“Proteotranscriptomic analysis of advanced colorectal cancer patient derived organoids for drug sensitivity prediction”

BACKGROUND: Patient-derived organoids (PDOs) from advanced colorectal cancer (CRC) patients could be a key platform to predict drug response and discover new biomarkers. We aimed to integrate PDO drug response with multi-omics characterization beyond genomics. METHODS: We generated 29 PDO lines from 22 advanced CRC patients and provided a morphologic, genomic, and transcriptomic characterization. We performed drug sensitivity assays with a panel of both standard and non-standard agents in five long-term cultures, and integrated drug response with a baseline proteomic and transcriptomic characterization by SWATH-MS and RNA-seq analysis, respectively. RESULTS: PDOs were successfully generated from heavily pre-treated patients, including a paired model of advanced MSI high CRC deriving from pre- and post-chemotherapy liver metastasis. Our PDOs faithfully reproduced genomic and phenotypic features of original tissue. Drug panel testing identified differential response among PDOs, particularly to oxaliplatin and palbociclib. Proteotranscriptomic analyses revealed that oxaliplatin non-responder PDOs present enrichment of the t-RNA aminoacylation process and showed a shift towards oxidative phosphorylation pathway dependence, while an exceptional response to palbociclib was detected in a PDO with activation of MYC and enrichment of chaperonin T-complex protein Ring Complex (TRiC), involved in proteome integrity. Proteotranscriptomic data fusion confirmed these results within a highly integrated network of functional processes involved in differential response to drugs. CONCLUSIONS: Our strategy of integrating PDOs drug sensitivity with SWATH-mass spectrometry and RNA-seq allowed us to identify different baseline proteins and gene expression profiles with the potential to predict treatment response/resistance and to help in the development of effective and personalized cancer therapeutics

Integrative immune transcriptomic classification improves patient selection for precision immunotherapy in advanced gastro-oesophageal adenocarcinoma

BACKGROUND: Advanced gastro-oesophageal cancer (GEA) treatment has been improved by the introduction of immune checkpoint inhibitors (CPIs), yet identifying predictive biomarkers remains a priority, particularly in patients with a combined positive score (CPS) < 5, where the benefit is less clear. Our study assesses certain immune microenvironment features related to sensitivity or resistance to CPIs with the aim of implementing a personalised approach across CPS < 5 GEA. DESIGN: Through integrative transcriptomic and clinicopathological analyses, we studied in both a retrospective and a prospective cohort, the immune tumour microenvironment features. We analysed the cell types composing the immune infiltrate highlighting their functional activity. RESULTS: This integrative study allowed the identification of four different groups across our patients. Among them, we identified a cluster whose tumours expressed the most gene signatures related to immunomodulatory pathways and immunotherapy response. These tumours presented an enriched immune infiltrate showing high immune function activity that could potentially achieve the best benefit from CPIs. Finally, our findings were proven in an external CPI-exposed population, where the use of our transcriptomic results combined with CPS helped better identify those patients who could benefit from immunotherapy than using CPS alone (p = 0.043). CONCLUSIONS: This transcriptomic classification could improve precision immunotherapy for GEA

Measurements of Higgs boson production and couplings in diboson final states with the ATLAS detector at the LHC

Measurements are presented of production properties and couplings of the recently discovered Higgs boson using the decays into boson pairs, H →γ γ, H → Z Z∗ →4l and H →W W∗ →lνlν. The results are based on the complete pp collision data sample recorded by the ATLAS experiment at the CERN Large Hadron Collider at centre-of-mass energies of √s = 7 TeV and √s = 8 TeV, corresponding to an integrated luminosity of about 25 fb−1. Evidence for Higgs boson production through vector-boson fusion is reported. Results of combined fits probing Higgs boson couplings to fermions and bosons, as well as anomalous contributions to loop-induced production and decay modes, are presented. All measurements are consistent with expectations for the Standard Model Higgs boson

Standalone vertex finding in the ATLAS muon spectrometer

A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011

Measurement of the top quark-pair production cross section with ATLAS in pp collisions at \sqrt{s}=7\TeV

