance. Scaffolds, drug-loaded implants, and prosthetics have been successfully manufactured; however, some challenges must be overcome to shift to clinical practice. The introduction of the fourth dimension has led to an increase in the degree of complexity and customization possibilities. However, 4DP is still in the early stages; thus, research is needed to prove its feasibility in healthcare applications. This review article provides an overview of current approaches for breast cancer management, including standard treatments and breast reconstruction strategies. The benefits and limitations of 3DP and 4DP technologies are discussed, as well as their application in the fight against breast cancer. Future perspectives and challenges are outlined to encourage and promote AM technologies in real-world practice.

The influence of treatment on hormone receptor subgroups and breast cancer-specific mortality within US integrated healthcare systems

PURPOSE

Estrogen receptor (ER) + /progesterone receptor (PR) - or ER-/PR + breast cancer prognosis has not been well-described outside of clinical trials. We evaluated the relationship between ER/PR (ER + /PR-, ER-/PR + , ER + /PR + , ER-/PR-) subgroups and breast cancer-specific mortality within a general community setting in the US.

METHODS

A Retrospective cohort of 11,737 women diagnosed with breast cancer between 1990 and 2016 within US integrated healthcare systems (median follow-up = 7 years; 1,104 breast cancer-specific deaths) were included in this analysis. Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) adjusting for site, demographic and clinicopathological characteristics, and treatment (surgery/radiotherapy, chemotherapy, endocrine therapy).

RESULTS

Breast cancer-specific mortality was higher for those with ER + /PR- (n = 1,233) compared with ER + /PR + tumors (n = 8,439) before (HR = 1.43; 95% CI = 1.17-1.75) and after treatment adjustment (HR = 1.58; 95% CI = 1.27-1.97). ER + /PR- breast cancer-specific mortality remained higher than ER + /PR + tumors when stratified by treatment received. Breast cancer-specific mortality was similar in ER-/PR + (n = 161) compared with ER + /PR + tumors.

CONCLUSION

Our findings suggest that ER + /PR- tumors may have worse breast cancer-specific mortality than ER + /PR + tumors in a community setting.

Update on prognostic and predictive biomarkers of breast cancer

Breast cancer represents a heterogeneous group of human cancer at both histological and molecular levels. Estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) are the most commonly used biomarkers in clinical practice for making treatment plans for breast cancer patients by oncologists. Recently, PD-L1 testing plays an important role for immunotherapy for triple-negative breast cancer. With the increased understanding of the molecular characterization of breast cancer and the emergence of novel targeted therapies, more potential biomarkers are needed for the development of more personalized treatments. In this review, we summarized several main prognostic and predictive biomarkers in breast cancer at genomic, transcriptomic and proteomic levels, including hormone receptors, HER2, Ki67, multiple gene expression assays, PD-L1 testing, mismatch repair deficiency/microsatellite instability, tumor mutational burden, PIK3CA, ESR1 andNTRK and briefly introduced the roles of digital imaging analysis in breast biomarker evaluation.

ROS1 altered breast cancers - a distinctive molecular subtype of PR- metastatic breast cancers: Expanding the scope of targeted therapeutics

BACKGROUND

Breast cancer, one of the leading causes of cancer-related mortality in women worldwide, exhibits wide-ranging histo-morphologic, clinical and molecular diversity.

OBJECTIVE

This study compares the genetic alterations of breast tumors with the histo-morphological, hormone receptor status and metastatic "organotropism".

MATERIALS AND METHODS

Twenty-two cases of primary invasive breast carcinoma with local/distant metastasis were retrieved from the pathology archives. The status of estrogen and progesterone receptors by immunohistochemistry was recorded along with other pertinent case data. Next generation sequencing was performed on formalin-fixed paraffin embedded blocks of tumor.

RESULTS

The mean age of the study subjects was 57.9 ± 13.3 years. TP53 mutation was the most common gene alteration in this study and was seen in 40.9% cases. ROS1 gene was mutated in 44.4% PR negative breast cancers while being wild type in the twelve PR positive tumors. (p = 0.021).STRING interaction network constructed with ROS1 and PR revealed a significantly higher number of interactions in this network than expected (p-value 0.000973).

CONCLUSION

This study highlights the significantly higher incidence of ROS1 gene alterations in metastatic PR- breast cancers, with STRING network analysis revealing higher nodal interaction in the nodal network comprised of PR and ROS1 exclusive of ER.

HER2-low-positive breast cancer: evolution from primary tumor to residual disease after neoadjuvant treatment

