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Enregistrement W2993833902 · doi:10.1074/mcp.ra119.001785

Profiling the Surfaceome Identifies Therapeutic Targets for Cells with Hyperactive mTORC1 Signaling

2019· article· en· W2993833902 sur OpenAlexfundno aff
Junnian Wei, Kevin Leung, Charles Truillet, Davide Ruggero, James A. Wells, Michael J. Evans

Notice bibliographique

RevueMolecular & Cellular Proteomics · 2019
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiquePI3K/AKT/mTOR signaling in cancer
Établissements canadiensnon disponible
Organismes subventionnairesDOD Prostate Cancer Research ProgramNational Institute of General Medical SciencesUniversity of California, San FranciscoNational Cancer InstituteNational Institutes of HealthCanadian Institutes of Health ResearchAmerican Cancer SocietyFoundation for the National Institutes of HealthU.S. Department of Defense
Mots-clésmTORC1Signal transductionAminopeptidaseBiologyProteomicsCell biologyCancer researchComputational biologyPI3K/AKT/mTOR pathwayGeneGeneticsAmino acidLeucine

Résumé

récupéré en direct d'OpenAlex

Aberrantly high mTORC1 signaling is a known driver of many cancers and human disorders, yet pharmacological inhibition of mTORC1 rarely confers durable clinical responses. To explore alternative therapeutic strategies, herein we conducted a proteomics survey to identify cell surface proteins upregulated by mTORC1. A comparison of the surfaceome from Tsc1−/− versus Tsc1+/+ mouse embryonic fibroblasts revealed 59 proteins predicted to be significantly overexpressed in Tsc1−/− cells. Further validation of the data in multiple mouse and human cell lines showed that mTORC1 signaling most dramatically induced the expression of the proteases neprilysin (NEP/CD10) and aminopeptidase N (APN/CD13). Functional studies showed that constitutive mTORC1 signaling sensitized cells to genetic ablation of NEP and APN, as well as the biochemical inhibition of APN. In summary, these data show that mTORC1 signaling plays a significant role in the constitution of the surfaceome, which in turn may present novel therapeutic strategies. Aberrantly high mTORC1 signaling is a known driver of many cancers and human disorders, yet pharmacological inhibition of mTORC1 rarely confers durable clinical responses. To explore alternative therapeutic strategies, herein we conducted a proteomics survey to identify cell surface proteins upregulated by mTORC1. A comparison of the surfaceome from Tsc1−/− versus Tsc1+/+ mouse embryonic fibroblasts revealed 59 proteins predicted to be significantly overexpressed in Tsc1−/− cells. Further validation of the data in multiple mouse and human cell lines showed that mTORC1 signaling most dramatically induced the expression of the proteases neprilysin (NEP/CD10) and aminopeptidase N (APN/CD13). Functional studies showed that constitutive mTORC1 signaling sensitized cells to genetic ablation of NEP and APN, as well as the biochemical inhibition of APN. In summary, these data show that mTORC1 signaling plays a significant role in the constitution of the surfaceome, which in turn may present novel therapeutic strategies. Because of the importance of mTORC1 to the pathobiology of many cancers and human diseases, there has been longstanding interest in developing therapeutic strategies to inhibit its signaling (1Benjamin D. Colombi M. Moroni C. Hall M.N. Rapamycin passes the torch: a new generation of mTOR inhibitors.Nat. Rev. Drug Discovery. 2011; 10: 868-880Crossref PubMed Scopus (706) Google Scholar). Over 20 years of research has shown that direct pharmacological inhibition of mTORC1 biochemistry with small molecules that disrupt the complex (e.g. rapalogues) or ATP-site directed inhibitors to mTOR generally show encouraging preclinical activity that often does not translate to durable clinical responses. The current state of the art suggests suboptimal clinical responses can reflect cellular adaptation to mTORC1 inhibition through complex feedback mechanisms or dose limiting toxicity (2Chandarlapaty S. Negative feedback and adaptive resistance to the targeted therapy of cancer.Cancer Discovery. 2012; 2: 311-319Crossref PubMed Scopus (150) Google Scholar, 3Zheng Y. Jiang Y. mTOR inhibitors at a glance.Mol. Cell. Pharmacol. 2015; 7: 15-20PubMed Google Scholar). These considerations motivated us to consider molecular profiling studies to probe for other therapeutic strategies. Much of how a cell defines itself and communicates outwardly is dictated by protein expression patterns on the cellular surface. In the case of mTORC1, some evidence already suggests that downstream signaling can alter protein expression at the cell surface. One prominent example is mTORC1 augmentation of glycolysis, which is upregulated in part by elevated GLUT transporter expression on the cell surface via transcriptional activation and vesicle translocation (4Saxton R.A. Sabatini D.M. mTOR signaling in growth, metabolism, and disease.Cell. 2017; 168: 960-976Abstract Full Text Full Text PDF PubMed Scopus (3117) Google Scholar). On this basis, we conducted a global survey of the surfaceome to identify proteins induced by mTORC1 signaling. In designing the proteomics screen, we appreciated that although many genetic lesions within the PI3K/Akt/mTOR signaling axis are known to confer constitutive mTORC1 activity, some events upstream of mTORC1 can activate branching signaling cascades (e.g. PTEN inactivation leading to elevated JNK signaling) (5Vivanco I. Palaskas N. Tran C. Finn S.P. Getz G. Kennedy N.J. Jiao J. Rose J. Xie W. Loda M. Golub T. Mellinghoff I.K. Davis R.J. Wu H. Sawyers C.L. Identification of the JNK signaling pathway as a functional target of the tumor suppressor PTEN.Cancer Cell. 2007; 11: 555-569Abstract Full Text Full Text PDF PubMed Scopus (200) Google Scholar). To steer the proteomic screen toward cell surface events upregulated by mTORC1, we opted to study cell line models isogenic with respect to expression of the TSC1/TSC2 complex. Under normal conditions, TSC1 heterodimerizes with TSC2 to provide protection from ubiquitin mediated degradation (6van Slegtenhorst M. Nellist M. Nagelkerken B. Cheadle J. Snell R. van den Ouweland A. Reuser A. Sampson J. Halley D. van der Sluijs P. Interaction between hamartin and tuberin, the TSC1 and TSC2 gene products.Human Mol. Gen. 1998; 7: 1053-1057Crossref PubMed Scopus (489) Google Scholar), whereas TSC2 employs a GTPase activating protein domain to biochemically convert GTP-Rheb to GDP-Rheb (7Zhang Y. Gao X. Saucedo L.J. Ru B. Edgar B.A. Pan D. Rheb is a direct target of the tuberous sclerosis tumour suppressor proteins.Nat. Cell Biol. 2003; 5: 578-581Crossref PubMed Scopus (715) Google Scholar). As GTP-Rheb is required for the activation of mTORC1, loss of the TSC1/TSC2 complex results in constitutively high mTORC1 signaling. Moreover, somatic or germline genetic mutations that inactivate TSC1 or TSC2 are observed in several deadly cancers (e.g. bladder, kidney) and debilitating human disorders (e.g. tuberous sclerosis complex, focal cortical dysplasia) (8Huang J. Manning B.D. The TSC1-TSC2 complex: a molecular switchboard controlling cell growth.Biochem. J. 2008; 412: 179-190Crossref PubMed Scopus (922) Google Scholar), underscoring the clinical relevance of studying the biology of cell lines lacking a functional TSC1/2 complex. By analyzing the surfaceome of Tsc1−/− versus Tsc1+/+ mouse embryonic fibroblasts (MEFs) 1The abbreviations used are:MEFmouse embryonic fibroblastsNEPneprilysinAPNaminopeptidase NECLenhanced chemiluminescence. 1The abbreviations used are:MEFmouse embryonic fibroblastsNEPneprilysinAPNaminopeptidase NECLenhanced chemiluminescence., we show that mTORC1 upregulates (and downregulates) the expression of many proteins on the cellular surface. Among them, we show that neprilysin (NEP/CD10) and aminopeptidase N (APN/CD13) are highly upregulated by mTORC1 in mouse and human cell lines of diverse lineage. Moreover, the growth of cells with constitutively active mTORC1 is dependent on the expression of NEP and APN, as well as the biochemical activity of APN. These data represent a first step toward defining alternative therapeutic strategies for the treatment of mTORC1 driven diseases. mouse embryonic fibroblasts neprilysin aminopeptidase N enhanced chemiluminescence. mouse embryonic fibroblasts neprilysin aminopeptidase N enhanced chemiluminescence. Tsc1−/− and Tsc1+/+MEFs were kindly provided by Professor David Kwiatkowski, and were maintained in high-glucose and glutamine containing DMEM supplemented with 10% FBS and 1% penicillin-streptomycin. The human bladder cancer cell lines T24, 5637, RT4, HCV29, and TCCSUP were purchased from ATCC (Manassas, VA) and subcultured according to the manufacturer's recommendations. The human thyroid cancer cell line 8505 C was purchased from Sigma-Aldrich (St. Louis, MO) and subcultured according to the manufacturer's recommendations. The bladder cancer cell line 97–1 was kindly provided by Professor Margaret Knowles, and subcultured in Hams F12 supplemented with 1% FBS, 1× penicillin-streptomycin, 1× insulin-transferrin-selenium, 2 mm glutamine, 1× non-essential amino acids (NEAA) and 1 μg/ml hydrocortisone. The cell lysis of human embryonic stem cell isogenic pairs were kindly provided by Prof. Helen Bateup from UC Berkeley. LBQ657 was purchased from Cayman Chemical (Ann Arbor, MI). Bestatin was purchased from Sigma-Aldrich (Morrisville, NC). CHR2797 was purchased from MedKoo Biosciences. GDC0941 was purchased from LC Laboratories (Woburn, MA). BKM120 was purchased from AdipoGen (Irvine, CA). Doxorubicin, MK-2206 and BYL-719 were purchased from Adooq Biosciences. All small molecule drugs were used without further purification. Antibodies to total Akt, p-Akt (S473), total S6, p-S6 (S235/236), total S6K, p-S6K (T389), APN (CD13) for mouse cells were acquired from Cell Signaling Technologies (Danvers, MA) and used at a 1:1000 dilution. APN (CD13) for human cells were acquired from Proteintech (Rosemont, Il) and used at a 1:1000 dilution. Actin (clone AC-15) was purchased from Sigma Aldrich and used at a 1:5000 dilution. The NEP (CD10) antibody was purchased from Invitrogen (Waltham, MA) and used at a 1:1000 dilution. Primary antibodies and their respective sources for flow cytometry are listed in supplemental Table S1. Rheb and Akt plasmids were obtained from Addgene (Watertown, MA) (#13831 and #9008, respectively). Primers for rtPCR were synthesized by Integrated DNA Technologies (Redwood City, CA), and a full list of primer sequences appear in supplemental Table S2. Tsc1+/+ and Tsc1−/− MEFs were cultured in DMEM SILAC media (Thermo MA) containing and (Thermo or and for to full of the on cells. were to and of were at a cell to cell surface cells were with a mm at for 20 to acids of by were with in a mm mm at for were in to and cell were with at for Cell was and with of (Thermo at for The were with high and mm to were with mm at for and with mm at for To we first 20 at to protein The were with high and mm To to the were MA) at for and a were (Thermo and in to 1 of was to a mm mm to a (Thermo The were the of at were in a 20 with of and a that with a of or Full were as data with a of target of of and of were as data with a of target of of with at and of with of for was mouse proteins obtained with a of data was of the from and SILAC were that without be on of at was used to for high and a from was for further and A and for To of the surface with N to were for To the of surface protein of proteins were with not or from and SILAC were and as for Tsc1−/− were were by and a mouse of the the gene from All cell lines were in were with and from cell by in and with the cells were by 1% in at The cells were and with and were in in to a of The antibodies were on the recommendations. were with in and in in One antibodies were and at for the antibodies were were with in and in were on flow Cell were in with and and was in (Thermo with and was with a and of protein of were by to and with and were enhanced and by with the from was with a a to disrupt cell The and of was a and of was to with a high City, CA). in were with a rtPCR (Thermo was the respective and was by to that of were as All were with at and are of at of cells was by the Cell One the treatment cells cells for MEFs and 2 cells for human cancer cell were on and for cell were for with All were with at and are of at containing sequences TSC1 were purchased from the The and the were purchased from To cells were and the was with DMEM media containing 10% and plasmids were in In a was in The containing and were and to a of cells. the media was with of DMEM containing 1% 10% FBS, and The containing media was at with and at The was at or used through a protein bladder cancer cell lines were the for the media was to media containing μg/ml of 2 1 of media was the media