High-throughput protein expression analysis using tissue microarray technology of a large well-characterised series identifies biologically distinct classes of breast cancer confirming recent cDNA expression analyses

Research progress on estrogen receptor-positive/progesterone receptor-negative breast cancer

Breast cancer, which arises from the epithelial tissue of the breast, is one of the most common cancers affecting women worldwide. Its incidence and mortality rates have been increasing in both developed and developing countries. As a hormone-dependent cancer, breast cancer is classified into several molecular subtypes based on the expression of key markers: Estrogen Receptor (ER), Progesterone Receptor (PR), Human Epidermal Growth Factor Receptor 2 (HER-2), and Ki67. PR loss is associated with endocrine resistance and a poorer prognosis in breast cancer. Despite this, the underlying mechanisms of ER-positive/PR-negative (ER+PR-) breast cancer remain poorly understood. This study aims to review recent advancements in research on ER+PR- breast cancer, analyze its clinical characteristics and molecular mechanisms, and provide recommendations for more targeted therapeutic approaches.

Cell division cycle 6 ​is an independent prognostic biomarker in breast cancer

Cell division cycle 6 (CDC6) is a cell cycle protein involved in cell cycle control, DNA replication and cancer cell apoptosis. This study investigated the prognostic value of CDC6 in breast cancer (BC) utilising large well-characterised cohorts of early-stage ​BC. CDC6 messenger RNA (mRNA) was assessed using the Molecular Taxonomy of the Breast Cancer International Consortium (n=1980), the Cancer Genome Atlas (n=854) and Kaplan-Meier plotter (n=4,929) cohorts. CDC6 protein expression was evaluated using immunohistochemistry in a large (n=951) well-characterised Nottingham BC cohort. The associations between CDC6, clinicopathological parameters, molecular features and patient outcomes were assessed. High CDC6 expression positively correlated with dysregulation of key BC-related genes, including gene involved in cell cycle, DNA damage repair, epithelial cell migration, ​and tumour microenvironment control, as well as with markers characteristic of the basal-like phenotype (CK5, CK14 and CK17). High CDC6 mRNA and protein expression were associated with clinicopathological parameters characteristic of aggressive behaviour, including high tumour grade, large tumour size, the presence of lymphovascular invasion and hormone receptor negativity. High CDC6 protein expression was an independent predictor of poor outcome [p=0.007; hazard ratio (HR)=1.3; 95% confidence interval (CI) 1.2-1.9). This study indicates that CDC6 is an independent prognostic biomarker in BC. These results warrant further functional validation for CDC6 as a potential therapeutic target in BC.

SLC1A5 is a key regulator of glutamine metabolism and a prognostic marker for aggressive luminal breast cancer

Cancer cells exhibit altered metabolism, often relying on glutamine (Gln) for growth. Breast cancer (BC) is a heterogeneous disease with varying clinical outcomes. We investigated the role of the amino acid transporter SLC1A5 (ASCT2) and its association with BC subtypes and patient outcomes. In large BC cohorts, SLC1A5 mRNA (n = 9488) and SLC1A5 protein (n = 1274) levels were assessed and correlated their expression with clinicopathological features, molecular subtypes, and patient outcomes. In vitro SLC1A5 knockdown and inhibition studies in luminal BC cell lines (ZR-75-1 and HCC1500) were used to further explore the role of SLC1A5 in Gln metabolism. Statistical analysis was performed using chi-squared tests, ANOVA, Spearman's correlation, Kaplan-Meier analysis, and Cox regression. SLC1A5 mRNA and SLC1A5 protein expression were strongly correlated in luminal B, HER2 + and triple-negative BC (TNBC). Both high SLC1A5 mRNA and SLC1A5 protein expression were associated with larger tumour size, higher grade, and positive axillary lymph node metastases (P < 0.01). Importantly, high SLC1A5 expression correlated with poor BC-specific survival specifically in the highly proliferative luminal subtype (P < 0.001). Furthermore, SLC1A5 knockdown by siRNA or GPNA inhibition significantly reduced cell proliferation and glutamine uptake in ZR-75-1 cells. Our findings suggest SLC1A5 plays a key role in the aggressive luminal BC subtype and represents a potential therapeutic target. Further research is needed to explore SLC1A5 function in luminal BC and its association with Gln metabolism pathways.

Updates and Future Directions for the Nottingham Research Programme on Primary Breast Cancer in Older Women

The global population is ageing and the risk of breast cancer increases with age. Therefore, we can expect an increase in the number of cases of breast cancer worldwide in the next 20 years. Currently, there are few age-specific guidelines for the management of breast cancer in older women. The International Society of Geriatric Oncology and European Society of Breast Cancer guidelines on this topic were last updated in 2021 and provide some recommendations, although it is worth noting that, generally, the level of evidence pertaining to older women is low. The Nottingham research team on older women with primary breast cancer is working on three main aims in this cohort: (1) understand the unique biological differences between breast cancer in older compared to younger women, (2) explore the unique psycho-social factors that may be present in this population and differ from those found in younger women, as well as how this may influence treatment decisions, and (3) the cost-effectiveness of various treatment strategies in this cohort. This paper will outline key studies published by the Nottingham team in these areas to gather data and highlight future directions for the research group.

Deciphering the Role of ASPM in Breast Cancer: A Comprehensive Multicohort Study

BACKGROUND

Assembly factor for spindle microtubules (ASPM) has gained significant attention in cancer research due to its association with tumor growth and progression. Through the analysis of large-scale genomic datasets, ASPM has been identified as the top upregulated gene in breast cancer (BC), characterized by high proliferation. This multicohort study aimed to investigate the clinicopathological and prognostic significance of ASPM mRNA and protein expression in BC.

METHODS

ASPM mRNA expression was assessed using the Cancer Genome Atlas (TCGA) BC cohort and has been further validated in the Molecular Taxonomy of BC International Consortium (METABRIC) (n = 1980), The Uppsala cohort (n = 249), in addition to the combined multicentric cohort (n = 7252). ASPM protein expression was evaluated in a large BC cohort (n = 1300) using immunohistochemistry. The correlations between ASPM expression, clinicopathological parameters, molecular subtypes and outcome were assessed. The response to taxane treatment was compared to the clinical prognosis of ASPM using the ROC plotter.

RESULTS

High ASPM mRNA and protein expression were significantly associated with aggressive BC features and poor survival across all cohorts. The association with poor outcomes was maintained in the adjuvant chemotherapy and radio-therapy-treated patients. Responders to taxane treatment showed significantly elevated ASPM levels compared to non-responders.

CONCLUSIONS

High ASPM expression predicts poor prognosis in BC. It may play a role in treatment resistance within a specific subgroup of patients. Further clinical trials are warranted to explore the potential of ASPM as a target for therapeutic interventions in cancer.

Research on biomarkers using innovative artificial intelligence systems in breast cancer

Cancer is highly diverse and heterogeneous. Accurate and rapid analysis of the characteristics of individual cancer cells, using a complex array of big data that includes various clinicopathological features and molecular mechanisms, is crucial for advancing precision medicine. In recent years, experts in biomedical sciences and data sciences have explored the potential of artificial intelligence (AI) to analyze such extensive data sets. The next phase of AI-based medical research on cancer should focus on the practical applications of AI tools and how they can be effectively used in actual medical research settings. Recently, translational research that leverages AI and comprehensive genetic analysis data has emerged as a significant research focus. This field represents an opportunity for groundbreaking discoveries to be shared globally. To further precision medicine in clinical practice, it is vital to develop sophisticated AI tools for cancer research. These tools should not only identify potential therapeutic targets through comprehensive genetic analysis but also predict therapeutic outcomes in clinical settings.

The characteristics and prognostic significance of histone H1 expression in breast cancer

Histone H1 (H.H1) is involved in chromatin organisation and gene regulation and is overexpressed in many malignant tumours, including breast cancer (BC). This study proposed and evaluated the prognostic role of H.H1 expression in BC. H.H1 mRNA expression was evaluated in publicly available BC dataset bc-GenExMiner database (n=4421). H.H1 protein expression was assessed immunohistochemically in a well-characterised early-stage BC cohort (n=1311), and associations with clinicopathological data and survival outcomes were evaluated. At the mRNA level, there was a significant association between high H.H1 mRNA and basal-like BC subtype and with poor outcome. The association with shorter survival was observed in the whole cohort and in the basal-like class. H.H1 protein expression was detected in both tumour cells and surrounding stroma. Total expression was detected in 72% of the cases, including 28% in tumour cell nuclei and 44% in the stroma. There was strong association between high tumour H.H1 expression and triple-negative BC (TNBC) subtype (p=0.007) and with shorter survival (p=0.019), independent of other variables including tumour size, histologic tumour grade, and lymph node status. H.H1 expression is associated with poor prognosis in BC. Given poor prognostic role of H.H1 in TNBC, it may represent a potential therapeutic target for patients with this aggressive disease.

The interferon/STAT1 signaling axis is a common feature of tumor-initiating cells in breast cancer

A tumor cell subpopulation of tumor-initiating cells (TIC), or "cancer stem cells", are associated with therapeutic resistance, as well as both local and distant recurrence. Enriched populations of TIC are identified by markers including aldehyde dehydrogenase (ALDH1) activity, the cell surface marker combination CD44 + /CD24 - , or fluorescent reporters for signaling pathways that regulate TIC function. We showed previously that S ignal T ransducer and A ctivator of T ranscription (STAT)-mediated transcription allows enrichment for TIC in claudin-low models of human triple-negative breast cancer using a STAT-responsive reporter. However, the molecular phenotypes of STAT TIC are not well understood, and there is no existing method to lineage-trace TIC as they undergo cell state changes. Using a new STAT-responsive lineage-tracing (LT) system in conjunction with our original reporter, we enriched for cells with enhanced mammosphere-forming potential in some, but not all, basal-like triple-negative breast cancer (TNBC) xenograft models (TNBC) indicating TIC-related and TIC-independent functions for STAT signaling. Single-cell RNA sequencing (scRNAseq) of reporter-tagged xenografts and clinical samples identified a common interferon (IFN)/STAT1-associated transcriptional state, previously linked to inflammation and macrophage differentiation, in TIC. Surprisingly, most of the genes we identified are not present in previously published TIC signatures derived using bulk RNA sequencing. Finally, we demonstrated that bone marrow stromal cell antigen 2 (BST2), is a cell surface marker of this state, and that it functionally regulates TIC frequency. These results suggest TIC may exploit the IFN/STAT1 signaling axis to promote their activity, and that targeting this pathway may help eliminate TIC.