Approximately a half of breast tumors classified as HER2-negative exhibit HER2-low-positive expression. We recently described a high instability of HER2-low-positive expression from primary breast cancer (BC) to relapse. Previous studies reporting discordance in HER2 status between baseline biopsy and residual disease (RD) in patients undergoing neoadjuvant treatment did not include the HER2-low-positive category. The aim of this study is to track the evolution of HER2-low-positive expression from primary BC to RD after neoadjuvant treatment. Patients undergoing neoadjuvant treatment with available baseline tumor tissue and matched samples of RD (in case of no pCR) were included. HER2-negative cases were sub-classified as HER2-0 or HER2-low-positive (IHC 1+ or 2+ and ISH negative). Four-hundred forty-six patients were included. Primary BC phenotype was: HR-positive/HER2-negative 23.5%, triple-negative (TN) 35%, HER2-positive 41.5%. HER2-low-positive cases were 55.6% of the HER2-negative cohort and were significantly enriched in the HR-positive/HER2-negative vs. TN subgroup (68.6% vs. 46.8%, p = 0.001 χ2 test). In all, 35.3% of non-pCR patients (n = 291) had a HER2-low-positive expression on RD. The overall rate of HER2 expression discordance was 26.4%, mostly driven by HER2-negative cases converting either from (14.8%) or to (8.9%) HER2-low-positive phenotype. Among HR-positive/HER2-negative patients with HER2-low-positive expression on RD, 32.0% and 57.1% had an estimated high risk of relapse according to the residual proliferative cancer burden and CPS-EG score, respectively. In conclusion, HER2-low-positive expression showed high instability from primary BC to RD after neoadjuvant treatment. HER2-low-positive expression on RD may guide personalized adjuvant treatment for high-risk patients in the context of clinical trials with novel anti-HER2 antibody-drug conjugates.

Definition of High-Risk Early Hormone-Positive HER2−Negative Breast Cancer: A Consensus Review

Breast cancer is one of the major causes of cancer-related morbidity and mortality in women worldwide. During the past three decades, several improvements in the adjuvant treatment of hormone receptor-positive/HER2−negative breast cancer have been achieved with the introduction of optimized adjuvant chemotherapy and endocrine treatment. However, estimating the risk of relapse of breast cancer on an individual basis is still challenging. The IRIDE (hIGh Risk DEfinition in breast cancer) working group was established with the aim of reviewing evidence from the literature to synthesize the current relevant features that predict hormone-positive/HER2−negative early breast cancer relapse. A panel of experts in breast cancer was involved in identifying clinical, pathological, morphological, and genetic factors. A RAND consensus method was used to define the relevance of each risk factor. Among the 21 features included, 12 were considered relevant risk factors for relapse. For each of these, we provided a consensus statement and relevant comments on the supporting scientific evidence. This work may guide clinicians in the practical management of hormone-positive/HER2−negative early breast cancers.

A Novel Data Analytics-derived Metric (Nearest Cluster Distance) Is Easily Implemented in Routine Practice and Correctly Identifies Breast Cancer Cases for Quality Review

Background

Errors in breast cancer grading and predictive testing are clinically important and can be difficult to detect in routine practice. A quality metric able to identify a subset of breast cancer cases which are high yield on quality review would be of practical clinical benefit.

Methods

Data analytic techniques were used to generate consensus tumor signature centers from a dataset over 500 breast cancer cases from a single practice. Cases were assigned a novel metric, Nearest Cluster Distance, corresponding to their distances from the nearest tumor signature center. The subset of tumors exceeding a cutoff for this metric were flagged, and then reviewed and rescored in a blinded fashion together with matched controls. A simplified version of this metric was created using universally accessible methods.

Results

Flagged cases showed statistically significant movement toward consensus tumor signature centers compared with controls, consistent with identification of cases which could benefit from review and possible rescoring. The simplified metric performs identically.

Conclusion

This method can be readily applied in routine practice and is promising as a real time quality check for breast cancer diagnosis and reporting.

De-escalation of five-year adjuvant endocrine therapy in patients with estrogen receptor-low positive (immunohistochemistry staining 1%-10%) breast cancer: Propensity-matched analysis from a prospectively maintained cohort

BACKGROUND

The standard 5 years of endocrine therapy has demonstrated additional benefits compared with short-term (2-3 years) treatment in patients with estrogen receptor (ER)-positive breast cancer; however, data specific to ER-low positive breast cancer (1%-10% by immunohistochemistry) are limited, and it is unclear whether long-term treatment is still necessary for this subgroup.

METHODS

The authors used the prospectively maintained Breast Surgery Database of Fudan University Shanghai Cancer Center for this propensity-matched analysis. The primary end point was disease-free survival. Multivariate Cox regression analysis and propensity score-matching methods were used to minimize bias. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated. All statistics were 2-sided.

RESULTS

From 2012 to 2017, 22,768 consecutive women had pathologically confirmed, early stage breast cancer, and 1013 (4.45%) were identified with ER-low positive disease. Among these, 634 patients met the inclusion criteria and were divided into 3 groups: those who received no endocrine therapy (n = 89), those who received 2 to 3 years of endocrine therapy (n = 185), and those who received approximately 5 years of endocrine therapy (n = 360). At a median follow-up of 65 months, there was no significant difference in disease-free survival between patients who received 2 to 3 years and 5 years of endocrine therapy (HR, 0.82; 95% CI, 0.51-1.33; P = .43). The findings were consistent after multivariate Cox analysis of the propensity score-matched samples (5 vs 2-3 years of treatment: HR, 0.74; 95% CI, 0.41-1.31; P = .30).

CONCLUSIONS

Short-term endocrine therapy for 2 to 3 years might be an alternative for patients who have ER-low positive breast cancer instead of the standard 5 years of treatment.

