Breast cancer subtypes: morphologic and biologic characterization

Insights into the molecular and genetic role of obesity in breast cancer pathogenesis

The epidemic of obesity is a growing concern and is one of the major risk factors for several chronic diseases, including several types of cancers. The correlation of breast cancer with obesity has been extensively studied and involves an interplay of hormonal, metabolic, and genetic factors explored in this review. Inflammation and hormone dysregulation play an important role in promoting a protumorigenic environment through adipose tissue, which is involved in energy storage and functions as an endocrine organ. As a result, various cytokines, primarily proinflammatory in nature, are released, resulting in low-grade inflammation promoting tumor growth. Additionally, obese conditions also induce imbalances in hormones, particularly estrogen and insulin, both of which drive carcinogenesis. Genetic components such as single nucleotide polymorphisms also play critical roles in modulating the correlation between obesity and breast cancer. This review provides a comprehensive overview of various mechanisms underlying obesity and breast cancer incidence and progression.

Associations Between Lipid Traits and Breast Cancer Risk: A Mendelian Randomization Study in African Women

BACKGROUND

Blood lipids are implicated in the development of breast cancer (BC), though the genetic connection remains unclear, particularly in African populations. Observational studies on this topic are limited by confounding factors and reverse causation, potentially affecting the reliability of findings.

METHODS

We applied univariate and multivariable two-sample Mendelian randomization to assess the causal association between blood lipids (total cholesterol [TC], high-density lipoprotein [HDL], low-density lipoprotein [LDL], and triglycerides [TG]) and BC. Summary-level data for lipid traits were sourced from the Africa Wits-INDEPTH partnership for Genomic Research (AWI-Gen) (N = 10,603 women). BC data were obtained from the largest genome-wide association study of BC in African women, comprising 18,034 BC cases and 22,104 controls.

RESULTS

Our analysis revealed that genetically predicted TG was associated with a decreased BC risk (OR = 0.73, 95% CI = 0.56-0.95, p = 0.018. In contrast, no significant associations were found between TC, HDL, or LDL levels and BC risk: TC (OR = 1.04, 95% CI = 0.93-1.18, p = 0.467), HDL (OR = 1.29, 95% CI = 0.93-1.79, p = 0.121), and LDL (OR = 1.04, 95% CI = 0.90-1.20, p = 0.577). After adjusting for the effects of other lipid traits, the association between TG and BC was attenuated, and no associations were observed for TC, HDL, or LDL. No causal relationship was found between lipid traits and BC subtypes.

CONCLUSIONS

This study provides evidence that elevated triglycerides may be associated with a reduced risk of BC, whereas no significant associations were observed for TC, HDL, or LDL. Further research is needed to better understand the underlying mechanisms and potential clinical implications of these findings.

Molecular Classification of Breast Cancer Using Weakly Supervised Learning

PURPOSE

The molecular classification of breast cancer is crucial for effective treatment. The emergence of digital pathology has ushered in a new era in which weakly supervised learning leveraging whole-slide images has gained prominence in developing deep learning models because this approach alleviates the need for extensive manual annotation. Weakly supervised learning was employed to classify the molecular subtypes of breast cancer.

MATERIALS AND METHODS

Our approach capitalizes on two whole-slide image datasets: one consisting of breast cancer cases from the Korea University Guro Hospital (KG) and the other originating from The Cancer Genomic Atlas dataset (TCGA). Furthermore, we visualized the inferred results using an attention-based heat map and reviewed the histomorphological features of the most attentive patches.

RESULTS

The KG+TCGA-trained model achieved an area under the receiver operating characteristics value of 0.749. An inherent challenge lies in the imbalance among subtypes. Additionally, discrepancies between the two datasets resulted in different molecular subtype proportions. To mitigate this imbalance, we merged the two datasets, and the resulting model exhibited improved performance. The attentive patches correlated well with widely recognized histomorphologic features. The triple-negative subtype has a high incidence of high-grade nuclei, tumor necrosis, and intratumoral tumor-infiltrating lymphocytes. The luminal A subtype showed a high incidence of collagen fibers.

CONCLUSION

The artificial intelligence (AI) model based on weakly supervised learning showed promising performance. A review of the most attentive patches provided insights into the predictions of the AI model. AI models can become invaluable screening tools that reduce costs and workloads in practice.

Unveiling the Link Between Breast Cancer Treatment and Osteoporosis: Implications for Anticancer Therapy and Bone Health

Background: The interplay between breast cancer treatment and osteoporosis has important consequences for anticancer therapy and patient bone health. Many breast cancer therapies involve hormonal treatments that lower estrogen levels, which can lead to an increased risk of osteoporosis due to reduced bone mineral density. Aromatase inhibitors, chemotherapy, and surgeries such as oophorectomy can further aggravate bone loss, highlighting the necessity of prioritizing bone health during cancer treatment. Objective: This review is aimed at investigating the complex relationship between breast cancer therapies and bone health by examining the molecular and cellular mechanisms through which anticancer treatments lead to bone loss. It also seeks to assess the effects of various treatment options, such as selective estrogen receptor modulators (SERMs) and bisphosphonates, on reducing bone loss and maintaining bone health during cancer therapy. Method: The review explores the mechanisms underlying bone loss in breast cancer patients undergoing treatment, focusing on factors such as estrogen depletion, inflammatory cytokines, and changes in bone remodelling processes. Additionally, it evaluates the efficacy of different therapeutic interventions, including pharmacological treatments like bisphosphonates and third-generation SERMs, in mitigating bone-related side effects. Results: The findings indicate a critical need to balance the effectiveness of breast cancer treatments with the preservation of bone health. Pharmacological treatments like bisphosphonates and denosumab have been identified as essential for managing bone health in breast cancer patients. Furthermore, third-generation SERMs show potential in reducing bone loss associated with cancer therapy.

Precision medicine in breast cancer (Review)

Precision medicine in breast cancer is a revolutionary approach that customizes diagnosis and treatment based on individual and tumor characteristics, departing from the traditional one-size-fits-all approach. Breast cancer is diverse, with various subtypes driven by distinct genetic mutations. Understanding this diversity is crucial for tailored treatment strategies that target specific vulnerabilities in each tumor. Genetic testing, particularly for mutations in breast cancer gene (BRCA) DNA repair-associated genes, helps assess hereditary risks and influences treatment decisions. Molecular subtyping guides personalized treatments, such as hormonal therapies for receptor-positive tumors and human epidermal growth factor receptor 2 (HER2)-targeted treatments. Targeted therapies, including those for HER2-positive and hormone receptor-positive breast cancers, offer more effective and precise interventions. Immunotherapy, especially checkpoint inhibitors, shows promise, particularly in certain subtypes such as triple-negative breast cancer, with ongoing research aiming to broaden its effectiveness. Integration of big data and artificial intelligence enhances personalized treatment strategies, while liquid biopsies provide real-time insights into tumor dynamics, aiding in treatment monitoring and modification. Challenges persist, including accessibility and tumor complexity, but emerging technologies and precision prevention offer hope for improved outcomes. Ultimately, precision medicine aims to optimize treatment efficacy, minimize adverse effects and enhance the quality of life for patients with breast cancer.

Comparative profiling of whole-cell and exosome samples reveals protein signatures that stratify breast cancer subtypes

Identifying novel breast cancer biomarkers will improve patient stratification, enhance therapeutic outcomes, and help develop non-invasive diagnostics. We compared the proteomic profiles of whole-cell and exosomal samples of representative breast cancer cell subtypes to evaluate the potential of extracellular vesicles as non-invasive disease biomarkers in liquid biopsies. Overall, differentially-expressed proteins in whole-cell and exosome samples (which included markers for invasion, metastasis, angiogenesis, and drug resistance) effectively discriminated subtypes; furthermore, our results confirmed that the proteomic profile of exosomes reflects breast cancer cell-of-origin, which underscores their potential as disease biomarkers. Our study will contribute to identifying biomarkers that support breast cancer patient stratification and developing novel therapeutic strategies. We include an open, interactive web tool to explore the data as a molecular resource that can explain the role of these protein signatures in breast cancer classification.

Associations amongst genes, molecules, cells, and organs in breast cancer metastasis

This paper is a cross fertilization of ideas about the importance of molecular aspects of breast cancer metastasis by basic scientists, a pathologist, and clinical oncologists at the Henry Ford Health symposium. We address four major topics: (i) the complex roles of lymphatic endothelial cells and the molecules that stimulate them to enhance lymph node and systemic metastasis and influence the anti-tumor immunity that might inhibit metastasis; (ii) the interaction of molecules and cells when breast cancer spreads to bone, and how bone metastases may themselves spread to internal viscera; (iii) how molecular expression and morphologic subtypes of breast cancer assist clinicians in determining which patients to treat with more or less aggressive therapies; (iv) how the outcomes of patients with oligometastases in breast cancer are different from those with multiple metastases and how that could justify the aggressive treatment of these patients with the hope of cure.

Exploring the antitumor potential of novel quinoline derivatives via tubulin polymerization inhibition in breast cancer; design, synthesis and molecular docking

A series of quinoline derivatives was designed and synthesized as novel tubulin inhibitors targeting the colchicine binding site. All the rationalized compounds 3a-e, 4a-e, 5a-e, and 6a-e have been chosen for screening their cytotoxic activity against 60 cell lines by NCI. Compounds 3b, 3c, 4c, 5c and 6c demonstrated the most notable antitumor activity against almost all cell lines. Compound 4c emerged as the most potent compound as an antiproliferative agent. This compound was subsequently chosen for five-dose testing and it exhibited remarkable broad-spectrum efficacy with strong antitumor activity against several cell lines. Compound 4c significantly induced cell cycle arrest in MDA-MB-231 cells at G2 and M phases where the cell population increased dramatically to 22.84% compared to the untreated cells at 10.42%. It also increased the population in MDA-MB-231 cells at both early and late stages of apoptosis. Compound 4c can successfully inhibit tubulin polymerization with an IC50 value of 17 ± 0.3 μM. The β-tubulin mRNA levels were notably reduced in MDA-MB-231 cells treated with compound 4c which is similar to the effect observed with colchicine treatment. Docking studies revealed that compound 4c interacted well with crucial amino acids in the active site.

Joint EANM-SNMMI guideline on the role of 2-[18F]FDG PET/CT in no special type breast cancer : (endorsed by the ACR, ESSO, ESTRO, EUSOBI/ESR, and EUSOMA)

INTRODUCTION

There is much literature about the role of 2-[18F]FDG PET/CT in patients with breast cancer (BC). However, there exists no international guideline with involvement of the nuclear medicine societies about this subject.

PURPOSE

To provide an organized, international, state-of-the-art, and multidisciplinary guideline, led by experts of two nuclear medicine societies (EANM and SNMMI) and representation of important societies in the field of BC (ACR, ESSO, ESTRO, EUSOBI/ESR, and EUSOMA).

METHODS

Literature review and expert discussion were performed with the aim of collecting updated information regarding the role of 2-[18F]FDG PET/CT in patients with no special type (NST) BC and summarizing its indications according to scientific evidence. Recommendations were scored according to the National Institute for Health and Care Excellence (NICE) criteria.

RESULTS

Quantitative PET features (SUV, MTV, TLG) are valuable prognostic parameters. In baseline staging, 2-[18F]FDG PET/CT plays a role from stage IIB through stage IV. When assessing response to therapy, 2-[18F]FDG PET/CT should be performed on certified scanners, and reported either according to PERCIST, EORTC PET, or EANM immunotherapy response criteria, as appropriate. 2-[18F]FDG PET/CT may be useful to assess early metabolic response, particularly in non-metastatic triple-negative and HER2+ tumours. 2-[18F]FDG PET/CT is useful to detect the site and extent of recurrence when conventional imaging methods are equivocal and when there is clinical and/or laboratorial suspicion of relapse. Recent developments are promising.

CONCLUSION

2-[18F]FDG PET/CT is extremely useful in BC management, as supported by extensive evidence of its utility compared to other imaging modalities in several clinical scenarios.

Immunohistochemical Expression of Cyclooxygenase 2 (COX-2) as a Prognostic Marker and Its Correlation With Clinicopathological Parameters in Breast Cancer

Introduction Breast cancer is considered the most common cancer among women. According to the literature, cyclooxygenase-2 (COX-2) expression in breast carcinoma is associated with aggressive tumor biology and acts as an independent prognostic marker. As COX-2 is a newly identified marker, studies are required to understand its immunoexpression and correlation with hormone receptor status and other prognostic factors, which helps in the therapeutic management of patients. Hence, this study evaluates the expression of COX-2 in breast carcinoma. Methods A hospital-based cross-sectional study was done on 55 mastectomy specimens collected at the Histopathology and Surgical Pathology Section of the Department of Pathology. The patient's age, histological type, tumor size, lymph node status, histological grade, and vascular invasion were noted. Immunohistochemical staining for estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2/neu protooncogene (HER2/neu), and COX-2 markers was performed, and its results were compared with these clinicopathological and prognostic parameters. Results were subjected to statistical analysis. Results COX-2 expression was seen in 37 out of 55 cases (67.2%). Expression of COX-2 showed a statistically significant correlation with vascular invasion, ER-negative status, and PR-negative status. No statistical association was found between other parameters like age, tumor size, histological type, histological grade, lymph node status, and HER2/neu status. Conclusion The expression of COX-2 correlated strongly with well-established poor prognostic markers, such as vascular invasion, ER-negative status, and PR-negative status. Thus, expression of COX-2 suggests aggressive tumor biology, and it can be used as an independent prognostic marker.

Shear Wave Elastography in Breast Cancer: Unveiling Correlations With Histopathological Grades and Subtypes

Objective This study explores the correlation between shear wave elastography (SWE) features and histopathological grades and subtypes in breast cancer, aiming to enhance diagnostic accuracy and personalized treatment strategies. Methods The study retrospectively analyzed 59 consecutive women with breast cancer who underwent breast ultrasound with SWE. SWE parameters and histopathologic information, including histological type and grade, were recorded. Qualitative and quantitative SWE findings were analyzed, and B-mode findings were evaluated. Sociodemographic and clinical factors and B-mode findings were assessed as predictors of elastography stiffness using logistic regression analysis. Results Of the 59 participants diagnosed with breast cancer, invasive ductal carcinoma of no special type (IDC-NST) was predominantly found in 50 (84.7%) cases, followed by invasive medullary carcinoma in 5 (8.5%) cases. The majority of participants belonged to the 50-59 age group, comprising 19 (32.2%) patients. Histopathological grading revealed grade II tumors in 27 (45.8%) cases and grade III tumors in 24 (40.7%) cases. Notably, grade III tumors exhibited higher tissue stiffness compared to grade II tumors. Out of 36 stiff lesions, 30 (83.3%%) were IDC-NST while 3 (8.3%) were invasive medullary carcinoma. A significant association was observed between higher histopathological grade (grade III) and increased tissue stiffness (p < 0.05). Furthermore, among participants with stiff lesions, 21 (58.3%) exhibited color defects while 4 (23.5%) cases with soft lesions also displayed color defects Conclusion The correlation between SWE findings and histopathological grades and subtypes underscores the potential of SWE as a valuable tool for predicting tumor aggressiveness and characterizing specific subtypes. SWE enhances diagnostic accuracy and complements traditional imaging modalities, holding promise for personalized treatment strategies.

Predictive factors for complete pathological response in hormone receptor-negative breast cancer patients undergoing neoadjuvant chemotherapy

Complete pathological response (pCR) is a pivotal predictor of enhanced disease-free and overall survival rates in breast cancer patients. Accurate prediction of pCR is therefore of paramount clinical significance. This retrospective study aimed to delineate the factors associated with pCR through a comprehensive analysis encompassing clinical, pathological, and immunohistochemical profiling of patients diagnosed with hormone receptor-negative invasive ductal carcinomas. The study cohort was composed of 73 female patients. The cases were reviewed retrospectively using data from University Hospital "Tsaritsa Yoanna" in Sofia, spanning the ten-year period from 2010 to 2020. Univariate analyses demonstrated that patients diagnosed with a higher disease stage, specifically stage IIIb, exhibited a notable association with an unfavorable response to neoadjuvant chemotherapy (NCT) [OR 4.5455 (95%CI 1.6810 - 12.2910); p = 0.0029]. Invasive carcinomas containing a ductal carcinoma in situ (DCIS) component [OR 0.3333 (95%CI 0.1226 - 0.9063); p = 0.0313] or were classified as poorly differentiated [OR 0.3056 (95%CI 0.1159 - 0.8055); p = 0.0165] demonstrated an enhanced likelihood of achieving pCR. Tumors expressing CD10 [OR 0.1452 (95%CI 0.0515 - 0.4093); p = 0.0003] and tumors lacking EGFR [OR 3.9722 (95%CI 1.4691 - 10.7399); p = 0.0066] exhibited a markedly elevated rate of pCR. Multivariate regression analysis supported findings. In conclusion, hormone receptor-negative breast tumors stand to benefit from increased pCR rates if they encompass a DCIS component and exhibit CD10 expression while lacking EGFR expression. These findings underscore the importance of comprehensive profiling in predicting pCR outcomes in hormone receptor-negative breast cancer patients undergoing neoadjuvant chemotherapy.

Breast cancer and its therapeutic targets: A comprehensive review

Breast cancer is a common and deadly disease, so there is a constant need for research to find efficient targets and therapeutic approaches. Breast cancer can be classified on a molecular and histological base. Breast cancer can be divided into ER (estrogen receptor)-positive and ER-negative, HER2 (human epidermal growth factor receptor2)-positive and HER2-negative subtypes based on the presence of specific biomarkers. Targeting hormone receptors, such as the HER2, progesterone receptor (PR), and ER, is very significant and plays a vital role in the onset and progression of breast cancer. Endocrine treatments and HER2-targeted drugs are examples of targeted therapies now being used against these receptors. Emerging immune-based medicines with promising outcomes in the treatment of breast cancer include immune checkpoint inhibitors, cancer vaccines, and adoptive T-cell therapy. It is also explored how immune cells and the tumor microenvironment affect breast cancer development and treatment response. The major biochemical pathways, signaling cascades, and DNA repair mechanisms that are involved in the development and progression of breast cancer, include the PI3K/AKT/mTOR system, the MAPK pathway, and others. These pathways are intended to be inhibited by a variety of targeted drugs, which are then delivered with the goal of restoring normal cellular function. This review aims to shed light on types of breast cancer with the summarization of different therapeutic approaches which can target different pathways for tailored medicines and better patient outcomes.

Risk factors and survival of triple-negative breast cancer among breast cancer patients: Ten-year cross-sectional study in the southwestern Iranian population

Background

Breast cancer results from genetic and epigenetic mutations, contributing significantly to cancer-related morbidity and mortality. This study aimed to determine the prevalence and survival rates of triple-negative breast cancer (TNBC) among breast cancer patients in southwestern Iran over a ten-year period.

Methods

This retrospective cross-sectional study aims to assess prognostic factors associated with survival in women diagnosed with breast cancer in Iran's southwestern region over a ten-year period (2007-2017). Data were collected from patients who visited the Clinical Oncology Department at Golestan Hospital in Ahvaz (the breast cancer center of the Southwestern country). The study enrolled women diagnosed with TNBC using a census method and data from medical records. The primary outcome (survival rates) and secondary outcomes (demographic data, diagnostic stages, and three receptors estrogen receptors [ER], progesterone receptor [PR], human epidermal growth factor receptor 2 [HER2] status) were collected.

Results

Breast cancer was diagnosed in 2641 women over ten years; TNBC was diagnosed in 227 individuals (8.59%). Statistical analysis revealed a significant correlation between negative ER status and TNBC (p > 0.05). Furthermore, the prevalence of TNBC differed significantly from that of other types of breast cancer (p = 0.0001). The variables of age, HER2, PR, and TNBC grade did not differ significantly (p > 0.05). The overall disease-free survival rate over 5 years was 88.1%, while the rate for individuals without recurrence was 77.97%.

Conclusion

This study highlights a differentially low incidence of TNBC in the southwestern part of Iran when compared to other regions; genetic or epigenetic influences may explain this discrepancy. ER-negative status is a crucial prognostic indicator in diagnosing TNBC. The incidence of this disease is expected to rise by 100% in 2 years and 77.97% in 5 years.

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.

ANO6 is a reliable prognostic biomarker and correlates to macrophage polarization in breast cancer

To investigate the value of Anoctamin 6 (ANO6) in breast cancer (BC) by analyzing its expression, prognostic impact, biological function, and its association with immune characteristics. We initially performed the expression and survival analyses, followed by adopting restricted cubic spline to analyze the nonlinear relationship between ANO6 and overall survival (OS). Stratified and interaction analyses were conducted to further evaluate its prognostic value in BC. Next, we performed enrichment analyses to explore the possible pathways regulated by ANO6. Finally, the correlations between ANO6 and immune characteristics were analyzed to reveal its role in immunotherapy. Lower ANO6 expression was observed in BC than that in the normal breast group, but its overexpression independently predicted poor OS among BC patients (P < .05). Restricted cubic spline analysis revealed a linear relationship between ANO6 and OS (P-Nonlinear > 0.05). Interestingly, menopause status was an interactive factor in the correlation between ANO6 and OS (P for interaction = 0.016). Additionally, ANO6 was involved in stroma-associated pathways, and its elevation was significantly linked to high stroma scores and macrophage polarization (P < .05). Moreover, ANO6 was notably correlated with immune checkpoint expression levels, and scores of tumor mutation burden and microsatellite instability (all P < .05). ANO6 was an independent prognostic factor for BC, and might be a potential target for the BC treatment. Besides, ANO6 might affect BC progression via the regulation of stroma-related pathways and macrophage polarization.

Molecular subtypes as a prognostic breast cancer factor in women users of the São Paulo public health system, Brazil

OBJECTIVE

This study aimed to analyze the prognosis of women with breast cancer by molecular subtypes, sociodemographic variables, and clinical and treatment characteristics.

METHODS

This hospital-based retrospective cohort study analyzed 1,654 women over 18 years of age diagnosed with invasive breast cancer from 2000 to 2018. Data were extracted from Brazil's Oncocenter Foundation of São Paulo. The variables analyzed were age, histology, molecular subtypes, clinical staging, treatment type, and diagnosis-to-treatment time. Cox regression analysis was applied to estimate death risk.

RESULTS

Women with HER-2-positive (nonluminal) and triple-negative molecular subtypes were more than twice more likely to be at risk of death, with adjusted hazard ratio - HRadj=2.30 (95% confidence interval - 95%CI 1.34-3.94) and HRadj=2.51 (95%CI 1.61-3.92), respectively. A delayed treatment associated with an advanced clinical stage at diagnosis increased fourfold the risk of death (HRadj=4.20 (95%CI 2.36-7.49).

CONCLUSION

In summary, besides that interaction between advanced clinical stage and longer time between diagnosis and treatment, HER-2-positive (nonluminal) and triple-negative phenotypes were associated with a worse prognosis. Therefore, actions to reduce barriers in diagnosis and treatment can provide better outcome, even in aggressive phenotypes.

Integrated Evaluation of Inflammatory, Nutritional, and Sarcopenia Markers to Predict Survival in Metastatic Breast Cancer Patients

BACKGROUND/AIM

The prognosis of a cancer patient is influenced by the tumor-related factors, as well as by various patient-related factors. We evaluated the association between inflammatory and nutritional factors and their outcomes, including the prognosis and therapeutic course, in patients with metastatic breast cancer.

PATIENTS AND METHODS

In this observational retrospective study, we evaluated 35 patients. The inflammatory and nutritional markers before systemic therapy included the lymphocyte count, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammatory index (SII), systemic inflammatory response index (SIRI), pan-immuno-inflammatory values (PIV), prognostic nutritional index (PNI), Glasgow prognostic score (GPS), and psoas muscle index (PMI).

RESULTS

Triple-negative, low PNI, and GPS 2 were correlated with worse overall survival in the univariable analysis. The GPS was the only independent predictor of overall survival [hazard ratio=5.85, 95% confidence interval=1.15-29.68, p<0.01]. The time to treatment failure of first-line therapy in patients with GPS 2 was significantly shorter than that in patients with GPS 0/1 (p<0.01).

CONCLUSION

The GPS was an independent predictive marker for overall survival in patients with metastatic breast cancer.

A Clinical Cognizance of Molecular and Pathological Diagnostic Approach of TNBC

Genetic, transcriptional, and clinical heterogeneity of disease has remained to be a prominent obstacle to the development of a targeted therapeutic approach against TNBC. So far, based on tumor size, lymph node status, and histologic features TNBC subtypes were stratified. Insights into inter and intratumoral heterogeneity of TNBC were gained by next-generation sequencing, genomic, transcriptomic, proteomic, and clinicopathological characterization. To depict tumor response to neoadjuvant chemotherapy, radiological characterization may also a play significant role. Biomarkers for subtyping TNBC were highly needed to depict the survival outcome. This chapter discussed the available and possible molecular and pathological diagnostic approaches to TNBC. Furthermore, the integration of morphological and genomic data may emerge as a promising approach for the identification of new therapeutic and prognostic markers to predict the likely outcome of the disease. This chapter aims to highlight the molecular and pathological diagnostic approaches to depict both metastatic and non-metastatic TNBC.&nbsp;<br>

RNA interference: Promising approach for breast cancer diagnosis and treatment

Today, cancer is one of the main health-related challenges, and in the meantime, breast cancer (BC) is one of the most common cancers among women, with an alarming number of incidences and deaths every year. For this reason, the discovery of novel and more effective approaches for the diagnosis, treatment, and monitoring of the disease are very important. In this regard, scientists are looking for diagnostic molecules to achieve the above-mentioned goals with higher accuracy and specificity. RNA interference (RNAi) is a posttranslational regulatory process mediated by microRNA intervention and small interfering RNAs. After transcription and edition, these two noncoding RNAs are integrated and activated with the RNA-induced silencing complex (RISC) and AGO2 to connect the target mRNA by their complementary sequence and suppress their translation, thus reducing the expression of their target genes. These two RNAi categories show different patterns in different BC types and stages compared to healthy cells, and hence, these molecules have high diagnostic, monitoring, and therapeutic potentials. This article aims to review the RNAi pathway and diagnostic and therapeutic potentials with a special focus on BC.

Advances of Epigenetic Biomarkers and Epigenome Editing for Early Diagnosis in Breast Cancer

Epigenetic modifications are known to regulate cell phenotype during cancer progression, including breast cancer. Unlike genetic alterations, changes in the epigenome are reversible, thus potentially reversed by epi-drugs. Breast cancer, the most common cause of cancer death worldwide in women, encompasses multiple histopathological and molecular subtypes. Several lines of evidence demonstrated distortion of the epigenetic landscape in breast cancer. Interestingly, mammary cells isolated from breast cancer patients and cultured ex vivo maintained the tumorigenic phenotype and exhibited aberrant epigenetic modifications. Recent studies indicated that the therapeutic efficiency for breast cancer regimens has increased over time, resulting in reduced mortality. Future medical treatment for breast cancer patients, however, will likely depend upon a better understanding of epigenetic modifications. The present review aims to outline different epigenetic mechanisms including DNA methylation, histone modifications, and ncRNAs with their impact on breast cancer, as well as to discuss studies highlighting the central role of epigenetic mechanisms in breast cancer pathogenesis. We propose new research areas that may facilitate locus-specific epigenome editing as breast cancer therapeutics.

Clinicopathological and Molecular Features of Secondary Cancer (Metastasis) to the Thyroid and Advances in Management

Secondary tumours to the thyroid gland are uncommon and often incidentally discovered on imaging. Symptomatic patients often present with a neck mass. Collision tumours of secondary tumours and primary thyroid neoplasms do occur. Ultrasound-guided fine-needle aspiration, core-needle biopsy, and surgical resection with histological and immunohistochemical analysis are employed to confirm diagnosis as well as for applying molecular studies to identify candidates for targeted therapy. Biopsy at the metastatic site can identify mutations (such as EGFR, K-Ras, VHL) and translocations (such as EML4-ALK fusion) important in planning target therapies. Patients with advanced-stage primary cancers, widespread dissemination, or unknown primary origin often have a poor prognosis. Those with isolated metastasis to the thyroid have better survival outcomes and are more likely to undergo thyroid resection. Systemic therapies, such as chemotherapy and hormonal therapy, are often used as adjuvant treatment post-operatively or in patients with disseminated disease. New targeted therapies, such as tyrosine kinase inhibitors and immune checkpoint inhibitors, have shown success in reported cases. A tailored treatment plan based on primary tumour features, overall cancer burden, and co-morbidities is imperative. To conclude, secondary cancer to the thyroid is uncommon, and awareness of the updates on diagnosis and management is needed.

A review on epidermal growth factor receptor's role in breast and non-small cell lung cancer

Epithelial growth factor receptor (EGFR) is a cell surface transmembrane receptor that mediates the tyrosine signaling pathway to carry the extracellular messages inside the cell and thereby alter the function of nucleus. This leads to the generation of various protein products to up or downregulate the cellular function. It is encoded by cell erythroblastosis virus oncogene B1, so called C-erb B1/ERBB2/HER-2 gene that acts as a proto-oncogene. It belongs to the HER-2 receptor-family in breast cancer and responds best with anti-Herceptin therapy (anti-tyrosine kinase monoclonal antibody). HER-2 positive breast cancer patient exhibits worse prognosis without Herceptin therapy. Similar incidence and prognosis are reported in other epithelial neoplasms like EGFR + lung non-small cell carcinoma and glioblastoma (grade IV brain glial tumor). Present study highlights the role and connectivity of EGF with various cancers via signaling pathways, cell surface receptors mechanism, macromolecules, mitochondrial genes and neoplasm. Present study describes the EGFR associated gene expression profiling (in breast cancer and NSCLC), relation between mitrochondrial genes and carcinoma, and several in vitro and in vivo models to screen the synergistic effect of various combination treatments. According to this study, although clinical studies including targeted treatments, immunotherapies, radiotherapy, TKi-EGFR combined targeted therapy have been carried out to investigate the synergism of combination therapy; however still there is a gap to apply the scenarios of experimental and clinical studies for further developments. This review will give an idea about the transition from experimental to most advanced clinical studies with different combination drug strategies to treat cancer.

Molecular markers, pathology, and ultrasound features of invasive breast cancer

INTRODUCTION

Ultrasound is commonly used in breast cancer screening and diagnosis. The use of ultrasound features to predict the subtypes of invasive breast cancer is of great clinical significance, since it facilitates a fast and early diagnosis and treatment. The correlation between breast lesion ultrasound features and the breast cancer subtypes requires further investigation.

METHODS

388 patients with invasive breast cancer were retrospectively analyzed by two sonographers. The tumor size, shape, margin, echogenicity, echotexture, posterior echo attenuation microcalcification, and blood vessel density were recorded. The correlation between the tumor ER, PR, HER2, and Ki67 status, the molecular subtypes, and the ultrasound features was analyzed using the chi-square test, Fisher's exact test, and multiple logistic regression.

RESULTS

ER and PR positivity were correlated with a low histologic grade, lymph node metastasis, and smaller-sized tumors. A hyperechoic or a mixed echogenicity was rare in the tumors of all groups but was enriched in the ER and PR tumors (9.57% and 7.64%, respectively, p < 0.01). A high percentage of posterior echo attenuation was found in the Ki67 low (53.94%) and ER+ (51.28%) tumors. Furthermore, heterogeneous and microcalcifications were enriched in HER2-positive tumors. In terms of the molecular subtypes, the luminal A subtype group had the lowest lymph node positivity and the smallest primary tumor size. The luminal B subtype had the lowest percentage of hyperechoic or mixed tumors. The HER2 subtype was positively correlated with microcalcification. Finally, TNBC showed the highest percentage of hyperechoic or mixed tumors and the lowest percentage of posterior echo attenuation and microcalcification.

CONCLUSION

Tumor pathologic and ultrasound features were correlated with invasive breast tumor molecular marker positivity and its molecular subtypes.

Amongst Women Stratified to Receive Endocrine Therapy on the Basis of Their Tumor Estrogen and Progesterone Receptor Levels, Those with Higher Tumor Progesterone Receptor Levels Had a Better Outcome Than Those with Lower Levels of Tumor Progesterone Receptor

Simple Summary

Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death of women worldwide. Several cut-points for estrogen receptor (ER) and progesterone receptor (PgR) have been proposed as predictive effects of hormone therapy; while the cut-off values were inconsistent. The aim of our retrospective study was to propose better prognostic cut-off levels for ER and PgR, and their effects on breast cancer-specific survival (BCSS) and disease-free survival (DFS) over 5 and 10 years were evaluated in 1807 eligible patients. Subgroups were generated based on ER and PgR expression percentage and scoring from the Allred scoring system (Allred scores). After comparing the hazard ratios (event rates in each group to reference group) of BCSS and DFS using multivariate analyses, our results suggested that patients with PgR expression ≤50% or Allred score ≤5 revealed a poor prognosis and should be paid more attention during follow-up.

Abstract

Background: To realize the association between stratified expression levels of ER and PgR and long-term prognosis of breast cancer patients who received adjuvant hormone therapy, this study aimed to propose better prognostic cut-off levels for estrogen receptor (ER) and progesterone receptor (PgR). Methods: Patients who received adjuvant hormone therapy after surgical intervention were selected. The ER and PgR status and their effects on breast cancer-specific survival (BCSS) and disease-free survival (DFS) over 5 and 10 years were evaluated. Next, subgroups were generated based on ER and PgR expression percentage and Allred scores. Survival curves were constructed using the Kaplan–Meier method. Results: ER and PgR expression were significantly associated with better prognosis in 5 years, whereas only PgR expression was significantly associated during the 10-year follow-up. The optimal cut-off values for better 5-year BCSS were ER > 50%; ER Allred score > 7; PgR ≥ 1%; or PgR Allred score ≥ 3; the corresponding values for DFS were ER > 40%; ER Allred score > 6; PgR > 10%; or PgR Allred score ≥ 3. In the long-term follow-up, PgR of > 50% or Allred score of > 5 carriers revealed a better prognosis of both BCSS and DFS. Conclusion: Patients with a PgR expression > 50% or an Allred score > 5 exhibited better 10-year BCSS and DFS.

Application of digital mammography-based radiomics in the differentiation of benign and malignant round-like breast tumors and the prediction of molecular subtypes

BACKGROUND

This study aimed to investigate the diagnostic performance of radiomic features based on digital mammography (DM) in the differential diagnosis of benign and malignant round-like (round and oval) solid tumors with circumscribed or obscured margins but without suspicious malignant or benign macrocalcifications and to investigate whether quantitative radiomic features can distinguish triple-negative breast cancer (TNBC) from non-TNBC (NTNBC).

METHODS

This retrospective study included 112 patients with round-like tumors who underwent DM within 20 days preoperatively. Breast masses were segmented manually on the DM images, then radiomic features were extracted. The predictive models were used to distinguish between benign and malignant tumors and to predict TNBC in invasive ductal carcinoma. The receiver operating characteristic curves (ROCs) for these models were obtained for initial DM characteristics, radiomic features to predict malignant tumors and TNBC. The decision curve was obtained to evaluate the clinical usefulness of the model for the prediction of benign or malignant tumors.

RESULTS

The study cohort included 79 patients with pathologically confirmed malignant masses and 33 patients with benign (training cohort: n=79; testing cohort: n=33). A total of 396 features were extracted from the DM images for each patient. The radiomics model for the prediction of malignant tumors achieved an area under the receiver operating characteristic curve (AUC) of 0.88 [95% confidence interval (CI), 0.76-1.00] in the testing cohort; the radiomics model for the prediction of TNBC achieved an AUC of 0.84 (95% CI, 0.73-0.96). In contrast, DM characteristics alone poorly predicted malignant tumors, with the density achieving an AUC 0.69 (95% CI, 0.59-0.79); there was no significant difference in DM characteristics between TNBC and NTNBC (P>0.05, all). The decision curve showed the good clinical usefulness of the model for the prediction of malignant tumors.

CONCLUSIONS

This study showed that DM-based radiomics can accurately discriminate between benign and malignant round-like tumors with circumscribed or obscured margins but without suspicious malignant or benign macrocalcifications. Additionally, it can be used to predict TNBC in invasive ductal carcinoma. DM-based radiomics can aid radiologists in mammogram reading, clinical diagnosis and decision-making.

Deep learning-enabled breast cancer hormonal receptor status determination from base-level H&E stains

For newly diagnosed breast cancer, estrogen receptor status (ERS) is a key molecular marker used for prognosis and treatment decisions. During clinical management, ERS is determined by pathologists from immunohistochemistry (IHC) staining of biopsied tissue for the targeted receptor, which highlights the presence of cellular surface antigens. This is an expensive, time-consuming process which introduces discordance in results due to variability in IHC preparation and pathologist subjectivity. In contrast, hematoxylin and eosin (H&E) staining—which highlights cellular morphology—is quick, less expensive, and less variable in preparation. Here we show that machine learning can determine molecular marker status, as assessed by hormone receptors, directly from cellular morphology. We develop a multiple instance learning-based deep neural network that determines ERS from H&E-stained whole slide images (WSI). Our algorithm—trained strictly with WSI-level annotations—is accurate on a varied, multi-country dataset of 3,474 patients, achieving an area under the curve (AUC) of 0.92 for sensitivity and specificity. Our approach has the potential to augment clinicians’ capabilities in cancer prognosis and theragnosis by harnessing biological signals imperceptible to the human eye.

Determination of estrogen receptor status (ERS) in breast cancer tissue requires immunohistochemistry, which is sensitive to the vagaries of sample processing and the subjectivity of pathologists. Here the authors present a deep learning model that determines ERS from H&E stained tissue, which could improve oncology decisions in under-resourced settings.

A deep learning image-based intrinsic molecular subtype classifier of breast tumors reveals tumor heterogeneity that may affect survival

BACKGROUND

Breast cancer intrinsic molecular subtype (IMS) as classified by the expression-based PAM50 assay is considered a strong prognostic feature, even when controlled for by standard clinicopathological features such as age, grade, and nodal status, yet the molecular testing required to elucidate these subtypes is not routinely performed. Furthermore, when such bulk assays as RNA sequencing are performed, intratumoral heterogeneity that may affect prognosis and therapeutic decision-making can be missed.

METHODS

As a more facile and readily available method for determining IMS in breast cancer, we developed a deep learning approach for approximating PAM50 intrinsic subtyping using only whole-slide images of H&E-stained breast biopsy tissue sections. This algorithm was trained on images from 443 tumors that had previously undergone PAM50 subtyping to classify small patches of the images into four major molecular subtypes-Basal-like, HER2-enriched, Luminal A, and Luminal B-as well as Basal vs. non-Basal. The algorithm was subsequently used for subtype classification of a held-out set of 222 tumors.

