Retrospective analysis of Schlafen11 (SLFN11) to predict the outcomes to therapies affecting the DNA damage response.

BACKGROUND: The absence of the putative DNA/RNA helicase Schlafen11 (SLFN11) is thought to cause resistance to DNA-damaging agents (DDAs) and PARP inhibitors. METHODS: We developed and validated a clinically applicable SLFN11 immunohistochemistry assay and retrospectively correlated SLFN11 tumour levels to patient outcome to the standard of care therapies and olaparib maintenance. RESULTS: High SLFN11 associated with improved prognosis to the first-line treatment with DDAs platinum-plus-etoposide in SCLC patients, but was not strongly linked to paclitaxel-platinum response in ovarian cancer patients. Multivariate analysis of patients with relapsed platinum-sensitive ovarian cancer from the randomised, placebo-controlled Phase II olaparib maintenance Study19 showed SLFN11 tumour levels associated with sensitivity to olaparib. Study19 patients with high SLFN11 had a lower progression-free survival (PFS) hazard ratio compared to patients with low SLFN11, although both groups had the benefit of olaparib over placebo. Whilst caveated by small sample size, this trend was maintained for PFS, but not overall survival, when adjusting for BRCA status across the olaparib and placebo treatment groups, a key driver of PARP inhibitor sensitivity. CONCLUSION: We provide clinical evidence supporting the role of SLFN11 as a DDA therapy selection biomarker in SCLC and highlight the need for further clinical investigation into SLFN11 as a PARP inhibitor predictive biomarker.

A graphical model approach visualizes regulatory relationships between genome-wide transcription factor binding profiles.

Integrated analysis of multiple genome-wide transcription factor (TF)-binding profiles will be vital to advance our understanding of the global impact of TF binding. However, existing methods for measuring similarity in large numbers of chromatin immunoprecipitation assays with sequencing (ChIP-seq), such as correlation, mutual information or enrichment analysis, are limited in their ability to display functionally relevant TF relationships. In this study, we propose the use of graphical models to determine conditional independence between TFs and showed that network visualization provides a promising alternative to distinguish 'direct' versus 'indirect' TF interactions. We applied four algorithms to measure 'direct' dependence to a compendium of 367 mouse haematopoietic TF ChIP-seq samples and obtained a consensus network known as a 'TF association network' where edges in the network corresponded to likely causal pairwise relationships between TFs. The 'TF association network' illustrates the role of TFs in developmental pathways, is reminiscent of combinatorial TF regulation, corresponds to known protein-protein interactions and indicates substantial TF-binding reorganization in leukemic cell types. With the rapid increase in TF ChIP-Seq data sets, the approach presented here will be a powerful tool to study transcriptional programmes across a wide range of biological systems.

CODEX: a next-generation sequencing experiment database for the haematopoietic and embryonic stem cell communities.

CODEX (http://codex.stemcells.cam.ac.uk/) is a user-friendly database for the direct access and interrogation of publicly available next-generation sequencing (NGS) data, specifically aimed at experimental biologists. In an era of multi-centre genomic dataset generation, CODEX provides a single database where these samples are collected, uniformly processed and vetted. The main drive of CODEX is to provide the wider scientific community with instant access to high-quality NGS data, which, irrespective of the publishing laboratory, is directly comparable. CODEX allows users to immediately visualize or download processed datasets, or compare user-generated data against the database's cumulative knowledge-base. CODEX contains four types of NGS experiments: transcription factor chromatin immunoprecipitation coupled to high-throughput sequencing (ChIP-Seq), histone modification ChIP-Seq, DNase-Seq and RNA-Seq. These are largely encompassed within two specialized repositories, HAEMCODE and ESCODE, which are focused on haematopoiesis and embryonic stem cell samples, respectively. To date, CODEX contains over 1000 samples, including 221 unique TFs and 93 unique cell types. CODEX therefore provides one of the most complete resources of publicly available NGS data for the direct interrogation of transcriptional programmes that regulate cellular identity and fate in the context of mammalian development, homeostasis and disease.

Shared transcription factors contribute to distinct cell fates.

Genome-wide transcription factor (TF) binding profiles differ dramatically between cell types. However, not much is known about the relationship between cell-type-specific binding patterns and gene expression. A recent study demonstrated how the same TFs can have functional roles when binding to largely non-overlapping genomic regions in hematopoietic progenitor and mast cells. Cell-type specific binding profiles of shared TFs are therefore not merely the consequence of opportunistic and functionally irrelevant binding to accessible chromatin, but instead have the potential to make meaningful contributions to cell-type specific transcriptional programs.

Constrained transcription factor spacing is prevalent and important for transcriptional control of mouse blood cells.

Combinatorial transcription factor (TF) binding is essential for cell-type-specific gene regulation. However, much remains to be learned about the mechanisms of TF interactions, including to what extent constrained spacing and orientation of interacting TFs are critical for regulatory element activity. To examine the relative prevalence of the 'enhanceosome' versus the 'TF collective' model of combinatorial TF binding, a comprehensive analysis of TF binding site sequences in large scale datasets is necessary. We developed a motif-pair discovery pipeline to identify motif co-occurrences with preferential distance(s) between motifs in TF-bound regions. Utilizing a compendium of 289 mouse haematopoietic TF ChIP-seq datasets, we demonstrate that haematopoietic-related motif-pairs commonly occur with highly conserved constrained spacing and orientation between motifs. Furthermore, motif clustering revealed specific associations for both heterotypic and homotypic motif-pairs with particular haematopoietic cell types. We also showed that disrupting the spacing between motif-pairs significantly affects transcriptional activity in a well-known motif-pair-E-box and GATA, and in two previously unknown motif-pairs with constrained spacing-Ets and Homeobox as well as Ets and E-box. In this study, we provide evidence for widespread sequence-specific TF pair interaction with DNA that conforms to the 'enhanceosome' model, and furthermore identify associations between specific haematopoietic cell-types and motif-pairs.

Parkin pathway activation mitigates glioma cell proliferation and predicts patient survival.

Mutations in the parkin gene, which encodes a ubiquitin ligase, are a major genetic cause of parkinsonism. Interestingly, parkin also plays a role in cancer as a putative tumor suppressor, and the gene is frequently targeted by deletion and inactivation in human malignant tumors. Here, we investigated a potential tumor suppressor role for parkin in gliomas. We found that parkin expression was dramatically reduced in glioma cells. Restoration of parkin expression promoted G(1) phase cell-cycle arrest and mitigated the proliferation rate of glioma cells in vitro and in vivo. Notably, parkin-expressing glioma cells showed a reduction in levels of cyclin D1, but not cyclin E, and a selective downregulation of Akt serine-473 phosphorylation and VEGF receptor levels. In accordance, cells derived from a parkin-null mouse model exhibited increased levels of cyclin D1, VEGF receptor, and Akt phosphorylation, and divided significantly faster when compared with wild-type cells, with suppression of these changes following parkin reintroduction. Clinically, analysis of parkin pathway activation was predictive for the survival outcome of patients with glioma. Taken together, our study provides mechanistic insight into the tumor suppressor function of parkin in brain tumors and suggests that measurement of parkin pathway activation may be used clinically as a prognostic tool in patients with brain tumor.