The prognostic and predictive value of ESR1 fusion gene transcripts in primary breast cancer

Background

In breast cancer (BC), recurrent fusion genes of estrogen receptor alpha (ESR1) and AKAP12, ARMT1 and CCDC170 have been reported. In these gene fusions the ligand binding domain of ESR1 has been replaced by the transactivation domain of the fusion partner constitutively activating the receptor. As a result, these gene fusions can drive tumor growth hormone independently as been shown in preclinical models, but the clinical value of these fusions have not been reported. Here, we studied the prognostic and predictive value of different frequently reported ESR1 fusion transcripts in primary BC.

Methods

We evaluated 732 patients with primary BC (131 ESR1-negative and 601 ESR1-positive cases), including two ER-positive BC patient cohorts: one cohort of 322 patients with advanced disease who received first-line endocrine therapy (ET) (predictive cohort), and a second cohort of 279 patients with lymph node negative disease (LNN) who received no adjuvant systemic treatment (prognostic cohort). Fusion gene transcript levels were measured by reverse transcriptase quantitative PCR. The presence of the different fusion transcripts was associated, in uni- and multivariable Cox regression analysis taking along current clinico-pathological characteristics, to progression free survival (PFS) during first-line endocrine therapy in the predictive cohort, and disease- free survival (DFS) and overall survival (OS) in the prognostic cohort.

Results

The ESR1-CCDC170 fusion transcript was present in 27.6% of the ESR1-positive BC subjects and in 2.3% of the ESR1-negative cases. In the predictive cohort, none of the fusion transcripts were associated with response to first-line ET. In the prognostic cohort, the median DFS and OS were respectively 37 and 93 months for patients with an ESR1-CCDC170 exon 8 gene fusion transcript and respectively 91 and 212 months for patients without this fusion transcript. In a multivariable analysis, this ESR1-CCDC170 fusion transcript was an independent prognostic factor for DFS (HR) (95% confidence interval (CI): 1.8 (1.2–2.8), P = 0.005) and OS (HR (95% CI: 1.7 (1.1–2.7), P = 0.023).

Conclusions

Our study shows that in primary BC only ESR1-CCDC170 exon 8 gene fusion transcript carries prognostic value. None of the ESR1 fusion transcripts, which are considered to have constitutive ER activity, was predictive for outcome in BC with advanced disease treated with endocrine treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09265-1.

Application of Microfluidic Systems for Breast Cancer Research

Cancer is a disease in which cells in the body grow out of control; breast cancer is the most common cancer in women in the United States. Due to early screening and advancements in therapeutic interventions, deaths from breast cancer have declined over time, although breast cancer remains the second leading cause of cancer death among women. Most deaths are due to metastasis, as cancer cells from the primary tumor in the breast form secondary tumors in remote sites in distant organs. Over many years, the basic biological mechanisms of breast cancer initiation and progression, as well as the subsequent metastatic cascade, have been studied using cell cultures and animal models. These models, although extremely useful for delineating cellular mechanisms, are poor predictors of physiological responses, primarily due to lack of proper microenvironments. In the last decade, microfluidics has emerged as a technology that could lead to a paradigm shift in breast cancer research. With the introduction of the organ-on-a-chip concept, microfluidic-based systems have been developed to reconstitute the dominant functions of several organs. These systems enable the construction of 3D cellular co-cultures mimicking in vivo tissue-level microenvironments, including that of breast cancer. Several reviews have been presented focusing on breast cancer formation, growth and metastasis, including invasion, intravasation, and extravasation. In this review, realizing that breast cancer can recur decades following post-treatment disease-free survival, we expand the discussion to account for microfluidic applications in the important areas of breast cancer detection, dormancy, and therapeutic development. It appears that, in the future, the role of microfluidics will only increase in the effort to eradicate breast cancer.

Integrating and validating automated digital imaging analysis of estrogen receptor immunohistochemistry in a fully digital workflow for clinical use

Background

Design

Results

Conclusions

Non-conventional and Investigational PET Radiotracers for Breast Cancer: A Systematic Review

Breast cancer is one of the most common malignancies in women, with high morbidity and mortality rates. In breast cancer, the use of novel radiopharmaceuticals in nuclear medicine can improve the accuracy of diagnosis and staging, refine surveillance strategies and accuracy in choosing personalized treatment approaches, including radioligand therapy. Nuclear medicine thus shows great promise for improving the quality of life of breast cancer patients by allowing non-invasive assessment of the diverse and complex biological processes underlying the development of breast cancer and its evolution under therapy. This review aims to describe molecular probes currently in clinical use as well as those under investigation holding great promise for personalized medicine and precision oncology in breast cancer.

Effect of Estrogen Receptor Expression Level and Hormonal Therapy on Prognosis of Early Breast Cancer

Purpose

Estrogen receptor (ER) expression in breast cancer plays an essential role in carcinogenesis and disease progression. Recently, tumors with low level (1%–10%) of ER expression have been separately defined as ER low positive (ER^low). It is suggested that ER^low tumors might be morphologically and behaviorally different from tumors with high ER expression (ER^high).

