Protocols for C-Brick DNA Standard Assembly Using Cpf1

CRISPR-associated protein Cpf1 cleaves double-stranded DNA under the guidance of CRISPR RNA (crRNA), generating sticky ends. Because of this characteristic, Cpf1 has been used for the establishment of a DNA assembly standard called C-Brick, which has the advantage of long recognition sites and short scars. On a standard C-Brick vector, there are four Cpf1 recognition sites - the prefix (T1 and T2 sites) and the suffix (T3 and T4 sites) - flanking biological DNA parts. The cleavage of T2 and T3 sites produces complementary sticky ends, which allow for the assembly of DNA parts with T2 and T3 sites. Meanwhile, a short "GGATCC" scar is generated between parts after assembly. As the newly formed plasmid once again contains the four Cpf1 cleavage sites, the method allows for the iterative assembly of DNA parts, which is similar to those of BioBrick and BglBrick standards. A procedure outlining the use of the C-Brick standard to assemble DNA parts is described here. The C-Brick standard can be widely used by scientists, graduate and undergraduate students, and even amateurs.

Tutorial: integrative computational analysis of bulk RNA-sequencing data to characterize tumor immunity using RIMA

RNA-sequencing (RNA-seq) has become an increasingly cost-effective technique for molecular profiling and immune characterization of tumors. In the past decade, many computational tools have been developed to characterize tumor immunity from gene expression data. However, the analysis of large-scale RNA-seq data requires bioinformatics proficiency, large computational resources and cancer genomics and immunology knowledge. In this tutorial, we provide an overview of computational analysis of bulk RNA-seq data for immune characterization of tumors and introduce commonly used computational tools with relevance to cancer immunology and immunotherapy. These tools have diverse functions such as evaluation of expression signatures, estimation of immune infiltration, inference of the immune repertoire, prediction of immunotherapy response, neoantigen detection and microbiome quantification. We describe the RNA-seq IMmune Analysis (RIMA) pipeline integrating many of these tools to streamline RNA-seq analysis. We also developed a comprehensive and user-friendly guide in the form of a GitBook with text and video demos to assist users in analyzing bulk RNA-seq data for immune characterization at both individual sample and cohort levels by using RIMA.

Transcriptomic and Functional Pathway Analysis of Human Cervical Carcinoma Cancer Cells Response to Microtubule Inhibitor

BACKGROUND

There clearly is a need for effective chemotherapy for early-stage, high-risk patients with human cervical carcinoma. Vinblastine (VBL) is a key microtubule inhibitor, but unproven in its mechanisms as an important antitumor agent in cervical carcinoma.

METHODS

We selected the concentration of vinblastine inducing 30% cell death for analyses assessing the DNA content, gene expression and transcriptional gene regulation of VBL-treated KB-3 cells.

RESULTS

Transcriptomic and hierarchical clustering analysis demonstrated that treatment of KB-3 cells with VBL altered the expression of a diverse group of genes with G2/M arrest, which regulated by four oncogenic or tumor suppresser transcription factors (AP1, NFKB1, RELA, and TP53). Functional pathway analysis revealed the disease response to the biological effects of vinblastine in cervical carcinoma chemotherapy including protein ubiquitination pathway, RhoGDI signaling, integrin signaling, agranulocyte adhesion and biapedesis, and actin nucleation pathways. Northern blots also confirmed that KRT-7, FN14, IER3, and ID1 were deregulated in VBL-treated KB-3 cells.

CONCLUSION

Transcriptional time series profiles and a functional pathway analysis of VBL-treated KB-3 cells will provide a new strategy for improving microtubule inhibitor chemotherapy for cervical carcinoma.

