Gli autori desiderano ringraziare Moriarity Branden, David Largaespada, e Vincent Keng presso l&#39;Università del Minnesota, e Adam Dupuy presso la University of Iowa per la loro assistenza nello sviluppo del protocollo sopra descritto.

1. Allevamento e invecchiamento di animali transgenici <ol><li> Selezionare i ceppi di topi transgenici appropriate per l&#39;esperimento. Un esperimento tipico utilizza tre linee transgeniche, un topo trasposasi condizionale, un mouse ospitare un concatamer di trasposoni, e un mouse esprimere ricombinasi Cre nelle cellule ritiene siano le cellule di origine per il cancro desiderato. Se il tumore viene modellata ha una mutazione nota in una grande percentuale di pazienti può essere desiderabile includere questa mutazione all&#39;inizio. Esempi di questi &quot;predisponenti&quot; mutazioni includono Kras attivati, TP53 dominanti negativi o un allele Pten floxed. Con l&#39;aggiunta di una mutazione che predispone il modello può rappresentare meglio il cancro umano (cfr. 1.3). Diversi trasposasi Bella Addormentata e topi trasposoni sono disponibili presso il National Cancer Institute del mouse Repository ( <a href="http://mouse.ncifcrf.gov/" target="_blank">http://mouse.ncifcrf.gov/</a> ). </li><li> Razza topi trasposasi condizionale per i topi che ospitano i trasposoni per ottenere alla fine i topi omozigoti per entrambi gli alleli, se possibile. Razza prole omozigote per topi che esprimono Cre ricombinasi per generare le triple topi transgenici sperimentali (Figura 2). Nota: Ottenere topi omozigoti non sono sempre possibili o ideale. Ad esempio, i topi omozigoti p53 dominanti negativi sono molto più difficili da allevare rispetto ai topi eterozigoti. Inoltre, è utile fare in modo che cucciolate seguire genetica mendeliana per confermare che il sistema di allevamento è riuscita. </li><li> Se si utilizza uno sfondo predisposto, i topi con la prima razza trasposasi a topi con l&#39;allele predisponente. Allo stesso tempo, i topi di razza esprimono Cre ricombinasi ai topi che trasportano i trasposoni. Creare topi omozigoti per ciascun allele se possibile. Infine, allevare la prole omozigote dai precedenti due regimi di allevamento per generare quadruple anim transgenico sperimentaleSLA. </li><li> Oltre agli animali da esperimento, generare coorti di topi di controllo. Il gruppo di controllo normalmente consiste di littermates dal allevamento sperimentale che ereditano solo due dei tre alleli (Figura 2). Nel caso di uno sfondo predisposto, topi compresi tre dei quattro alleli sarà anche necessario. </li><li> Monitorare topi sperimentali e di controllo giornalieri per lo sviluppo del tumore e / o agonia. Segui la tua assistenza istituzionale degli animali e uso delle commissioni (IACUC) i requisiti per la zootecnia. Inoltre, è tipico di determinare un&#39;epoca in cui si sacrifica un animale se non è ancora diventata moribonda. Diciotto mesi è un età tipica in cui sono eutanasia topi. </li></ol> 2. Necroscopico di animali transgenici <table border="1"><tbody><tr><td> Nome del reagente </td><td> Azienda </td><td> Numero di catalogo </td></tr><tr><td> Sure-Seal Induczione della Camera </td><td> Cervello Albero scientifico </td><td> EZ-177 </td></tr><tr><td> Provetta Microbank ™ </td><td> Bioexpress </td><td> C-3355-2 </td></tr><tr><td> 10% formalina tamponata </td><td> Sigma Aldrich </td><td> HT501128-4L </td></tr></tbody></table> Reagenti Tabella 1. Richiesta. <ol><li> Quando il mouse è moribondo o ha raggiunto la fine del ciclo di vita determinato, eutanasia animale con un CO 2 camera dopo le vostre linee guida IACUC. In generale, posizionare l&#39;animale in una camera a gas pulito, aprire il serbatoio del gas e regolare il regolatore di leggere non superiore a 5 libbre per pollice quadrato. Riempire lentamente per ridurre al minimo l&#39;irritazione nasale e oculare e l&#39;avversione a CO 2. Assicurarsi che il cuore dell&#39;animale non è più battere e non risponde quando viene toccato negli occhi. </li><li> Esterno Spruzzi di topo sacrificato con il 70% di etanolo. </li><li> Posizionare il mouse su un bordo l&#39;autopsia e fissare con perni dissezione. Usare le forbici und pinzette per aprire il mouse e rimuovere gli organi. Determinare quali organi devono essere raccolti è il progetto dipendente. Tuttavia, si raccomanda di raccogliere sempre la milza e il fegato come questi organi danno spesso informazioni importanti sul perché il mouse era moribonda. Anche raccogliere lo sterno per l&#39;analisi potenziale di midollo osseo. Inoltre, è sempre utile per raccogliere qualsiasi organo o tessuto che appare anomalo. </li><li> I tessuti e tumori che vengono raccolti dovrebbe essere diviso in quattro sezioni. Una sezione è fissato in formalina tamponata al 10% per 18 ore seguito da 70% di etanolo. Questa sezione può essere utilizzata per H &amp; E colorazione e / o IHC. I rimanenti tre sezioni, che sono generalmente 50 a 100 mg di dimensione, sono congelati in azoto liquido. Questi possono essere utilizzati per DNA, RNA e proteine ​​isolamento. </li><li> Smaltire i tessuti della carcassa e rimanenti secondo le linee guida IACUC. </li></ol> 3. Isolamento del DNA genomico da tumori <table border="1"><tbody><tr><td> &lt;&gt; Nome forte del reagente </td><td> Azienda </td><td> Numero di catalogo </td></tr><tr><td> Proteine ​​Precipitazioni soluzione </td><td> Qiagen </td><td> 158910 </td></tr><tr><td> Tampone di lisi cellulare </td><td> Qiagen </td><td> 158906 </td></tr><tr><td> Proteinasi K </td><td> Qiagen </td><td> 158920 </td></tr><tr><td> RNasi A </td><td> Qiagen </td><td> 158924 </td></tr><tr><td> TE Buffer </td><td> Promega </td><td> V6232 </td></tr></tbody></table> Reagenti Tabella 2. Richiesta. <ol><li> Tritare finemente il campione congelato tumorale (da 50 a 100 mg) usando una lama di rasoio pulito. </li><li> Posto tritata tessuto in una provetta da 1,5 ml microcentrifuga e aggiungere 1 ml di tampone di lisi cellulare contenente 5 microlitri soluzione proteinasi K (20 mg / ml). </li><li> Vortex accuratamente. </li><li> Incubare a 55 ° C un agitatore fissato a 250 rpm per almeno 4 ore, preferibilmente durante la notte. </li><li> Aggiungere 1 ml RNasi A soluzione (10 mg / ml) e capovolgere tubo 25 volte. </li><li> Incubare a 37 ° C per 30 min. </li><li> Raffreddare a temperatura ambiente, ponendo in ghiaccio per 3 min. </li><li> Aggiungere 333 microlitri soluzione di precipitazione delle proteine ​​e agitare vigorosamente. </li><li> Centrifugare a 14.000 rpm 10 min. Le proteine ​​dovrebbero pellet. Se pellet è molto piccola, vortice di nuovo, incubare su ghiaccio per 5 min, e quindi ri-centrifuga. </li><li> Decantare il surnatante contenente il DNA in una provetta pulita da 15 ml per centrifuga. </li><li> Aggiungere ugual volume di isopropanolo% 100 e mescolare delicatamente capovolgendo 50 volte. </li><li> Centrifugare a 3500 rpm per 3 min. </li><li> Gettare il surnatante. </li><li> Aggiungere 1 ml di etanolo 70% e invertire tubo più volte per lavare il pellet. </li><li> Trasferire il pellet lavato con l&#39;etanolo in una provetta da 1,5 ml. </li><li> Centrifugare a 14.000 rpm per 5 min a 4 ° C. </li><li> Versare etanolo e invertire tubo di aria secca (circa 5 a 30 minuti). </li><li> Risospendere DNA pEllet in 50-500 microlitri di TE a seconda delle dimensioni del DNA pellet. </li><li> Incubazione opzionale a 37 ° C per risospendere il DNA. </li><li> Conservare a 4 ° C o -20 ° C per una conservazione a lungo termine. </li></ol> 4. Linker Mediated-PCR DNA genomico Utilizzo da tumori <table border="1"><tbody><tr><td> Nome del reagente </td><td> Azienda </td><td> Numero di catalogo </td></tr><tr><td> Bfai </td><td> New England Biolabs </td><td> R0568S </td></tr><tr><td> NlaIII </td><td> New England Biolabs </td><td> R0125S </td></tr><tr><td> MinElute piastre a 96 pozzetti </td><td> Qiagen </td><td> 28051 </td></tr><tr><td> QIAvac 96 collettore sottovuoto </td><td> Qiagen </td><td> 19504 </td></tr><tr><td> Multi-Genie per micropiastre, 120V </td><td> Scientific Industries, Inc. </td><td> SI-4000 </td></tr><tr><td> DNA ligasi T4 con il tampone di legatura 5x </td><td> Invitrogen </td><html><td> 15224-041 </td></tr><tr><td> BamHI </td><td> New England Biolabs </td><td> R0136S </td></tr><tr><td> DNTP 25 mM </td><td> Bioexpress </td><td> C-5014-200 </td></tr><tr><td> Platinum Taq </td><td> Invitrogen </td><td> 10966-034 </td></tr><tr><td> FastStart Taq DNA Polymerase </td><td> Roche </td><td> 12032929001 </td></tr><tr><td> Agarosio </td><td> Promega </td><td> V3121 </td></tr><tr><td> TAE buffer </td><td> Promega </td><td> V4271 </td></tr><tr><td> TE Buffer </td><td> Promega </td><td> V6232 </td></tr><tr><td> Etidio bromuro </td><td> Promega </td><td> H5041 </td></tr></tbody></table> Reagenti Tabella 3. Richiesto. Sequenze del linker Bfai linker + 5 &#39;GTAATACGACTCACTATAGGGCTCCGCTTAAGGGAC 3&#39; Bfai linker-5 &#39;Phos-TAGTCCCTTAAGCGGAG 3&#39;NH2 &quot;&gt; Linker NlaIII 5&#39;GTAATACGACTCACTATAGGGCTCCGCTTAAGGGACCATG + 3 &#39; NlaIII linker-5 &#39;Phos-GTCCCTTAAGCGGAGCC 3&#39; Primer Sequenze Primaria PCR in avanti a destra (NlaIII): Spl IRDR R1 1 GCTTGTGGAAGGCTACTCGAAATGTTTGACCC Primaria PCR in avanti lato sinistro (bfai): Spl IRDR L1 1 CTGGAATTTTCCAAGCTGTTTAAAGGCACAGTCAAC Primaria inversa PCR per il lato destro e sinistro: Spl Link1 1 GTAATACGACTCACTATAGGGC Lato secondario PCR destro avanti: Esempio di un codice a barre Illumina fondo secondario 5 &#39;AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCTNNNNNNNNNNNNaGgtgtatgtaaacttccgacttcaa (Il N rappresentano il 12 bp codice a barre, la sequenza in maiuscolo sono necessari per la piattaforma Illumina, e la sequenza in minuscolo si legherà al trasposone.) Secondaria PCR in avanti lato sinistro: Esempio di una seconda Illumina codice a barredary fondo 5&#39;AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCTNNNNNNNNNNNNaAgtgtatgtaaacttccgacttcaa (Il N rappresentano il 12 bp codice a barre, la sequenza in maiuscolo sono necessari per la piattaforma Illumina, e la sequenza in minuscolo si legherà al trasposone.) Secondaria inversa PCR per il lato destro e sinistro: linker innesco nidificato inverso 5 &#39;CAAGCAGAAGACGGCATACGAGCTCTTCCGATCTAGGGCTCCGCTTAAGGGAC <ol><li> Anneal + e - linkers per entrambe linkers bfai e linker NlaII mescolando 50 pl di linker + (100 pM) con 50 pl di linker-(100 mM) e aggiungere 2 microlitri di NaCl (5 M) in una provetta da 1,5 ml. Posto a 95 ° blocco termico C per 5 min. Disattivare blocco riscaldante e lasciare raffreddare lentamente a temperatura ambiente (questo richiede un&#39;ora o più). Dopo raffreddamento, linkers ricotti possono essere conservati in un congelatore -20 ° C fino al momento dell&#39;uso. </li><li> Preparare due aliquote di DNA tumorale, ciascuna aliquota contenente 1 ug di DNA. Una aliquota sarà digerito spiritoha enzima di restrizione che taglierà vicino alla fine &quot;diritto&quot; del trasposone. La seconda aliquota viene digerito con un enzima di restrizione che taglia vicino alla fine &quot;sinistra&quot; del trasposone. Questo viene fatto per massimizzare le possibilità di amplificare ogni sito di inserzione di trasposoni. </li><li> Digerire il DNA tumorale in un&#39;aliquota utilizzando l&#39;enzima &quot;giusto&quot; NlaII