Marco Mernberger

A Senescence-Inflammatory Switch from Cancer-Inhibitory to Cancer-Promoting Mechanism

Senescence, perceived as a cancer barrier, is paradoxically associated with inflammation, which promotes tumorigenesis. Here, we characterize a distinct low-grade inflammatory process in stressed epithelium that is related to para-inflammation; this process either represses or promotes tumorigenesis, depending on p53 activity. Csnk1a1 (CKIα) downregulation induces a senescence-associated inflammatory response (SIR) with growth arrest in colorectal tumors, which loses its growth control capacity in the absence of p53 and instead, accelerates growth and invasiveness. Corresponding processes occur in CKIα-deleted intestinal organoids, assuming tumorigenic transformation properties ex vivo, upon p53 loss. Treatment of organoids and mice with anti-inflammatory agents suppresses the SIR and prevents p53-deficient organoid transformation and mouse carcinogenesis. SIR/para-inflammation suppression may therefore constitute a key mechanism in the anticarcinogenic effects of nonsteroidal anti-inflammatory drugs.

Characterization of the p53 Cistrome - DNA Binding Cooperativity Dissects p53's Tumor Suppressor Functions

p53 protects us from cancer by transcriptionally regulating tumor suppressive programs designed to either prevent the development or clonal expansion of malignant cells. How p53 selects target genes in the genome in a context- and tissue-specific manner remains largely obscure. There is growing evidence that the ability of p53 to bind DNA in a cooperative manner prominently influences target gene selection with activation of the apoptosis program being completely dependent on DNA binding cooperativity. Here, we used ChIP-seq to comprehensively profile the cistrome of p53 mutants with reduced or increased cooperativity. The analysis highlighted a particular relevance of cooperativity for extending the p53 cistrome to non-canonical binding sequences characterized by deletions, spacer insertions and base mismatches. Furthermore, it revealed a striking functional separation of the cistrome on the basis of cooperativity; with low cooperativity genes being significantly enriched for cell cycle and high cooperativity genes for apoptotic functions. Importantly, expression of high but not low cooperativity genes was correlated with superior survival in breast cancer patients. Interestingly, in contrast to most p53-activated genes, p53-repressed genes did not commonly contain p53 binding elements. Nevertheless, both the degree of gene activation and repression were cooperativity-dependent, suggesting that p53-mediated gene repression is largely indirect and mediated by cooperativity-dependently transactivated gene products such as CDKN1A, E2F7 and non-coding RNAs. Since both activation of apoptosis genes with non-canonical response elements and repression of pro-survival genes are crucial for p53s apoptotic activity, the cistrome analysis comprehensively explains why p53-induced apoptosis, but not cell cycle arrest, strongly depends on the intermolecular cooperation of p53 molecules as a possible safeguard mechanism protecting from accidental cell killing.

Antithetical NFATc1–Sox2 and p53–miR200 signaling networks govern pancreatic cancer cell plasticity

In adaptation to oncogenic signals, pancreatic ductal adenocarcinoma (PDAC) cells undergo epithelial–mesenchymal transition (EMT), a process combining tumor cell dedifferentiation with acquisition of stemness features. However, the mechanisms linking oncogene‐induced signaling pathways with EMT and stemness remain largely elusive. Here, we uncover the inflammation‐induced transcription factor NFATc1 as a central regulator of pancreatic cancer cell plasticity. In particular, we show that NFATc1 drives EMT reprogramming and maintains pancreatic cancer cells in a stem cell‐like state through Sox2‐dependent transcription of EMT and stemness factors. Intriguingly, NFATc1–Sox2 complex‐mediated PDAC dedifferentiation and progression is opposed by antithetical p53‐miR200c signaling, and inactivation of the tumor suppressor pathway is essential for tumor dedifferentiation and dissemination both in genetically engineered mouse models (GEMM) and human PDAC. Based on these findings, we propose the existence of a hierarchical signaling network regulating PDAC cell plasticity and suggest that the molecular decision between epithelial cell preservation and conversion into a dedifferentiated cancer stem cell‐like phenotype depends on opposing levels of p53 and NFATc1 signaling activities.

Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules

The concept of multiple graph alignment (MGA) has recently been introduced as a novel method for the structural analysis of biomolecules. Using approximate graph matching techniques, this method enables the robust identification of approximately conserved patterns in biologically related structures. In particular, MGA enables the characterization of functional protein families independent of sequence or fold homology. This article first recalls the concept of MGA and then addresses the problem of computing optimal alignments from an algorithmic point of view. In this regard, a method from the field of evolutionary algorithms is proposed and empirically compared with a hitherto existing heuristic approach. Empirically, it is shown that the former yields significantly better results than the latter, albeit at the cost of an increased runtime.

Mutant p53 promotes tumor progression and metastasis by the endoplasmic reticulum UDPase ENTPD5

Significance p53 mutations are the most frequent genetic alteration in cancer and are often indicative of poor patient survival prognosis. The most prevalent missense mutations lead to a “gain of function” (GOF) that actively drives tumor progression, metastasis, and therapy resistance. Our study links the mutant p53 (mutp53) GOF to enhanced N-glycoprotein folding via ectonucleoside triphosphate diphosphohydrolase 5 (ENTPD5) in the calnexin/calreticulin cycle of the endoplasmic reticulum. Mutp53 thus increases expression of prometastatic cell surface proteins, such as receptors and integrins, not only quantitatively but also qualitatively, with respect to N-glycosylation state. Our study reveals N-glycoprotein quality control in the endoplasmic reticulum as an indispensable mechanism underlying the progression of tumors with GOF mutp53 that could provide new possibilities for treating prognostically challenging p53-mutated cancers. Mutations in the p53 tumor suppressor gene are the most frequent genetic alteration in cancer and are often associated with progression from benign to invasive stages with metastatic potential. Mutations inactivate tumor suppression by p53, and some endow the protein with novel gain of function (GOF) properties that actively promote tumor progression and metastasis. By comparative gene expression profiling of p53-mutated and p53-depleted cancer cells, we identified ectonucleoside triphosphate diphosphohydrolase 5 (ENTPD5) as a mutant p53 target gene, which functions as a uridine 5′-diphosphatase (UDPase) in the endoplasmic reticulum (ER) to promote the folding of N-glycosylated membrane proteins. A comprehensive pan-cancer analysis revealed a highly significant correlation between p53 GOF mutations and ENTPD5 expression. Mechanistically, mutp53 is recruited by Sp1 to the ENTPD5 core promoter to induce its expression. We show ENTPD5 to be a mediator of mutant p53 GOF activity in clonogenic growth, architectural tissue remodeling, migration, invasion, and lung colonization in an experimental metastasis mouse model. Our study reveals folding of N-glycosylated membrane proteins in the ER as a mechanism underlying the metastatic progression of tumors with mutp53 that could provide new possibilities for cancer treatment.

Galectin-3 interacts with components of the nuclear ribonucleoprotein complex

BackgroundThe multifunctional β-galactoside-binding protein galectin-3 is found in many distinct subcellular compartments including the cell nucleus. Expression and distribution of galectin-3 between the cell nucleus and the cytosol changes during cell differentiation and cancer development. Nuclear functions of galectin-3 and how they contribute to tumorigenesis are not understood.MethodsIn order to identify nuclear galectin-3 interaction partners, we used affinity chromatography and co-immunoprecipitation. Spatial proximity in the nucleus was assessed by immunofluorescence and proximity ligation assay. We also investigated the function of galectin-3 on mRNA-export by fluorescence in situ hybridization and on mRNA-processing by RNA-sequencing.ResultsThe heterogeneous ribonucleoprotein particle component hnRNPA2B1 was identified as a novel galectin-3 binding protein that associates with the lectin in a lactose-dependent manner in the cell nucleus. Specific individual depletion of galectin-3 does not affect the mRNA distribution between cytoplasm and nucleus. A significant alteration of this distribution was observed after combined depletion of galectin-1 and −3. However, silencing of galectin-3 was sufficient to alter the splicing patterns of several genes.ConclusionsGalectin-3 and hnRNPA2B1 interact as members of the early splicing machinery. Galectin-3 and −1 have redundant functions in mRNA transport and at least in part in mRNA splicing. RNA-sequencing data points to a specific function of the hnRNPA2B1/galectin-3 interaction in the processing of transcripts coding for the nuclear oncoprotein SET.

