The molecular portraits of breast tumors are conserved across microarray platforms

Glycosylation defects, offset by PEPCK-M, drive entosis in breast carcinoma cells

On glucose restriction, epithelial cells can undergo entosis, a cell-in-cell cannibalistic process, to allow considerable withstanding to this metabolic stress. Thus, we hypothesized that reduced protein glycosylation might participate in the activation of this cell survival pathway. Glucose deprivation promoted entosis in an MCF7 breast carcinoma model, as evaluated by direct inspection under the microscope, or revealed by a shift to apoptosis + necrosis in cells undergoing entosis treated with a Rho-GTPase kinase inhibitor (ROCKi). In this context, curbing protein glycosylation defects with N-acetyl-glucosamine partially rescued entosis, whereas limiting glycosylation in the presence of glucose with tunicamycin or NGI-1, but not with other unrelated ER-stress inducers such as thapsigargin or amino-acid limitation, stimulated entosis. Mitochondrial phosphoenolpyruvate carboxykinase (PEPCK-M; PCK2) is upregulated by glucose deprivation, thereby enhancing cell survival. Therefore, we presumed that PEPCK-M could play a role in this process by offsetting key metabolites into glycosyl moieties using alternative substrates. PEPCK-M inhibition using iPEPCK-2 promoted entosis in the absence of glucose, whereas its overexpression inhibited entosis. PEPCK-M inhibition had a direct role on total protein glycosylation as determined by Concanavalin A binding, and the specific ratio of fully glycosylated LAMP1 or E-cadherin. The content of metabolites, and the fluxes from ¹³C-glutamine label into glycolytic intermediates up to glucose-6-phosphate, and ribose- and ribulose-5-phosphate, was dependent on PEPCK-M content as measured by GC/MS. All in all, we demonstrate for the first time that protein glycosylation defects precede and initiate the entosis process and implicates PEPCK-M in this survival program to dampen the consequences of glucose deprivation. These results have broad implications to our understanding of tumor metabolism and treatment strategies.

Loss of RPTPγ primes breast tissue for acid extrusion, promotes malignant transformation and results in early tumour recurrence and shortened survival

BACKGROUND

While cellular metabolism and acidic waste handling accelerate during breast carcinogenesis, temporal patterns of acid-base regulation and underlying molecular mechanisms responding to the tumour microenvironment remain unclear.

METHODS

We explore data from human cohorts and experimentally investigate transgenic mice to evaluate the putative extracellular HCO₃^--sensor Receptor Protein Tyrosine Phosphatase (RPTP)γ during breast carcinogenesis.

RESULTS

RPTPγ expression declines during human breast carcinogenesis and particularly in high-malignancy grade breast cancer. Low RPTPγ expression associates with poor prognosis in women with Luminal A or Basal-like breast cancer. RPTPγ knockout in mice favours premalignant changes in macroscopically normal breast tissue, accelerates primary breast cancer development, promotes malignant breast cancer histopathologies, and shortens recurrence-free survival. In RPTPγ knockout mice, expression of Na⁺,HCO₃^--cotransporter NBCn1-a breast cancer susceptibility protein-is upregulated in normal breast tissue but, contrary to wild-type mice, shows no further increase during breast carcinogenesis. Associated augmentation of Na⁺,HCO₃^--cotransport in normal breast tissue from RPTPγ knockout mice elevates steady-state intracellular pH, which has known pro-proliferative effects.

CONCLUSIONS

Loss of RPTPγ accelerates cellular net acid extrusion and elevates NBCn1 expression in breast tissue. As these effects precede neoplastic manifestations in histopathology, we propose that RPTPγ-dependent enhancement of Na⁺,HCO₃^--cotransport primes breast tissue for cancer development.

Epstein-Barr Virus Association with Breast Cancer: Evidence and Perspectives

Epstein-Barr virus (EBV) is an enveloped DNA virus that belongs to the gamma Herpesviridae family. The virus establishes a latent/lytic persistent infection, though it can be involved in cancer development in some subjects. Indeed, evidence supports an etiological role of EBV in undifferentiated nasopharyngeal carcinoma (NPC), a subset of gastric carcinomas and lymphomas. Additionally, EBV has been detected in breast carcinomas (BCs) although its role has not been established. In this review, we summarize epidemiological information regarding the presence of EBV in BC and we propose mechanistic models. However, additional epidemiological and experimental evidence is warranted to confirm these models.

Reassessment of Reliability and Reproducibility for Triple-Negative Breast Cancer Subtyping

Simple Summary

Triple-negative breast cancer (TNBC) is a heterogeneous disease. A proper classification system is needed to develop targetable biomarkers and guide personalized treatment in clinical practice. However, there has been no consensus on the molecular subtypes of TNBC, probably due to discrepancies in technical and computational methods chosen by different research groups. In this paper, we reassessed each major step for TNBC subtyping and provided suggestions, which promote rational workflow design and ensure reliable and reproducible results for future studies. We presented a recommended pipeline to the existing data, validated established TNBC subtypes with a larger sample size, and revealed two intermediate subtypes with prognostic significance. This work provides perspectives on issues and limitations regarding TNBC subtyping, indicating promising directions for developing targeted therapy based on the molecular characteristics of each TNBC subtype.

Abstract

Triple-negative breast cancer (TNBC) is a heterogeneous disease with diverse, often poor prognoses and treatment responses. In order to identify targetable biomarkers and guide personalized care, scientists have developed multiple molecular classification systems for TNBC based on transcriptomic profiling. However, there is no consensus on the molecular subtypes of TNBC, likely due to discrepancies in technical and computational methods used by different research groups. Here, we reassessed the major steps for TNBC subtyping, validated the reproducibility of established TNBC subtypes, and identified two more subtypes with a larger sample size. By comparing results from different workflows, we demonstrated the limitations of formalin-fixed, paraffin-embedded samples, as well as batch effect removal across microarray platforms. We also refined the usage of computational tools for TNBC subtyping. Furthermore, we integrated high-quality multi-institutional TNBC datasets (discovery set: n = 457; validation set: n = 165). Performing unsupervised clustering on the discovery and validation sets independently, we validated four previously discovered subtypes: luminal androgen receptor, mesenchymal, immunomodulatory, and basal-like immunosuppressed. Additionally, we identified two potential intermediate states of TNBC tumors based on their resemblance with more than one well-characterized subtype. In summary, we addressed the issues and limitations of previous TNBC subtyping through comprehensive analyses. Our results promote the rational design of future subtyping studies and provide new insights into TNBC patient stratification.

Global Increase in Breast Cancer Incidence: Risk Factors and Preventive Measures

Breast cancer is a global cause for concern owing to its high incidence around the world. The alarming increase in breast cancer cases emphasizes the management of disease at multiple levels. The management should start from the beginning that includes stringent cancer screening or cancer registry to effective diagnostic and treatment strategies. Breast cancer is highly heterogeneous at morphology as well as molecular levels and needs different therapeutic regimens based on the molecular subtype. Breast cancer patients with respective subtype have different clinical outcome prognoses. Breast cancer heterogeneity emphasizes the advanced molecular testing that will help on-time diagnosis and improved survival. Emerging fields such as liquid biopsy and artificial intelligence would help to under the complexity of breast cancer disease and decide the therapeutic regimen that helps in breast cancer management. In this review, we have discussed various risk factors and advanced technology available for breast cancer diagnosis to combat the worst breast cancer status and areas that need to be focused for the better management of breast cancer.

Hypoxia Drives Centrosome Amplification in Cancer Cells via HIF1α-dependent Induction of Polo-Like Kinase 4

Centrosome amplification (CA) has been implicated in the progression of various cancer types. Although studies have shown that overexpression of PLK4 promotes CA, the effect of tumor microenvironment on polo-like kinase 4 (PLK4) regulation is understudied. The aim of this study was to examine the role of hypoxia in promoting CA via PLK4. We found that hypoxia induced CA via hypoxia-inducible factor-1α (HIF1α). We quantified the prevalence of CA in tumor cell lines and tissue sections from breast cancer, pancreatic ductal adenocarcinoma (PDAC), colorectal cancer, and prostate cancer and found that CA was prevalent in cells with increased HIF1α levels under normoxic conditions. HIF1α levels were correlated with the extent of CA and PLK4 expression in clinical samples. We analyzed the correlation between PLK4 and HIF1A mRNA levels in The Cancer Genome Atlas (TCGA) datasets to evaluate the role of PLK4 and HIF1α in breast cancer and PDAC prognosis. High HIF1A and PLK4 levels in patients with breast cancer and PDAC were associated with poor overall survival. We confirmed PLK4 as a transcriptional target of HIF1α and demonstrated that in PLK4 knockdown cells, hypoxia-mimicking agents did not affect CA and expression of CA-associated proteins, underscoring the necessity of PLK4 in HIF1α-related CA. To further dissect the HIF1α-PLK4 interplay, we used HIF1α-deficient cells overexpressing PLK4 and showed a significant increase in CA compared with HIF1α-deficient cells harboring wild-type PLK4. These findings suggest that HIF1α induces CA by directly upregulating PLK4 and could help us risk-stratify patients and design new therapies for CA-rich cancers.