A measurement of the production cross-section for top quark pairs(\ttbar) in $pp$ collisions at \sqrt{s}=7 \TeV is presented using data recorded with the ATLAS detector at the Large Hadron Collider. Events are selected in two different topologies: single lepton (electron $e$ or muon $\mu$) with large missing transverse energy and at least four jets, and dilepton ($ee$, $\mu\mu$ or $e\mu$) with large missing transverse energy and at least two jets. In a data sample of 2.9 pb-1, 37 candidate events are observed in the single-lepton topology and 9 events in the dilepton topology. The corresponding expected backgrounds from non-\ttbar Standard Model processes are estimated using data-driven methods and determined to be $12.2 \pm 3.9$ events and $2.5 \pm 0.6$ events, respectively. The kinematic properties of the selected events are consistent with SM \ttbar production. The inclusive top quark pair production cross-section is measured to be \sigmattbar=145 \pm 31 ^{+42}_{-27} pb where the first uncertainty is statistical and the second systematic. The measurement agrees with perturbative QCD calculations.Comment: 30 pages plus author list (50 pages total), 9 figures, 11 tables, CERN-PH number and final journal adde

Genetic polymorphisms located in genes related to immune and inflammatory processes are associated with end-stage renal disease: a preliminary study

Background Chronic kidney disease progression has been linked to pro-inflammatory cytokines and markers of inflammation. These markers are also elevated in end-stage renal disease (ESRD), which constitutes a serious public health problem. Objective To investigate whether single nucleotide polymorphisms (SNPs) located in genes related to immune and inflammatory processes, could be associated with ESRD development. Design and methods A retrospective case-control study was carried out on 276 patients with ESRD and 288 control subjects. Forty-eight SNPs were genotyped via SNPlex platform. Logistic regression was used to assess the relationship between each sigle polymorphism and the development of ESRD. Results Four polymorphisms showed association with ESRD: rs1801275 in the interleukin 4 receptor (IL4R) gene (OR: 0.66 (95%CI=0.46-0.95); p=0.025; overdominant model), rs4586 in chemokine (C-C motif) ligand 2 (CCL2) gene (OR: 0.70 (95%CI=0.54-0.90); p=0.005; additive model), rs301640 located in an intergenic binding site for signal transducer and activator of transcription 4 (STAT4) (OR: 1.82 (95%CI=1.17-2.83); p=0.006; additive model) and rs7830 in the nitric oxide synthase 3 (NOS3) gene (OR: 1.31 (95%CI=1.01-1.71); p=0.043; additive model). After adjusting for multiple testing, results lost significance. Conclusion Our preliminary data suggest that four genetic polymorphisms located in genes related to inflammation and immune processes could help to predict the risk of developing ESRD.This work was supported by grants from Instituto de Salud Carlos III (Ref: PI08/0738 and PI11/00245) to SR and Junta de Castilla y Leon (Ref: GRS 234/A/08) to ET. MAJS is supported by a grant from Instituto de Salud Carlos III (CM10/00105).Jimenez-Sousa, MA.; López, E.; Fernandez-Rodriguez, A.; Tamayo, E.; Fernández-Navarro, P.; Segura Roda, L.; Heredia, M.... (2012). Genetic polymorphisms located in genes related to immune and inflammatory processes are associated with end-stage renal disease: a preliminary study. BMC Medical Genetics. 13(58):1-6. https://doi.org/10.1186/1471-2350-13-58S161358Otero A, de Francisco A, Gayoso P, Garcia F: Prevalence of chronic renal disease in Spain: results of the EPIRCE study. Nefrologia. 2010, 30 (1): 78-86.Kottgen A: Genome-wide association studies in nephrology research. Am J Kidney Dis. 2010, 56 (4): 743-758. 