Estrogen receptor (ER) mRNA expression and molecular subtype distribution in ER-negative/progesterone receptor-positive breast cancers

Aromatase inhibitors for the treatment of breast cancer: An overview (2019-2023)

Aromatase inhibition is considered a legitimate approach for the treatment of ER-positive (ER+) breast cancer as it accounts for more than 70% of breast cancer cases. Aromatase inhibitor therapy has been demonstrated to be highly effective in decreasing tumour size, increasing survival rates, and lowering the chance of cancer recurrence. The present review deliberates the pathophysiology and the role of aromatase in estrogen biosynthesis. Estrogen biosynthesis, various androgens, and their function in the human body have also been discussed. The salient aspects of the aromatase active site, its mode of action, and AIs, along with their intended interactions with presently FDA-approved inhibitors, have been briefly discussed. It has been detailed how different reported AIs were designed, their SAR investigations, in silico analysis, and biological evaluations. Various AIs from multiple origins, such as synthetic and semi-synthetic, have also been discussed.

GSDME-mediated pyroptosis promotes anti-tumor immunity of neoadjuvant chemotherapy in breast cancer

Paclitaxel and anthracycline-based chemotherapy is one of the standard treatment options for breast cancer. However, only about 6-30% of breast cancer patients achieved a pathological complete response (pCR), and the mechanism responsible for the difference is still unclear. In this study, random forest algorithm was used to screen feature genes, and artificial neural network (ANN) algorithm was used to construct an ANN model for predicting the efficacy of neoadjuvant chemotherapy for breast cancer. Furthermore, digital pathology, cytology, and molecular biology experiments were used to verify the relationship between the efficacy of neoadjuvant chemotherapy and immune ecology. It was found that paclitaxel and doxorubicin, an anthracycline, could induce typical pyroptosis and bubbling in breast cancer cells, accompanied by gasdermin E (GSDME) cleavage. Paclitaxel with LDH release and Annexin V/PI doubule positive cell populations, and accompanied by the increased release of damage-associated molecular patterns, HMGB1 and ATP. Cell coculture experiments also demonstrated enhanced phagocytosis of macrophages and increased the levels of IFN-γ and IL-2 secretion after paclitaxel treatment. Mechanistically, GSDME may mediate paclitaxel and doxorubicin-induced pyroptosis in breast cancer cells through the caspase-9/caspase-3 pathway, activate anti-tumor immunity, and promote the efficacy of paclitaxel and anthracycline-based neoadjuvant chemotherapy. This study has practical guiding significance for the precision treatment of breast cancer, and can also provide ideas for understanding molecular mechanisms related to the chemotherapy sensitivity.

Novel markers of MCL1 inhibitor sensitivity in triple-negative breast cancer cells

Triple-negative breast cancer (TNBC) is an aggressive breast cancer sub-type with limited treatment options and poor prognosis. Currently, standard treatments for TNBC include surgery, chemotherapy, and anti-PDL1 therapy. These therapies have limited efficacy in advanced stages. Myeloid-cell leukemia 1 (MCL1) is an anti-apoptotic BCL2 family protein. High expression of MCL1 contributes to chemotherapy resistance and is associated with a worse prognosis in TNBC. MCL1 inhibitors are in clinical trials for TNBC, but response rates to these inhibitors can vary and predictive markers are lacking. Currently, we identified a 4-member (AXL, ETS1, IL6, EFEMP1) gene signature (GS) that predicts MCL1 inhibitor sensitivity in TNBC cells. Factors encoded by these genes regulate signaling pathways to promote MCL1 inhibitor resistance. Small molecule inhibitors of the GS factors can overcome resistance and sensitize otherwise resistant TNBC cells to MCL1 inhibitor treatment. These findings offer insights into potential therapeutic strategies and tumor stratification for MCL1 inhibitor use in TNBC.

An analysis of the prognostic role of reactive oxygen species-associated genes in breast cancer

BACKGROUND

This study aimed to type breast cancer in relation to reactive oxygen species (ROS), clinical indicators, single nucleotide variant (SNV) mutations, functional differences, immune infiltration, and predictive responses to immunotherapy or chemotherapy, and constructing a prognostic model.

METHODS

We used uniCox analysis, ConsensusClusterPlus, and the proportion of ambiguous clustering (PAC) to analyze The Cancer Genome Atlas (TCGA) data to determine optimal groupings and obtain differentially expressed ROS-related genes. Clinical indicators were then combined with the classification results and the Chi-square test was used to assess differences. We further examined SNV mutations, and functional differences using gene set enrichment analysis (GSEA) analysis, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, immune cell infiltration, and response to immunotherapy and chemotherapy. A prognostic model for breast cancer was constructed using these differentially expressed genes, immunotherapy or chemotherapy responses, and survival curves. RT-qPCR was used to detect the differences in the expression of LCE3D, CA1, PIRT and SMR3A in breast cancer cell lines and normal breast epithelial cell line.

RESULTS

We identified two distinct tumor types with significant differences in ROS-related gene expression, clinical indicators, SNV mutations, functional pathways, and immune infiltration. The response to specific chemotherapy drugs and immunotherapy treatments also documented significant differences. The prognostic model constructed with 16 genes linked to survival could efficiently divide patients into high- and low-risk groups. The high-risk group showed a poorer prognosis, higher tumor purity, distinct immune microenvironment, and lower immunotherapy response. RT-qPCR results showed that LCE3D, CA1, PIRT and SMR3A are highly expressed in breast cancer.

CONCLUSION

Our methodical examination presented an enhanced insight into the molecular and immunological heterogeneity of breast cancer. It can contribute to the understanding of prognosis and offer valuable insights for personalized treatment strategies. Further, the prognostic model can potentially serve as a powerful tool for risk stratification and therapeutic decision-making in clinical settings.

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.

The Biological Significance of AFF4: Promoting Transcription Elongation, Osteogenic Differentiation and Tumor Progression

As a member of the AF4/FMR2 (AFF) family, AFF4 is a scaffold protein in the superelongation complex (SEC). In this mini-view, we discuss the role of AFF4 as a transcription elongation factor that mediates HIV activation and replication and stem cell osteogenic differentiation. AFF4 also promotes the progression of head and neck squamous cell carcinoma, leukemia, breast cancer, bladder cancer and other malignant tumors. The biological function of AFF4 is largely achieved through SEC assembly, regulates SRY-box transcription factor 2 (SOX2), MYC, estrogen receptor alpha (ESR1), inhibitor of differentiation 1 (ID1), c-Jun and noncanonical nuclear factor-κB (NF-κB) transcription and combines with fusion in sarcoma (FUS), unique regulatory cyclins (CycT1), or mixed lineage leukemia (MLL). We explore the prospects of using AFF4 as a therapeutic in Acquired immunodeficiency syndrome (AIDS) and malignant tumors and its potential as a stemness regulator.

Transcriptomic correlates of cell cycle checkpoints with distinct prognosis, molecular characteristics, immunological regulation, and therapeutic response in colorectal adenocarcinoma

Backgrounds

Colorectal adenocarcinoma (COAD), accounting for the most common subtype of colorectal cancer (CRC), is a kind of malignant digestive tumor. Some cell cycle checkpoints (CCCs) have been found to contribute to CRC progression, whereas the functional roles of a lot of CCCs, especially the integrated role of checkpoint mechanism in the cell cycle, remain unclear.

Materials and methods

The Genomic Data Commons (GDC) The Cancer Genome Atlas (TCGA) COAD cohort was retrieved as the training dataset, and GSE24551 and GSE29623 were downloaded from Gene Expression Omnibus (GEO) as the validation datasets. A total of 209 CCC-related genes were derived from the Gene Ontology Consortium and were subsequently enrolled in the univariate, multivariate, and least absolute shrinkage and selection operator (LASSO) Cox regression analyses, finally defining a CCC signature. Cell proliferation and Transwell assay analyses were utilized to evaluate the functional roles of signature-related CCCs. The underlying CCC signature, molecular characteristics, immune-related features, and therapeutic response were finally estimated. The Genomics of Drug Sensitivity in Cancer (GDSC) database was employed for the evaluation of chemotherapeutic responses.