IMPLICATIONS

Hypoxia drives CA in cancer cells by regulating expression of PLK4, uncovering a novel HIF1α/PLK4 axis.

Gpr125 is a unifying hallmark of multiple mammary progenitors coupled to tumor latency

Gpr125 is an orphan G-protein coupled receptor, with homology to cell adhesion and axonal guidance factors, that is implicated in planar polarity and control of cell movements. By lineage tracing we demonstrate that Gpr125 is a highly specific marker of bipotent mammary stem cells in the embryo and of multiple long-lived unipotent basal mammary progenitors in perinatal and postnatal glands. Nipple-proximal Gpr125+ cells express a transcriptomic profile indicative of chemo-repulsion and cell movement, whereas Gpr125+ cells concentrated at invasive ductal tips display a hybrid epithelial-mesenchymal phenotype and are equipped to bind chemokine and growth factors and secrete a promigratory matrix. Gpr125 progenitors acquire bipotency in the context of transplantation and cancer and are greatly expanded and massed at the pushing margins of short latency MMTV-Wnt1 tumors. High Gpr125 expression identifies patients with particularly poor outcome within the basal breast cancer subtype highlighting its potential utility as a factor to stratify risk.

Gpr125 has emerged as a specific marker of mammary stem cells and basal progenitors. Here they show that Gpr125 cells congregate at ductal tips during morphogenesis and amass at tumor margins, and that high Gpr125 predicts early tumor onset and poor outcome in basal breast cancer.

The extended concurrent genes signature for disease-free survival in breast cancer

BACKGROUND/PURPOSE

Previously we had identified concurrent genes, which highlighted the interplay between copy number variation (CNV) and differential gene expression (GE) for Han Chinese breast cancers. The merit of the approach is to discovery biomarkers not identifiable by conventional GE only data, for which phenotype-correlation or gene variability is the criteria of gene selection.

MATERIALS AND METHODS

Thirty-one comparative genomic hybridization (CGH) and 83 GE microarrays were performed, with 29 breast cancers assayed from both platforms. Potential targets were revealed by Genomic Identification of Significant Targets in Cancer (GISTIC) from CGH arrays. Concurrent genes and genes with significant GISTIC scores were used to derive the extended concurrent genes signature, which was consensus from leading edge analysis across all studies and a supervised partial least square (PLS) regression predictive model of disease-free survival was constructed.

RESULTS

There were 1584 concurrent genes from 29 samples with both CGH and GE microarrays. Enriched concurrent genes sets for disease-free survival were identified independently from 83 GE arrays and another one with Han Chinese origin as well as three studies of Western origin. For five studies with disease-free survival follow up, prognostic discrepancy was observed between predicted high-risk and low-risk group patients.

CONCLUSION

We concluded that through parallel analyses of CGH and GE microarrays, the proposed extended concurrent gene expression signature can identify biomarkers with prognostic values.

A chemokine regulatory loop induces cholesterol synthesis in lung-colonizing triple-negative breast cancer cells to fuel metastatic growth

Triple-negative breast cancer (TNBC) has a high propensity for organ-specific metastasis. However, the underlying mechanisms are not well understood. Here we show that the primary TNBC tumor-derived C-X-C motif chemokines 1/2/8 (CXCL1/2/8) stimulate lung-resident fibroblasts to produce the C-C motif chemokines 2/7 (CCL2/7), which, in turn, activate cholesterol synthesis in lung-colonizing TNBC cells and induce angiogenesis at lung metastatic sites. Inhibiting cholesterol synthesis in lung-colonizing breast tumor cells by pulmonary administration of simvastatin-carrying HER3-targeting nanoparticles reduces angiogenesis and growth of lung metastases in a syngeneic TNBC mouse model. Our findings reveal a novel, chemokine-regulated mechanism for the cholesterol synthesis pathway and a critical role of metastatic site-specific cholesterol synthesis in the pulmonary tropism of TNBC metastasis. The study has implications for the unresolved epidemiological observation that use of cholesterol-lowering drugs has no effect on breast cancer incidence but can unexpectedly reduce breast cancer mortality, suggesting interventions of cholesterol synthesis in lung metastases as an effective treatment to improve survival in individuals with TNBC.

Human Microbiota and Immunotherapy in Breast Cancer - A Review of Recent Developments

Breast cancer (BC) is the most common malignancy and the second cause of cancer-specific death in women from high-income countries. Infectious agents are the third most important risk factor for cancer incidence after tobacco and obesity. Dysbiosis emerged as a key player that may influence cancer development, treatment, and prognosis through diverse biological processes. Metastatic BC has a highly variable clinical course, and more recently, immune checkpoint inhibitors (ICIs) have become an emerging therapy in BC. Even with standardised treatment protocols, patients do not respond similarly, reflecting each individual´s heterogeneity, unique BC features, and tumour microenvironment. However, there is insufficient data regarding predictive factors of response to available treatments for BC. The microbiota could be a crucial piece of the puzzle to anticipate better individual BC risk and prognosis, pharmacokinetics, pharmacodynamics, and clinical efficacy. In recent years, it has been shown that gut microbiota may modulate cancer treatments' efficacy and adverse effects, and it is also apparent that both cancer itself and anticancer therapies interact with gut microbiota bidirectionally. Moreover, it has been proposed that certain gut microbes may protect the host against inappropriate inflammation and modulate the immune response. Future clinical research will determine if microbiota may be a prognostic and predictive factor of response to ICI and/or its side effects. Also, modulation of microbiota can be used to improve outcomes in BC patients. In this review, we discuss the potential implications of metabolomics and pharmacomicrobiomics that might impact BC immunotherapy treatment.

Spectrum of MAP3K1 mutations in breast cancer is luminal subtype-predominant and related to prognosis

MAP3K1 is a MAPK family serine-threonine kinase that is frequently mutated in human cancer. The association between mutations in the MAP3K1 gene and the clinicopathological characteristics and prognosis of patients with breast cancer remain unclear in the Chinese population. Thus, the aim of the present retrospective study was to investigate the possible role and function of MAP3K1 in breast cancer. Data obtained from 412 consecutive patients with breast cancer were selected from Guangdong Provincial People's Hospital (GDPH) for analysis in the present study. Mutations were assessed using next-generation sequencing. The association between MAP3K1 mutations and clinicopathological features were analyzed and further compared with the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort and data from The Cancer Genome Atlas (TCGA). In the GDPH cohort, a total of 45 mutations MAP3K1 were identified in 8.5% (n=35) of the 412 patients, compared with 9.7% (n=244) in METABRIC and 7.9% (n=88) in TCGA. The majority of the mutations identified in the in three cohorts were truncating mutations, followed by mis-sense mutations. Mutations in MAP3K1 were predominant in patients with the luminal A and B breast cancer subtypes in METABRIC datasets (P<0.001), although no significant differences were observed in the GDPH cohort (P=0.227). In the METABRIC cohort, patients with MAP3K1 mutations experienced a improved overall survival (OS) rate than patients without MAP3K1 mutations (P=0.006). In patient with hormone receptor (HR)⁺ breast cancer, a more significantly higher OS rate was observed in patients with MAP3K1 mutations (P<0.001). MAP3K1 expression was associated with OS in the HR⁺ subgroup. Moreover, the MAP3K1 methylation levels were reduced in primary breast cancer tissue, compared with normal tissue. Thus, the present findings identified MAP3K1 mutations in Chinese patients with breast cancer, and compared MAP3K1 mutations between the cohorts from Western and Eastern countries.