was with media which 1 μg/ml by for 2 the were by and the cells were for the sequences we that was with the To mediated gene of TSC1 and TSC2 in the and cell a was the and sequences were used in the for TSC1 in cell lines and and for 11: PubMed Scopus Google Scholar). sequences were used in the for TSC2 in cell and sequences used in the for TSC1 and TSC2 in cell lines and The sequences were with a for the generation of PubMed Scopus Google Scholar). of cells for 2 the cells were to in media to the TSC1/TSC2 via and were purchased from A was used as a were by according to the manufacturer's (Thermo In for a cells were in well and for cell were the of was in cells were by was in were by according to the manufacturer's (Thermo In for a 1 cells were in well and for cell plasmids were in with 20 for and the cells were for of cells was by the of activity and cells were on and for cell were with CHR2797 2 for or All were with at and were APN activity was with a aminopeptidase N activity CA). cells were in of and the was by the of APN by APN was at 20 for at A was to cellular NEP activity a neprilysin activity 1 the NEP and In the data were and a was to the which a of to cell surface The activity was in and All studies were in with and were by the at 97–1 or 8505 C cells in the in a tumor were or CHR2797 was and the dose for the treatment was in 10% were with and the was the of its the were were by for data and by for of data with multiple comparison were significant and in pairs of Tsc1−/− and Tsc1+/+ MEFs were for the proteomics screen as the genetic of TSC1 for a comparison of proteomic of mTORC1 signaling. A SILAC was to to and cell surface M. A for by amino acids in cell PubMed Scopus Google Scholar, B. D. C. R. M. R. R. and of cell surface PubMed Scopus Google Scholar). these are and for high and of surface and SILAC were Tsc1−/− versus Tsc1−/− versus of and in of to cell surface protein The or for protein was and showed proteins were significantly and proteins as significantly in Tsc1−/− versus Tsc1+/+ and supplemental Table upregulated proteins were predicted to a 2 versus with These the and transporter proteins already known to be induced by mTORC1 C. D. of mTORC1 signaling with 2017; PubMed Scopus Google Scholar, T. M.N. J. T. screen of the human signaling the signaling pathway as a of Biol. 2007; PubMed Scopus Google Scholar, C.L. A pathway and transporter J. Cell 2008; PubMed Scopus Google Scholar). To the surface proteins gene was to the proteomics A significant of with focal was a of and gene The proteins on the leading of the focal pathway and is with that the TSC1/TSC2 complex can cellular C. Hall A. The TSC1 tumour suppressor hamartin cell through proteins and the GTPase Cell Biol. 2: PubMed Scopus Google Scholar). not identify significantly gene the proteins predicted to be upregulated in Tsc1−/− used flow cytometry to by the 20 predicted to be upregulated on the surface of Tsc1−/− MEFs by of the were significantly upregulated antibodies The most highly upregulated by flow neprilysin aminopeptidase N the protein 1 and protein supplemental and supplemental Table Because NEP and APN were the upregulated we to studies on these NEP is a dependent that at the amino of In normal cell surface NEP to inactivate their signaling A. J. A in and PubMed Scopus Google Scholar). APN is a dependent that to the of the which can the amino acids from P. The and new to Mol. 2008; Full Text Full Text PDF PubMed Scopus Google Scholar). In normal APN plays a role in the of or the of first NEP and APN were in cell of the isogenic or the expression on the cell surface were by a showed that NEP and APN were in Tsc1−/− versus Tsc1+/+ MEFs to us that the of may be with this of and were significantly in Tsc1−/− with Tsc1+/+ MEFs by rtPCR and supplemental These are by gene expression profiling data S. P. R. S. Manning B.D. of a gene downstream of mTOR complex Cell. Full Text Full Text PDF PubMed Scopus Google Scholar). the we NEP and APN were upregulated by TSC1 or TSC2 loss in mouse and human cell lines of diverse pairs of cells isogenic with respect to TSC1 or TSC2 expression were targeted TSC1 or and elevated mTORC1 signaling was by for NEP and APN expression were observed in the TSC1 or TSC2 cell lines with the motivated us to NEP and APN were by mTORC1 that NEP and APN expression were elevated in cells with of or Rheb the TSC1 or TSC2 cell lines with NEP and APN expression mTORC1 the expression of these proteases downstream of TSC1 or TSC2 NEP and APN expression in cells from human embryonic stem cells with or of TSC1 or TSC2 D. Bateup human cortical models of tuberous PubMed Scopus Google Scholar). showed NEP and APN in the TSC1 and TSC2 cells with the cell line To the between mTORC1 and the proteases in human cancer we to of the human bladder cancer cell line with TSC1 or TSC2 As the with TSC1 or TSC2 elevated total NEP and APN expression with the cell line and Cell surface NEP or APN expression was upregulated in or cells with of TSC1 via with cells we elevated NEP and APN expression in biochemical activity in models with mTORC1. In biochemical showed biochemical activity in the with TSC1 and TSC2 with cells and the TSC1 or TSC2 with NEP and APN activity as these data that NEP and APN is mTORC1 dependent in multiple cell lines of diverse and NEP and APN are in human tumor mutations known to activate mTORC1 signaling. To this we to the data Because TSC1 and TSC2 mutations are the data were (1Benjamin D. Colombi M. Moroni C. Hall M.N. Rapamycin passes the torch: a new generation of mTOR inhibitors.Nat. Rev. Drug Discovery. 2011; 10: 868-880Crossref PubMed Scopus (706) Google activating mutations in or PTEN or mutations in and (2Chandarlapaty S. Negative feedback and adaptive resistance to the targeted therapy of cancer.Cancer Discovery. 2012; 2: 311-319Crossref PubMed Scopus (150) Google other The of NEP and APN were the data cancer As is in NEP and APN were to be in or PTEN mutations for several other cancers showed significant or the which that the of the proteases by mTORC1 is cell or can be driven by other signaling NEP and APN are required for in cells with constitutive mTORC1 signaling. human cancer cell lines with somatic TSC1 mutations were the bladder cancer cell lines 97–1 and the thyroid cancer cell line 8505 C supplemental NEP and APN expression were in cell lines via we the of NEP or APN on with NEP or APN in cell lines at and with treatment with a was via rtPCR To the of the for NEP or APN NEP and APN cell lines cell lines were with the respective were observed at and with cells treatment biochemical inhibition of cellular to first study a APN with enhanced and with that has shown clinical activity in with and cancers for the treatment of and PubMed Scopus Google Scholar, J. D. A. R. M. H. of in with or a 2 Full Text Full Text PDF PubMed Scopus Google Scholar). was not at 1 although a was in cell lines at and the cells with high of the not cellular at or underscoring the importance of and APN inhibition to the and supplemental CHR2797 induced activity, that APN inhibition can to cell treatment of the cell line with the NEP of the not of the cells at or The of CHR2797 in as the growth of 97–1 and 8505 C were by CHR2797 treatment these data show that mTORC1 upregulates cell surface proteins that can be targeted to cell and the of NEP or APN were to or enhanced in cells with elevated mTORC1 ablation of NEP or APN in in cells significantly the of TSC1 and cells and and TSC2 and cells and the data at as a with cells with show that TSC1 and TSC2 are sensitized to NEP or APN with cells In the of the was by and the was to be between the or in cells the were sensitized to treatment with CHR2797 several of for showed that the for growth inhibition in TSC1 and TSC2 cells was significantly the Moreover, cells with CHR2797 at for in in the TSC1 and TSC2 cells with that a for the enhanced of TSC1 and TSC2 cells to APN inhibition be downstream inhibition of mTORC1. were to this as CHR2797 treatment was shown to mTORC1 signaling in human cancer cell and clinical data that cancers TSC1 mutations are sensitized to mTORC1 D. L.J. N. H. J. S. P. J. T. S. G. D. R. A. A. aminopeptidase that to amino in human 2008; PubMed Scopus Google G. H. M. M. C. I. A. A. B. a for 2012; PubMed Scopus Google 97–1 cells with high of CHR2797 on the of mTORC1 in Moreover, cells with CHR2797 and of several pathway inhibitors or in the respective in human TSC1 cell The that CHR2797 does not the of the pathway inhibitors further to us on mTORC1 activity and supplemental isogenic pairs with