Significance

TIC differentially express interferon response genes, which were not previously reported in bulk RNA sequencing-derived TIC signatures, highlighting the importance of coupling single-cell transcriptomics with enrichment to derive TIC signatures.

The role of the ALKBH5 RNA demethylase in invasive breast cancer

BACKGROUND

N6-methyladenosine (m6A) is the most common internal RNA modification and is involved in regulation of RNA and protein expression. AlkB family member 5 (ALKBH5) is a m6A demethylase. Given the important role of m6A in biological mechanisms, m6A and its regulators, have been implicated in many disease processes, including cancer. However, the contribution of ALKBH5 to invasive breast cancer (BC) remains poorly understood. The aim of this study was to evaluate the clinicopathological value of ALKBH5 in BC.

METHODS

Publicly available data were used to investigate ALKBH5 mRNA alterations, prognostic significance, and association with clinical parameters at the genomic and transcriptomic level. Differentially expressed genes (DEGs) and enriched pathways with low or high ALKBH5 expression were investigated. Immunohistochemistry (IHC) was used to assess ALKBH5 protein expression in a large well-characterised BC series (n = 1327) to determine the clinical significance and association of ALKBH5 expression.

RESULTS

Reduced ALKBH5 mRNA expression was significantly associated with poor prognosis and unfavourable clinical parameters. ALKBH5 gene harboured few mutations and/or copy number alternations, but low ALKBH5 mRNA expression was seen. Patients with low ALKBH5 mRNA expression had a number of differentially expressed genes and enriched pathways, including the cytokine-cytokine receptor interaction pathway. Low ALKBH5 protein expression was significantly associated with unfavourable clinical parameters associated with tumour progression including larger tumour size and worse Nottingham Prognostic Index group.

CONCLUSION

This study implicates ALKBH5 in BC and highlights the need for further functional studies to decipher the role of ALKBH5 and RNA m6A methylation in BC progression.

A novel Nav1.5-dependent feedback mechanism driving glycolytic acidification in breast cancer metastasis

Solid tumours have abnormally high intracellular [Na+]. The activity of various Na+ channels may underlie this Na+ accumulation. Voltage-gated Na+ channels (VGSCs) have been shown to be functionally active in cancer cell lines, where they promote invasion. However, the mechanisms involved, and clinical relevance, are incompletely understood. Here, we show that protein expression of the Nav1.5 VGSC subtype strongly correlates with increased metastasis and shortened cancer-specific survival in breast cancer patients. In addition, VGSCs are functionally active in patient-derived breast tumour cells, cell lines, and cancer-associated fibroblasts. Knockdown of Nav1.5 in a mouse model of breast cancer suppresses expression of invasion-regulating genes. Nav1.5 activity increases ATP demand and glycolysis in breast cancer cells, likely by upregulating activity of the Na+/K+ ATPase, thus promoting H+ production and extracellular acidification. The pH of murine xenograft tumours is lower at the periphery than in the core, in regions of higher proliferation and lower apoptosis. In turn, acidic extracellular pH elevates persistent Na+ influx through Nav1.5 into breast cancer cells. Together, these findings show positive feedback between extracellular acidification and the movement of Na+ into cancer cells which can facilitate invasion. These results highlight the clinical significance of Nav1.5 activity as a potentiator of breast cancer metastasis and provide further evidence supporting the use of VGSC inhibitors in cancer treatment.

Expression of Cathepsin D in early-stage breast cancer and its prognostic and predictive value

PURPOSE

Cathepsin D is a proteolytic enzyme that is normally localized in the lysosomes and is involved in the malignant progression of breast cancer. There are conflicting results regarding Cathepsin D significance as prognostic and predictor marker in breast cancer. This study aimed to evaluate the expression and prognostic significance of Cathepsin D in early-stage breast cancer.

METHODS

Expression of Cathepsin D was assessed by immunohistochemical staining of tissue microarrays, in a large well-characterized series of early-stage operable breast cancer (n = 954) from Nottingham Primary Breast Carcinoma Series between the period of 1988 and 1998 who underwent primary surgery. Correlation of Cathepsin D expression with clinicopathological parameters and prognosis was evaluated.

RESULTS

Cathepsin D expression was positive in 71.2% (679/954) of breast cancer tumours. Positive expression of Cathepsin D was significantly associated with high histological grade (p = 0.007), pleomorphism (p = 0.002), poor Nottingham Prognostic Index (NPI) score (p < 0.002), recurrence (p = 0.005) and distant metastasis (p < 0.0001). Kaplan-Meier analysis showed that Cathepsin D expression was significantly associated with shorter breast cancer-specific survival (p = 0.001), higher risk of recurrence (p = 0.001) and distant metastasis (p < 0.0001). ER-positive tumours expressing Cathepsin D and treated with tamoxifen demonstrated a significantly higher risk of distant metastasis.

CONCLUSION

Cathepsin D expression significantly predicts poor prognosis in breast cancer and is associated with variables of poor prognosis and shorter outcome. The strong association of Cathepsin D with aggressive tumour characteristics and poor outcomes warrants further research of its potential as a therapeutic target The results also suggest a possible interaction between Cathepsin D and tamoxifen therapy in ER-positive breast cancer which needs further investigation to elucidate the underlying mechanisms.

ATF4 as a Prognostic Marker and Modulator of Glutamine Metabolism in Oestrogen Receptor-Positive Breast Cancer

INTRODUCTION

ATF4, a stress-responsive transcription factor that upregulates adaptive genes, is a potential prognostic marker and modulator of glutamine metabolism in breast cancer. However, its exact role remains to be elucidated.

METHODS

ATF4 expression was evaluated at genomic and transcriptomic levels using METABRIC (n = 1,980), GeneMiner (n = 4,712), and KM-Plotter datasets. Proteomic expression was assessed via immunohistochemistry (n = 2,225) in the Nottingham Primary Breast Cancer Series. ATF4 genomic copy number (CN) variation and mRNA/protein in association with clinicopathological parameters, amino acid transporters (AATs), and patient outcome were investigated.

RESULTS

Genomic, transcriptomic, and proteomic overexpression of ATF4 was associated with more aggressive ER-negative tumours. ATF4 mRNA and protein expression were significantly associated with increased expression of glutamine related AATs including SLC1A5 (p < 0.01) and SLC7A11 (p < 0.02). High ATF4 and SLC1A5 protein expression was significantly associated with shorter breast cancer-specific survival (p < 0.01), especially in ER+ tumours (p < 0.01), while high ATF4 and SLC7A11 protein expression was associated with shorter survival (p < 0.01).

CONCLUSION

These findings suggest a complex interplay between ATF4 and AATs in breast cancer biology and underscore the potential role for ATF4 as a prognostic marker in ER+ breast cancer, offering a unique opportunity for risk stratification and personalized treatment strategies.

Clinicopathological Significance of Cyclin-Dependent Kinase 2 (CDK2) in Ductal Carcinoma In Situ and Early-Stage Invasive Breast Cancers

Cyclin-dependent kinase 2 (CDK2) is a key cell cycle regulator, with essential roles during G1/S transition. The clinicopathological significance of CDK2 in ductal carcinomas in situ (DCIS) and early-stage invasive breast cancers (BCs) remains largely unknown. Here, we evaluated CDK2's protein expression in 479 BC samples and 216 DCIS specimens. Analysis of CDK2 transcripts was completed in the METABRIC cohort (n = 1980) and TCGA cohort (n = 1090), respectively. A high nuclear CDK2 protein expression was significantly associated with aggressive phenotypes, including a high tumour grade, lymph vascular invasion, a poor Nottingham prognostic index (all p-values < 0.0001), and shorter survival (p = 0.006), especially in luminal BC (p = 0.009). In p53-mutant BC, high nuclear CDK2 remained linked with worse survival (p = 0.01). In DCIS, high nuclear/low cytoplasmic co-expression showed significant association with a high tumour grade (p = 0.043), triple-negative and HER2-enriched molecular subtypes (p = 0.01), Comedo necrosis (p = 0.024), negative ER status (p = 0.004), negative PR status (p < 0.0001), and a high proliferation index (p < 0.0001). Tumours with high CDK2 transcripts were more likely to have higher expressions of genes involved in the cell cycle, homologous recombination, and p53 signaling. We provide compelling evidence that high CDK2 is a feature of aggressive breast cancers. The clinical evaluation of CDK2 inhibitors in early-stage BC patients will have a clinical impact.

Novel 2 Gene Signatures Associated With Breast Cancer Proliferation: Insights From Predictive Differential Gene Expression Analysis

The use of proliferation markers provides valuable information about the rate of tumor growth, which can guide treatment decisions. However, there is still a lack of consensus regarding the optimal molecular markers or tests to use in clinical practice. Integrating gene expression data with clinical and histopathologic parameters enhances our understanding of disease processes, facilitates the identification of precise prognostic predictors, and supports the development of effective therapeutic strategies. The purpose of this study was to apply an integrated approach that combines morphologic, clinical, and bioinformatic data to reveal effective regulators of proliferation. Whole-slide images generated from hematoxylin-and-eosin-stained sections of The Cancer Genome Atlas (TCGA) breast cancer (BC) database (n = 1053) alongside their transcriptomic and clinical data were used to identify genes differentially expressed between tumors with high and low mitotic scores. Genes enriched in the cell-cycle pathway were used to predict the protein-protein interaction (PPI) network. Ten hub genes (ORC6, SKP2, SMC1B, CDKN2A, CDC25B, E2F1, E2F2, ORC1, PTTG1, and CDC25A) were identified using CytoHubba a Cytoscape plugin. In a multivariate Cox regression model, ORC6 and SKP2 were predictors of survival independent of existing methods of proliferation assessment including mitotic score and Ki67. The prognostic ability of these genes was validated using the Molecular Taxonomy of Breast Cancer International Consortium, Nottingham cohort, Uppsala cohort, and a combined multicentric cohort. The protein expression of these 2 genes was investigated on a large cohort of BC cases, and they were significantly associated with poor prognosis and patient outcome. A positive correlation between ORC6 and SKP2 mRNA and protein expression was observed. Our study has identified 2 gene signatures, ORC6 and SKP2, which play a significant role in BC proliferation. These genes surpassed both mitotic scores and Ki67 in multivariate analysis. Their identification provides potential opportunities for the development of targeted treatments for patients with BC.