Breast cancer metastasis: immune profiling of lymph nodes reveals exhaustion of effector T cells and immunosuppression

Sentinel lymph nodes are the first nodes draining the lymph from a breast and could reveal early changes in the host immune system upon dissemination of breast cancer cells. To investigate this, we performed single-cell immune profiling of lymph nodes with and without metastatic cells. Whereas no significant changes were observed for B-cell and natural killer (NK)-cell subsets, metastatic lymph nodes had a significantly increased frequency of CD8 T cells and a skewing toward an effector/memory phenotype of CD4 and CD8 T cells, suggesting an ongoing immune response. Additionally, metastatic lymph nodes had an increased frequency of TIGIT (T-cell immunoreceptor with Ig and ITIM domains)-positive T cells with suppressed TCR signaling compared with non-metastatic nodes, indicating exhaustion of effector T cells, and an increased frequency of regulatory T cells (Tregs) with an activated phenotype. T-cell alterations correlated with the percentage of metastatic tumor cells, reflecting the presence of metastatic tumor cells driving T effector cells toward exhaustion and promoting immunosuppression by recruitment or increased differentiation toward Tregs. These results show that immune suppression occurs already in early stages of tumor progression.

Identification of Crucial lncRNAs for Luminal A Breast Cancer through RNA Sequencing

BACKGROUND

The growing body of evidence indicates aberrant expression of long noncoding RNAs (lncRNAs) in breast cancer. Nevertheless, a few studies have focused on identifying key lncRNAs for patients with luminal A breast cancer. In our study, we tried to find key lncRNAs and mRNAs in luminal A breast cancer.

METHODS

RNA sequencing was performed to identify differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs) in luminal A breast cancer. The protein-protein interaction (PPI), DElncRNA-DEmRNA coexpression, DElncRNA-nearby DEmRNA interaction networks, and functional annotation were performed to uncover the function of DEmRNAs. Online databases were used to validate the RNA sequencing result. The diagnostic value of candidate mRNAs was evaluated by receiver operating characteristic (ROC) curve analysis.

RESULTS

A total number of 1451 DEmRNAs and 272 DElncRNAs were identified. Several hub proteins were identified in the PPI network, including TUBB3, HIST2H3C, MCM2, MYOC, NEK2, LIPE, FN1, FOXJ1, S100A7, and DLK1. In the DElncRNA-DEmRNA coexpression, some hub lncRNAs were identified, including AP001528.2, LINC00968, LINC02202, TRHDE-AS1, LINC01140, AL354707.1, AC097534.1, MIR222HG, and AL662844.4. The mRNA expression result of TFF1, COL10A1, LEP, PLIN1, PGM5-AS1, and TRHDE-AD1 in the GSE98793 was consistent with the RNA sequencing result. The protein expression results of TUBB3, MCM2, MYOC, FN1, S100A7, and TFF1 were consistent with the mRNA expression result COL10A1, LEP, PLIN1, PGM5-AS1, and TRHDE-AD1 were capable of discriminating luminal A breast cancer and normal controls. Four lncRNA-nearby and coexpressed mRNA pairs of HOXC-AS3-HOXC10, AC020907.2-FXYD1, AC026461.1-MT1X, and AC132217.1-IGF2 were identified. AMPK (involved LIPE and LEP) and PPAR (involved PLIN1) were two significantly enriched pathways in luminal A breast cancer.

CONCLUSION

This study could be helpful in unraveling the pathogenesis and providing novel therapeutic strategies for luminal A breast cancer.

A Competitive Endogenous RNA Network Based on Differentially Expressed lncRNA in Lipopolysaccharide-Induced Acute Lung Injury in Mice

Non-coding RNAs have remarkable roles in acute lung injury (ALI) initiation. Nevertheless, the significance of long non-coding RNAs (lncRNAs) in ALI is still unknown. Herein, we purposed to identify potential key genes in ALI and create a competitive endogenous RNA (ceRNA) modulatory network to uncover possible molecular mechanisms that affect lung injury. We generated a lipopolysaccharide-triggered ALI mouse model, whose lung tissue was subjected to RNA sequencing, and then we conducted bioinformatics analysis to select genes showing differential expression (DE) and to build a lncRNA-miRNA (microRNA)- mRNA (messenger RNA) modulatory network. Besides, GO along with KEGG assessments were conducted to identify major biological processes and pathways, respectively, involved in ALI. Then, RT-qPCR assay was employed to verify levels of major RNAs. A protein-protein interaction (PPI) network was created using the Search Tool for the Retrieval of Interacting Genes (STRING) database, and the hub genes were obtained with the Molecular Complex Detection plugin. Finally, a key ceRNA subnetwork was built from major genes and their docking sites. Overall, a total of 8,610 lncRNAs were identified in the normal and LPS groups. Based on the 308 DE lncRNAs [p-value < 0.05, |log2 (fold change) | > 1] and 3,357 DE mRNAs [p-value < 0.05, |log2 (fold change) | > 1], lncRNA-miRNA and miRNA-mRNA pairs were predicted using miRanda. The lncRNA-miRNA-mRNA network was created from 175 lncRNAs, 22 miRNAs, and 209 mRNAs in ALI. The RT-qPCR data keep in step with the RNA sequencing data. GO along with KEGG analyses illustrated that DE mRNAs in this network were mainly bound up with the inflammatory response, developmental process, cell differentiation, cell proliferation, apoptosis, and the NF-kappa B, PI3K-Akt, HIF-1, MAPK, Jak-STAT, and Notch signaling pathways. A PPI network on the basis of the 209 genes was established, and three hub genes (Nkx2-1, Tbx2, and Atf5) were obtained from the network. Additionally, a lncRNA-miRNA-hub gene subnetwork was built from 15 lncRNAs, 3 miRNAs, and 3 mRNAs. Herein, novel ideas are presented to expand our knowledge on the regulation mechanisms of lncRNA-related ceRNAs in the pathogenesis of ALI.

mRNA expression of specific HER ligands and their association with clinical outcome in patients with metastatic breast cancer treated with trastuzumab

Prognostic and predictive biomarkers are being studied for the diagnosis and treatment of breast cancer. The present study retrospectively assessed the mRNA expression of HER family receptor ligands and of other potential prognostic biomarkers and their association with time to progression (TTP), survival and clinicopathological characteristics in patients with metastatic breast cancer (MBC) treated with trastuzumab. A total of 145 tumour tissue samples were analysed. mRNA expression analysis of the transcripts of interest was performed and the association of these markers with selected clinicopathological parameters was examined. HER2 status was centrally re-evaluated. Only 67.6% of patients were truly HER2-positive according to the central HER2 re-evaluation. Heparin binding epidermal growth factor (EGF)-like growth factor, transforming growth factor β1 (TGFB1) and thyroid hormone receptor α (THRA) mRNA expression was higher in HER2-positive patients (P=0.026, P<0.001 and P<0.001). Insulin-like growth factor binding protein 4 was correlated with retinoic acid receptor α, TGFB1 and THRA (rho=0.45, rho=0.60 and rho=0.45). In HER2-positive patients, high neuregulin 1 and high betacellulin were unfavourable factors for TTP [hazard ratio (HR) = 1.78, P=0.040 and HR=2.00, P=0.043, respectively]. In patients with de novo MBC, high EGF expression was associated with a non-significant prolongation of TTP (HR=0.52, P=0.080) and significantly longer survival (HR=0.40, P=0.020). The present study examined clinical and biological implications of specific genes and it was concluded that their expression has an impact on the outcome of trastuzumab-treated patients with MBC.

Mammary collagen is under reproductive control with implications for breast cancer

Mammographically-detected breast density impacts breast cancer risk and progression, and fibrillar collagen is a key component of breast density. However, physiologic factors influencing collagen production in the breast are poorly understood. In female rats, we analyzed gene expression of the most abundantly expressed mammary collagens and collagen-associated proteins across a pregnancy, lactation, and weaning cycle. We identified a triphasic pattern of collagen gene regulation and evidence for reproductive state-dependent composition. An initial phase of collagen deposition occurred during pregnancy, followed by an active phase of collagen suppression during lactation. The third phase of collagen regulation occurred during weaning-induced mammary gland involution, which was characterized by increased collagen deposition. Concomitant changes in collagen protein abundance were confirmed by Masson's trichrome staining, second harmonic generation (SHG) imaging, and mass spectrometry. We observed similar reproductive-state dependent collagen patterns in human breast tissue obtained from premenopausal women. SHG analysis also revealed structural variation in collagen across a reproductive cycle, with higher packing density and more collagen fibers arranged perpendicular to the mammary epithelium in the involuting rat mammary gland compared to nulliparous and lactating glands. Involution was also characterized by high expression of the collagen cross-linking enzyme lysyl oxidase, which was associated with increased levels of cross-linked collagen. Breast cancer relevance is suggested, as we found that breast cancer diagnosed in recently postpartum women displayed gene expression signatures of increased collagen deposition and crosslinking compared to breast cancers diagnosed in age-matched nulliparous women. Using publically available data sets, we found this involution-like, collagen gene signature correlated with poor progression-free survival in breast cancer patients overall and in younger women. In sum, these findings of physiologic collagen regulation in the normal mammary gland may provide insight into normal breast function, the etiology of breast density, and inform breast cancer risk and outcomes.

A comparison of rule-based and centroid single-sample multiclass predictors for transcriptomic classification

MOTIVATION

Gene expression-based multiclass prediction, such as tumor subtyping, is a non-trivial bioinformatic problem. Most classifier methods operate by comparing expression levels relative to other samples. Methods that base predictions on the expression pattern within a sample have been proposed as an alternative. As these methods are invariant to the cohort composition and can be applied to a sample in isolation, they can collectively be termed single sample predictors (SSP). Such predictors could potentially be used for preprocessing-free classification of new samples and be built to function across different expression platforms where proper batch and dataset normalization is challenging. Here, we evaluate the behavior of several multiclass SSPs based on binary gene-pair rules (k-Top Scoring Pairs, Absolute Intrinsic Molecular Subtyping and a new Random Forest approach) and compare them to centroids built with centered or raw expression values, with the criteria that an optimal predictor should have high accuracy, overcome differences in tumor purity, be robust across expression platforms and provide an informative prediction output score.

RESULTS

We found that gene-pair-based SSPs showed excellent performance on many expression-based classification tasks. The three methods differed in prediction score output, handling of tied scores and behavior in low purity samples. The k-Top Scoring Pairs and Random Forest approach both achieved high classification accuracy while providing an informative prediction score. Although gene-pair-based SSPs have been touted as being cross-platform compatible (through training on mixed platform data), out-of-the-box compatibility with a new dataset remains a potential issue that warrants cohort-to-cohort verification.

AVAILABILITY AND IMPLEMENTATION

Our R package 'multiclassPairs' (https://cran.r-project.org/package=multiclassPairs) (https://doi.org/10.1093/bioinformatics/btab088) is freely available and enables easy training, prediction, and visualization using the gene-pair rule-based Random Forest SSP method and provides additional multiclass functionalities to the switchBox k-Top-Scoring Pairs package.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Triple-negative breast cancer and basal-like subtype : Pathology and targeted therapy

Triple-negative breast cancer (TNBC) is a heterogenous disease. For personalized medicine, it is essential to identify and classify tumor subtypes to develop effective therapeutic strategies. Although gene expression profiling has identified several TNBC subtypes, classification of these tumors remains complex. Most TNBCs exhibit an aggressive phenotype, but some rare types have a favorable clinical course. In this review, we summarize the classification and characteristics related to the various TNBC subtypes, including the rare types. Therapeutic methods that are suitable for each subtype are also discussed. Of the intrinsic breast cancer subtypes identified by gene expression analysis, the basal-like subtype specifically displayed decreased expression of an estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) cluster. We also present results that characterize the TNBC and basal-like phenotypes. TNBC may be categorized into four major classes : basal-like, immune-enriched, mesenchymal, and luminal androgen receptor. Therapeutic strategies for each subtype have been proposed along with newly approved targeted therapies for TNBC, such as immune checkpoint inhibitors. Understanding the classification of TNBC based on gene expression profiling in association with clinicopathological factors will facilitate accurate pathological diagnosis and effective treatment selection. J. Med. Invest. 68 : 213-219, August, 2021.

Postpartum breast cancer has a distinct molecular profile that predicts poor outcomes

Young women's breast cancer (YWBC) has poor prognosis and known interactions with parity. Women diagnosed within 5-10 years of childbirth, defined as postpartum breast cancer (PPBC), have poorer prognosis compared to age, stage, and biologic subtype-matched nulliparous patients. Genomic differences that explain this poor prognosis remain unknown. In this study, using RNA expression data from clinically matched estrogen receptor positive (ER+) cases (n = 16), we observe that ER+ YWBC can be differentiated based on a postpartum or nulliparous diagnosis. The gene expression signatures of PPBC are consistent with increased cell cycle, T-cell activation and reduced estrogen receptor and TP53 signaling. When applied to a large YWBC cohort, these signatures for ER+ PPBC associate with significantly reduced 15-year survival rates in high compared to low expressing cases. Cumulatively these results provide evidence that PPBC is a unique entity within YWBC with poor prognostic phenotypes.

Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue

Lung cancer remains the leading cause of cancer death worldwide and non-small cell lung carcinoma (NSCLC) represents 85% of newly diagnosed lung cancers. In this study, we utilized our untargeted assignment tool Small Molecule Isotope Resolved Formula Enumerator (SMIRFE) and ultra-high-resolution Fourier transform mass spectrometry to examine lipid profile differences between paired cancerous and non-cancerous lung tissue samples from 86 patients with suspected stage I or IIA primary NSCLC. Correlation and co-occurrence analysis revealed significant lipid profile differences between cancer and non-cancer samples. Further analysis of machine-learned lipid categories for the differentially abundant molecular formulas identified a high abundance sterol, high abundance and high m/z sphingolipid, and low abundance glycerophospholipid metabolic phenotype across the NSCLC samples. At the class level, higher abundances of sterol esters and lower abundances of cardiolipins were observed suggesting altered stearoyl-CoA desaturase 1 (SCD1) or acetyl-CoA acetyltransferase (ACAT1) activity and altered human cardiolipin synthase 1 or lysocardiolipin acyltransferase activity respectively, the latter of which is known to confer apoptotic resistance. The presence of a shared metabolic phenotype across a variety of genetically distinct NSCLC subtypes suggests that this phenotype is necessary for NSCLC development and may result from multiple distinct genetic lesions. Thus, targeting the shared affected pathways may be beneficial for a variety of genetically distinct NSCLC subtypes.

Microarray analysis of differentially expressed long non-coding RNAs in daidzein-treated lung cancer cells

Daidzein has been found to significantly inhibit the proliferation of lung cancer cells, while its potential molecular mechanisms remain unclear. To determine the molecular mechanism of daidzein on lung cancer cells, the Capital Bio Technology Human long non-coding (lnc) RNA Array v4, 4×180K chip was used to detect the gene expression profiles of 40,000 lncRNAs and 34,000 mRNAs in a human cancer cell line. Reverse transcription-quantitative (RT-q) PCR analysis was performed to detect the expression levels of target lncRNA and mRNAs in the H1299 cells treated with and without daidzein, using the lncRNA and mRNA gene chip. Bioinformatics analysis was performed to determine the differentially expressed genes from the results of the chip assays. There were 119 and 40 differentially expressed lncRNAs and mRNAs, respectively, that had a 2-fold change in expression level. A total of eight lncRNAs were upregulated in the H1299 lung cancer cells, while 111 lncRNAs were downregulated. Furthermore, five mRNAs were upregulated, and 35 mRNAs were downregulated. A total of six differentially expressed lncRNAs (ENST00000608897.1, ENST00000444196.1, ENST00000608741.1, XR_242163.1, ENST00000505196.1 and ENST00000498032.1) were randomly selected to validate the microarray data, which were consistent with the RT-qPCR analysis results. Differentially expressed mRNAs were enriched in important Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. Taken together, the results of the present study demonstrated that daidzein affected the expression level of lncRNAs in lung cancer cells, suggesting that daidzein may have potential effects on lung cancer cells.

Analysis of breast cancer subtypes and their correlations with receptors and ultrasound

The study aim was to evaluate the ultrasound (US) signs of the mammary lesions classified in the Breast Imaging-Reporting and Data System (BI-RADS) score category 3, 4, and 5, corresponding to US BI-RADS. It also followed the correlation between US changes of lesions suggestive for malignancy with the histopathological results and evaluated the proper management of those lesions. There were correlations of breast cancer (BC) subtypes with the receptors [estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2)], and Ki67 index, and the signs of conventional ultrasonography and US elastography. We selected 108 female patients examined with US, mammography and fine-needle biopsy who presented suspicions for malignancy lesions. Following the immunohistochemical analysis, they were classified in one of the BC subtypes. According to chi-squared analysis of molecular cancer subtypes correlation to receptors and Ki67 index, we found significant associations between both luminal A and luminal B HER2-negative subtypes and hormone receptors (ER, PR). These have an inverse relationship with Ki67 index elevated values; luminal B HER2-positive subtype has a direct association with HER2 presence; HER2-enriched subtype was statistically significant associated to HER2 presence and elevated Ki67 index values but had an inverse relationship to hormone receptors (ER, PR); triple-negative subtype was strongly associated to Ki67 index values and inversely correlated to ER and PR. We found luminal A subtype as being the most common and luminal B HER2-positive subtype as having the fewer cases.