10.1053/j.ajkd.2010.05.018.Gansevoort RT, Matsushita K, van der Velde M, Astor BC, Woodward M, Levey AS, Jong PE, Coresh J, de Jong PE, El-Nahas M, et al: Lower estimated GFR and higher albuminuria are associated with adverse kidney outcomes in both general and high-risk populations. A collaborative meta-analysis of general and high-risk population cohorts. Kidney Int. 2011, 80 (1): 93-104. 10.1038/ki.2010.531.Reich HN, Gladman DD, Urowitz MB, Bargman JM, Hladunewich MA, Lou W, Fan SC, Su J, Herzenberg AM, Cattran DC, et al: Persistent proteinuria and dyslipidemia increase the risk of progressive chronic kidney disease in lupus erythematosus. Kidney Int. 2011, 9 (8): 914-920.Rao M, Wong C, Kanetsky P, Girndt M, Stenvinkel P, Reilly M, Raj DS: Cytokine gene polymorphism and progression of renal and cardiovascular diseases. Kidney Int. 2007, 72 (5): 549-556. 10.1038/sj.ki.5002391.Munshi R, Hsu C, Himmelfarb J: Advances in understanding ischemic acute kidney injury. BMC Med. 2011, 9 (1): 11-10.1186/1741-7015-9-11.Kottgen A, Pattaro C, Boger CA, Fuchsberger C, Olden M, Glazer NL, Parsa A, Gao X, Yang Q, Smith AV, et al: New loci associated with kidney function and chronic kidney disease. Nat Genet. 2010, 42 (5): 376-384. 10.1038/ng.568.Chambers JC, Zhang W, Lord GM, van der Harst P, Lawlor DA, Sehmi JS, Gale DP, Wass MN, Ahmadi KR, Bakker SJ, et al: Genetic loci influencing kidney function and chronic kidney disease. Nat Genet. 2010, 42 (5): 373-375. 10.1038/ng.566.Ribases M, Ramos-Quiroga JA, Sanchez-Mora C, Bosch R, Richarte V, Palomar G, Gastaminza X, Bielsa A, Arcos-Burgos M, Muenke M, et al: Contribution of LPHN3 to the genetic susceptibility to ADHD in adulthood: a replication study. Genes Brain Behav. 2010, 10 (2): 149-157.Sole X, Guino E, Valls J, Iniesta R, Moreno V: SNPStats: a web tool for the analysis of association studies. Bioinformatics. 2006, 22 (15): 1928-1929. 10.1093/bioinformatics/btl268.Fried L, Solomon C, Shlipak M, Seliger S, Stehman-Breen C, Bleyer AJ, Chaves P, Furberg C, Kuller L, Newman A: Inflammatory and prothrombotic markers and the progression of renal disease in elderly individuals. J Am Soc Nephrol. 2004, 15 (12): 3184-3191. 10.1097/01.ASN.0000146422.45434.35.Wolkow PP, Niewczas MA, Perkins B, Ficociello LH, Lipinski B, Warram JH, Krolewski AS: Association of urinary inflammatory markers and renal decline in microalbuminuric type 1 diabetics. J Am Soc Nephrol. 2008, 19 (4): 789-797. 10.1681/ASN.2007050556.Nakamura E, Megumi Y, Kobayashi T, Kamoto T, Ishitoya S, Terachi T, Tachibana M, Matsushiro H, Habuchi T, Kakehi Y, et al: Genetic polymorphisms of the interleukin-4 receptor alpha gene are associated with an increasing risk and a poor prognosis of sporadic renal cell carcinoma in a Japanese population. Clin Cancer Res. 2002, 8 (8): 2620-2625.Burgos PI, Causey ZL, Tamhane A, Kelley JM, Brown EE, Hughes LB, Danila MI, van Everdingen A, Conn DL, Jonas BL, et al: Association of IL4R single-nucleotide polymorphisms with rheumatoid nodules in African Americans with rheumatoid arthritis. Arthritis Res Ther. 2010, 12 (3): R75-10.1186/ar2994.Tachdjian R, Mathias C, Al Khatib S, Bryce PJ, Kim HS, Blaeser F, O'Connor BD, Rzymkiewicz D, Chen A, Holtzman MJ, et al: Pathogenicity of a disease-associated human IL-4 receptor allele in experimental asthma. J Exp Med. 2009, 206 (10): 2191-2204. 10.1084/jem.20091480.Zheng G, Wang Y, Xiang SH, Tay YC, Wu H, Watson D, Coombes J, Rangan GK, Alexander SI, Harris DC: DNA vaccination with CCL2 DNA modified by the addition of an adjuvant epitope protects against "nonimmune" toxic renal injury. J Am Soc Nephrol. 2006, 17 (2): 465-474. 10.1681/ASN.2005020164.Kang YS, Lee MH, Song HK, Ko GJ, Kwon OS, Lim TK, Kim SH, Han SY, Han KH, Lee JE, et al: CCR2 antagonism improves insulin resistance, lipid metabolism, and diabetic nephropathy in type 2 diabetic mice. Kidney Int. 2010, 78 (9): 883-894. 