BKM120 or GDC0941 showed that the TSC1 and TSC2 were to treatment as the which that the enhanced of TSC1 cell lines not be to mTORC1 inhibition and The of this was to new strategies to cells by mTORC1 signaling. A global proteomics survey revealed that mTORC1 significantly the surfaceome to therapeutic NEP and APN. of the proteomics data that NEP and APN by mTORC1 may be a cellular as their by mTORC1 was observed in diverse cell lines of mouse or human studies in the data showed that NEP and APN are upregulated in some cancers with mutations in PTEN with with Functional studies showed that cells with elevated mTORC1 signaling are sensitized to genetic or pharmacological inhibition of APN, and genetic ablation of In summary, this first survey of the cell surface proteomic with mTORC1 signaling at protein that be to the treatment of mTORC1 driven for the the data mTORC1 signaling to the proteins from the proteomics screen is generally of the several APN that we as of APN were shown to be induced by loss of TSC2 in MEFs S. S. Tran Xie J. of and by J. 2011; PubMed Scopus Google Scholar). APN were in MEFs by treatment in the although protein expression were not Moreover, APN were in TSC2 with normal W. J. J. H. H. The of tuberous sclerosis 2017; PubMed Scopus Google Scholar). data that mTORC1 may the expression of NEP and APN through transcriptional as of are by mTORC1. which are in NEP or APN may be several that APN expression is induced by in normal or cell lines via transcriptional activation N. Y. The is a transcriptional target of signaling in 2003; PubMed Scopus Google Scholar, N. is induced by of in Biol. 2003; Full Text Full Text PDF PubMed Scopus Google Scholar). are of APN mTORC1, and mTORC1 to APN APN is well in many human and to its biochemistry to and M. R. P. J. N (CD13) as a target for cancer 2011; PubMed Scopus Google Scholar). data to role for APN in cellular which further its importance as a cancer high of were required to inhibit the treatment data with CHR2797 are encouraging and for to identify and APN we the of CHR2797 to APN within the of this study for at the other for which CHR2797 is a (e.g. aminopeptidase and were not or not appear in the proteomics data D. L.J. N. H. J. S. P. J. T. S. G. D. R. A. A. aminopeptidase that to amino in human 2008; PubMed Scopus Google Scholar). treatment of a with APN not in the of developing and APN we highly and human the of APN C. J. M. G. J. J. S. M. human cancer cells with antibodies to upregulated and PubMed Scopus Google Scholar). are these molecules to APN as well as with for the treatment of mTORC1 cells. The data that mTORC1 NEP expression is as its to mTORC1 signaling is as of Akt NEP is to as a tumor suppressor by a to which PTEN can on the of the M. A. R. D. D. R. D.M. in tumor by direct of with PTEN.Cancer Cell. 5: Full Text Full Text PDF PubMed Scopus Google Scholar). In this be that mTORC1 may NEP to and Akt as part or the feedback D. D. H. J. N. mTOR inhibition upstream signaling and PubMed Scopus Google Scholar). NEP not NEP is required for cellular to already complex this role in NEP has been of as a tumor although data that NEP can tumor and NEP with was to inhibit the of was Y. Jiang J. C. B. J. X. X. R. X. X. and to through of the 2017; PubMed Scopus Google Scholar). NEP can as a tumor driver or suppressor within the cancer as was in cancer models M. A. J. M. is in and cell signaling of cancer cell lines from of tumor Biol. PubMed Scopus Google Scholar). Further studies are to the of NEP in cells with constitutive mTORC1 signaling. from the other from the proteomics data may yet as therapeutic and are as or and the normal expression of the protein a for further of this and further studies are data been to via the and for and Helen Bateup for human cell with

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,110
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,007
Tête enseignante GPT0,224
Écart entre enseignants0,216 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

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Citations14
Publié2019
Routes d'admission1
Résumé présentoui

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Même revueMolecular & Cellular ProteomicsMême sujetPI3K/AKT/mTOR signaling in cancerTravaux en français237 207