Results

The aberrant gene expression of CCCs greatly contributed to COAD development and progression. Univariate Cox regression analysis identified 27 CCC-related genes significantly affecting the overall survival (OS) of COAD patients; subsequently, LASSO analysis determined a novel CCC signature. Noticeably, CDK5RAP2, MAD1L1, NBN, RGCC, and ZNF207 were first identified to be correlated with the prognosis of COAD, and it was proven that all of them were significantly correlated with the proliferation and invasion of HCT116 and SW480 cells. In TCGA COAD cohort, CCC signature robustly stratified COAD patients into high and low CCC score groups (median OS: 57.24 months vs. unreached, p< 0.0001), simultaneously, with the good AUC values for OS prediction at 1, 2, and 3 years were 0.74, 0.78, and 0.77. Furthermore, the prognostic capacity of the CCC signature was verified in the GSE24551 and GSE29623 datasets, and the CCC signature was independent of clinical features. Moreover, a higher CCC score always indicated worse OS, regardless of clinical features, histological subtypes, or molecular subgroups. Intriguingly, functional enrichment analysis confirmed the CCC score was markedly associated with extracellular, matrix and immune (chemokine)-related signaling, cell cycle-related signaling, and metabolisms. Impressively, a higher CCC score was positively correlated with a majority of chemokines, receptors, immunostimulators, and anticancer immunity, indicating a relatively immune-promoting microenvironment. In addition, GSE173839, GSE25066, GSE41998, and GSE194040 dataset analyses of the underlying CCC signature suggested that durvalumab with olaparib and paclitaxel, taxane-anthracycline chemotherapy, neoadjuvant cyclophosphamide/doxorubicin with ixabepilone or paclitaxel, and immunotherapeutic strategies might be suitable for COAD patients with higher CCC score. Eventually, the GDSC database analysis showed that lower CCC scores were likely to be more sensitive to 5-fluorouracil, bosutinib, gemcitabine, gefitinib, methotrexate, mitomycin C, and temozolomide, while patients with higher CCC score seemed to have a higher level of sensitivity to bortezomib and elesclomol.

Conclusion

The novel CCC signature exhibited a good ability for prognosis prediction for COAD patients, and the CCC score was found to be highly correlated with molecular features, immune-related characteristics, and therapeutic responses, which would greatly promote clinical management and precision medicine for COAD.

PTCH1 and CTNNB1 emerge as pivotal predictors of resistance to neoadjuvant chemotherapy in ER+/HER2- breast cancer

Introduction

Endeavors in the molecular characterization of breast cancer opened the doors to endocrine therapies in ER+/HER2- breast cancer, increasing response rates substantially. Despite that, taxane-based neoadjuvant chemotherapy is still a cornerstone for achieving breast-conserving surgery and complete tumor resection in locally advanced cancers with high recurrence risk. Nonetheless, the rate of chemoresistance is high, and deselecting patients who will not benefit from chemotherapy is a significant task to prevent futile toxicities. Several multigene assays are being used to guide decisions on chemotherapy. However, their development as prognostic assays but not predictive assays limits predictive strength, leading to discordant results. Moreover, high costs impediment their use in developing countries. For global health equity, robust predictors that can be cost-effectively incorporated into routine clinical management are essential.

Methods

In this study, we comprehensively analyzed 5 GEO datasets, 2 validation sets, and The Cancer Genome Atlas breast cancer data to identify predictors of resistance to taxane-based neoadjuvant therapy in ER+/HER2- breast cancer using efficient bioinformatics algorithms.

Results

Gene expression and gene set enrichment analysis of 5 GEO datasets revealed the upregulation of 63 genes and the enrichment of CTNNB1-related oncogenic signatures in non-responsive patients. We validated the upregulation and predictive strength of 18 genes associated with resistance in the validation cohort, all exhibiting higher predictive powers for residual disease and higher specificities for ER+/HER2- breast cancers compared to one of the benchmark multi-gene assays. Cox Proportional Hazards Regression in three different treatment arms (neoadjuvant chemotherapy, endocrine therapy, and no systemic treatment) in a second comprehensive validation cohort strengthened the significance of PTCH1 and CTNNB1 as key predictors, with hazard ratios over 1.5, and 1.6 respectively in the univariate and multivariate models.

Discussion

Our results strongly suggest that PTCH1 and CTNNB1 can be used as robust and cost-effective predictors in developing countries to guide decisions on chemotherapy in ER +/HER2- breast cancer patients with a high risk of recurrence. The dual function of PTCH1 as a multidrug efflux pump and a hedgehog receptor, and the active involvement of CTNNB1 in breast cancer strongly indicate that PTCH1 and CTNNB1 can be potential drug targets to overcome chemoresistance in ER +/HER2- breast cancer patients.

Identification of cell subpopulations associated with disease phenotypes from scRNA-seq data using PACSI

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) has revolutionized the transcriptomics field by advancing analyses from tissue-level to cell-level resolution. Despite the great advances in the development of computational methods for various steps of scRNA-seq analyses, one major bottleneck of the existing technologies remains in identifying the molecular relationship between disease phenotype and cell subpopulations, where "disease phenotype" refers to the clinical characteristics of each patient sample, and subpopulation refer to groups of single cells, which often do not correspond to clusters identified by standard single-cell clustering analysis. Here, we present PACSI, a method aimed at distinguishing cell subpopulations associated with disease phenotypes at the single-cell level.

RESULTS

PACSI takes advantage of the topological properties of biological networks to introduce a proximity-based measure that quantifies the correlation between each cell and the disease phenotype of interest. Applied to simulated data and four case studies, PACSI accurately identified cells associated with disease phenotypes such as diagnosis, prognosis, and response to immunotherapy. In addition, we demonstrated that PACSI can also be applied to spatial transcriptomics data and successfully label spots that are associated with poor survival of breast carcinoma.

CONCLUSIONS

PACSI is an efficient method to identify cell subpopulations associated with disease phenotypes. Our research shows that it has a broad range of applications in revealing mechanistic and clinical insights of diseases.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Selective Estrogen receptor degraders (SERDs) for the treatment of breast cancer: An overview

Discovery of SERDs has changed the direction of anticancer research, as more than 70% of breast cancer cases are estrogen receptor positive (ER+). Therapies such as selective estrogen receptor modulators (SERM) and aromatase inhibitors (AI's) have been effective, but due to endocrine resistance, SERDs are now considered essential therapeutics for the treatment of ER+ breast cancer. The present review deliberates the pathophysiology of SERDs from the literature covering various molecules in clinical trials. Estrogen receptors active sites distinguishing characteristics and interactions with currently available FDA-approved drugs have also been discussed. Designing strategy of previously reported SERDs, their SAR analysis, in silico, and the biological efficacy have also been summarized along with appropriate examples.

Single progesterone receptor-positive phenotype has the similar clinicopathological features and outcome as triple-negative subtype in metastatic breast cancer

Objective

The same clinicopathological features and prognosis have been reported between single progesterone receptor-positive (sPR-positive) and triple-negative phenotype in early-stage breast cancer, but such similarity has not been studied in metastatic breast cancer (MBC). Therefore, the purpose of this study was to estimate the difference between sPR-positive phenotype and other phenotypes in MBC.

Methods

Patients with HER-2-negative MBC were selected from the Surveillance, Epidemiology and End Results database. Pearson's χ2 test was used to compare the difference of clinicopathologic factors between sPR-positive phenotype and other phenotypes. Univariate and multivariate analyses were performed to evaluate the effects of hormone receptor (HoR) phenotypes and other clinicopathologic factors on the cancer-specific survival (CSS) and overall survival (OS).

Results

Overall, 10877 patients including 7060 patients (64.9%) with double HoR-positive (dHoR-positive), 1533 patients (14.1%) with single estrogen receptor-positive (sER-positive), 126 patients (1.2%) with sPR-positive and 2158 patients (19.8%) with double HoR-negative (dHoR-negative) were analyzed. The patients with sPR-positive or dHoR-negative were more likely to be younger, higher grade and tumor stage, visceral and brain metastasis than ER-positive phenotypes (P<0.001). MBC with sPR-positive had the similar CSS (HR: 1.135, 95%CI: 0.909-1.417, P=2.623) and OS (HR: 1.141, 95%CI: 0.921-1.413, P=0.229) as dHoR-negative, but worse outcome than ER-positive phenotypes. Chemotherapy significantly improved the survival for MBC, especially for sPR-positive MBC (CSS, HR: 0.39, 95%CI: 0.213-0.714, P=0.002; OS, HR: 0.366, 95%CI: 0.203-0.662, P=0.001).

Conclusions

Patients with sPR-positive and triple-negative have similar biological behavior and prognosis in MBC. Chemotherapy may be a preferred recommendation for MBC with sPR-positive.

Prolylcarboxypeptidase promotes IGF1R/HER3 signaling and is a potential target to improve endocrine therapy response in estrogen receptor positive breast cancer

Prolylcarboxypeptidase (PRCP) is a lysosomal serine protease that cleaves peptide substrates when the penultimate amino acid is proline. Previous studies have linked PRCP to blood-pressure and appetite control through its ability to cleave peptide substrates such as angiotensin II and α-MSH. A potential role for PRCP in cancer has to date not been widely appreciated. Endocrine therapy resistance in breast cancer is an enduring clinical problem mediated in part by aberrant receptor tyrosine kinase (RTK) signaling. We previously found PRCP overexpression promoted 4-hydroxytamoxifen (4-OHT) resistance in estrogen receptor-positive (ER+) breast cancer cells. Currently, we tested the potential association between PRCP with breast cancer patient outcome and RTK signaling, and tumor responsiveness to endocrine therapy. We found high PRCP protein levels in ER+ breast tumors associates with worse outcome and earlier recurrence in breast cancer patients, including patients treated with TAM. We found a PRCP specific inhibitor (PRCPi) enhanced the response of ER+ PDX tumors and MCF7 tumors to endoxifen, an active metabolite of TAM in mice. We found PRCP increased IGF1R/HER3 signaling and AKT activation in ER+ breast cancer cells that was blocked by PRCPi. Thus, PRCP is an adverse prognostic marker in breast cancer and a potential target to improve endocrine therapy in ER+ breast cancers.

