A novel n-UV convertible colour-tunable emitting oxynitride phosphor: Realization based on Ce3+ -Tb3+ energy transfer.

In the present work, a novel n-UV convertible colour-tunable emitting phosphor was obtained based on the efficient Ce3+ -Tb3+ energy transfer in the Y10 Al2 Si3 O18 N4 host. By properly controlling the ratio of Ce3+ /Tb3+ , the colour hue of the obtained powder covered the blue and green regions, under excitation of 365 nm. The steady-state and dynamic-state luminescence measurement was performed to shed light on the related mechanism, which was justified by the electronic dipole-quadrupole dominating the related energy transfer process. Preliminary studies showed that Y10 Al2 Si3 O18 N4 :Ce3+ ,Tb3+ can be promising as an inorganic phosphor for white LED applications.

Targeting RNA N6-methyladenosine modification: a precise weapon in overcoming tumor immune escape.

Immunotherapy, especially immune checkpoint inhibitors (ICIs), has revolutionized the treatment of many types of cancer, particularly advanced-stage cancers. Nevertheless, although a subset of patients experiences dramatic and long-term disease regression in response to ICIs, most patients do not benefit from these treatments. Some may even experience cancer progression. Immune escape by tumor cells may be a key reason for this low response rate. N6-methyladenosine (m6A) is the most common type of RNA methylation and has been recognized as a critical regulator of tumors and the immune system. Therefore, m6A modification and related regulators are promising targets for improving the efficacy of tumor immunotherapy. However, the association between m6A modification and tumor immune escape (TIE) has not been comprehensively summarized. Therefore, this review summarizes the existing knowledge regarding m6A modifications involved in TIE and their potential mechanisms of action. Moreover, we provide an overview of currently available agents targeting m6A regulators that have been tested for their elevated effects on TIE. This review establishes the association between m6A modifications and TIE and provides new insights and strategies for maximizing the efficacy of immunotherapy by specifically targeting m6A modifications involved in TIE.

PSAT1 Promotes Metastasis via p-AKT/SP1/ITGA2 Axis in Estrogen Receptor-Negative Breast Cancer Cell.

BACKGROUND: Accumulating evidence indicates that PSAT1 not only reprogrammed metabolic function but also exhibits "moonlighting" functions in promoting tumor malignancy. However, the underlying molecular mechanisms of PSAT1 promoting ER-negative breast cancer cell migration need further investigation. METHODS: Briefly, the PSAT1 and ITGA2 expression in cells and tissues was detected using qRT-PCR, immunofluorescence staining and western blot assay. The effect of PSAT1 and ITGA2 was verified both in vitro and in vivo. RNA-seq analysis explored a series of differently expressed genes. The regulation between SP1 and ITGA2 was investigated by ChIP analysis. RESULTS: We reported PSAT1 was highly expressed in ER-breast cancer tissues and tumor cells and positively correlated with metastasis. Moreover, RNA-seq analysis explored a series of differently expressed genes, including ITGA2, in PSAT1 overexpressed cells. Mechanistically, PSAT1 facilitated breast cancer metastasis via the p-AKT/SP1/ITGA2 axis. We further elucidated that PSAT1 promoted the entry of SP1 into the nucleus through the upregulation of p-AKT and confirmed ITGA2 is a target of SP1. In addition, enhanced cell migration was remarkably reversed by ITGA2 depletion or p-AKT inhibitor treatment. CONCLUSION: This study clarified the mechanism of PSAT1 in promoting ER-negative breast cancer metastasis, which may provide mechanistic clues for attenuating breast cancer metastasis.

Precise subtyping reveals immune heterogeneity for hormone receptor-positive breast cancer.

A significant proportion of breast cancer cases are characterized by hormone receptor positivity (HR+). Clinically, the heterogeneity of HR+ breast cancer leads to different therapeutic effects on endocrine. Therefore, definition of subgroups in HR+ breast cancer is important for effective treatment. Here, we have developed a CMBR method utilizing computational functional networks based on DNA methylation to identify conserved subgroups in HR+ breast cancer. Calculated by CMBR, HR+ breast cancer was divided into five subgroups, of which HR+/negative epidermal growth factor receptor-2 (Her2-) was divided into two subgroups, and HR+/positive epidermal growth factor receptor-2 (Her2+) was divided into three subgroups. These subgroups had heterogeneity in the immune microenvironment, tumor infiltrating lymphocyte patterns, somatic mutation patterns and drug sensitivity. Specifically, CMBR identified two subgroups with the "Hot" tumor phenotype. In addition, these conserved subgroups were broadly validated on external validation datasets. CMBR identified the molecular signature of HR+ breast cancer subgroups, providing valuable insights into personalized treatment strategies and management options.