Materials and Methods

Retrospective analysis of a prospective cohort database was performed. Patients who underwent curative surgery for early breast cancer and had available medical records were included for analysis. Difference in clinicopathological characteristics, endocrine responsiveness and five-year recurrence-free survival was evaluated between different ER subgroups (ER^high, ER^low, and ER-negative [ER⁻]).

Results

A total of 2,162 breast cancer patients were included in the analysis, Tis and T1 stage. Among them, 1,654 (76.5%) were ER^high, 54 (2.5%) were ER^low, and 454 (21.0%) were ER⁻ patients. ER^low cases were associated with smaller size, higher histologic grade, positive human epidermal growth factor receptor 2, negative progesterone receptor, and higher Ki-67 expression. Recurrence rate was highest in ER⁻ tumors and was inversely proportional to ER expression. Recurrence-free survival was not affected by hormonal therapy in the ER^low group (p=0.418).

Conclusion

ER^low breast cancer showed distinct clinicopathological features. ER^low tumors seemed to have higher recurrence rates compared to ER^high tumors, and they showed no significant benefit from hormonal therapy. Future large scale prospective studies are necessary to validate the treatment options for ER^low breast cancer.

Phenotype Discordance between Primary Tumor and Metastasis Impacts Metastasis Site and Outcome: Results of WSG-DETECT-PriMet

Introduction

Tumor biological factors of breast cancer (BC) such as hormone receptor (HR) status, HER2 status, and grade can differ in the metastatic cascade from primary to lymph node (LN) metastasis and to distant metastatic tissue. Systematic data regarding therapeutic consequences are yet limited.

Methods

We conducted a prospectively planned, retrospective cohort study comparing BC phenotype in tissue from primary tumors (PTs), locoregional LN metastases, and disease recurrence (DR). HR and HER2 as well as tumor grade in PTs and DR were obtained by a database search. No centralized biomarker testing was performed. The impact of changes in tumor biological factors on post-recurrence survival (PRS) and overall survival was analyzed.

Results

PriMet comprises 635 patients (LN tissue in 142 patients). Discrepancies for HR or HER2 status between PT and DR were observed in 18.7 and 21.6% of cases, respectively. For HR status, positivity of PT and negativity of DR was seen more often (13.2%) than vice versa (5.5%). For HER2 status, negativity of the primary and positivity of DR was seen more often (14.9%) than vice versa (6.7%). Discordance was more often observed between PT and LN metastasis compared to LN versus DR. However, numbers were small. Compared to concordant non-triple-negative (TN) disease, concordant TN disease showed significantly inferior PRS.

Conclusion

We demonstrate receptor discordance to occur relatively frequently between PT, LN metastasis, and DR and to impact patient prognosis. However, clinical consequences of receptor discordance need to be drawn with caution considering clinical aspects as well as tumor biology.

Radionuclide-Based Imaging of Breast Cancer: State of the Art

Simple Summary

Breast cancer is one of the most commonly diagnosed malignant tumors, possessing high incidence and mortality rates that threaten women’s health. Thus, early and effective breast cancer diagnosis is crucial for enhancing the survival rate. Radionuclide molecular imaging displays its advantages for detecting breast cancer from a functional perspective. Noninvasive visualization of biological processes with radionuclide-labeled small metabolic compounds helps elucidate the metabolic state of breast cancer, while radionuclide-labeled ligands/antibodies for receptor-targeted radionuclide molecular imaging is sensitive and specific for visualization of the overexpressed molecular markers in breast cancer. This review focuses on the most recent developments of novel radiotracers as promising tools for early breast cancer diagnosis.

Abstract

Breast cancer is a malignant tumor that can affect women worldwide and endanger their health and wellbeing. Early detection of breast cancer can significantly improve the prognosis and survival rate of patients, but with traditional anatomical imagine methods, it is difficult to detect lesions before morphological changes occur. Radionuclide-based molecular imaging based on positron emission tomography (PET) and single-photon emission computed tomography (SPECT) displays its advantages for detecting breast cancer from a functional perspective. Radionuclide labeling of small metabolic compounds can be used for imaging biological processes, while radionuclide labeling of ligands/antibodies can be used for imaging receptors. Noninvasive visualization of biological processes helps elucidate the metabolic state of breast cancer, while receptor-targeted radionuclide molecular imaging is sensitive and specific for visualization of the overexpressed molecular markers in breast cancer, contributing to early diagnosis and better management of cancer patients. The rapid development of radionuclide probes aids the diagnosis of breast cancer in various aspects. These probes target metabolism, amino acid transporters, cell proliferation, hypoxia, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), gastrin-releasing peptide receptor (GRPR) and so on. This article provides an overview of the development of radionuclide molecular imaging techniques present in preclinical or clinical studies, which are used as tools for early breast cancer diagnosis.

