A data-adaptive methods in detecting exogenous methyltransferase accessible chromatin in human genome using nanopore sequencing.

MOTIVATION: Identifying chromatin accessibility is one of the key steps in studying the regulation of eukaryotic genomes. The combination of exogenous methyltransferase and nanopore sequencing provides an strategy to identify open chromatin over long genomic ranges at the single-molecule scale. However, endogenous methylation, non-open-chromatin-specific exogenous methylation and base-calling errors limit the accuracy and hinders its application to complex genomes. RESULTS: We systematically evaluated the impact of these three influence factors, and developed a model-based computational method, methyltransferase accessible genome region finder (MAGNIFIER), to address the issues. By incorporating control data, MAGNIFIER attenuates the three influence factors with data-adaptive comparison strategy. We demonstrate that MAGNIFIER is not only sensitive to identify the open chromatin with much improved accuracy, but also able to detect the chromatin accessibility of repetitive regions that are missed by NGS-based methods. By incorporating long-read RNA-seq data, we revealed the association between the accessible Alu elements and non-classic gene isoforms. AVAILABILITY AND IMPLEMENTATION: Freely available on web at https://github.com/Goatofmountain/MAGNIFIER.

capTEs enables locus-specific dissection of transcriptional outputs from reference and nonreference transposable elements.

Transposable elements (TEs) serve as both insertional mutagens and regulatory elements in cells, and their aberrant activity is increasingly being revealed to contribute to diseases and cancers. However, measuring the transcriptional consequences of nonreference and young TEs at individual loci remains challenging with current methods, primarily due to technical limitations, including short read lengths generated and insufficient coverage in target regions. Here, we introduce a long-read targeted RNA sequencing method, Cas9-assisted profiling TE expression sequencing (capTEs), for quantitative analysis of transcriptional outputs for individual TEs, including transcribed nonreference insertions, noncanonical transcripts from various transcription patterns and their correlations with expression changes in related genes. This method selectively identified TE-containing transcripts and outputted data with up to 90% TE reads, maintaining a comparable data yield to whole-transcriptome sequencing. We applied capTEs to human cancer cells and found that internal and inserted Alu elements may employ distinct regulatory mechanisms to upregulate gene expression. We expect that capTEs will be a critical tool for advancing our understanding of the biological functions of individual TEs at the locus level, revealing their roles as both mutagens and regulators in biological and pathogenic processes.

Single-cell exome sequencing reveals multiple subclones in metastatic colorectal carcinoma.

BACKGROUND: Colorectal cancer (CRC) is a major cancer type whose mechanism of metastasis remains elusive. METHODS: In this study, we characterised the evolutionary pattern of metastatic CRC (mCRC) by analysing bulk and single-cell exome sequencing data of primary and metastatic tumours from 7 CRC patients with liver metastases. Here, 7 CRC patients were analysed by bulk whole-exome sequencing (WES); 4 of these were also analysed using single-cell sequencing. RESULTS: Despite low genomic divergence between paired primary and metastatic cancers in the bulk data, single-cell WES (scWES) data revealed rare mutations and defined two separate cell populations, indicative of the diverse evolutionary trajectories between primary and metastatic tumour cells. We further identified 24 metastatic cell-specific-mutated genes and validated their functions in cell migration capacity. CONCLUSIONS: In summary, scWES revealed rare mutations that failed to be detected by bulk WES. These rare mutations better define the distinct genomic profiles of primary and metastatic tumour cell clones.

Accurate single-cell genotyping utilizing information from the local genome territory.

Single-nucleotide variant (SNV) detection in the genome of single cells is affected by DNA amplification artefacts, including imbalanced alleles and early PCR errors. Existing single-cell genotyper accuracy often depends on the quality and coordination of both the target single-cell and external data, such as heterozygous profiles determined by bulk data. In most single-cell studies, information from different sources is not perfectly matched. High-accuracy SNV detection with a limited single data source remains a challenge. We developed a new variant detection method, SCOUT (Single Cell Genotyper Utilizing Information from Local Genome Territory), the greatest advantage of which is not requiring external data while base calling. By leveraging base count information from the adjacent genomic region, SCOUT classifies all candidate SNVs into homozygous, heterozygous, intermediate and low major allele SNVs according to the highest likelihood score. Compared with other genotypers, SCOUT improves the variant detection performance by 2.0-77.5% in real and simulated single-cell datasets. Furthermore, the running time of SCOUT increases linearly with sequence length; as a result, it shows 400% average acceleration in operating efficiency compared with other methods.

Integrated epigenetic biomarkers in circulating cell-free DNA as a robust classifier for pancreatic cancer.

