Salmonella Typhimurium (S. Tm) is a leading cause of diarrhea. The disease is triggered by pathogen invasion into the gut epithelium. Invasion is attributed to the SPI-1 type 3 secretion system (T1). T1 injects effector proteins into epithelial cells and thereby elicits rearrangements of the host cellular actin cytoskeleton and pathogen invasion. The T1 effector proteins SopE, SopB, SopE2 and SipA are contributing to this. However, the host cell factors contributing to invasion are still not completely understood. To address this question comprehensively, we used Hela tissue culture cells, a genome-wide siRNA library, a modified gentamicin protection assay and S. TmSipA, a sopBsopE2sopE mutant which strongly relies on the T1 effector protein SipA to invade host cells. We found that S. TmSipA invasion does not elicit membrane ruffles, nor promote the entry of non-invasive bacteria "in trans". However, SipA-mediated infection involved the SPIRE family of actin nucleators, besides well-established host cell factors (WRC, ARP2/3, RhoGTPases, COPI). Stage-specific follow-up assays and knockout fibroblasts indicated that SPIRE1 and SPIRE2 are involved in different steps of the S. Tm infection process. Whereas SPIRE1 interferes with bacterial binding, SPIRE2 influences intracellular replication of S. Tm. Hence, these two proteins might fulfill non-redundant functions in the pathogen-host interaction. The lack of co-localization hints to a short, direct interaction between S. Tm and SPIRE proteins or to an indirect effect.

Mutations in transcription factor (TF) genes are frequently observed in tumors, often leading to aberrant transcriptional activity. Unfortunately, TFs are often considered undruggable due to the absence of targetable enzymatic activity. To address this problem, we developed CRAFTT, a computational drug-repositioning approach for targeting TF activity. CRAFTT combines ChIP-seq with drug-induced expression profiling to identify small molecules that can specifically perturb TF activity. Application to ENCODE ChIP-seq datasets revealed known drug-TF interactions, and a global drug-protein network analysis supported these predictions. Application of CRAFTT to ERG, a pro-invasive, frequently overexpressed oncogenic TF, predicted that dexamethasone would inhibit ERG activity. Dexamethasone significantly decreased cell invasion and migration in an ERG-dependent manner. Furthermore, analysis of electronic medical record data indicates a protective role for dexamethasone against prostate cancer. Altogether, our method provides a broadly applicable strategy for identifying drugs that specifically modulate TF activity.

Intratumoral hypoxia plays an important role with regard to tumor biology and susceptibility to radio- and chemotherapy. For further investigation of hypoxia-related changes, areas of certain hypoxia must be reliably detected within cancer tissues. Pimonidazole, a 2-nitroimindazole, accumulates in hypoxic tissue and can be easily visualized using immunohistochemistry.

The L1 cell adhesion molecule (L1CAM) is potentially involved in epithelial-mesenchymal transition (EMT). EMT marker expression is of prognostic significance in non-small cell lung cancer (NSCLC). The relevance of L1CAM for NSCLC is unclear. We investigated the protein expression of L1CAM in a cohort of NSCLC patients. L1CAM protein expression was correlated with clinico-pathological parameters including survival and markers of epithelial-mesenchymal transition.

Decreased β cell mass and function are hallmarks of type 2 diabetes. Here we identified, through a siRNA screen, beta site amyloid precursor protein cleaving enzyme 2 (Bace2) as the sheddase of the proproliferative plasma membrane protein Tmem27 in murine and human β cells. Mice with functionally inactive Bace2 and insulin-resistant mice treated with a newly identified Bace2 inhibitor both display augmented β cell mass and improved control of glucose homeostasis due to increased insulin levels. These results implicate Bace2 in the control of β cell maintenance and provide a rational strategy to inhibit this protease for the expansion of functional pancreatic β cell mass.

Cancer has long been understood as a somatic evolutionary process, but many details of tumor progression remain elusive. Here, we present BitPhylogenyBitPhylogeny, a probabilistic framework to reconstruct intra-tumor evolutionary pathways. Using a full Bayesian approach, we jointly estimate the number and composition of clones in the sample as well as the most likely tree connecting them. We validate our approach in the controlled setting of a simulation study and compare it against several competing methods. In two case studies, we demonstrate how BitPhylogeny BitPhylogeny reconstructs tumor phylogenies from methylation patterns in colon cancer and from single-cell exomes in myeloproliferative neoplasm.