10.1038/ki.2010.263.Dai R, Ahmed SA: MicroRNA, a new paradigm for understanding immunoregulation, inflammation, and autoimmune diseases. Transl Res. 2011, 157 (4): 163-179. 10.1016/j.trsl.2011.01.007.Messeguer X, Escudero R, Farre D, Nunez O, Martinez J, Alba MM: PROMO: detection of known transcription regulatory elements using species-tailored searches. Bioinformatics. 2002, 18 (2): 333-334. 10.1093/bioinformatics/18.2.333.Farre D, Roset R, Huerta M, Adsuara JE, Rosello L, Alba MM, Messeguer X: Identification of patterns in biological sequences at the ALGGEN server: PROMO and MALGEN. Nucleic Acids Res. 2003, 31 (13): 3651-3653. 10.1093/nar/gkg605.Wei L, Vahedi G, Sun HW, Watford WT, Takatori H, Ramos HL, Takahashi H, Liang J, Gutierrez-Cruz G, Zang C, et al: Discrete roles of STAT4 and STAT6 transcription factors in tuning epigenetic modifications and transcription during T helper cell differentiation. Immunity. 2010, 32 (6): 840-851. 10.1016/j.immuni.2010.06.003.Nakayama T, Sato W, Kosugi T, Zhang L, Campbell-Thompson M, Yoshimura A, Croker BP, Johnson RJ, Nakagawa T: Endothelial injury due to eNOS deficiency accelerates the progression of chronic renal disease in the mouse. Am J Physiol Renal Physiol. 2009, 296 (2): F317-327.Webber JL, Tooze SA: New insights into the function of Atg9. FEBS Lett. 2010, 584 (7): 1319-1326. 10.1016/j.febslet.2010.01.020.Kullo IJ, Greene MT, Boerwinkle E, Chu J, Turner ST, Kardia SL: Association of polymorphisms in NOS3 with the ankle-brachial index in hypertensive adults. Atherosclerosis. 2008, 196 (2): 905-912. 10.1016/j.atherosclerosis.2007.02.008.Popov AF, Hinz J, Schulz EG, Schmitto JD, Wiese CH, Quintel M, Seipelt R, Schoendube FA: The eNOS 786C/T polymorphism in cardiac surgical patients with cardiopulmonary bypass is associated with renal dysfunction. Eur J Cardiothorac Surg. 2009, 36 (4): 651-656. 10.1016/j.ejcts.2009.04.049.Wang CH, Li F, Hiller S, Kim HS, Maeda N, Smithies O, Takahashi N: A modest decrease in endothelial NOS in mice comparable to that associated with human NOS3 variants exacerbates diabetic nephropathy. Proc Natl Acad Sci U S A. 2011, 108 (5): 2070-2075. 10.1073/pnas.1018766108.Desmet FO, Hamroun D, Lalande M, Collod-Beroud G, Claustres M, Beroud C: Human Splicing Finder: an online bioinformatics tool to predict splicing signals. Nucleic Acids Res. 2009, 37 (9): e67-10.1093/nar/gkp215.Sironi M, Menozzi G, Riva L, Cagliani R, Comi GP, Bresolin N, Giorda R, Pozzoli U: Silencer elements as possible inhibitors of pseudoexon splicing. Nucleic Acids Res. 2004, 32 (5): 1783-1791. 10.1093/nar/gkh341.Perneger TV: What's wrong with Bonferroni adjustments. BMJ. 1998, 316 (7139): 1236-1238. 10.1136/bmj.316.7139.1236.Sterne JA, Davey Smith G: Sifting the evidence-what's wrong with significance tests?. BMJ. 2001, 322 (7280): 226-231. 10.1136/bmj.322.7280.226

Measurement of the top quark pair cross section with ATLAS in pp collisions at √s=7 TeV using final states with an electron or a muon and a hadronically decaying τ lepton

A measurement of the cross section of top quark pair production in proton-proton collisions recorded with the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy of 7 TeV is reported. The data sample used corresponds to an integrated luminosity of 2.05 fb -1. Events with an isolated electron or muon and a τ lepton decaying hadronically are used. In addition, a large missing transverse momentum and two or more energetic jets are required. At least one of the jets must be identified as originating from a b quark. The measured cross section, σtt-=186±13(stat.)±20(syst.)±7(lumi.) pb, is in good agreement with the Standard Model prediction

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal

Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics

A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN