Breast Cancer: Multiple Subtypes within a Tumor?

H3K27me3 loss plays a vital role in CEMIP mediated carcinogenesis and progression of breast cancer with poor prognosis

BACKGROUND

H3K27me3 modification inactivates gene transcription by resulting in condensed chromatin. However, the landscape and biological functions of H3K27me3 in breast cancer remain unclear.

METHODS

Fluorescence enzyme assay was used to analyze the cell proliferation. Transwell assay was used to test the ability of migration and invasion in MDA-MB-231 cells with designed treatment. Transfection of exogenous plasmid was used to intervene specific gene expression. Nude mouse tumor xenograft model was employed to detect the effect of GSKJ-4 in vivo. ChIP-Seq analyzed the modification state of H3K27me3 around the TSS of the gene CEMIP. RNA-Seq was used to analyze the mRNA levels after treating with GSKJ-4 in MDA-MB-231 cells.

RESULTS

Loss of H3K27me3 is specific for aggressive subtypes of breast cancer and may be a useful diagnostic marker. Epigenetic chemical screening identified histone H3K27me3 demethylation inhibition as a therapeutic strategy for triple-negative breast cancer (TNBC). Functional studies and RNA-seq/ChIP-seq data revealed that inactivation of the protein CEMIP (which is translated by oncogene KIAA1199) by increasing H3K27me3 leads to decreased tumor cell growth and migration. Moreover, survival analysis showed that CEMIP was associated with poor outcome in TNBC.

CONCLUSIONS

Our data suggest H3K27me3 loss as an important event in CEMIP mediated breast cancer carcinogenesis and progression. Loss of H3K27me3 is specific for aggressive subtypes of breast cancer and may be a useful diagnostic marker.

miR-200 affects tamoxifen resistance in breast cancer cells through regulation of MYB

Resistance to tamoxifen is a major clinical challenge. Research in recent years has identified epigenetic changes as mediated by dysregulated miRNAs that can possibly play a role in resistance to tamoxifen in breast cancer patients expressing estrogen receptor (ER). We report here elevated levels of EMT markers (vimentin and ZEB1/2) and reduced levels of EMT-regulating miR-200 (miR-200b and miR-200c) in ER-positive breast cancer cells, MCF-7, that were resistant to tamoxifen, in contrast with the naïve parental MCF-7 cells that were sensitive to tamoxifen. Further, we established regulation of c-MYB by miR-200 in our experimental model. C-MYB was up-regulated in tamoxifen resistant cells and its silencing significantly decreased resistance to tamoxifen and the EMT markers. Forced over-expression of miR-200b/c reduced c-MYB whereas reduced expression of miR-200b/c resulted in increased c-MYB We further confirmed the results in other ER-positive breast cancer cells T47D cells where forced over-expression of c-MYB resulted in induction of EMT and significantly increased resistance to tamoxifen. Thus, we identify a novel mechanism of tamoxifen resistance in breast tumor microenvironment that involves miR-200-MYB signaling.

Radiation and Stemness Phenotype May Influence Individual Breast Cancer Outcomes: The Crucial Role of MMPs and Microenvironment

Breast cancer is the most common cancer in women. Radiotherapy (RT) is one of the mainstay treatments for cancer but in some cases is not effective. Cancer stem cells (CSCs) within the tumor can be responsible for recurrence and metastasis after RT. Matrix metalloproteases (MMPs), regulated mainly by tissue inhibitors of metalloproteinases (TIMPs) and histone deacetylases (HDACs), may also contribute to tumor development by modifying its activity after RT. The aim of this work was to study the effects of RT on the expression of MMPs, TIMPs and HDACs on different cell subpopulations in MCF-7, MDA-MB-231 and SK-BR-3 cell lines. We assessed the in vitro expression of these genes in different 3D culture models and induced tumors in female NSG mice by orthotopic xenotransplants. Our results showed that gene expression is related to the cell subpopulation studied, the culture model used and the single radiation dose administered. Moreover, the crucial role played by the microenvironment in terms of cell interactions and CSC plasticity in tumor growth and RT outcome is also shown, supporting the use of higher doses (6 Gy) to achieve better control of tumor development.

Systems-level network modeling of Small Cell Lung Cancer subtypes identifies master regulators and destabilizers

Adopting a systems approach, we devise a general workflow to define actionable subtypes in human cancers. Applied to small cell lung cancer (SCLC), the workflow identifies four subtypes based on global gene expression patterns and ontologies. Three correspond to known subtypes (SCLC-A, SCLC-N, and SCLC-Y), while the fourth is a previously undescribed ASCL1+ neuroendocrine variant (NEv2, or SCLC-A2). Tumor deconvolution with subtype gene signatures shows that all of the subtypes are detectable in varying proportions in human and mouse tumors. To understand how multiple stable subtypes can arise within a tumor, we infer a network of transcription factors and develop BooleaBayes, a minimally-constrained Boolean rule-fitting approach. In silico perturbations of the network identify master regulators and destabilizers of its attractors. Specific to NEv2, BooleaBayes predicts ELF3 and NR0B1 as master regulators of the subtype, and TCF3 as a master destabilizer. Since the four subtypes exhibit differential drug sensitivity, with NEv2 consistently least sensitive, these findings may lead to actionable therapeutic strategies that consider SCLC intratumoral heterogeneity. Our systems-level approach should generalize to other cancer types.

A 23 gene-based molecular prognostic score precisely predicts overall survival of breast cancer patients

BACKGROUND

Although many prognosis-predicting molecular scores for breast cancer have been developed, they are applicable to only limited disease subtypes. We aimed to develop a novel prognostic score that is applicable to a wider range of breast cancer patients.

METHODS

We initially examined The Cancer Genome Atlas breast cancer cohort to identify potential prognosis-related genes. We then performed a meta-analysis of 36 international breast cancer cohorts to validate such genes. We trained artificial intelligence models (random forest and neural network) to predict prognosis precisely, and we finally validated our prediction with the log-rank test.

FINDINGS

We identified a comprehensive list of 184 prognosis-related genes, most of which have been not extensively studied to date. We then established a universal molecular prognostic score (mPS) that relies on the expression status of only 23 of these genes. The mPS system is almost universally applicable to breast cancer patients (log-rank P < 0.05) in a manner independent of platform (microarray or RNA sequencing).

INTERPRETATION

The mPS system is simple and cost-effective to apply and yet is able to reveal previously unrecognized heterogeneity among patient subpopulations in a platform-independent manner. The combination of mPS and clinical stage stratifies prognosis even more precisely and should prove of value for avoidance of overtreatment. In addition, the prognosis-related genes uncovered in this study are potential drug targets. FUND: This work was supported by KAKENHI grants from the Ministry of Education, Culture, Sports, Science, and Technology of Japan to H.S. (19K20403) and to K.I·N (18H05215).

Breast cancer: Occluded role of mitochondria N-acetylserotonin/melatonin ratio in co-ordinating pathophysiology

A plethora of factors contribute to the biochemical underpinnings of breast cancer, in the absence of any clear, integrative framework. This article proposes that melatonergic pathway regulation within mitochondria provides an integrative framework for the wide array of data driving breast cancer pathophysiology. As melatonin is toxic to breast cancer cells, its production within mitochondria poses a significant challenge to breast cancer cell survival. Consequently, the diverse plasticity in breast cancer cells may arise from a requirement to decrease mitochondria melatonin synthesis. The aryl hydrocarbon receptor role in breast cancer pathophysiology may be mediated by an increase in cytochrome P450 (CYP)1b1 in mitochondria, leading to the backward conversion of melatonin to N-acetylserotonin (NAS). NAS has distinct effects to melatonin, including its activation of the tyrosine receptor kinase B (TrkB) receptor. TrkB activation significantly contributes to breast cancer cell survival and migration. However, the most important aspect of NAS induction by CYP1b1 in breast cancer cells is the prevention of melatonin effects in mitochondria. Many of the changes occurring in breast cancer cells arise from the need to regulate this pathway in mitochondria, allowing this to provide a framework that integrates a host of previously disparate data, including: microRNAs, estrogen, 14-3-3 proteins, sirtuins, glycolysis, oxidative phosphorylation, indoleamine 2,3-dioxygenase and the kynurenine pathways. It is also proposed that this framework provides a pathoetiological model incorporating the early developmental regulation of the gut microbiome that integrates breast cancer risk factors, including obesity. This has significant treatment, prevention and research implications.

Identification of TC2N as a novel promising suppressor of PI3K-AKT signaling in breast cancer

Although TC2N has proven to be an oncogene in lung cancer, its biological function and molecular mechanisms in other cancer still remains unclear. Here, we investigate in breast cancer that TC2N expression is sharply overexpressed in breast cancer specimens compared with normal breast specimens, and the low TC2N expression was associated with advanced stage, lymphatic metastasis, larger tumors and shorter survival time. Upregulation of TC2N significantly restrains breast cancer cell proliferation in vitro and tumor growth in vivo. Mechanistically, TC2N blocks AKT signaling in a PI3K dependent and independent way through weakening the interaction between ALK and p55γ or inhibiting the binding of EBP1 and AKT. To sum up, these results unmask an ambivalent role of TC2N in cancer, providing a promising inhibitor for PI3K-AKT signaling.

Mitochondrial ncRNA targeting induces cell cycle arrest and tumor growth inhibition of MDA-MB-231 breast cancer cells through reduction of key cell cycle progression factors

The family of long noncoding mitochondrial RNAs (ncmtRNAs), comprising sense (SncmtRNA), and antisense (ASncmtRNA-1 and ASncmtRNA-2) members, are differentially expressed according to cell proliferative status; SncmtRNA is expressed in all proliferating cells, while ASncmtRNAs are expressed in normal proliferating cells, but is downregulated in tumor cells. ASncmtRNA knockdown with an antisense oligonucleotide induces massive apoptosis in tumor cell lines, without affecting healthy cells. Apoptotic death is preceded by proliferation blockage, suggesting that these transcripts are involved in cell cycle regulation. Here, we show that ASncmtRNA knockdown induces cell death preceded by proliferative blockage in three different human breast cancer cell lines. This effect is mediated by downregulation of the key cell cycle progression factors cyclin B1, cyclin D1, CDK1, CDK4, and survivin, the latter also constituting an essential inhibitor of apoptosis, underlying additionally the onset of apoptosis. The treatment also induces an increase in the microRNA hsa-miR-4485-3p, whose sequence maps to ASncmtRNA-2 and transfection of MDA-MB-231 cells with a mimic of this miRNA induces cyclin B1 and D1 downregulation. Other miRNAs that are upregulated include nuclear-encoded hsa-miR-5096 and hsa-miR-3609, whose mimics downregulate CDK1. Our results suggest that ASncmtRNA targeting blocks tumor cell proliferation through reduction of essential cell cycle proteins, mediated by mitochondrial and nuclear miRNAs. This work adds to the elucidation of the molecular mechanisms behind cell cycle arrest preceding tumor cell apoptosis induced by ASncmtRNA knockdown. As proof-of-concept, we show that in vivo knockdown of ASncmtRNAs results in drastic inhibition of tumor growth in a xenograft model of MDA-MB-231 subcutaneous tumors, further supporting this approach for the development of new therapeutic strategies against breast cancer.

Antitumoral Effect of Laurinterol on 3D Culture of Breast Cancer Explants

Macroalgae represent an important source of bioactive compounds with a wide range of biotechnological applications. Overall, the discovery of effective cytotoxic compounds with pharmaceutical potential is a significant challenge, mostly because they are scarce in nature or their total synthesis is not efficient, while the bioprospecting models currently used do not predict clinical responses. Given this context, we used three-dimensional (3D) cultures of human breast cancer explants to evaluate the antitumoral effect of laurinterol, the major compound of an ethanolic extract of Laurencia johnstonii. To this end, we evaluated the metabolic and histopathological effects of the crude extract of L. johnstonii and laurinterol on Vero and MCF-7 cells, in addition to breast cancer explants. We observed a dose-dependent inhibition of the metabolic activity, as well as morphologic and nuclear changes characteristic of apoptosis. On the other hand, a reduced metabolic viability and marked necrosis areas were observed in breast cancer explants incubated with the crude extract, while explants treated with laurinterol exhibited a heterogeneous response which was associated with the individual response of each human tumor sample. This study supports the cytotoxic and antitumoral effects of laurinterol in in vitro cell cultures and in ex vivo organotypic cultures of human breast cancer explants.

Moving Breast Cancer Therapy up a Notch

Breast cancer is the second most common malignancy, worldwide. Treatment decisions are based on tumor stage, histological subtype, and receptor expression and include combinations of surgery, radiotherapy, and systemic treatment. These, together with earlier diagnosis, have resulted in increased survival. However, initial treatment efficacy cannot be guaranteed upfront, and these treatments may come with (long-term) serious adverse effects, negatively affecting a patient's quality of life. Gene expression-based tests can accurately estimate the risk of recurrence in early stage breast cancers. Disease recurrence correlates with treatment resistance, creating a major need to resensitize tumors to treatment. Notch signaling is frequently deregulated in cancer and is involved in treatment resistance. Preclinical research has already identified many combinatory therapeutic options where Notch involvement enhances the effectiveness of radiotherapy, chemotherapy or targeted therapies for breast cancer. However, the benefit of targeting Notch has remained clinically inconclusive. In this review, we summarize the current knowledge on targeting the Notch pathway to enhance current treatments for breast cancer and to combat treatment resistance. Furthermore, we propose mechanisms to further exploit Notch-based therapeutics in the treatment of breast cancer.

LncRNA MIR100HG promotes cell proliferation in triple-negative breast cancer through triplex formation with p27 loci

Triple-negative breast cancer (TNBC) exhibits poor prognosis, with high metastasis and low survival. Long non-coding RNAs (lncRNAs) play critical roles in tumor progression. Here, we identified lncRNA MIR100HG as a pro-oncogene for TNBC progression. Knockdown of MIR100HG decreased cell proliferation and induced cell arrest in the G1 phase, whereas overexpression of MIR100HG significantly increased cell proliferation. Furthermore, MIR100HG regulated the p27 gene to control the cell cycle, and subsequently impacted the progression of TNBC. In analyzing its underlying mechanism, bioinformatics prediction and experimental data demonstrated that MIR100HG participated in the formation of RNA–DNA triplex structures. MIR100HG in The Cancer Genome Atlas (TCGA) and breast cancer cell lines showed higher expression in TNBC than in other tumor types with poor prognosis. In conclusion, our data indicated a novel working pattern of lncRNA in TNBC progression, which may be a potential therapeutic target in such cancers.

An NFκB-dependent mechanism of tumor cell plasticity and lateral transmission of aggressive features

Breast cancer is a complex disease exhibiting extensive inter- and intra-tumor heterogeneity. Inflammation is a well-known driver of cancer progression, often attributed to immune cells infiltrating the tumor stroma. However, tumor cells themselves are capable to secrete a variety of inflammatory molecules, of which we understand very little about their role in intra-clonal communication. We recently reported the capacity of triple negative cell lines to induce a cancer stem cell (CSC)-like phenotype and invasion properties into luminal cells, a mechanism mediated by pro-inflammatory cytokines that up-regulated the CXCL12/CXCR4/CXCR7 chemokine signaling axis. We performed transcriptional array analyses of CSCs-associated genes and cancer-inflammatory cell crosstalk genes and built regulatory networks with the data collected. We found a specific molecular signature segregating with the induced-invasive/stemness phenotype. Regulatory network analysis pointed out to an NFκB transcriptional signature, active in aggressive triple negative cells and in induced-invasive/CSC-like luminal cells. In agreement, NFκB inhibition abolished the induction of the stemness/invasive features. These data support an NFκB dependent mechanism of intra-clonal communication responsible for tumor cell plasticity leading the acquisition of cancer aggressive features. Understanding the communication between different tumor clones would help to find better therapeutic and prophylactic targets to prevent BrC progression and relapse.

Breast cancer identification via modeling of peripherally circulating miRNAs

Prolonged life expectancy in humans has been accompanied by an increase in the prevalence of cancers. Breast cancer (BC) is the leading cause of cancer-related deaths. It accounts for one-fourth of all diagnosed cancers and affects one in eight females worldwide. Given the high BC prevalence, there is a practical need for demographic screening of the disease. In the present study, we re-analyzed a large microRNA (miRNA) expression dataset (GSE73002), with the goal of optimizing miRNA biomarker selection using neural network cascade (NNC) modeling. Our results identified numerous candidate miRNA biomarkers that are technically suitable for BC detection. We combined three miRNAs (miR-1246, miR-6756-5p, and miR-8073) into a single panel to generate an NNC model, which successfully detected BC with 97.1% accuracy in an independent validation cohort comprising 429 BC patients and 895 healthy controls. In contrast, at least seven miRNAs were merged in a multiple linear regression model to obtain equivalent diagnostic performance (96.4% accuracy in the independent validation set). Our findings suggested that suitable modeling can effectively reduce the number of miRNAs required in a biomarker panel without compromising prediction accuracy, thereby increasing the technical possibility of early detection of BC.