The von Hippel-Lindau (VHL) tumor suppressor gene is mutated as an early event in almost all cases of clear cell renal cell carcinoma (ccRCC), the most frequent form of kidney cancer. In this review we discuss recent advances in understanding how dysregulation of the many hypoxia-inducible factor α-dependent and -independent functions of the VHL tumor suppressor protein (pVHL) can contribute to tumor initiation and progression. Recent evidence showing extensive inter- and intratumoral genetic diversity has given rise to the idea that ccRCC should actually be considered as a series of molecularly related, yet distinct, diseases defined by the pattern of combinatorial genetic alterations present within the cells of the tumor. We highlight the range of genetic and epigenetic alterations that recur in ccRCC and discuss the mechanisms through which these events appear to function cooperatively with a loss of pVHL function in tumorigenesis.

Toward development of a precision medicine framework for metastatic, castration-resistant prostate cancer (mCRPC), we established a multi-institutional clinical sequencing infrastructure to conduct prospective whole-exome and transcriptome sequencing of bone or soft tissue tumor biopsies from a cohort of 150 mCRPC affected individuals. Aberrations of AR, ETS genes, TP53, and PTEN were frequent (40%-60% of cases), with TP53 and AR alterations enriched in mCRPC compared to primary prostate cancer. We identified new genomic alterations in PIK3CA/B, R-spondin, BRAF/RAF1, APC, β-catenin, and ZBTB16/PLZF. Moreover, aberrations of BRCA2, BRCA1, and ATM were observed at substantially higher frequencies (19.3% overall) compared to those in primary prostate cancers. 89% of affected individuals harbored a clinically actionable aberration, including 62.7% with aberrations in AR, 65% in other cancer-related genes, and 8% with actionable pathogenic germline alterations. This cohort study provides clinically actionable information that could impact treatment decisions for these affected individuals.

CCNE1 is frequently amplified in high grade serous ovarian cancer and may serve as a target for ovarian cancer treatment. URI is closely related to CCNE1 at the 19q12 amplicon and may also contribute to the oncogenic effect. Our objective was to investigate the relevance of CCNE1 and URI gene amplification and protein expression in different histological subtypes of epithelial ovarian cancer (EOC).

Promoter CpG islands are typically unmethylated in normal cells, but in cancer a proportion are subject to hypermethylation. Using methylome sequencing we identified CpG islands that display partial methylation encroachment across the 5' or 3' CpG island borders. CpG island methylation encroachment is widespread in prostate and breast cancer and commonly associates with gene suppression. We show that the pattern of H3K4me1 at CpG island borders in normal cells predicts the different modes of cancer CpG island hypermethylation. Notably, genetic manipulation of Kmt2d results in concordant alterations in H3K4me1 levels and CpG island border DNA methylation encroachment. Our findings suggest a role for H3K4me1 in the demarcation of CpG island methylation borders in normal cells, which become eroded in cancer.

Reconstructing the evolution of tumors is a key aspect towards the identification of appropriate cancer therapies. The task is challenging because tumors evolve as heterogeneous cell populations. Single-cell sequencing holds the promise of resolving the heterogeneity of tumors; however, it has its own challenges including elevated error rates, allelic drop-out, and uneven coverage. Here, we develop a new approach to mutation detection in individual tumor cells by leveraging the evolutionary relationship among cells. Our method, called SCIΦ, jointly calls mutations in individual cells and estimates the tumor phylogeny among these cells. Employing a Markov Chain Monte Carlo scheme enables us to reliably call mutations in each single cell even in experiments with high drop-out rates and missing data. We show that SCIΦ outperforms existing methods on simulated data and applied it to different real-world datasets, namely a whole exome breast cancer as well as a panel acute lymphoblastic leukemia dataset.