Estrogen receptor-negative/progesterone receptor-positive breast cancer has distinct characteristics and pathologic complete response rate after neoadjuvant chemotherapy

PURPOSE

The status of hormone receptors (HR) is an independent factor affecting survival and chemotherapy sensitivity in breast cancer (BC) patients, with estrogen receptor (ER) and progesterone receptor (PR) having the most significant effects. The ER-/PR + phenotype has been controversial in BC, and experts will face many challenges in determining treatment strategies. Herein, we systematically analyzed the clinicopathological characteristics of the ER-/PR + phenotype in BC patients and the response to chemotherapy.

PATIENTS AND METHODS

We included two cohorts. The first cohort counted the relationship between clinicopathologic data and survival outcomes for 72,666 female patients in the Surveillance, Epidemiology, and End Results (SEER) database. The second cohort analyzed the relationship between clinicopathological data and pathologic complete response (pCR) rate in 879 patients at the Harbin Medical University Cancer Hospital. The classification data were compared by the chi-square test and Fister's exact test of the Logistic regression model, and predictor variables with P < 0.05 in the univariate analysis were included in the multivariate regression analysis. The Kaplan-Meier method evaluated breast cancer-specific survival (BCSS) and overall survival (OS) to investigate the relationship between different HR typing and survival and pCR.

RESULTS

In the two cohorts, 704 (0.9%) and 11 (1.3%) patients had the ER-/PR + phenotype, respectively. The clinicopathologic features of patients with the ER-/PR + phenotype are more similar to those of the ER-/PR- phenotype. The ER-/PR + phenotype is more common in younger and premenopausal women, and most ER-/PR + phenotypes exhibit higher histological grades. Survival analysis showed that there were significant differences in OS and BCSS among patients with different HR states (P < 0.001). The survival results of patients with the ER + /PR + phenotype were the best. The prognosis of the ER-/PR + phenotype was similar to that of the ER-/PR- phenotype. On the other hand, we found that HR status was also an independent predictor of post-NAC pCR rate in BC patients. The ER + /PR- and ER-/PR- phenotypes were more sensitive to chemotherapy than the ER + /PR + phenotypes.

CONCLUSION

HR status is the main factor affecting BC's survival outcome and pCR rate. Patients with the ER-/PR + phenotype possess more aggressive biological factors and can benefit significantly from chemotherapy. We need to pay more attention to this group and achieve individualized treatment, which will help us treat BC better and provide new targets and blueprints for our clinical treatment.

Cellular zinc metabolism and zinc signaling: from biological functions to diseases and therapeutic targets

Zinc metabolism at the cellular level is critical for many biological processes in the body. A key observation is the disruption of cellular homeostasis, often coinciding with disease progression. As an essential factor in maintaining cellular equilibrium, cellular zinc has been increasingly spotlighted in the context of disease development. Extensive research suggests zinc's involvement in promoting malignancy and invasion in cancer cells, despite its low tissue concentration. This has led to a growing body of literature investigating zinc's cellular metabolism, particularly the functions of zinc transporters and storage mechanisms during cancer progression. Zinc transportation is under the control of two major transporter families: SLC30 (ZnT) for the excretion of zinc and SLC39 (ZIP) for the zinc intake. Additionally, the storage of this essential element is predominantly mediated by metallothioneins (MTs). This review consolidates knowledge on the critical functions of cellular zinc signaling and underscores potential molecular pathways linking zinc metabolism to disease progression, with a special focus on cancer. We also compile a summary of clinical trials involving zinc ions. Given the main localization of zinc transporters at the cell membrane, the potential for targeted therapies, including small molecules and monoclonal antibodies, offers promising avenues for future exploration.

Characteristics and prognostic significance of polo-like kinase-1 (PLK1) expression in breast cancer

AIM

Polo-like kinase-1 (PLK1) plays a crucial role in cell cycle progression, and it is considered a potential therapeutic target in many cancers. Although the role of PLK1 is well established in triple-negative breast cancer (TNBC) as an oncogene, its role in luminal BC is still controversial. In this study, we aimed to evaluate the prognostic and predictive role of PLK1 in BC and its molecular subtypes.

METHODS

A large BC cohort (n = 1208) were immunohistochemically stained for PLK1. The association with clinicopathological, molecular subtypes, and survival data was analysed. PLK1 mRNA was evaluated in the publicly available datasets (n = 6774), including The Cancer Genome Atlas and the Kaplan-Meier Plotter tool.

RESULTS

20% of the study cohort showed high cytoplasmic PLK1 expression. High PLK1 expression was significantly associated with a better outcome in the whole cohort, luminal BC. In contrast, high PLK1 expression was associated with a poor outcome in TNBC. Multivariate analyses indicated that high PLK1 expression is independently associated with longer survival in luminal BC, and in poorer prognosis in TNBC. At the mRNA levels, PLK1 expression was associated with short survival in TNBC consistent with the protein expression. However, in luminal BC, its prognostic value significantly varies between cohorts.

CONCLUSION

The prognostic role of PLK1 in BC is molecular subtype-dependent. As PLK1 inhibitors are introduced to clinical trials for several cancer types, our study supports evaluation of the pharmacological inhibition of PLK1 as an attractive therapeutic target in TNBC. However, in luminal BC, PLK1 prognostic role remains controversial.

Proteomic Profile Distinguishes New Subpopulations of Breast Cancer Patients with Different Survival Outcomes

As a highly heterogeneous disease, breast cancer (BRCA) demonstrates a diverse molecular portrait. The well-established molecular classification (PAM50) relies on gene expression profiling. It insufficiently explains the observed clinical and histopathological diversity of BRCAs. This study aims to demographically and clinically characterize the six BRCA subpopulations (basal, HER2-enriched, and four luminal ones) revealed by their proteomic portraits. GMM-based high variate protein selection combined with PCA/UMAP was used for dimensionality reduction, while the k-means algorithm allowed patient clustering. The statistical analysis (log-rank and Gehan-Wilcoxon tests, hazard ratio HR as the effect size ES) showed significant differences across identified subpopulations in Disease-Specific Survival (p = 0.0160) and Progression-Free Interval (p = 0.0264). Luminal subpopulations vary in prognosis (Disease-Free Interval, p = 0.0277). The A2 subpopulation is of the poorest, comparable to the HER2-enriched subpopulation, prognoses (HR = 1.748, referenced to Luminal B, small ES), while A3 is of the best (HR = 0.250, large ES). Similar to PAM50 subtypes, no substantial dependency on demographic and clinical factors was detected across Luminal subpopulations, as measured by χ2 test and Cramér's V for ES, and ANOVA with appropriate post hocs combined with η2 or Cohen's d-type ES, respectively. Progesterone receptors can serve as the potential A2 biomarker within Luminal patients. Further investigation of molecular differences is required to examine the potential prognostic or clinical applications.

Impact of non-adherence to endocrine therapy on recurrence risk in older women with stage I breast cancer after breast-conserving surgery

PURPOSE

We examined the impact of non-adherence to adjuvant endocrine therapy (ET) on the risk and site of recurrence among older women with early stage, hormone receptor positive (HR+) breast cancer (EBC).

METHODS

A population-based cohort of women age ≥ 65 years with T1N0 HR + EBC who were diagnosed between 2010 and 2016 and treated with breast-conserving surgery (BCS) + ET was identified. Treatment and outcomes were ascertained through linkage with administrative databases. ET non-adherence was examined as a time-dependent covariate in multivariable cause-specific Cox regression models to evaluate its effect on the risks of ipsilateral local recurrence (LR), contralateral breast cancer, and distant metastases.

RESULTS

The population cohort includes 2637 women; 73% (N = 1934) received radiation (RT) + ET and 27% (N = 703) received ET alone. At a median follow-up of 8.14 years, the first event was LR in 3.6% of women treated with ET alone and 1.4% for those treated with RT + ET (p < 0.001); the risk of distant metastases was < 1% in both groups. The proportion of time adherent to ET was 69.0% among those treated with RT + ET and 62.8% for those treated with ET alone. On multivariable analysis, increasing proportion of time non-adherent to ET was associated with increased risk of LR ((HR = 1.52 per 20% increase in time; 95%CI 1.25, 1.85; p < 0.001), contralateral BC (HR = 1.55; 95%CI 1.30, 1.84; p < 0.001), and distant metastases (HR = 1.44; 95%CI 1.08, 1.94; p = 0.01) but absolute risks were low.

CONCLUSION

Non-adherence to adjuvant ET was associated with an increased risk of recurrence, but absolute recurrence rates were low.

Assessment of the Androgen Receptor in Older Women with Primary Breast Cancer: Association with a Panel of Biomarkers and Breast Cancer Specific Survival

INTRODUCTION

Breast cancer in older women tends to have more favourable biology, compared to younger women. Androgen receptor (AR) is significant for breast tumour carcinogenesis; however, the role of AR in older women has not been fully explored.

METHODS

Surgical specimens were obtained from an existing series of 1758 older women (≥ 70 years) with primary breast cancer, treated in a single institution with long-term (≥ 37 years) follow-up. As part of previous work, it was possible to construct good quality tissue microarrays (TMAs) in 575 surgical specimens and a panel of 24 biomarkers was measured by immunohistochemistry (IHC) in these TMAs. AR positivity was assessed by IHC and defined as H-score ≥ 40. The relationship between AR in this cohort was compared to an equivalent group of younger women (< 70 years, n = 1708); the panel of 24 biomarkers and breast cancer specific survival (BCSS) in the older cohort.

RESULTS

AR was assessed in 509 samples. Overall, 59% of the older women cohort had positive expression of AR, compared to 63% in the younger cohort. AR positivity (regardless of age) was associated with smaller size of tumour, lower grade of tumour, lower tubule formation, lower nuclear polymorphism and lower mitotic frequency. AR positivity was associated with positive expression of oestrogen receptor (ER), progesterone receptor (PR), breast cancer gene 1 (BRCA1), cytokeratin (CK) 7/8, CK18, CK19, B cell lymphoma (Bcl)2 and Mucin 1 (Muc1) expression. Conversely, AR-positive expression was associated with negative expression of human epidermal growth factor receptor 2 (HER2), Ki-67, CK5, CK17, epidermal growth factor receptor (EGFR), and CD44 expression. Older women with AR-positive tumours had better BCSS compared to AR-negative tumours (p = 0.009).

CONCLUSIONS

There was no difference in AR expression between older and younger women with breast cancer. AR has prognostic potential in terms of BCSS. Further work is needed to investigate AR as a therapeutic target.

RANK is a poor prognosis marker and a therapeutic target in ER-negative postmenopausal breast cancer

Despite strong preclinical data, the therapeutic benefit of the RANKL inhibitor, denosumab, in breast cancer patients, beyond the bone, is unclear. Aiming to select patients who may benefit from denosumab, we hereby analyzed RANK and RANKL protein expression in more than 2,000 breast tumors (777 estrogen receptor-negative, ER- ) from four independent cohorts. RANK protein expression was more frequent in ER- tumors, where it associated with poor outcome and poor response to chemotherapy. In ER- breast cancer patient-derived orthoxenografts (PDXs), RANKL inhibition reduced tumor cell proliferation and stemness, regulated tumor immunity and metabolism, and improved response to chemotherapy. Intriguingly, tumor RANK protein expression associated with poor prognosis in postmenopausal breast cancer patients, activation of NFKB signaling, and modulation of immune and metabolic pathways, suggesting that RANK signaling increases after menopause. Our results demonstrate that RANK protein expression is an independent biomarker of poor prognosis in postmenopausal and ER- breast cancer patients and support the therapeutic benefit of RANK pathway inhibitors, such as denosumab, in breast cancer patients with RANK+ ER- tumors after menopause.

High Inner Centromere Protein Expression Correlates with Aggressive Features and Predicts Poor Prognosis in Patients with Invasive Breast Cancer

INTRODUCTION

Inner centromere protein (INCENP) is a member of the chromosomal passenger complex and plays a key role in mitosis and cell proliferation. This study aimed to evaluate the clinical and prognostic significance of INCENP in invasive breast cancer (BC).

METHODS

INCENP expression was evaluated on a tissue microarray of a large BC cohort (n = 1,295) using immunohistochemistry. At the mRNA level, INCENP expression was assessed using the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (n = 1,980) and The Cancer Genome Atlas (TCGA) BC cohorts (n = 854). The correlations between INCENP expression, clinicopathological parameters, and patient outcome were investigated.

RESULTS

INCENP expression was detected in the nucleus and cytoplasm of the tumour cells. Its expression was significantly associated with features characteristic of aggressive BC behaviour including high tumour grade, larger tumour size, and high Nottingham prognostic index scores. High INCENP nuclear expression was a predictor of shorter BC-specific survival in the whole cohort, as well as in the luminal subtype (p < 0.001). High INCENP nuclear expression was predictive of poor prognosis in BC patients who received hormone treatment or chemotherapy.

CONCLUSION

High INCENP expression is a poor prognostic biomarker in BC with potential therapeutic benefits.

The clinical significance of cyclin B1 (CCNB1) in invasive breast cancer with emphasis on its contribution to lymphovascular invasion development

BACKGROUND

Lymphovascular invasion (LVI) is regulated through complex molecular mechanisms. Cyclin B1 (CCNB1) was previously determined as being associated with LVI using large cohorts of breast cancer (BC) and artificial neural network (ANN) technique. In this study, we aimed to assess the association between CCNB1 and LVI, other clinicopathological and other LVI-related biomarkers at the molecular (RNA transcriptomic) and proteomic levels in BC.

METHODS

Two transcriptomic BC cohorts (n = 2834) were used to assess the association between the expression of CCNB1 at the mRNA level and clinicopathological characteristics and patient outcome. Tissue microarrays (TMAs) from a well-characterised BC cohort (n = 2480) with long-term outcome were also used to assess the clinical significance of CCNB1 protein expression using immunohistochemistry.

RESULTS

High CCNB1 mRNA expression was associated with aggressive tumour behaviour, including LVI, larger size, higher tumour grade, high lymph nodal stage, hormonal receptor negativity, HER2 positivity and poor clinical outcome (all p < 0.0001). Similarly, high CCNB1 protein expression was associated with higher tumour grade, hormonal receptor negativity and HER2 positivity (all p < 0.0001). Additionally, there was a significant association between CCNB1- and LVI-related biomarkers including N-cadherin, P-cadherin and TWIST2 at the transcriptomic and proteomic level. Multivariate analysis revealed that CCNB1 was an independent predictor of shorter BC-specific survival (HR = 1.3; 95% CI 1.2-1.5; p = 0.010).

CONCLUSION

CCNB1 is a key gene associated with LVI in BC and has prognostic value. More functional studies are warranted to unravel the mechanistic role of CCNB1 in the development of LVI.

Prognostic and Predictive Value of LIV1 Expression in Early Breast Cancer and by Molecular Subtype

Background: LIV1 is a transmembrane protein that may become a new therapeutic target through the development of antibody–drug conjugates (ADCs). Few studies are available regarding the assessment of LIV1 expression in clinical breast cancer (BC) samples. Methods: We analyzed LIV1 mRNA expression in 8982 primary BC. We searched for correlations between LIV1 expression and clinicopathological data, including disease-free survival (DFS), overall survival (OS), pathological complete response to chemotherapy (pCR), and potential vulnerability and actionability to anti-cancer drugs used or under development in BC. Analyses were performed in the whole population and each molecular subtype separately. Results: LIV1 expression was associated with good-prognosis features and with longer DFS and OS in multivariate analysis. However, patients with high LIV1 expression displayed a lower pCR rate than patients with low expression after anthracycline-based neoadjuvant chemotherapy, including in multivariate analysis adjusted on grade and molecular subtypes. LIV1-high tumors were associated with higher probabilities of sensitivity to hormone therapy and CDK4/6 inhibitors and lower probabilities of sensitivity to immune-checkpoint inhibitors and PARP inhibitors. These observations were different according to the molecular subtypes when analyzed separately. Conclusions: These results may provide novel insights into the clinical development and use of LIV1-targeted ADCs by identifying prognostic and predictive value of LIV1 expression in each molecular subtype and associated vulnerability to other systemic therapies.

Proposal of SVM Utility Kernel for Breast Cancer Survival Estimation

The advancement of medical research in the field of cancer prognosis and diagnosis using various modalities has put oncologists under tremendous stress. The complexity and heterogeneity involved in multiple modalities and their significantly varied clinical outcomes make it difficult to analyze the disease and provide the correct treatment. Breast cancer is the major concern among all cancers worldwide, specifically for females. To help oncologists and cancer patients, research for breast cancer survival estimation has been proposed. It ranges from complex deep neural networks to simple and interpretable architectures. We propose a utility kernel for a support vector machine (SVM) in this article. It is a simple yet powerful function, which performs better than other popular machine learning algorithms and deep neural networks in the task of breast cancer survival prediction using the TCGA-BRCA dataset. This study validates the proposed utility kernel using four different modalities (gene expression, copy number variation, clinical, and histopathological tissue images) and their multi-modal combinations. The SVM based on our utility kernel empirically proves its efficacy by achieving the highest value on various performance measures, whereas advanced deep neural networks fail to train on small and highly imbalanced breast cancer data.

EHD2 overexpression promotes tumorigenesis and metastasis in triple-negative breast cancer by regulating store-operated calcium entry

With nearly all cancer deaths a result of metastasis, elucidating novel pro-metastatic cellular adaptations could provide new therapeutic targets. Here, we show that overexpression of the EPS15-Homology Domain-containing 2 (EHD2) protein in a large subset of breast cancers (BCs), especially the triple-negative (TNBC) and HER2+ subtypes, correlates with shorter patient survival. The mRNAs for EHD2 and Caveolin-1/2, structural components of caveolae, show co-overexpression across breast tumors, predicting shorter survival in basal-like BC. EHD2 shRNA knockdown and CRISPR-Cas9 knockout with mouse Ehd2 rescue, in TNBC cell line models demonstrate a major positive role of EHD2 in promoting tumorigenesis and metastasis. Mechanistically, we link these roles of EHD2 to store-operated calcium entry (SOCE), with EHD2-dependent stabilization of plasma membrane caveolae ensuring high cell surface expression of the SOCE-linked calcium channel Orai1. The novel EHD2-SOCE oncogenic axis represents a potential therapeutic target in EHD2- and CAV1/2-overexpressing BC.

Mechanistic and Clinical Evidence Supports a Key Role for Cell Division Cycle Associated 5 (CDCA5) as an Independent Predictor of Outcome in Invasive Breast Cancer

BACKGROUND

Cell Division Cycle Associated 5 (CDCA5) plays a role in the phosphoinositide 3-kinase (PI3K)/AKT/mTOR signalling pathway involving cell division, cancer cell migration and apoptosis. This study aims to assess the prognostic and biological value of CDCA5 in breast cancer (BC).

METHODS

The biological and prognostic value of CDCA5 were evaluated at mRNA (n = 5109) and protein levels (n = 614) utilizing multiple well-characterized early stage BC cohorts. The effects of CDCA5 knockdown (KD) on multiple oncogenic assays were assessed in vitro using a panel of BC cell lines.

RESULTS

this study examined cohorts showed that high CDCA5 expression was correlated with features characteristic of aggressive behavior and poor prognosis, including the presence of high grade, large tumor size, lymphovascular invasion (LVI), hormone receptor negativity and HER2 positivity. High CDCA5 expression, at both mRNA and protein levels, was associated with shorter BC-specific survival independent of other variables (p = 0.034, Hazard ratio (HR) = 1.6, 95% CI; 1.1-2.3). In line with the clinical data, in vitro models indicated that CDCA5 depletion results in a marked decrease in BC cell invasion and migration abilities and a significant accumulation of the BC cells in the G2/M-phase.

CONCLUSIONS

These results provide evidence that CDCA5 plays an important role in BC development and metastasis and could be used as a potential biomarker to predict disease progression in BC.

A Case Series Exploration of Multi-Regional Expression Heterogeneity in Triple-Negative Breast Cancer Patients

Extensive intratumoral heterogeneity (ITH) is believed to contribute to therapeutic failure and tumor recurrence, as treatment-resistant cell clones can survive and expand. However, little is known about ITH in triple-negative breast cancer (TNBC) because of the limited number of single-cell sequencing studies on TNBC. In this study, we explored ITH in TNBC by evaluating gene expression-derived and imaging-derived multi-region differences within the same tumor. We obtained tissue specimens from 10 TNBC patients and conducted RNA sequencing analysis of 2-4 regions per tumor. We developed a novel analysis framework to dissect and characterize different types of variability: between-patients (inter-tumoral heterogeneity), between-patients across regions (inter-tumoral and region heterogeneity), and within-patient, between-regions (regional intratumoral heterogeneity). We performed a Bayesian changepoint analysis to assess and classify regional variability as low (convergent) versus high (divergent) within each patient feature (TNBC and PAM50 subtypes, immune, stroma, tumor counts and tumor infiltrating lymphocytes). Gene expression signatures were categorized into three types of variability: between-patients (108 genes), between-patients across regions (183 genes), and within-patients, between-regions (778 genes). Based on the between-patient gene signature, we identified two distinct patient clusters that differed in menopausal status. Significant intratumoral divergence was observed for PAM50 classification, tumor cell counts, and tumor-infiltrating T cell abundance. Other features examined showed a representation of both divergent and convergent results. Lymph node stage was significantly associated with divergent tumors. Our results show extensive intertumoral heterogeneity and regional ITH in gene expression and image-derived features in TNBC. Our findings also raise concerns regarding gene expression based TNBC subtyping. Future studies are warranted to elucidate the role of regional heterogeneity in TNBC as a driver of treatment resistance.

CYP2S1 and CYP2W1 expression is associated with patient survival in breast cancer

The cytochrome P450 family of enzymes metabolise a wide range of compounds and play important roles in breast cancer pathogenesis due to their involvement in estrogen metabolism and the production of carcinogenic metabolites during this process. The orphan CYPs, CYP2S1, and CYP2W1 are reportedly upregulated in breast cancer. However, their expression and association with clinicopathological and survival parameters have not been previously assessed in a large cohort of breast cancers. Protein expression of CYP2S1 and CYP2W1 was assessed in early-stage invasive breast cancers (n = 1,426) using immunohistochemistry and correlated with various clinicopathological parameters and survival. mRNA expression of CYP2S1 and CYP2W1 was also assessed in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort. Low nuclear and cytoplasmic CYP2S1 was significantly associated with high-grade tumours (p ≤ 0.009), intermediate Nottingham prognostic index (NPI) group (p ≤ 0.025), high mitotic frequency (p ≤ 0.002), human epidermal growth factor receptor 2 (HER2)-negative disease (p ≤ 0.011), and ductal carcinoma (p ≤ 0.022). Cytoplasmic CYP2S1 was additionally associated with patients ≥50 years (p < 0.001), estrogen receptor (ER)-positive tumours (p = 0.011), and high nuclear pleomorphism (p = 0.003). Low cytoplasmic CYP2W1 was significantly associated with patients ≥50 years (p = 0.002), HER2-negative disease (p = 0.003), intermediate NPI (p = 0.013), and mitosis (p = 0.009). Low cytoplasmic CYP2S1 was significantly associated with adverse breast cancer specific survival (p = 0.034), which remained so in multivariate analysis (hazard ratio [HR]: 0.639; 95% confidence interval [CI]: 0.483-0.846; p = 0.002). Low nuclear CYP2W1 was significantly associated with adverse breast cancer specific survival (p = 0.012), with significance also maintained in multivariate analysis (HR: 0.677; 95% CI: 0.510-0.898; p = 0.007). No associations with survival were observed in the METABRIC cohort. CYP2S1 and CYP2W1 are associated with patient survival in breast cancer and may be important prognostic biomarkers.

Prognostic value of neutrophil-to-lymphocyte ratio for patients with triple-negative breast cancer: A meta-analysis

We aimed to evaluate the prognostic role of the neutrophil-to-lymphocyte ratio (NLR) in patients with triple-negative breast cancer (TNBC). We searched the PubMed Database, Cochrane Library, Web of science, and Embase. Overall survival (OS), disease-free survival (DFS), and hazard ratio (HR) were the endpoints of the study. Eleven studies involving 2355 patients with TNBC were included in this meta-analysis. Among them, 10 studies involving 2069 patients with TNBC investigated the role of NLR in predicting OS; elevated NLR was associated with poor prognosis (hazard ratio [HR]: 2.48, 95% confidence interval [CI]: 2.03-3.03, P < 0.001). Ten studies involving 2054 patients with TNBC explored the role of NLR in predicting DFS; elevated NLR was associated with a significantly worse prognosis with a pooled HR of 2.20 (95% CI: 1.88-2.58, P < 001). This meta-analysis suggests that patients with TNBC who have a higher NLR have poorer prognoses. As a clinical parameter that we can easily obtain, NLR might be a potential predictor of patients' survival, and may be useful for physicians' treatment decisions.

Chemokines in Triple-Negative Breast Cancer Heterogeneity: New Challenges for Clinical Implications

Tumor heterogeneity is a hallmark of cancer and one of the primary causes of resistance to therapies. Triple-negative breast cancer (TNBC), which accounts for 15% to 20% of all breast cancers and is the most aggressive subtype, is very diverse, connected to metastatic potential and response to therapy. It is a very diverse disease at the molecular, pathologic, and clinical levels. TNBC is substantially more likely to recur and has a worse overall survival rate following diagnosis than other breast cancer subtypes. Chemokines, low molecular weight proteins that stimulate chemotaxis, have been shown to control the cues responsible for TNBC heterogeneity. In this review, we have focused on tumor heterogeneity and the role of chemokines in modulating tumor heterogeneity, since this is the most critical issue in treating TNBC. Additionally, we examined numerous cues mediated by chemokine networks that contribute to the heterogeneity of TNBC. Recent developments in our knowledge of the chemokine networks that regulate TNBC heterogeneity may pave the door for developing difficult-to-treat TNBC treatment options.

Transcriptional Factor Repertoire of Breast Cancer in 3D Cell Culture Models

Simple Summary

Knowledge of the transcriptional regulation of breast cancer tumorigenesis is largely based on studies performed in two-dimensional (2D) monolayer culture models, which lack tissue architecture and therefore fail to represent tumor heterogeneity. However, three-dimensional (3D) cell culture models are better at mimicking in vivo tumor microenvironment, which is critical in regulating cellular behavior. Hence, 3D cell culture models hold great promise for translational breast cancer research.

Abstract

Intratumor heterogeneity of breast cancer is driven by extrinsic factors from the tumor microenvironment (TME) as well as tumor cell–intrinsic parameters including genetic, epigenetic, and transcriptomic traits. The extracellular matrix (ECM), a major structural component of the TME, impacts every stage of tumorigenesis by providing necessary biochemical and biomechanical cues that are major regulators of cell shape/architecture, stiffness, cell proliferation, survival, invasion, and migration. Moreover, ECM and tissue architecture have a profound impact on chromatin structure, thereby altering gene expression. Considering the significant contribution of ECM to cellular behavior, a large body of work underlined that traditional two-dimensional (2D) cultures depriving cell–cell and cell–ECM interactions as well as spatial cellular distribution and organization of solid tumors fail to recapitulate in vivo properties of tumor cells residing in the complex TME. Thus, three-dimensional (3D) culture models are increasingly employed in cancer research, as these culture systems better mimic the physiological microenvironment and shape the cellular responses according to the microenvironmental cues that will regulate critical cell functions such as cell shape/architecture, survival, proliferation, differentiation, and drug response as well as gene expression. Therefore, 3D cell culture models that better resemble the patient transcriptome are critical in defining physiologically relevant transcriptional changes. This review will present the transcriptional factor (TF) repertoire of breast cancer in 3D culture models in the context of mammary tissue architecture, epithelial-to-mesenchymal transition and metastasis, cell death mechanisms, cancer therapy resistance and differential drug response, and stemness and will discuss the impact of culture dimensionality on breast cancer research.

Ubiquitin-conjugating enzyme 2C (UBE2C) is a poor prognostic biomarker in invasive breast cancer

Background

The Ubiquitin-conjugating enzyme 2C (UBE2C) is essential for the ubiquitin–proteasome system and is involved in cancer cell migration and apoptosis. This study aimed to determine the prognostic value of UBE2C in invasive breast cancer (BC).

Methods

UBE2C was evaluated using the Molecular Taxonomy of Breast Cancer International Consortium (n = 1980), The Cancer Genome Atlas (n = 854) and Kaplan–Meier Plotter (n = 3951) cohorts. UBE2C protein expression was assessed using immunohistochemistry in the BC cohort (n = 619). The correlation between UBE2C, clinicopathological parameters and patient outcome was assessed.