Translocon-associated protein subunit SSR3 determines and predicts susceptibility to paclitaxel in breast cancer and glioblastoma

PURPOSE

Paclitaxel (PTX) is one the most potent and commonly used chemotherapies for breast and pancreatic cancer. Several ongoing clinical trials are investigating means of enhancing delivery of PTX across the blood-brain barrier for glioblastomas (GBMs). Despite the widespread use of PTX for breast cancer, and the initiative to repurpose this drug for gliomas, there are no predictive biomarkers to inform which patients will likely benefit from this therapy.

EXPERIMENTAL DESIGN

To identify predictive biomarkers for susceptibility to PTX, we performed a genome-wide CRISPR knock-out (KO) screen using human glioma cells. The genes whose KO was most enriched in the CRISPR screen underwent further selection based on their correlation with survival in the breast cancer patient cohorts treated with PTX and not in patients treated with other chemotherapies, a finding that was validated on a second independent patient cohort using progression-free survival.

RESULTS

Combination of CRISPR screen results with outcomes from taxane-treated breast cancer patients led to the discovery of endoplasmic reticulum (ER) protein SSR3 as a putative predictive biomarker for PTX. SSR3 protein levels showed positive correlation with susceptibility to PTX in breast cancer cells, glioma cells and in multiple intracranial glioma xenografts models. Knockout of SSR3 turned the cells resistant to PTX while its overexpression sensitized the cells to PTX. Mechanistically, SSR3 confers susceptibility to PTX through regulation of phosphorylation of ER stress sensor IRE1α.

CONCLUSION

Our hypothesis generating study showed SSR3 as a putative biomarker for susceptibility to PTX, warranting its prospective clinical validation.

High RAD51 gene expression is associated with aggressive biology and with poor survival in breast cancer

PURPOSE

Although the DNA repair mechanism is important in preventing carcinogenesis, its activation in established cancer cells may support their proliferation and aggravate cancer progression. RAD51 cooperates with BRCA2 and is essential in the homologous recombination of DNA repair. To this end, we hypothesized that RAD51 gene expression is associated with cancer cell proliferation and poor prognosis of breast cancer (BC) patients.

METHODS

A total of 8515 primary BC patients with transcriptome and clinical data from 17 independent cohorts were analyzed. The median value was used to divide each cohort into high and low RAD51 expression groups.

RESULTS

High RAD51 expression enriched the DNA repair gene set and was correlated with DNA repair-related genes. Nottingham histological grade, Ki67 expression and cell proliferation-related gene sets (E2F Targets, G2M Checkpoint and Myc Targets) were all significantly associated with the high RAD51 BC group. RAD51 expression was positively correlated with Homologous Recombination Deficiency, as well as both mutational burden and neoantigens that accompanied a higher infiltration of immune cells. Primary BC with lymph node metastases was associated with high expression of RAD51 in two cohorts. There was no strong correlation between RAD51 expression and drug sensitivity in cell lines, and RAD51 expression was lower after the neoadjuvant chemotherapy compared to before the treatment. High RAD51 BC was associated with poor prognosis consistently in three independent cohorts.

CONCLUSION

RAD51 gene expression is associated with aggressive cancer biology, cancer cell proliferation, and poor survival in breast cancer.

The high methylation level of a novel 151-bp CpG island in the ESR1 gene promoter is associated with a poor breast cancer prognosis

BACKGROUND

The ESR1 gene suffers methylation changes in many types of cancers, including breast cancer (BC), the most frequently diagnosed cancer in women that is also present in men. Methylation at promoter A of ESR1 is the worse prognosis in terms of overall survival; thus, the early detection, prognostic, and prediction of therapy involve some methylation biomarkers.

METHODS

Therefore, our study aimed to examine the methylation levels at the ESR1 gene in samples from Mexican BC patients and its possible association with menopausal status.

RESULTS

We identified a novel 151-bp CpG island in the promoter A of the ESR1 gene. Interestingly, methylation levels at this CpG island in positive ERα tumors were approximately 50% less than negative ERα or control samples. Furthermore, methylation levels at ESR1 were associated with menopausal status. In postmenopausal patients, the methylation levels were 1.5-fold higher than in premenopausal patients. Finally, according to tumor malignancy, triple-negative cancer subtypes had higher ESR1 methylation levels than luminal/HER2+ or luminal A subtypes.

CONCLUSIONS

Our findings suggest that methylation at this novel CpG island might be a promising prognosis marker.

Is oestrogen receptor-negative/progesterone receptor-positive (ER-/PR+) a real pathological entity?

Background

The existence of oestrogen receptor-negative (ER−)/progesterone receptor-positive (PR+) breast cancer continues to be an area of controversy amongst oncologists and pathologists.

Methods

To re-evaluate breast cancers originally classified as ER−/PR+ via Oncotype DX® assay and compare molecular phenotype with Recurrence Score® (RS) result, clinicopathologic features and clinical outcomes were retrospectively obtained from electronic health records between January 1998 and June 2005. Archived formalin-fixed, paraffin-embedded (FFPE) tumour specimens were tested for the expression of ER, PR and human-epidermal-growth-factor-2. The number of positive ER−/PR+ samples confirmed by transcriptional analysis was the primary outcome of interest with event-free and overall survival as secondary outcomes. Biopsies from 26 patients underwent Oncotype DX testing and analysis.

Results

Approximately 60% were middle-aged (40–50 years old) women, and 84.6% had invasive ductal carcinoma. Based on the Oncotype DX assay, approximately 65% (N = 17) had ER+/PR+ status; 23% (N = 6) had ER−/PR− status; and 12% had a single hormone positive receptor (1 ER–/PR+, 2 ER+/PR–) status. Almost one-quarter of patients were stratified into the low-RS (<18) or intermediate-RS (18–30) results, and half of the patients had a high-RS (>30) result.

Conclusion

Our findings suggest the ER−/PR+ subtype is not a reproducible entity and emphasises the value of retesting this subtype via molecular methods for appropriate treatment selection and patient outcomes. Multigene assay analysis may serve as a second-line or confirming tool for clinical determination of ER/PR phenotype in breast cancer patients for targeted therapies.

Immunohistochemical and clinicopathologic features of estrogen receptor-negative, progesterone receptor-positive, HER-2 negative breast carcinomas

OBJECTIVE

Currently, there is an ongoing debate whether progesterone receptor positive and estrogen receptor negative breast carcinomas represent a true distinct subtype of tumor or a mere immunohistochemical artifact. In this study, we conducted an immunohistochemistry panel with the antibodies TFF1, EGFR, and CK5 to reclassify this phenotype in a luminal or basal-like subtype.

METHODS

Tumors estrogen receptor -/progesterone receptor +, Her-2 - from a large population of breast cancer patients were selected to be studied. Immunohistochemistry with the antibodies TFF1, EGFR, and CK5 was performed. Tumors showing positivity for TFF1, regardless of EGFR and CK5 results, were classified as luminal-like carcinomas. Those lesions that were negative for TFF1, but were positive for EGFR and/or CK5, were classified as basal-like triple-negative carcinomas. When the three markers were negative, tumors were classified as undetermined. Clinical pathologic characteristics of patients and tumor recurrence were evaluated.

RESULTS

Out of 1188 breast carcinomas investigated, 30 cases (2.5%) presented the estrogen receptor -/progesterone receptor +/HER2- phenotype. Of them, 27 tumors (90%) were classified as basal-like triple-negative carcinomas, one as luminal-like (3.3%), and two as undetermined tumors (6.7%). The mean follow-up for the study group was 27.7 (2.7 to 50) months. Out of the 26 patients, 6 had cancer recurrence: 2 local and 4 systemic recurrences. The average time for recurrence was 17 (8 to 38) months.

CONCLUSION

Estrogen receptor -/progesterone receptor +/tumors exhibit aggressive behavior, similar to triple-negative tumors. An appropriate categorization of these tumors should be made to improve their therapeutic management.

Clinical features of patients with HER2-positive breast cancer and development of a nomogram for predicting survival

Background

Different estrogen receptor (ER) and progesterone receptor (PR) expression patterns have important biological and therapeutic implications in patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer. However, little is known about hormone receptor (HR)-positive and triple-positive subtypes, making therapy selection and survival prognosis difficult. This study investigated the clinical characteristics and nomogram-predicted survival of patients with HER2-positive breast cancer.

Materials and methods

Data on patients with HER2-positive breast cancer were retrieved from the Surveillance, Epidemiology, and End Results database. Comparisons were carried out between single HR-positive and double HR-positive/double HR-negative subtypes. A nomogram-based model of predicted outcomes was developed.

