Molecular subtype and tumor characteristics of breast cancer metastases as assessed by gene expression significantly influence patient post-relapse survival

Identification of Genes Crucial for Biological Processes in Breast Cancer Liver Metastasis Relapse

Breast cancer, when advancing to a metastatic stage, involves the liver, impacting over 50% of cases and significantly diminishing survival rates. Presently, a lack of tailored therapeutic protocols for breast cancer liver metastasis (BCLM) underscores the need for a deeper understanding of molecular patterns governing this complication. Therefore, by analyzing differentially expressed genes (DEGs) between primary breast tumors and BCLM lesions, we aimed to shed light on the diversities of this process. This research investigated breast cancer liver metastasis relapse by employing a comprehensive approach that integrated data filtering, gene ontology and KEGG pathway analysis, overall survival analysis, identification of the alteration in the DEGs, visualization of the protein-protein interaction network, Signor 2.0, identification of positively correlated genes, immune cell infiltration analysis, genetic alternation analysis, copy number variant analysis, gene-to-mRNA interaction, transcription factor analysis, molecular docking, and identification of potential treatment targets. This study's integrative approach unveiled metabolic reprogramming, suggesting altered PCK1 and LPL expression as key in breast cancer metastasis recurrence.

Bioinformatics analysis of the potentially functional circRNA-miRNA-mRNA network in breast cancer

Breast cancer (BC) is the most common cancer among women with high morbidity and mortality. Therefore, new research is still needed for biomarker detection. GSE101124 and GSE182471 datasets were obtained from the Gene Expression Omnibus (GEO) database to evaluate differentially expressed circular RNAs (circRNAs). The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases were used to identify the significantly dysregulated microRNAs (miRNAs) and genes considering the Prediction Analysis of Microarray classification (PAM50). The circRNA-miRNA-mRNA relationship was investigated using the Cancer-Specific CircRNA, miRDB, miRTarBase, and miRWalk databases. The circRNA-miRNA-mRNA regulatory network was annotated using Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database. The protein-protein interaction network was constructed by the STRING database and visualized by the Cytoscape tool. Then, raw miRNA data and genes were filtered using some selection criteria according to a specific expression level in PAM50 subgroups. A bottleneck method was utilized to obtain highly interacted hub genes using cytoHubba Cytoscape plugin. The Disease-Free Survival and Overall Survival analysis were performed for these hub genes, which are detected within the miRNA and circRNA axis in our study. We identified three circRNAs, three miRNAs, and eighteen candidate target genes that may play an important role in BC. In addition, it has been determined that these molecules can be useful in the classification of BC, especially in determining the basal-like breast cancer (BLBC) subtype. We conclude that hsa_circ_0000515/miR-486-5p/SDC1 axis may be an important biomarker candidate in distinguishing patients in the BLBC subgroup of BC.

Molecular subtyping improves breast cancer diagnosis in the Copenhagen Breast Cancer Genomics Study

BACKGROUNDIntrinsic molecular subtypes define distinct biological breast cancers and can be used to further improve diagnosis and risk allocation.METHODSThe Copenhagen Breast Cancer Genomics Study (CBCGS) prospectively included women diagnosed with breast cancer at Rigshospitalet from 2014 to 2021. Eligible patients were females with a primary invasive breast cancer (T1c, if N0M0; otherwise, any T, any N, or any M stage) and no prior malignancy. All patients underwent molecular profiling with the CIT256 and PAM50 molecular profile.RESULTSIn the study period, 2,816 patients were included in the CBCGS. Molecular subtyping showed an increase in nonluminal (molecular-apocrine, luminal C, and Basal-like) as compared with luminal (luminal A, luminal B, and Normal-like) subtypes with increasing stage from I to IV. Across all stages, we found a significant difference in survival among subtypes; 91% of patients with LumA were alive at 5 years compared with 91% for LumB, 84% for LumC, 82% for mApo, and 80% for Basal-like. We identified 442 tumors (16%) that were discordant in subtype between CIT256 and IHC. Discordant subtype proved to be a risk factor of death among patients with IHC luminal breast cancer (hazard ratio [HR], 2.08; 95% CI, 1.51-2.86) in a multivariable Cox regression analysis. Discordance occurred more often among patients with N3, stage IV, or grade III disease.CONCLUSIONOur findings indicate that molecular subtypes are a predominant classification for survival. Assessment is particularly crucial for patients with IHC luminal breast cancer with known high-risk factors, since they are at an increased risk of harboring an aggressive molecular subtype.

Clinically relevant gene signatures provide independent prognostic information in older breast cancer patients

BACKGROUND

The clinical utility of gene signatures in older breast cancer patients remains unclear. We aimed to determine signature prognostic capacity in this patient subgroup.

METHODS

Research versions of the genomic grade index (GGI), 70-gene, recurrence score (RS), cell cycle score (CCS), PAM50 risk-of-recurrence proliferation (ROR-P), and PAM50 signatures were applied to 39 breast cancer datasets (N = 9583). After filtering on age ≥ 70 years, and the presence of estrogen receptor (ER) and survival data, 871 patients remained. Signature prognostic capacity was tested in all (n = 871), ER-positive/lymph node-positive (ER + /LN + , n = 335) and ER-positive/lymph node-negative (ER + /LN-, n = 374) patients using Kaplan-Meier and multivariable Cox-proportional hazard (PH) modelling.

RESULTS

All signatures were statistically significant in Kaplan-Meier analysis of all patients (Log-rank P < 0.001). This significance remained in multivariable analysis (Cox-PH, P ≤ 0.05). In ER + /LN + patients all signatures except PAM50 were significant in Kaplan-Meier analysis (Log-rank P ≤ 0.05) and remained so in multivariable analysis (Cox-PH, P ≤ 0.05). In ER + /LN- patients all except RS were significant in Kaplan-Meier analysis (Log-rank P ≤ 0.05) but only the 70-gene, CCS, ROR-P, and PAM50 signatures remained so in multivariable analysis (Cox-PH, P ≤ 0.05).

CONCLUSIONS

We found that gene signatures provide prognostic information in survival analyses of all, ER + /LN + and ER + /LN- older (≥ 70 years) breast cancer patients, suggesting a potential role in aiding treatment decisions in older patients.

Update on the Use of Molecular Subtyping in Breast Cancer

The standard of care for invasive cancers of the breast has been and continues to be to evaluate them for breast prognostic markers: estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 by immunohistochemistry. Over 2 decades ago, a study was the first to report on the molecular subtypes of breast cancer. Four main subtypes were reported. Since then there have been some changes in the molecular subtype classification, but overall many studies have shown that this subtyping has clinical prognostic and predictive value. More recently, molecular assays have been developed and studies have shown similar clinical prognostic and predictive value. We reviewed the literature for studies evaluating the clinical significance of all 3 of these methods of evaluation and the follow-up findings of that review are presented below.

A genetic mosaic mouse model illuminates the pre-malignant progression of basal-like breast cancer

Basal-like breast cancer (BLBC) is highly aggressive, and often characterized by BRCA1 and p53 deficiency. Although conventional mouse models enabled the investigation of BLBC at malignant stages, its initiation and pre-malignant progression remain understudied. Here, we leveraged a mouse genetic system known as mosaic analysis with double markers (MADM) to study BLBC initiation by generating rare GFP+Brca1, p53-deficient mammary cells alongside RFP+ wild-type sibling cells. After confirming the close resemblance of mammary tumors arising in this model to human BLBC at both transcriptomic and genomic levels, we focused our studies on the pre-malignant progression of BLBC. Initiated GFP+ mutant cells showed a stepwise pre-malignant progression trajectory from focal expansion to hyper-alveolarization and then to micro-invasion. Furthermore, despite morphological similarities to alveoli, hyper-alveolarized structures actually originate from ductal cells based on twin-spot analysis of GFP-RFP sibling cells. Finally, luminal-to-basal transition occurred exclusively in cells that have progressed to micro-invasive lesions. Our MADM model provides excellent spatiotemporal resolution to illuminate the pre-malignant progression of BLBC, and should enable future studies on early detection and prevention for this cancer.

Distinct shared and compartment-enriched oncogenic networks drive primary versus metastatic breast cancer

Metastatic breast-cancer is a major cause of death in women worldwide, yet the relationship between oncogenic drivers that promote metastatic versus primary cancer is still contentious. To elucidate this relationship in treatment-naive animals, we hereby describe mammary-specific transposon-mutagenesis screens in female mice together with loss-of-function Rb, which is frequently inactivated in breast-cancer. We report gene-centric common insertion-sites (gCIS) that are enriched in primary-tumors, in metastases or shared by both compartments. Shared-gCIS comprise a major MET-RAS network, whereas metastasis-gCIS form three additional hubs: Rho-signaling, Ubiquitination and RNA-processing. Pathway analysis of four clinical cohorts with paired primary-tumors and metastases reveals similar organization in human breast-cancer with subtype-specific shared-drivers (e.g. RB1-loss, TP53-loss, high MET, RAS, ER), primary-enriched (EGFR, TGFβ and STAT3) and metastasis-enriched (RHO, PI3K) oncogenic signaling. Inhibitors of RB1-deficiency or MET plus RHO-signaling cooperate to block cell migration and drive tumor cell-death. Thus, targeting shared- and metastasis- but not primary-enriched derivers offers a rational avenue to prevent metastatic breast-cancer.

Machine Learning Algorithms to Predict Breast Cancer Recurrence Using Structured and Unstructured Sources from Electronic Health Records

Recurrence is a critical aspect of breast cancer (BC) that is inexorably tied to mortality. Reuse of healthcare data through Machine Learning (ML) algorithms offers great opportunities to improve the stratification of patients at risk of cancer recurrence. We hypothesized that combining features from structured and unstructured sources would provide better prediction results for 5-year cancer recurrence than either source alone. We collected and preprocessed clinical data from a cohort of BC patients, resulting in 823 valid subjects for analysis. We derived three sets of features: structured information, features from free text, and a combination of both. We evaluated the performance of five ML algorithms to predict 5-year cancer recurrence and selected the best-performing to test our hypothesis. The XGB (eXtreme Gradient Boosting) model yielded the best performance among the five evaluated algorithms, with precision = 0.900, recall = 0.907, F1-score = 0.897, and area under the receiver operating characteristic AUROC = 0.807. The best prediction results were achieved with the structured dataset, followed by the unstructured dataset, while the combined dataset achieved the poorest performance. ML algorithms for BC recurrence prediction are valuable tools to improve patient risk stratification, help with post-cancer monitoring, and plan more effective follow-up. Structured data provides the best results when fed to ML algorithms. However, an approach based on natural language processing offers comparable results while potentially requiring less mapping effort.

A genetic mosaic mouse model illuminates the pre-malignant progression of basal-like breast cancer

Basal-like breast cancer is an aggressive breast cancer subtype, often characterized by a deficiency in BRCA1 function and concomitant loss of p53 . While conventional mouse models enable the investigation of its malignant stages, one that reveals its initiation and pre-malignant progression is lacking. Here, we leveraged a mouse genetic system known as M osaic A nalysis with D ouble M arkers (MADM) to generate rare GFP-labeled Brca1 , p53 -deficient cells alongside RFP+ wildtype sibling cells in the mammary gland. The mosaicism resembles the sporadic initiation of human cancer and enables spatially resolved analysis of mutant cells in comparison to paired wildtype sibling cells. Mammary tumors arising in the model show transcriptomic and genomic characteristics similar to human basal-like breast cancer. Analysis of GFP+ mutant cells at interval time points before malignancy revealed a stepwise progression of lesions from focal expansion to hyper-alveolarization and then to micro-invasion. These stereotyped morphologies indicate the pre-malignant stage irrespective of the time point at which it is observed. Paired analysis of GFP-RFP siblings during focal expansion suggested that hyper-alveolarized structures originate from ductal rather than alveolar cells, despite their morphological similarities to alveoli. Evidence for luminal-to-basal transition at the pre-malignant stages was restricted to cells that had escaped hyper-alveoli and progressed to micro-invasive lesions. Our MADM-based mouse model presents a useful tool for studying the pre-malignancy of basal-like breast cancer.

Summary statement

A mouse model recapitulates the process of human basal-like breast tumorigenesis initiated from sporadic Brca1, p53 -deficient cells, empowering spatially-resolved analysis of mutant cells during pre-malignant progression.

Prognostic value of intrinsic subtypes in hormone-receptor-positive metastatic breast cancer: systematic review and meta-analysis

BACKGROUND

In hormone receptor-positive (HoR+) breast cancer (BC), gene expression analysis identifies luminal A (LumA), luminal B (LumB), human epidermal growth factor receptor 2 (HER2)-enriched (HER2-E), basal-like (BL) intrinsic subtypes and a normal-like group. This classification has an established prognostic value in early-stage HoR+ BC. Here, we carried out a trial-level meta-analysis to determine the prognostic ability of subtypes in metastatic BC (MBC).

MATERIALS AND METHODS

We systematically reviewed all the available prospective phase II/III trials in HoR+ MBC where subtype was assessed. The primary endpoint was progression-free survival (PFS)/time to progression (TTP) of the LumA subtype compared to non-LumA. Secondary endpoints were PFS/TTP of each individual subtype, according to treatment, menopausal and HER2 status and overall survival (OS). The random-effect model was applied, and heterogeneity assessed through Cochran's Q and I². Threshold for significance was set at P < 0.05. The study was registered in PROSPERO (ID: CRD42021255769).

RESULTS

Seven studies were included (2536 patients). Non-LumA represented 55.2% and was associated with worse PFS/TTP than LumA [hazard ratio (HR) 1.77, P < 0.001, I² = 61%], independently of clinical HER2 status [P_{subgroup difference} (P_sub) = 0.16], systemic treatment (P_sub = 0.96) and menopausal status (P_sub = 0.12). Non-LumA tumors also showed worse OS (HR 2.00, P < 0.001, I² = 65%), with significantly different outcomes for LumB (PFS/TTP HR 1.46; OS HR 1.41), HER2-E (PFS/TTP HR 2.39; OS HR 2.08) and BL (PFS/TTP HR 2.67; OS HR 3.26), separately (PFS/TTP P_sub = 0.01; OS P_sub = 0.005). Sensitivity analyses supported the main result. No publication bias was observed.

CONCLUSIONS

In HoR+ MBC, non-LumA disease is associated with poorer PFS/TTP and OS than LumA, independently of HER2, treatment and menopausal status. Future trials in HoR+ MBC should consider this clinically relevant biological classification.

Molecular subtypes predict the preferential site of distant metastasis in advanced breast cancer: a nationwide retrospective study

Objective

This study aimed to explore possible associations between molecular subtypes and site of distant metastasis in advanced breast cancer (ABC).

Methods

3577 ABC patients were selected from 21 hospitals of seven geographic regions in China from 2012-2014. A questionnaire was designed to collect medical information regarding demographic characteristics, risk factors, molecular subtype, recurrence/metastasis information, and disease-free survival (DFS). The cancers were classified into Luminal A, Luminal B, HER2-enriched and Triple Negative subtypes. Chi-square test and multivariate Cox proportional hazard models were performed to explore the associations between molecular subtypes and distant metastasis sites.

Results

A total of 2393 cases with molecular subtypes information were finally examined. Patients with Luminal A (51.1%) and Luminal B (44.7%) were most prone to bone metastasis, whereas liver metastasis was more frequently observed in HER2-enriched ABC patients (29.1%).The cumulative recurrence and metastasis rates of ABC patients at 36 months of DFS were the most significant within molecular types, of which Triple Negative was the highest (82.7%), while that of Luminal A was the lowest (58.4%). In the adjusted Cox regression analysis, Luminal B, HER2-enriched and Triple Negative subtypes increased the risk of visceral metastasis by 23%, 46% and 87% respectively. In addition, Triple Negative patients had a higher probability of brain metastasis (HR 3.07, 95% CI: 1.04-9.07).

Conclusion

Molecular subtypes can predict the preferential sites of distant metastasis, emphasizing that these associations were of great help in choices for surveillance, developing appropriate screening and cancer management strategies for follow-up and personalized therapy in ABC patients.

Clinical implications of the intrinsic molecular subtypes in hormone receptor-positive and HER2-negative metastatic breast cancer

Traditionally, the classification of breast cancer relies on the expression of immunohistochemical (IHC) biomarkers readily available in clinical practice. Using highly standardized and reproducible assays across patient cohorts, intrinsic molecular subtypes of breast cancer - also called "intrinsic subtypes" (IS) - have been identified based on the expression of 50 genes. Although IHC-based subgroups and IS moderately correlate to each other, they are not superimposable. In fact, non-luminal biology has been detected in a substantial proportion (5-20%) of hormone receptor-positive (HoR+) tumors, has prognostic value, and identifies reduced and increased sensitivity to endocrine therapy and chemotherapy, respectively. During tumor progression, a shift toward a non-luminal estrogen-independent and more aggressive phenotype has been demonstrated. Intrinsic genomic instability and cell plasticity, alone or combined with external constraints deriving from treatment selective pressure or interplay with the tumor microenvironment, may represent the determinants of such biological diversity between primary and metastatic disease, and during metastatic tumor evolution. In this review, we describe the distribution and the clinical behavior of IS as the disease progresses, focusing on HoR+/HER2-negative advanced breast cancer. In addition, we provide an overview of the ongoing clinical trials aiming to validate the predictive and prognostic value of IS towards their incorporation into routine care.

Myricetin-induced apoptosis in triple-negative breast cancer cells through inhibition of the PI3K/Akt/mTOR pathway

Breast cancer is still a severe origin of malignant demise in females, and its prevalence is rising worldwide. Triple-negative breast cancer (TNBC) is a diversified aggressive breast tumor distinguished by inadequate prognosis, early recurrence, high invasion, and extremely metastasized disease. Chemotherapy is being used to treat it; however, it has low efficacy. On the other hand, with the growing number of corroborations on subtypes of TNBC and molecular biology of tumors, significant advancement in TNBC targeted treatment has been made. Myricetin (MYR), a polyhydroxyflavonol compound widely found in nature, has been shown to possess anticancer effects in various cancers. Though, the mechanisms and impacts of MYR on metastasis of TNBC remain unclear. Early and late apoptotic cell death and cell proliferation inhibition were observed in MYR-treated TNBC cells. MYR modulated cell cycle, pro-angiogenic, and invasion effects via the mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K)/Protein kinase B (PKB/also known as AKT) signaling pathways. Moreover, it regulates the expression of MAPK, PI3K/AKT/mTOR, IκB/NF-κB, Hippo, STAT3, GSK-3β, Nrf2/HO-1, TLR, eNOS / NO, ACE, and AChE. Here, we review the anticancer effects of MYR for TNBC and target the PI3K/AKT/mTOR pathway as a therapeutic target for the fruitful treatment of TNBC to summarize MYR's therapeutic potential.

Advances in the Structural and Physiological Functions of SHARPIN

SHARPIN was initially found as a SHANK-associated protein. SHARPIN can be used as an important component to form the linear ubiquitin chain assembly complex (LUBAC) with HOIL-1L, HOIP to produce a linear ubiquitin chain connected N-terminal Met1, playing a critical role in various cellular processes including NF-κB signaling, inflammation, embryogenesis and apoptosis. SHARPIN alone can also participate in many critical physiological activities and cause various disorders such as chronic dermatitis, tumor, and Alzheimer’s disease. Mice with spontaneous autosomal recessive mutations in the SHARPIN protein mainly exhibit chronic dermatitis and immunodeficiency with elevated IgM. Additionally, SHARPIN alone also plays a key role in various cellular events, such as B cells activation and platelet aggregation. Structural studies of the SHARPIN or LUBAC have been reported continuously, advancing our understanding of it at the molecular level. However, the full-length structure of the SHARPIN or LUBAC was lagging, and the molecular mechanism underlying these physiological processes is also unclear. Herein, we summarized the currently resolved structure of SHARPIN as well as the emerging physiological role of SHARPIN alone or in LUBAC. Further structural and functional study of SHARPIN will provide insight into the role and underlying mechanism of SHARPIN in disease, as well as its potential application in therapeutic.

Socioeconomic, Clinical, and Molecular Features of Breast Cancer Influence Overall Survival of Latin American Women

Molecular profile of breast cancer in Latin-American women was studied in five countries: Argentina, Brazil, Chile, Mexico, and Uruguay. Data about socioeconomic characteristics, risk factors, prognostic factors, and molecular subtypes were described, and the 60-month overall cumulative survival probabilities (OS) were estimated. From 2011 to 2013, 1,300 eligible Latin-American women 18 years or older, with a diagnosis of breast cancer in clinical stage II or III, and performance status ≦̸1 were invited to participate in a prospective cohort study. Face-to-face interviews were conducted, and clinical and outcome data, including death, were extracted from medical records. Unadjusted associations were evaluated by Chi-squared and Fisher's exact tests and the OS by Kaplan-Meier method. Log-rank test was used to determine differences between cumulative probability curves. Multivariable adjustment was carried out by entering potential confounders in the Cox regression model. The OS at 60 months was 83.9%. Multivariable-adjusted death hazard differences were found for women living in Argentina (2.27), Chile (1.95), and Uruguay (2.42) compared with Mexican women, for older (≥60 years) (1.84) compared with younger (≤40 years) women, for basal-like subtype (5.8), luminal B (2.43), and HER2-enriched (2.52) compared with luminal A subtype, and for tumor clinical stages IIB (1.91), IIIA (3.54), and IIIB (3.94) compared with stage IIA women. OS was associated with country of residence, PAM50 intrinsic subtype, age, and tumor stage at diagnosis. While the latter is known to be influenced by access to care, including cancer screening, timely diagnosis and treatment, including access to more effective treatment protocols, it may also influence epigenetic changes that, potentially, impact molecular subtypes. Data derived from heretofore understudied populations with unique geographic ancestry and sociocultural experiences are critical to furthering our understanding of this complexity.

Therapeutic progress and challenges for triple negative breast cancer: targeted therapy and immunotherapy

Triple negative breast cancer (TNBC) is a subtype of breast cancer, with estrogen receptor, human epidermal growth factor receptor 2 and progesterone receptor negative. TNBC is characterized by high heterogeneity, high rates of metastasis, poor prognosis, and lack of therapeutic targets. Now the treatment of TNBC is still based on surgery and chemotherapy, which is effective only in initial stage but almost useless in advanced stage. And due to the lack of hormone target, hormonal therapies have little beneficial effects. In recent years, signaling pathways and receptor-specific targets have been reported to be effective in TNBC patients under specific clinical conditions. Now targeted therapies have been approved for many other cancers and even other subtypes of breast cancer, but treatment options for TNBC are still limited. Most of TNBC patients showed no response, which may be related to the heterogeneity of TNBC, therefore more effective treatments and predictive biomarkers are needed. In the present review, we summarize potential treatment opinions for TNBC based on the dysregulated receptors and signaling pathways, which play a significant role in multiple stages of TNBC development. We also focus on the application of immunotherapy in TNBC, and summarize the preclinical and clinical trials of therapy for patients with TNBC. We hope to accelerate the research and development of new drugs for TNBC by understanding the relevant mechanisms, and to improve survival.

Clinical and Molecular Characteristics of ER-Positive Ultralow Risk Breast Cancer Tumors Identified by the 70-Gene Signature

The metastatic potential of estrogen receptor (ER)-positive breast cancers is heterogenous and distant recurrences occur months to decades after primary diagnosis. We have previously shown that patients with tumors classified as ultralow risk by the 70-gene signature have a minimal long-term risk of fatal breast cancer. Here, we evaluate the previously unexplored underlying clinical and molecular characteristics of ultralow risk tumors in 538 ER-positive patients from the Stockholm tamoxifen randomized trial (STO-3). Out of the 98 ultralow risk tumors, 89% were luminal A molecular subtype, whereas 26% of luminal A tumors were of ultralow risk. Compared with other ER-positive tumors, ultralow risk tumors were significantly (Fisher's test, P<0.05) more likely to be of smaller tumor size, lower grade, progesterone receptor (PR)-positive, human epidermal growth factor 2 (HER2)-negative and have low Ki-67 levels (proliferation-marker). Moreover, ultralow risk tumors showed significantly lower expression scores of multi-gene modules associated with the AKT/mTOR-pathway, proliferation (AURKA), HER2/ERBB2-signaling, IGF1-pathway, PTEN-loss, and immune response (IMMUNE1 and IMMUNE2), and higher expression scores of the PIK3CA-mutation-associated module. Furthermore, 706 genes were significantly (FDR<0.001) differentially expressed in ultralow risk tumors, including lower expression of genes involved in immune response, PI3K/Akt/mTOR-pathway, histones, cell cycle, DNA repair, apoptosis, and higher expression of genes coding for epithelial-to-mesenchymal transition, and homeobox proteins, among others. In conclusion, ultralow risk tumors, associated with minimal long-term risk of fatal disease, differ from other ER-positive tumors, including luminal A molecular subtype tumors. Identification of these characteristics is important to improve our prediction of non-fatal versus fatal breast cancer. This article is protected by copyright. All rights reserved.

Prognostic Model Construction and Immune Microenvironment Analysis of Breast Cancer Based on Ferroptosis-Related lncRNAs

Purpose

To construct a prognostic model of breast cancer using ferroptosis-related lncRNAs and explore novel therapeutic targets.

Materials and Methods

A prognostic characteristic model based on differential expression of ferroptosis-related lncRNAs in breast cancer was established based on TCGA data.

Results

Eleven ferroptosis-related lncRNAs associated with breast cancer prognosis were identified. Kaplan–Meier analysis suggested that high-risk lncRNA signatures correspond to a poor prognosis. The AUC of the signature lncRNAs was 0.682, demonstrating that it is accurate in predicting BC prognosis. GSEA showed that ferroptosis-related lncRNAs in high-risk individuals are mainly enriched in cell cycle, cell adhesion and tumor pathways. Immunity and gene expression analysis revealed that APC co-inhibition, check-point, HLA, inflammation-promoting and T cell co-stimulation among others were significantly different between the high-and low-risk group. Three immune checkpoints were highly expressed in the high-risk group.

Conclusion

Ferroptosis-related lncRNAs can be used as a prognostic feature to construct a prognostic model of breast cancer, based on which early detection markers, therapeutic targets and anti-tumor immune microenvironment can be studied, and clinical treatment can also be instructive.

The Context-Dependent Impact of Integrin-Associated CD151 and Other Tetraspanins on Cancer Development and Progression: A Class of Versatile Mediators of Cellular Function and Signaling, Tumorigenesis and Metastasis

Simple Summary

Tetraspanins are a family of molecules abundantly expressed on the surface of normal or tumor cells. They have been implicated in recruiting or sequestering key molecular regulators of malignancy of a variety of human cancers, including breast and lung cancers, glioblastoma and leukemia. Yet, how their actions take place remains mysterious due to a lack of traditional platform for molecular interactions. The current review digs into this mystery by examining findings from recent studies of multiple tetraspanins, particularly CD151. The molecular basis for differential impact of tetraspanins on tumor development, progression, and spreading to secondary sites is highlighted, and the complexity and plasticity of their control over tumor cell activities and interaction with their surroundings is discussed. Finally, an outlook is provided regarding tetraspanins as candidate biomarkers and targets for the diagnosis and treatment of human cancer.