Results

High UBE2C mRNA and protein expressions were correlated with features of poor prognosis, including high tumour grade, large size, the presence of lymphovascular invasion, hormone receptor negativity and HER2 positivity. High UBE2C mRNA expression showed a negative association with E-cadherin, and a positive association with adhesion molecule N-cadherin, matrix metalloproteinases and cyclin-related genes. There was a positive correlation between high UBE2C protein expression and cell cycle-associated biomarkers, p53, Ki67, EGFR and PI3K. High UBE2C protein expression was an independent predictor of poor outcome (p = 0.011, HR = 1.45, 95% CI; 1.10–1.93).

Conclusion

This study indicates that UBE2C is an independent prognostic biomarker in BC. These results warrant further functional validation for UBE2C as a potential therapeutic target in BC.

The Biological and Clinical Significance of Glutaminase in Luminal Breast Cancer

Simple Summary

Certain nutrients are needed by cancers to grow. Some breast cancers need the nutrient glutamine to grow and without it they don’t grow as quickly. In this study, we wanted to know the role of an enzyme, glutaminase, which is a substance produced by the body that breaks down glutamine so it can be used by cancers to grow. This enzyme occurs as two different types but we don’t know what their roles are in breast cancer. We therefore looked at the two types of enzyme in over 7000 breast cancers. We found that patients with high amounts of enzyme in early forms of breast cancer died earlier. Therefore, this enzyme has an important role in breast cancer and could be used to identify cancers which will get worse. We also think that using a drug to stop this enzyme will stop cancers growing. More studies are needed to confirm this.

Abstract

The glutamine metabolism has a key role in the regulation of uncontrolled tumour growth. This study aimed to evaluate the expression and prognostic significance of glutaminase in luminal breast cancer (BC). The glutaminase isoforms (GLS/GLS2) were assessed at genomic/transcriptomic levels, using METABRIC (n = 1398) and GeneMiner datasets (n = 4712), and protein using immunohistochemistry in well-characterised cohorts of Oestrogen receptor-positive/HER2-negative BC patients: ductal carcinoma in situ (DCIS; n = 206) and invasive breast cancer (IBC; n = 717). Glutaminase expression was associated with clinicopathological features, patient outcome and glutamine-metabolism-related genes. In DCIS, GLS alone and GLS+/GLS2- expression were risk factors for shorter local recurrence-free interval (p < 0.0001 and p = 0.001, respectively) and remained prognostic factors independent of tumour size, grade and comedo necrosis (p = 0.0008 and p = 0.003, respectively). In IBC, GLS gene copy number gain with high mRNA expression was associated with poor patient outcome (p = 0.011), whereas high GLS2 protein was predictive of a longer disease-free survival (p = 0.006). Glutaminase plays a role in the biological function of luminal BC, particularly GLS in the early non-invasive stage, which could be used as a potential biomarker to predict disease progression and a target for inhibition. Further validation is required to confirm these observations, and functional assessments are needed to explore their specific roles.

Cluster Analysis According to Immunohistochemistry is a Robust Tool for Non-Small Cell Lung Cancer and Reveals a Distinct, Immune Signature-defined Subgroup

Clustering in medicine is the subgrouping of a cohort according to specific phenotypical or genotypical traits. For breast cancer and lymphomas, clustering by gene expression profiles has already resulted in important prognostic and predictive subgroups. For non-small cell lung cancer (NSCLC), however, little is known. We performed a cluster analysis on a cohort of 365 surgically resected, well-documented NSCLC patients, which was followed-up for a median of 62 months, incorporating 70 expressed proteins and several genes. Our data reveal that tumor grading by architecture is significant, that large cell carcinoma is likely not a separate entity, and that an immune signature cluster exists. For squamous cell carcinomas, a prognostically relevant cluster with poorer outcome was found, defined by a high CD4/CD8 ratio and lower presence of granzyme B+ tumor-infiltrating lymphocytes (TIL). This study shows that clustering analysis is a useful tool for verifying established characteristics and generating new insights for NSCLC. Importantly, for one "immune signature" cluster, the signature of the TIL (especially the amount of CD8+ TIL) was more crucial than the histologic or any other phenotypical aspect. This may be an important finding toward explaining why only a fraction of eligible patients respond to immunomodulating anticancer therapies.

SLC7A5 serves as a prognostic factor of breast cancer and promotes cell proliferation through activating AKT/mTORC1 signaling pathway

Background

The purpose of our research was to determine if the clinical, pathological, and prognostic functions of SLC7A5 are the same as those of other molecular breast cancer (BC) subgroups.

Methods

We used the Oncomine and The Cancer Genome Atlas (TCGA) online databases to examine the expression and genetic changes of SLC7A5 in BC tissues. Immunohistochemical analysis was used to validate the SLC7A5 protein expression in subtypes of BC, while Kaplan-Meier figures and log-rank tests were used to evaluate the prognostic relevance of SLC7A5. Uni- and multivariate Cox regression models were adapted to analyze hazard ratios (HRs) and the independent prognostic factors. We analyzed the alterations of different malignancies of luminal cells by up-regulation of SLC7A5 in human luminal cell lines MCF-7. SLC7A5 was overexpressed in luminal cells, and then the AKT, mTOR, and p70-S6K phosphorylation and expression were analyzed by western blot analysis and real-time quantitative polymerase chain reaction (qPCR).

Results

Our results suggested that SLC7A5 was overexpressed in BC cell lines and in patients’ tissues. Elevated SLC7A5 messenger RNA (mRNA) and SLC7A5 protein expression was correlated to a worse clinical prognosis (P<0.001) in luminal subtypes of BC. The multivariate analysis suggested that high level of SLC7A5 expression could be an independent prognostic factor for decreased overall survival (OS). The study also demonstrated that SLC7A5 overexpression increased proliferation of MCF-7 cells by reducing the cell cycle arrest in G1 phase. Our mechanistic study further indicates that SLC7A5 enhances the proliferation of the MCF-7 cell by activation of AKT/mTORC1 pathway through phosphorylation.

Conclusions

Our study demonstrated that SLC7A5 may have a vital function in the biology of BC cells, indicating that SLC7A5 is a potential prognostic biomarker and may be a valuable therapeutic target in BC patients.

Radiomic and radiogenomic modeling for radiotherapy: strategies, pitfalls, and challenges

The power of predictive modeling for radiotherapy outcomes has historically been limited by an inability to adequately capture patient-specific variabilities; however, next-generation platforms together with imaging technologies and powerful bioinformatic tools have facilitated strategies and provided optimism. Integrating clinical, biological, imaging, and treatment-specific data for more accurate prediction of tumor control probabilities or risk of radiation-induced side effects are high-dimensional problems whose solutions could have widespread benefits to a diverse patient population-we discuss technical approaches toward this objective. Increasing interest in the above is specifically reflected by the emergence of two nascent fields, which are distinct but complementary: radiogenomics, which broadly seeks to integrate biological risk factors together with treatment and diagnostic information to generate individualized patient risk profiles, and radiomics, which further leverages large-scale imaging correlates and extracted features for the same purpose. We review classical analytical and data-driven approaches for outcomes prediction that serve as antecedents to both radiomic and radiogenomic strategies. Discussion then focuses on uses of conventional and deep machine learning in radiomics. We further consider promising strategies for the harmonization of high-dimensional, heterogeneous multiomics datasets (panomics) and techniques for nonparametric validation of best-fit models. Strategies to overcome common pitfalls that are unique to data-intensive radiomics are also discussed.

RANK signaling increases after anti-HER2 therapy contributing to the emergence of resistance in HER2-positive breast cancer

BACKGROUND

Around 15-20% of primary breast cancers are characterized by HER2 protein overexpression and/or HER2 gene amplification. Despite the successful development of anti-HER2 drugs, intrinsic and acquired resistance represents a major hurdle. This study was performed to analyze the RANK pathway contribution in HER2-positive breast cancer and anti-HER2 therapy resistance.

METHODS

RANK and RANKL protein expression was assessed in samples from HER2-positive breast cancer patients resistant to anti-HER2 therapy and treatment-naive patients. RANK and RANKL gene expression was analyzed in paired samples from patients treated with neoadjuvant dual HER2-blockade (lapatinib and trastuzumab) from the SOLTI-1114 PAMELA trial. Additionally, HER2-positive breast cancer cell lines were used to modulate RANK expression and analyze in vitro the contribution of RANK signaling to anti-HER2 resistance and downstream signaling.

RESULTS

RANK and RANKL proteins are more frequently detected in HER2-positive tumors that have acquired resistance to anti-HER2 therapies than in treatment-naive ones. RANK (but not RANKL) gene expression increased after dual anti-HER2 neoadjuvant therapy in the cohort from the SOLTI-1114 PAMELA trial. Results in HER2-positive breast cancer cell lines recapitulate the clinical observations, with increased RANK expression observed after short-term treatment with the HER2 inhibitor lapatinib or dual anti-HER2 therapy and in lapatinib-resistant cells. After RANKL stimulation, lapatinib-resistant cells show increased NF-κB activation compared to their sensitive counterparts, confirming the enhanced functionality of the RANK pathway in anti-HER2-resistant breast cancer. Overactivation of the RANK signaling pathway enhances ERK and NF-κB signaling and increases lapatinib resistance in different HER2-positive breast cancer cell lines, whereas RANK loss sensitizes lapatinib-resistant cells to the drug. Our results indicate that ErbB signaling is required for RANK/RANKL-driven activation of ERK in several HER2-positive cell lines. In contrast, lapatinib is not able to counteract the NF-κB activation elicited after RANKL treatment in RANK-overexpressing cells. Finally, we show that RANK binds to HER2 in breast cancer cells and that enhanced RANK pathway activation alters HER2 phosphorylation status.

CONCLUSIONS

Our data support a physical and functional link between RANK and HER2 signaling in breast cancer and demonstrate that increased RANK signaling may contribute to the development of lapatinib resistance through NF-κB activation. Whether HER2-positive breast cancer patients with tumoral RANK expression might benefit from dual HER2 and RANK inhibition therapy remains to be elucidated.