Results

This cohort study included 34 819 patients with breast cancer (34 606 women and 213 men). Single HR-positive and double HR-positive/double HR-negative subtypes showed distinct clinicopathological characteristics. Multivariable Cox regression analysis showed that patients with ER-positive/PR-negative/HER2-positive [hazard ratio (HR) = 1.24; 95% confidence interval (CI): 1.14-1.39], ER-negative/PR-positive/HER2-positive (HR = 1.56; 95% CI: 1.23-1.97), and ER-negative/PR-negative/HER2-positive (HR = 1.56; 95% CI: 1.43-1.70) subtypes had worse breast cancer-specific survival than patients with the triple-positive subtype. Thirteen clinical parameters were included as prognostic factors in the nomogram: age, sex, race, grade, histology type, bone, brain, liver, and lung metastasis, TNM (tumor–node–metastasis) staging, and molecular subtype. The C-index was 0.853 (95% CI: 0.845-0.861). Calibration plots indicated that the nomogram-predicted survival was consistent with the recorded 3-year and 5-year prognoses.

Conclusions

Significant differences in survival rates were observed between single HR-positive and double HR-positive/double HR-negative subtypes. A nomogram accurately predicted survival. Different treatment strategies may be required for HER2-positive patients with single HR-positive and double HR-positive tumors to ensure optimal treatment and benefits.

•

Significant differences in survival were observed in single HR-positive and double HR-positive/double HR-negative subtypes.

•

A nomogram based on molecular subtypes of HER2-positive breast cancer accurately predicted breast cancer-specific survival.

•

Different treatment strategies may be required for HER2-positive breast cancer to ensure optimal treatment and benefits.

Molybdenum Target X-Ray Features and Estrogen Receptor, Progesterone Receptor, and Human Epidermal Growth Factor Receptor 2 in Invasive Breast Cancer

Objective

The aim of this study was to investigate the correlations between molybdenum target X-ray mammography features and the expressions of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) in invasive breast cancer (IBC) and their clinical significance.

Methods

The correlations between the mammographic features and expressions of ER, PR, and HER2 in 378 cases of IBC confirmed by pathology were analyzed retrospectively.

Results

The differences in the ER, PR, and HER2 positive expression between gland types were statistically significant (P < 0.05). The expression of ER was positively correlated with the presence of nipple depression (P < 0.05). Moreover, ER and PR expressions were positively correlated with the absence of axillary lymph node enlargement (P < 0.05) and negatively correlated with the maximum tumor diameter (P < 0.05).

Conclusion

The mammographic features of IBC are correlated with the expression of immunity indices ER, PR, and HER2 and reflect several pathological features.

Enhanced Thermogenesis in Triple-Negative Breast Cancer Is Associated with Pro-Tumor Immune Microenvironment

Mild cold stress induced by housing mice with a 4T1 triple-negative breast cancer (TNBC) cell implantation model at 22 °C increases tumor growth rate with a pro-tumorigenic immune microenvironment (lower CD8 +T cells, higher myeloid-derived suppressor cells (MDSCs) and regulatory T-cells (Tregs)). Since cold stress also activates thermogenesis, we hypothesized that enhanced thermogenesis is associated with more aggressive cancer biology and unfavorable tumor microenvironment (TME) in TNBC patients. A total of 6479 breast cancer patients from METABRIC, TCGA, GSE96058, GSE20194, and GSE25066 cohorts were analyzed using Kyoto Encyclopedia of Genes and Genomes (KEGG) thermogenesis score. High-thermogenesis TNBC was associated with a trend towards worse survival and with angiogenesis, adipogenesis, and fatty acid metabolism pathways. On the other hand, low-thermogenesis TNBC enriched most of the hallmark cell-proliferation-related gene sets (i.e., mitotic spindle, E2F targets, G2M checkpoint, MYC targets), as well as immune-related gene sets (i.e., IFN-α and IFN-γ response). Favorable cytotoxic T-cell-attracting chemokines CCL5, CXCL9, CXCL10, and CXCL11 were lower; while the MDSC- and Treg-attracting chemokine CXCL12 was higher. There were higher M2 but lower M1 macrophages and Tregs. In conclusion, high-thermogenesis TNBC is associated with pro-tumor immune microenvironment and may serve as biomarker for testing strategies to overcome this immunosuppression.

MHC Class I Loss in Triple-negative Breast Cancer: A Potential Barrier to PD-1/PD-L1 Checkpoint Inhibitors

Suppression of the immune system is intimately linked to the development and progression of malignancy, and immune modulating treatment options have shown promise in a variety of tumor types, including some triple-negative breast cancers (TNBC). The most dramatic therapeutic success has been seen with immune checkpoint inhibitors targeting programmed cell death protein 1 (PD-1) and its ligand, PD-L1. Difficulty remains, however, in appropriate patient selection for treatment, as many PD-L1-positive cancers fail to show durable responses to PD-1/PD-L1 inhibition. Checkpoint inhibitor targeting of the adaptive immune response relies on the presence of major histocompatibility complex (MHC) class I molecules on the tumor cell surface for tumor antigen presentation. MHC class I loss has been previously described in breast cancer and represents a putative mechanism of immunotherapeutic resistance in this tumor type. One hundred seventeen invasive primary breast carcinomas with a range of histologic subtypes were evaluated on tissue microarrays containing formalin-fixed paraffin-embedded tissue. Loss of MHC class I expression was common among breast cancers, with greater than half of cases demonstrating either subclonal or diffuse loss. Fifty-nine percent of TNBC demonstrated loss of MHC class I, including 46% of those meeting the Food and Drug Administration-approved threshold of 1% for tumor-associated immune cell PD-L1 expression. MHC class I loss was particularly common in the apocrine subtype of TNBC (78%). MHC class I's employment as a predictive biomarker should be considered, as its loss may represent a barrier to successful enhancement of the antitumor adaptive immune response by PD-1/PD-L1 inhibition.

Single Hormone Receptor-Positive Metaplastic Breast Cancer: Similar Outcome as Triple-Negative Subtype

Background

Metaplastic breast cancer (MBC) is a rare and aggressive subtype of the breast. To understand the characteristics and prognosis of single hormone receptor-positive (HR+) MBC (estrogen receptor-positive [ER+]/progesterone receptor-negative [PR-] and ER-/PR+), we compared these tumors to double HR+ tumors as well as HR- tumors.

Patients and Methods

The Surveillance, Epidemiology, and End Results database was used to analyze MBC between 1975 and 2016. The effect of HR status was evaluated using a multivariate Cox regression model.

Results

We included 3369 patients with a median follow-up time of 42 months (range 0-322 months). In this study, 280 (8.3%) cases were double HR+ tumors, 2597 (77.1%) were double HR- tumors, and 492 (14.6%) cases were single HR+ tumors, of which 159 (4.7%) cases were ER-/PR+ tumors and 333 (9.9%) were ER+/PR- tumors. On multivariate Cox analysis, the prognosis was related to age, race/ethnicity, tumor grade, TNM stage, and surgery. HR status remained no impact on breast cancer-specific survival (BCSS). In the Kaplan-Meier curve, HR status was not associated with better BCSS or overall survival (OS). In patients without HER2 overexpression, the BCSS and OS of ER+/PR- and ER-/PR+ tumors were not significantly different from that of ER-/PR- and ER+/PR+ tumors. The difference remains no significant in patients with HER2 overexpression.

Conclusions

In comparison with both ER-/PR- and ER+/PR+ tumors, we have identified clinically and biologically distinct features of single HR+ tumors. In patients with or without HER2 overexpression, the prognosis of single HR+ tumors was similar to ER-/PR- and ER+/PR+ tumors.

High expression levels of centromere protein A plus upregulation of the phosphatidylinositol 3-kinase/Akt/mammalian target of rapamycin signaling pathway affect chemotherapy response and prognosis in patients with breast cancer

Centromere proteins (CENPs) are involved in mitosis, and CENP gene expression levels are associated with chemotherapy responses in patients with breast cancer. The present study aimed to examine the roles and underlying mechanisms of the effects of CENP genes on chemotherapy responses and breast cancer prognosis. Using data obtained from the Gene Expression Omnibus (GEO) database, correlation and Cox multivariate regression analyses were used to determine the CENP genes associated with chemotherapy responses and survival in patients with breast cancer. Weighted gene co-expression network and correlation analyses were used to determine the gene modules co-expressed with the identified genes and the differential expression of gene modules associated with the pathological complete response (PCR) and residual disease (RD) subgroups. CENPA, CENPE, CENPF, CENPI, CENPJ and CENPN were associated with a high nuclear grade and low estrogen and progesterone receptor expression levels. In addition, CENPA, CENPB, CENPC and CENPO were independent factors affecting the distant relapse-free survival (DRFS) rates in patients with breast cancer. Patients with high expression levels of CENPA or CENPO exhibited poor prognoses, whereas those with high expression levels of CENPB or CENPC presented with favorable prognoses. For validation between databases, the Cancer Genome Atlas (TCGA) database analysis also revealed that CENPA, CENPB and CENPO exerted similar effects on overall survival. However, according to the multivariate analyses, only CENPA was an independent risk factor associated with DRFS in GEO database. In addition, in the RD subgroup, patients with higher CENPA expression levels had a worse prognosis compared with those with lower CENPA expression levels. Among patients with high expression levels of CENPA, the PI3K/Akt/mTOR pathway was more likely to be activated in the RD compared with the PCR subgroup. The same trend was observed in TCGA data. These results suggested that high CENPA expression levels plus upregulation of the PI3K/Akt/mTOR signaling pathway may affect DRFS in patients with breast cancer.