Abstract

As a family of integral membrane proteins, tetraspanins have been functionally linked to a wide spectrum of human cancers, ranging from breast, colon, lung, ovarian, prostate, and skin carcinomas to glioblastoma. CD151 is one such prominent member of the tetraspanin family recently suggested to mediate tumor development, growth, and progression in oncogenic context- and cell lineage-dependent manners. In the current review, we summarize recent advances in mechanistic understanding of the function and signaling of integrin-associated CD151 and other tetraspanins in multiple cancer types. We also highlight emerging genetic and epigenetic evidence on the intrinsic links between tetraspanins, the epithelial-mesenchymal transition (EMT), cancer stem cells (CSCs), and the Wnt/β-catenin pathway, as well as the dynamics of exosome and cellular metabolism. Finally, we discuss the implications of the highly plastic nature and epigenetic susceptibility of CD151 expression, function, and signaling for clinical diagnosis and therapeutic intervention for human cancer.

PAM50 Intrinsic Subtype Profiles in Primary and Metastatic Breast Cancer Show a Significant Shift toward More Aggressive Subtypes with Prognostic Implications

Simple Summary

The majority of breast cancer deaths are caused by the spread of the disease to distant locations. The biological processes and molecular characteristics that eventually transform breast cancer into a life-threatening metastatic disease are not fully understood. The molecular subtyping of breast cancer into four tumor subtypes—namely luminal A, luminal B, human epidermal growth factor receptor 2-enriched, and basal-like subtypes—has been implemented for therapeutic guidance in patients with early breast cancer. It is not settled whether molecular subtypes in metastatic tissue can guide the choice of systemic therapy and how these subtypes may change throughout tumor progression. In this study, breast cancer subtypes at different stages of the disease were investigated, and we found changes to more unfavorable subtypes to be common throughout the progression of the disease. These findings suggests that molecular subtyping in metastatic disease could add important prognostic and predictive information to complement information from the primary tumor.

Abstract

Background: PAM50 breast cancer intrinsic subtyping adds prognostic information in early breast cancer; however, the role in metastatic disease is unclear. We aimed to identify PAM50 subtypes in primary tumors (PTs) and metastases to outline subtype changes and their prognostic role. Methods: RNA was isolated from PTs, lymph node metastases (LNMs), and distant metastases (DMs) in metastatic breast cancer patients (n = 140) included in a prospective study (NCT01322893). Gene expression analyses were performed using the Breast Cancer 360 (BC360) assay from Nano-String. The subtype shifts were evaluated using McNemar and symmetry tests, and clinical outcomes were evaluated with log-rank tests and Cox regression. Results: The PAM50 subtype changed in 25/59 of paired samples between PTs and LNMs (P_symmetry = 0.002), in 31/61 between PTs and DMs (P_symmetry < 0.001), and in 16/38 between LNMs and DMs (P_symmetry = 0.004). Shifts toward subtypes with worse outcomes were the most common. Patients with shifts from the luminal PT to non-luminal DM subtypes had worse progression-free survival compared to patients with a stable subtype (hazard ratio (HR): 2.3; 95% confidence interval (CI): 1.14–4.68, p = 0.02). Conclusion: Strong evidence of PAM50 subtype shifts toward unfavorable subtypes were seen between PTs and metastatic samples. For patients with a shift in subtype from luminal PT to non-luminal DM, a worse prognosis was noted.

Molecular features of untreated breast cancer and initial metastatic event inform clinical decision-making and predict outcome: long-term results of ESOPE, a single-arm prospective multicenter study

Background

Prognosis evaluation of advanced breast cancer and therapeutic strategy are mostly based on clinical features of advanced disease and molecular profiling of the primary tumor. Very few studies have evaluated the impact of metastatic subtyping during the initial metastatic event in a prospective study. The genomic landscape of metastatic breast cancer has mostly been described in very advanced, pretreated disease, limiting the findings transferability to clinical use.

Methods

We developed a multicenter, single-arm, prospective clinical trial in order to address these issues. Between November 2010 and September 2013, 123 eligible patients were included. Patients at the first, untreated metastatic event were eligible. All matched primary tumors and metastatic samples were centrally reviewed for pathological typing. Targeted and whole-exome sequencing was applied to matched pairs of frozen tissue. A multivariate overall survival analysis was performed (median follow-up 64 months).

Results

Per central review in 84 patients (out of 130), we show that luminal A breast tumors are more prone to subtype switching. By combining targeted sequencing of a 91 gene panel (n = 67) and whole-exome sequencing (n = 30), a slight excess of mutations is observed in the metastases. Luminal A breast cancer has the most heterogeneous mutational profile and the highest number of mutational signatures, when comparing primary tumor and the matched metastatic tissue. Tumors with a subtype change have more mutations that are private. The metastasis-specific mutation load is significantly higher in late than in de novo metastases. The most frequently mutated genes were TP53 and PIK3CA. The most frequent metastasis-specific druggable genes were PIK3CA, PTEN, KDR, ALK, CDKN2A, NOTCH4, POLE, SETD2, SF3B1, and TSC2. Long-term outcome is driven by a combination of tumor load and metastasis biology.

Conclusions

Profiling of the first, untreated, metastatic event of breast cancer reveals a profound heterogeneity mostly in luminal A tumors and in late metastases. Based on this profiling, we can derive information relevant to prognosis and therapeutic intervention, which support current guidelines recommending a biopsy at the first metastatic relapse.

Trial registration

The trial was registered at ClinicalTrials.gov (NCT01956552).

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00862-6.

High expression of ACE2 in HER2 subtype of breast cancer is a marker of poor prognosis

Background

ACE2 a key molecule of the Renin-Angiotensin system has been identified as the receptor for SARS-CoV-2 entry into human cells. In the context of human cancers, there is evidence that ACE2 might function as a tumor suppressor. The expression levels of ACE2 among the different subtypes of breast cancer has not been investigated.

Methods

We have examined the differential expression of ACE2 and its correlation with prognosis in breast cancer subtypes using the METABRIC (n = 1898) and TCGA (n = 832) cohorts. Correlations were evaluated by Pearsons's correlation co-efficient and Kaplan-Meier analysis was used to estimate differences in disease-free survival between the ACE2 high and ACE2 low groups.

Results

There is minimal expression of ACE2 in the luminal classes, but significantly higher levels in the Basal-like and HER2-enriched subclasses. Metastatic biopsies of these tumor types also show enhanced expression of ACE2. High levels of ACE2 correlated with decreased disease-free survival in the HER2-enriched subtype, and it was positively correlated with EGFR expression.

Conclusion

These observations suggest ACE2 might function as a context dependent factor driving tumor progression in breast cancer and permit new opportunities for targeted therapy.

Prognostic factors and survival according to tumour subtype in women presenting with breast cancer bone metastases at initial diagnosis: a SEER-based study

Background

Tumour subtype has a significant effect on bone metastasis in breast cancer, but population-based estimates of the prognosis of patients with bone metastases at breast cancer diagnosis are lacking. The aim of this study was to analyse the influence of tumour subtype and other factors on the prognosis and survival of patients with bone metastases of breast cancer.

Methods

Using the Surveillance, Epidemiology, and End Results (SEER) Program data from 2012 to 2016, a retrospective cohort study was conducted to investigate stage IV breast cancer patients with bone metastases. Stage IV patient characteristics according to subtype were compared using chi-square tests. Overall survival (OS) and prognostic factors were compared using the Kaplan-Meier method and the Cox proportional hazards model, respectively.

Results

A total of 3384 stage IV patients were included in this study; 63.42% were HR+/HER2-, 19.86% were HR+/HER2+, 9.34% were HR−/HER2-, and 7.39% were HR−/HER2+. The median OS for the whole population was 38 months, and 33.9% of the patients were alive at 5 years. The median OS and five-year survival rate were significantly different among stage IV breast cancer patients with different molecular subtypes (p < 0.05). Multivariate Cox regression analysis showed that age of 55–59 (HR = 1.270), black race (HR = 1.317), grade III or IV (HR = 1.960), HR−/HER2- (HR = 2.808), lung metastases (HR = 1.378), liver metastases (HR = 2.085), and brain metastases (HR = 1.903) were independent risk factors for prognosis; married status (HR = 0.819), HR+/HER2+ (HR = 0.631), HR−/HER2+ (HR = 0.716), insurance (HR = 0.587) and surgery (HR = 0.504) were independent protection factors of prognosis. There was an interaction between the HR+/HER2+ subtype and other metastases (except bone metastases, HR = 0.694, 95% CI: 0.485–0.992), but the interaction between race and subtype did not reach significance for prognosis.

Conclusions

There were substantial differences in OS according to tumour subtype. In addition to tumour subtype, other independent predictors of OS were age at diagnosis, race, marital status, insurance, grade, surgery and visceral metastases. There was an interaction between the HR+/HER2+ subtype and other metastases (except bone metastases) for prognosis. Tumour subtype, as a significant prognostic factor, warrants further investigation.

