Aneuploid IMR90 cells induced by depletion of pRB, DNMT1 and MAD2 show a common gene expression signature

Patterns of Aneuploidy and Signaling Consequences in Cancer

Aneuploidy, or a change in the number of whole chromosomes or chromosome arms, is a near-universal feature of cancer. Chromosomes affected by aneuploidy are not random, with observed cancer-specific and tissue-specific patterns. Recent advances in genome engineering methods have allowed the creation of models with targeted aneuploidy events. These models can be used to uncover the downstream effects of individual aneuploidies on cancer phenotypes including proliferation, apoptosis, metabolism, and immune signaling. Here, we review the current state of research into the patterns of aneuploidy in cancer and their impact on signaling pathways and biological processes.

Chromatin epigenetics and nuclear lamina keep the nucleus in shape: Examples from natural and accelerated aging

As the repository of genetic information, the cell nucleus must protect DNA integrity from mechanical stresses. The nuclear lamina, which resides within the nuclear envelope (NE), is made up of lamins, intermediate filaments bound to DNA. The nuclear lamina provides the nucleus with the ability to deal with inward as well as outward mechanical stimuli. Chromatin, in turn, through its degrees of compaction, shares this role with the nuclear lamina, thus, ensuring the plasticity of the nucleus. Perturbation of chromatin condensation or the nuclear lamina has been linked to a plethora of biological conditions, that range from cancer and genetic diseases (laminopathies) to aging, both natural and accelerated, such as the case of Hutchinson-Gilford Progeria Syndrome (HGPS). From the experimental results accumulated so far on the topic, a direct link between variations of the epigenetic pattern and nuclear lamina structure would be suggested, however, it has never been clarified thoroughly. This relationship, instead, has a downstream important implication on nucleus shape, genome preservation, force sensing, and, ultimately, aging-related disease onset. With this review, we aim to collect recent studies on the importance of both nuclear lamina components and chromatin status in nuclear mechanics. We also aim to bring to light evidence of the link between DNA methylation and nuclear lamina in natural and accelerated aging.

Transcriptomic Changes Following Partial Depletion of CENP-E in Normal Human Fibroblasts

The centromere is a fundamental chromosome structure in which the macro-molecular kinetochore assembles and is bound by spindle microtubules, allowing the segregation of sister chromatids during mitosis. Any alterations in kinetochore assembly or functioning or kinetochore-microtubule attachments jeopardize chromosome stability, leading to aneuploidy, a common feature of cancer cells. The spindle assembly checkpoint (SAC) supervises this process, ensuring a faithful segregation of chromosomes. CENP-E is both a protein of the kinetochore and a crucial component of the SAC required for kinetochore-microtubule capture and stable attachment, as well as congression of chromosomes to the metaphase plate. As the function of CENP-E is restricted to mitosis, its haploinsufficiency has been used to study the induced cell aneuploidy; however, the gene expression profile triggered by CENP-E reduction in normal cells has never been explored. To fill this gap, here we investigated whether a gene network exists that is associated with an siRNA-induced 50% reduction in CENP-E and consequent aneuploidy. Gene expression microarray analyses were performed at early and late timepoints after transfection. Initially, cell cycle regulation and stress response pathways were downregulated, while afterwards pathways involved in epithelial-mesenchymal transition, hypoxia and xenobiotic metabolism were altered. Collectively, our results suggest that CENP-E reduction triggers a gene expression program that recapitulates some features of tumor cells.

Losing DNA methylation at repetitive elements and breaking bad

Background

DNA methylation is an epigenetic chromatin mark that allows heterochromatin formation and gene silencing. It has a fundamental role in preserving genome stability (including chromosome stability) by controlling both gene expression and chromatin structure. Therefore, the onset of an incorrect pattern of DNA methylation is potentially dangerous for the cells. This is particularly important with respect to repetitive elements, which constitute the third of the human genome.

Main body

Repetitive sequences are involved in several cell processes, however, due to their intrinsic nature, they can be a source of genome instability. Thus, most repetitive elements are usually methylated to maintain a heterochromatic, repressed state. Notably, there is increasing evidence showing that repetitive elements (satellites, long interspersed nuclear elements (LINEs), Alus) are frequently hypomethylated in various of human pathologies, from cancer to psychiatric disorders. Repetitive sequences’ hypomethylation correlates with chromatin relaxation and unscheduled transcription. If these alterations are directly involved in human diseases aetiology and how, is still under investigation.

Conclusions

Hypomethylation of different families of repetitive sequences is recurrent in many different human diseases, suggesting that the methylation status of these elements can be involved in preservation of human health. This provides a promising point of view towards the research of therapeutic strategies focused on specifically tuning DNA methylation of DNA repeats.

EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer

BACKGROUND

Today, there are a lot of markers on the prognosis and diagnosis of complex diseases such as primary breast cancer. However, our understanding of the drivers that influence cancer aggression is limited.

METHODS

In this work, we study somatic mutation data consists of 450 metastatic breast tumor samples from cBio Cancer Genomics Portal. We use four software tools to extract features from this data. Then, an ensemble classifier (EC) learning algorithm called EARN (Ensemble of Artificial Neural Network, Random Forest, and non-linear Support Vector Machine) is proposed to evaluate plausible driver genes for metastatic breast cancer (MBCA). The decision-making strategy for the proposed ensemble machine is based on the aggregation of the predicted scores obtained from individual learning classifiers to be prioritized homo sapiens genes annotated as protein-coding from NCBI.

RESULTS

This study is an attempt to focus on the findings in several aspects of MBCA prognosis and diagnosis. First, drivers and passengers predicted by SVM, ANN, RF, and EARN are introduced. Second, biological inferences of predictions are discussed based on gene set enrichment analysis. Third, statistical validation and comparison of all learning methods are performed by some evaluation metrics. Finally, the pathway enrichment analysis (PEA) using ReactomeFIVIz tool (FDR < 0.03) for the top 100 genes predicted by EARN leads us to propose a new gene set panel for MBCA. It includes HDAC3, ABAT, GRIN1, PLCB1, and KPNA2 as well as NCOR1, TBL1XR1, SIRT4, KRAS, CACNA1E, PRKCG, GPS2, SIN3A, ACTB, KDM6B, and PRMT1. Furthermore, we compare results for MBCA to other outputs regarding 983 primary tumor samples of breast invasive carcinoma (BRCA) obtained from the Cancer Genome Atlas (TCGA). The comparison between outputs shows that ROC-AUC reaches 99.24% using EARN for MBCA and 99.79% for BRCA. This statistical result is better than three individual classifiers in each case.

CONCLUSIONS

This research using an integrative approach assists precision oncologists to design compact targeted panels that eliminate the need for whole-genome/exome sequencing. The schematic representation of the proposed model is presented as the Graphic abstract.