Identification of cuproptosis-related patterns and construction of a scoring system for predicting prognosis, tumor microenvironment-infiltration characteristics, and immunotherapy efficacy in breast cancer.

Background: Cuproptosis, a recently discovered refreshing form of cell death, is distinct from other known mechanisms. As copper participates in cell death, the induction of cancer cell death with copper ionophores may emerge as a new avenue for cancer treatment. However, the role of cuproptosis in tumor microenvironment (TME) cell infiltration remains unknown. Methods: We systematically evaluated the cuproptosis patterns in The Cancer Genome Atlas (TCGA) database in breast cancer (BRCA) samples based on 10 cuproptosis-related genes (CRGs), and correlated these patterns with the prognosis and characteristics of TME cell infiltration. A principal component analysis algorithm was used to construct a cuproptosis score to quantify the cuproptosis pattern in individual tumors. Further, the relationships between the cuproptosis score and transcription background, clinical features, characteristics of TME cell infiltration, drug response, and efficacy of immunotherapy were assessed. Results: Two distinct cuproptosis patterns with distinct prognoses were identified; their TME characteristics were found to be consistent with the immune-excluded and immune-inflamed phenotypes, respectively. The cuproptosis patterns in individual patients were evaluated using the cuproptosis score based on the cuproptosis phenotype-related genes, contributing to distinguishing biological processes, clinical outcome, immune cell infiltration, genetic variation, and drug response. Univariate and multivariate Cox regression analyses verified this score as an independent prognostic predictor in BRCA. A high cuproptosis score, characterized by immune activation, suggests an inflamed tumor and immune-inflamed phenotype with poor survival and a low cuproptosis score, characterized by immune suppression, indicates a non-inflamed tumor and immune-excluded phenotype with better survival. Significant differences were observed in the IC50 between the high and low cuproptosis score groups receiving chemotherapy and targeted therapy drugs. In the two immunotherapy cohorts, patients with a higher cuproptosis score experienced considerable therapeutic advantages and clinical benefits. Conclusions: This study is the first to elucidate the prominent role of cuproptosis in the clinical outcome and the formation of TME diversity and complexity in BRCA. Estimating cuproptosis patterns in tumors could help predict the prognosis and characteristics of TME cell infiltration and guide more effective chemotherapeutic and immunotherapeutic strategies.

Revealing the Potential Markers of N(4)-Acetylcytidine through acRIP-seq in Triple-Negative Breast Cancer.

Understanding the causes of tumorigenesis and progression in triple-receptor negative breast cancer (TNBC) can help the design of novel and personalized therapies and prognostic assessments. Abnormal RNA modification is a recently discovered process in TNBC development. TNBC samples from The Cancer Genome Atlas database were categorized according to the expression level of NAT10, which drives acetylation of cytidine in RNA to N(4)-acetylcytidine (ac4C) and affects mRNA stability. A total of 703 differentially expressed long non-coding RNAs (lncRNAs) were found between high- and low-expressed NAT10 groups in TNBC. Twenty of these lncRNAs were significantly associated with prognosis. Two breast cancer tissues and their paired normal tissues were sequenced at the whole genome level using acetylated RNA immunoprecipitation sequencing (acRIP-seq) technology to identify acetylation features in TNBC, and 180 genes were significantly differentially ac4c acetylated in patients. We also analyzed the genome-wide lncRNA expression profile and constructed a co-expression network, containing 116 ac4C genes and 1080 lncRNAs. Three of these lncRNAs were prognostic risk lncRNAs affected by NAT10 and contained in the network. The corresponding reciprocal pairs were "LINC01614-COL3A1", "OIP5-AS1-USP8", and "RP5-908M14.9-TRIR". These results indicate that RNA ac4c acetylation involves lncRNAs and affects the tumor process and prognosis of TNBC. This will aid the prediction of drug targets and drug sensitivity.

A Novel Necroptosis-Associated lncRNA Signature Can Impact the Immune Status and Predict the Outcome of Breast Cancer.