Construction of an immune-related genes nomogram for the preoperative prediction of axillary lymph node metastasis in triple-negative breast cancer

Immune system disorder is associated with metastasis of triple-negative breast cancers (TNBCs). A robust, individualized immune-related genes (IRGs)-based classifier was aimed to develop and validate in our study to precisely estimate the axillary lymph node (ALN) status preoperatively in patients with early-stage TNBC. We first analyzed RNA sequencing profiles in TNBC patients from The Cancer Genome Atlas database by using bioinformatics approaches, and screened 23 differentially expressed IRGs. A 9-gene panel was generated with an area under the curve (AUC) of 0.77 [95% confidence interval (95% CI), 0.68-0.87]. We detected the 9 ALN-status-related IRGs in the training set (n = 133) and developed a reduced and optimized five-IRGs signature, which effectively distinguished TNBC patients with ALN metastasis (AUC, 0.80; 95% CI, 0.65-0.86), and was superior to preoperative ultrasound-based ALN status (AUC, 0.73; 95% CI, 0.53-0.93). Predictive efficiency (AUC, 0.77; 95% CI 0.61-0.93) of this five-IRGs signature was validated in the validation set (n = 81). Furthermore, IRGs nomogram incorporated IRGs signature with US-based ALN status showed higher ALN status prediction efficacy than US-based ALN status and five-IRGs signature alone in both training and validation sets. IRGs nomogram may aid in identifying patients who can be exempted from axillary surgery.Novelty and impact: An immune-related genes (IRGs) nomogram was first developed and externally validated in our study, which incorporated the IRGs signature with ultrasound (US)-based axillary lymph nodes (ALN) status. IRGs nomogram is superior to IRGs signature alone for preoperative estimation of ALN metastasis in patients with triple-negative breast cancer (TNBC). It is a favourable biomarker for preoperatively predicting ALN metastasis risk and may aid in clinical decision-making in early-stage TNBCs.

High expression of FUSE binding protein 1 in breast cancer stimulates cell proliferation and diminishes drug sensitivity

Breast cancer is the most common malignant tumor affecting women worldwide and is divided into the following subtypes: Luminal A, Luminal B, HER-2 overexpression and triple-negative breast cancer (TNBC). TNBC accounts for approximately 15-20% of all breast cancer cases. Due to the characteristics of low differentiation, the likelyhood of recurrence and metastasis, strong invasiveness and the lack of hormone receptors and human epidermal growth factor receptor 2 (HER2), patients with TNBC cannot benefit from endocrine therapy or other available targeted agents. Chemotherapy is one of the main treatments for patients with TNBC, and cisplatin is one of the most commonly used and effective drugs. The human far upstream element binding protein 1 (FBP1) is a potent pro-proliferative and anti-apoptotic oncoprotein, which is overexpressed in numerous tumor types. The present study demonstrated that FBP1 and its target, c-Myc, were more highly expressed in breast cancer tissues compared with para-carcinoma tissues, and the FBP1 and c-Myc levels are decreased by cisplatin treatment. The knockdown of FBP1 in TNBC cells decreased cell proliferation by arresting the cell cycle at the G2 phase. The knockdown of FBP1 decreased the expression of G2 phase-associateed protein cyclin A2, whereas it increased that of cyclin B1 and p-CDC2. Furthermore, the knockdown of FBP1 decreased cell migration and metastasis by downregulating matrix metalloproteinase 2 expression, and enhanced the sensitivity of TNBC cells to cisplatin by inducing apoptosis. These results thus suggest that FBP1 is a potential novel biological marker for the diagnosis and treatment of TNBC.

Ribonuclease H2 Subunit A impacts invasiveness and chemoresistance resulting in poor survivability of breast cancer in ER dependent manner

Ribonuclease H2 subunit A (RNASEH2A), a member of the RNase HII family, acts in DNA replication by mediating removal of lagging-strand Okazaki fragment RNA primers. We explored the roles of RNASEH2A in the prognosis of breast cancer, specifically in relation to proliferation, invasiveness, and sensitivity to cytotoxins of cells in the estrogen receptor (ER)-positive MCF-7 and the ER-negative MDA-MB-231 breast cancer cell lines. We collected 26 datasets from around the world, comprising 7815 accessible cases. In these datasets, we probed the association between expression of RNASEH2A and clinical parameters, primarily by inhibiting the expression of RNASEH2A with siRNAs. Such inhibition inhibited the growth and invasiveness of MCF-7 cells. Independent and pooled Kaplan-Meier and Cox analyses revealed that RNASEH2A overexpression was associated with aggressiveness and poor outcomes in a dose-dependent manner in breast cancers of ER-positive subtypes, but not with ER-negative subtypes. The prognostic performance of RNASEH2A mRNA in ER-positive breast cancer was comparable to that for other gene signatures, such as the 21-gene recurrence score. Overexpression of RNASEH2A was also positively associated with cancer cell resistance to chemotherapy; inhibition of RNASEH2A by siRNA enhanced the chemosensitivity in an in vitro study. Bioinformatic analyses indicated that the ER may modulate RNASEH2A action in mitosis, DNA repair, and differentiation through transcriptional regulation. RNASEH2A may be a useful prognostic and predictive biomarker in ER-positive breast cancer and may serve as a therapeutic target for the treatment of ER-positive breast cancer.

Targeting Metabolic Deregulation Landscapes in Breast Cancer Subtypes

Metabolic deregulation is an emergent hallmark of cancer. Altered patterns of metabolic pathways result in exacerbated synthesis of macromolecules, increased proliferation, and resistance to treatment via alteration of drug processing. In addition, molecular heterogeneity creates a barrier to therapeutic options. In breast cancer, this broad variation in molecular metabolism constitutes, simultaneously, a source of prognostic and therapeutic challenges and a doorway to novel interventions. In this work, we investigated the metabolic deregulation landscapes in breast cancer molecular subtypes. Such landscapes are the regulatory signatures behind subtype-specific metabolic features. n = 735 breast cancer samples of the Luminal A, Luminal B, Her2+, and Basal subtypes, as well as n = 113 healthy breast tissue samples were analyzed. By means of a single-sample-based algorithm, deregulation for all metabolic pathways in every sample was determined. Deregulation levels match almost perfectly with the molecular classification, indicating that metabolic anomalies are closely associated with gene-expression signatures. Luminal B tumors are the most deregulated but are also the ones with higher within-subtype variance. We argued that this variation may underlie the fact that Luminal B tumors usually present the worst prognosis, a high rate of recurrence, and the lowest response to treatment in the long term. Finally, we designed a therapeutic scheme to regulate purine metabolism in breast cancer, independently of the molecular subtype. This scheme is founded on a computational tool that provides a set of FDA-approved drugs to target pathway-specific differentially expressed genes. By providing metabolic deregulation patterns at the single-sample level in breast cancer subtypes, we have been able to further characterize tumor behavior. This approach, together with targeted therapy, may open novel avenues for the design of personalized diagnostic, prognostic, and therapeutic strategies.

Prognostic and Therapeutic Significance of Adhesion-regulating Molecule 1 in Estrogen Receptor-positive Breast Cancer

INTRODUCTION

Adhesion-regulating molecule 1 (ADRM1) is a polyubiquitin receptor on the 26S proteasome. ADRM1 is upregulated in many cancers. In this study, we evaluated the potential prognostic and predictive value of ADRM1 in breast cancer.

MATERIALS AND METHODS

Individual and pooled survival analyses were performed on 19 independent breast cancer microarray datasets. Gene signatures enriched by ADRM1 were also analyzed in pooled datasets.

RESULTS

Gene set enrichment analysis revealed that high expression of ADRM1 was significantly associated with aggressive breast cancer. Our findings revealed that ADRM1 mRNA levels were significantly associated with estrogen receptor (ER) status, progesterone receptor status, tumor size, lymph node status, histologic grade, and molecular subtypes. We also found that higher mRNA ADRM1 expression was significantly correlated with poor survival in patients with breast cancer. The prognostic power of ADRM1 mRNA was similar to the 70-gene wound response genes and 21 gene recurrence score; it was superior to TNM staging. The prognostic value of ADRM1 was better in ER-positive (ER⁺) breast cancer cases than in ER-negative breast cancer cases. In cases involving stage II breast cancer, radiotherapy significantly reduced the relative risk of OS in the ADRM1-low subgroup.

CONCLUSION

ADRM1 mRNA levels were significantly related to poor outcome in our breast cancer sample population. It could serve as a prognostic biomarker, especially in ER⁺ breast cancer and Luminal A breast cancer cases, as well as a predictive biomarker for ER⁺ breast cancer.

Identification of Alternatively-Activated Pathways between Primary Breast Cancer and Liver Metastatic Cancer Using Microarray Data

Alternatively-activated pathways have been observed in biological experiments in cancer studies, but the concept had not been fully explored in computational cancer system biology. Therefore, an alternatively-activated pathway identification method was proposed and applied to primary breast cancer and breast cancer liver metastasis research using microarray data. Interestingly, the results show that cytokine-cytokine receptor interaction and calcium signaling were significantly enriched under both conditions. TGF beta signaling was found to be the hub in network topology analysis. In total, three types of alternatively-activated pathways were recognized. In the cytokine-cytokine receptor interaction pathway, four active alteration patterns in gene pairs were noticed. Thirteen cytokine-cytokine receptor pairs with inverse activity changes of both genes were verified by the literature. The second type was that some sub-pathways were active under only one condition. For the third type, nodes were significantly active in both conditions, but with different active genes. In the calcium signaling and TGF beta signaling pathways, node E2F5 and E2F4 were significantly active in primary breast cancer and metastasis, respectively. Overall, our study demonstrated the first time using microarray data to identify alternatively-activated pathways in breast cancer liver metastasis. The results showed that the proposed method was valid and effective, which could be helpful for future research for understanding the mechanism of breast cancer metastasis.