Genetic and molecular biological characterization of two homologous cheR genes from Leptospira interrogans

The Leptospira interrogans genome encodes two copies of cheR genes and each of them is able to complement for the swarming defective phenotype of Escherichia coli cheR null mutant RP1254 to certain extent, while over-expression of either of them inhibits the swarming of the chemotactic wild-type E. coli strain, RP437. Therefore, both CheR1 and CheR2 ought to bear the methyltransferase activities, although CheR1 has only one instead of two conserved basic amino acid residues located on the positively charged face of α2-helix. When this residue as well as the Lys48 and Arg55 of CheR2 was mutated, none of the CheRs was able to maintain aforementioned complementation functions, suggesting their critical roles in recognition of methyl-accepting chemotaxis proteins similar to that of E. coli. Demonstrated by microarray assay, the expression of cheR1 in L. interrogans cultured at 28°C in Ellinghausen-McCullough-Johnson-Harris medium was significantly lower than the average transcription level of all other genes, while the transcription of cheR2 was significantly higher than that of cheR1 in accordance with real-time reverse transcriptase-polymerase chain reaction assay. Tandem MS-MS data mining for the proteome of the same culture detected 16 peptides derived from CheR2 but none from CheR1. Therefore, although both genes were shown to be functional in E. coli, the structurally more conserved CheR2 rather than CheR1 might be the major functional component of L. interrogans chemotaxis adaptation system under our laboratory culture conditions.

Circular RNAs as novel potential biomarkers for pancreatic cancer

Pancreatic cancer (PaCa) is the fourth leading cause of cancer-related deaths in the United States, and the vast majority of these malignancies are pancreatic ductal adenocarcinomas (PDAC), but there is still a lack of early detection biomarkers for PaCa. Unlike linear RNAs, circRNAs form covalently closed continuous loops and can act as mammalian gene regulators. They may be diagnostic or predictive biomarkers for some tumors, also be novel potential therapeutic targets in different diseases. This review focuses on (1) the biogenesis of circRNAs, RNA binding proteins (RBPs) and complementary sequences of circRNAs; (2) the characteristics of circRNAs which allow them to interact with miRNAs; (3) the roles of circRNAs playing in the regulation of gene expression, cell behavior and cancer, and their potential role as novel biomarkers and therapeutic targets in pancreatic cancer.

Alpha-ketoglutarate protects Streptomyces coelicolor from visible light-induced phototoxicity

It has been known that some Streptomyces species, including the model strain Streptomyces coelicolor, are vulnerable to visible light. Much evidence demonstrated that the phototoxicity induced by visible light is a consequence of the formation of intracellular reactive oxygen species (ROS), which are potentially harmful to cells. In this study, we found that α-ketoglutarate (α-KG) has a protective role against the phototoxicity in S. coelicolor. It could be because that α-KG can detoxify the ROS with the concomitant formation of succinate, which mediates the cells getting into anaerobiosis to produce more NADH and maintain intracellular redox homeostasis, a situation that was demonstrated by overexpressing gdhA in S. coelicolor. This finding, therefore, connects the central metabolites with the bacterial resistance against phototoxicity effect induced by visible light.

Elevated cyclin A associated kinase activity promotes sensitivity of metastatic human cancer cells to DNA antimetabolite drug

Drug resistance is a major obstacle in successful systemic therapy of metastatic cancer. We analyzed the involvement of cell cycle regulatory proteins in eliciting response to N (phosphonoacetyl)-L-aspartate (PALA), an inhibitor of de novo pyrimidine synthesis, in two metastatic variants of human cancer cell line MDA-MB-435 isolated from lung (L-2) and brain (Br-1) in nude mouse, respectively. L-2 and Br-l cells markedly differed in their sensitivity to PALA. While both cell types displayed an initial S phase delay/arrest, Br-l cells proliferated but most L-2 cells underwent apoptosis. There was distinct elevation in cyclin A, and phosphorylated Rb proteins concomitant with decreased expression of bcl-2 protein in the PALA treated L-2 cells undergoing apoptosis. Markedly elevated cyclin A associated and cdk2 kinase activities together with increased E2F1-DNA binding were detected in these L-2 cells. Induced ectopic cyclin A expression sensitized Br-l cells to PALA by activating an apoptotic pathway. Our findings demonstrate that elevated expression of cyclin A and associated kinase can activate an apoptotic pathway in cells exposed to DNA antimetabolites. Abrogation of this pathway can lead to resistance against these drugs in metastatic variants of human carcinoma cells.