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AIMS

The mechanisms that drive breast cancer (BC) progression and poor outcome are not fully understood. The human heat shock protein 90 alpha family class A member 1 (HSP90α) encoded by the HSP90ΑA1 gene has a vital role in cellular responses to stress and is implicated in the development and progression of many cancers. The current study aims to explore the clinical and prognostic importance of HSP90α in BC.

METHODS

The Molecular Taxonomy of Breast Cancer International Consortium (n=1980); The Cancer Genome Atlas (n=1097) and the Breast Cancer Gene-Expression Miner (Bc-GenExMiner) BC datasets (n=5056) were used to evaluate HSP90ΑA1 mRNA expression. HSP90α protein expression was further assessed using immunohistochemistry in a large (n=911) well-characterised BC series. The association between mRNA and protein expressions with other clinicopathological parameters and outcome was analysed.

RESULTS

High expression of HSP90ΑA1 both at the mRNA and protein levels was significantly associated with characteristics of BC poor prognosis, including high grade, lymphovascular invasion, poor Nottingham Prognostic Index and positive expression of p53 and PIK3CA. Outcome analysis revealed that high HSP90α protein expression is an independent predictor of shorter BC-specific survival.

CONCLUSION

HSP90α can be used as a potential prognostic marker in BC. Further mechanistic studies are warranted to determine the underlying molecular mechanisms mediated by HSP90α in BC.

Age-Related Biology of Early-Stage Operable Breast Cancer and Its Impact on Clinical Outcome

Simple Summary

Breast cancer incidence not only increases with advancing age but also changes its biology. This study was conducted to understand aging related change in the biological characteristics of breast cancer. The results highlighted that the change occurs in a gradual fashion, where 40 years and 70 years become the milestones for significant difference. Breast cancer in patients <40 years showed aggressive characteristics while at 70 years and above they are more indolent. The molecular pattern between 40 years and 70 years appears to be a transition from aggressive to less aggressive phenotypes. This change in the biology of the breast cancer significantly influences clinical outcome.

Abstract

As age advances, breast cancer (BC) tends to change its biological characteristics. This study aimed to explore the natural progression of such changes. The study included 2383 women with clinically T0-2N0-1M0 BC, managed by primary surgery and optimal adjuvant therapy in a dedicated BC facility. Tissue micro-arrays were constructed from their surgical specimens and indirect immunohistochemistry was used for analysis of a large panel (n = 16) of relevant biomarkers. There were significant changes in the pattern of expression of biomarkers related to luminal (oestrogen receptor (ER), progesterone receptors (PgR), human epidermal growth factor receptor (HER-2), E-cadherin, MUC1, bcl2 CK7/8, CK18 and bcl2) and basal (CK5/6, CK14, p53 and Ki67) phenotypes, lymph node stage, histological grade and pathological size when decade-wise comparison was made (p < 0.05). The ages of 40 years and 70 years appeared to be the milestones marking a change of the pattern. There were significantly higher metastasis free and breast cancer specific survival rates among older women with ER positive tumours while there was no significant difference in the ER negative group according to age. Biological characteristics of BC show a pattern of change with advancing age, where 40 years and 70 years appear as important milestones. The pattern suggests <40 years as the phase with aggressive phenotypes, >70 years as the less aggressive phase and 40–70 years being the transitional phase.

The prognostic significance of interferon-stimulated gene 15 (ISG15) in invasive breast cancer

BACKGROUND

Lymphovascular invasion (LVI) is a prognostic factor in early-stage invasive breast cancer (BC). Through bioinformatics, data analyses of multiple BC cohorts revealed the positive association between interferon-stimulated gene 15 (ISG15) LVI status. Thus, we explored the prognostic significance of ISG15 in BC.

METHODS

The prognostic significance of ISG15 mRNA was assessed in METABRIC (n = 1980), TCGA (n = 854) and Kaplan-Meier Plotter (n = 3951). ISG15 protein was evaluated using immunohistochemistry (n = 859) in early-stage invasive BC patients with long-term follow-up. The associations between ISG15 expression and clinicopathological features, expression of immune cell markers and patient outcome data were evaluated.

RESULTS

High mRNA and protein ISG15 expression were associated with LVI, higher histological grade, larger tumour size, hormonal receptor negativity, HER2 positivity, p53 and Ki67. High ISG15 protein expression was associated with HER2-enriched BC subtypes and immune markers (CD8, FOXP3 and CD68). High ISG15 mRNA and ISG15 expressions were associated with poor patient outcome. Cox proportional multivariate analysis revealed that the elevated ISG15 expression was an independent prognostic factor of shorter BC-specific survival.

CONCLUSION

This study provides evidence for the role of ISG15 in LVI development and BC prognosis. Further functional studies in BC are warranted to evaluate the therapeutic potential of ISG15.

Oestrogen-regulated protein SLC39A6: a biomarker of good prognosis in luminal breast cancer

PURPOSE

The outcome of the luminal oestrogen receptor-positive (ER +) subtype of breast cancer (BC) is highly variable and patient stratification needs to be refined. We assessed the prognostic significance of oestrogen-regulated solute carrier family 39 member 6 (SLC39A6) in BC, with emphasis on ER + tumours.

MATERIALS AND METHODS

SLC39A6 mRNA expression and copy number alterations were assessed using the METABRIC cohort (n = 1980). SLC39A6 protein expression was evaluated in a large (n = 670) and annotated series of early-stage (I-III) operable BC using tissue microarrays and immunohistochemistry. The associations between SLC39A6 expression and clinicopathological parameters, patient outcomes and other ER-related markers were evaluated using Chi-square tests and Kaplan-Meier curves.

RESULTS

High SLC39A6 mRNA and protein expression was associated with features characteristic of less aggressive tumours in the entire BC cohort and ER + subgroup. SLC39A6 protein expression was detected in the cytoplasm and nuclei of the tumour cells. High SLC39A6 nuclear expression and mRNA levels were positively associated with ER + tumours and expression of ER-related markers, including the progesterone receptor, forkhead box protein A1 and GATA binding protein 3. In the ER + luminal BC, high SLC39A6 expression was independently associated with longer BC-specific survival (BCSS) (P = 0.015, HR 0.678, 95% CI 0.472‒0.972) even in those who did not receive endocrine therapy (P = 0.001, HR 0.701, 95% CI 0.463‒1.062).

CONCLUSION

SLC39A6 may be prognostic for a better outcome in ER + luminal BC. Further functional studies to investigate the role of SLC39A6 in ER + luminal BC are warranted.

Increased expression of glutamine transporter SNAT2/SLC38A2 promotes glutamine dependence and oxidative stress resistance, and is associated with worse prognosis in triple-negative breast cancer

BACKGROUND

Glutamine (Gln) is an abundant nutrient used by cancer cells. Breast cancers cells and particularly triple-receptor negative breast cancer (TNBC) are reported to be dependent on Gln to produce the energy required for survival and proliferation. Despite intense research on the role of the intracellular Gln pathway, few reports have focussed on Gln transporters in breast cancer and TNBC.

METHODS

The role and localisation of the Gln transporter SLC38A2/SNAT2 in response to Gln deprivation or pharmacological stresses was examined in a panel of breast cancer cell lines. Subsequently, the effect of SLC38A2 knockdown in Gln-sensitive cell lines was analysed. The prognostic value of SLC38A2 in a cohort of breast cancer was determined by immunohistochemistry.

RESULTS

SLC38A2 was identified as a strongly expressed amino acid transporter in six breast cancer cell lines. We confirmed an autophagic route of degradation for SLC38A2. SLC38A2 knockdown decreased Gln consumption, inhibited cell growth, induced autophagy and led to ROS production in a subgroup of Gln-sensitive cell lines. High expression of SLC38A2 protein was associated with poor breast cancer specific survival in a large cohort of patients (p = 0.004), particularly in TNBC (p = 0.02).

CONCLUSIONS

These results position SLC38A2 as a selective target for inhibiting growth of Gln-dependent breast cancer cell lines.

Patterns of biomarker expression in patients treated with primary endocrine therapy - a unique insight using core needle biopsy tissue microarray

Purpose

Prediction of response to primary endocrine therapy (PET) in older women is based on measurement of oestrogen receptor (ER), progesterone receptor (PgR) and human epidermal growth factor (HER)-2. This study uses a unique method for construction of core needle biopsy (CNB) tissue microarray (TMA), to correlate expression of a panel of 17 biomarkers with clinical outcome, in patients receiving PET.

Methods

Over 37 years (1973–2010), 1758 older (≥ 70 years) women with operable primary breast cancer were managed in a single institution. Of these, 693 had sufficient good-quality CNB to construct TMA, of which 334 had ER-positive tumours treated by PET with a minimum of 6-month follow-up. A panel of biomarkers was measured by immunohistochemistry (ER, PgR, HER2, Ki-67, p53, CK5/6, CK 7/8, EGFR, BCL-2, MUC1, VEGF, LKB1, BRCA1, HER3, HER4, PTEN and AIB1). Expression of each biomarker was dichotomised into ‘low’ or ‘high’ based on breast cancer-specific survival (BCSS).

Results

From the panel of biomarkers, multivariate analysis showed:

High ER (p = 0.003) and PgR (p = 0.002) were associated with clinical benefit of PET at 6 months, as opposed to progressive disease.

High ER (p = 0.0023), PgR (p < 0.001) and BCL-2 (p = 0.043) and low LKB1 (p = 0.022) were associated with longer time to progression.

High PgR (p < 0.001) and low MUC1 (p = 0.021) were associated with better BCSS.

Expression of other biomarkers did not show any significant correlation.

Conclusions

In addition to ER and PgR; MUC1, BCL-2 and LKB1 are important in determining the outcome of PET in this cohort.

Electronic supplementary material

The online version of this article (10.1007/s10549-020-06023-4) contains supplementary material, which is available to authorised users.

Nucleolar protein 10 (NOP10) predicts poor prognosis in invasive breast cancer

Purpose

Nucleolar protein 10 (NOP10) is required for ribosome biogenesis and telomere maintenance and plays a key role in carcinogenesis. This study aims to evaluate the clinical and prognostic significance of NOP10 in breast cancer (BC).