Type 1 Nuclear Receptor Activity in Breast Cancer: Translating Preclinical Insights to the Clinic

The nuclear receptor (NR) family of transcription factors is intimately associated with the development, progression and treatment of breast cancer. They are used diagnostically and prognostically, and crosstalk between nuclear receptor pathways and growth factor signalling has been demonstrated in all major subtypes of breast cancer. The majority of breast cancers are driven by estrogen receptor α (ER), and anti-estrogenic therapies remain the backbone of treatment, leading to clinically impactful improvements in patient outcomes. This serves as a blueprint for the development of therapies targeting other nuclear receptors. More recently, pivotal findings into modulating the progesterone (PR) and androgen receptors (AR), with accompanying mechanistic insights into NR crosstalk and interactions with other proliferative pathways, have led to clinical trials in all of the major breast cancer subtypes. A growing body of evidence now supports targeting other Type 1 nuclear receptors such as the glucocorticoid receptor (GR), as well as Type 2 NRs such as the vitamin D receptor (VDR). Here, we reviewed the existing preclinical insights into nuclear receptor activity in breast cancer, with a focus on Type 1 NRs. We also discussed the potential to translate these findings into improving patient outcomes.

Customizing local and systemic therapies for women with early breast cancer: the St. Gallen International Consensus Guidelines for treatment of early breast cancer 2021

The 17th St Gallen International Breast Cancer Consensus Conference in 2021 was held virtually, owing to the global COVID-19 pandemic. More than 3300 participants took part in this important bi-annual critical review of the 'state of the art' in the multidisciplinary care of early-stage breast cancer. Seventy-four expert panelists (see Appendix 1) from all continents discussed and commented on the previously elaborated consensus questions, as well as many key questions on early breast cancer diagnosis and treatment asked by the audience. The theme of this year's conference was 'Customizing local and systemic therapies.' A well-organized program of pre-recorded symposia, live panel discussions and real-time panel voting results drew a worldwide audience of thousands, reflecting the far-reaching impact of breast cancer on every continent. The interactive technology platform allowed, for the first time, audience members to ask direct questions to panelists, and to weigh in with their own vote on several key panel questions. A hallmark of this meeting was to focus on customized recommendations for treatment of early-stage breast cancer. There is increasing recognition that the care of a breast cancer patient depends on highly individualized clinical features, including the stage at presentation, the biological subset of breast cancer, the genetic factors that may underlie breast cancer risk, the genomic signatures that inform treatment recommendations, the extent of response before surgery in patients who receive neoadjuvant therapy, and patient preferences. This customized approach to treatment requires integration of clinical care between patients and radiology, pathology, genetics, and surgical, medical and radiation oncology providers. It also requires a dynamic response from clinicians as they encounter accumulating clinical information at the time of diagnosis and then serially with each step in the treatment plan and follow-up, reflecting patient experiences and treatment response.

Lost but Not Least-Novel Insights into Progesterone Receptor Loss in Estrogen Receptor-Positive Breast Cancer

Estrogen receptor α (ERα) and progesterone receptor (PgR) are crucial prognostic and predictive biomarkers that are usually co-expressed in breast cancer (BC). However, 12-24% of BCs present ERα(+)/PgR(-) phenotype at immunohistochemical evaluation. In fact, BC may either show primary PgR(-) status (in chemonaïve tumor sample), lose PgR expression during neoadjuvant treatment, or acquire PgR(-) phenotype in local relapse or metastasis. The loss of PgR expression in ERα(+) breast cancer may signify resistance to endocrine therapy and poorer outcomes. On the other hand, ERα(+)/PgR(-) BCs may have a better response to neoadjuvant chemotherapy than double-positive tumors. Loss of PgR expression may be a result of pre-transcriptional alterations (copy number loss, mutation, epigenetic modifications), decreased transcription of the PGR gene (e.g., by microRNAs), and post-translational modifications (e.g., phosphorylation, sumoylation). Various processes involved in the down-regulation of PgR have distinct consequences on the biology of cancer cells. Occasionally, negative PgR status detected by immunohistochemical analysis is paradoxically associated with enhanced transcriptional activity of PgR that might be inhibited by antiprogestin treatment. Identification of the mechanism of PgR loss in each patient seems challenging, yet it may provide important information on the biology of the tumor and predict its responsiveness to the therapy.

A novel immune subtype classification of ER-positive, PR-negative and HER2-negative breast cancer based on the genomic and transcriptomic landscape

BACKGROUND

The diversity and plasticity behind ER+/PR-/HER2- breast cancer have not been widely explored. It is essential to identify heterogeneous microenvironment phenotypes and investigate specific genomic events driving the formation of these phenotypes.

METHODS

Based on the immune-related gene expression profiles of 411 ER+/PR-/HER2- breast cancers in the METABRIC cohort, we used consensus clustering to identify heterogeneous immune subtypes and assessed their reproducibility in an independent meta-cohort including 135 patients collected from GEO database. We further analyzed the differences of cellular and molecular characteristics, and potential immune escape mechanism among immune subtypes. In addition, we constructed a transcriptional trajectory to visualize the distribution of individual patient.

RESULTS

Our analysis identified and validated five reproducible immune subtypes with distinct cellular and molecular characteristics, potential immune escape mechanisms, genomic drivers, as well as clinical outcomes. An immune-cold subtype, with the least amount of lymphocyte infiltration, had a poorer prognosis. By contrast, an immune-hot subtype, which demonstrated the highest infiltration of CD8+ T cells, DCs and NK cells, and elevated IFN-γ response, had a comparatively favorable prognosis. Other subtypes showed more diverse gene expression and immune infiltration patterns with distinct clinical outcomes. Finally, our analysis revealed a complex immune landscape consisting of both discrete cluster and continuous spectrum.

