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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.

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

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.

Background: Triple-negative breast cancer (TNBC) still lacks effective treatments, and understanding the causes of its tumorigenesis and tumor progression is helpful for prognostic evaluation. N(4)-acetylcytidine (ac4C), an epigenetic modification of RNA, whose regulatory mechanism is still unclear in TNBC tumors may provide a new perspective for understanding the development of TNBC.Methods: Two pairs of TNBC patient tissues were sequenced at the genome level using acRIP-seq technology, and differential ac4C genes were identified by Robust Rank Aggregation (RRA). Then, by integrating genome-wide lncRNA expression profiles in TCGA, we constructed a co-expression network containing 180 ac4C genes and mined 1080 lncRNA gene relationship pairs. And use cox regression analysis to screen genes associated with prognosis. Additionally, drug sensitivity was predicted using a drug target network of differential ac4C genes.Results: We screened a total of 180 differential ac4c genes, of which 6 genes were significantly associated with prognosis. In addition, we screened out three lncRNAs interacting with prognostic risk genes, and the corresponding interaction pairs were "LINC01614-COL3A1", "OIP5-AS1-USP8" and "RP5-908M14.9-TRIR". Significant ac4C genes COL3A, USP8 and TRIR1 were accurately predicted with the sensitivity of Doxorubicin and Paclitaxel, the main chemotherapy drugs in TNBC. Conclusions: This study suggests that RNA ac4C acetylation may be a potential marker of prognosis and drug sensitivity/target through the involvement of lncRNA. These results will be used as a guide for experiments.

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. N

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.

Background: Colorectal cancer (CRC), a severe disease in the world. The dysregulation of genes plays a significant role in cancer. Method: In the present study, we first identified differentially expressed genes (DEGs) of CRC in the GSE71187 data set from the Gene Expression Omnibus (GEO) database. And through GO terminology and Gene and Genome (KEGG) pathway, the up-regulated DEG and down-regulated genes were enriched. Then, we selected hub genes and studied their related prognostic value through protein-protein interaction (PPI) network and integrated bioinformatics analysis. Finally, 7 genes with prognostic value were obtained by survival analysis and multivariate Cox proportional hazards regression models, as well as verified in the Oncomine and UALCAN database.Result: A total of 3,588 DEGs were identified with 1,474 upregulated and 3,114 downregulated. Then, GO terms and Genes and Genomes (KEGG) pathway analysis revealed that upregulated DEGs and down-regulated genes were mainly involved in important GO terms and KEGG pathway, for example, defense response to other organism, leukocyte differentiation and epidermis developmen. In the PP network analysis, 6 hub modules and 86 module genes were identified. In the end, 7 genes with prognostic value were obtained through survival and multi-factor analysis. They have significant differences in varying degrees at the level of DNA, mRNA and protein.Conclusion: The results of the study may provide novel insight into the genes and associated pathways involved in CRC, and aid the identifcation of novel therapeutic targets and prognostic marker of CRC.

Additional file 2 : Figure S2. Potential therapeutic role of LINC00673 in breast cancer progression. (a) Effect of ASO on apoptosis in mouse organs. (b) H&E staining and sections were observed under an Olympus microscope. (c) Serum chemistry markers of liver and renal function in the 0.9% normal saline and ASO treatment groups. GPT: glutamic pyruvic transaminase; ALP: alkaline phosphatase; GGT: gamma-glutamyl transpeptidase; BUN: blood urea nitrogen; CRE: serum creatinine; and TBIL: total bilirubin.*P

Additional file 1 : Figure S1. LINC00673 is highly expressed in breast cancer tissues. (a) LINC00673 data downloaded from the MiTranscriptome database. (b) Expression of LINC00673 in 950 breast cancer tissues and 107 normal breast tissues (TCGA). *** P

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.

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.

Additional file 2: Figure S2. Potential therapeutic role of LINC00673 in breast cancer progression. (a) Effect of ASO on apoptosis in mouse organs. (b) H&E staining and sections were observed under an Olympus microscope. (c) Serum chemistry markers of liver and renal function in the 0.9% normal saline and ASO treatment groups. GPT: glutamic pyruvic transaminase; ALP: alkaline phosphatase; GGT: gamma-glutamyl transpeptidase; BUN: blood urea nitrogen; CRE: serum creatinine; and TBIL: total bilirubin.*P

Background: 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. Method: 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 5 sponge driver genes (sp_driver genes) in breast cancer were identified in the CMD network using a computational process. Findings: 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. Interpretation: We developed a strategy to predict sponge circRNAs by DNA methylation mediated with playing the role of regulating breast cancer sponge driver genes. Funding Statement: This work was supported by National Natural Science Foundation of China [grant number 81573021], the Natural Science Foundation of Heilongjiang Province [grant number ZD2015003], and the Heilongjiang Science and Technology Plan Project [YS17C22]. Declaration of Interests: We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and company that could be construed as influencing the position presented in, or the review of, this manuscript. Ethics Approval Statement: The authors declare: "Not applicable."

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.