Breast cancer (BRCA) is one of the leading causes of death among women worldwide, and drug resistance often leads to a poor prognosis. Necroptosis is a type of programmed cell death (PCD) and exhibits regulatory effects on tumor progression, but few studies have focused on the relationships between necroptosis-associated lncRNAs and BRCA. In this study, we established a signature basis of 7 necroptosis-related lncRNAs associated with prognosis and divided BRCA patients into high- and low-risk groups. Kaplan-Meier curves all showed an adverse prognosis for patients in the high-risk group. Cox assays confirmed that risk score was an independent prognostic factor for BRCA patients. The receiver operating characteristic (ROC) curve proved the predictive accuracy of the signature and the area under the curve (AUC) values of the risk score reached 0.722. The nomogram relatively accurately predicted the prognosis of the patients. GSEA analysis suggested that the related signaling pathways and biological processes enriched in the high- and low-risk groups may influence the tumor microenvironment (TME) of BRCA. ssGSEA showed the difference in immune cell infiltration, immune pathway activation, and immune checkpoint expression between the two risk groups, with the low-risk group more suitable for immunotherapy. According to the significant difference in IC50 between risk groups, patients can be guided for an individualized treatment plan. Overall, the authors established a prognostic signature consisting of 7 necroptosis-associated lncRNAs that can independently predict the clinical outcome of BRCA patients. The difference in the tumor immune microenvironment between the low- and high-risk populations may be the reason for the resistance to immunotherapy in some patients.

Toward Exempting from Sentinel Lymph Node Biopsy in T1 Breast Cancer Patients: A Retrospective Study.

Background and Objective: Sentinel lymph node biopsy (SLNB) is used to assess the status of axillary lymph node (ALN), but it causes many adverse reactions. Considering the low rate of sentinel lymph node (SLN) metastasis in T1 breast cancer, this study aims to identify the characteristics of T1 breast cancer without SLN metastasis and to select T1 breast cancer patients who avoid SLNB through constructing a nomogram. Methods: A total of 1,619 T1 breast cancer patients with SLNB in our hospital were enrolled in this study. Through univariate and multivariate logistic regression analysis, we analyzed the tumor anatomical and clinicopathological factors and constructed the Heilongjiang Medical University (HMU) nomogram. We selected the patients exempt from SLNB by using the nomogram. Results: In the training cohort of 1,000 cases, the SLN metastasis rate was 23.8%. Tumor volume, swollen axillary lymph nodes, pathological types, and molecular subtypes were found to be independent predictors for SLN metastasis in multivariate regression analysis. Distance from nipple or surface and position of tumor have no effect on SLN metastasis. A regression model based on the results of the multivariate analysis was developed to predict the risk of SLN metastasis, indicating an AUC of 0.798. It showed excellent diagnostic performance (AUC = 0.773) in the validation cohort. Conclusion: The HMU nomogram for predicting SLN metastasis incorporates four variables, including tumor volume, swollen axillary lymph nodes, pathological types, and molecular subtypes. The SLN metastasis rates of intraductal carcinoma and HER2 enriched are 2.05% and 6.67%. These patients could be included in trials investigating the SLNB exemption.

Exploring effects of DNA methylation and gene expression on pan-cancer drug response by mathematical models.

Since genetic alteration only accounts for 20%-30% in the drug effect-related factors, the role of epigenetic regulation mechanisms in drug response is gradually being valued. However, how epigenetic changes and abnormal gene expression affect the chemotherapy response remains unclear. Therefore, we constructed a variety of mathematical models based on the integrated DNA methylation, gene expression, and anticancer drug response data of cancer cell lines from pan-cancer levels to identify genes whose DNA methylation is associated with drug response and then to assess the impact of epigenetic regulation of gene expression on the sensitivity of anticancer drugs. The innovation of the mathematical models lies in: Linear regression model is followed by logistic regression model, which greatly shortens the calculation time and ensures the reliability of results by considering the covariates. Second, reconstruction of prediction models based on multiple dataset partition methods not only evaluates the model stability but also optimizes the drug-gene pairs. For 368,520 drug-gene pairs with P < 0.05 in linear models, 999 candidate pairs with both AUC ≥ 0.8 and P < 0.05 were obtained by logistic regression models between drug response and DNA methylation. Then 931 drug-gene pairs with 45 drugs and 491 genes were optimized by model stability assessment. Integrating both DNA methylation and gene expression markedly increased predictive power for 732 drug-gene pairs where 598 drug-gene pairs including 44 drugs and 359 genes were prioritized. Several drug target genes were enriched in the modules of the drug-gene-weighted interaction network. Besides, for cancer driver genes such as EGFR, MET, and TET2, synergistic effects of DNA methylation and gene expression can predict certain anticancer drugs' responses. In summary, we identified potential drug sensitivity-related markers from pan-cancer levels and concluded that synergistic regulation of DNA methylation and gene expression affect anticancer drug response.

