Ehm2 transcript variant 1 inhibits breast cancer progression and increases E-cadherin stability.

Ehm2/1, an Ehm2 transcript variant, regulates the cytoskeleton by binding to plasma membrane proteins. However, the role of Ehm2/1 in breast cancer development remains poorly understood. This study shows that, the expression of Ehm2/1 was decreased in breast cancer and that patients with low Ehm2/1 expression had a significantly poorer prognosis than those with high expression of Ehm2/1. Overexpression of Ehm2/1 in MCF-7 breast cancer cells inhibited cell migration and invasion. Ehm2/1 markedly increased the stability and half-life of E-cadherin. Moreover, Ehm2/1 was collocated with E-cadherin in the plasma membrane of MCF-7 cells. Furthermore, downregulation of Ehm2/1 promoted ubiquitination of E-cadherin, whereas overexpression of Ehm2/1 inhibited ubiquitination of E-cadherin. These results suggest that Ehm2/1 could suppress the migration and invasion of breast cancer cells by increasing E-cadherin stability.

How previous treatment changes the metabolomic profile in patients with metastatic breast cancer.

PURPOSE: Metabolites are in the spotlight of attention as promising novel breast cancer biomarkers. However, no study has been conducted concerning changes in the metabolomics profile of metastatic breast cancer patients according to previous therapy. METHODS: We performed a retrospective, single-center, nonrandomized, partially blinded, treatment-based study. Metastatic breast cancer (MBC) patients were enrolled between 03/2010 and 09/2016 at the beginning of a new systemic therapy. The endogenous metabolites in the plasma samples were analyzed using the AbsoluteIDQ® p180 Kit (Biocrates Life Sciences AG, Innsbruck) a targeted, quality and quantitative-controlled metabolomics approach. The statistical analysis was performed using R package, version 3.3.1. ANOVA was used to statistically assess age differences within groups. Furthermore, we analyzed the CTC status of the patients using the CellSearch™ assay. RESULTS: We included 178 patients in our study. Upon dividing the study population according to therapy before study inclusion, we found the following: 4 patients had received no therapy, 165 chemotherapy, and 135 anti-hormonal therapy, 30 with anti-Her2 therapy and 38 had received treatment with bevacizumab. Two metabolites were found to be significantly different, depending on the further therapy of the patients: methionine and serine. Whereas methionine levels were higher in the blood of patients who received an anti-Her2-therapy, serine was lower in patients with endocrine therapy only. CONCLUSION: We identified two metabolites for which concentrations differed significantly depending on previous therapies, which could help to choose the next therapy in patients who have already received numerous different treatments.

A plasma metabolite panel as biomarkers for early primary breast cancer detection.

In recent years, metabolites have attracted substantial attention as promising novel biomarkers of various diseases. However, breast cancer plasma metabolite studies are still in their infancy. Here, we investigated the potential of metabolites to serve as minimally invasive, early detection markers of primary breast cancer. We profiled metabolites extracted from the plasma of primary breast cancer patients and healthy controls using tandem mass spectrometry (UHPLC-MS/MS and FIA-MS/MS). Two metabolites were found to be upregulated, while 16 metabolites were downregulated in primary breast cancer patients compared to healthy controls in both the training and validation cohorts. A panel of seven metabolites was selected by LASSO regression analysis. This panel could differentiate primary breast cancer patients from healthy controls, with an AUC of 0.87 (95% CI: 0.81 ~ 0.92) in the training cohort and an AUC of 0.80 (95% CI: 0.71 ~ 0.87) in the validation cohort. These significantly differentiated metabolites are mainly involved in the amino acid metabolism and breast cancer cell growth pathways. In conclusion, using a metabolomics approach, we identified metabolites that have potential value for development of a multimarker blood-based test to complement and improve early breast cancer detection. The panel identified herein might be part of a prescreening tool, especially for younger women or for closely observing women with certain risks, to facilitate decision making regarding which individuals should undergo further diagnostic tests. In the future, the combination of metabolites and other blood-based molecular marker sets, such as DNA methylation, microRNA, and cell-free DNA mutation markers, will be an attractive option.

Identifying key transcription factors and immune infiltration in non-small-cell lung cancer using weighted correlation network and Cox regression analyses.

Introduction: Lung cancer is one of the most common cancers and a significant cause of cancer-related deaths. Non-small cell lung cancer (NSCLC) accounts for about 85% of all lung cancer cases. Therefore, it is crucial to identify effective diagnostic and therapeutic methods. In addition, transcription factors are essential for eukaryotic cells to regulate their gene expression, and aberrant expression transcription factors are an important step in the process of oncogenesis in NSCLC. Methods: Differentially expressed transcription factors between NSCLC and normal tissues by analyzing mRNA profiling from The Cancer Genome Atlas (TCGA) database program were identified. Weighted correlation network analysis (WGCNA) and line plot of least absolute shrinkage and selection operator (LASSO) were performed to find prognosis-related transcription factors. The cellular functions of transcription factors were performed by 5-ethynyl-2'-deoxyuridine (EdU) assay, wound healing assay, cell invasion assay in lung cancer cells. Results: We identified 725 differentially expressed transcription factors between NSCLC and normal tissues. Three highly related modules for survival were discovered, and transcription factors highly associated with survival were obtained by using WGCNA. Then line plot of LASSO was applied to screen transcription factors related to prognosis and build a prognostic model. Consequently, SETDB2, SNAI3, SCML4, and ZNF540 were identified as prognosis-related transcription factors and validated in multiple databases. The low expression of these hub genes in NSCLC was associated with poor prognosis. The deletions of both SETDB2 and SNAI3 were found to promote proliferation, invasion, and stemness in lung cancer cells. Furthermore, there were significant differences in the proportions of 22 immune cells between the high- and low-score groups. Discussion: Therefore, our study identified the transcription factors involved in regulating NSCLC, and we constructed a panel for the prediction of prognosis and immune infiltration to inform the clinical application of transcription factor analysis in the prevention and treatment of NSCLC.

Prognostic analysis of patients with breast cancer based on tumor mutational burden and DNA damage repair genes.

Background: Breast cancer has a high tumor-specific death rate and poor prognosis. In this study, we aimed to provide a basis for the prognostic risk in patients with breast cancer using significant gene sets selected by analyzing tumor mutational burden (TMB) and DNA damage repair (DDR). Methods: Breast cancer genomic and transcriptomic data were obtained from The Cancer Genome Atlas (TCGA). Breast cancer samples were dichotomized into high- and low-TMB groups according to TMB values. Differentially expressed DDR genes between high- and low-TMB groups were incorporated into univariate and multivariate cox regression model to build prognosis model. Performance of the prognosis model was validated in an independently new GEO dataset and evaluated by time-dependent ROC curves. Results: Between high- and low-TMB groups, there were 6,424 differentially expressed genes, including 67 DDR genes. Ten genes associated with prognosis were selected by univariate cox regression analysis, among which seven genes constituted a panel to predict breast cancer prognosis. The seven-gene prognostic model, as well as the gene copy numbers are closely associated with tumor-infiltrating immune cells. Conclusion: We established a seven-gene prognostic model comprising MDC1, PARP3, PSMB1, PSMB9, PSMD2, PSMD7, and PSMD14 genes, which provides a basis for further exploration of a population-based prediction of prognosis and immunotherapy response in patients with breast cancer.

The PRMT6/PARP1/CRL4B Complex Regulates the Circadian Clock and Promotes Breast Tumorigenesis.

Circadian rhythms, as physiological systems with self-regulatory functions in living organisms, are controlled by core clock genes and are involved in tumor development. The protein arginine methyltransferase 6 (PRMT6) serves as an oncogene in a myriad of solid tumors, including breast cancer. Hence, the primary aim of the current study is to investigate the molecular mechanisms by which the PRMT6 complex promotes breast cancer progression. The results show that PRMT6, poly(ADP-ribose) polymerase 1 (PARP1), and the cullin 4 B (CUL4B)-Ring E3 ligase (CRL4B) complex interact to form a transcription-repressive complex that co-occupies the core clock gene PER3 promoter. Moreover, genome-wide analysis of PRMT6/PARP1/CUL4B targets identifies a cohort of genes that is principally involved in circadian rhythms. This transcriptional-repression complex promotes the proliferation and metastasis of breast cancer by interfering with circadian rhythm oscillation. Meanwhile, the PARP1 inhibitor Olaparib enhances clock gene expression, thus, reducing breast carcinogenesis, indicating that PARP1 inhibitors have potential antitumor effects in high-PRMT6 expression breast cancer.

JARID2 coordinates with the NuRD complex to facilitate breast tumorigenesis through response to adipocyte-derived leptin.

BACKGROUND: Proteins containing the Jumonji C (JmjC) domain participated in tumorigenesis and cancer progression. However, the mechanisms underlying this effect are still poorly understood. Our objective was to investigate the role of Jumonji and the AT-rich interaction domain-containing 2 (JARID2) - a JmjC family protein - in breast cancer, as well as its latent association with obesity. METHODS: Immunohistochemistry, The Cancer Genome Atlas, Gene Expression Omnibus, and other databases were used to analyze the expression of JARID2 in breast cancer cells. Growth curve, 5-ethynyl-2-deoxyuridine (EdU), colony formation, and cell invasion experiments were used to detect whether JARID2 affected breast cancer cell proliferation and invasion. Spheroidization-based experiments and xenotumor transplantation in NOD/SCID mice were used to examine the association between JARID2 and breast cancer stemness. RNA-sequencing, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis were used to identify the cell processes in which JARID2 participates. Immunoaffinity purification and silver staining mass spectrometry were conducted to search for proteins that might interact with JARID2. The results were further verified using co-immunoprecipitation and glutathione S-transferase (GST) pull-down experiments. Using chromatin immunoprecipitation (ChIP) sequencing, we sought the target genes that JARID2 and metastasis-associated protein 1 (MTA1) jointly regulated; the results were validated by ChIP-PCR, quantitative ChIP (qChIP) and ChIP-reChIP assays. A coculture experiment was used to explore the interactions between breast cancer cells and adipocytes. RESULTS: In this study, we found that JARID2 was highly expressed in multiple types of cancer including breast cancer. JARID2 promoted glycolysis, lipid metabolism, proliferation, invasion, and stemness of breast cancer cells. Furthermore, JARID2 physically interacted with the nucleosome remodeling and deacetylase (NuRD) complex, transcriptionally repressing a series of tumor suppressor genes such as BRCA2 DNA repair associated (BRCA2), RB transcriptional corepressor 1 (RB1), and inositol polyphosphate-4-phosphatase type II B (INPP4B). Additionally, JARID2 expression was regulated by the obesity-associated adipokine leptin via Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) pathway in the breast cancer microenvironment. Analysis of various online databases also indicated that JARID2/MTA1 was associated with a poor prognosis of breast cancer. CONCLUSION: Our data indicated that JARID2 promoted breast tumorigenesis and development, confirming JARID2 as a target for cancer treatment.

Utilizing Gut Microbiota to Improve Hepatobiliary Tumor Treatments: Recent Advances.

Hepatobiliary tumors, which include cholangiocarcinoma, hepatocellular carcinoma (HCC), and gallbladder cancer, are common cancers that have high morbidity and mortality rates and poor survival outcomes. In humans, the microbiota is comprised of symbiotic microbial cells (10-100 trillion) that belong to the bacterial ecosystem mainly residing in the gut. The gut microbiota is a complicated group that can largely be found in the intestine and has a dual role in cancer occurrence and progression. Previous research has focused on the crucial functions of the intestinal microflora as the main pathophysiological mechanism in HCC development. Intestinal bacteria produce a broad range of metabolites that exhibit a variety of pro- and anticarcinogenic effects on HCC. Therefore, probiotic alteration of the gut microflora could promote gut flora balance and help prevent the occurrence of HCC. Recent evidence from clinical and translational studies suggests that fecal microbiota transplant is one of the most successful therapies to correct intestinal bacterial imbalance. We review the literature describing the effects and mechanisms of the microbiome in the gut in the context of HCC, including gut bacterial metabolites, probiotics, antibiotics, and the transplantation of fecal microbiota, and discuss the potential influence of the microbiome environment on cholangiocarcinoma and gallbladder cancer. Our findings are expected to reveal therapeutic targets for the prevention of hepatobiliary tumors, and the development of clinical treatment strategies, by emphasizing the function of the gut microbiota.

The hub ten gene-based risk score system using RNA m6A methylation regulator features and tumor immune microenvironment in breast cancer.

BACKGROUND: RNA N6-methyladenosine (m6A) modification is primarily regulated by m6A regulators, which play significant epigenetic regulatory roles in tumorigenesis, tumor development, and tumor immune microenvironment. However, the correlation between m6A regulators and immune cell infiltration in breast cancer remains unclear. METHODS: In this study, m6A modification patterns were evaluated based on 31 m6A modification regulators. m6A clusters were determined by consensus clustering. Immune landscape and immune cell infiltration subgroups were characterized by m6A clusters. Key module and hub genes related to m6A regulators and immune infiltration cells were identified by WGCNA. LASSO algorithm was applied to select prognostic signatures. Multivariate Cox regression analysis was applied to assess the prognostic value of gene signatures. RESULTS: Two distinct m6A clusters were determined based on the expression of 31 m6A modification regulators and characterized by two tumor immune microenvironment (TIME) immune cell infiltration subgroups. Further, a total of 1971 differentially expressed genes between breast cancer patients and healthy controls were screened, nine modules associated with clinical characteristics of breast cancer patients were identified. Later, one key module and 13 hub genes correlated with m6A regulators and immune infiltration cells were identified. LASSO Cox regression analysis selected and constructed a ten-gene prognostic model to build a risk score system for individual breast cancer patient prognosis. The performance of the ten-gene-based risk score system was further validated in an independent dataset with an AUC of 0.659. CONCLUSIONS: This study revealed that m6A modification regulators played a significant role in the TIME regulation of breast cancer. The hub ten gene-based risk score system is valuable in predicting the prognosis of breast cancer patients, which may provide potential significance for breast cancer diagnosis, prognosis, and immunotherapy in the future.

m6A regulators featured by tumor immune microenvironment landscapes and correlated with immunotherapy in non-small cell lung cancer (NSCLC).