Research progress on GlnR-mediated regulation in Actinomycetes

This review constitutes a summary of current knowledge on GlnR, a global regulator, that assumes a critical function in the regulation of nitrogen metabolism of Actinomycetes. In cross-regulation with other regulators, GlnR was also shown to play a role in the regulation of carbon and phosphate metabolisms as well as of secondary metabolism. A description of the structure of the GlnR protein and of its binding sites in various genes promoters regions is also provided. This review thus provides a global understanding of the critical function played by GlnR in the regulation of primary and secondary metabolism in Actinomycetes.

Single-cell assignment using multiple-adversarial domain adaptation network with large-scale references

The rapid accumulation of single-cell RNA-seq data has provided rich resources to characterize various human cell populations. However, achieving accurate cell-type annotation using public references presents challenges due to inconsistent annotations, batch effects, and rare cell types. Here, we introduce SELINA (single-cell identity navigator), an integrative and automatic cell-type annotation framework based on a pre-curated reference atlas spanning various tissues. SELINA employs a multiple-adversarial domain adaptation network to remove batch effects within the reference dataset. Additionally, it enhances the annotation of less frequent cell types by synthetic minority oversampling and fits query data with the reference data using an autoencoder. SELINA culminates in the creation of a comprehensive and uniform reference atlas, encompassing 1.7 million cells covering 230 distinct human cell types. We substantiate its robustness and superiority across a multitude of human tissues. Notably, SELINA could accurately annotate cells within diverse disease contexts. SELINA provides a complete solution for human single-cell RNA-seq data annotation with both python and R packages.

Cross-Site Concordance Evaluation of Tumor DNA and RNA Sequencing Platforms for the CIMAC-CIDC Network

PURPOSE

Whole-exome (WES) and RNA sequencing (RNA-seq) are key components of cancer immunogenomic analyses. To evaluate the consistency of tumor WES and RNA-seq profiling platforms across different centers, the Cancer Immune Monitoring and Analysis Centers (CIMAC) and the Cancer Immunologic Data Commons (CIDC) conducted a systematic harmonization study.

EXPERIMENTAL DESIGN

DNA and RNA were centrally extracted from fresh frozen and formalin-fixed paraffin-embedded non-small cell lung carcinoma tumors and distributed to three centers for WES and RNA-seq profiling. In addition, two 10-plex HapMap cell line pools with known mutations were used to evaluate the accuracy of the WES platforms.

RESULTS

The WES platforms achieved high precision (> 0.98) and recall (> 0.87) on the HapMap pools when evaluated on loci using > 50× common coverage. Nonsynonymous mutations clustered by tumor sample, achieving an index of specific agreement above 0.67 among replicates, centers, and sample processing. A DV200 > 24% for RNA, as a putative presequencing RNA quality control (QC) metric, was found to be a reliable threshold for generating consistent expression readouts in RNA-seq and NanoString data. MedTIN > 30 was likewise assessed as a reliable RNA-seq QC metric, above which samples from the same tumor across replicates, centers, and sample processing runs could be robustly clustered and HLA typing, immune infiltration, and immune repertoire inference could be performed.

CONCLUSIONS

The CIMAC collaborating laboratory platforms effectively generated consistent WES and RNA-seq data and enable robust cross-trial comparisons and meta-analyses of highly complex immuno-oncology biomarker data across the NCI CIMAC-CIDC Network.