Intratumor heterogeneity of breast cancer detected by epialleles shows association with hypoxic microenvironment.

Rationale: In breast cancer, high intratumor DNA methylation heterogeneity can lead to drug-resistant, metastasis and poor prognosis of tumors, which increases the complexity of cancer diagnosis and treatment. However, most studies are limited to average DNA methylation level of individual CpGs and ignore heterogeneous DNA methylation patterns of cell subpopulations within the tumor. Thus, quantifying the variability in DNA methylation pattern in sequencing reads is valuable for understanding intratumor heterogeneity. Methods: We performed Reduced Representation Bisulfite Sequencing and RNA sequencing for tumor core and tumor periphery regions within one breast tumor. By developing a method named "epialleJS" based on Jensen-Shannon divergence, we detected the differential epialleles between tumor core and tumor periphery (CPDEs). We then explored the correlation between intratumor methylation heterogeneity and hypoxic microenvironment in TCGA breast cancer cohort. Results: More than 70% of CPDEs had higher epipolymorphism in tumor core than tumor periphery, and these CPDEs had lower methylation in tumor core. The CPDEs with lower methylation in tumor core may associate with hypoxic tumor microenvironment. Moreover, we identified a signature of five hypoxia-related DNA methylation markers which can predict the prognosis of breast cancer patients, including a CpG site cg15190451 in gene SLC16A5. Furthermore, immunohistochemical analysis confirmed that the expression of SLC16A5 was associated with clinicopathological characteristics and survival of breast cancer patients. Conclusions: The analysis of intratumor DNA methylation heterogeneity based on epialleles reveals that disordered methylation patterns in tumor core are associated with hypoxic microenvironment, which provides a framework for understanding biological heterogeneous behavior and guidance for developing effective treatment schemes for breast cancer patients.

Low Expression of the Polycomb Protein RING1 Predicts Poor Prognosis in Human Breast Cancer.

BACKGROUND: To date, breast cancer remains the most common malignant tumor in women. In recent years, a growing number of studies on polycomb proteins have been conducted. The Ring finger protein1 (RING1), an essential component of the polycomb family of proteins, plays vital roles in the tumorigenesis of various cancer types. However, further research is required in determining RING1 expression and prognostic value in breast cancer. METHOD: RING1 expression level in multiple cancer types was evaluated using the XENA and UALCAN databases. Real-time quantitative PCR (real-time qPCR) and immunohistochemistry (IHC) were used to confirm this expression. The prognostic value was analyzed using our follow-up data and the Kaplan-Meier plotter website. RING1 co-expressed genes and its promoter methylation level were calculated using the cBioPortal and UALCAN online tools. The gene ontology (GO) and the Kyoto encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed using the DAVID online analysis tool. RESULT: RING1 expression was upregulated in CHOL (Bile Duct Cancer), ESCA (Esophageal Cancer), LIHC (Liver Cancer), and PCPG (Pheochromocytoma & Paraganglioma). However, its expression level was decreased in COAD (Colon Cancer), KICH (Kidney Chromophobe), KIRP (kidney papillary cell carcinoma), THCA (Thyroid Cancer), and BRCA (Breast carcinoma). RING1 low expression is an unfavorable prognostic factor in many cancer patients, especially in breast cancer patients. For breast cancer, the IHC result showed that RING1 protein expression significantly and negatively correlates with tumor size (P = 0.029), LNM (P = 0.017), TNM stage (P = 0.016), ER (P = 0.005), Ki67 (P = 0.015), and p53 status (P = 0.034). Moreover, the multivariate Cox regression model indicated that RING1 (P = 0.038) and ER (P = 0.029) expressions were independent prognostic markers for breast cancer. RING1 co-expressed genes were selected and included HDAC10, PIN1, CDK3, BAX, and BAD. GO analysis and KEGG pathway analyses revealed that RING1 related genes, were mainly enriched in "regulation of transcription", "apoptotic process", "protein transport", "protein binding", "Notch signaling pathway", and "Homologous recombination". CONCLUSION: RING1 expression was downregulated in breast cancer, and its low expression was associated with worse disease outcomes. RING1 may act as a new prognostic biomarker for breast cancer.

