Super-enhancers are important for controlling and defining the expression of cell-specific genes. With research on human disease and biological processes, human H3K27ac ChIP-seq datasets are accumulating rapidly, creating the urgent need to collect and process these data comprehensively and efficiently. More importantly, many studies showed that super-enhancer-associated single nucleotide polymorphisms (SNPs) and transcription factors (TFs) strongly influence human disease and biological processes. Here, we developed a comprehensive human super-enhancer database (SEdb, http://www.licpathway.net/sedb) that aimed to provide a large number of available resources on human super-enhancers. The database was annotated with potential functions of super-enhancers in the gene regulation. The current version of SEdb documented a total of 331 601 super-enhancers from 542 samples. Especially, unlike existing super-enhancer databases, we manually curated and classified 410 available H3K27ac samples from >2000 ChIP-seq samples from NCBI GEO/SRA. Furthermore, SEdb provides detailed genetic and epigenetic annotation information on super-enhancers. Information includes common SNPs, motif changes, expression quantitative trait locus (eQTL), risk SNPs, transcription factor binding sites (TFBSs), CRISPR/Cas9 target sites and Dnase I hypersensitivity sites (DHSs) for in-depth analyses of super-enhancers. SEdb will help elucidate super-enhancer-related functions and find potential biological effects.

In non–small cell lung cancer (NSCLC), estrogen significantly promotes NSCLC cell growth via estrogen receptor beta (ERβ). However, the effects by which ERβ contributes to metastasis in NSCLC have not been previously reported. This study aims at defining whether the stimulation of ERβ promotes NSCLC metastasis in vitro and in vivo. Here, Our results showed that estrogen and ERβ agonist enhanced aggressiveness of two lung cancer cell lines (A549 and H1793) and promoted murine lung metastasis formation. ER-inhibitor Fulvestrant treatment or ERβ-knockdown significantly suppressed the migration, invasion and nodule formation of NSCLC cells. The expression level of ERβ protein was analyzed in matched samples of metastatic lymph node and primary tumor tissues from the same individuals, and we found significantly higher levels of ERβ were expressed in lymph node compared to primary tumor tissues. Moreover, Studies on both surgical biopsies and on lung cancer cells revealed that the expression level of ERβ and matrix-metalloproteinase-2 (MMP-2) were associated. Furthermore, inhibition of ERβ resulted in down-regulation of MMP-2 expression. Taken together, our results demonstrate that activation of ERβ in lung cancer cells promotes tumor metastasis through increasing expression of invasiveness-associated MMP-2. These results also highlight the therapeutic potential of inhibition of ERβin the treatment of advanced NSCLC.

Circulating cell-free DNA (cfDNA), which can be obtained from plasma or serum by non-invasive procedures, has showed great potential to predict treatment response and survival for cancer patients. Several studies have assessed the prognostic and predictive value of cfDNA in non-small cell lung cancer (NSCLC). However, these studies were often small and reported varying results. To address this issue, a meta-analysis was carried out. A total of 22 studies involving 2518 patients were subjected to the final analysis. Our results indicated that NSCLC patients with higher cfDNA concentration had shorter median progression-free survival (PFS) and overall survival (OS) time. In addition, high levels of cfDNA were significantly associated with poor PFS (hazard ratio or HR, 1.32; 95% CI, 1.02-1.71) and OS (HR, 1.64; 95% CI, 1.26-2.15). With respect to tumor specific mutations, we failed to reveal significant differences for PFS (HR, 1.30; 95% CI, 0.66-2.56) and OS (HR, 1.05; 95% CI, 0.49-2.25) when NSCLC patients were grouped according to KRAS genotype detected in cfDNA. However, NSCLC patients which harbored EGFR activating mutation in cfDNA had a greater chance of response to EGFR-TKIs (odds ratio or OR, 1.96; 95% CI, 1.59-2.42). No significant publication bias was detected in this study. In conclusion, cfDNA could act as a prognostic and predictive biomarker for patients with NSCLC.

BackgroundIn non-small cell lung cancer (NSCLC), estrogen (E2) significantly promotes NSCLC cell growth via estrogen receptor beta (ERβ). Discovery and elucidation of the mechanism underlying estrogen-promoted NSCLC progression is critical for effective preventive interventions. IL6 has been demonstrated to be involved in the development, progression and metastasis in several cancers and IL6 overexpression is associated with poor prognosis in NSCLC. However, the exact role played by IL6 in estrogen-promoted NSCLC progress remain unknown. Here, we evaluated the expression and biological effects of IL6 in NSCLC cells when treated with E2 and explored the underlying mechanism of IL6 in E2-promoted NSCLC progression.MethodsExpression of ERβ/IL6 in 289 lung cancer samples was assessed by immunohistochemistry. Matched samples of metastatic lymph node and primary tumor tissues were used to quantify the expression of ERβ/IL6 by western blot. Expression levels of IL6 in NSCLC cells were quantified by western blotting, ELISA, and immunofluorescence staining. The effects of IL6 stimulated by E2 on cell malignancy were evaluated using CCK8, colony formation, wound healing and transwell. Furthermore, overexpression and knockdown ERβ constructs were constructed to measure the expression of IL6. The effects of IL6 stimulated by E2 on tumor growth were evaluated using a urethane-induced adenocarcinoma model. In addition, a xenograft mouse model was used to observe differences in ERβ subtype tumor growth with respect to IL6 expression.ResultsIL6/ERβ expression were significantly increased in lung cancer. Higher IL6/ERβ expression was associated with decreased differentiation or increased metastasis. IL6 was an independent prognostic factor for overall survival (OS), higher IL6 expression was associated with decreased OS. Furthermore, ERβ regulates IL6 expression via MAPK/ERK and PI3K/AKT pathways when stimulated by E2 and promotes cell malignancy in vitro and induced tumor growth in vivo. Finally we confirm that ERβ isolation 1/5 is essential for E2 promotion of IL6 expression, while ERβ2 not.ConclusionsOur findings demonstrate that E2 stimulates IL6 expression to promote lung adenocarcinoma progression through the ERβ pathway. We also clarify the difference in each ERβ subtype for E2 promoting IL6 expression, suggesting that ERβ/IL6 might be potential targets for prognostic assessment and therapeutic intervention in lung cancer.Electronic supplementary materialThe online version of this article (10.1186/s13046-018-0804-5) contains supplementary material, which is available to authorized users.

