👤 Birgit Kunz

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

Recent studies showed lower apolipoprotein A-IV (apoA-IV) plasma concentrations in patients with coronary artery disease (CAD). The actual distribution of the antiatherogenic apoA-IV in human plasma, however, is discussed controversially and it was never investigated in CAD patients. We therefore developed a gentle technique to separate the various apoA-IV-containing plasma fractions. Using a combination of precipitation of all lipoproteins with 40% phosphotungstic acid and 4 M MgCl2, as well as immunoprecipitation of all apoA-I-containing particles with an anti-apoA-I antibody, we obtained three fractions of apoA-IV: lipid-free apoA-IV (about 4% of total apoA-IV), apoA-IV associated with apoA-I (LpA-I:A-IV, 12%), and apoA-I-unbound but lipoprotein-containing apoA-IV (LpA-IV, 84%). We compared these three apoA-IV fractions between 52 patients with a history of CAD and 52 age- and sex-matched healthy controls. Patients had significantly lower apoA-IV levels when compared to controls (10.28 +/- 3.67 mg/dl vs. 11.85 +/- 2.82 mg/dl, P = 0.029), but no major differences for the three plasma apoA-IV fractions. We conclude that our gentle separation method reveals a different distribution of apoA-IV than in many earlier studies. No major differences exist in the apoA-IV plasma distribution pattern between CAD patients and controls. Therefore, the antiatherogenic effect of apoA-IV has to be explained by other functional properties of apoA-IV (e.g., the antioxidative characteristics). Show less