Intratumor Heterogeneity of the Estrogen Receptor and the Long-term Risk of Fatal Breast Cancer

Background

Breast cancer patients with estrogen receptor (ER)–positive disease have a continuous long-term risk for fatal breast cancer, but the biological factors influencing this risk are unknown. We aimed to determine whether high intratumor heterogeneity of ER predicts an increased long-term risk (25 years) of fatal breast cancer.

Methods

The STO-3 trial enrolled 1780 postmenopausal lymph node–negative breast cancer patients randomly assigned to receive adjuvant tamoxifen vs not. The fraction of cancer cells for each ER intensity level was scored by breast cancer pathologists, and intratumor heterogeneity of ER was calculated using Rao’s quadratic entropy and categorized into high and low heterogeneity using a predefined cutoff at the second tertile (67%). Long-term breast cancer-specific survival analyses by intra-tumor heterogeneity of ER were performed using Kaplan-Meier and multivariable Cox proportional hazard modeling adjusting for patient and tumor characteristics.

Results

A statistically significant difference in long-term survival by high vs low intratumor heterogeneity of ER was seen for all ER-positive patients (P < .001) and for patients with luminal A subtype tumors (P = .01). In multivariable analyses, patients with high intratumor heterogeneity of ER had a twofold increased long-term risk as compared with patients with low intratumor heterogeneity (ER-positive: hazard ratio [HR] = 1.98, 95% confidence interval [CI] = 1.31 to 3.00; luminal A subtype tumors: HR = 2.43, 95% CI = 1.18 to 4.99).

Conclusions

Patients with high intratumor heterogeneity of ER had an increased long-term risk of fatal breast cancer. Interestingly, a similar long-term risk increase was seen in patients with luminal A subtype tumors. Our findings suggest that intratumor heterogeneity of ER is an independent long-term prognosticator with potential to change clinical management, especially for patients with luminal A tumors.

Pan-cancer analysis connects tumor matrisome to immune response

Recent sequencing efforts unveil genomic landscapes of tumor microenvironment. A key compartment in this niche is the extracellular matrix (ECM) and its related components - matrisome. Yet, little is known about the extent to which matrisome pattern is conserved in progressive tumors across diverse cancer types. Using integrative genomic approaches, we conducted multi-platform assessment of a measure of deregulated matrisome associated with tumor progression, termed as tumor matrisome index (TMI), in over 30,000 patient-derived samples. Combined quantitative analyses of genomics and proteomics reveal that TMI is closely associated with mutational load, tumor pathology, and predicts survival across different malignancies. Interestingly, we observed an enrichment of specific tumor-infiltrating immune cell populations, along with signatures predictive of resistance to immune checkpoint blockade immunotherapy, and clinically targetable immune checkpoints in TMI_high tumors. B7-H3 emerged as a particularly promising target for anti-tumor immunity in these tumors. Here, we show that matrisomal abnormalities could represent a potential clinically useful biomarker for prognostication and prediction of immunotherapy response.

Quantitative assessment of breast cancer liver metastasis expansion with patient-derived xenografts

Advanced breast cancer often spreads to the bone, brain, liver, and lungs. The survival time of a patient with breast cancer liver metastasis is often less than 9 months without treatment. Experimental model systems often focus on the lung as a site of metastatic relapse, and therefore, there is less of an understanding of the biological processes that occur during expansive liver metastasis growth. In these studies, 14 genetically distinct breast cancer patient-derived xenografts (PDXs) were characterized for growth in the liver after portal vein injection of cancer cells. Growth in the liver occurred in 12 of 14 models, and the relative growth rate across the PDXs was overall similar to growth in the mammary gland. Pathological and immunohistochemical analyses revealed that the proliferation rates of metastases were relatively similar as the metastases expanded until the tumors became necrotic, and then slightly lower proliferation rates were observed. There were influxes of macrophages and neutrophils as the metastases increased in size, suggesting these innate immune cells may result in differential responses to therapeutics in micrometastases compared to macrometastases. The development and characterization of these models is important as future studies can utilize this information to determine if targeted therapies can slow the progression of metastatic disease at different stages in the liver.

Separation of breast cancer and organ microenvironment transcriptomes in metastases

Background

The seed and soil hypothesis was proposed over a century ago to describe why cancer cells (seeds) grow in certain organs (soil). Since then, the genetic properties that define the cancer cells have been heavily investigated; however, genomic mediators within the organ microenvironment that mediate successful metastatic growth are less understood. These studies sought to identify cancer- and organ-specific genomic programs that mediate metastasis.

Methods

In these studies, a set of 14 human breast cancer patient-derived xenograft (PDX) metastasis models was developed and then tested for metastatic tropism with two approaches: spontaneous metastases from mammary tumors and intravenous injection of PDX cells. The transcriptomes of the cancer cells when growing as tumors or metastases were separated from the transcriptomes of the microenvironment via species-specific separation of the genomes. Drug treatment of PDX spheroids was performed to determine if genes activated in metastases may identify targetable mediators of viability.

Results

The experimental approaches that generated metastases in PDX models were identified. RNA sequencing of 134 tumors, metastases, and normal non-metastatic organs identified cancer- and organ-specific genomic properties that mediated metastasis. A common genomic response of the liver microenvironment was found to occur in reaction to the invading PDX cells. Genes within the cancer cells were found to be either transiently regulated by the microenvironment or permanently altered due to clonal selection of metastatic sublines. Gene Set Enrichment Analyses identified more than 400 gene signatures that were commonly activated in metastases across basal-like PDXs. A Src signaling signature was found to be extensively upregulated in metastases, and Src inhibitors were found to be cytotoxic to PDX spheroids.

Conclusions

These studies identified that during the growth of breast cancer metastases, there were genomic changes that occurred within both the cancer cells and the organ microenvironment. We hypothesize that pathways upregulated in metastases are mediators of viability and that simultaneously targeting changes within different cancer cell pathways and/or different tissue compartments may be needed for inhibition of disease progression.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1123-2) contains supplementary material, which is available to authorized users.

Bone Metastasis Prognostic Factors in Breast Cancer

Objective:

Bone is the most common site of metastasis in breast cancer. Prognostic factors for predicting bone metastases in breast cancer are controversial yet. In this study, we investigated clinical factors associated with secondary bone metastasis of breast cancer.

Methods:

In total, 1690 patients with breast cancer recorded between 2002 and 2012 in Motamed Cancer Institute, Tehran, Iran entered in the retrospective study. We studied age, menopausal status, histologic type, tumor size, number of cancerous axillary lymph nodes, serum concentrations of alkaline phosphatase (ALP), carcinogenicity antigen (CEA), cancer antigen (CA)-153, and hemoglobin (HB) in 2 groups with bone metastases (n = 123) and without it, respectively. We applied logistic regression to identify bone metastasis prognostic factors in breast cancer patients and calculated the cut-off value, sensitivity, and characteristics of independent prognostic factors using receiver operating characteristic (ROC) curve analysis.

Results:

Menopause, larger tumor size, and the greater number of cancerous axillary lymph nodes increased the chance of bone metastases significantly (P < .05). There was no significant difference between mean groups with and without bone metastases regarding serum concentration of CEA, CA-153, HB, and histopathologic type (P > .05). Logistic regression showed that age (odds ratio (OR) = 1.021), menopausal status (OR = 1.854), number of cancerous axillary lymph nodes (OR = 1.065), a tumor size between 2 and 5 cm diameter (OR = 2.002) and more than 5 cm diameter (OR = 4.009), and ALP (OR = 1.005) are independent prognostic factors associated with bone metastases. The ROC curve showed that the abovementioned factors have comparable predictive accuracy for bone metastases.

Conclusions:

Age, menopausal status, number of axillary lymph node metastases, tumor size, and ALP were identified as prognostic factors for bone metastasis in patients with breast cancer. So patients with these characteristics should be monitored more precisely with regular follow-ups.

Chronological occurrence of PI3KCA mutations in breast cancer liver metastases after repeat partial liver resection

Background

Liver metastases of breast cancer are frequent and can recur even after “complete/R0” resection in combination with systemic and hormonal treatments. The aim of this study was to analyze throughout repeat hepatectomies for liver metastases the evolution of PI3KCA gene mutational status.

Methods

All liver metastases nodules (n = 70) from 19 women who underwent at least 2 liver resections were reexamined. DNA extraction from archived tumoral tissue was performed and the major ‘hot spot’ mutations in the helical and catalytic domains of PI3KCA have been analyzed using Massarray platform (Agena Bioscience) based on allelic discrimination PCR amplification followed by sensitive mass spectrometry detection.

Results

The two major somatic hot spot PI3KCA mutations were found in 27 (38.6%) nodules corresponding to 8 of the 19 patients (42%). The frequency of women whose breast cancer liver metastases (BCLM) carries PI3KCA mutations increased from the first to the third hepatectomy. Tumors carrying PI3KCA mutations are significantly larger and more frequently observed when resections were R0 compared to patients with no PI3KCA mutation.