Methods

NOP10 expression was assessed at mRNA level employing the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (n = 1980) and Cancer Genome Atlas (TCGA) BC cohorts (n = 854). Protein expression was evaluated on tissue microarray of a large BC cohort (n = 1081) using immunohistochemistry. The correlation between NOP10 expression, clinicopathological parameters and patient outcome was assessed.

Results

NOP10 expression was detected in the nucleus and nucleolus of the tumour cells. At the transcriptomic and proteomic levels, NOP10 was significantly associated with aggressive BC features including high tumour grade, high nucleolar score and poor Nottingham Prognostic Index. High NOP10 protein expression was an independent predictor of poor outcome in the whole cohort and in triple-negative BC (TNBC) class (p = 0.002 & p = 0.014, respectively). In chemotherapy- treated patients, high NOP10 protein expression was significantly associated with shorter survival (p = 0.03) and was predictive of higher risk of death (p = 0.028) and development of distant metastasis (p = 0.02) independent of tumour size, nodal stage and tumour grade.

Conclusion

High NOP10 expression is a poor prognostic biomarker in BC and its expression can help in predicting chemotherapy resistance. Functional assessments are necessary to decipher the underlying mechanisms and to reveal its potential therapeutic values in various BC subtypes especially in the aggressive TNBC class.

Electronic supplementary material

The online version of this article (doi:10.1007/s10549-020-05999-3) contains supplementary material, which is available to authorized users.

The nucleolar-related protein Dyskerin pseudouridine synthase 1 (DKC1) predicts poor prognosis in breast cancer

BACKGROUND

Hypertrophy of the nucleolus is a distinctive cytological feature of malignant cells and corresponds to aggressive behaviour. This study aimed to identify the key gene associated with nucleolar prominence (NP) in breast cancer (BC) and determine its prognostic significance.

METHODS

From The Cancer Genome Atlas (TCGA) cohort, digital whole slide images identified cancers having NP served as label and an information theory algorithm was applied to find which mRNA gene best explained NP. Dyskerin Pseudouridine Synthase 1 (DKC1) was identified. DKC1 expression was assessed using mRNA data of Molecular Taxonomy of Breast Cancer International Consortium (METABRIC, n = 1980) and TCGA (n = 855). DKC1 protein expression was assessed using immunohistochemistry in Nottingham BC cohort (n = 943).

RESULTS

Nuclear and nucleolar expressions of DKC1 protein were significantly associated with higher tumour grade (p < 0.0001), high nucleolar score (p < 0.001) and poor Nottingham Prognostic Index (p < 0.0001). High DKC1 expression was associated with shorter BC-specific survival (BCSS). In multivariate analysis, DKC1 mRNA and protein expressions were independent risk factors for BCSS (p < 0.01).

CONCLUSION

DKC1 expression is strongly correlated with NP and its overexpression in BC is associated with unfavourable clinicopathological characteristics and poor outcome. This has been a detailed example in the correlation of phenotype with genotype.

RNA-Seq-Based Breast Cancer Subtypes Classification Using Machine Learning Approaches

Background

Breast invasive carcinoma (BRCA) is not a single disease as each subtype has a distinct morphology structure. Although several computational methods have been proposed to conduct breast cancer subtype identification, the specific interaction mechanisms of genes involved in the subtypes are still incomplete. To identify and explore the corresponding interaction mechanisms of genes for each subtype of breast cancer can impose an important impact on the personalized treatment for different patients.

Methods

We integrate the biological importance of genes from the gene regulatory networks to the differential expression analysis and then obtain the weighted differentially expressed genes (weighted DEGs). A gene with a high weight means it regulates more target genes and thus holds more biological importance. Besides, we constructed gene coexpression networks for control and experiment groups, and the significantly differentially interacting structures encouraged us to design the corresponding Gene Ontology (GO) enrichment based on gene coexpression networks (GOEGCN). The GOEGCN considers the two-side distinction analysis between gene coexpression networks for control and experiment groups. The method allows us to study how the modulated coexpressed gene couples impact biological functions at a GO level.

Results

We modeled the binary classification with weighted DEGs for each subtype. The binary classifier could make a good prediction for an unseen sample, and the experimental results validated the effectiveness of our proposed approaches. The novel enriched GO terms based on GOEGCN for control and experiment groups of each subtype explain the specific biological function changes according to the two-side distinction of coexpression network structures to some extent.

Conclusion

The weighted DEGs contain biological importance derived from the gene regulatory network. Based on the weighted DEGs, five binary classifiers were learned and showed good performance concerning the “Sensitivity,” “Specificity,” “Accuracy,” “F1,” and “AUC” metrics. The GOEGCN with weighted DEGs for control and experiment groups presented a novel GO enrichment analysis results and the novel enriched GO terms would further unveil the changes of specific biological functions among all the BRCA subtypes to some extent. The R code in this research is available at https://github.com/yxchspring/GOEGCN_BRCA_Subtypes.

The prognostic significance of ALDH1A1 expression in early invasive breast cancer

AIMS

Aldehyde dehydrogenase family 1 member A1 (ALDH1A1) is reportedly a key ALDH isozyme linked to the cancer stem cells (CSC) of many solid tumours, where it is involved in self-renewal, differentiation and self-protection. In this study, the prognostic significance of ALDH1A1 expression in early invasive breast cancer (BC) and its role as a BC stem cell (BCSC) were evaluated.

METHODS AND RESULTS

ALDH1A1 expression was assessed, using immunohistochemistry and tissue microarrays, in a large well-characterised BC cohort. ALDH1A1 mRNA expression was also assessed at transcriptomic levels, utilising data from the Molecular Taxonomy of Breast Cancer International Consortium. The associations of ALDH1A1 with clinicopathological parameters, other stem cell markers and patient outcomes were determined. ALDH1A1 was expressed in 71% of BC cases at both the protein and mRNA levels. High ALDH1A1 expression was associated with poor prognostic features, including high grade, poor Nottingham Prognostic Index (NPI), lymph node metastasis and highly proliferative ER⁺ (luminal B) and triple-negative (TNBC) subtypes. ALDH1A1 expression was positively correlated with the expression of CD44, CD24, TWIST, SOX9, EPCAM and CD133. The high immunoexpression of ALDH1A1 was significantly associated with poor BC-specific survival (P < 0.001), and specifically in the luminal B and TNBC subtypes (P = 0.042 and P = 0.003, respectively). The immunoexpression of ALDH1A1 was an independent predictor of poor prognosis (P = 0.015).

CONCLUSIONS

ALDH1A1, as assessed using immunohistochemistry, seems to act as a BCSC marker associated not only with other BCSC markers but also with poor prognostic characteristics and poor outcomes, particularly in the luminal B and TNBC subtypes.

Biology of Oestrogen-Receptor Positive Primary Breast Cancer in Older Women with Utilisation of Core Needle Biopsy Samples and Correlation with Clinical Outcome

The majority of biological profiling studies use surgical excision (SE) samples, excluding patients receiving nonsurgical and neoadjuvant therapy. We propose using core needle biopsy (CNB) for biological profiling in older women. Over 37 years (1973–2010), 1 758 older (≥70 years) women with operable primary breast cancer attended a dedicated clinic. Of these, 693 had sufficient quality CNB to construct tissue microarray (TMA). The pattern of biomarkers was analysed in oestrogen receptor (ER)-positive cases, using immunohistochemistry and partitional clustering analysis. The biomarkers measured were: progesterone receptor (PgR), Ki67, Epidermal Growth Factor Receptor (EGFR), Human Epidermal Growth Factor Receptor (HER)-2, HER3, HER4, p53, cytokeratins CK5/6 and CK7/8, Mucin (MUC)1, liver kinase B1 (LKB1), Breast Cancer Associated gene (BRCA) 1, B-Cell Lymphoma (BCL)-2, phosphate and tensin homolog (PTEN), vascular endothelial growth factor (VEGF), and Amplified in breast cancer 1 (AIB1). CNB TMA construction was possible in 536 ER-positive cases. Multivariate analysis showed progesterone receptor (PgR) (p = 0.015), Ki67 (p = 0.001), and mucin (MUC)1 (p = 0.033) as independent predictors for breast-cancer-specific survival (BCSS). Cluster analysis revealed three biological clusters, which were consistent with luminal A, luminal B, and low-ER luminal. The low-ER luminal cluster had lower BCSS compared to luminal A and B. The presence of the low-ER luminal cluster unique to older women, identified in a previous study in SE TMAs in the same cohort, is confirmed. This present study is novel in its use of core needle biopsy tissue microarrays to profile the biology of breast cancer in older women.

Prognostic significance of branched-chain amino acid transferase 1 and CD133 in triple-negative breast cancer

BACKGROUND

Previous studies have shown that branched-chain amino acid transferase 1 (BCAT1) is associated with tumour progression in triple-negative breast cancer (TNBC). Furthermore, CD133 has emerged as a novel cancer stem cell marker for indicating tumour progression. However, the prognostic significance of these two markers remains to be verified. This study was conducted to investigate the correlation between BCAT1 and CD133 expression and clinicopathological features, as well as the prognosis of patients with TNBC.

METHODS

The study cohort included 291 patients with TNBC. Tissue microarrays were constructed for both cancer and normal tissues. The expression of BCAT1 and CD133 was detected by immunohistochemical staining, and the levels were evaluated using an H-scoring system. Cut-off points for BCAT1 and CD133 expression were determined using receiver operating characteristic curves.

RESULTS

The median follow-up time for the study participants was 68.73 months (range: 1.37-103.6 months). The 5-year disease-free survival (DFS) and overall survival (OS) rates of the 291 patients with TNBC were 72.51 and 82.47%, respectively. Higher levels of BCAT1 and CD133 expression independently indicated shorter DFS and OS. High levels of both BCAT1 and CD133 expression were detected in 36 (12.37%) patients, who had significantly shorter DFS and OS (both P < 0.001) compared to other patients.

CONCLUSION

BCAT1 and CD133 can be considered as biomarkers with prognostic significance for TNBC.