CONCLUSION

Overall, this study revealed five heterogeneous immune subtypes among ER+/PR-/HER2- breast cancer, also provided important implications for clinical translations.

Prevalence, treatment patterns, and prognosis of low estrogen receptor-positive (1% to 10%) breast cancer: a single institution's experience in Korea

PURPOSE

To determine prevalence, clinicopathological characteristics, initial treatments, and outcomes associated with low estrogen receptor (ER)-expressing invasive breast cancer.

METHODS

This retrospective, non-interventional database study included patients undergoing surgery with curative intent for invasive ductal or lobular breast cancer. Patients were treated between January 2003-December 2012. Demographics, clinicopathological characteristics, initial treatments, and outcomes were abstracted from patient records. Patients were categorized using immunohistochemistry to determine ER, progesterone receptor, and human epidermal growth factor receptor 2 (HER2) levels. ER-positive patients were subclassified as ER-low (1% to 10%) and ER-high (> 10%) according to the Allred Proportion Score. Disease-free survival (DFS) and overall survival (OS) were estimated by the Kaplan-Meier method and compared among groups by log-rank test.

RESULTS

5930 patients were included (median follow-up, 80.9 months). Of all patients included, 117 (2.0%) had ER-low tumors: 63 (53.8%) of whom had HER2- tumors and 54 (46.2%) HER2+ tumors. Five-year DFS and OS were highest in the ER-high/HER2- cohort (94.0% and 98.6%, respectively) and lowest in the triple-negative breast cancer (TNBC; 81.3% and 90.1%) and ER-low/HER2- (85.7% and 92.1%) cohorts. Menopausal status, elevated Ki-67, higher nuclear grade, higher tumor stage, presence of lymphovascular invasion, greater regional lymph node involvement, and larger tumor size were all potential prognostic factors for shorter DFS and OS.

CONCLUSION

Patients with ER-low/HER2- breast cancer had similar clinicopathological characteristics, treatments, and outcomes as patients with TNBC irrespective of disease setting. Further research is needed to understand predictive and prognostic factors associated with ER-low/HER2- disease.

Impact of estrogen receptor levels on outcome in non-metastatic triple negative breast cancer patients treated with neoadjuvant/adjuvant chemotherapy

Although 1% is the recommended cut-off to define estrogen receptor (ER) positivity, a 10% cut-off is often used in clinical practice for therapeutic purposes. We here evaluate clinical outcomes according to ER levels in a monoinstitutional cohort of non-metastatic triple-negative breast cancer (BC) patients undergoing (neo)adjuvant chemotherapy. Clinicopathological data of 406 patients with ER < 10% HER2-negative BC treated with (neo)adjuvant chemotherapy between 01/2000 and 04/2019 were collected. Patients were categorized in ER-negative (ER < 1%; N = 364) and ER-low positive (1-9%, N = 42). At a median follow-up of 54 months, 88 patients had relapsed and 64 died. No significant difference was observed in invasive relapse-free survival (iRFS) and overall survival (OS) according to ER expression levels, both at univariate and multivariate analysis (5-years iRFS 74.0% versus 73.1% for ER-negative and ER-low positive BC, respectively, p = 0.6; 5-years OS 82.3% versus 76.7% for ER-negative and ER-low positive BC, respectively, p = 0.8). Among the 165 patients that received neoadjuvant chemotherapy, pathological complete response rate was similar in the two cohorts (38% in ER-negative, 44% in ER-low positive, p = 0.498). In conclusion, primary BC with ER1-9% shows similar clinical behavior to ER 1% BC. Our results suggest the use of a 10% cut-off, rather than <1%, to define triple-negative BC.

Estrogen receptor-low breast cancer: Biology chaos and treatment paradox

Hormone receptor testing mainly serves the purpose of guiding treatment choices for breast cancer patients. Patients with estrogen receptor (ER)‐positive breast cancers show significant response to endocrine therapy. However, the methods to define ER status and eligibility for treatment remain controversial. Despite recent guidelines considering staining ≥1% of tumor nuclei by immunohistology as ER‐positive, it has raised concerns on the benefit of endocrine therapy for tumors with ER 1%‐10% expression, termed “ER‐low positive”. This subgroup accounts for 3% to 9% of all patients and is likely to have unique molecular features, and therefore distinct therapeutic response to endocrine therapy compared with ER‐high positive tumors. The latest guidelines did not provide detailed descriptions for those patients, resulting in inconsistent treatment strategies. Consequently, we aimed to resolve this dilemma comprehensively. This review discusses molecular traits and recent ER‐low positive breast cancer innovations, highlighting molecular‐targeted treatment rather than traditional unified endocrine therapy for future basic and clinical research.

Aptamer-based sensing of breast cancer biomarkers: a comprehensive review of analytical figures of merit

INTRODUCTION

Accurate determination of the aberrantly expressed biomarkers such as human epidermal growth factor receptor 2 (HER2), carcinoembryonic antigen (CEA), platelet-derived growth factor (PDGF), mucin 1 (MUC1), and vascular endothelial growth factor VEGF₁₆₅ have played an essential role in the clinical management of the breast cancer. Assessment of these cancer-specific biomarkers has conventionally relied on time-taking methods like the enzyme-linked immunosorbent assay and immunohistochemistry. However, recent development in the aptamer-based diagnostics has allowed developing tools that may substitute the conventional means of biomarker assessment in breast cancer. Adopting the aptamer-based diagnostic tools (aptasensors) to clinical practices will depend on their analytical performance on clinical samples.