Systems Medicine Design for Triple-Negative Breast Cancer and Non-Triple-Negative Breast Cancer Based on Systems Identification and Carcinogenic Mechanisms

Triple-negative breast cancer (TNBC) is a heterogeneous subtype of breast cancers with poor prognosis. The etiology of triple-negative breast cancer (TNBC) is involved in various biological signal cascades and multifactorial aberrations of genetic, epigenetic and microenvironment. New therapeutic for TNBC is urgently needed because surgery and chemotherapy are the only available modalities nowadays. A better understanding of the molecular mechanisms would be a great challenge because they are triggered by cascade signaling pathways, genetic and epigenetic regulations, and drug–target interactions. This would allow the design of multi-molecule drugs for the TNBC and non-TNBC. In this study, in terms of systems biology approaches, we proposed a systematic procedure for systems medicine design toward TNBC and non-TNBC. For systems biology approaches, we constructed a candidate genome-wide genetic and epigenetic network (GWGEN) by big databases mining and identified real GWGENs of TNBC and non-TNBC assisting with corresponding microarray data by system identification and model order selection methods. After that, we applied the principal network projection (PNP) approach to obtain the core signaling pathways denoted by KEGG pathway of TNBC and non-TNBC. Comparing core signaling pathways of TNBC and non-TNBC, essential carcinogenic biomarkers resulting in multiple cellular dysfunctions including cell proliferation, autophagy, immune response, apoptosis, metastasis, angiogenesis, epithelial-mesenchymal transition (EMT), and cell differentiation could be found. In order to propose potential candidate drugs for the selected biomarkers, we designed filters considering toxicity and regulation ability. With the proposed systematic procedure, we not only shed a light on the differences between carcinogenetic molecular mechanisms of TNBC and non-TNBC but also efficiently proposed candidate multi-molecule drugs including resveratrol, sirolimus, and prednisolone for TNBC and resveratrol, sirolimus, carbamazepine, and verapamil for non-TNBC.

Progesterone Receptor Signaling in the Breast Tumor Microenvironment

The tumor microenvironment (TME) is a complex infrastructure composed of stromal, epithelial, and immune cells embedded in a vasculature ECM. The microenvironment surrounding mammary epithelium plays a critical role during the development and differentiation of the mammary gland, enabling the coordination of the complex multihormones and growth factor signaling processes. Progesterone/progesterone receptor paracrine signaling interactions in the microenvironment play vital roles in stem/progenitor cell function during normal breast development. In breast cancer, the female sex hormones, estrogen and progesterone, and growth factor signals are altered in the TME. Progesterone signaling modulates not only breast tumors but also the breast TME, leading to the activation of a series of cross-communications that are implicated in the genesis of breast cancers. This chapter reviews the evidence that progesterone and PR signaling modulates not only breast epitheliums but also the breast TME. Furthermore, crosstalk between estrogen and progesterone signaling affecting different cell types within the TME is discussed. A better understanding of how PR and progesterone affect the TME of breast cancer may lead to novel drugs or a therapeutic approach for the treatment of breast cancer shortly.

Inflammation Is Associated with Worse Outcome in the Whole Cohort but with Better Outcome in Triple-Negative Subtype of Breast Cancer Patients

Inflammation has been linked with cancer, but whether it is part of the problem or part of the solution remains to be a matter of debate in breast cancer. Our group and others have demonstrated that inflammation aggravates cancer progression; however, some claim that inflammation may support immune cell infiltration and suppress cancer. We defined the gene set variation analysis of the Molecular Signatures Database Hallmark inflammatory response gene set as the inflammatory pathway score and analyzed 3632 tumors in total from 4 breast cancer cohorts (METABRIC, TCGA, GSE25066, and GSE21094). In the whole breast cancer cohort, high-score tumors were associated with aggressive clinical characteristics, such as worse disease specific survival, higher Nottingham histological grade, and younger age. Inflammatory score was significantly higher in triple-negative (TNBC) as well as basal and normal subtypes compared with the other subtypes, which suggest that the detrimental effect of high level of inflammation may be because it includes a more aggressive subtype. On the contrary, high score within TNBC was significantly associated with better survival. TNBC with high score enriched not only IFN-α, IFN-γ response, IL-2/STAT5 signaling, Allograft rejection, Complement, p53 pathway, Reactive Oxygen, and Apoptosis but also TNF-α signaling, IL6-JAK-STAT signaling, TGF-β signaling, Coagulation, Angiogenesis, EMT, KRAS signaling, and PI3K-AKT-MTOR signaling gene sets. High score was associated with mainly favorable anticancerous immune cell infiltration as well as Leukocyte fraction, TIL regional fraction, Lymphocyte infiltration, IFN-γ response, TGF-β response, and cytolytic activity scores. Although the inflammatory pathway score was not associated with neoadjuvant treatment response, it associated with expressions of immune checkpoint molecules. In conclusion, inflammation was associated with worse outcome in the whole breast cancer cohort, but with better outcome in TNBC, which was associated with favorable anticancerous immune response and immune cell infiltrations.

Abundance of Regulatory T Cell (Treg) as a Predictive Biomarker for Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

Regulatory CD4+ T cell (Treg), a subset of tumor-infiltrating lymphocytes (TILs), are known to suppress anticancer immunity but its clinical relevance in human breast cancer remains unclear. In this study, we estimated the relative abundance of Tregs in breast cancer of multiple patient cohorts by using the xCell algorithm on bulk tumor gene expression data. In total, 5177 breast cancer patients from five independent cohorts (TCGA-BRCA, GSE96058, GSE25066, GSE20194, and GSE110590) were analyzed. Treg abundance was not associated with cancer aggressiveness, patient survival, or immune activity markers, but it was lower in metastatic tumors when compared to matched primary tumors. Treg was associated with a high mutation rate of TP53 genes and copy number mutations as well as with increased tumor infiltration of M2 macrophages and decreased infiltration of T helper type 1 (Th1) cells. Pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) was significantly associated with low Treg abundance in triple negative breast cancer (TNBC) but not in ER-positive/Her2-negative subtype. High Treg abundance was significantly associated with high tumor expression of multiple immune checkpoint inhibitor genes. In conclusion, Treg abundance may have potential as a predictive biomarker of pCR after NAC in TNBC.

Negative estrogen receptors and positive progesterone receptors breast cancers

CONTEXT

Hormone receptors (estrogen receptor ER and progesterone receptor PR) are prognostic and predictive factors of outcome for invasive breast cancer. Some tumors only express one of these hormone receptors (ER or PR). ER negative/PR positive breast cancer is a rare subtype (1-4 %) and its existence still controversial. The aim of this study was to evaluate characteristics of this group of tumors.

METHODS

We collected data of all consecutive patients managed in our institution for invasive breast cancer between the 1st January 2007 and 31 December 2013. The aim of the study was to compare data of patients with ER-/PR+tumors with the three other subgroups.

RESULTS

Of the 2071 patients included during the study period, 1.2 % were ER-/PR+. These patients were younger than those with the two ER+groups (p<0.0001). The ER-/PR+tumors differed from the ER+groups for several histological prognostic factors: greater histological size (p=0.0004), higher histological grade, more HER2 overexpression/amplification, more association with ductal carcinoma in situ, more lymphovascular invasion, more nodal metastasis (p<0.0001). Chemotherapy was more often used as an adjuvant treatment in addition of endocrine therapy. Survival was equivalent for patients with ER-/PR+tumors and ER+tumors and significantly higher than patients with ER-/PR- tumors (p<0.0001).

CONCLUSION

Women with ER-/PR+breast cancer have worse prognostic factors than women with ER+cancers but have better overall survival than women with ER-/PR- tumors. We may think that the more frequent association of chemotherapy and endocrine therapy is responsible for this better outcome.

CD8 T Cell Score as a Prognostic Biomarker for Triple Negative Breast Cancer

CD8 T cell is an essential component of tumor-infiltrating lymphocytes (TIL) and tumor immune microenvironment (TIME). Using the xCell CD8 T cell score of whole tumor gene expression data, we estimated these cells in total of 3837 breast cancer patients from TCGA, METABRIC and various GEO cohorts. The CD8 score correlated strongly with expression of CD8 genes. The score was highest for triple-negative breast cancer (TNBC), and a high score was associated with high tumor immune cytolytic activity and better survival in TNBC but not other breast cancer subtypes. In TNBC, tumors with a high CD8 score had enriched expression of interferon (IFN)-α and IFN-γ response and allograft rejection gene sets, and greater infiltration of anti-cancerous immune cells. The score strongly correlated with CD4 memory T cells in TNBC, and tumors with both a high CD8 score and high CD4 memory T cell abundance had significantly better survival. Finally, a high CD8 score was significantly associated with high expression of multiple immune checkpoint molecules. In conclusion, a high CD8 T cell score is associated with better survival in TNBC, particularly when tumor CD4 memory T cells were elevated. Our findings also suggest a possible use of the score as a predictive biomarker for response to immune checkpoint therapy.