lato, e digerire il DNA tumorale nella parte aliquota prelevata altro utilizzando il lato &quot;sinistro&quot; enzima bfai: unire 1 microlitri di enzima, 5 microlitri di buffer NEB 10x # 4, DNA ( 1 pg) e DDH 2 O ad un volume totale di 50 microlitri. Digest DNA notte a 37 ° C a bagnomaria o incubatore. </li><li> Riscaldare inattivare enzimi (bfai = 80 ° C per 20 min, NlaIII = 65 ° C per 20 min). </li><li> Pulire i campioni digeriti ponendo i campioni in MinElute piastra a 96 pozzetti, piastra posto nel collettore a vuoto e vuoto per circa 15 minuti fino a quando i pozzi aspetto secco. </li><li> Rimuovere la piastra di collettore a vuoto e fondo macchia di piastra a 96 pozzetti con carta assorbente per togliere tutti liquidazioned </li><li> Aggiungere 30 microlitri DDH 2 O a ciascun pozzetto e agitare su un agitatore orbitale impostato su alto per 2 minuti, o pipettare su e giù 20 a 40 volte. </li><li> Trasferimento intero volume in pozzi (30 microlitri) da MinElute piastra a 96 pozzetti in piastre da 96 pozzetti puliti. </li><li> Eseguire reazioni di ligazione del linker con il DNA digerito dal punto 4.8 e leganti a partire dal punto 4.1. Mix 10 microlitri di DNA digerito, 4 microlitri di buffer legatura 5x, 5.5 linker ul ricotto (950 mg / pl), 0,5 microlitri ligasi T4 (5 U / mL). </li><li> Incubare per 4 ore a tutta la notte a 16 ° C. </li><li> Inattivare a caldo la DNA ligasi T4 a 65 ° C per 10 min. </li><li> Pulire legatura con MinElute piastre da 96 pozzetti e un collettore sottovuoto come descritto nei passaggi 4,5-4,6. </li><li> Risospendere in 30 microlitri H 2 O e trasferimento in un ambiente pulito piastra a 96 pozzetti. </li><li> Eseguire una seconda digestione del DNA, al fine di distruggere le rimanenti concatamer trasposoni. Ciò è ottenuto tagliando il DNA una seconda volta usando un enzima che taglia il plasmide vettore DNA che è stato utilizzato per creare i topi transgenici contenenti il ​​concatamer trasposone. </li><li> Digest utilizzando DNA BamHI (lato destro e sinistro): Mix 25 pl di linker-DNA ligato dal passo 4,13, 5 microlitri di buffer NEB 10x # 3, 0,5 microlitri BamHI (20 U / pl), 0,5 microlitri BSA (10 mg / ml ), e 19 microlitri DDH 2 O. </li><li> Digest 3-6 ore o per una notte a 37 ° C. </li><li> Effettuare primaria PCR usando un primer specifico per il trasposone e un primer specifico per il linker. Questi variano a seconda di ciò trasposone e linker in uso. I primer elencati nella tabella sopra innesco di lavoro per l&#39;T2/Onc e T2/Onc2 trasposoni. </li><li> PCR primaria: 5 microlitri di buffer 10x, 2,0 microlitri MgCl2 (50 mM), 4 pl dNTP (2,5 nM), 1 pl Primer 1 (20 pM), 1 pl Primer 2 (20 pM), 0,25 microlitri Platinum Taq (5 U / pl), 3 microlitri di DNA digerito con linkers (importo può variare), fino a 50 pl DDH 2 O. </li><li> Programma di PCR: 94 ° C per 5 min, 30 cicli di 94 ° C per 30 sec, 60 &amp; deg; C per 30 sec, 72 ° C per 90 sec. Estensione finale a 72 ° C per 5 min. </li><li> Ripulire prodotto PCR utilizzando MinElute 96 pozzetti e un collettore di vuoto, come descritto sopra. </li><li> Risospendere in 30 microlitri H 2 O e trasferimento in un ambiente pulito piastra a 96 pozzetti. </li><li> Fai una diluizione 1:75 del 1 ° PCR diluendo 2 microlitri di DNA dal passaggio 4,21 in 148 microlitri DDH 2 O </li><li> Effettuare secondaria PCR annidate usando versioni dei primer che hanno anche la sequenza richiesta per la macchina Illumina GAIIx così come un codice a barre 12 paia di basi che è unico per ciascun campione di tumore trattati (vedi tabella fondo sopra per esempi di questi primer). </li><li> Secondaria PCR: 10 microlitri di buffer 10x con MgCl2, 8 dNTPs ul (2,5 mm), 1 Illumina microlitri codice a barre fondo secondario (20 mM), 1 Nest Illumina pl 1 Primer secondaria (20 mM), 0,25 microlitri FastStart Taq (5 U / mL ), 2 microlitri di DNA da PCR 1:75 primari diluiti, fino a 100 pl DDH 2 O. </li><li> PCR Programma: 94 °; C per 2 min, 30 cicli di 94 ° C per 30 sec, 53 ° C per 45 sec, 72 ° C per 90 sec. Estensione finale a 72 ° C per 5 min. </li><li> Eseguire 45 pl di questa reazione PCR su un gel di agarosio 1% contenente etidio bromuro (0,5 mcg / ml). Ci dovrebbe essere una &quot;macchia&quot; di prodotti che rappresentano PCR amplificati delle alte inserzioni di trasposoni diversi nel tumore (Figura 3). </li><li> Pulire restante 50 pl di prodotto di PCR utilizzando MinElute 96 pozzetti e un collettore di vuoto come descritto sopra. Lavare una volta mettendo 50 microlitri DDH 2 O nei pozzetti e aspirare di nuovo. </li><li> Risospendere in 30 microlitri TE e trasferimento in un ambiente pulito piastra a 96 pozzetti. </li><li> Determinare la concentrazione di DNA in ciascun campione. Combina la stessa quantità di DNA in una singola provetta da microcentrifuga 1,5 ml. Questa sarà la libreria che è in sequenza in una sola corsia di un Illumina HiSeq 2000 macchina. È possibile sequenziare diverse centinaia tumori in una singola corsia di corsa Illumina. </li><li> Presentarel&#39;unico tubo contenente la stessa quantità di DNA da tutti i tumori per sequenziamento. Questo può essere fatto con l&#39;istituto o per finalità commerciali. </li></ol> 5. Analisi di inserimenti trasposone <ol><li> Software per l&#39;analisi dei trasposoni inserimento dei dati è disponibile per il download gratuito attraverso SourceForge ( <a href="http://sourceforge.net/projects/tapdancebio/" target="_blank">http://sourceforge.net/projects/tapdancebio/</a> ). Il programma, chiamato TapDance, richiede il file di sequenza dalla piattaforma Illumina e un codice a barre in un file di testo la mappa della libreria. </li></ol>

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Viene visualizzata una schermata in avanti genetica utilizzando il sistema di Sleeping Beauty trasposone fornisce un metodo per identificare le mutazioni che causano il cancro. Selezionando il promotore appropriato controllare ricombinasi Cre in aggiunta a qualsiasi mutazioni predisponenti, lo schermo SB identificherà noti e nuovi geni del cancro candidati. Il successo di uno schermo SB dipende in larga misura i topi selezionati per creare lo schermo. Per il trasposone, si...

<table border="1"><tbody><tr><td> Nome del reagente </td><td> Azienda </td><td> Numero di catalogo </td><td> Commenti (opzionale) </td></tr><tr><td> Sure-Seal induzione Camera </td><td> Cervello Albero scientifico </td><td> EZ-177 </td><td></td></tr><tr><td> Provetta Microbank ™ </td><td> Bioexpress </td><td> C-3355-2 </td><td></td></tr><tr><td> 10% formalina tamponata </td><td> Sigma Aldrich </td><td> HT501128-4L </td><td></td></tr><tr><td> Proteine ​​Precipitazioni soluzione </td><td> Qiagen </td><td> 158910 </td><td></td></tr><tr><td> Tampone di lisi cellulare </td><td> Qiagen </td><td> 158906 </td><td></td></tr><tr><td> Proteinasi K </td><td> Qiagen </td><td> 158920 </td><td></td></tr><tr><td> RNasi A </td><td> Qiagen </td><td> 158924 </td><td></td></tr><tr><td> TE Buffer </td> &lt;td&gt; Promega </td><td> V6232 </td><td></td></tr><tr><td> Bfai </td><td> New England Biolabs </td><td> R0568S </td><td></td></tr><tr><td> NlaIII </td><td> New England Biolabs </td><td> R0125S </td><td></td></tr><tr><td> MinElute piastre a 96 pozzetti </td><td> Qiagen </td><td> 28051 </td><td></td></tr><tr><td> QIAvac 96 collettore sottovuoto </td><td> Qiagen </td><td> 19504 </td><td></td></tr><tr><td> Multi-Genie per micropiastre, 120V </td><td> Scientific Industries, Inc. </td><td> SI-4000 </td><td></td></tr><tr><td> DNA ligasi T4 con il tampone di legatura 5x </td><td> Invitrogen </td><td> 15224-041 </td><td></td></tr><tr><td> BamHI </td><td> New England Biolabs </td><td> R0136S </td><td></td></tr><tr><td> DNTP 25MM </td><td> Bioexpress </td><td> C-5014-200 </td><td></td></tr><tr><td> Platinum Taq </td><td> Invitrogen </td><td&gt; 10966-034 </td><td></td></tr><tr><td> FastStart Taq DNA Polymerase </td><td> Roche </td><td> 12032929001 </td><td></td></tr><tr><td> Agarosio </td><td> Promega </td><td> V3121 </td><td></td></tr><tr><td> TAE buffer </td><td> Promega </td><td> V4271 </td><td></td></tr><tr><td> TE Buffer </td><td> Promega </td><td> V6232 </td><td></td></tr><tr><td> Etidio bromuro </td><td> Promega </td><td> H5041 </td><td></td></tr></tbody></table>