AREAS COVERED

In this review, we provide an overview of the analytical merits of HER2, CEA, PDGF, MUC1, and VEGF₁₆₅ aptasensors. Scopus and Pubmed databases were searched for studies reporting aptasensor development for the listed breast cancer biomarkers in the past one decade. Linearity, detection limit, and response time are emphasized.

EXPERT OPINION

In our opinion, aptasensors have proven to be on a par with the antibody-based methods for detection of various breast cancer biomarkers. Though robust validation of the aptasensors on significant sample size is required, their ability to detect pathophysiological range of biomarkers suggest the possibility of future clinical adoption.

Estrogen Receptor-α Quantification in Breast Cancer: Concordance Between Immunohistochemical Assays and mRNA-In Situ Hybridization for ESR1 Gene

Immunohistochemical (IHC) quantification of estrogen receptor-α (ER) is used for assessment of treatment regimen in breast cancer. Different ER IHC assays may produce diverging results, because of different antibody clones, protocols, and stainer platforms. Objective tissue-based techniques to assess sensitivity and specificity of IHC assays are therefore needed. We tested the usability of ER mRNA-in situ hybridization (mRNA-ISH) in comparison with assays based on clones SP1 and 6F11. We selected 56 archival specimens according to their reported ER IHC positivity, representing a wide spectrum from negative to strongly positive cases. The specimens were used to prepare 4 TMAs with 112 cores. Serial sections of each TMA were stained for ER and pan-cytokeratin (PCK) by IHC and ESR1 (ER gene) by mRNA-ISH. Digital image analysis (DIA) was used to determine ER IHC H-score. ESR1 mRNA-ISH was scored both manually and by DIA. DIA showed a nonlinear correlation between IHC and ESR1 mRNA-ISH with R²-values of 0.80 and 0.78 for the ER antibody clones SP1 and 6F11, respectively. Comparison of manual mRNA-ISH scoring categories and SP1 and 6F11 IHC H-scores showed a highly significant relationship (P<0.001). In conclusion, the study showed good correlation between mRNA-ISH and IHC, suggesting that mRNA-ISH can be a valuable tool in the assessment of the sensitivity and specificity of ER IHC assays.

A simple digital image analysis system for automated Ki67 assessment in primary breast cancer

AIMS

Ki67 is a well-established immunohistochemical marker associated with cell proliferation that has prognostic and predictive value in breast cancer. Quantitative evaluation of Ki67 is traditionally performed by assessing stained tissue slides with light microscopy. Automated image analysis systems have become available and, if validated, could provide greater standardisation and improved precision of Ki67 scoring. Here, we aimed to evaluate the use of the Cognition Master Professional Suite (CogM) image analysis software, which is a simple system for scoring Ki67 in primary breast cancer samples.

METHODS AND RESULTS

Sections from 94 core-cut biopsies, 20 excision specimens and 29 pairs of core-cut biopsies and excision specimens were stained for Ki67 with MIB1 antibody and the Dako EnVision FLEX Detection System. Stained slides were scanned to convert them to digital data. Computer-based Ki67 scoring was performed with CogM. Manual Ki67 scoring assessment was conducted on previously stained sections from the same biopsies with a clinically validated system that had been calibrated against the risk of recurrence. A high correlation between manual and digital scores was observed [r_Cores  = 0.92, 95% confidence interval (CI) 0.87-0.94, P < 0.0001; r_Excisions  = 0.95, 95% CI 0.86-0.98, P < 0.0001] and there was no significant bias between them (P = 0.45). There was also a high correlation of Ki67 scores between paired core-cut biopsies and excision specimens when CogM was used (r = 0.78, 95% CI 0.59-0.89, P < 0.0001).

CONCLUSIONS

CogM image analysis allows for standardised automated Ki67 scoring that accurately replicates previously clinically validated and calibrated manual scores.

Characterization of estrogen receptor-low-positive breast cancer

PURPOSE

The biology of breast cancer with a low expression level (1-10%) of estrogen receptor (ER) remains a matter of confusion. The recent American Society of Oncology/College of American Pathologist Guidelines have recommended reporting such tumors as a new "ER-low-positive" category with a recommended comment to emphasize the possible overall benefit of endocrine therapies in these patients. The aim of the study was to analyze the clinicopathologic features and clinical outcomes of ER-low-positive breast cancers.

METHODS

We characterized the clinicopathologic features and survival outcomes of ER-low-positive breast cancers in our 4179 patients diagnosed from 1998 to 2018.