BackgroundNon-small cell lung cancer (NSCLC) patients with sensitive epidermal growth factor receptor (EGFR) mutations are successfully treated with EGFR tyrosine kinase inhibitors (EGFR-TKIs); however, resistance to treatment inevitably occurs. Given lipid metabolic reprogramming is widely known as a hallmark of cancer and intimately linked with EGFR-stimulated cancer growth. Activation of EGFR signal pathway increased monounsaturated fatty acids (MUFA) and lipid metabolism key enzyme Stearoyl-CoA Desaturase 1 (SCD1) expression. However the correlation between EGFR-TKI resistance and lipid metabolism remains to be determined.MethodsIn this study the differences in lipid synthesis between paired TKI-sensitive and TKI-resistant patient tissues and NSCLC cell lines were explored. Oleic acid (OA, a kind of MUFA, the SCD1 enzymatic product) was used to simulate a high lipid metabolic environment and detected the affection on the cytotoxic effect of TKIs (Gefitinib and osimertinib) in cell lines with EGFR-activating mutations. (20S)-Protopanaxatriol (g-PPT), an aglycone of ginsenosides, has been reported to be an effective lipid metabolism inhibitor, was used to inhibit lipid metabolism. Additionally, synergism in cytotoxic effects and signal pathway activation were evaluated using CCK-8 assays, Western blotting, flow cytometry, Edu assays, plate clone formation assays and immunofluorescence. Furthermore, two xenograft mouse models were used to verify the in vitro results.ResultsGefitinib-resistant cells have higher lipid droplet content and SCD1 expression than Gefitinib-sensitive cells in both NSCLC cell lines and patient tissues. Additionally oleic acid (OA, a kind of MUFA, the SCD1 enzymatic product) abrogates the cytotoxic effect of both Gefitinib and osimertinib in cell lines with EGFR-activating mutations. As a reported effective lipid metabolism inhibitor, g-PPT significantly inhibited the expression of SCD1 in lung adenocarcinoma cells, and then down-regulated the content of intracellular lipid droplets. Combined treatment with Gefitinib and g-PPT reverses the resistance to Gefitinib and inhibits the activation of p-EGFR and the downstream signaling pathways.ConclusionsOur findings uncover a link between lipid metabolic reprogramming and EGFR-TKI resistance, confirmed that combination target both EGFR and abnormal lipid metabolism maybe a promising therapy for EGFR-TKI resistance and highlighting the possibility of monitoring lipid accumulation in tumors for predicting drug resistance.Electronic supplementary materialThe online version of this article (10.1186/s13046-019-1120-4) contains supplementary material, which is available to authorized users.

Enhancers are a class of cis-regulatory elements that can increase gene transcription by forming loops in intergenic regions, introns and exons. Enhancers, as well as their associated target genes, and transcription factors (TFs) that bind to them, are highly associated with human disease and biological processes. Although some enhancer databases have been published, most only focus on enhancers identified by high-throughput experimental techniques. Therefore, it is highly desirable to construct a comprehensive resource of manually curated enhancers and their related information based on low-throughput experimental evidences. Here, we established a comprehensive manually-curated enhancer database for human and mouse, which provides a resource for experimentally supported enhancers, and to annotate the detailed information of enhancers. The current release of ENdb documents 737 experimentally validated enhancers and their related information, including 384 target genes, 263 TFs, 110 diseases and 153 functions in human and mouse. Moreover, the enhancer-related information was supported by experimental evidences, such as RNAi, in vitro knockdown, western blotting, qRT-PCR, luciferase reporter assay, chromatin conformation capture (3C) and chromosome conformation capture-on-chip (4C) assays. ENdb provides a user-friendly interface to query, browse and visualize the detailed information of enhancers. The database is available at http://www.licpathway.net/ENdb.

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Accessible chromatin is a highly informative structural feature for identifying regulatory elements, which provides a large amount of information about transcriptional activity and gene regulatory mechanisms. Human ATAC-seq datasets are accumulating rapidly, prompting an urgent need to comprehensively collect and effectively process these data. We developed a comprehensive human chromatin accessibility database (ATACdb, http://www.licpathway.net/ATACdb), with the aim of providing a large amount of publicly available resources on human chromatin accessibility data, and to annotate and illustrate potential roles in a tissue/cell type-specific manner. The current version of ATACdb documented a total of 52 078 883 regions from over 1400 ATAC-seq samples. These samples have been manually curated from over 2200 chromatin accessibility samples from NCBI GEO/SRA. To make these datasets more accessible to the research community, ATACdb provides a quality assurance process including four quality control (QC) metrics. ATACdb provides detailed (epi)genetic annotations in chromatin accessibility regions, including super-enhancers, typical enhancers, transcription factors (TFs), common single-nucleotide polymorphisms (SNPs), risk SNPs, eQTLs, LD SNPs, methylations, chromatin interactions and TADs. Especially, ATACdb provides accurate inference of TF footprints within chromatin accessibility regions. ATACdb is a powerful platform that provides the most comprehensive accessible chromatin data, QC, TF footprint and various other annotations.