Correction to: LINC00673 is activated by YY1 and promotes the proliferation of breast cancer cells via the miR-515-5p/MARK4/Hippo signaling pathway.

An amendment to this paper has been published and can be accessed via the original article.

Prediction of transcription factors binding events based on epigenetic modifications in different human cells.

Aim: We aim to predict transcription factor (TF) binding events from knowledge of gene expression and epigenetic modifications. Materials & methods: TF-binding events based on the Encode project and The Cancer Genome Atlas data were analyzed by the random forest method. Results: We showed the high performance of TF-binding predictive models in GM12878, HeLa, HepG2 and K562 cell lines and applied them to other cell lines and tissues. The genes bound by the top TFs (MAX and MAZ) were significantly associated with cancer-related processes such as cell proliferation and DNA repair. Conclusion: We successfully constructed TF-binding predictive models in cell lines and applied them in tissues.

Isobaric Tags for Relative and Absolute Quantitation in Proteomic Analysis of Potential Biomarkers in Invasive Cancer, Ductal Carcinoma In Situ, and Mammary Fibroadenoma.

OBJECTIVES: Breast malignancy is a serious threat to women's health around the world. Following the rapid progress in the field of cancer diagnostics and identification of pathological markers, breast tumor treatment methods have been greatly improved. However, for invasive, ductal carcinomas and mammary fibroadenoma, there is an urgent demand for better breast tumor-linked biomarkers. The current study was designed to identify diagnostic and/or therapeutic protein biomarkers for breast tumors. METHODS: A total of 140 individuals were included, comprising 35 healthy women, 35 invasive breast cancers (IBC), 35 breast ductal carcinomas in situ (DCIS), and 35 breast fibroadenoma patients. Isobaric tags for relative and absolute quantitation (iTRAQ) proteomic analysis was employed to characterize differentially expressed proteins for potential biomarkers in IBC, DCIS, and fibroadenomas by comparisons with their matched adjacent tissues and/or normal breast tissues. The public databases Metascape and String were used for bioinformatic analyses. RESULTS: Using the proteomics approach, we identified differentially expressed proteins in tissues of different breast tumors compared to normal/adjacent breast tissues, including 100 in IBC, 52 in DCIS, and 44 in fibroadenoma. Among the 100 IBC differentially expressed proteins, 37 were found to be specific to this type of cancer only. Additionally, four proteins were specifically expressed in DCIS and four in fibroadenoma. Compared to corresponding adjacent tissues and normal breast tissues, 18 step-changing proteins were differentially expressed in IBC, 14 in DCIS, and 13 in fibroadenoma, respectively. Compared to DCIS and normal breast tissues, 65 proteins were differentially expressed in IBC with growing levels of malignancy. CONCLUSIONS: The identified potential protein biomarkers may be used as diagnostic and/or therapeutic targets in breast tumors.

Nrf2 drives oxidative stress-induced autophagy in nucleus pulposus cells via a Keap1/Nrf2/p62 feedback loop to protect intervertebral disc from degeneration.

Intervertebral disc (IVD) degeneration is known to aggravate with age and oxidative stress is implicated in the pathogenesis of many age-related diseases. Nuclear factor (erythroid-derived-2)-like 2 (Nrf2) can confer adaptive protection against oxidative and proteotoxic stress in cells. In this study, we assessed whether Nrf2 can protect against oxidative stress in nucleus pulposus (NP) cells. In addition, we investigated Nrf2 expression in NP tissue samples from patients with different degrees of IVD degeneration and a mouse model of aging and IVD degeneration and the influence of H2O2-induced oxidative stress on autophagic pathways in NP cells. Autophagy was assessed by measuring levels of autophagy-related protein (ATG) family members and the autophagic markers, p62 and LC3. We found that expression of Nrf2 progressively decreased in human NP tissue samples of patients with increasing degrees of IVD degeneration. Nrf2 deficiency leads to the degeneration of IVDs during aging. Nrf2 knockout also aggravates IVD degeneration and reduces autophagic gene expression in an induced mouse model of IVD degeneration. The detrimental effects of H2O2-induced oxidative stress were increased in autophagy-deficient cells via reduced expression of Atg7 and the Keap1-Nrf2-p62 autophagy pathway. Taken together, these results suggest that excessive oxidative stress causes the upregulation of autophagy, and autophagy acts as an antioxidant feedback response activated by a Keap1-Nrf2-p62 feedback loop in IVD degeneration.