CRISPR-based non-nucleic acid detection

Characterization of clustered regularly interspaced short palindromic repeat (CRISPR)-associated (Cas) trans-cleavage activities has initiated the era of next-generation CRISPR diagnostics. By using the trans-cleavage reaction for signal output, CRISPR systems have been engineered to detect non-nucleic acids (NNAs), including ions, inorganic small molecules, organic compounds, proteins, and bacteria. Diverse strategies are being used to specifically recognize NNAs and regulate Cas trans-cleavage activities, via generation or depletion of output signals. In this review, we introduce the principles and advantages of CRISPR-based NNA detection. We then classify CRISPR-based NNA detection strategies into three classes: the generation or depletion of free activators, synthesis of crRNAs, and reconstruction of active Cas effectors. Finally, we discuss the challenges and potential strategies to advance both clinical and nonclinical applications of CRISPR-based NNA detection.

Plasma-derived exosomal long noncoding RNAs of pancreatic cancer patients as novel blood-based biomarkers of disease

BACKGROUND

Pancreatic cancer (PaCa) is one of the most intractable and fatal malignancies and is associated with the dysregulation of long noncoding RNAs (lncRNAs), which are a large class of noncoding RNAs larger than 200 nt that act as competing endogenous RNAs or sponges for miRNAs to induce tumour biological behaviours. However, their clinical value in treating pancreatic cancer has been poorly explained, but they are essential for improving the prognosis of PaCa patients.

METHODS

We analysed the plasma-derived exosomal lncRNA profiles of PaCa patients by using whole-transcriptome sequencing analysis and identified significantly differentially expressed lncRNAs, including LINC01268, LINC02802, AC124854.1, and AL132657.1. In the current study, the expression levels of four plasma-derived exosomal lncRNAs in PaCa plasma were validated via quantitative real-time polymerase chain reaction (qRT‒PCR). The relationship between the expression of the four lncRNAs and the clinicopathological features of patients with PaCa was also evaluated.

RESULTS

We demonstrated that exosomal LINC01268, LINC02802, AC124854.1 and AL132657.1 were highly expressed in PaCa plasma compared with those in normal controls; moreover, they were positively correlated with the serum expression of carbohydrate antigen 19-9 (CA19-9). The receiver operating characteristic curves (AUCs) of the four lncRNAs were 0.8421, 0.6544, 0.7190, and 0.6321, and the AUC value of the combination of the four exosomal lncRNAs increased to 0.8476, with a sensitivity of 0.72 and specificity of 0.89. These results suggested that the plasma-derived exosomal genes LINC01268, LINC02802, AC124854.1, and AL132657.1 may be novel diagnostic markers for PaCa.

CONCLUSIONS

Our research demonstrated that the plasma-derived exosomal lncRNAs of PaCa patients are novel blood-based biomarkers of disease.

NCKAP1 Inhibits the Progression of Renal Carcinoma via Modulating Immune Responses and the PI3K/AKT/mTOR Signaling Pathway

Nck-associated protein 1 (NCKAP1) is critical for cytoskeletal functions and various cellular activities, and deregulation of NCKAP1 in many cancers significantly influences the outcomes of malignant diseases. However, the functions of NCKAP1 in the progression of renal cancer are yet unknown. To investigate the specific roles of NCKAP1 in the immune regulation and tumor progression of renal cancer, the expression of NCKAP1 and genetic variations were analyzed across cancer types at different pathological stages via UALCAN and cBioPortal. Immune cell infiltration in renal cancer was also assessed by ssGSEA and single-cell gene expression data from the GEO. RNA sequencing of NCKAP1-overexpressing 769P cells further examined the impact of NCKAP1 on kidney cancer. Our pancancer analyses revealed a complex NCKAP1 expression profile across various cancer types, with reduced levels in renal cancer patients linked to patient prognosis. CIBERSORT and single-cell RNA sequencing revealed the expression patterns of NCKAP1 in different cell lineages in renal cancer and a significant correlation between NCKAP1 and immune cell infiltration in the kidney tumor microenvironment. We further verified that NCKAP1 suppressed cancer cell growth and affected tumor development in renal cancer via the PI3K/AKT/mTOR signaling pathway. Our results indicate that NCKAP1 is a potential predictive marker and treatment target for renal cancer.

