Gene expression profiling identifies IL-13 receptor alpha 2 chain as a therapeutic target in prostate tumor cells overexpressing adrenomedullin

Human adrenomedullin (AM) is a 52 amino acid peptide, which shares homology with the calcitonin gene-related peptide. Overexpression of AM in the prostate carcinoma cell line PC-3 results in growth inhibition with a 20% (for human AM) and 35% (for rat AM) increase in doubling time compared to parental or mock-transfected cells. We demonstrate by gene expression profiling that AM overexpression results in the dysregulation of approximately 100 genes. Examples of such genes include many involved in the formation of the cytoskeleton, cell adhesion and the extracellular matrix, as well as regulators of the cell cycle and apoptosis, cytokines and transcription factors. Several genes related to cell growth arrest, such as GADD45, IGF-BP6 and RUNX-3, are upregulated by AM. Interestingly, interleukin-13 receptor alpha 2 (IL-13R alpha 2) transcripts were significantly increased in clones overexpressing AM, which was confirmed by semiquantitative RT-PCR analysis. In addition, PC-3 cells treated with AM showed an overexpression of IL-13R alpha 2, which was abolished when cells were preincubated with an anti-AM blocking antibody. When PC-3 cells overexpressing AM and the IL-13R alpha 2 were treated with the highly specific IL13-PE38 cytotoxin, which binds to this receptor, a concentration-dependent inhibition of protein synthesis was observed. The IC(50) (concentration of cytotoxin inhibiting protein synthesis by 50%) ranged from 1 to 4 ng/ml. This cytotoxicity was specific as it was neutralized by the excess of IL-13 and confirmed by clonogenic assays. This study describes a novel AM-induced mechanism of tumor sensitization through the upregulation of functional IL-13R alpha 2 chain, an ideal target for the highly specific recombinant chimeric cytotoxin IL13-PE38

Identification of VEGF-regulated genes associated with increased lung metastatic potential: functional involvement of tenascin-C in tumor growth and lung metastasis

Metastasis is the primary cause of death in patients with breast cancer. Overexpression of c-myc in humans correlates with metastases, but transgenic mice only show low rates of micrometastases. We have generated transgenic mice that overexpress both c-myc and vascular endothelial growth factor (VEGF) (Myc/VEGF) in the mammary gland, which develop high rates of pulmonary macrometastases. Gene expression profiling revealed a set of deregulated genes in Myc/VEGF tumors compared to Myc tumors associated with the increased metastatic phenotype. Cross-comparisons between this set of genes with a human breast cancer lung metastasis gene signature identified five common targets: tenascin-C(TNC), matrix metalloprotease-2, collagen-6-A1, mannosidase-alpha-1A and HLA-DPA1. Signaling blockade or knockdown of TNC in MDA-MB-435 cells resulted in a significant impairment of cell migration and anchorage-independent cell proliferation. Mice injected with clonal MDA-MB-435 cells with reduced expression of TNC demonstrated a significant decrease (P<0.05) in (1) primary tumor growth; (2) tumor relapse after surgical removal of the primary tumor and (3) incidence of lung metastasis. Our results demonstrate that VEGF induces complex alterations in tissue architecture and gene expression. The TNC signaling pathway plays an important role in mammary tumor growth and metastases, suggesting that TNC may be a relevant target for therapy against metastatic breast cancer

Fine-Scale Mapping of the 4q24 Locus Identifies Two Independent Loci Associated with Breast Cancer Risk

Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10−4; OR, 1.04; 95% confidence interval (CI), 1.02–1.07] and rs77928427 (P = 1.86 × 10−4; OR, 1.04; 95% CI, 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor–binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Identification of VEGF-regulated genes associated with increased lung metastatic potential: functional involvement of tenascin-C in tumor growth and lung metastasis

Metastasis is the primary cause of death in patients with breast cancer. Overexpression of c-myc in humans correlates with metastases, but transgenic mice only show low rates of micrometastases. We have generated transgenic mice that overexpress both c-myc and vascular endothelial growth factor (VEGF) (Myc/VEGF) in the mammary gland, which develop high rates of pulmonary macrometastases. Gene expression profiling revealed a set of deregulated genes in Myc/VEGF tumors compared to Myc tumors associated with the increased metastatic phenotype. Cross-comparisons between this set of genes with a human breast cancer lung metastasis gene signature identified five common targets: tenascin-C(TNC), matrix metalloprotease-2, collagen-6-A1, mannosidase-alpha-1A and HLA-DPA1. Signaling blockade or knockdown of TNC in MDA-MB-435 cells resulted in a significant impairment of cell migration and anchorage-independent cell proliferation. Mice injected with clonal MDA-MB-435 cells with reduced expression of TNC demonstrated a significant decrease (P<0.05) in (1) primary tumor growth; (2) tumor relapse after surgical removal of the primary tumor and (3) incidence of lung metastasis. Our results demonstrate that VEGF induces complex alterations in tissue architecture and gene expression. The TNC signaling pathway plays an important role in mammary tumor growth and metastases, suggesting that TNC may be a relevant target for therapy against metastatic breast cancer

The Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument

International audienceWe describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4-m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the Universe with the Baryon Acoustic Oscillation technique and the growth rate of structure with Redshift Space Distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near UV to near infrared (3600 to 9800 Angstrom) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline's algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project's requirements for redshift performance, with high efficiency and a purity greater than 99 percent for all target classes

On the Use of Hydrological Models and Satellite Data to Study the Water Budget of River Basins Affected by Human Activities: Examples from the Garonne Basin of France

Natural and anthropogenic forcing factors and their changes significantly impact water resources in many river basins around the world. Information on such changes can be derived from fine scale in situ and satellite observations, used in combination with hydrological models. The latter need to account for hydrological changes caused by human activities to correctly estimate the actual water resource. In this study, we consider the catchment area of the Garonne river (in France) to investigate the capabilities of space-based observations and up-to-date hydrological modeling in estimating water resources of a river basin modified by human activities and a changing climate. Using the ISBA-MODCOU and SWAT hydrological models, we find that the water resources of the Garonne basin display a negative climate trend since 1960. The snow component of the two models is validated using the moderate-resolution imaging spectroradiometer snow cover extent climatology. Crop sowing dates based on remote sensing studies are also considered in the validation procedure. Use of this dataset improves the simulated evapotranspiration and river discharge amounts when compared to conventional data. Finally, we investigate the benefit of using the MAELIA multi-agent model that accounts for a realistic agricultural and management scenario. Among other results, we find that changes in crop systems have significant impacts on water uptake for agriculture. This work constitutes a basis for the construction of a future modeling framework of the sociological and hydrological system of the Garonne river region