The transcriptional landscape of lncRNAs reveals the oncogenic function of LINC00511 in ER-negative breast cancer.

Advances in the molecular characteristics of cancers have facilitated the classification system from morphology to molecular characteristic-based subtypes. Cancer profiling has expanded in its focus from protein-coding genes to noncoding RNAs, with advances in the depth and quality of transcriptome sequencing. Here, we examined the profiles of long noncoding RNAs (lncRNAs) according to breast cancer subtype categories in The Cancer Genome Atlas (TCGA) database to identify a cohort of breast cancer- and oestrogen receptor (ER)-negative-associated lncRNAs. According to the prioritization of variation in ER-negative-associated lncRNAs, we identified and investigated the role of LINC00511 in breast cancer. We determined that high LINC00511 expression was an unfavourable prognostic factor for patients with breast cancer. Furthermore, LINC00511 promoted tumour growth by accelerating the G1/S transition and inhibiting apoptosis. At the transcriptional level, ER deficiency directly affected the expression of LINC00511 activated by transcription factor AP-2 (TFAP-2) in breast cancer cells. Moreover, mechanistic investigations demonstrated that ER-negative-associated LINC00511 interacted with enhancer of zeste homologue 2 (EZH2, the catalytic subunit of polycomb repressive complex 2, PRC2) and recruited PRC2 to mediate histone methylation, contributing to the repression of CDKN1B in the nucleus. This process resulted in altered ER-negative breast cancer cell biology. By highlighting the oncogenic function of LINC00511, we revealed the role of lncRNAs in regulating the network of cell cycle control in ER-negative breast cancer and suggested the exploitation of LINC00511 as an anticancer therapy in the future.

Landscape of tumor suppressor long noncoding RNAs in breast cancer.

BACKGROUND: The landscape and biological functions of tumor suppressor long noncoding RNAs in breast cancer are still unknown. METHODS: Data from whole transcriptome sequencing of 33 breast specimens in the Harbin Medical University Cancer Center cohort and The Cancer Genome Atlas was applied to identify and validate the landscape of tumor suppressor long noncoding RNAs, which was further validated by The Cancer Genome Atlas pancancer data including 33 cancer types and 12,839 patients. Next, the expression model, prognostic roles, potential biological functions and epigenetic regulation of tumor suppressor long noncoding RNAs were investigated and validated in the breast cancer and pancancer cohorts. Finally, EPB41L4A-AS2 was selected to validate our novel finding, and the tumor suppressive roles of EPB41L4A-AS2 in breast cancer were examined. RESULTS: We identified and validated the landscape of tumor suppressor long noncoding RNAs in breast cancer. The expression of the identified long noncoding RNAs was downregulated in cancer tissue samples compared with normal tissue samples, and these long noncoding RNAs correlated with a favorable prognosis in breast cancer patients and the patients in the pancancer cohort. Multiple carcinogenesis-associated biological functions were predicted to be regulated negatively by these long noncoding RNAs. Moreover, these long noncoding RNAs were transcriptionally regulated by epigenetic modification, including DNA methylation and histone methylation modification. Finally, EPB41L4A-AS2 inhibited breast cancer cell proliferation, migration and invasion and induced cell apoptosis in vitro. Mechanistically, EPB41L4A-AS2, acting at least in part as a tumor suppressor, upregulated tumor suppressor gene expression. Moreover, ZNF217 recruited EZH2 to the EPB41L4A-AS2 locus and suppressed the expression of EPB41L4A-AS2 by epigenetically increasing H3K27me3 enrichment. CONCLUSIONS: This work enlarges the functional landscape of known long noncoding RNAs in human cancer and provides novel insights into the suppressive roles of these long noncoding RNAs.

LINC00673 is activated by YY1 and promotes the proliferation of breast cancer cells via the miR-515-5p/MARK4/Hippo signaling pathway.