The global nitrogen regulator GlnR is a direct transcriptional repressor of the key gluconeogenic gene pckA in actinomycetes

In most actinomycetes, GlnR governs both nitrogen and non-nitrogen metabolisms (e.g., carbon, phosphate, and secondary metabolisms). Although GlnR has been recognized as a global regulator, its regulatory role in central carbon metabolism [e.g., glycolysis, gluconeogenesis, and the tricarboxylic acid (TCA) cycle] is largely unknown. In this study, we characterized GlnR as a direct transcriptional repressor of the pckA gene that encodes phosphoenolpyruvate carboxykinase, catalyzing the conversion of the TCA cycle intermediate oxaloacetate to phosphoenolpyruvate, a key step in gluconeogenesis. Through the transcriptomic and quantitative real-time PCR analyses, we first showed that the pckA transcription was upregulated in the glnR null mutant of Amycolatopsis mediterranei. Next, we proved that the pckA gene was essential for A. mediterranei gluconeogenesis when the TCA cycle intermediate was used as a sole carbon source. Furthermore, with the employment of the electrophoretic mobility shift assay and DNase I footprinting assay, we revealed that GlnR was able to specifically bind to the pckA promoter region from both A. mediterranei and two other representative actinomycetes (Streptomyces coelicolor and Mycobacterium smegmatis). Therefore, our data suggest that GlnR may repress pckA transcription in actinomycetes, which highlights the global regulatory role of GlnR in both nitrogen and central carbon metabolisms in response to environmental nutrient stresses.

IMPORTANCE

The GlnR regulator of actinomycetes controls nitrogen metabolism genes and many other genes involved in carbon, phosphate, and secondary metabolisms. Currently, the known GlnR-regulated genes in carbon metabolism are involved in the transport of carbon sources, the assimilation of short-chain fatty acid, and the 2-methylcitrate cycle, although little is known about the relationship between GlnR and the TCA cycle and gluconeogenesis. Here, based on the biochemical and genetic results, we identified GlnR as a direct transcriptional repressor of pckA, the gene that encodes phosphoenolpyruvate carboxykinase, a key enzyme for gluconeogenesis, thus highlighting that GlnR plays a central and complex role for dynamic orchestration of cellular carbon, nitrogen, and phosphate fluxes and bioactive secondary metabolites in actinomycetes to adapt to changing surroundings.

5-mRNA-based prognostic signature of survival in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the most common non-small-cell lung cancer, with a high incidence and a poor prognosis.

AIM

To construct effective predictive models to evaluate the prognosis of LUAD patients.

METHODS

In this study, we thoroughly mined LUAD genomic data from the Gene Expression Omnibus (GEO) (GSE43458, GSE32863, and GSE27262) and the Cancer Genome Atlas (TCGA) datasets, including 698 LUAD and 172 healthy (or adjacent normal) lung tissue samples. Univariate regression and LASSO regression analyses were used to screen differentially expressed genes (DEGs) related to patient prognosis, and multivariate Cox regression analysis was applied to establish the risk score equation and construct the survival prognosis model. Receiver operating characteristic curve and Kaplan-Meier survival analyses with clinically independent prognostic parameters were performed to verify the predictive power of the model and further establish a prognostic nomogram.

RESULTS

A total of 380 DEGs were identified in LUAD tissues through GEO and TCGA datasets, and 5 DEGs (TCN1, CENPF, MAOB, CRTAC1 and PLEK2) were screened out by multivariate Cox regression analysis, indicating that the prognostic risk model could be used as an independent prognostic factor (Hazard ratio = 1.520, P < 0.001). Internal and external validation of the model confirmed that the prediction model had good sensitivity and specificity (Area under the curve = 0.754, 0.737). Combining genetic models and clinical prognostic factors, nomograms can also predict overall survival more effectively.