Deciphering cell-intrinsic mechanisms of metastasis progression in vivo is essential to identify novel therapeutic approaches. Here we elucidate cell-intrinsic drivers of metastatic prostate cancer progression through analyses of genetically engineered mouse models (GEMM) and correlative studies of human prostate cancer. Expression profiling of lineage-marked cells from mouse primary tumors and metastases defines a signature of de novo metastatic progression. Cross-species master regulator analyses comparing this mouse signature with a comparable human signature identifies conserved drivers of metastatic progression with demonstrable clinical and functional relevance. In particular, nuclear receptor binding SET Domain Protein 2 (NSD2) is robustly expressed in lethal prostate cancer in humans, while its silencing inhibits metastasis of mouse allografts in vivo. We propose that cross-species analysis can elucidate mechanisms of metastasis progression, thus providing potential additional therapeutic opportunities for treatment of lethal prostate cancer.

A major hurdle in the study of rare tumors is a lack of existing preclinical models. Neuroendocrine prostate cancer is an uncommon and aggressive histologic variant of prostate cancer that may arise de novo or as a mechanism of treatment resistance in patients with pre-existing castration-resistant prostate cancer. There are few available models to study neuroendocrine prostate cancer. Here, we report the generation and characterization of tumor organoids derived from needle biopsies of metastatic lesions from four patients. We demonstrate genomic, transcriptomic, and epigenomic concordance between organoids and their corresponding patient tumors. We utilize these organoids to understand the biologic role of the epigenetic modifier EZH2 in driving molecular programs associated with neuroendocrine prostate cancer progression. High-throughput organoid drug screening nominated single agents and drug combinations suggesting repurposing opportunities. This proof of principle study represents a strategy for the study of rare cancer phenotypes.

Annotation and interpretation of DNA aberrations identified through next-generation sequencing is becoming an increasingly important task. Even more so in the context of data analysis pipelines for medical applications, where genomic aberrations are associated with phenotypic and clinical features. Here we describe a workflow to identify potential gene targets in aberrated genes or pathways and their corresponding drugs. To this end, we provide the R/Bioconductor package rDGIdb, an R wrapper to query the drug-gene interaction database (DGIdb). DGIdb accumulates drug-gene interaction data from 15 different resources and allows filtering on different levels. The rDGIdb package makes these resources and tools available to R users. Moreover, rDGIdb queries can be automated through incorporation of the rDGIdb package into NGS sequencing pipelines.

Clear cell Renal Cell Carcinoma (ccRCC) formation is connected to functional loss of the von Hippel-Lindau (VHL) gene. Recent data identified its gene product, pVHL, as a multifunctional adaptor protein which interacts with HIFα subunits but also with the tumor suppressor p53. p53 is hardly expressed and rarely mutated in most ccRCC. We showed that low and absent p53 expression correlated with the severity of VHL mutations in 262 analyzed ccRCC tissues. In contrast to nonsense and frameshift mutations which abrogate virtually all pVHL functions, missense mutations may rather influence one or few functions. Therefore, we focused on four VHL missense mutations, which affect the overlapping pVHL binding sites of p53 and Elongin C, by investigating their impact on HIFα degradation, p53 expression and signaling, as well as on cellular behavior using ccRCC cell lines and tissues. TP53 mRNA and its effector targets p21, Bax and Noxa, were altered both in engineered cell lines and in tumor tissues which carried the same missense mutations. Two of these mutations were not able to degrade HIFα whereas the remaining two mutations led to HIFα downregulation, suggesting the latter are p53 binding site-specific. The selected VHL missense mutations further enhanced tumor cell survival, but had no effects on cell proliferation. Whereas Sunitinib was able to efficiently reduce cell proliferation, Camptothecin was additionally able to increase apoptotic activity of the tumor cells. It is concluded that systematic characterization of the VHL mutation status may help optimizing targeted therapy for patients with metastatic ccRCC.

Breast tumors of the basal-like, hormone receptor-negative subtype remain an unmet clinical challenge, as there is high rate of recurrence and poor survival in patients following treatment. Coevolution of the malignant mammary epithelium and its underlying stroma instigates cancer-associated fibroblasts (CAFs) to support most, if not all, hallmarks of cancer progression. Here we delineate a previously unappreciated role for CAFs as determinants of the molecular subtype of breast cancer. We identified paracrine crosstalk between cancer cells expressing platelet-derived growth factor (PDGF)-CC and CAFs expressing the cognate receptors in human basal-like mammary carcinomas. Genetic or pharmacological intervention of PDGF-CC activity in mouse models of cancer resulted in conversion of basal-like breast cancers into a hormone receptor-positive state that enhanced sensitivity to endocrine therapy in previously resistant tumors. We conclude that specification of breast cancer to the basal-like subtype is under microenvironmental control and is therapeutically actionable.