identification of sleeping beauty transposon insertions in solid tumors using linker-mediated pcr

Genomiche, analisi proteomica, trascrittomica e epigenomic di tumori umani indicano che ci sono migliaia di anomalie all&#39;interno di ogni genoma del cancro rispetto al corrispondente tessuto normale. Sulla base di queste analisi è evidente che ci sono molti piloti sconosciute genetiche del cancro 1. Purtroppo questi driver sono nascoste all&#39;interno di un numero molto maggiore di passeggeri anomalie nel genoma che non contribuiscono direttamente alla formazione del tumore. Un altro aspetto del genoma del cancro è che vi è una notevole eterogeneità genetica all&#39;interno simili tipi di tumore. Ogni tumore può ospitare differenti mutazioni che forniscono un vantaggio selettivo per la formazione del tumore 2. Esecuzione di un imparziale schermo in avanti genetica nei topi fornisce gli strumenti per generare tumori e analizzare la loro composizione genetica, riducendo lo sfondo di mutazioni passeggeri. La bella addormentata (SB) trasposoni sistema è uno di questi metodi 3. Il sistema utilizza Mobile V SBettori (trasposoni) che possono essere inseriti nel genoma dall&#39;enzima trasposasi. Mutazioni sono limitati a un tipo specifico di cellula attraverso l&#39;uso di un allele trasposasi condizionale che viene attivato da ricombinasi Cre. Esistono molte linee di topi che esprimono ricombinasi Cre in tessuti specifici. Attraversando una di queste linee per l&#39;allele trasposasi condizionale (ad es Lox-stop-Lox-SB11), il sistema SB si attiva solo nelle cellule che esprimono Cre ricombinasi. La ricombinasi Cre sarà accise una cassetta di arresto che blocca l&#39;espressione dell&#39;allele trasposasi, attivando così mutagenesi trasposone nel tipo di cellula designato. Uno schermo SB è avviata da allevando tre ceppi di topi transgenici in modo che i topi sperimentali portano un allele condizionale trasposasi, un concatamer dei trasposoni, e un tessuto-specifico allele ricombinasi Cre. Questi topi sono lasciati maturare fino a formare tumori e diventano moribondo. I topi sono poiDNA genomico necroscopia ed è isolato dai tumori. Successivamente, il DNA genomico è sottoposto a linker-mediata-PCR (LM-PCR) che si traduce in amplificazione di loci genomici contenenti un trasposone SB. LM-PCR eseguita su un singolo tumore provocherà centinaia di ampliconi distinti rappresentano le centinaia di loci genomici contenenti inserzioni di trasposoni in un 4 singolo tumore. Le inserzioni di trasposoni in tutti i tumori vengono analizzati e siti di inserzione comuni (Ciss) sono identificati con un adeguato metodo statistico 5. I geni all&#39;interno del CIS sono altamente probabile che sia oncogeni o geni oncosoppressori, e sono considerati i geni del cancro candidati. I vantaggi di usare il sistema SB per identificare geni tumorali candidati sono: 1) il trasposone può essere facilmente collocato nel genoma perché la sua sequenza è nota, 2) trasposizione può essere diretto a qualsiasi tipo di cellula e 3) il trasposone è in grado di sia l&#39;introduzione di guadagno e perdita-di-funzione mutazioni 6. Il following protocollo descrive il modo di concepire ed eseguire una schermata in avanti genetica utilizzando il sistema SB trasposoni per identificare i geni del cancro candidati (Figura 1).

