High-quality ChIP-seq analysis of MBD3 in human breast cancer cells

CRISPR-Cas9 Library Screening Identifies Novel Molecular Vulnerabilities in KMT2A-Rearranged Acute Lymphoblastic Leukemia

In acute lymphoblastic leukemia (ALL), chromosomal translocations involving the KMT2A gene represent highly unfavorable prognostic factors and most commonly occur in patients less than 1 year of age. Rearrangements of the KMT2A gene drive epigenetic changes that lead to aberrant gene expression profiles that strongly favor leukemia development. Apart from this genetic lesion, the mutational landscape of KMT2A-rearranged ALL is remarkably silent, providing limited insights for the development of targeted therapy. Consequently, identifying potential therapeutic targets often relies on differential gene expression, yet the inhibition of these genes has rarely translated into successful therapeutic strategies. Therefore, we performed CRISPR-Cas9 knock-out screens to search for genetic dependencies in KMT2A-rearranged ALL. We utilized small-guide RNA libraries directed against the entire human epigenome and kinome in various KMT2A-rearranged ALL, as well as wild-type KMT2A ALL cell line models. This screening approach led to the discovery of the epigenetic regulators ARID4B and MBD3, as well as the receptor kinase BMPR2 as novel molecular vulnerabilities and attractive therapeutic targets in KMT2A-rearranged ALL.

DriverGroup: a novel method for identifying driver gene groups

MOTIVATION

Identifying cancer driver genes is a key task in cancer informatics. Most existing methods are focused on individual cancer drivers which regulate biological processes leading to cancer. However, the effect of a single gene may not be sufficient to drive cancer progression. Here, we hypothesize that there are driver gene groups that work in concert to regulate cancer, and we develop a novel computational method to detect those driver gene groups.

RESULTS

We develop a novel method named DriverGroup to detect driver gene groups by using gene expression and gene interaction data. The proposed method has three stages: (i) constructing the gene network, (ii) discovering critical nodes of the constructed network and (iii) identifying driver gene groups based on the discovered critical nodes. Before evaluating the performance of DriverGroup in detecting cancer driver groups, we firstly assess its performance in detecting the influence of gene groups, a key step of DriverGroup. The application of DriverGroup to DREAM4 data demonstrates that it is more effective than other methods in detecting the regulation of gene groups. We then apply DriverGroup to the BRCA dataset to identify driver groups for breast cancer. The identified driver groups are promising as several group members are confirmed to be related to cancer in literature. We further use the predicted driver groups in survival analysis and the results show that the survival curves of patient subpopulations classified using the predicted driver groups are significantly differentiated, indicating the usefulness of DriverGroup.

AVAILABILITY AND IMPLEMENTATION

DriverGroup is available at https://github.com/pvvhoang/DriverGroup.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Role of TET1 and 5hmC in an Obesity-Linked Pathway Driving Cancer Stem Cells in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that lacks expression of estrogen receptor, progesterone receptor, and the HER2 but is enriched with cancer stem cell-like cells (CSC). CSCs are the fraction of cancer cells recognized as the source of primary malignant tumors that also give rise to metastatic recurrence. 5-Hydroxymethylcytosine (5hmC) is a DNA epigenetic feature derived from 5-methylcytosine by action of tet methylcytosine dioxygenase enzymes (e.g., TET1); and although TET1 and 5hmC are required to maintain embryonic stem cells, the mechanism and role in CSCs remain unknown. Data presented in this report support the conclusion that TET1 and TET1-dependent 5hmC mediate hydrogen peroxide (H2O2)-dependent activation of a novel gene expression cascade driving self-renewal and expansion of CSCs in TNBC. Evidence presented also supports that the H2O2 affecting this pathway arises due to endogenous mechanisms-including downregulation of antioxidant enzyme catalase in TNBC cells-and by exogenous routes, such as systemic inflammation and oxidative stress coupled with obesity, a known risk factor for TNBC incidence and recurrence. IMPLICATIONS: This study elucidates a pathway dependent on H2O2 and linked to obesity-driven TNBC tumor-initiating CSCs; thus, it provides new understanding that may advance TNBC prevention and treatment strategies.

Identification of novel dysregulated key genes in Breast cancer through high throughput ChIP-Seq data analysis

Breast cancer is the most common cancer in women both in the developed and less developed countries, and it imposes a considerable threat to human health. Therefore, in order to develop effective targeted therapies against Breast cancer, a deep understanding of its underlying molecular mechanisms is required. The application of deep transcriptional sequencing has been found to be reported to provide an efficient genomic assay to delve into the insights of the diseases and may prove to be useful in the study of Breast cancer. In this study, ChIP-Seq data for normal samples and Breast cancer were compared, and differential peaks identified, based upon fold enrichment (with P-values obtained via t-tests). The Protein-protein interaction (PPI) network analysis was carried out, following which the highly connected genes were screened and studied, and the most promising ones were selected. Biological pathway involved in the process were then identified. Our findings regarding potential Breast cancer-related genes enhances the understanding of the disease and provides prognostic information in addition to standard tumor prognostic factors for future research.