Lung Cancer Heterogeneity and New Strategies for Drug Therapy

Roles of NIPBL in maintenance of genome stability

A cohesin-loading factor (NIPBL) is one of important regulatory factors in the maintenance of 3D genome organization and function, by interacting with a large number of factors, e.g. cohesion, CCCTC-binding factor (CTCF) or cohesin complex component. The present article overviews the critical and regulatory roles of NIBPL in cohesion loading on chromotin and in gene expression and transcriptional signaling. We explore molecular mechanisms by which NIPBL recruits endogenous histone deacetylase (HDAC) to induce histone deacetylation and influence multi-dimensions of genome, through which NIPBL "hop" movement in chromatin regulates gene expression and alters genome folding. NIPBL regulates the process of CTCF and cohesion into chromatin loops and topologically associated domains, binding of cohesion and H3K4mes3 through interaction among promoters and enhancers. HP1 recruits NIPBL to DNA damage site through RNF8/RNF168 ubiquitylation pathway. NIPBL contributes to regulation of genome-controlled gene expression through the influence of cohesin in chromosome structure. NIPBL interacts with cohesin and then increases transcriptional activities of REC8 promoter, leading to up-regulation of gene expression. NIPBL movement among chromosomal loops regulates gene expression through dynamic alterations of genome organization. Thus, we expect a new and deep insight to understand dynamics of chromosome and explore potential strategies of therapiesc on basis of NIPBL.

A comparison of next-generation sequencing analysis methods for cancer xenograft samples

The application of next-generation sequencing (NGS) technology in cancer is influenced by the quality and purity of tissue samples. This issue is especially critical for patient-derived xenograft (PDX) models, which have proven to be by far the best preclinical tool for investigating human tumor biology, because the sensitivity and specificity of NGS analysis in xenograft samples would be compromised by the contamination of mouse DNA and RNA. This definitely affects downstream analyses by causing inaccurate mutation calling and gene expression estimates. The reliability of NGS data analysis for cancer xenograft samples is therefore highly dependent on whether the sequencing reads derived from the xenograft could be distinguished from those originated from the host. That is, each sequence read needs to be accurately assigned to its original species. Here, we review currently available methodologies in this field, including Xenome, Disambiguate, bamcmp and pdxBlacklist, and provide guidelines for users.

Roles of Single Cell Systems Biomedicine in Lung Diseases

Single cell sequencing is important to detect the gene heterogeneity between cells, as the part of single-cell systems biology which combines computational science, mathematical modelling and high-throughput technologies with biological function and organization in the cell. We initially arise the question how to integrate the outcomes of single-cell systems biology with clinical phenotype, interpret alterations of single-cell gene sequencing and function in patient response to therapies, and understand the significance of single-cell systems biology in the discovery and development of new molecular diagnostics and therapeutics. The present review furthermore focuses the significance of singe cell systems biology in respiratory diseases and calls the special attention from scientists who are working on single cell systems biology to improve the diagnosis and therapy for patients with lung diseases.

Can the Single Cell Make Biomedicine Different?

The single-cell as the basic unit of biological organs and tissues has recently been considered an important window to furthermore understand molecular mechanisms of organ function and biology. The current issue with a special focus on single cell biomedicine is the first effort to collect the evidence of disease-associated single cell research, define the significance of single cell biomedicine in the pathogenesis of diseases, value the correlation of single cell gene sequencing with disease-specific biomarkers, and monitor the dynamics of RNA processes and responses to microenvironmental changes and drug resistances.