BACKGROUND: The high lethal rate of pancreatic cancer is partly due to a lack of efficient biomarkers for screening and early diagnosis. We attempted to develop effective and noninvasive methods using 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) markers from circulating cell-free DNA (cfDNA) for the detection of pancreatic ductal adenocarcinoma (PDAC). RESULTS: A 24-feature 5mC model that can accurately discriminate PDAC from healthy controls (area under the curve (AUC) = 0.977, sensitivity = 0.824, specificity = 1) and a 5hmC prediction model with 27 features demonstrated excellent detection power in two distinct validation sets (AUC = 0.992 and 0.960, sensitivity = 0.786 and 0.857, specificity = 1 and 0.993). The 51-feature model combining 5mC and 5hmC markers outperformed both of the individual models, with an AUC of 0.997 (sensitivity = 0.938, specificity = 0.955) and particularly an improvement in the prediction sensitivity of PDAC. In addition, the weighted diagnosis score (wd-score) calculated with the 5hmC model can distinguish stage I patients from stage II-IV patients. CONCLUSIONS: Both 5mC and 5hmC biomarkers in cfDNA are effective in PDAC detection, and the 5mC-5hmC integrated model significantly improve the detection sensitivity.

The Open Chromatin Landscape of Non-Small Cell Lung Carcinoma.

Non-small cell lung carcinoma (NSCLC) is a major cancer type whose epigenetic alteration remains unclear. We analyzed open chromatin data with matched whole-genome sequencing and RNA-seq data of 50 primary NSCLC cases. We observed high interpatient heterogeneity of open chromatin profiles and the degree of heterogeneity correlated to several clinical parameters. Lung adenocarcinoma and lung squamous cell carcinoma (LUSC) exhibited distinct open chromatin patterns. Beyond this, we uncovered that the broadest open chromatin peaks indicated key NSCLC genes and led to less stable expression. Furthermore, we found that the open chromatin peaks were gained or lost together with somatic copy number alterations and affected the expression of important NSCLC genes. In addition, we identified 21 joint-quantitative trait loci (joint-QTL) that correlated to both assay for transposase accessible chromatin sequencing peak intensity and gene expression levels. Finally, we identified 87 regulatory risk loci associated with lung cancer-related phenotypes by intersecting the QTLs with genome-wide association study significant loci. In summary, this compendium of multiomics data provides valuable insights and a resource to understand the landscape of open chromatin features and regulatory networks in NSCLC. SIGNIFICANCE: This study utilizes state of the art genomic methods to differentiate lung cancer subtypes.See related commentary by Bowcock, p. 4808.

Longitudinal personal DNA methylome dynamics in a human with a chronic condition.

Epigenomics regulates gene expression and is as important as genomics in precision personal health, as it is heavily influenced by environment and lifestyle. We profiled whole-genome DNA methylation and the corresponding transcriptome of peripheral blood mononuclear cells collected from a human volunteer over a period of 36 months, generating 28 methylome and 57 transcriptome datasets. We found that DNA methylomic changes are associated with infrequent glucose level alteration, whereas the transcriptome underwent dynamic changes during events such as viral infections. Most DNA meta-methylome changes occurred 80-90 days before clinically detectable glucose elevation. Analysis of the deep personal methylome dataset revealed an unprecedented number of allelic differentially methylated regions that remain stable longitudinally and are preferentially associated with allele-specific gene regulation. Our results revealed that changes in different types of 'omics' data associate with different physiological aspects of this individual: DNA methylation with chronic conditions and transcriptome with acute events.

Improved Macaca fascicularis gene annotation reveals evolution of gene expression profiles in multiple tissues.

BACKGROUNDS: Macaca fascicularis (M. fascicularis) is a primate model organism that played important role in studying human health. It is vital to better understand the similarity and differences of gene regulation between M. fascicularis and human. Current comparative study of gene regulation between the two species are limited by low quality of gene annotation and lack of regulatory element data on M. fascicularis genome. RESULTS: In this study, we improved the M. fascicularis gene annotation with 57 gene expression data from multiple tissues and, more importantly, a manual curation procedure. The new annotation enabled us to map gene expression and identify gene location more accurately. CONCLUSIONS: Comparing with human gene expression data from the same cell types, we characterized the evolution of expression patterns of homologous genes.

FASN, ErbB2-mediated glycolysis is required for breast cancer cell migration.

