Multi-omics analysis identifies RFX7 targets involved in tumor suppression and neuronal processes.

Recurrently mutated in lymphoid neoplasms, the transcription factor RFX7 is emerging as a tumor suppressor. Previous reports suggested that RFX7 may also have a role in neurological and metabolic disorders. We recently reported that RFX7 responds to p53 signaling and cellular stress. Furthermore, we found RFX7 target genes to be dysregulated in numerous cancer types also beyond the hematological system. However, our understanding of RFX7's target gene network and its role in health and disease remains limited. Here, we generated RFX7 knock-out cells and employed a multi-omics approach integrating transcriptome, cistrome, and proteome data to obtain a more comprehensive picture of RFX7 targets. We identify novel target genes linked to RFX7's tumor suppressor function and underscoring its potential role in neurological disorders. Importantly, our data reveal RFX7 as a mechanistic link that enables the activation of these genes in response to p53 signaling.

The landscape of human p53-regulated long non-coding RNAs reveals critical host gene co-regulation.

The role of long non-coding RNAs (lncRNAs) in p53-mediated tumor suppression has become increasingly appreciated in the past decade. Thus, the identification of p53-regulated lncRNAs can be a promising starting point to select and prioritize lncRNAs for functional analyses. By integrating transcriptome and transcription factor-binding data, we identified 379 lncRNAs that are recurrently differentially regulated by p53. Dissecting the mechanisms by which p53 regulates many of them, we identified sets of lncRNAs regulated either directly by p53 or indirectly through the p53-RFX7 and p53-p21-DREAM/RB:E2F pathways. Importantly, we identified multiple p53-responsive lncRNAs that are co-regulated with their protein-coding host genes, revealing an important mechanism by which p53 may regulate lncRNAs. Further analysis of transcriptome data and clinical data from cancer patients showed that recurrently p53-regulated lncRNAs are associated with patient survival. Together, the integrative analysis of the landscape of p53-regulated lncRNAs provides a powerful resource facilitating the identification of lncRNA function and displays the mechanisms of p53-dependent regulation that could be exploited for developing anticancer approaches.

TargetGeneReg 2.0: a comprehensive web-atlas for p53, p63, and cell cycle-dependent gene regulation.

In recent years, our web-atlas at www.TargetGeneReg.org has enabled many researchers to uncover new biological insights and to identify novel regulatory mechanisms that affect p53 and the cell cycle - signaling pathways that are frequently dysregulated in diseases like cancer. Here, we provide a substantial upgrade of the database that comprises an extension to include non-coding genes and the transcription factors ΔNp63 and RFX7. TargetGeneReg 2.0 combines gene expression profiling and transcription factor DNA binding data to determine, for each gene, the response to p53, ΔNp63, and cell cycle signaling. It can be used to dissect common, cell type and treatment-specific effects, identify the most promising candidates, and validate findings. We demonstrate the increased power and more intuitive layout of the resource using realistic examples.

p53-mediated AKT and mTOR inhibition requires RFX7 and DDIT4 and depends on nutrient abundance.

In recent years the tumor suppressor p53 has been increasingly recognized as a potent regulator of the cell metabolism and for its ability to inhibit the critical pro-survival kinases AKT and mTOR. The mechanisms through which p53 controls AKT and mTOR, however, are largely unclear. Here, we demonstrate that p53 activates the metabolic regulator DDIT4 indirectly through the regulatory factor X 7 (RFX7). We provide evidence that DDIT4 is required for p53 to inhibit mTOR complex 2 (mTORC2)-dependent AKT activation. Most strikingly, we also find that the DDIT4 regulator RFX7 is required for p53-mediated inhibition of mTORC1 and AKT. Our results suggest that AMPK activation plays no role and p53-mediated AKT inhibition is not critical for p53-mediated mTORC1 inhibition. Moreover, using recently developed physiological cell culture media we uncover that basal p53 and RFX7 activity can play a critical role in restricting mTORC1 activity under physiological nutrient conditions, and we propose a nutrient-dependent model for p53-RFX7-mediated mTORC1 inhibition. These results establish RFX7 and its downstream target DDIT4 as essential effectors in metabolic control elicited by p53.

Transcription factor RFX7 governs a tumor suppressor network in response to p53 and stress.

Despite its prominence, the mechanisms through which the tumor suppressor p53 regulates most genes remain unclear. Recently, the regulatory factor X 7 (RFX7) emerged as a suppressor of lymphoid neoplasms, but its regulation and target genes mediating tumor suppression remain unknown. Here, we identify a novel p53-RFX7 signaling axis. Integrative analysis of the RFX7 DNA binding landscape and the RFX7-regulated transcriptome in three distinct cell systems reveals that RFX7 directly controls multiple established tumor suppressors, including PDCD4, PIK3IP1, MXD4, and PNRC1, across cell types and is the missing link for their activation in response to p53 and stress. RFX7 target gene expression correlates with cell differentiation and better prognosis in numerous cancer types. Interestingly, we find that RFX7 sensitizes cells to Doxorubicin by promoting apoptosis. Together, our work establishes RFX7's role as a ubiquitous regulator of cell growth and fate determination and a key node in the p53 transcriptional program.

Dissecting the DNA binding landscape and gene regulatory network of p63 and p53.

The transcription factor p53 is the best-known tumor suppressor, but its sibling p63 is a master regulator of epidermis development and a key oncogenic driver in squamous cell carcinomas (SCC). Despite multiple gene expression studies becoming available, the limited overlap of reported p63-dependent genes has made it difficult to decipher the p63 gene regulatory network. Particularly, analyses of p63 response elements differed substantially among the studies. To address this intricate data situation, we provide an integrated resource that enables assessing the p63-dependent regulation of any human gene of interest. We use a novel iterative de novo motif search approach in conjunction with extensive ChIP-seq data to achieve a precise global distinction between p53-and p63-binding sites, recognition motifs, and potential co-factors. We integrate these data with enhancer:gene associations to predict p63 target genes and identify those that are commonly de-regulated in SCC representing candidates for prognosis and therapeutic interventions.

Differential transcriptional responses to Ebola and Marburg virus infection in bat and human cells.

The unprecedented outbreak of Ebola in West Africa resulted in over 28,000 cases and 11,000 deaths, underlining the need for a better understanding of the biology of this highly pathogenic virus to develop specific counter strategies. Two filoviruses, the Ebola and Marburg viruses, result in a severe and often fatal infection in humans. However, bats are natural hosts and survive filovirus infections without obvious symptoms. The molecular basis of this striking difference in the response to filovirus infections is not well understood. We report a systematic overview of differentially expressed genes, activity motifs and pathways in human and bat cells infected with the Ebola and Marburg viruses, and we demonstrate that the replication of filoviruses is more rapid in human cells than in bat cells. We also found that the most strongly regulated genes upon filovirus infection are chemokine ligands and transcription factors. We observed a strong induction of the JAK/STAT pathway, of several genes encoding inhibitors of MAP kinases (DUSP genes) and of PPP1R15A, which is involved in ER stress-induced cell death. We used comparative transcriptomics to provide a data resource that can be used to identify cellular responses that might allow bats to survive filovirus infections.