RESULTS

This deep learning image-based classifier correctly subtyped the majority of samples in the held-out set of tumors. However, in many cases, significant heterogeneity was observed in assigned subtypes across patches from within a single whole-slide image. We performed further analysis of heterogeneity, focusing on contrasting Luminal A and Basal-like subtypes because classifications from our deep learning algorithm-similar to PAM50-are associated with significant differences in survival between these two subtypes. Patients with tumors classified as heterogeneous were found to have survival intermediate between Luminal A and Basal patients, as well as more varied levels of hormone receptor expression patterns.

CONCLUSIONS

Here, we present a method for minimizing manual work required to identify cancer-rich patches among all multiscale patches in H&E-stained WSIs that can be generalized to any indication. These results suggest that advanced deep machine learning methods that use only routinely collected whole-slide images can approximate RNA-seq-based molecular tests such as PAM50 and, importantly, may increase detection of heterogeneous tumors that may require more detailed subtype analysis.

Diagnosis and Treatment of Breast Cancer in the Precision Medicine Era

Breast cancer is one of the most leading causes of death for women worldwide. According to statistics published by the International Agency for Research on Cancer (IARC), the incidence of breast cancer is on the rise year by year in most parts of the world. The existence of heterogeneity limits the early diagnosis and targeted therapy of breast cancer. Nowadays, precision medicine brings a new perspective to personalized diagnosis and targeted therapy, overcomes the heterogeneity of different patients, and provides an opportunity for screening of high-risk populations. As a clinician, we are committed to using genomic to provide a favorable perspective in the field of breast cancer. The current review describes the recent advances in the understanding of precision medicine for breast cancer in the aspect of the genomics which could be applied to improve our ability to diagnose and treat breast cancer individually and effectively.

TFAP2C regulates carbonic anhydrase XII in human breast cancer

The expression of carbonic anhydrase XII (CA12) is associated with the expression of estrogen receptor alpha (ERα) in breast cancer and is linked to a good prognosis with a lower risk of metastasis. Transcription Factor Activator Protein 2γ (TFAP2C, AP-2γ) governs luminal breast cancer phenotype through direct and indirect regulation of ERα and ERα-associated genes, GATA3, FOXA1, EGFR, CDH1, DSP, KRT7, FBP1, MYB, RET, KRT8, MUC1, and ERBB2-genes which are responsible for the luminal signature in breast cancer. Herein, utilizing chromatin immunoprecipitation and direct sequencing (ChIP-seq), we show that CA12 is regulated by AP-2γ through binding with its promoter region in luminal breast cancer cell lines and indirectly through a distal estrogen-responsive region in ERα-positive cell lines by upregulation of ERα. CA12 is transcriptionally silenced in basal breast cancer cell lines through histone deacetylation and CpG methylation of the promoter region and can be re-activated with Trichostatin A (histone deacetylase inhibitor) and/or 5-aza-dC (an inhibitor of DNA methylation). Strong concordance in co-expression of CA12 and ESR1 (R² = 0.1128, p = 0486) and TFAP2C (R² = 0.1823, p = 0.0105) was found using a panel of primary breast tumor samples (n = 35), supporting a synergetic role of AP-2γ and ERα in activation of CA12. Our results highlight the essential role of AP-2γ in maintaining the luminal breast cancer phenotype and provide evidence that epigenetic mechanisms silence luminal gene expression in the basal phenotype. Additional studies to decipher mechanisms that drive epigenetic silencing of AP-2γ target genes are a critical area for further research.

Invasive Lobular Carcinoma With Extensive Clear Cells: A Pitfall in Diagnosis

Carcinomas in the breast with a predominantly clear cytoplasm are rare. In this article, we review the differential diagnosis of clear cell breast neoplasms and report a case of invasive lobular carcinoma with extensive clear cell morphology that was diagnosed as invasive ductal carcinoma, not otherwise specified, on ultrasound-guided biopsy. Lobular carcinomas with extensive clear cell change are unusual, but must be considered when evaluating a clear cell neoplasm in the breast.

RILPL2 regulates breast cancer proliferation, metastasis, and chemoresistance via the TUBB3/PTEN pathway

Breast cancer (BC) is the most common malignancy in women and is one of the leading causes of cancer-associated deaths. The analysis of data obtained from online databases revealed that RILPL2 expression in BC tissues is lower than that in normal tissues, and that RILPL2 upregulation is correlated with prolonged recurrence-free survival (RFS), overall survival (OS), and distant metastasis-free survival (DMFS). However, the function of RILPL2 in tumor proliferation and metastasis remains unclear. In this study, we demonstrated that RILPL2 had lower expression in BC tissues than in adjacent normal tissues, and that RILPL2 expression was significantly negatively correlated with tumor size, histological grade, and lymph node metastasis. Univariate analysis showed a positive correlation between RILPL2 and estrogen receptor (ER) expression and a negative correlation between RILPL2 and human epidermal growth factor receptor 2 (HER2) expression. Overexpression of RILPL2 inhibited BC cell proliferation and metastasis in vitro and in vivo. In addition, the interaction of exogenous RILPL2 with TUBB3 resulted in the downregulation of BC cell proliferation and migration and upregulation of PTEN expression by promoting destabilization of TUBB3. Furthermore, RILPL2 could reverse BC cell resistance to taxotere-mediated apoptosis by regulating the TUBB3/PTEN/AKT pathway. In conclusion, these results suggest that RILPL2 could be a novel biomarker for the diagnosis and treatment of BC.

Evaluation of a novel monoclonal antibody against tumor-associated MUC1 for diagnosis and prognosis of breast cancer