Both fatty acid synthase (FASN) and ErbB2 have been shown to promote breast cancer cell migration. However, the underlying molecular mechanism remains poorly understood and there is no reported evidence that directly links glycolysis to breast cancer cell migration. In this study, we investigated the role of FASN, ErbB2-mediated glycolysis in breast cancer cell migration. First, we compared lactate dehydrogenase A (LDHA) protein levels, glycolysis and cell migration between FASN, ErbB2-overexpressing SK-BR-3 cells and FASN, ErbB2-low-expressing MCF7 cells. Then, SK-BR-3 cells were treated with cerulenin (Cer), an inhibitor of FASN, and ErbB2, LDHA protein levels, glycolysis, and cell migration were detected. Next, we transiently transfected ErbB2 plasmid into MCF7 cells and detected FASN, LDHA protein levels, glycolysis and cell migration. Heregulin-ß1 (HRG-ß1) is an activator of ErbB2 and 2-deoxyglucose (2-DG) and oxamate (OX) are inhibitors of glycolysis. MCF7 cells were treated with HRG-ß1 alone, HRG-ß1 plus 2-DG, OX or cerulenin and glycolysis, and cell migration were measured. We found that FASN, ErbB2-high-expressing SK-BR-3 cells displayed higher levels of glycolysis and migration than FASN, ErbB2-low-expressing MCF7 cells. Inhibition of FASN by cerulenin impaired glycolysis and migration in SK-BR-3 cells. Transient overexpression of ErbB2 in MCF7 cells promotes glycolysis and migration. Moreover, 2-deoxyglucose (2-DG), oxamate (OX), or cerulenin partially reverses heregulin-ß1 (HRG-ß1)-induced glycolysis and migration in MCF7 cells. In conclusion, this study demonstrates that FASN, ErbB2-mediated glycolysis is required for breast cancer cell migration. These novel findings indicate that targeting FASN, ErbB2-mediated glycolysis may be a new approach to reverse breast cancer cell migration.

[Heregulin-ß1-induced Glycolysis Promotes Migration of Breast Cancer Cell Line MCF7].

OBJECTIVES: To explore whether heregulin-ß1 (HRG-ß1) can induce glycolysis and the role of HRG-ß1-induced glycolysis in the migration of human breast cancer cell line MCF7. METHODS: MCF7 cells were treated with PBS (PBS group) or HRG-ß1 for 12, 24 and 48 h. Culture media were harvested for glucose uptake and lactate production assays, and cells were collected and lactate dehydrogenase A (LDHA) protein levels were detected by using Western blot. MCF7 cells were treated with PBS (PBS group), HRG-ß1 or HRG-ß1 plus oxamate (OX) for 24 h. Culture media were harvested for glucose uptake and lactate production assays, and cells were harvested and the protein levels of LDHA was detected by Western blot. The wound healing assay was used to detect the migration of MCF7 cells treated with PBS (PBS group), HRG-ß1 or HRG-ß1 plus OX for 48 h. RESULTS: MCF7 cells treated with HRG-ß1 for 12, 24 and 48 h displayed higher levels of glucose uptake, lactate production and LDHA protein levels when the levels reached the peak at 24 h. The differences of glucose uptake, lactate production and LDHA protein levels between PBS group and HRG-ß1 group were statistically significant ( P<0.05). Compared to HRG-ß1 group, the glucose uptake of HRG-ß1 plus OX treated group was not significantly different ( P>0.05), but the statistically significant decrease of lactate production and LDHA protein levels were noticed ( P<0.01 and P<0.05). When MCF7 cells were scratched for 48 h, the wound healing rate of control group, HRG-ß1 group and HRG-ß1 plus OX group was (49±5.09)%, (100±2.21)% and (51±4.10)% respectively. The difference of each group was statistically significant ( P<0.001). CONCLUSIONS: HRG-ß1 induces glycolysis via upregualtion of LDHA and HRG-ß1-induced glycolysis promotes the migration of breast cancer cells line MCF7.

Multifaceted roles of HSF1 in cancer.

Heat shock transcription factor 1 (HSF1) is the master regulator of the heat shock response. Accumulating evidence shows that HSF1 is overexpressed in a variety of human cancers, is associated with cancer aggressiveness, and could serve as an independent diagnostic or prognostic biomarker. In this review, we will provide an overview of the multifaceted roles of HSF1 in cancer, with a special focus on the four underlying molecular mechanisms involved. First, HSF1 regulates the expression of heat shock proteins (HSPs) including HSP90, HSP70, and HSP27. Second, HSF1 regulates cellular metabolism, including glycolysis and lipid metabolism. Third, HSF1 serves as a regulator of different signaling pathways, such as HuR-HIF-1, Slug, protein kinase C (PKC), nuclear factor-kappaB (NF-κB), PI3K-AKT-mTOR, and mitogen-activated protein kinase (MAPK) pathways. Finally, HSF1 regulates microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). Overall, HSF1 plays many important roles in cancer via regulating cell proliferation, anti-apoptosis, epithelial-mesenchymal transition (EMT), migration, invasion, and metastasis and may be a potential therapeutic target for human cancers.