Conclusion

PI3KCA mutations are frequently observed in BCLM and persist along with the recurrence. Their identification in circulating tumor cells should become a useful biomarker in the routine practice of breast cancer management to prevent tumor recurrence and overcome the problems of intra- and inter-tumoral heterogeneity of the current biomarkers,

Molecular Classification of Lymph Node Metastases Subtypes Predict for Survival in Head and Neck Cancer

PURPOSE

In advanced stage head and neck squamous cell cancers (HNSCC), approximately half of the patients with lymph node metastases (LNM) are not cured. Given the heterogeneous outcomes in these patients, we profiled the expression patterns of LNMs to identify the biological factors associated with patient outcomes.Experimental Design: We performed mRNAseq and miRNAseq on 72 LNMs and 29 matched primary tumors from 34 patients with HNSCC. Clustering identified molecular subtypes in LNMs and in primary tumors. Prediction Analysis of Microarrays algorithm identified a 73-gene classifier that distinguished LNM subtypes. Gene-set enrichment analysis identified pathways upregulated in LNM subtypes.

RESULTS

Integrative clustering identified three distinct LNM subtypes: (i) an immune subtype (Group 1), (ii) an invasive subtype (Group 2), and (iii) a metabolic/proliferative subtype (Group 3). Group 2 subtype was associated with significantly worse locoregional control and survival. LNM-specific subtypes were not observed in matched primary tumor specimens. In HNSCCs, breast cancers, and melanomas, a 73-gene classifier identified similar Group 2 LNM subtypes that were associated with worse disease control and survival only when applied to lymph node sites, but not when applied to other primary tumors or metastatic sites. Similarly, previously proposed prognostic classifiers better distinguished patients with worse outcomes when applied to the transcriptional profiles of LNMs, but not the profiles of primary tumors.

CONCLUSIONS

The transcriptional profiles of LNMs better predict outcomes than transcriptional profiles of primary tumors. The LNMs display site-specific subtypes associated with worse disease control and survival across multiple cancer types.

A mouse model featuring tissue-specific deletion of p53 and Brca1 gives rise to mammary tumors with genomic and transcriptomic similarities to human basal-like breast cancer

Purpose and methods

In human basal-like breast cancer, mutations and deletions in TP53 and BRCA1 are frequent oncogenic events. Thus, we interbred mice expressing the CRE-recombinase with mice harboring loxP sites at TP53 and BRCA1 (K14-Cre; p53^f/f Brca1^f/f) to test the hypothesis that tissue-specific deletion of TP53 and BRCA1 would give rise to tumors reflective of human basal-like breast cancer.

Results

In support of our hypothesis, these transgenic mice developed tumors that express basal-like cytokeratins and demonstrated intrinsic gene expression features similar to human basal-like tumors. Array comparative genomic hybridization revealed a striking conservation of copy number alterations between the K14-Cre; p53^f/f Brca1^f/f mouse model and human basal-like breast cancer. Conserved events included MYC amplification, KRAS amplification, and RB1 loss. Microarray analysis demonstrated that these DNA copy number events also led to corresponding changes in signatures of pathway activation including high proliferation due to RB1 loss. K14-Cre; p53^f/f Brca1^f/f also matched human basal-like breast cancer for a propensity to have immune cell infiltrates. Given the long latency of K14-Cre; p53^f/f Brca1^f/f tumors (~ 250 days), we created tumor syngeneic transplant lines, as well as in vitro cell lines, which were tested for sensitivity to carboplatin and paclitaxel. These therapies invoked acute regression, extended overall survival, and resulted in gene expression signatures of an anti-tumor immune response.

Conclusion

These findings demonstrate that this model is a valuable preclinical resource for the study of human basal-like breast cancer.

Electronic supplementary material

The online version of this article (10.1007/s10549-018-5061-y) contains supplementary material, which is available to authorized users.

Management of hormone-receptor positive human epidermal receptor 2 negative advanced or metastatic breast cancers

Hormone therapy, rather than chemotherapy, is recommended for hormone-receptor positive (HR+), human epidermal receptor 2 negative (HER2-) advanced or metastatic breast cancer (A/MBC) according to the European Society of Medical Oncology (ESMO), American Society of Clinical Oncology (ASCO) and National Comprehensive Cancer Network (NCCN) guidelines, unless in visceral crisis in which chemotherapy is indicated. Hormonal monotherapy of selective estrogen receptor modulator (SERM) or selective estrogen receptor down-regulator (SERD), aromatase inhibitor (AI), or their combination as doublets, used to be the mainstay options as first-line (1L) therapy for most patients. More recently, combination targeted drugs plus AI or SERD (such as fulvestrant) has been extensively investigated in both 1L and second-line (2L) treatments of HR+ HER2- patients. Cyclin-D kinase 4/6 inhibitors (CDK4/6i) can halt tumor proliferation by blocking the ER related transcription signaling that drives the CDK4/6-dependent cell cycle in HR+ tumors, and they work best together with AI or SERD. On the other hand, favorable results were reported from inhibition of m-TOR pathway, both in 2L setting when PI3K-AKT-mTOR pathway is frequently overexpressed, as well as in 1L setting. Currently, the major guidelines have all included CDK4/6i plus AI as a standard 1L therapy, while Everolimus plus AI, and CDK4/6i plus fulvestrant, are recommended 2L options. Selecting appropriate patients for such therapeutic options and harnessing the sequence of these new therapies in the new paradigm of managing HR+ HER2- A/MBC are the key priorities for future clinical research.

Aldolase B-Mediated Fructose Metabolism Drives Metabolic Reprogramming of Colon Cancer Liver Metastasis

Cancer metastasis accounts for the majority of cancer-related deaths and remains a clinical challenge. Metastatic cancer cells generally resemble cells of the primary cancer, but they may be influenced by the milieu of the organs they colonize. Here, we show that colorectal cancer cells undergo metabolic reprogramming after they metastasize and colonize the liver, a key metabolic organ. In particular, via GATA6, metastatic cells in the liver upregulate the enzyme aldolase B (ALDOB), which enhances fructose metabolism and provides fuel for major pathways of central carbon metabolism during tumor cell proliferation. Targeting ALDOB or reducing dietary fructose significantly reduces liver metastatic growth but has little effect on the primary tumor. Our findings suggest that metastatic cells can take advantage of reprogrammed metabolism in their new microenvironment, especially in a metabolically active organ such as the liver. Manipulation of involved pathways may affect the course of metastatic growth.

Immunity drives TET1 regulation in cancer through NF-κB

Ten-eleven translocation enzymes (TET1, TET2, and TET3), which induce DNA demethylation and gene regulation by converting 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC), are often down-regulated in cancer. We uncover, in basal-like breast cancer (BLBC), genome-wide 5hmC changes related to TET1 regulation. We further demonstrate that TET1 repression is associated with high expression of immune markers and high infiltration by immune cells. We identify in BLBC tissues an anticorrelation between TET1 expression and the major immunoregulator family nuclear factor κB (NF-κB). In vitro and in mice, TET1 is down-regulated in breast cancer cells upon NF-κB activation through binding of p65 to its consensus sequence in the TET1 promoter. We lastly show that these findings extend to other cancer types, including melanoma, lung, and thyroid cancers. Together, our data suggest a novel mode of regulation for TET1 in cancer and highlight a new paradigm in which the immune system can influence cancer cell epigenetics.

Luminal A Breast Cancer and Molecular Assays: A Review

PURPOSE

Chemotherapy has been the historical mainstay of treatment for patients with breast cancer, with immunohistochemical markers and tumor characteristics driving treatment decisions. The discovery of different intrinsic subtypes of breast cancer has advanced the understanding of breast cancer, with gene-based assays shedding further light on tumor behavior and response to treatment.

DESIGN

This review focuses on the landscape of the luminal A subtype, its definition based on immunohistochemistry (IHC) and gene assays, the prognostic and predictive value of these assays, guideline recommendations, and treatment implications.

RESULTS

Clinical studies of the prognostic value of gene-based and IHC-based assays in patients with luminal A-subtype breast cancers suggest a better prognosis for these patients compared with those with breast cancers of other subtypes.

CONCLUSION

In today's era of precision medicine, the best treatment regimen for patients with luminal A-subtype tumors is still undetermined, but available data raise the question whether chemotherapy can be omitted and endocrine therapy alone is sufficient for this patient population.

IMPLICATIONS FOR PRACTICE

Immunohistochemical markers have traditionally guided treatment decisions in breast cancer. However, advances in gene-expression profiling and availability of gene-based assays have launched these newer tests into everyday clinical practice. Luminal A-subtype tumors are a unique subset that may have favorable tumor biology. Properly defining this tumor subtype is important and may identify a subset of patients for whom endocrine therapy alone is sufficient.

Exome sequencing of primary breast cancers with paired metastatic lesions reveals metastasis-enriched mutations in the A-kinase anchoring protein family (AKAPs)

Background

Tumor heterogeneity in breast cancer tumors is today widely recognized. Most of the available knowledge in genetic variation however, relates to the primary tumor while metastatic lesions are much less studied. Many studies have revealed marked alterations of standard prognostic and predictive factors during tumor progression. Characterization of paired primary- and metastatic tissues should therefore be fundamental in order to understand mechanisms of tumor progression, clonal relationship to tumor evolution as well as the therapeutic aspects of systemic disease.

Methods

We performed full exome sequencing of primary breast cancers and their metastases in a cohort of ten patients and further confirmed our findings in an additional cohort of 20 patients with paired primary and metastatic tumors. Furthermore, we used gene expression from the metastatic lesions and a primary breast cancer data set to study the gene expression of the AKAP gene family.