Cancer gene expression profiles associated with clinical outcomes to chemotherapy treatments

Background

Machine learning (ML) methods still have limited applicability in personalized oncology due to low numbers of available clinically annotated molecular profiles. This doesn’t allow sufficient training of ML classifiers that could be used for improving molecular diagnostics.

Methods

We reviewed published datasets of high throughput gene expression profiles corresponding to cancer patients with known responses on chemotherapy treatments. We browsed Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and Tumor Alterations Relevant for GEnomics-driven Therapy (TARGET) repositories.

Results

We identified data collections suitable to build ML models for predicting responses on certain chemotherapeutic schemes. We identified 26 datasets, ranging from 41 till 508 cases per dataset. All the datasets identified were checked for ML applicability and robustness with leave-one-out cross validation. Twenty-three datasets were found suitable for using ML that had balanced numbers of treatment responder and non-responder cases.

Conclusions

We collected a database of gene expression profiles associated with clinical responses on chemotherapy for 2786 individual cancer cases. Among them seven datasets included RNA sequencing data (for 645 cases) and the others – microarray expression profiles. The cases represented breast cancer, lung cancer, low-grade glioma, endothelial carcinoma, multiple myeloma, adult leukemia, pediatric leukemia and kidney tumors. Chemotherapeutics included taxanes, bortezomib, vincristine, trastuzumab, letrozole, tipifarnib, temozolomide, busulfan and cyclophosphamide.

Intra-Tumoral Angiogenesis Is Associated with Inflammation, Immune Reaction and Metastatic Recurrence in Breast Cancer

Angiogenesis is one of the hallmarks of cancer. We hypothesized that intra-tumoral angiogenesis correlates with inflammation and metastasis in breast cancer patients. To test this hypothesis, we generated an angiogenesis pathway score using gene set variation analysis and analyzed the tumor transcriptome of 3999 breast cancer patients from The Cancer Genome Atlas Breast Cancer (TCGA-BRCA), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), GSE20194, GSE25066, GSE32646, and GSE2034 cohorts. We found that the score correlated with expression of various angiogenesis-, vascular stability-, and sphingosine-1-phosphate (S1P)-related genes. Surprisingly, the angiogenesis score was not associated with breast cancer subtype, Nottingham pathological grade, clinical stage, response to neoadjuvant chemotherapy, or patient survival. However, a high score was associated with a low fraction of both favorable and unfavorable immune cell infiltrations except for dendritic cell and M2 macrophage, and with Leukocyte Fraction, Tumor Infiltrating Lymphocyte Regional Fraction and Lymphocyte Infiltration Signature scores. High-score tumors had significant enrichment for unfavorable inflammation-related gene sets (interleukin (IL)6, and tumor necrosis factor (TNF)α- and TGFβ-signaling), as well as metastasis-related gene sets (epithelial mesenchymal transition, and Hedgehog-, Notch-, and WNT-signaling). High score was significantly associated with metastatic recurrence particularly to brain and bone. In conclusion, using the angiogenesis pathway score, we found that intra-tumoral angiogenesis is associated with immune reaction, inflammation and metastasis-related pathways, and metastatic recurrence in breast cancer.

The E2F Pathway Score as a Predictive Biomarker of Response to Neoadjuvant Therapy in ER+/HER2- Breast Cancer

E2F transcription factors play critical roles in the cell cycle. Therefore, their activity is expected to reflect tumor aggressiveness and responsiveness to therapy. We scored 3905 tumors of nine breast cancer cohorts for this activity based on their gene expression for the Hallmark E2F targets gene set. As expected, tumors with a high score had an increased expression of cell proliferation-related genes. A high score was significantly associated with shorter patient survival, greater MKI67 expression, histological grade, stage, and genomic aberrations. Furthermore, metastatic tumors had higher E2F scores than the primary tumors from which they arose. Although tumors with a high score had greater infiltration by both pro- and anti-cancerous immune cells, they had an increased expression of immune checkpoint genes. Estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative cancer with a high E2F score achieved a significantly higher pathological complete response (pCR) rate to neoadjuvant chemotherapy. The E2F score was significantly associated with the expression of cyclin-dependent kinase (CDK)-related genes and strongly correlated with sensitivity to CDK inhibition in cell lines. In conclusion, the E2F score is a marker of breast cancer aggressiveness and predicts the responsiveness of ER-positive/HER2-negative patients to neoadjuvant chemotherapy and possibly to CDK and immune checkpoint inhibitors.

Intrinsic and Extrinsic Factors Governing the Transcriptional Regulation of ESR1

Transcriptional regulation of ESR1, the gene that encodes for estrogen receptor α (ER), is critical for regulating the downstream effects of the estrogen signaling pathway in breast cancer such as cell growth. ESR1 is a large and complex gene that is regulated by multiple regulatory elements, which has complicated our understanding of how ESR1 expression is controlled in the context of breast cancer. Early studies characterized the genomic structure of ESR1 with subsequent studies focused on identifying intrinsic (chromatin environment, transcription factors, signaling pathways) and extrinsic (tumor microenvironment, secreted factors) mechanisms that impact ESR1 gene expression. Currently, the introduction of genomic sequencing platforms and additional genome-wide technologies has provided additional insight on how chromatin structures may coordinate with these intrinsic and extrinsic mechanisms to regulate ESR1 expression. Understanding these interactions will allow us to have a clearer understanding of how ESR1 expression is regulated and eventually provide clues on how to influence its regulation with potential treatments. In this review, we highlight key studies concerning the genomic structure of ESR1, mechanisms that affect the dynamics of ESR1 expression, and considerations towards affecting ESR1 expression and hormone responsiveness in breast cancer.

Molecular Biological Features of Nottingham Histological Grade 3 Breast Cancers

INTRODUCTION

Cancer biology dominates the behavior and prognosis of a tumor. Although Nottingham histological grade is a subjective pathological determination, it has been accepted as a surrogate model for cancer biology. As such, histologic grade was incorporated into the latest 8th edition of the American Joint Committee on Cancer breast cancer staging system. In this study, we hypothesized that grade 3 breast cancers demonstrate aggressive molecular biological profiles, reflecting worse biology and possible underlying immunogenicity.

METHODS

Transcriptomic and clinical data were obtained from the Molecular Taxonomy of Breast Cancer International Consortium, and the findings were validated by The Cancer Genome Atlas breast cancer cohort and GSE25066.

RESULTS

Overall, 2876 patients were analyzed in this study. Grade 3 tumors were more common in estrogen receptor (ER)-negative, advanced-stage patients, and were associated with human epidermal growth factor receptor 2 and basal subtypes by the PAM50 classifier, as well as with increased MKI67 expression (all p <0.001). Disease-free survival was significantly worse in grade 3 tumors (all cohorts). Gene set enrichment analysis demonstrated that grade 3 tumors were significantly enriched with not only cell proliferation and cell cycle-related gene sets but also immune activity-related gene sets. CIBERSORT confirmed that grade 3 tumors were infiltrated with macrophage M1, follicular helper T cells, and activated natural killer cells (all p <0.001). Furthermore, grade 3 tumors were associated with more diverse T cell receptors (p =0.001) and increased cytolytic activity (p <0.001). Lastly, major T-cell exhaustion markers were significantly elevated in grade 3 breast cancers (p <0.001).

CONCLUSION

Grade 3 breast cancers demonstrated aggressive transcriptomic features with enhanced immunogenicity and elevated T-cell exhaustion markers.

High dimensional model representation of log-likelihood ratio: binary classification with expression data

Background

Binary classification rules based on a small-sample of high-dimensional data (for instance, gene expression data) are ubiquitous in modern bioinformatics. Constructing such classifiers is challenging due to (a) the complex nature of underlying biological traits, such as gene interactions, and (b) the need for highly interpretable glass-box models. We use the theory of high dimensional model representation (HDMR) to build interpretable low dimensional approximations of the log-likelihood ratio accounting for the effects of each individual gene as well as gene-gene interactions. We propose two algorithms approximating the second order HDMR expansion, and a hypothesis test based on the HDMR formulation to identify significantly dysregulated pairwise interactions. The theory is seen as flexible and requiring only a mild set of assumptions.

Results

We apply our approach to gene expression data from both synthetic and real (breast and lung cancer) datasets comparing it also against several popular state-of-the-art methods. The analyses suggest the proposed algorithms can be used to obtain interpretable prediction rules with high prediction accuracies and to successfully extract significantly dysregulated gene-gene interactions from the data. They also compare favorably against their competitors across multiple synthetic data scenarios.

Conclusion

The proposed HDMR-based approach appears to produce a reliable classifier that additionally allows one to describe how individual genes or gene-gene interactions affect classification decisions. Both real and synthetic data analyses suggest that our methods can be used to identify gene networks with dysregulated pairwise interactions, and are therefore appropriate for differential networks analysis.