GPU-based Cloud computing for comparing the structure of protein binding sites

In this paper, we present a novel approach for using a GPU-based Cloud computing infrastructure to efficiently perform a structural comparison of protein binding sites. The original CPU-based Java version of a recent graph-based algorithm called SEGA has been rewritten in OpenCL to run on NVIDIA GPUs in parallel on a set of Amazon EC2 Cluster GPU Instances. This new implementation of SEGA has been tested on a subset of protein structure data contained in the CavBase, providing a structural comparison of protein binding sites on a much larger scale than in previous research efforts reported in the literature.

SEGA: Semiglobal Graph Alignment for Structure-Based Protein Comparison

Comparative analysis is a topic of utmost importance in structural bioinformatics. Recently, a structural counterpart to sequence alignment, called multiple graph alignment, was introduced as a tool for the comparison of protein structures in general and protein binding sites in particular. Using approximate graph matching techniques, this method enables the identification of approximately conserved patterns in functionally related structures. In this paper, we introduce a new method for computing graph alignments motivated by two problems of the original approach, a conceptual and a computational one. First, the existing approach is of limited usefulness for structures that only share common substructures. Second, the goal to find a globally optimal alignment leads to an optimization problem that is computationally intractable. To overcome these disadvantages, we propose a semiglobal approach to graph alignment in analogy to semiglobal sequence alignment that combines the advantages of local and global graph matching.

Effects of YM155 on survivin levels and viability in neuroblastoma cells with acquired drug resistance

Resistance formation after initial therapy response (acquired resistance) is common in high-risk neuroblastoma patients. YM155 is a drug candidate that was introduced as a survivin suppressant. This mechanism was later challenged, and DNA damage induction and Mcl-1 depletion were suggested instead. Here we investigated the efficacy and mechanism of action of YM155 in neuroblastoma cells with acquired drug resistance. The efficacy of YM155 was determined in neuroblastoma cell lines and their sublines with acquired resistance to clinically relevant drugs. Survivin levels, Mcl-1 levels, and DNA damage formation were determined in response to YM155. RNAi-mediated depletion of survivin, Mcl-1, and p53 was performed to investigate their roles during YM155 treatment. Clinical YM155 concentrations affected the viability of drug-resistant neuroblastoma cells through survivin depletion and p53 activation. MDM2 inhibitor-induced p53 activation further enhanced YM155 activity. Loss of p53 function generally affected anti-neuroblastoma approaches targeting survivin. Upregulation of ABCB1 (causes YM155 efflux) and downregulation of SLC35F2 (causes YM155 uptake) mediated YM155-specific resistance. YM155-adapted cells displayed increased ABCB1 levels, decreased SLC35F2 levels, and a p53 mutation. YM155-adapted neuroblastoma cells were also characterized by decreased sensitivity to RNAi-mediated survivin depletion, further confirming survivin as a critical YM155 target in neuroblastoma. In conclusion, YM155 targets survivin in neuroblastoma. Furthermore, survivin is a promising therapeutic target for p53 wild-type neuroblastomas after resistance acquisition (neuroblastomas are rarely p53-mutated), potentially in combination with p53 activators. In addition, we show that the adaptation of cancer cells to molecular-targeted anticancer drugs is an effective strategy to elucidate a drug’s mechanism of action.

Similarity Analysis of Protein Binding Sites: A Generalization of the Maximum Common Subgraph Measure Based on Quasi-Clique Detection

Protein binding sites are often represented by means of graphs capturing their most important geometrical and physicochemical properties. Searching for structural similarities and identifying functional relationships between them can thus be reduced to matching their corresponding graph descriptors. In this paper, we propose a method for the structural analysis of protein binding sites that makes use of such matching techniques to assess the similarity between proteins independently of sequence or fold homology. More specifically, we propose a similarity measure that generalizes the commonly used maximum common subgraph measure in two ways. First, using algorithms for so-called quasi-clique detection, our measure is based on maximum ‘approximately’ common subgraphs, a relaxation of maximum common subgraphs which is tolerant toward edge mismatches. Second, instead of focusing on equivalence, our measure is a compromise between a generalized equivalence and an inclusion measure. An experimental study is presented to illustrate the effectiveness of the method and to show that both types of relaxation are useful in the context of protein structure analysis.