👤 Martin Pichler

FGFR inhibitors are a new therapeutic option for urothelial carcinoma (UC) with FGFR2/3 alterations. In this study, we analyzed genetic alterations, co-regulation, and differential expression for 45 genes encoding FGF, FGFR, or FGF-binding proteins (FGFBPs) in five published UC cohorts (n = 3939 MIBC) and 39 UC cell lines (DepMap portal). Network analyses identified FGFR1/3 genes as critical oncogenic hubs, co-regulated with their ligands and co-receptors, and abundantly expressed at protein level in the HPA immunohistochemistry data set. Machine learning with 38 FGFR-, FGF-, and FGFBP-coding transcripts reproduced consensus molecular subtypes with high accuracy of 0.72-0.84 (Cohen's κ 0.59-0.77). FGFR3 mutations in the transmembrane/hinge region, which were enriched in luminal papillary tumors, trigger ligand-independent signaling. Conversely, overexpression of FGFR1 and its ligands and accessory protein transcripts indicates ligand-dependent FGFR1 signaling in stroma-rich and basal/squamous subtypes. The sensitivity of most DepMap UC cell lines to pan-FGFR inhibitors in the GDSC and PRISM drug screens was independent of FGFR3 alterations. In vitro, erdafitinib reduced proliferation in FGFR wild-type UC cell lines in a similar manner to FGFR3-mutated cell lines. Our findings highlight FGFR1 and FGFR3 as pivotal signaling pathways with distinct, molecular subtype-specific activation mechanisms. The results suggest that FGFR inhibitors may have therapeutic applications beyond UC tumors with FGFR2/3 alterations. Show less

FGFR3 mutations are among the most frequent genomic alterations in urothelial cancer (UC) being mainly associated with the luminal papillary (LumP) subtype. With the establishment of fibroblast growth factor receptor (FGFR) inhibitors, the treatment of UC is now shifting more and more towards personalized medicine. A systematic review using Medline and scientific meeting records was carried out according to the Preferred Reporting Items for Systematic Review and Meta-analyses guidelines to assess the potential role of FGFR inhibitors in combination with additional therapies for the management of UC. Ongoing trials were identified via a systematic search on ClinicalTrials.gov. A total of eleven full-text papers, ten congress abstracts, and 5 trials on ClinicalTrials.gov were identified. Following the BLC2001 and THOR study, erdafitinib is the only approved FGFR1-4 inhibitor for metastatic UC with susceptible FGFR2/3 alterations following platinum-based chemotherapy. According to the THOR data of cohort 2, erdafitinib should not be recommended in patients who are eligible for and have not received prior immune checkpoint inhibitors (ICIs). One phase 3 trial is currently evaluating the intravesical device system (TAR210) in FGFR-altered intermediate non-muscle invasive bladder cancer (MoonRISe-1). Preclinical evidence suggests that combination-based approaches could be considered to improve the efficacy of FGFR inhibitors in patients with UC. Nine phase 1b/2 trials are focusing on the combination of FGFR inhibitors with ICIs, chemotherapy, or enfortumab vedotin. In metastatic disease, some preliminary analyses have reported promising results from these combinations (e.g. NORSE and FORT-2 trial). However, no phase 3 trial is terminated, so there is currently no level 1 evidence with long-term outcomes to support the combination of FGFR inhibitors with ICIs, chemotherapy, or targeted therapies. A better understanding of the different mechanisms of action to inhibit FGFR signaling pathways, optimal patient selection and treatment approaches is still needed. Show less