Triple-Negative Breast Cancer: Breast Tumors With an Identity Crisis

ABSTRACT

Triple-negative breast cancer (TNBC) is pathologically defined by lack of expression of the estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 amplification and portends an aggressive clinical course with worse outcomes compared with other breast cancers. Until recently, standard treatment options consisted of sequential cytotoxic chemotherapies for both early and metastatic disease. Advances in sequencing technology have led to the identification of 4 main subtypes of TNBC based on recurrent genetic alterations, transcriptional patterns, and molecular features: basal-like 1 (BL1), basal-like 2 (BL2), mesenchymal (M), and luminal androgen receptor (LAR). Frequent alterations found in DNA damage response pathways, germline and somatic BRCA1/2 genes, PI3K signaling pathways, and the presence of androgen receptors and infiltrating immune cells could serve as actionable targets to optimize treatments and improve outcomes for patients with TNBC. Recent approvals for immune checkpoint inhibitors and the antibody-drug conjugate, sacituzumab govitecan-hziy, for advanced TNBC illustrate the advances in treatment that can result from these molecular discoveries. This review will explore the molecular subtypes of TNBC and their distinct characteristics, as well as highlight the molecular features and potential "drivers" that have been identified as promising targets for new treatment strategies.

A matrisome RNA signature from early-pregnancy mouse mammary fibroblasts predicts distant metastasis-free breast cancer survival in humans

BACKGROUND

During pregnancy, the mouse mammary ductal epithelium branches and grows into the surrounding stroma, requiring extensive extracellular matrix (ECM) and tissue remodelling. It therefore shows parallels to cancer invasion. We hypothesised that similar molecular mechanisms may be utilised in both processes, and that assessment of the stromal changes during pregnancy-associated branching may depict the stromal involvement during human breast cancer progression.

METHODS

Immunohistochemistry (IHC) was employed to assess the alterations within the mouse mammary gland extracellular matrix during early pregnancy when lateral branching of the primary ductal epithelium is initiated. Primary mouse mammary fibroblasts from three-day pregnant and age-matched non-pregnant control mice, respectively, were 3D co-cultured with mammary epithelial cells to assess differences in their abilities to induce branching morphogenesis in vitro. Transcriptome analysis was performed to identify the underlying molecular changes. A signature of the human orthologues of the differentially expressed matrisome RNAs was analysed by Kaplan-Meier and multi-variate analysis in two large breast cancer RNA datasets (Gene expression-based Outcome for Breast cancer Online (GOBO) und Kaplan-Meier Plotter), respectively, to test for similarities in expression between early-pregnancy mouse mammary gland development and breast cancer progression.

RESULTS

The ECM surrounding the primary ductal network showed significant differences in collagen and basement membrane protein distribution early during pregnancy. Pregnancy-associated fibroblasts (PAFs) significantly enhanced branching initiation compared to age-matched control fibroblast. A combined signature of 64 differentially expressed RNAs, encoding matrisome proteins, was a strong prognostic indicator of distant metastasis-free survival (DMFS) independent of other clinical parameters. The prognostic power could be significantly strengthened by using only a subset of 18 RNAs (LogRank P ≤ 1.00e-13; Hazard ratio (HR) = 2.42 (1.8-3.26); p = 5.61e-09). The prognostic power was confirmed in a second breast cancer dataset, as well as in datasets from ovarian and lung cancer patients.

CONCLUSIONS

Our results describe for the first time the early stromal changes that accompany pregnancy-associated branching morphogenesis in mice, specify the early pregnancy-associated molecular alterations in mouse mammary fibroblasts, and identify a matrisome signature as a strong prognostic indicator of human breast cancer progression, with particular strength in oestrogen receptor (ER)-negative breast cancers.

Cancer Grade Model: a multi-gene machine learning-based risk classification for improving prognosis in breast cancer

BACKGROUND

Prognostic stratification of breast cancers remains a challenge to improve clinical decision making. We employ machine learning on breast cancer transcriptomics from multiple studies to link the expression of specific genes to histological grade and classify tumours into a more or less aggressive prognostic type.

MATERIALS AND METHODS

Microarray data of 5031 untreated breast tumours spanning 33 published datasets and corresponding clinical data were integrated. A machine learning model based on gradient boosted trees was trained on histological grade-1 and grade-3 samples. The resulting predictive model (Cancer Grade Model, CGM) was applied on samples of grade-2 and unknown-grade (3029) for prognostic risk classification.

RESULTS

A 70-gene signature for assessing clinical risk was identified and was shown to be 90% accurate when tested on known histological-grade samples. The predictive framework was validated through survival analysis and showed robust prognostic performance. CGM was cross-referenced with existing genomic tests and demonstrated the competitive predictive power of tumour risk.

CONCLUSIONS

CGM is able to classify tumours into better-defined prognostic categories without employing information on tumour size, stage, or subgroups. The model offers means to improve prognosis and support the clinical decision and precision treatments, thereby potentially contributing to preventing underdiagnosis of high-risk tumours and minimising over-treatment of low-risk disease.

Intrinsic Subtypes and Androgen Receptor Gene Expression in Primary Breast Cancer. A Meta-Analysis

The androgen receptor (AR) is frequently expressed in breast cancer (BC), but its association with clinical and biological parameters of BC patients remains unclear. Here, we investigated the association of AR gene expression according to intrinsic BC subtypes by meta-analysis of large-scale microarray transcriptomic datasets. Sixty-two datasets including 10315 BC patients were used in the meta-analyses. Interestingly, AR mRNA level is significantly increased in patients categorized with less aggressive intrinsic molecular subtypes including, Luminal A compared to Basal-like (standardized mean difference, SMD: 2.12; 95% confidence interval, CI: 1.88 to 2.35; p < 0.001) or when comparing Luminal B to Basal-like (SMD: 1.53; CI: 1.33 to 1.72; p < 0.001). The same trend was observed when analyses were performed using immunohistochemistry-based surrogate subtypes. Consistently, the AR mRNA expression was higher in patients with low histological grade (p < 0.001). Furthermore, our data revealed higher levels of AR mRNA in BC patients expressing either estrogen or progesterone receptors (p < 0.001). Together, our findings indicate that high mRNA levels of AR are associated with BC subgroups with the less aggressive clinical features.

Molecular subtyping of breast cancer intrinsic taxonomy with oligonucleotide microarray and NanoString nCounter

Breast cancer intrinsic subtypes have been identified based on the transcription of a predefined gene expression (GE) profiles and algorithm (PAM50). This study compared molecular subtyping with oligonucleotide microarray and NanoString nCounter assay. A total of 109 Taiwanese breast cancers (24 with adjacent normal breast tissues) were assayed with Affymetrix Human Genome U133 plus 2.0 microarrays and 144 were assayed with the NanoString nCounter while 64 patients were assayed for both platforms. Subtyping with the nearest centroid (single sample prediction) was performed, and 16 out of 24 (67%) matched normal breasts were categorized as the normal breast-like subtype. For 64 breast cancers assayed for both platforms, 41 (65%, one unclassified by microarray) were predicted with an identical subtype, resulting in a fair Kappa statistic of 0.60. Taking nCounter subtyping as the gold standard, prediction accuracy was 43% (3/7), 81% (13/16), 25% (5/20), and 100% (20/20) for basal-like, HER2-enriched, luminal A and luminal B subtype predicted from microarray GE profiles. Microarray identified more luminal B cases from luminal A subtype predicted by nCounter. It's not uncommon to use microarray for breast cancer molecular subtyping for research. Our study showed that fundamental discrepancy existed between distinct GE assays, and cross platform equivalence should be carefully appraised when molecular subtyping was conducted with oligonucleotide microarray.

Cross-reactivity of a pathogenic autoantibody to a tumor antigen in GABAA receptor encephalitis

Encephalitis associated with antibodies against the neuronal gamma-aminobutyric acid A receptor (GABA_A-R) is a rare form of autoimmune encephalitis. The pathogenesis is still unknown but autoimmune mechanisms were surmised. Here we identified a strongly expanded B cell clone in the cerebrospinal fluid of a patient with GABA_A-R encephalitis. We expressed the antibody produced by it and showed by enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry that it recognizes the GABA_A-R. Patch-clamp recordings revealed that it tones down inhibitory synaptic transmission and causes increased excitability of hippocampal CA1 pyramidal neurons. Thus, the antibody likely contributed to clinical disease symptoms. Hybridization to a protein array revealed the cross-reactive protein LIM-domain-only protein 5 (LMO5), which is related to cell-cycle regulation and tumor growth. We confirmed LMO5 recognition by immunoprecipitation and ELISA and showed that cerebrospinal fluid samples from two other patients with GABA_A-R encephalitis also recognized LMO5. This suggests that cross-reactivity between GABA_A-R and LMO5 is frequent in GABA_A-R encephalitis and supports the hypothesis of a paraneoplastic etiology.

Identification of Somatic Mutation-Driven Immune Cells by Integrating Genomic and Transcriptome Data

Tumor somatic mutations in protein-coding regions may generate neoantigens which may trigger antitumor immune cell response. Increasing evidence supports that immune cell response may profoundly influence tumor progression. However, there are no calculated tools to systematically identify immune cells driven by specific somatic mutations. It is urgent to develop a calculated method to comprehensively detect tumor-infiltrating immune cells driven by the specific somatic mutations in cancer. We developed a novel software package (SMDIC) that enables the automated identification of somatic mutation-driven immune cell. SMDIC provides a novel pipeline to discover mutation-specific immune cells by integrating genomic and transcriptome data. The operation modes include inference of the relative abundance matrix of tumor-infiltrating immune cells, detection of differential abundance immune cells with respect to the gene mutation status, conversion of the abundance matrix of significantly dysregulated cells into two binary matrices (one for upregulated and one for downregulated cells), identification of somatic mutation-driven immune cells by comparing the gene mutation status with each immune cell in the binary matrices across all samples, and visualization of immune cell abundance of samples in different mutation status for each gene. SMDIC provides a user-friendly tool to identify somatic mutation-specific immune cell response. SMDIC may contribute to understand the mechanisms underlying anticancer immune response and find targets for cancer immunotherapy. The SMDIC was implemented as an R-based tool which was freely available from the CRAN website https://CRAN.R-project.org/package=SMDIC.

Acid-base transporters and pH dynamics in human breast carcinomas predict proliferative activity, metastasis, and survival

Breast cancer heterogeneity in histology and molecular subtype influences metabolic and proliferative activity and hence the acid load on cancer cells. We hypothesized that acid-base transporters and intracellular pH (pH_i) dynamics contribute inter-individual variability in breast cancer aggressiveness and prognosis. We show that Na⁺,HCO₃^- cotransport and Na⁺/H⁺ exchange dominate cellular net acid extrusion in human breast carcinomas. Na⁺/H⁺ exchange elevates pH_i preferentially in estrogen receptor-negative breast carcinomas, whereas Na⁺,HCO₃^- cotransport raises pH_i more in invasive lobular than ductal breast carcinomas and in higher malignancy grade breast cancer. HER2-positive breast carcinomas have elevated protein expression of Na⁺/H⁺ exchanger NHE1/SLC9A1 and Na⁺,HCO₃^- cotransporter NBCn1/SLC4A7. Increased dependency on Na⁺,HCO₃^- cotransport associates with severe breast cancer: enlarged CO₂/HCO₃^--dependent rises in pH_i predict accelerated cell proliferation, whereas enhanced CO₂/HCO₃^--dependent net acid extrusion, elevated NBCn1 protein expression, and reduced NHE1 protein expression predict lymph node metastasis. Accordingly, we observe reduced survival for patients suffering from luminal A or basal-like/triple-negative breast cancer with high SLC4A7 and/or low SLC9A1 mRNA expression. We conclude that the molecular mechanisms of acid-base regulation depend on clinicopathological characteristics of breast cancer patients. NBCn1 expression and dependency on Na⁺,HCO₃^- cotransport for pH_i regulation, measured in biopsies of human primary breast carcinomas, independently predict proliferative activity, lymph node metastasis, and patient survival.

WBP2 promotes BTRC mRNA stability to drive migration and invasion in triple-negative breast cancer via NF-κB activation

WW‐domain‐binding protein 2 (WBP2) is an oncogene that drives breast carcinogenesis through regulating Wnt, estrogen receptor (ER), and Hippo signaling. Recent studies have identified neoteric modes of action of WBP2 other than its widely recognized function as a transcriptional coactivator. Here, we identified a previously unexplored role of WBP2 in inflammatory signaling in breast cancer via an integrated proteogenomic analysis of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA BRCA) dataset. WBP2 was shown to enhance the migration and invasion in triple‐negative breast cancer (TNBC) cells especially under tumor necrosis factor alpha (TNF‐α) stimulation. Molecularly, WBP2 potentiates TNF‐α‐induced nuclear factor kappa B (NF‐κB) transcriptional activity and nuclear localization through aggrandizing ubiquitin‐mediated proteasomal degradation of its upstream inhibitor, NF‐κB inhibitor alpha (NFKBIA; also known as IκBα). We further demonstrate that WBP2 induces mRNA stability of beta‐transducin repeat‐containing E3 ubiquitin protein ligase (BTRC), which targets IκBα for ubiquitination and degradation. Disruption of IκBα rescued the impaired migratory and invasive phenotypes in WBP2‐silenced cells, while loss of BTRC ameliorated WBP2‐driven migration and invasion. Clinically, the WBP2‐BTRC‐IκBα signaling axis correlates with poorer prognosis in breast cancer patients. Our findings reveal a pivotal mechanism of WBP2 in modulating BTRC‐IκBα‐NF‐κB pathway to promote TNBC aggressiveness.

Triple-negative breast cancer: A run-through of features, classification and current therapies

Breast cancer is the most prevalent cancer in women worldwide. Triple-negative breast cancer (TNBC) is characterized by the lack of expression of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. It is the most aggressive subtype of breast cancer and accounts for 12-20% of all breast cancer cases. TNBC is associated with younger age of onset, greater metastatic potential, higher incidence of relapse, and lower overall survival rates. Based on molecular phenotype, TNBC has been classified into six subtypes (BL1, BL2, M, MES, LAR, and IM). TNBC treatment is challenging due to its heterogeneity, highly invasive nature, and relatively poor therapeutics response. Chemotherapy and radiotherapy are conventional strategies for the treatment of TNBC. Recent research in TNBC and mechanistic understanding of disease pathogenesis using cutting-edge technologies has led to the unfolding of new lines of therapies that have been incorporated into clinical practice. Poly (ADP-ribose) polymerase and immune checkpoint inhibitors have made their way to the current TNBC treatment paradigm. This review focuses on the classification, features, and treatment progress in TNBC. Histological subtypes connected to recurrence, molecular classification of TNBC, targeted therapy for early and advanced TNBC, and advances in non-coding RNA in therapy are the key highlights in this review.

Heterogeneity within molecular subtypes of breast cancer

Breast cancer is the quintessential example of how molecular characterization of tumor biology guides therapeutic decisions. From the discovery of the estrogen receptor to current clinical molecular profiles to evolving single-cell analytics, the characterization and compartmentalization of breast cancer into divergent subtypes is clear. However, competing with this divergent model of breast cancer is the recognition of intratumoral heterogeneity, which acknowledges the possibility that multiple different subtypes exist within a single tumor. Intratumoral heterogeneity is driven by both intrinsic effects of the tumor cells themselves as well as extrinsic effects from the surrounding microenvironment. There is emerging evidence that these intratumoral molecular subtypes are not static; rather, plasticity between divergent subtypes is possible. Interconversion between seemingly different subtypes within a tumor drives tumor progression, metastases, and treatment resistance. Therapeutic strategies must, therefore, contend with changing phenotypes in an individual patient's tumor. Identifying targetable drivers of molecular heterogeneity may improve treatment durability and disease progression.

Revealing nuclear receptor hub modules from Basal-like breast cancer expression networks

Nuclear receptors are a class of transcriptional factors. Together with their co-regulators, they regulate development, homeostasis, and metabolism in a ligand-dependent manner. Their ability to respond to environmental stimuli rapidly makes them versatile cellular components. Their coordinated activities regulate essential pathways in normal physiology and in disease. Due to their complexity, the challenge remains in understanding their direct associations in cancer development. Basal-like breast cancer is an aggressive form of breast cancer that often lacks ER, PR and Her2. The absence of these receptors limits the treatment for patients to the non-selective cytotoxic and cytostatic drugs. To identify potential drug targets it is essential to identify the most important nuclear receptor association network motifs in Basal-like subtype progression. This research aimed to reveal the transcriptional network patterns, in the hope to capture the underlying molecular state driving Basal-like oncogenesis. In this work, we illustrate a multidisciplinary approach of integrating an unsupervised machine learning clustering method with network modelling to reveal unique transcriptional patterns (network motifs) underlying Basal-like breast cancer. The unsupervised clustering method provides a natural stratification of breast cancer patients, revealing the underlying heterogeneity in Basal-like. Identification of gene correlation networks (GCNs) from Basal-like patients in both the TCGA and METABRIC databases revealed three critical transcriptional regulatory constellations that are enriched in Basal-like. These represent critical NR components implicated in Basal-like breast cancer transcription. This approach is easily adaptable and applicable to reveal critical signalling relationships in other diseases.