Dopo che il sistema di allevamento è stata stabilita, gli allevatori devono produrre una cucciolata ogni 19-21 giorni. Dimensione cucciolata variano tra 5 e 12 cuccioli, a seconda dell&#39;età degli allevatori e il background genetico. Inoltre, assicurarsi che il genotipo della cucciolata segue la genetica mendeliana come un modo per confermare che il sistema di allevamento è sia corretto e di successo. Per l&#39;esperimento abbia successo, dell&#39;incidenza di tumori negli animali da es...

Watch this Scientific Journal Video about Identification of Sleeping Beauty Transposon Insertions in Solid Tumors using Linker-mediated PCR at JoVE.com

Identification of Sleeping Beauty Transposon Insertions in Solid Tumors using Linker-mediated PCR

Un metodo di identificazione conducenti sconosciuti di carcinogenesi utilizzando un approccio imparziale è descritto. Il metodo utilizza l&#39;<em&gt; Bella Addormentata</em&gt; Trasposone come mutageno casuale diretto a tessuti specifici. Mappatura genomica di inserzioni di trasposoni che guidano la formazione del tumore identifica nuovi oncogeni e geni oncosoppressori

Identificazione dei<em&gt; Bella Addormentata</em&gt; Inserimenti trasposone nei tumori solidi utilizzando Linker-mediata PCR

Genomic, proteomic, transcriptomic, and epigenomic analyses of human tumors indicate that there are thousands of anomalies within each cancer genome ...

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Research

JoVE Journal

Medicine

Identification of Sleeping Beauty Transposon Insertions in Solid Tumors using Linker-mediated PCR

14.0K Views.  University of Minnesota, Minneapolis. Un metodo di identificazione conducenti sconosciuti di carcinogenesi utilizzando un approccio imparziale è descritto. Il metodo utilizza l' Bella Addormentata Trasposone come mutageno casuale diretto a tessuti specifici. Mappatura genomica di inserzioni di trasposoni che guidano la formazione del tumore identifica nuovi oncogeni e geni oncosoppressori

Video: Identification of Sleeping Beauty Transposon Insertions in Solid Tumors using Linker-mediated PCR

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor1,2, and some of these sub-clones give rise to metastatic (and therefore lethal) disease. 
Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension3, or on macrodissection4. A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue5, providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi-quantitative and subject to intra- and inter-observer bias, more sensitive and quantitative methodologies are required in order to accurately map and quantify tissue heterogeneity in situ.
We have developed and applied an experimental and statistical methodology in order to systematically quantify the heterogeneity of protein expression in whole tissue sections of tumors, based on the Automated QUantitative Analysis (AQUA) system6. Tissue sections are labeled with specific antibodies directed against cytokeratins and targets of interest, coupled to fluorophore-labeled secondary antibodies. Slides are imaged using a whole-slide fluorescence scanner. Images are subdivided into hundreds to thousands of tiles, and each tile is then assigned an AQUA score which is a measure of protein concentration within the epithelial (tumor) component of the tissue. Heatmaps are generated to represent tissue expression of the proteins and a heterogeneity score assigned, using a statistical measure of heterogeneity originally used in ecology, based on the Simpson's biodiversity index7.
To date there have been no attempts to systematically map and quantify this variability in tandem with protein expression, in histological preparations. Here, we illustrate the first use of the method applied to ER and HER2 biomarker expression in ovarian cancer. Using this method paves the way for analyzing heterogeneity as an independent variable in studies of biomarker expression in translational studies, in order to establish the significance of heterogeneity in prognosis and prediction of responses to therapy.

Here we describe a method to quantify molecular heterogeneity in histological sections of tumor material using quantitative immunofluorescence, image analysis, and a statistical measure of heterogeneity. The method is intended for use in clinical biomarker development and analysis.

Mappatura eterogeneità di espressione delle proteine ​​nei tumori mediante immunofluorescenza quantitativa

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of ...