Gonadotropin dysregulation seems to play a potential role in the carcinogenesis of testicular germ cell tumor (TGCT). The aim of this study was to explore the expression of specific genes related to sex hormone regulation, synthesis, and metabolism in TGCT and to define specific hormonal clusters. Two publicly available databases were used for this analysis (TCGA and GSE99420). By means of hard-threshold regularized KMEANS clustering, we assigned TGCT samples into four clusters defined in respect to different expression of the sex hormone-related genes. We analysed clinical data, protein and gene expression, signaling regarding hormonal clusters. Based on whole-transcriptome gene expression, prediction of anti-cancer drug response was made by RIDGE models. Cluster #1 (12-16%) consisted primarily of non-seminomatous germ cell tumor (NSGCT), characterized by high expression of PRL, GNRH1, HSD17B2 and SRD5A1. Cluster #2 (42-50%) included predominantly seminomas with high expression of SRD5A3, being highly infiltrated by T and B cells. Cluster #3 (8.3-18%) comprised of NSGCT with high expression of CGA, CYP19A1, HSD17B12, HSD17B1, SHBG. Cluster #4 (23-30%), which consisted primarily of NSGCT with a small fraction of seminomas, was outlined by increased expression of STAR, POMC, CYP11A1, CYP17A1, HSD3B2 and HSD17B3. Elevated fibroblast levels and increased extracellular matrix- and growth factor signaling-related gene signature scores were described in cluster #1 and #3. In the combined model of progression-free survival, S2/S3 tumor marker status, hormonal cluster #1 or #3 and teratoma histology, were independently associated with 25-30% increase of progression risk. Based on the increased receptor tyrosine kinase and growth factor signaling, cluster #1, #3 and #4 were predicted to be sensitive to tyrosine kinase inhibitors, FGFR inhibitors or EGFR/ERBB inhibitors. Cluster #2 and #4 were responsive to compounds interfering with DNA synthesis, cytoskeleton, cell cycle and epigenetics. Response to apoptosis modulators was predicted only for cluster #2. Hormonal cluster #1 or #3 is an independent prognostic factor regarding poor progression-free survival. Hormonal cluster assignment also affects the predicted drug response with cluster-dependent susceptibility to specific novel therapeutic compounds. Show less

Fluorescent fusion proteins are widely used to study protein localization and interaction dynamics in living cells. However, to fully characterize proteins and to understand their function it is crucial to determine biochemical characteristics such as enzymatic activity and binding specificity. Here we demonstrate an easy, reliable and versatile medium/high-throughput method to study biochemical and functional characteristics of fluorescent fusion proteins. Using a new system based on 96-well micro plates comprising an immobilized GFP-binding protein (GFP-mulitTrap), we performed fast and efficient one-step purification of different GFP- and YFP-fusion proteins from crude cell lysate. After immobilization we determined highly reproducible binding ratios of cellular expressed GFP-fusion proteins to histone-tail peptides, DNA or selected RFP-fusion proteins. In particular, we found Cbx1 preferentially binding to di-and trimethylated H3K9 that is abolished by phosphorylation of the adjacent serine. DNA binding assays showed, that the MBD domain of MeCP2 discriminates between fully methylated over unmethylated DNA and protein-protein interactions studies demonstrate, that the PBD domain of Dnmt1 is essential for binding to PCNA. Moreover, using an ELISA-based approach, we detected endogenous PCNA and histone H3 bound at GFP-fusions. In addition, we quantified the level of H3K4me2 on nucleosomes containing different histone variants. In summary, we present an innovative medium/high-throughput approach to analyse binding specificities of fluroescently labeled fusion proteins and to detect endogenous interacting factors in a fast and reliable manner in vitro. Show less

Phospho- and sphingolipids are crucial cellular and intracellular compounds. These lipids are required for active transport, a number of enzymatic processes, membrane formation, and cell signalling. Disruption of their metabolism leads to several diseases, with diverse neurological, psychiatric, and metabolic consequences. A large number of phospholipid and sphingolipid species can be detected and measured in human plasma. We conducted a meta-analysis of five European family-based genome-wide association studies (N = 4034) on plasma levels of 24 sphingomyelins (SPM), 9 ceramides (CER), 57 phosphatidylcholines (PC), 20 lysophosphatidylcholines (LPC), 27 phosphatidylethanolamines (PE), and 16 PE-based plasmalogens (PLPE), as well as their proportions in each major class. This effort yielded 25 genome-wide significant loci for phospholipids (smallest P-value = 9.88×10(-204)) and 10 loci for sphingolipids (smallest P-value = 3.10×10(-57)). After a correction for multiple comparisons (P-value<2.2×10(-9)), we observed four novel loci significantly associated with phospholipids (PAQR9, AGPAT1, PKD2L1, PDXDC1) and two with sphingolipids (PLD2 and APOE) explaining up to 3.1% of the variance. Further analysis of the top findings with respect to within class molar proportions uncovered three additional loci for phospholipids (PNLIPRP2, PCDH20, and ABDH3) suggesting their involvement in either fatty acid elongation/saturation processes or fatty acid specific turnover mechanisms. Among those, 14 loci (KCNH7, AGPAT1, PNLIPRP2, SYT9, FADS1-2-3, DLG2, APOA1, ELOVL2, CDK17, LIPC, PDXDC1, PLD2, LASS4, and APOE) mapped into the glycerophospholipid and 12 loci (ILKAP, ITGA9, AGPAT1, FADS1-2-3, APOA1, PCDH20, LIPC, PDXDC1, SGPP1, APOE, LASS4, and PLD2) to the sphingolipid pathways. In large meta-analyses, associations between FADS1-2-3 and carotid intima media thickness, AGPAT1 and type 2 diabetes, and APOA1 and coronary artery disease were observed. In conclusion, our study identified nine novel phospho- and sphingolipid loci, substantially increasing our knowledge of the genetic basis for these traits. Show less

