Aberrant ErbB2 receptor tyrosine kinase activation in breast cancer is strongly linked to an invasive disease. The molecular basis of ErbB2-driven invasion is largely unknown. We show that cysteine cathepsins B and L are elevated in ErbB2 positive primary human breast cancer and function as effectors of ErbB2-induced invasion in vitro. We identify Cdc42-binding protein kinase beta, extracellular regulated kinase 2, p21-activated protein kinase 4, and protein kinase C alpha as essential mediators of ErbB2-induced cysteine cathepsin expression and breast cancer cell invasiveness. The identified signaling network activates the transcription of cathepsin B gene (CTSB) via myeloid zinc finger-1 transcription factor that binds to an ErbB2-responsive enhancer element in the first intron of CTSB. This work provides a model system for ErbB2-induced breast cancer cell invasiveness, reveals a signaling network that is crucial for invasion in vitro, and defines a specific role and targets for the identified serine-threonine kinases.

BackgroundCoordinated efforts to collect large-scale data sets provide a basis for systems level understanding of complex diseases. In order to translate these fragmented and heterogeneous data sets into knowledge and medical benefits, advanced computational methods for data analysis, integration and visualization are needed.MethodsWe introduce a novel data integration framework, Anduril, for translating fragmented large-scale data into testable predictions. The Anduril framework allows rapid integration of heterogeneous data with state-of-the-art computational methods and existing knowledge in bio-databases. Anduril automatically generates thorough summary reports and a website that shows the most relevant features of each gene at a glance, allows sorting of data based on different parameters, and provides direct links to more detailed data on genes, transcripts or genomic regions. Anduril is open-source; all methods and documentation are freely available.ResultsWe have integrated multidimensional molecular and clinical data from 338 subjects having glioblastoma multiforme, one of the deadliest and most poorly understood cancers, using Anduril. The central objective of our approach is to identify genetic loci and genes that have significant survival effect. Our results suggest several novel genetic alterations linked to glioblastoma multiforme progression and, more specifically, reveal Moesin as a novel glioblastoma multiforme-associated gene that has a strong survival effect and whose depletion in vitro significantly inhibited cell proliferation. All analysis results are available as a comprehensive website.ConclusionsOur results demonstrate that integrated analysis and visualization of multidimensional and heterogeneous data by Anduril enables drawing conclusions on functional consequences of large-scale molecular data. Many of the identified genetic loci and genes having significant survival effect have not been reported earlier in the context of glioblastoma multiforme. Thus, in addition to generally applicable novel methodology, our results provide several glioblastoma multiforme candidate genes for further studies.Anduril is available at http://csbi.ltdk.helsinki.fi/anduril/The glioblastoma multiforme analysis results are available at http://csbi.ltdk.helsinki.fi/anduril/tcga-gbm/

Aims/hypothesis We aimed to identify a sparse panel of biomarkers for improving the prediction of renal disease progression in type 1 diabetes. Methods We considered 859 individuals recruited from the Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) and 315 individuals from the Finnish Diabetic Nephropathy (FinnDiane) study. All had an entry eGFR between 30 and 75 ml min −1 [1.73 m] −2 , with those from FinnDiane being oversampled for albuminuria. A total of 297 circulating biomarkers (30 proteins, 121 metabolites, 146 tryptic peptides) were measured in non-fasting serum samples using the Luminex platform and LC electrospray tandem MS (LC-MS/MS). We investigated associations with final eGFR adjusted for baseline eGFR and with rapid progression (a loss of more than 3 ml min −1 [1.73 m] −2 year −1 ) using linear and logistic regression models. Panels of biomarkers were identified using a penalised Bayesian approach, and their performance was evaluated through 10-fold cross-validation and compared with using clinical record data alone. Results For final eGFR, 16 proteins and 30 metabolites or tryptic peptides showed significant association in SDRNT1BIO, and nine proteins and five metabolites or tryptic peptides in FinnDiane, beyond age, sex, diabetes duration, study day eGFR and length of follow-up (all at p < 10 −4 ). The strongest associations were with CD27 antigen (CD27), kidney injury molecule 1 (KIM-1) and α1-microglobulin. Including the Luminex biomarkers on top of baseline covariates increased the r 2 for prediction of final eGFR from 0.47 to 0.58 in SDRNT1BIO and from 0.33 to 0.48 in FinnDiane. At least 75% of the increment in r 2 was attributable to CD27 and KIM-1. However, using the weighted average of historical eGFR gave similar performance to biomarkers. The LC-MS/MS platform performed less well. Conclusions/interpretation Among a large set of associated biomarkers, a sparse panel of just CD27 and KIM-1 contains most of the predictive information for eGFR progression. The increment in prediction beyond clinical data was modest but potentially useful for oversampling individuals with rapid disease progression into clinical trials, especially where there is little information on prior eGFR trajectories. Electronic supplementary material The online version of this article (10.1007/s00125-019-4915-0) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