Ricerca

Medicina

MicroRNA Detection in Prostate Tumors by Quantitative Real-time PCR (qPCR)

MicroRNAs (miRNAs) are single-stranded, 18&#x2013;24 nucleotide long, non-coding RNA molecules. They are involved in virtually every cellular process including development1, apoptosis2, and cell cycle regulation3. MiRNAs are estimated to regulate the expression of 30% to 90% of human genes4 by binding to their target messenger RNAs (mRNAs)5. Widespread dysregulation of miRNAs has been reported in various diseases and cancer subtypes6. Due to their prevalence and unique structure, these small molecules are likely to be the next generation of biomarkers, therapeutic agents and/or targets.
Methods used to investigate miRNA expression include SYBR green I dye- based as well as Taqman-probe based qPCR. If miRNAs are to be effectively used in the clinical setting, it is imperative that their detection in fresh and/or archived clinical samples be accurate, reproducible, and specific. qPCR has been widely used for validating expression of miRNAs in whole genome analyses such as microarray studies7. The samples used in this protocol were from patients who underwent radical prostatectomy for clinically localized prostate cancer; however other tissues and cell lines can be substituted in. Prostate specimens were snap-frozen in liquid nitrogen after resection. Clinical variables and follow-up information for each patient were collected for subsequent analysis8.
Quantification of miRNA levels in prostate tumor samples. The main steps in qPCR analysis of tumors are: Total RNA extraction, cDNA synthesis, and detection of qPCR products using miRNA-specific primers. Total RNA, which includes mRNA, miRNA, and other small RNAs were extracted from specimens using TRIzol reagent. Qiagen's miScript System was used to synthesize cDNA and perform qPCR (Figure 1). Endogenous miRNAs are not polyadenylated, therefore during the reverse transcription process, a poly(A) polymerase polyadenylates the miRNA. The miRNA is used as a template to synthesize cDNA using oligo-dT and Reverse Transcriptase. A universal tag sequence on the 5' end of oligo-dT primers facilitates the amplification of cDNA in the PCR step. PCR product amplification is detected by the level of fluorescence emitted by SYBR Green, a dye which intercalates into double stranded DNA. Specific miRNA primers, along with a Universal Primer that binds to the universal tag sequence will amplify specific miRNA sequences. 
The miScript Primer Assays are available for over a thousand human-specific miRNAs, and hundreds of murine-specific miRNAs. Relative quantification method was used here to quantify the expression of miRNAs. To correct for variability amongst different samples, expression levels of a target miRNA is normalized to the expression levels of a reference gene. The choice of a gene on which to normalize the expression of targets is critical in relative quantification method of analysis. Examples of reference genes typically used in this capacity are the small RNAs RNU6B, RNU44, and RNU48 as they are considered to be stably expressed across most samples. In this protocol, RNU6B is used as the reference gene.

MicroRNA Detection in Prostate Tumors by Quantitative Real-time PCR qPCR

Quantitative Real Time polymerase chain reaction (qPCR) is a rapid and sensitive method to investigate the expression levels of various microRNA (miRNA) molecules in tumor samples. Using this method expression of hundreds of different miRNA molecules can be amplified, quantified, and analyzed from the same cDNA template.

Rilevamento MicroRNA in tumori della prostata dal Quantitative Real-time PCR (qPCR)

MicroRNAs (miRNAs) are single-stranded, 18&#x2013;24 nucleotide long, non-coding RNA molecules. They are involved in virtually every cellular process ...

In vitro Organoid Culture of Primary Mouse Colon Tumors

Several human and murine colon cancer cell lines have been established, physiologic integrity of colon tumors such as multiple cell layers, basal-apical polarity, ability to differentiate, and anoikis are not maintained in colon cancer derived cell lines. The present study demonstrates a method for culturing primary mouse colon tumor organoids adapted from Sato T et al. 1, which retains important physiologic features of colon tumors. This method consists of mouse colon tumor tissue collection, adjacent normal colon epithelium dissociation, colon tumor cells digestion into single cells, embedding colon tumor cells into matrigel, and selective culture based on the principle that tumor cells maintain growth on limiting nutrient conditions compared to normal epithelial cells.
The primary tumor organoids if isolated from genetically modified mice provide a very useful system to assess tumor autonomous function of specific genes. Moreover, the tumor organoids are amenable to genetic manipulation by virus meditated gene delivery; therefore signaling pathways involved in the colon tumorigenesis could also be extensively investigated by overexpression or knockdown. Primary tumor organoids culture provides a physiologic relevant and feasible means to study the mechanisms and therapeutic modalities for colon tumorigenesis.

In vitro Organoid Culture of Primary Mouse Colon Tumors

A simple method to establish primary murine colon tumor organoid is described. This method utilizes the feature that colon tumor cells survive and grow into organoids in media containing limited growth factors, whereas normal colon epithelial do not.

In vitro organoide Cultura di primari tumori del colon mouse

Several  human and murine colon cancer cell lines have been established, physiologic  integrity of colon tumors such as multiple cell layers, basal-apical ...

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.

Multivariate techniques including principal component analysis (PCA) have been used to identify signature patterns of regional change in functional brain images. We have developed an algorithm to identify reproducible network biomarkers for the diagnosis of neurodegenerative disorders, assessment of disease progression, and objective evaluation of treatment effects in patient populations.

Identificazione delle malattie legate Patterns covarianza spaziale utilizzando i dati Neuroimmagine

The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain ...