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation. Show less

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes. Show less

Sphingolipids have essential roles as structural components of cell membranes and in cell signalling, and disruption of their metabolism causes several diseases, with diverse neurological, psychiatric, and metabolic consequences. Increasingly, variants within a few of the genes that encode enzymes involved in sphingolipid metabolism are being associated with complex disease phenotypes. Direct experimental evidence supports a role of specific sphingolipid species in several common complex chronic disease processes including atherosclerotic plaque formation, myocardial infarction (MI), cardiomyopathy, pancreatic beta-cell failure, insulin resistance, and type 2 diabetes mellitus. Therefore, sphingolipids represent novel and important intermediate phenotypes for genetic analysis, yet little is known about the major genetic variants that influence their circulating levels in the general population. We performed a genome-wide association study (GWAS) between 318,237 single-nucleotide polymorphisms (SNPs) and levels of circulating sphingomyelin (SM), dihydrosphingomyelin (Dih-SM), ceramide (Cer), and glucosylceramide (GluCer) single lipid species (33 traits); and 43 matched metabolite ratios measured in 4,400 subjects from five diverse European populations. Associated variants (32) in five genomic regions were identified with genome-wide significant corrected p-values ranging down to 9.08x10(-66). The strongest associations were observed in or near 7 genes functionally involved in ceramide biosynthesis and trafficking: SPTLC3, LASS4, SGPP1, ATP10D, and FADS1-3. Variants in 3 loci (ATP10D, FADS3, and SPTLC3) associate with MI in a series of three German MI studies. An additional 70 variants across 23 candidate genes involved in sphingolipid-metabolizing pathways also demonstrate association (p = 10(-4) or less). Circulating concentrations of several key components in sphingolipid metabolism are thus under strong genetic control, and variants in these loci can be tested for a role in the development of common cardiovascular, metabolic, neurological, and psychiatric diseases. Show less

Recent genome-wide association (GWA) studies of lipids have been conducted in samples ascertained for other phenotypes, particularly diabetes. Here we report the first GWA analysis of loci affecting total cholesterol (TC), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and triglycerides sampled randomly from 16 population-based cohorts and genotyped using mainly the Illumina HumanHap300-Duo platform. Our study included a total of 17,797-22,562 persons, aged 18-104 years and from geographic regions spanning from the Nordic countries to Southern Europe. We established 22 loci associated with serum lipid levels at a genome-wide significance level (P < 5 x 10(-8)), including 16 loci that were identified by previous GWA studies. The six newly identified loci in our cohort samples are ABCG5 (TC, P = 1.5 x 10(-11); LDL, P = 2.6 x 10(-10)), TMEM57 (TC, P = 5.4 x 10(-10)), CTCF-PRMT8 region (HDL, P = 8.3 x 10(-16)), DNAH11 (LDL, P = 6.1 x 10(-9)), FADS3-FADS2 (TC, P = 1.5 x 10(-10); LDL, P = 4.4 x 10(-13)) and MADD-FOLH1 region (HDL, P = 6 x 10(-11)). For three loci, effect sizes differed significantly by sex. Genetic risk scores based on lipid loci explain up to 4.8% of variation in lipids and were also associated with increased intima media thickness (P = 0.001) and coronary heart disease incidence (P = 0.04). The genetic risk score improves the screening of high-risk groups of dyslipidemia over classical risk factors. Show less