Results

We report that somatic mutations in A-kinase anchoring proteins are enriched in metastatic lesions. The frequency of mutation in the AKAP gene family was 10% in the primary tumors and 40% in metastatic lesions. Several copy number variations, including deletions in regions containing AKAP genes were detected and showed consistent patterns in both investigated cohorts. In a second cohort containing 20 patients with paired primary and metastatic lesions, AKAP mutations showed an increasing variant allele frequency after multiple relapses. Furthermore, gene expression profiles from the metastatic lesions (n = 120) revealed differential expression patterns of AKAPs relative to the tumor PAM50 intrinsic subtype, which were most apparent in the basal-like subtype. This pattern was confirmed in primary tumors from TCGA (n = 522) and in a third independent cohort (n = 182).

Conclusion

Several studies from primary cancers have reported individual AKAP genes to be associated with cancer risk and metastatic relapses as well as direct involvement in cellular invasion and migration processes. Our findings reveal an enrichment of mutations in AKAP genes in metastatic breast cancers and suggest the involvement of AKAPs in the metastatic process. In addition, we report an AKAP gene expression pattern that consistently follows the tumor intrinsic subtype, further suggesting AKAP family members as relevant players in breast cancer biology.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4021-6) contains supplementary material, which is available to authorized users.

Bone metastasis pattern in initial metastatic breast cancer: a population-based study

Purpose

Bone is one of the most common sites of breast cancer metastasis, and population-based studies of patients with bone metastasis in initial metastatic breast cancer (MBC) are lacking.

Materials and methods

From 2010 to 2013, 245,707 breast cancer patients and 8901 patients diagnosed with initial bone metastasis were identified by Surveillance, Epidemiology, and End Results database of the National Cancer Institute. Multivariate logistic and Cox regression were used to identify predictive factors for the presence of bone metastasis and prognosis factors. Kaplan-Meier method and log-rank test were used for survival analysis.

Results

Eight thousand nine hundred one patients with initial MBC had bone involvement, accounting for 3.6% of the entire cohort and 62.5% of the patients with initial MBC. Also, 70.5% of patients with bone metastasis were hormone receptor (HR) positive (HR+/human epidermal growth factor receptor 2 [HER2]-: 57.6%; HR+/HER2+: 12.9%). Patients with initial bone metastasis had a better 5-year survival rate compared to those with initial brain, liver, or lung metastasis. HR+/HER2- and HR+/HER2+ breast cancer had a propensity of bone metastasis in the entire cohort and were correlated with better prognosis in patients with initial bone metastasis. Local surgery had significantly improved overall survival in initial MBC patients with bone metastasis.

Conclusion

Our study has provided population-based estimates of epidemiologic characteristics and prognosis in patients with bone metastasis at the time of breast cancer diagnosis. These findings would lend support to optimal surveillance and treatment of bone metastasis in breast cancer.

Immune gene expression and response to chemotherapy in advanced breast cancer

Background:

Transcriptomic profiles have shown promise as predictors of response to neoadjuvant chemotherapy in breast cancer (BC). This study aimed to explore their predictive value in the advanced BC (ABC) setting.

Methods:

In a Phase 3 trial of first-line chemotherapy in ABC, a fine needle aspiration biopsy (FNAB) was obtained at baseline. Intrinsic molecular subtypes and gene modules related to immune response, proliferation, oestrogen receptor (ER) signalling and recurring genetic alterations were analysed for association with objective response to chemotherapy. Gene-set enrichment analysis (GSEA) of responders vs non-responders was performed independently. Lymphocytes were enumerated in FNAB smears and the absolute abundance of immune cell types was calculated using the Microenvironment Cell Populations counter method.

Results:

Gene expression data were available for 109 patients. Objective response to chemotherapy was statistically significantly associated with an immune module score (odds ratio (OR)=1.62; 95% confidence interval (CI), 1.03–2.64; P=0.04). Subgroup analysis showed that this association was restricted to patients with ER-positive or luminal tumours (OR=3.54; 95%, 1.43–10.86; P=0.012 and P for interaction=0.04). Gene-set enrichment analysis confirmed that in these subgroups, immune-related gene sets were enriched in responders.

Conclusions:

Immune-related transcriptional signatures may predict response to chemotherapy in ER-positive and luminal ABC.

Thresher: determining the number of clusters while removing outliers

Background

Cluster analysis is the most common unsupervised method for finding hidden groups in data. Clustering presents two main challenges: (1) finding the optimal number of clusters, and (2) removing “outliers” among the objects being clustered. Few clustering algorithms currently deal directly with the outlier problem. Furthermore, existing methods for identifying the number of clusters still have some drawbacks. Thus, there is a need for a better algorithm to tackle both challenges.

Results

We present a new approach, implemented in an R package called Thresher, to cluster objects in general datasets. Thresher combines ideas from principal component analysis, outlier filtering, and von Mises-Fisher mixture models in order to select the optimal number of clusters. We performed a large Monte Carlo simulation study to compare Thresher with other methods for detecting outliers and determining the number of clusters. We found that Thresher had good sensitivity and specificity for detecting and removing outliers. We also found that Thresher is the best method for estimating the optimal number of clusters when the number of objects being clustered is smaller than the number of variables used for clustering. Finally, we applied Thresher and eleven other methods to 25 sets of breast cancer data downloaded from the Gene Expression Omnibus; only Thresher consistently estimated the number of clusters to lie in the range of 4–7 that is consistent with the literature.

Conclusions

Thresher is effective at automatically detecting and removing outliers. By thus cleaning the data, it produces better estimates of the optimal number of clusters when there are more variables than objects. When we applied Thresher to a variety of breast cancer datasets, it produced estimates that were both self-consistent and consistent with the literature. We expect Thresher to be useful for studying a wide variety of biological datasets.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1998-9) contains supplementary material, which is available to authorized users.

Caspase-3 over-expression is associated with poor overall survival and clinicopathological parameters in breast cancer: a meta-analysis of 3091 cases

Caspase-3 is a vital executioner molecule during the apoptotic process. Numerous studies have revealed the close association of caspase-3 expression and breast cancer. Nevertheless, the prognostic value of caspase-3 expression for patients with breast cancer remains uncertain. To thoroughly analyze the prognostic effect of caspase-3 expression on the clinicopathological features and survival of breast cancer, we conducted this meta-analysis. With various search strategies, electronic databases were comprehensively searched. A total of 3091 patients from 21 studies were ultimately obtained. The analysis results indicated that increased expression of caspase-3 had a negative influence on the overall survival (OS) of breast cancer (HR = 1.73, 95%CI 1.12–2.67, P = 0.014). Subgroup analyses based on race revealed that the value of caspase-3 for evaluating patients’ OS was more useful in Asian patients (HR = 3.16, 95%CI 1.20–8.15, P = 0.020), and subgroup analyses based on study analytical methods revealed that caspase-3 was a risk factor for breast cancer patients in multivariate overall survival analyses (HR = 1.67, 95%CI 1.02–2.75, P = 0.044). As for the relationship between caspase-3 expression and breast cancer subtype as well as progression, caspase-3 might serve as a risk factor for the progestogen receptor (PR) and human epidermal growth factor receptor-2 (HER-2) subtypes (OR = 1.44, 95%CI 1.09–1.89, P = 0.010; OR = 1.76, 95%CI 1.18–2.62, P = 0.050, respectively) of breast cancer. However, no evidence showed that increased expression of caspase-3 was statistically correlated with tumor differentiation state (low/moderate or high), tumor TNM stage (I-II/III-IV) or lymph node metastasis (–/+). In conclusion, this meta-analysis revealed that increased caspase-3 expression was significantly associated with worse prognosis and two subtypes of breast cancer. More prospective studies are urgently needed to define the prognostic value of caspase-3 expression in patients with breast cancer.

Gene modules associated with breast cancer distant metastasis-free survival in the PAM50 molecular subtypes

To identify PAM50 subtype–specific associations between distant metastasis-free survival (DMFS) in breast cancer (BC) patients and gene modules describing potentially targetable oncogenic pathways, a comprehensive analysis evaluating the prognostic efficacy of published gene signatures in 2027 BC patients from 13 studies was conducted. We calculated 21 gene modules and computed hazard ratios (HRs) for DMFS for one-unit increases in module score, with and without adjustment for clinical characteristics. By comparing gene expression to survival outcomes, we derived four subtype-specific prognostic signatures for BC. Univariate and multivariate analyses showed that in the luminal A subgroup, E2F3, PTEN and GGI gene module scores were associated with clinical outcome. In the luminal B tumors, RAS was associated with DMFS and in the basal-like tumors, ER was associated with DMFS. Our defined gene modules predicted high-risk patients in multivariate analyses for the basal-like (HR: 2.19, p=2.5×10⁻⁴), luminal A (HR: 3.03, p=7.2×10⁻⁵), luminal B (HR: 3.00, p=2.4×10⁻¹⁰) and HER2+ (HR: 5.49, p=9.7×10⁻¹⁰) subgroups. We found that different modules are associated with DMFS in different BC subtypes. The results of this study could help to identify new therapeutic strategies for specific molecular subgroups of BC, and could enhance efforts to improve patient-specific therapy options.