Can aggressive cancers be identified by the "aggressiveness" of their chromatin?

Image-Based Quantitative Single-Cell Method Showed Increase of Global Chromatin Accessibility in Tumor Compared to Normal Cells

The phenotypic plasticity of cancer cells has recently emerged as an important factor of treatment failure. The mechanisms of phenotypic plasticity are not fully understood. One of the hypotheses is that the degree of chromatin accessibility defines the easiness of cell transitions between different phenotypes. To test this, a method to compare overall chromatin accessibility between cells in a population or between cell populations is needed. We propose to measure chromatin accessibility by fluorescence signal from nuclei of cells stained with DNA binding fluorescent molecules. This method is based on the observations that small molecules bind nucleosome-free DNA more easily than nucleosomal DNA. Thus, nuclear fluorescence is proportional to the amount of nucleosome-free DNA, serving as a measure of chromatin accessibility. We optimized the method using several DNA intercalators and minor groove binders and known chromatin-modulating agents and demonstrated that chromatin accessibility is increased upon oncogene-induced transformation and further in tumor cells.

Chromatin as an old and new anticancer target

Recent genome-wide analyses identified chromatin modifiers as one of the most frequently mutated classes of genes across all cancers. However, chemotherapies developed for cancers involving DNA damage remain the standard of care for chromatin-deranged malignancies. In this review we address this conundrum by establishing the concept of 'chromatin damage': the non-genetic damage to protein-DNA interactions induced by certain small molecules. We highlight anthracyclines, a class of chemotherapeutic agents ubiquitously applied in oncology, as an example of overlooked chromatin-targeting agents. We discuss our current understanding of this phenomenon and explore emerging chromatin-damaging agents as a basis for further studies to maximize their impact in modern cancer treatment.

Pericentromeric satellite RNAs as flexible protein partners in the regulation of nuclear structure

Pericentromeric heterochromatin is mainly composed of satellite DNA sequences. Although being historically associated with transcriptional repression, some pericentromeric satellite DNA sequences are transcribed. The transcription events of pericentromeric satellite sequences occur in highly flexible biological contexts. Hence, the apparent randomness of pericentromeric satellite transcription incites the discussion about the attribution of biological functions. However, pericentromeric satellite RNAs have clear roles in the organization of nuclear structure. Silencing pericentromeric heterochromatin depends on pericentromeric satellite RNAs, that, in a feedback mechanism, contribute to the repression of pericentromeric heterochromatin. Moreover, pericentromeric satellite RNAs can also act as scaffolding molecules in condensate subnuclear structures (e.g., nuclear stress bodies). Since the formation/dissociation of nuclear condensates provides cell adaptability, pericentromeric satellite RNAs can be an epigenetic platform for regulating (sub)nuclear structure. We review current knowledge about pericentromeric satellite RNAs that, irrespective of the meaning of biological function, should be functionally addressed in regular and disease settings. This article is categorized under: RNA Methods > RNA Analyses in Cells RNA in Disease and Development > RNA in Disease.

DNA choreography: correlating mobility and organization of DNA across different resolutions from loops to chromosomes

The dynamics of DNA in the cell nucleus plays a role in cellular processes and fates but the interplay of DNA mobility with the hierarchical levels of DNA organization is still underexplored. Here, we made use of DNA replication to directly label genomic DNA in an unbiased genome-wide manner. This was followed by live-cell time-lapse microscopy of the labeled DNA combining imaging at different resolutions levels simultaneously and allowing one to trace DNA motion across organization levels within the same cells. Quantification of the labeled DNA segments at different microscopic resolution levels revealed sizes comparable to the ones reported for DNA loops using 3D super-resolution microscopy, topologically associated domains (TAD) using 3D widefield microscopy, and also entire chromosomes. By employing advanced chromatin tracking and image registration, we discovered that DNA exhibited higher mobility at the individual loop level compared to the TAD level and even less at the chromosome level. Additionally, our findings indicate that chromatin movement, regardless of the resolution, slowed down during the S phase of the cell cycle compared to the G1/G2 phases. Furthermore, we found that a fraction of DNA loops and TADs exhibited directed movement with the majority depicting constrained movement. Our data also indicated spatial mobility differences with DNA loops and TADs at the nuclear periphery and the nuclear interior exhibiting lower velocity and radius of gyration than the intermediate locations. On the basis of these insights, we propose that there is a link between DNA mobility and its organizational structure including spatial distribution, which impacts cellular processes.

Assessing RNA-Seq Workflow Methodologies Using Shannon Entropy

RNA-seq faces persistent challenges due to the ongoing, expanding array of data processing workflows, none of which have yet achieved standardization to date. It is imperative to determine which method most effectively preserves biological facts. Here, we used Shannon entropy as a tool for depicting the biological status of a system. Thus, we assessed the measurement of Shannon entropy by several RNA-seq workflow approaches, such as DESeq2 and edgeR, but also by combining nine normalization methods with log2 fold change on paired samples of TCGA RNA-seq representing datasets of 515 patients and spanning 12 different cancer types with 5-year overall survival rates ranging from 20% to 98%. Our analysis revealed that TPM, RLE, and TMM normalization, coupled with a threshold of log2 fold change ≥1, for identifying differentially expressed genes, yielded the best results. We propose that Shannon entropy can serve as an objective metric for refining the optimization of RNA-seq workflows and mRNA sequencing technologies.