Ras is one of the most frequently activated oncogenes in cancer. Two mitogen-activated protein kinases (MAPKs) are important for ras transformation: extracellular signal-regulated kinase (ERK) and c-Jun N-terminal kinase 2 (JNK2). Here we present a downstream signal amplification cascade that is critical for ras transformation in murine embryonic fibroblasts. This cascade is coordinated by ERK and JNK2 MAPKs, whose Rasmediated activation leads to the enhanced levels of three oncogenic transcription factors, namely, c-Myc, activating transcription factor 2 (ATF2) and ATF3, all of which are essential for ras transformation. Previous studies show that ERK-mediated serine 62 phosphorylation protects c-Myc from proteasomal degradation. ERK is, however, not alone sufficient to stabilize c-Myc but requires the cooperation of cancerous inhibitor of protein phosphatase 2A (CIP2A), an oncogene that counteracts protein phosphatase 2A-mediated dephosphorylation of c-Myc. Here we show that JNK2 regulates Cip2a transcription via ATF2. ATF2 and c-Myc cooperate to activate the transcription of ATF3. Remarkably, not only ectopic JNK2, but also ectopic ATF2, CIP2A, c-Myc and ATF3 are sufficient to rescue the defective ras transformation of JNK2-deficient cells. Thus, these data identify the key signal converging point of JNK2 and ERK pathways and underline the central role of CIP2A in ras transformation.

Regulation of angiotensin II type 1 receptor (AT1R) has a pathophysiological role in hypertension, atherosclerosis and heart failure. We started from an observation that the 3′-untranslated region (3′-UTR) of AT1R mRNA suppressed AT1R translation. Using affinity purification for the separation of 3′-UTR-binding proteins and mass spectrometry for their identification, we describe glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as an AT1R 3′-UTR-binding protein. RNA electrophoretic mobility shift analysis with purified GAPDH further demonstrated a direct interaction with the 3′-UTR while GAPDH immunoprecipitation confirmed this interaction with endogenous AT1R mRNA. GAPDH-binding site was mapped to 1–100 of 3′-UTR. GAPDH-bound target mRNAs were identified by expression array hybridization. Analysis of secondary structures shared among GAPDH targets led to the identification of a RNA motif rich in adenines and uracils. Silencing of GAPDH increased the expression of both endogenous and transfected AT1R. Similarly, a decrease in GAPDH expression by H2O2 led to an increased level of AT1R expression. Consistent with GAPDH having a central role in H2O2-mediated AT1R regulation, both the deletion of GAPDH-binding site and GAPDH overexpression attenuated the effect of H2O2 on AT1R mRNA. Taken together, GAPDH is a translational suppressor of AT1R and mediates the effect of H2O2 on AT1R mRNA.