CONCLUSION

A 5-mRNA-based model was constructed to predict the prognosis of lung adenocarcinoma, which may provide clinicians with reliable prognostic assessment tools and help clinical treatment decisions.

Molecular Mechanisms and Clinical Implications of Noncoding RNAs in Cancer

Noncoding RNAs (ncRNAs), which include small nuclear RNAs (snRNAs), small nucleolar RNAs (snoRNAs), microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs), are RNA molecules that arise from genomic regions without protein-coding potential and display a variety of mechanisms and functions by regulating gene expression at the transcriptional, RNA processing, and translational levels and participating in virtually all cellular processes [...].

Angiotensin-Converting Enzyme 2 SNPs as Common Genetic Loci and Optimal Early Identification Genetic Markers for COVID-19

Background: Angiotensin-converting enzyme 2 (ACE2) is implicated as a host cell receptor that causes infection in the pathogenesis of coronavirus disease 2019 (COVID-19), and its genetic polymorphisms in the ACE2 gene may promote cardiovascular disease and systemic inflammatory injury in COVID-19 patients. Hence, the genetic background may potentially explain the broad interindividual variation in disease susceptibility and/or severity. Methods: Genetic susceptibility to COVID-19 was analyzed by examining single-nucleotide polymorphisms (SNPs) of ACE2 in 246 patients with COVID-19 and 210 normal controls using the TaqMan genotyping assay. Results: We demonstrated that the ACE2 SNPs rs4646142, rs6632677, and rs2074192 were associated with COVID-19 (for all, p  <  0.05), and the differences in the ACE2 SNPs rs4646142 and rs6632677 were correlated with COVID-19-related systemic inflammatory injury and cardiovascular risk. Specifically, rs4646142 was associated with high-sensitivity C-reactive protein (hs-CRP), prealbumin (PAB), apolipoprotein A (APOA), high-density lipoprotein (HDL), and acid glycoprotein (AGP) levels. Rs6632677 was also associated with elevated CRP, acid glycoprotein (AGP), and haptoglobin (HPT). Conclusions: Our results suggest that the ACE2 SNPs rs4646142 and rs6632677 may be common genetic loci and optimal early identification genetic markers for COVID-19 with cardiovascular risk.

Comprehensive RNA-seq reveals molecular changes in kidney malignancy among people living with HIV

To heighten the awareness of kidney malignancy in patients with HIV infection to facilitate the early diagnosis of kidney cancer, the differentially expressed mRNAs were analyzed in this malignant tumor using RNA sequencing. We identified 2,962 protein-coding transcripts in HIV-associated kidney cancer. KISS1R, CAIX, and NPTX2 mRNA expression levels were specifically increased in HIV-associated kidney cancer while UMOD and TMEM213 mRNA were decreased in most cases based on real-time PCR analyses. These findings were similar to those noted for the general population with renal cell carcinoma. Immunohistochemical staining analysis also showed that a total of 18 malignant kidney cases among the people living with HIV (PLWH) exhibited positive staining for KISS1R and CAIX. Pathway analysis of the differentially expressed mRNAs in HIV-associated kidney cancer revealed that several key pathways were involved, including vascular endothelial growth factor-activated receptor activity, IgG binding, and lipopolysaccharide receptor activity. Altogether, our findings reveal the identified molecular changes in kidney malignancy, which may offer a helpful explanation for cancer progression and open up new therapeutic avenues that may decrease mortality after a cancer diagnosis among PLWH.

[Enabling technologies in synthetic biology--DNA synthesis, assembly and editing]

Synthetic biology is an emerging discipline, which aims at creating artificial lives or remolding the present organisms to generate new features. To achieve these goals, synthetic biologists need to design and synthesize new genes, pathways, modules or even whole genomes. As these enabling technologies (e.g. gene synthesis, DNA assembly and genome editing) are very important for the progress of synthetic biology, we will focus on the development of these technologies in this review.