RESULTS

The ER-positive, ER-low-positive, and ER-negative cases in our cohort were 2982 (71.4%), 97 (2.3%), and 1100 (26.3%), respectively. ER-low-positive tumors showed similar clinicopathologic characteristics yet significantly superior prognosis when compared to ER-negative tumors, while demonstrated largely overlapping survival outcomes with ER-positive tumors in the entire cohort. In the subcohort of tumors with a PR-positive phenotype, the prognosis of ER-low-positive tumors was intermediate between that of the ER-positive and ER-negative groups. ER-low-positive/PR-positive tumors had a significantly worse prognosis than ER-positive tumors, and a trend toward favorable survival outcomes when compared to ER-negative tumors, although no significant difference was identified for the latter. In contrast, the ER-positive and ER-low-positive groups showed similar survival outcomes in the subset of tumors with a PR-negative status, both being significantly better than ER-negative tumors.

CONCLUSIONS

PR status as a surrogate marker of functional ER signaling provides critical information in this regard. These findings suggest that while ER-low-positive tumors are themselves heterogeneous, they often respond to endocrine treatment. Analysis of molecular signatures and standardization of therapeutic strategies are important to understand the biology of ER-low-positive tumors and to enable optimal treatment in the pursuit of individualized medicine.

Molecular intrinsic versus clinical subtyping in breast cancer: A comprehensive review

Breast cancer is a heterogeneous disease manifesting diversity at the molecular, histological and clinical level. The development of breast cancer classification was centered on informing clinical decisions. The current approach to the classification of breast cancer, which categorizes this disease into clinical subtypes based on the detection of estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and proliferation marker Ki67, is not ideal. This is manifested as a heterogeneity of therapeutic responses and outcomes within the clinical subtypes. The newer classification model, based on gene expression profiling (intrinsic subtyping) informs about transcriptional responses downstream from IHC single markers, revealing deeper appreciation for the disease heterogeneity and capturing tumor biology in a more comprehensive way than an expression of a single protein or gene alone. While accumulating evidences suggest that intrinsic subtypes provide clinically relevant information beyond clinical surrogates, it is imperative to establish whether the current conventional immunohistochemistry-based clinical subtyping approach could be improved by gene expression profiling and if this approach has a potential to translate into clinical practice.

Hormone Receptor Loss in Breast Cancer: Molecular Mechanisms, Clinical Settings, and Therapeutic Implications

Hormone receptor-positive breast cancer (HR+ BC) accounts for approximately 75% of new BC diagnoses. Despite the undisputable progresses obtained in the treatment of HR+ BC in recent years, primary or acquired resistance to endocrine therapies still represents a clinically relevant issue, and is largely responsible for disease recurrence after curative surgery, as well as for disease progression in the metastatic setting. Among the mechanisms causing primary or acquired resistance to endocrine therapies is the loss of estrogen/progesterone receptor expression, which could make BC cells independent of estrogen stimulation and, consequently, resistant to estrogen deprivation or the pharmacological inhibition of estrogen receptors. This review aims at discussing the molecular mechanisms and the clinical implications of HR loss as a result of the therapies used in the neoadjuvant setting or for the treatment of advanced disease in HR+ BC patients.

Survey of low ER-positive expression and its correlation with other clinical and pathological factors in breast cancer

Introduction

Breast cancer is the most common cancer in women. Owning to the prominent role of biomarkers in molecular classification of breast cancer in recent years, evaluation of estrogen receptor (ER), progesterone receptor (PR), and Her2/neu seems to be required for prognosis and treatment of patients.

Material and Methods

One-hundred twenty two patients with primary breast carcinoma were selected and immunohistochemistry staining for ER, PR, and Her2/neu were performed on representative paraffin blocks. ER level can be semi-quantified by immunohistochemistry using the H-score. The score, given as the sum of the percent of tumor cells staining multiplied by the intensity level, ranges from 0 to 300 as low, intermediate, and high grades. The statistical association of ER expression with the level of PR and Her2/neu, tumor size, necrosis, microscopic grade, vascular invasion, and lymph node involvement were analyzed using SPSS16 software.

Results

Results showed that among 122 studied patients, 44.3% were in the low ER-positive group where most of these cases (22.1%) were Her2/neu negative. Although there was a reciprocal interplay between the expression of ER and Her2/neu, increased expression of ER had a direct relation with PR level. However, there was no statistical relation between ER level with age, tumor size, necrosis, microscopic grade, vascular invasion, and lymph node involvement.

Discussion

The study clearly indicated that low ER group encompasses the high frequency of breast cancer patients. Furthermore, the most cases of low ER patients were in Her2/neu negative group.

How to Predict Metastasis in Luminal Breast Cancer? Current Solutions and Future Prospects

Breast cancer metastasis is the main cause of breast cancer mortality. Luminal breast cancer represents the majority of breast cancer cases and, despite relatively good prognosis, its heterogeneity creates problems with a proper stratification of patients and correct identification of the group with a high risk of metastatic relapse. Current prognostic tools are based on the analysis of the primary tumor and, despite their undisputed power of prediction, they might be insufficient to foresee the relapse in an accurate and precise manner, especially if the relapse occurs after a long period of dormancy, which is very common in luminal breast cancer. New approaches tend to rely on body fluid analyses, which have the advantage of being non-invasive and versatile and may be repeated and used for monitoring the disease in the long run. In this review we describe the current, newly-developed, and only-just-discovered methods which are or may become useful in the assessment of the probability of the relapse.