AR/ER Ratio Correlates with Expression of Proliferation Markers and with Distinct Subset of Breast Tumors

The co-expression of androgen (AR) and estrogen (ER) receptors, in terms of higher AR/ER ratio, has been recently associated with poor outcome in ER-positive (ER+) breast cancer (BC) patients. The aim of this study was to analyze if the biological aggressiveness, underlined in ER+ BC tumors with higher AR/ER ratio, could be due to higher expression of genes related to cell proliferation. On a cohort of 47 ER+ BC patients, the AR/ER ratio was assessed by immunohistochemistry and by mRNA analysis. The expression level of five gene proliferation markers was defined through TaqMan^®-qPCR assays. Results were validated using 979 BC cases obtained from gene expression public databases. ER+ BC tumors with ratios of AR/ER ≥ 2 have higher expression levels of cellular proliferation genes than tumors with ratios of AR/ER < 2, in both the 47 ER+ BC patients (P < 0.001) and in the validation cohort (P = 0.005). Moreover, BC cases with ratios of AR/ER ≥ 2 of the validation cohort were mainly assigned to luminal B and HER2-enriched molecular subtypes, typically characterized by higher proliferation and poorer prognosis. These data suggest that joint routine evaluation of AR and ER expression may identify a unique subset of tumors, which show higher levels of cellular proliferation and therefore a more aggressive behavior.

G2M Cell Cycle Pathway Score as a Prognostic Biomarker of Metastasis in Estrogen Receptor (ER)-Positive Breast Cancer

The vast majority of breast cancer death is a result of metastasis. Thus, accurate identification of patients who are likely to have metastasis is expected to improve survival. The G2M checkpoint plays a critical role in cell cycle. We hypothesized that breast cancer tumors with high activity of G2M pathway genes are more aggressive and likely to metastasize. To test this, we used the single-sample gene set variation analysis method to calculate the score for the Hallmark G2M checkpoint pathway using gene expression data of a total of 4626 samples from 12 human breast cancer cohorts. As expected, a high G2M pathway score correlated with enriched tumor expression of other cell proliferation-related gene sets. The score was significantly associated with clinical aggressive features of tumors and patient survival in estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative breast cancer. Interestingly, a high G2M score of metastasis tumors was also significantly associated with worse survival. In primary as well as metastasis tumors with high scores, the infiltration of both pro- and anti-cancerous immune cells increased. Tumor G2M score was also associated with treatment response to systemic chemotherapy in ER-positive/HER2-negative cancer, and was predictive of response to cyclin-dependent kinase inhibition therapy.

Flexible Data Trimming Improves Performance of Global Machine Learning Methods in Omics-Based Personalized Oncology

(1) Background: Machine learning (ML) methods are rarely used for an omics-based prescription of cancer drugs, due to shortage of case histories with clinical outcome supplemented by high-throughput molecular data. This causes overtraining and high vulnerability of most ML methods. Recently, we proposed a hybrid global-local approach to ML termed floating window projective separator (FloWPS) that avoids extrapolation in the feature space. Its core property is data trimming, i.e., sample-specific removal of irrelevant features. (2) Methods: Here, we applied FloWPS to seven popular ML methods, including linear SVM, k nearest neighbors (kNN), random forest (RF), Tikhonov (ridge) regression (RR), binomial naïve Bayes (BNB), adaptive boosting (ADA) and multi-layer perceptron (MLP). (3) Results: We performed computational experiments for 21 high throughput gene expression datasets (41–235 samples per dataset) totally representing 1778 cancer patients with known responses on chemotherapy treatments. FloWPS essentially improved the classifier quality for all global ML methods (SVM, RF, BNB, ADA, MLP), where the area under the receiver-operator curve (ROC AUC) for the treatment response classifiers increased from 0.61–0.88 range to 0.70–0.94. We tested FloWPS-empowered methods for overtraining by interrogating the importance of different features for different ML methods in the same model datasets. (4) Conclusions: We showed that FloWPS increases the correlation of feature importance between the different ML methods, which indicates its robustness to overtraining. For all the datasets tested, the best performance of FloWPS data trimming was observed for the BNB method, which can be valuable for further building of ML classifiers in personalized oncology.

FusionLearn: a biomarker selection algorithm on cross-platform data

MOTIVATION

In high dimensional genetic data analysis, the objective is to select important biomarkers which are involved in some biological processes, such as disease progression, immune response, etc. The experimental data are often collected from different platforms including microarray experiments and proteomic experiments. The conventional single-platform approach lacks the capability to learn from multiple platforms, and the resulted lists of biomarkers vary across different platforms. There is a great need to develop an algorithm which can aggregate information across platforms and provide a consolidated list of biomarkers across different platforms.

RESULTS

In this paper, we introduce an R package FusionLearn, which implements a fusion learning algorithm to analyze cross-platform data. The consolidated list of biomarkers is selected by the technique of group penalization. We first apply the algorithm on a collection of breast cancer microarray experiments from the NCBI (National Centre for Biotechnology Information) microarray database and the resulted list of selected genes have higher classification accuracy rate across different datasets than the lists generated from each single dataset. Secondly, we use the software to analyze a combined microarray and proteomic dataset for the study of the growth phase versus the stationary phase in Streptomyces coelicolor. The selected biomarkers demonstrate consistent differential behavior across different platforms.

AVAILABILITY AND IMPLEMENTATION

R package: https://cran.r-project.org/package=FusionLearn.

Low infiltration of tumor-associated macrophages in high c-Myb-expressing breast tumors

Tumor-associated macrophages (TAMs) are prominent components of tumor stroma that promotes tumorigenesis. Many soluble factors participate in the deleterious cross-talk between TAMs and transformed cells; however mechanisms how tumors orchestrate their production remain relatively unexplored. c-Myb is a transcription factor recently described as a negative regulator of a specific immune signature involved in breast cancer (BC) metastasis. Here we studied whether c-Myb expression is associated with an increased presence of TAMs in human breast tumors. Tumors with high frequency of c-Myb-positive cells have lower density of CD68-positive macrophages. The negative association is reflected by inverse correlation between MYB and CD68/CD163 markers at the mRNA levels in evaluated cohorts of BC patients from public databases, which was found also within the molecular subtypes. In addition, we identified potential MYB-regulated TAMs recruiting factors that in combination with MYB and CD163 provided a valuable clinical multigene predictor for BC relapse. We propose that identified transcription program running in tumor cells with high MYB expression and preventing macrophage accumulation may open new venues towards TAMs targeting and BC therapy.

Single hormone receptor-positive breast cancer patients experienced poor survival outcomes: a systematic review and meta-analysis

BACKGROUND

The prognostic and clinical significance of single hormone receptor expression in breast cancer has not been clearly established. The goal of this study was to conduct a meta-analysis to compare the clinical outcomes of patients with ER+PR- tumours and ER-PR+ tumours to those of patients with ER+PR+ tumours.

METHODS

A systematic review of the literature was conducted to identify studies that compared the clinical outcome of patients with ER+PR- tumours or ER-PR+ tumours with those of patients with ER+PR+ tumours. A total of 18 studies met the inclusion criteria and included 217,485 women. Standard methods for meta-analysis were used, including fixed-effect models.

RESULTS

Patients with ER+PR- tumours or ER-PR+ tumours had significantly worse DFS (HR 1.60, 95% CI 1.44-1.77 and HR 2.27, 95% CI 1.67-3.09), BCSS (HR 1.43, 95% CI 1.33-1.53 and HR 1.82, 95% CI 1.68-1.98) and OS (HR 1.38, 95% CI 1.28-1.47 and HR 1.48, 95% CI 1.17-1.89) than those of patients with ER+PR+ tumours. In subgroup analyses, patients who had ER+PR- tumours experienced a higher risk of recurrence than patients with ER+PR+ tumours in the HER2- (HR 1.57, 95% CI 1.32-1.87), LN - (HR 2.07, 95% CI 1.44-2.86) and endocrine therapy (HR 1.65, 95% CI 1.45-1.89) subgroup. Patients who had HER2- and ER-PR+ tumours had an increased risk of recurrence compared with patients who had HER2- and ER+PR+ tumours (HR 3.10, 95% CI 1.92-5.10).

CONCLUSIONS

Among patients with hormone receptor-positive breast cancer, patients with either ER+PR- tumours or ER-PR+ tumours have a higher risk of recurrence and a shorter survival time than those with ER+PR+ tumours. Patients with both types of breast cancer need additional or better treatments.

Correlation-adjusted regression survival scores for high-dimensional variable selection

BACKGROUND

The development of classification methods for personalized medicine is highly dependent on the identification of predictive genetic markers. In survival analysis, it is often necessary to discriminate between influential and noninfluential markers. It is common to perform univariate screening using Cox scores, which quantify the associations between survival and each of the markers to provide a ranking. Since Cox scores do not account for dependencies between the markers, their use is suboptimal in the presence of highly correlated markers.