CRISPR-HOLMES-based NAD+ detection

Studies have indicated that the intracellular nicotinamide adenine dinucleotide (NAD+) level is associated with the occurrence and development of many diseases. However, traditional nicotinamide adenine dinucleotide (NAD+) detection techniques are time-consuming and may require large and expensive instruments. We recently found that the clustered regularly interspaced short palindromic repeat (CRISPR)-Cas12a protein can be inactivated by AcrVA5-mediated acetylation and reactivated by CobB, using NAD+ as the co-factor. Therefore, in this study, we created a CRISPR-Cas12a-based one-step HOLMES(NAD+) system for rapid and convenient NAD+ detection with the employment of both acetylated Cas12a and CobB. In HOLMES(NAD+), acetylated Cas12a loses its trans-cleavage activities and can be reactivated by CobB in the presence of NAD+, cutting ssDNA reporters to generate fluorescence signals. HOLMES(NAD+) shows both sensitivity and specificity in NAD+ detection and can be used for quantitative determination of intracellular NAD+ concentrations. Therefore, HOLMES(NAD+) not only provides a convenient and rapid approach for target NAD+ quantitation but also expands the application scenarios of HOLMES to non-nucleic acid detection.

meHOLMES: A CRISPR-cas12a-based method for rapid detection of DNA methylation in a sequence-independent manner

Aberrant DNA methylation is closely associated with various diseases, particularly cancer, and its precise detection plays an essential role in disease diagnosis and monitoring. In this study, we present a novel DNA methylation detection method (namely meHOLMES), which integrates both the TET2/APOBEC-mediated cytosine deamination step and the CRISPR-Cas12a-based signal readout step. TET2/APOBEC efficiently converts unmethylated cytosine to uracil, which is subsequently changed to thymine after PCR amplification. Utilizing a rationally designed crRNA, Cas12a specifically identifies unconverted methylated cytosines and generates detectable signals using either fluorescent reporters or lateral flow test strips. meHOLMES quantitatively detects methylated CpG sites with or without Protospacer Adjacent Motif (PAM) sequences in both artificial and real biological samples. In addition, meHOLMES can complete the whole detection process within 6 h, which is much faster than traditional bisulfite-based sample pre-treatment method. Above all, meHOLMES provides a simpler, faster, more accurate, and cost-effective approach for quantitation of DNA methylation levels in a sequence-independent manner.

N6-Methylandenosine-related lncRNAs as potential biomarkers for predicting prognosis and the immunotherapy response in pancreatic cancer

Emerging evidence has shown that the N6-methyladenosine (m6A) modification of RNA plays key roles in tumorigenesis and the progression of various cancers. However, the potential roles of the m6A modification of long noncoding RNAs (lncRNAs) in pancreatic cancer (PaCa) are still unknown. To analyze the prognostic value of m6A-related lncRNAs in PaCa, an m6A-related lncRNA signature was constructed as a risk model via Pearson's correlation and univariate Cox regression analyses in The Cancer Genome Atlas (TCGA) database. The tumor microenvironment (TME), tumor mutation burden, and drug sensitivity of PaCa were investigated by m6A-related lncRNA risk score analyses. We established an m6A-related risk prognostic model consisting of five lncRNAs, namely, LINC01091, AC096733.2, AC092171.5, AC015660.1, and AC005332.6, which not only revealed significant differences in immune cell infiltration associated with the TME between the high-risk and low-risk groups but also predicted the potential benefit of immunotherapy for patients with PaCa. Drugs such as WZ8040, selumetinib, and bortezomib were also identified as more effective for high-risk patients. Our results indicate that the m6A-related lncRNA risk model could be an independent prognostic indicator, which may provide valuable insights for identifying therapeutic approaches for PaCa.