Understanding the integrated immunogenomic landscape of advanced prostate cancer (APC) could impact stratified treatment selection.

Personalized, precision, P4, or stratified medicine is understood as a medical approach in which patients are stratified based on their disease subtype, risk, prognosis, or treatment response using specialized diagnostic tests. The key idea is to base medical decisions on individual patient characteristics, including molecular and behavioral biomarkers, rather than on population averages. Personalized medicine is deeply connected to and dependent on data science, specifically machine learning (often named Artificial Intelligence in the mainstream media). While during recent years there has been a lot of enthusiasm about the potential of 'big data' and machine learning-based solutions, there exist only few examples that impact current clinical practice. The lack of impact on clinical practice can largely be attributed to insufficient performance of predictive models, difficulties to interpret complex model predictions, and lack of validation via prospective clinical trials that demonstrate a clear benefit compared to the standard of care. In this paper, we review the potential of state-of-the-art data science approaches for personalized medicine, discuss open challenges, and highlight directions that may help to overcome them in the future.

The classification of neuroendocrine neoplasms (NENs) differs between organ systems and currently causes considerable confusion. A uniform classification framework for NENs at any anatomical location may reduce inconsistencies and contradictions among the various systems currently in use. The classification suggested here is intended to allow pathologists and clinicians to manage their patients with NENs consistently, while acknowledging organ-specific differences in classification criteria, tumor biology, and prognostic factors. The classification suggested is based on a consensus conference held at the International Agency for Research on Cancer (IARC) in November 2017 and subsequent discussion with additional experts. The key feature of the new classification is a distinction between differentiated neuroendocrine tumors (NETs), also designated carcinoid tumors in some systems, and poorly differentiated NECs, as they both share common expression of neuroendocrine markers. This dichotomous morphological subdivision into NETs and NECs is supported by genetic evidence at specific anatomic sites as well as clinical, epidemiologic, histologic, and prognostic differences. In many organ systems, NETs are graded as G1, G2, or G3 based on mitotic count and/or Ki-67 labeling index, and/or the presence of necrosis; NECs are considered high grade by definition. We believe this conceptual approach can form the basis for the next generation of NEN classifications and will allow more consistent taxonomy to understand how neoplasms from different organ systems inter-relate clinically and genetically.

Mutations in PIK3CA, which encodes the p110α subunit of the insulin-activated phosphatidylinositol-3 kinase (PI3K), and loss of function mutations in PTEN, which encodes a phosphatase that degrades the phosphoinositide lipids generated by PI3K, are among the most frequent events in human cancers1,2. However, pharmacological inhibition of PI3K has resulted in variable clinical responses, raising the possibility of an inherent mechanism of resistance to treatment. As p110α mediates virtually all cellular responses to insulin, targeted inhibition of this enzyme disrupts glucose metabolism in multiple tissues. For example, blocking insulin signalling promotes glycogen breakdown in the liver and prevents glucose uptake in the skeletal muscle and adipose tissue, resulting in transient hyperglycaemia within a few hours of PI3K inhibition. The effect is usually transient because compensatory insulin release from the pancreas (insulin feedback) restores normal glucose homeostasis3. However, the hyperglycaemia may be exacerbated or prolonged in patients with any degree of insulin resistance and, in these cases, necessitates discontinuation of therapy3-6. We hypothesized that insulin feedback induced by PI3K inhibitors may reactivate the PI3K-mTOR signalling axis in tumours, thereby compromising treatment effectiveness7,8. Here we show, in several model tumours in mice, that systemic glucose-insulin feedback caused by targeted inhibition of this pathway is sufficient to activate PI3K signalling, even in the presence of PI3K inhibitors. This insulin feedback can be prevented using dietary or pharmaceutical approaches, which greatly enhance the efficacy/toxicity ratios of PI3K inhibitors. These findings have direct clinical implications for the multiple p110α inhibitors that are in clinical trials and provide a way to increase treatment efficacy for patients with many types of tumour.