Aims/hypothesis This prospective, observational study examines associations between 51 urinary metabolites and risk of progression of diabetic nephropathy in individuals with type 1 diabetes by employing an automated NMR metabolomics technique suitable for large-scale urine sample collections. Methods We collected 24-h urine samples for 2670 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy study and measured metabolite concentrations by NMR. Individuals were followed up for 9.0 ± 5.0 years until their first sign of progression of diabetic nephropathy, end-stage kidney disease or study end. Cox regressions were performed on the entire study population (overall progression), on 1999 individuals with normoalbuminuria and 347 individuals with macroalbuminuria at baseline. Results Seven urinary metabolites were associated with overall progression after adjustment for baseline albuminuria and chronic kidney disease stage (p < 8 × 10−4): leucine (HR 1.47 [95% CI 1.30, 1.66] per 1-SD creatinine-scaled metabolite concentration), valine (1.38 [1.22, 1.56]), isoleucine (1.33 [1.18, 1.50]), pseudouridine (1.25 [1.11, 1.42]), threonine (1.27 [1.11, 1.46]) and citrate (0.84 [0.75, 0.93]). 2-Hydroxyisobutyrate was associated with overall progression (1.30 [1.16, 1.45]) and also progression from normoalbuminuria (1.56 [1.25, 1.95]). Six amino acids and pyroglutamate were associated with progression from macroalbuminuria. Conclusions/interpretation Branched-chain amino acids and other urinary metabolites were associated with the progression of diabetic nephropathy on top of baseline albuminuria and chronic kidney disease. We found differences in associations for overall progression and progression from normo- and macroalbuminuria. These novel discoveries illustrate the utility of analysing urinary metabolites in entire population cohorts. Graphical abstract

Aims/hypothesis Diabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets. Methods We performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets. Results The meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR<60 ml/min per 1.73 m2) and DKD (microalbuminuria or worse) phenotype (p=9.8×10−9; although not withstanding correction for multiple testing, p>9.3×10−9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN–RESP18, GPR158, INIP–SNX30, LSM14A and MFF; p<2.7×10−6). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in individuals with vs without DKD (p=1.1×10−6). The lead SNPs within six loci significantly altered DNA methylation of a nearby CpG site in kidneys (p<1.5×10−11). Expression of lead genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes (e.g. TENM2 expression correlated positively with eGFR [p=1.6×10−8] and negatively with tubulointerstitial fibrosis [p=2.0×10−9], tubular DCLK1 expression correlated positively with fibrosis [p=7.4×10−16], and SNX30 expression correlated positively with eGFR [p=5.8×10−14] and negatively with fibrosis [p<2.0×10−16]). Conclusions/interpretation Altogether, the results point to novel genes contributing to the pathogenesis of DKD. Data availability The GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages (https://t1d.hugeamp.org/downloads.html; https://t2d.hugeamp.org/downloads.html; https://hugeamp.org/downloads.html). Graphical abstract

OBJECTIVEPatients with type 1 diabetes and diabetic nephropathy are targets for intervention to reduce high risk of end-stage renal disease (ESRD) and deaths. This study compares risks of these outcomes in four international cohorts.RESEARCH DESIGN AND METHODSIn the 1990s and early 2000s, Caucasian patients with type 1 diabetes with persistent macroalbuminuria in chronic kidney disease stages 1–3 were identified in the Joslin Clinic (U.S., 432), Finnish Diabetic Nephropathy Study (FinnDiane) (Finland, 486), Steno Diabetes Center Copenhagen (Denmark, 368), and INSERM (France, 232) and were followed for 3–18 years with annual creatinine measurements to ascertain ESRD and deaths unrelated to ESRD.RESULTSDuring 15,685 patient-years, 505 ESRD cases (rate 32/1,000 patient-years) and 228 deaths unrelated to ESRD (rate 14/1,000 patient-years) occurred. Risk of ESRD was associated with male sex; younger age; lower estimated glomerular filtration rate (eGFR); higher albumin/creatinine ratio, HbA1c, and systolic blood pressure; and smoking. Risk of death unrelated to ESRD was associated with older age, smoking, and higher baseline eGFR. In adjusted analysis, ESRD risk was highest in Joslin versus reference FinnDiane (hazard ratio [HR] 1.44, P = 0.003) and lowest in Steno (HR 0.54, P < 0.001). Differences in eGFR slopes paralleled risk of ESRD. Mortality unrelated to ESRD was lowest in Joslin (HR 0.68, P = 0.003 vs. the other cohorts). Competing risk did not explain international differences in the outcomes.CONCLUSIONSDespite almost universal renoprotective treatment, progression to ESRD and mortality in patients with type 1 diabetes with advanced nephropathy are still very high and differ among countries. Finding causes of these differences may help reduce risk of these outcomes.