METHODS

As an alternative to the Cox score, we propose the correlation-adjusted regression survival (CARS) score for right-censored survival outcomes. By removing the correlations between the markers, the CARS score quantifies the associations between the outcome and the set of "decorrelated" marker values. Estimation of the scores is based on inverse probability weighting, which is applied to log-transformed event times. For high-dimensional data, estimation is based on shrinkage techniques.

RESULTS

The consistency of the CARS score is proven under mild regularity conditions. In simulations with high correlations, survival models based on CARS score rankings achieved higher areas under the precision-recall curve than competing methods. Two example applications on prostate and breast cancer confirmed these results. CARS scores are implemented in the R package carSurv.

CONCLUSIONS

In research applications involving high-dimensional genetic data, the use of CARS scores for marker selection is a favorable alternative to Cox scores even when correlations between covariates are low. Having a straightforward interpretation and low computational requirements, CARS scores are an easy-to-use screening tool in personalized medicine research.

Gene Expression-Based Predictive Markers for Paclitaxel Treatment in ER+ and ER- Breast Cancer

One of the objectives of precision oncology is to identify patient’s responsiveness to a given treatment and prevent potential overtreatments through molecular profiling. Predictive gene expression biomarkers are a promising and practical means to this purpose. The overall response rate of paclitaxel drugs in breast cancer has been reported to be in the range of 20–60% and is in the even lower range for ER-positive patients. Predicting responsiveness of breast cancer patients, either ER-positive or ER-negative, to paclitaxel treatment could prevent individuals with poor response to the therapy from undergoing excess exposure to the agent. In this study, we identified six sets of gene signatures whose gene expression profiles could robustly predict nonresponding patients with precisions more than 94% and recalls more than 93% on various discovery datasets (n = 469 for the largest set) and independent validation datasets (n = 278), using the previously developed Multiple Survival Screening algorithm, a random-sampling-based methodology. The gene signatures reported were stable regardless of half of the discovery datasets being swapped, demonstrating their robustness. We also reported a set of optimizations that enabled the algorithm to train on small-scale computational resources. The gene signatures and optimized methodology described in this study could be used for identifying unresponsiveness in patients of ER-positive or ER-negative breast cancers.

FLOating-Window Projective Separator (FloWPS): A Data Trimming Tool for Support Vector Machines (SVM) to Improve Robustness of the Classifier

Here, we propose a heuristic technique of data trimming for SVM termed FLOating Window Projective Separator (FloWPS), tailored for personalized predictions based on molecular data. This procedure can operate with high throughput genetic datasets like gene expression or mutation profiles. Its application prevents SVM from extrapolation by excluding non-informative features. FloWPS requires training on the data for the individuals with known clinical outcomes to create a clinically relevant classifier. The genetic profiles linked with the outcomes are broken as usual into the training and validation datasets. The unique property of FloWPS is that irrelevant features in validation dataset that don’t have significant number of neighboring hits in the training dataset are removed from further analyses. Next, similarly to the k nearest neighbors (kNN) method, for each point of a validation dataset, FloWPS takes into account only the proximal points of the training dataset. Thus, for every point of a validation dataset, the training dataset is adjusted to form a floating window. FloWPS performance was tested on ten gene expression datasets for 992 cancer patients either responding or not on the different types of chemotherapy. We experimentally confirmed by leave-one-out cross-validation that FloWPS enables to significantly increase quality of a classifier built based on the classical SVM in most of the applications, particularly for polynomial kernels.

Resistance to endocrine therapy in breast cancer: molecular mechanisms and future goals

Introduction

The majority of breast cancers (BCs) are characterized by the expression of estrogen receptor alpha (ERα+). ERα acts as ligand-dependent transcription factor for genes associated with cell survival, proliferation, and tumor growth. Thus, blocking the estrogen agonist effect on ERα is the main strategy in the treatment of ERα+ BCs. However, despite the development of targeted anti-estrogen therapies for ER+ BC, around 30–50% of early breast cancer patients will relapse. Acquired resistance to endocrine therapy is a great challenge in ER+ BC patient treatment.

Discussion

Anti-estrogen resistance is a consequence of molecular changes, which allow for tumor growth irrespective of estrogen presence. Those changes may be associated with ERα modifications either at the genetic, regulatory or protein level. Additionally, the activation of alternate growth pathways and/or cell survival mechanisms can lead to estrogen-independence and endocrine resistance.

Conclusion

This comprehensive review summarizes molecular mechanisms associated with resistance to anti-estrogen therapy, focusing on genetic alterations, stress responses, cell survival mechanisms, and cell reprogramming.

Fatty acid oxidation is associated with proliferation and prognosis in breast and other cancers

Background

Altered cellular metabolism is a hallmark of cancer but the association between utilisation of particular metabolic pathways in tumours and patient outcome is poorly understood. We sought to investigate the association between fatty acid metabolism and outcome in breast and other cancers.

Methods

Cox regression analysis and Gene Set Enrichment Analysis (GSEA) of a gene expression dataset from primary breast tumours with well annotated clinical and survival information was used to identify genesets associated with outcome. A geneset representing fatty acid oxidation (FAO) was then examined in other datasets. A doxycycline-inducible breast cancer cell line model overexpressing the rate-limiting enzyme in FAO, carnitine palmitoyl transferase 1A (CPT1A) was generated and analysed to confirm the association between FAO and cancer-associated characteristics in vitro.

Results

We identified a gene expression signature composed of 19 genes associated with fatty acid oxidation (FAO) that was significantly associated with patient outcome. We validated this observation in eight independent breast cancer datasets, and also observed the FAO signature to be prognostic in other cancer types. Furthermore, the FAO signature expression was significantly downregulated in tumours, compared to normal tissues from a variety of anatomic origins. In breast cancer, the expression of CPT1A was higher in oestrogen receptor (ER)-positive, compared to ER-negative tumours and cell lines. Importantly, overexpression of CPT1A significantly decreased the proliferation and wound healing migration rates of MDA-MB231 breast cancer cells, compared to basal expression control.

Conclusions

Our findings suggest that FAO is downregulated in multiple tumour types, and activation of this pathway may lower cancer cell proliferation, and is associated with improved outcomes in some cancers.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4626-9) contains supplementary material, which is available to authorized users.

Vav proteins maintain epithelial traits in breast cancer cells using miR-200c-dependent and independent mechanisms

The bidirectional regulation of epithelial-mesenchymal transitions (EMT) is key in tumorigenesis. Rho GTPases regulate this process via canonical pathways that impinge on the stability of cell-to-cell contacts, cytoskeletal dynamics, and cell invasiveness. Here, we report that the Rho GTPase activators Vav2 and Vav3 utilize a new Rac1-dependent and miR-200c-dependent mechanism that maintains the epithelial state by limiting the abundance of the Zeb2 transcriptional repressor in breast cancer cells. In parallel, Vav proteins engage a mir-200c-independent expression prometastatic program that maintains epithelial cell traits only under 3D culture conditions. Consistent with this, the depletion of endogenous Vav proteins triggers mesenchymal features in epithelioid breast cancer cells. Conversely, the ectopic expression of an active version of Vav2 promotes mesenchymal-epithelial transitions using E-cadherin-dependent and independent mechanisms depending on the mesenchymal breast cancer cell line used. In silico analyses suggest that the negative Vav anti-EMT pathway is operative in luminal breast tumors. Gene signatures from the Vav-associated proepithelial and prometastatic programs have prognostic value in breast cancer patients.

Oestrogen receptor-negative/progesterone receptor-positive phenotype of invasive breast carcinoma in Japan: re-evaluated using immunohistochemical staining

Background

The existence of progesterone receptor (PgR) expression in oestrogen receptor (ER)-negative breast carcinoma is controversial. Here, we re-evaluated ER-negative/PgR-positive (ER−/PgR+) carcinoma cases by immunohistochemical staining (IHC).

Materials and methods

We selected patients who underwent surgery for primary breast carcinoma from our databases at Dokkyo Medical University Hospital and Kameda General Hospital. Among the 9844 patients, the largest series in Japan, 27 (0.3%) were initially diagnosed as ER−/PgR+ breast carcinomas and we re-evaluated by IHC.

Results

The re-evaluated IHC showed that of the 27 patients with the initial results of ER−/PgR+, 12 were ER+/PgR+, 8 were ER−/PgR−, and 7 were ER−/PgR+. ER was negative in 12 of 27 patients (44.4%), and PgR was positive in 8 of 27 patients (29.6%). In our seven re-evaluated and confirmed as ER−/PgR+ cases, the staining proportions of tumor cells were 0% in ER and 1–69% (average 15.8%) in PgR. The average staining proportion of PgR in the re-evaluated ER−/PgR+ phenotype was lower than the initial diagnosis. Histological grading was as follows: grade I, one case; grade II, two cases; grade III, four cases. There were two lymph-node-positive cases.

Conclusions

The ER−/PgR+ phenotype was confirmed after re-evaluation of ER and PgR assessment by a different pathologist. We recommend that pathologists discuss with clinicians, or re-test and re-evaluate ER/PgR expression, particularly in low-grade carcinoma and with a high staining proportion of PgR in the ER−/PgR+ phenotype.