OUP accepted manuscript

An Epigenomic fingerprint of human cancers by landscape interrogation of super enhancers at the constituent level

Super enhancers (SE), large genomic elements that activate transcription and drive cell identity, have been found with cancer-specific gene regulation in human cancers. Recent studies reported the importance of understanding the cooperation and function of SE internal components, i.e., the constituent enhancers (CE). However, there are no pan-cancer studies to identify cancer-specific SE signatures at the constituent level. Here, by revisiting pan-cancer SE activities with H3K27Ac ChIP-seq datasets, we report fingerprint SE signatures for 28 cancer types in the NCI-60 cell panel. We implement a mixture model to discriminate active CEs from inactive CEs by taking into consideration ChIP-seq variabilities between cancer samples and across CEs. We demonstrate that the model-based estimation of CE states provides improved functional interpretation of SE-associated regulation. We identify cancer-specific CEs by balancing their active prevalence with their capability of encoding cancer type identities. We further demonstrate that cancer-specific CEs have the strongest per-base enhancer activities in independent enhancer sequencing assays, suggesting their importance in understanding critical SE signatures. We summarize fingerprint SEs based on the cancer-specific statuses of their component CEs and build an easy-to-use R package to facilitate the query, exploration, and visualization of fingerprint SEs across cancers.

The novel CDK9 inhibitor, XPW1, alone and in combination with BRD4 inhibitor JQ1, for the treatment of clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is a highly lethal malignancy with few therapeutic options. Cyclin‑dependent kinase 9 (CDK9), a potential therapeutic target of many cancers, has been recently observed to be upregulated in ccRCC patients. Therefore, we aimed to investigate the therapeutic potential of CDK9 in ccRCC and develop a novel CDK9 inhibitor with low toxicity for ccRCC treatment.

METHODS

The expression of CDK9 in ccRCC was checked using the online database and tissue microarray analysis. shRNA-mediated CDK9 knockdown and CDK inhibitor were applied to evaluate the effect of CDK9 on ccRCC. Medicinal chemistry methods were used to develop a new CDK9 inhibitor with drugability. RNA-seq and ChIP-seq experiments were conducted to explore the mechanism of action. MTS, western blotting, and colony formation assays were performed to evaluate the anti-ccRCC effects of CDK9 knockdown and inhibition in vitro. The in vivo anti-tumour efficacy was evaluated in a xenograft model.

RESULTS

CDK9 is overexpressed and associated with poor survival in ccRCC. Knockdown or inhibition of CDK9 significantly suppressed ccRCC cells. XPW1 was identified as a new potent and selective CDK9 inhibitor with excellent anti-ccRCC activity and low toxicity. In mechanism, XPW1 transcriptionally inhibited DNA repair programmes in ccRCC cells, resulting in an excellent anti-tumour effect. CDK9 and BRD4 were two highly correlated transcriptional regulators in ccRCC patients, and the BRD4 inhibitor JQ1 enhanced XPW1's anti-ccRCC effects in vitro and in vivo.

CONCLUSIONS

This work provides valuable insights into the therapeutic potential of CDK9 in ccRCC. The CDK9 inhibitor XPW1 would be a novel therapeutic agent for targeting ccRCC, alone or in rational combinations.

Experimental Validation and Prediction of Super-Enhancers: Advances and Challenges

Super-enhancers (SEs) are cis-regulatory elements of the human genome that have been widely discussed since the discovery and origin of the term. Super-enhancers have been shown to be strongly associated with the expression of genes crucial for cell differentiation, cell stability maintenance, and tumorigenesis. Our goal was to systematize research studies dedicated to the investigation of structure and functions of super-enhancers as well as to define further perspectives of the field in various applications, such as drug development and clinical use. We overviewed the fundamental studies which provided experimental data on various pathologies and their associations with particular super-enhancers. The analysis of mainstream approaches for SE search and prediction allowed us to accumulate existing data and propose directions for further algorithmic improvements of SEs' reliability levels and efficiency. Thus, here we provide the description of the most robust algorithms such as ROSE, imPROSE, and DEEPSEN and suggest their further use for various research and development tasks. The most promising research direction, which is based on topic and number of published studies, are cancer-associated super-enhancers and prospective SE-targeted therapy strategies, most of which are discussed in this review.