There is still a great unmet medical need concerning diagnosis and treatment of breast cancer which could be addressed by utilizing specific molecular targets. Tumor-associated MUC1 is expressed on over 90 % of all breast cancer entities and differs strongly from its physiological form on epithelial cells, therefore presenting a unique target for breast cancer diagnosis and antibody-mediated immune therapy. Utilizing an anti-tumor vaccine based on a synthetically prepared glycopeptide, we generated a monoclonal antibody (mAb) GGSK-1/30, selectively recognizing human tumor-associated MUC1. This antibody targets exclusively tumor-associated MUC1 in the absence of any binding to MUC1 on healthy epithelial cells thus enabling the generation of breast tumor-specific radiolabeled immune therapeutic tools. Methods: MAb GGSK-1/30 was used for immunohistochemical analysis of human breast cancer tissue. Its desferrioxamine (Df')-conjugate was synthesized and labelled with ⁸⁹Zr. [⁸⁹Zr]Zr-Df'-GGSK-1/30 was evaluated as a potential PET tracer. Binding and pharmacokinetic properties of [⁸⁹Zr]Zr-Df'-GGSK-1/30 were analyzed in vitro using human and murine cell lines that express tumor-associated MUC1. Self-generated primary murine breast cancer cells expressing human tumor-associated MUC1 were transplanted subcutaneously in wild type and human MUC1-transgenic mice. The pharmacology of [⁸⁹Zr]Zr-Df'-GGSK-1/30 was investigated using breast tumor-bearing mice in vivo by PET/MRT imaging as well as by ex vivo organ biodistribution analysis. Results: The mAb GGSK-1/30 stained specifically human breast tumor tissue and can be possibly used to predict the severity of disease progression based on the expression of the tumor-associated MUC1. For in vivo imaging, the Df'-conjugated mAb was radiolabeled with a radiochemical yield of 60 %, a radiochemical purity of 95 % and an apparent specific activity of 6.1 GBq/µmol. After 7 d, stabilities of 84 % in human serum and of 93 % in saline were observed. In vitro cell studies showed strong binding to human tumor-associated MUC1 expressing breast cancer cells. The breast tumor-bearing mice showed an in vivo tumor uptake of >50 %ID/g and clearly visible specific enrichment of the radioconjugate via PET/MRT. Principal conclusions: Tumor-associated MUC1 is a very important biomarker for breast cancer next to the traditional markers estrogen receptor (ER), progesterone receptor (PR) and HER/2-neu. The mAb GGSK-1/30 can be used for the diagnosis of over 90% of breast cancers, including triple negative breast cancer based on biopsy staining. Its radioimmunoconjugate represents a promising PET-tracer for breast cancer imaging selectively targeting breast cancer cells.

Relationships between Reproductive Risk Factors for Breast Cancer and Tumor Molecular Subtypes

Background: Due to wide clinical differences in the various pathological types of breast cancer and also close associations between disease prognosis and molecular subtypes, relationships of the latter with traditional risk factors have been suggested. Hence, the present study aimed to assess any associations. Methods: This bi-center cross-sectional study was performed on 800 consecutive women with known breast cancer referred to two Comprehensive Cancer Centers in Tehran between 2006 and 2016. Baseline information related to reproductive risk profiles as well as pathological tumor diagnosis and molecular subtypes determined using immunohistochemical analysis by immune-staining for ER, PR, and HER2 molecules were collected by reviewing hospital records. Results: Of 800 samples included for immunohistochemical analysis, 314 (39.3%) were diagnosed as of Luminal A subtype, 107 (13.4%) as Luminal B subtype, 153 (19.1%) as HER-2 over-expressing, and 226 (28.3%) as triple negative. Among all reproductive risk factors initially assessed, young age was associated with HER-2 over-expression, greater tumor size and a history of abortion with the luminal B subtype, lower age at pregnancy with the luminal A subtype, and lower gravidity and a shorter duration of breastfeeding with the triple negative subtype. Conclusion: Each molecular subtype of breast cancer in our population may be associated with specific reproductive risk factors.

Expression and function of the miR-143/145 cluster in vitro and in vivo in human breast cancer

MicroRNAs (miRNAs) are small non-coding RNAs that function as post-transcriptional regulators of gene expression and are dysregulated in cancer. Studies of miRNAs to explore their potential as diagnostic and prognostic markers are of great scientific interest. Here, we investigate the functional properties and expression of the miR-143/145 cluster in breast cancer (BC) in vitro and in vivo. The ER positive MCF7, the HER2 positive SK-BR-3, and the triple negative cell line MDA-MB-231 were used to assess cell proliferation and cell invasion. Expression of miRNA in 108 breast cancers in the Norwegian Women and Cancer Study and 44 benign tissue controls were analyzed by microarray and validated by RT-PCR. Further, in situ hybridization (ISH) was used to study the cellular and subcellular distribution of the miRNAs. In vitro, miR-143 promoted proliferation of MCF7 and MDA-MB-231 cells, whereas miR-145 and the cotransfection of both miRNAs inhibited proliferation in all three cell lines. The cells’ invasive capacity was reduced after transfection and cotransfection of the miRNAs. In line with the tumor suppressive functions in vitro, the expression of miR-143 and miR-145 was lower in malignant compared to benign breast tissue, and lower in the more aggressive tumors with higher tumor grade, loss of ER and the basal-like phenotype. ISH revealed miR-143 to be cytoplasmatic and predominantly expressed in luminal cells in benign tissue, whilst miR-145 was nuclear and with strong staining in myoepithelial cells. Both miRNAs were present in malignant epithelial cells and stromal fibroblasts in BC. This study demonstrates that miR-143 and -145 have functional properties and expression patterns typical for tumor suppressors, but the function is influenced by cellular factors such as cell type and miRNA cotransfection. Further, the nuclear functions of miR-145 should be explored for a more complete understanding of the complexity of miRNA regulation and function in BC.

Profile of palbociclib in the treatment of metastatic breast cancer

Breast cancer is the most common cancer diagnosed in women. Each year, thousands die either because of disease progression or failure of treatment. Breast cancer is classified into different subtypes based on the molecular expression of estrogen receptor (ER), progesterone receptor, and/or human epidermal growth factor receptor 2 (HER2). These receptors represent important therapeutic targets either through monoclonal antibodies or through small-molecule inhibitors directed toward them. However, up to 40% of patients develop either a primary or a secondary resistance to the current treatments. Therefore, there is an urgent need for investigating new targets in order to overcome the resistance and/or enhance the current therapies. Cell cycle is altered in many human cancers, especially in breast cancer. Cyclin-dependent kinases (CDKs), especially CDK4 and CDK6, play a pivotal role in cell cycle progression that makes them potential targets for new promising therapies. CDK inhibition has shown strong antitumor activities, ranging from cytostatic antiproliferative effects to synergistic effects in combination with other antitumor drugs. In order to overcome the drawbacks of the first-generation CDK inhibitors, recently, new CDK inhibitors have emerged that are more selective to CDK4 and CDK6 such as palbociclib, which is the most advanced CDK4/6 inhibitor in trials. In preclinical studies, palbociclib has shown a very promising antitumor activity, especially against ERα+ breast cancer subtype. Palbociclib has gained world attention, and US the Food and Drug Administration has accelerated its approval for first-line treatment in combination with letrozole for the first-line systematic treatment of postmenopausal women with ERα+/HER2− locally advanced or metastatic breast cancer. In this review, we discuss the potential role of CDK inhibition in breast cancer treatment, and focus on palbociclib progress from preclinical studies to clinical trials with mentioning the most recent ongoing as well as planned Phase II and Phase III trials of palbociclib in advanced breast cancer.