Molecular Classification and Future Therapeutic Challenges of Triple-negative Breast Cancer

Triple-negative breast cancer (TNBC) is an extremely diverse group of breast tumors, with aggressive clinical behavior, higher rates of distant recurrence and worse overall survival compared to other types of breast cancers. The genetic, transcriptional histological and clinical heterogeneity of this disease has been an obstacle in the progression of targeted therapeutic approaches, as a ubiquitous TNBC marker has not yet been discerned. In terms of that, current studies focus on the classification of TNBC tumors in subgroups with similar characteristics in order to develop a treatment specialized for each group of patients. To date, a series of gene expression profiles analysis in order to identify the different molecular subtypes have been used. Complementary DNA microarrays, PAM50 assays, DNA and RNA sequencing as well as immunohistochemical analysis are some of the methods utilized to classify TNBC tumors. In 2012, the Cancer Genome Atlas (TCGA) Research Network conducted a major analysis of breast cancers using six different platforms, the genomic DNA copy number arrays, DNA methylation, exome sequencing, messenger RNA arrays, microRNA sequencing and reverse-phase protein arrays, in order to assort the tumors in homogenous subgroups. Since then, an increasing number of breast cancer data sets are being examined in an attempt to distinguish the classification with biological interpretation and clinical implementation. In this review, the progress in molecular subtyping of TNBC is discussed, providing a brief insight in novel TNBC biomarkers and therapeutic strategies.

Highly connected, non-redundant microRNA functional control in breast cancer molecular subtypes

Breast cancer is a complex, heterogeneous disease at the phenotypic and molecular level. In particular, the transcriptional regulatory programs are known to be significantly affected and such transcriptional alterations are able to capture some of the heterogeneity of the disease, leading to the emergence of breast cancer molecular subtypes. Recently, it has been found that network biology approaches to decipher such abnormal gene regulation programs, for instance by means of gene co-expression networks, have been able to recapitulate the differences between breast cancer subtypes providing elements to further understand their functional origins and consequences. Network biology approaches may be extended to include other co-expression patterns, like those found between genes and non-coding transcripts such as microRNAs (miRs). As is known, miRs play relevant roles in the establishment of normal and anomalous transcription processes. Commodore miRs (cdre-miRs) have been defined as miRs that, based on their connectivity and redundancy in co-expression networks, are potential control elements of biological functions. In this work, we reconstructed miR–gene co-expression networks for each breast cancer molecular subtype, from high throughput data in 424 samples from the Cancer Genome Atlas consortium. We identified cdre-miRs in three out of four molecular subtypes. We found that in each subtype, each cdre-miR was linked to a different set of associated genes, as well as a different set of associated biological functions. We used a systematic literature validation strategy, and identified that the associated biological functions to these cdre-miRs are hallmarks of cancer such as angiogenesis, cell adhesion, cell cycle and regulation of apoptosis. The relevance of such cdre-miRs as actionable molecular targets in breast cancer is still to be determined from functional studies.

Co-expression of transcription factor AP-2beta (TFAP2B) and GATA3 in human mammary epithelial cells with intense, apicobasal immunoreactivity for CK8/18

AP-2β is a new mammary epithelial differentiation marker and its expression is preferentially retained and enhanced in lobular carcinoma in situ and invasive lobular breast cancer. In normal breast epithelium AP-2β is expressed in a scattered subpopulation of luminal cells. So far, these cells have not been further characterized. Co-expression of AP-2β protein and luminal epithelium markers (GATA3, CK8/18), hormone receptors [estrogen receptor (ER), androgen receptor (AR)] and candidate stem cells markers (CK5/14, CD44) were assessed by double-immunofluorescence staining in normal mammary gland epithelium. The subpopulation of AP-2β-positive mammary epithelial cells showed an almost complete, superimposable co-expression with GATA3 and a peculiar intense, ring-like appearing immunoreactivity for CK8/18. Confocal immunofluorescence microscopy revealed an apicobasal staining for CK8/18 in AP-2β-positive cells, which was not seen in in AP-2β-negative cells. Furthermore, AP-2β-positive displayed a partial co-expression with ER and AR, but lacked expression of candidate stem cell markers CK5/14 and CD44. In summary, AP-2β is a new luminal mammary epithelial differentiation marker, which is expressed in the GATA3-positive subpopulation of luminal epithelial cells. These AP-2β-positive/GATA3-positive cells also show a peculiar CK8/18-expression which may indicate a previously unknown functionally specialized mammary epithelial cell population.

FUT8-mediated aberrant N-glycosylation of B7H3 suppresses the immune response in triple-negative breast cancer

Most patients with triple negative breast cancer (TNBC) do not respond to anti-PD1/PDL1 immunotherapy, indicating the necessity to explore immune checkpoint targets. B7H3 is a highly glycosylated protein. However, the mechanisms of B7H3 glycosylation regulation and whether the sugar moiety contributes to immunosuppression are unclear. Here, we identify aberrant B7H3 glycosylation and show that N-glycosylation of B7H3 at NXT motif sites is responsible for its protein stability and immunosuppression in TNBC tumors. The fucosyltransferase FUT8 catalyzes B7H3 core fucosylation at N-glycans to maintain its high expression. Knockdown of FUT8 rescues glycosylated B7H3-mediated immunosuppressive function in TNBC cells. Abnormal B7H3 glycosylation mediated by FUT8 overexpression can be physiologically important and clinically relevant in patients with TNBC. Notably, the combination of core fucosylation inhibitor 2F-Fuc and anti-PDL1 results in enhanced therapeutic efficacy in B7H3-positive TNBC tumors. These findings suggest that targeting the FUT8-B7H3 axis might be a promising strategy for improving anti-tumor immune responses in patients with TNBC.

Pan-cancer application of a lung-adenocarcinoma-derived gene-expression-based prognostic predictor

Gene-expression profiling can be used to classify human tumors into molecular subtypes or risk groups, representing potential future clinical tools for treatment prediction and prognostication. However, it is less well-known how prognostic gene signatures derived in one malignancy perform in a pan-cancer context. In this study, a gene-rule-based single sample predictor (SSP) called classifier for lung adenocarcinoma molecular subtypes (CLAMS) associated with proliferation was tested in almost 15 000 samples from 32 cancer types to classify samples into better or worse prognosis. Of the 14 malignancies that presented both CLAMS classes in sufficient numbers, survival outcomes were significantly different for breast, brain, kidney and liver cancer. Patients with samples classified as better prognosis by CLAMS were generally of lower tumor grade and disease stage, and had improved prognosis according to other type-specific classifications (e.g. PAM50 for breast cancer). In all, 99.1% of non-lung cancer cases classified as better outcome by CLAMS were comprised within the range of proliferation scores of lung adenocarcinoma cases with a predicted better prognosis by CLAMS. This finding demonstrates the potential of tuning SSPs to identify specific levels of for instance tumor proliferation or other transcriptional programs through predictor training. Together, pan-cancer studies such as this may take us one step closer to understanding how gene-expression-based SSPs act, which gene-expression programs might be important in different malignancies, and how to derive tools useful for prognostication that are efficient across organs.

Detection of acquired radioresistance in breast cancer cell lines using Raman spectroscopy and machine learning

Radioresistance-a living cell's response to, and development of resistance to ionising radiation-can lead to radiotherapy failure and/or tumour recurrence. We used Raman spectroscopy and machine learning to characterise biochemical changes that occur in acquired radioresistance for breast cancer cells. We were able to distinguish between wild-type and acquired radioresistant cells by changes in chemical composition using Raman spectroscopy and machine learning with 100% accuracy. In studying both hormone receptor positive and negative cells, we found similar changes in chemical composition that occur with the development of acquired radioresistance; these radioresistant cells contained less lipids and proteins compared to their parental counterparts. As well as characterising acquired radioresistance in vitro, this approach has the potential to be translated into a clinical setting, to look for Raman signals of radioresistance in tumours or biopsies; that would lead to tailored clinical treatments.