Introduction: Recent research has confirmed the critical role that epigenetic factors play in regulating the immune response. Nonetheless, what role m6A methylation modification might play in the immune response of non-small cell lung cancer (NSCLC) remains vague. Methods: Herein, the gene expression, copy number variations (CNVs), and somatic mutations of 31 m6A regulators in NSCLC and adjacent control samples from the GEO and TCGA databases were comprehensively explored. Using consensus clustering, m6A modification patterns were identified. Correlations between m6A modification patterns and immune cell infiltration traits in the tumor immune microenvironment (TME) were systematically analyzed. Differentially expressed genes were verified and screened by random forest and cox regression analysis by comparing different m6A modification patterns. Based on the retained gene panel, a risk model was built, and m6Ascore for each sample was calculated. The function of m6Ascore in NSCLC prognosis, tumor somatic mutations, and chemotherapy/immunotherapy response prediction were evaluated. Results: Consensus clustering classified all NSCLC samples into two m6A clusters (m6A_clusterA and m6A_clusterB) according to the expression levels of 25 m6A regulator genes. Hierarchical clustering further divides the NSCLC samples into two m6A gene clusters: m6AgeneclusterA and m6AgeneclusterB. A panel of 83 genes was screened from the 194 differentially expressed genes between m6A gene clusters. Based on this, a risk score model was established. m6A modification clusters, m6A gene clusters, and m6Ascore calculated from the risk model were able to predict tumor stages, immune cell infiltration, clinical prognosis, and tumor somatic mutations. NSCLC patients with high m6Ascore have poor drug resistance to chemotherapy drugs (Cisplatin and Gemcitabine) and exhibit considerable therapeutic benefits and favorable clinical responses to anti-PD1 or anti-CTLA4 immunotherapy. Discussion: In conclusion, methylation modification patterns mediated by the m6A regulators in individuals play a non-negligible role in prognosis prediction and immunotherapy response, which will facilitate personalized treatment and immunotherapeutic strategies for NSCLC patients in the future.

RUNX2 recruits the NuRD(MTA1)/CRL4B complex to promote breast cancer progression and bone metastasis.

Runt-related transcription factor 2 (RUNX2) is an osteogenesis-related transcription factor that has emerged as a prominent transcription repressing factor in carcinogenesis. However, the role of RUNX2 in breast cancer metastasis remains poorly understood. Here, we show that RUNX2 recruits the metastasis-associated 1 (MTA1)/NuRD and the Cullin 4B (CUL4B)-Ring E3 ligase (CRL4B) complex to form a transcriptional-repressive complex, which catalyzes the histone deacetylation and ubiquitylation. Genome-wide analysis of the RUNX2/NuRD(MTA1)/CRL4B complex targets identified a cohort of genes including peroxisome proliferator-activated receptor alpha (PPARα) and superoxide dismutase 2 (SOD2), which are critically involved in cell growth, epithelial-to-mesenchymal transition (EMT) and invasion. We demonstrate that the RUNX2/NuRD(MTA1)/CRL4B complex promotes the proliferation, invasion, tumorigenesis, bone metastasis, cancer stemness of breast cancer in vitro and in vivo. Strikingly, RUNX2 expression is upregulated in multiple human carcinomas, including breast cancer. Our study suggests that RUNX2 is a promising potential target for the future treatment strategies of breast cancer.

Snail/PRMT5/NuRD complex contributes to DNA hypermethylation in cervical cancer by TET1 inhibition.

The biological function of PRMT5 remains poorly understood in cervical cancer metastasis. Here, we report that PRMT5 physically associates with the transcription factor Snail and the NuRD(MTA1) complex to form a transcriptional-repressive complex that catalyzes the symmetrical histone dimethylation and deacetylation. This study shows that the Snail/PRMT5/NuRD(MTA1) complex targets genes, such as TET1 and E-cadherin, which are critical for epithelial-mesenchymal transition (EMT). This complex also affects the conversion of 5mC to 5hmC. This study demonstrates that the Snail/PRMT5/NuRD(MTA1) complex promotes the invasion and metastasis of cervical cancer in vitro and in vivo. This study also shows that PRMT5 expression is upregulated in cervical cancer and various human cancers, and the PRMT5 inhibitor EPZ015666 suppresses EMT and the invasion potential of cervical cancer cells by disinhibiting the expression of TET1 and increasing 5hmC, suggesting that PRMT5 is a potential target for cancer therapy.