BACKGROUND: An increasing number of studies have shown that long noncoding RNAs (lncRNAs) play essential roles in tumor initiation and progression. LncRNAs act as tumor promoters or suppressors by targeting specific genes via epigenetic modifications and competing endogenous RNA (ceRNA) mechanisms. In this study, we explored the function and detailed mechanisms of long intergenic nonprotein coding RNA 673 (LINC00673) in breast cancer progression. METHODS: Quantitative real-time PCR (qRT-PCR) was used to examine the expression of LINC00673 in breast cancer tissues and in adjacent normal tissues. Gain-of-function and loss-of function experiments were conducted to investigate the biological functions of LINC00673 in vitro and in vivo. We also explored the potential role of LINC00673 as a therapeutic target using antisense oligonucleotide (ASO) in vivo. RNA sequencing (RNA-seq), dual-luciferase reporter assays, chromatin immunoprecipitation (ChIP) assay, and rescue experiments were performed to uncover the detailed mechanism of LINC00673 in promoting breast cancer progression. RESULTS: In the present study, LINC00673 displayed a trend of remarkably increased expression in breast cancer tissues and was associated with poor prognosis in breast cancer patients. Importantly, LINC00673 depletion inhibited breast cancer cell proliferation by inhibiting the cell cycle and increasing apoptosis. Furthermore, ASO therapy targeting LINC00673 substantially suppressed breast cancer cell proliferation in vivo. Mechanistically, LINC00673 was found to act as a ceRNA by sponging miR-515-5p to regulate MARK4 expression, thus inhibiting the Hippo signaling pathway. Finally, ChIP assay showed that the transcription factor Yin Yang 1 (YY1) could bind to the LINC00673 promoter and increase its transcription in cis. CONCLUSIONS: YY1-activated LINC00673 may exert an oncogenic function by acting as a sponge for miR-515-5p to upregulate the MARK4 and then inhibit Hippo signaling pathway, and may serve as a potential therapeutic target.

Prediction of circRNAs Based on the DNA Methylation-Mediated Feature Sponge Function in Breast Cancer.

Several studies have found that DNA methylation is associated with transcriptional regulation and affect sponge regulation of non-coding RNAs in cancer. The integration of circRNA, miRNA, DNA methylation and gene expression data to identify sponge circRNAs is important for revealing the role of DNA methylation-mediated regulation of sponge circRNAs in cancer progression. We established a DNA methylation-mediated circRNA crosstalk network by integrating gene expression, DNA methylation and non-coding RNA data of breast cancer in TCGA. Four modules (26 candidate circRNAs) were mined. Next, 10 DNA methylation-mediated sponge circRNAs (sp_circRNAs) and five sponge driver genes (sp_driver genes) in breast cancer were identified in the CMD network using a computational process. Among the identified genes, ERBB2 was associated with six sponge circRNAs, which illustrates its better sponge regulatory function. Survival analysis showed that DNA methylations of 10 sponge circRNA host genes are potential prognostic biomarkers in the TCGA dataset (p = 0.0239) and GSE78754 dataset (p = 0.0377). In addition, the DNA methylation of two sponge circRNA host genes showed a significant negative correlation with their driver gene expressions. We developed a strategy to predict sponge circRNAs by DNA methylation mediated with playing the role of regulating breast cancer sponge driver genes.

Development of a method for identifying and functionally analyzing allele-specific DNA methylation based on BS-seq data.

Aim: To comprehensively identify allele-specific DNA methylation (ASM) at the genome-wide level. Methods: Here, we propose a new method, called GeneASM, to identify ASM using high-throughput bisulfite sequencing data in the absence of haplotype information. Results: A total of 2194 allele-specific DNA methylated genes were identified in the GM12878 lymphocyte lineage using GeneASM. These genes are mainly enriched in cell cytoplasm function, subcellular component movement or cellular linkages. GM12878 methylated DNA immunoprecipitation sequencing, and methylation sensitive restriction enzyme sequencing data were used to evaluate ASM. The relationship between ASM and disease was further analyzed using the The Cancer Genome Atlas (TCGA) data of lung adenocarcinoma (LUAD), and whole genome bisulfite sequencing data. Conclusion: GeneASM, which recognizes ASM by high-throughput bisulfite sequencing and heterozygous single-nucleotide polymorphisms, provides new perspective for studying genomic imprinting.