Luminal A Breast Cancer Co-expression Network: Structural and Functional Alterations

Luminal A is the most common breast cancer molecular subtype in women worldwide. These tumors have characteristic yet heterogeneous alterations at the genomic and transcriptomic level. Gene co-expression networks (GCNs) have contributed to better characterize the cancerous phenotype. We have previously shown an imbalance in the proportion of intra-chromosomal (cis-) over inter-chromosomal (trans-) interactions when comparing cancer and healthy tissue GCNs. In particular, for breast cancer molecular subtypes (Luminal A included), the majority of high co-expression interactions connect gene-pairs in the same chromosome, a phenomenon that we have called loss of trans- co-expression. Despite this phenomenon has been described, the functional implication of this specific network topology has not been studied yet. To understand the biological role that communities of co-expressed genes may have, we constructed GCNs for healthy and Luminal A phenotypes. Network modules were obtained based on their connectivity patterns and they were classified according to their chromosomal homophily (proportion of cis-/trans- interactions). A functional overrepresentation analysis was performed on communities in both networks to observe the significantly enriched processes for each community. We also investigated possible mechanisms for which the loss of trans- co-expression emerges in cancer GCN. To this end we evaluated transcription factor binding sites, CTCF binding sites, differential gene expression and copy number alterations (CNAs) in the cancer GCN. We found that trans- communities in Luminal A present more significantly enriched categories than cis- ones. Processes, such as angiogenesis, cell proliferation, or cell adhesion were found in trans- modules. The differential expression analysis showed that FOXM1, CENPA, and CIITA transcription factors, exert a major regulatory role on their communities by regulating expression of their target genes in other chromosomes. Finally, identification of CNAs, displayed a high enrichment of deletion peaks in cis- communities. With this approach, we demonstrate that network topology determine, to at certain extent, the function in Luminal A breast cancer network. Furthermore, several mechanisms seem to be acting together to avoid trans- co-expression. Since this phenomenon has been observed in other cancer tissues, a remaining question is whether the loss of long distance co-expression is a novel hallmark of cancer.

Evaluation of the antiproliferative effects of the HASPIN inhibitor CHR-6494 in breast cancer cell lines

HASPIN is a serine/threonine kinase that regulates mitosis by phosphorylating histone H3 at threonine 3. The expression levels of HASPIN in various cancers are associated with tumor malignancy and poor survival, suggesting that HASPIN inhibition may suppress cancer growth. As HASPIN mRNA levels are elevated in human breast cancer tissues compared with adjacent normal tissues, we examined the growth-suppressive effects of CHR-6494, a potent HASPIN inhibitor, in breast cancer cell lines in vitro and in vivo. We found that HASPIN was expressed in breast cancer cells of all molecular subtypes, as well as in immortalized mammary epithelial cells. HASPIN expression levels appeared to be correlated with the cell growth rate but not the molecular subtype of breast cancer. CHR-6494 exhibited potent antiproliferative effects against breast cancer cell lines and immortalized mammary epithelial cells in vitro, but failed to inhibit the growth of MDA-MB-231 xenografted tumors under conditions that have significant effects in a colorectal cancer model. These results imply that CHR-6494 does have antiproliferative effects in some situations, and further drug screening efforts are anticipated to identify more potent and selective HASPIN inhibition for use as an anticancer agent in breast cancer patients.

Inhibition of Cdc20 suppresses the metastasis in triple negative breast cancer (TNBC)

BACKGROUND

Cdc20 is a crucial activator of the anaphase-promoting complex (APC/C) and is known to be essential in mitosis regulation. Abnormally high expression of Cdc20 has been reported in several malignancies. We aimed to study the Cdc20 expression in human breast cancer tissues, focusing specifically on Cdc20 in Triple-Negative Breast Cancer (TNBC).

METHODS

The expression of mitotic regulators mRNA in three TNBC cell lines or three other breast cancer cell lines was determined by the RNA-sequencing database. 14,713 human breast cancer patient samples included in Breast Cancer-GenExminer v4.5 were used to analyze whether cell division cycle 20 (Cdc20) expression was related to TNBC. To find whether Cdc20 expression impacted prognosis in TNBC, we used 2,249 TNBC patients database. The loss of Cdc20 by RNA interference (shRNA) and several mitotic inhibitors including Apcin, ZM447439, BI 2536, and VX-680 on the capacities of proliferation, migration, invasion were evaluated by colony-forming, wound-healing, transwell assay, and western blot, respectively.

RESULTS

We studied the mitosis-related genes and proteins that are closely related to TNBC through the National Center for Biotechnology Information (NCBI) database. We found that Cdc20, one of the central mitotic regulators, is significantly upregulated in human TNBC, and its expression level is positively correlated with metastasis-free and relapse-free patient survival. We also found Cdc20 is highly conserved in TNBC in comparison to other breast cancer subtype cell lines. Cdc20 deficiency results in a decrease in cell growth and migration in four TNBC cell lines. Also, several mitotic inhibitors, such as Apcin, VX-680, ZM447439, and BI 2536, blocked cancer cell growth and invasion.

CONCLUSIONS

These results suggest an essential role of Cdc20 in tumor formation and metastasis of TNBC, which might be a potential target therapy for TNBC treatment.

Breast Cancer and the Other Non-Coding RNAs

Breast cancer is very heterogenous and the most common gynaecological cancer, with various factors affecting its development. While its impact on human lives and national health budgets is still rising in almost all global areas, many molecular mechanisms affecting its onset and development remain unclear. Conventional treatments still prove inadequate in some aspects, and appropriate molecular therapeutic targets are required for improved outcomes. Recent scientific interest has therefore focused on the non-coding RNAs roles in tumour development and their potential as therapeutic targets. These RNAs comprise the majority of the human transcript and their broad action mechanisms range from gene silencing to chromatin remodelling. Many non-coding RNAs also have altered expression in breast cancer cell lines and tissues, and this is often connected with increased proliferation, a degraded extracellular environment, and higher endothelial to mesenchymal transition. Herein, we summarise the known abnormalities in the function and expression of long non-coding RNAs, Piwi interacting RNAs, small nucleolar RNAs and small nuclear RNAs in breast cancer, and how these abnormalities affect the development of this deadly disease. Finally, the use of RNA interference to suppress breast cancer growth is summarised.

Development of CDK4/6 Inhibitors: A Five Years Update

The inhibition of cyclin dependent kinases 4 and 6 plays a role in aromatase inhibitor resistant metastatic breast cancer. Three dual CDK4/6 inhibitors have been approved for the breast cancer treatment that, in combination with the endocrine therapy, dramatically improved the survival outcomes both in first and later line settings. The developments of the last five years in the search for new selective CDK4/6 inhibitors with increased selectivity, treatment efficacy, and reduced adverse effects are reviewed, considering the small-molecule inhibitors and proteolysis-targeting chimeras (PROTACs) approaches, mainly pointing at structure-activity relationships, selectivity against different kinases and antiproliferative activity.

Advanced Approaches to Breast Cancer Classification and Diagnosis

The International Agency for Research on Cancer (IARC) has recently reported a 66% increase in the global number of cancer deaths since 1960. In the US alone, about one in eight women is expected to develop invasive breast cancer(s) (breast cancer) at some point in their lifetime. Traditionally, a BC diagnosis includes mammography, ultrasound, and some high-end molecular bioimaging. Unfortunately, these techniques detect BC at a later stage. So early and advanced molecular diagnostic tools are still in demand. In the past decade, various histological and immuno-molecular studies have demonstrated that BC is highly heterogeneous in nature. Its growth pattern, cytological features, and expression of key biomarkers in BC cells including hormonal receptor markers can be utilized to develop advanced diagnostic and therapeutic tools. A cancer cell's progression to malignancy exhibits various vital biomarkers, many of which are still underrepresented in BC diagnosis and treatment. Advances in genetics have also enabled the development of multigene assays to detect genetic heterogeneity in BC. However, thus far, the FDA has approved only four such biomarkers-cancer antigens (CA); CA 15-3, CA 27-29, Human epidermal growth factor receptor 2 (HER2), and circulating tumor cells (CTC) in assessing BC in body fluids. An adequately structured portable-biosensor with its non-invasive and inexpensive point-of-care analysis can quickly detect such biomarkers without significantly compromising its specificity and selectivity. Such advanced techniques are likely to discriminate between BC and a healthy patient by accurately measuring the cell shape, structure, depth, intracellular and extracellular environment, and lipid membrane compositions. Presently, BC treatments include surgery and systemic chemo- and targeted radiation therapy. A biopsied sample is then subjected to various multigene assays to predict the heterogeneity and recurrence score, thus guiding a specific treatment by providing complete information on the BC subtype involved. Thus far, we have seven prognostic multigene signature tests for BC providing a risk profile that can avoid unnecessary treatments in low-risk patients. Many comparative studies on multigene analysis projected the importance of integrating clinicopathological information with genomic-imprint analysis. Current cohort studies such as MINDACT, TAILORx, Trans-aTTOM, and many more, are likely to provide positive impact on long-term patient outcome. This review offers consolidated information on currently available BC diagnosis and treatment options. It further describes advanced biomarkers for the development of state-of-the-art early screening and diagnostic technologies.