Flexible Colonoscopy in Mice to Evaluate the Severity of Colitis and Colorectal Tumors Using a Validated Endoscopic Scoring System

The use of modern endoscopy for research purposes has greatly facilitated our understanding of gastrointestinal pathologies. In particular, experimental endoscopy has been highly useful for studies that require repeated assessments in a single laboratory animal, such as those evaluating mechanisms of chronic inflammatory bowel disease and the progression of colorectal cancer. However, the methods used across studies are highly variable. At least three endoscopic scoring systems have been published for murine colitis and published protocols for the assessment of colorectal tumors fail to address the presence of concomitant colonic inflammation. This study develops and validates a reproducible endoscopic scoring system that integrates evaluation of both inflammation and tumors simultaneously. This novel scoring system has three major components: 1) assessment of the extent and severity of colorectal inflammation (based on perianal findings, transparency of the wall, mucosal bleeding, and focal lesions), 2) quantitative recording of tumor lesions (grid map and bar graph), and 3) numerical sorting of clinical cases by their pathological and research relevance based on decimal units with assigned categories of observed lesions and endoscopic complications (decimal identifiers). The video and manuscript presented herein were prepared, following IACUC-approved protocols, to allow investigators to score their own experimental mice using a well-validated and highly reproducible endoscopic methodology, with the system option to differentiate distal from proximal endoscopic colitis (D-PECS).

Over the past few years, new generation endoscopes have emerged as important diagnostic research aids for evaluating murine colitis and colorectal tumors. We present herein a detailed protocol for endoscopic assessment of inflammation and colorectal tumors in mice, as well as a novel scoring system that uses decimal identifiers to document the endoscopic severity of colitis and colorectal tumors.

La colonscopia flessibile in topi per valutare la gravità della colite e colon-retto Tumori Utilizzo di un sistema Validated endoscopica Scoring

The use of modern endoscopy for research purposes has greatly facilitated our understanding of gastrointestinal pathologies. In particular, experimental ...

Cerebrospinal Fluid MicroRNA Profiling Using Quantitative Real Time PCR

MicroRNAs (miRNAs) constitute a potent layer of gene regulation by guiding RISC to target sites located on mRNAs and, consequently, by modulating their translational repression. Changes in miRNA expression have been shown to be involved in the development of all major complex diseases. Furthermore, recent findings showed that miRNAs can be secreted to the extracellular environment and enter the bloodstream and other body fluids where they can circulate with high stability. The function of such circulating miRNAs remains largely elusive, but systematic high throughput approaches, such as miRNA profiling arrays, have lead to the identification of miRNA signatures in several pathological conditions, including neurodegenerative disorders and several types of cancers. In this context, the identification of miRNA expression profile in the cerebrospinal fluid, as reported in our recent study, makes miRNAs attractive candidates for biomarker analysis.
There are several tools available for profiling microRNAs, such as microarrays, quantitative real-time PCR (qPCR), and deep sequencing. Here, we describe a sensitive method to profile microRNAs in cerebrospinal fluids by quantitative real-time PCR. We used the Exiqon microRNA ready-to-use PCR human panels I and II V2.R, which allows detection of 742 unique human microRNAs. We performed the arrays in triplicate runs and we processed and analyzed data using the GenEx Professional 5 software.
Using this protocol, we have successfully profiled microRNAs in various types of cell lines and primary cells, CSF, plasma, and formalin-fixed paraffin-embedded tissues.

We describe a protocol of real time PCR to profile microRNAs in the cerebrospinal fluid (CSF). With the exception of RNA extraction protocols, the procedure can be extended to RNA extracted from other body fluids, cultured cells, or tissue specimens.

Liquido cerebrospinale MicroRNA profiling Utilizzando quantitativa Real Time PCR

MicroRNAs (miRNAs) constitute a potent layer of gene regulation by guiding RISC to target sites located on mRNAs and, consequently, by modulating their ...

In Vivo Optical Imaging of Brain Tumors and Arthritis Using Fluorescent SapC-DOPS Nanovesicles

We describe a multi-angle rotational optical imaging (MAROI) system for in vivo monitoring of physiopathological processes labeled with a fluorescent marker. Mouse models (brain tumor and arthritis) were used to evaluate the usefulness of this method. Saposin C (SapC)-dioleoylphosphatidylserine (DOPS) nanovesicles tagged with CellVue Maroon (CVM) fluorophore were administered intravenously. Animals were then placed in the rotational holder (MARS) of the in vivo imaging system. Images were acquired in 10&#176; steps over 380&#176;. A rectangular&#160;region of interest (ROI) was placed across the full image width at the model disease site. Within the ROI, and for every image, mean fluorescence intensity was computed after background subtraction. In the mouse models studied, the labeled nanovesicles were taken up in both the orthotopic and transgenic brain tumors, and in the arthritic sites (toes and ankles). Curve analysis of the multi angle image ROIs determined the angle with the highest signal. Thus, the optimal angle for imaging each disease site was characterized. The MAROI method applied to imaging of fluorescent compounds is a noninvasive, economical, and precise tool for in vivo quantitative analysis of the disease states in the described mouse models.

In Vivo Optical Imaging of Brain Tumors and Arthritis Using Fluorescent SapC-DOPS Nanovesicles

We describe a multi-angle rotational optical imaging (MAROI) system for in vivo quantitation of a fluorescent marker delivered by saposin C (SapC)-dioleoylphosphatidylserine (DOPS) nanovesicles. Employing mouse models of cancer and arthritis, we demonstrate how the MAROI signal curve analysis can be used for the precise mapping and biological characterization of disease processes.

In Vivo Imaging ottico dei tumori cerebrali e artrite Uso fluorescente SAPC-DOPS nanovesicles

We describe a multi-angle rotational optical imaging (MAROI) system for in vivo monitoring of physiopathological processes labeled with a fluorescent ...

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

In-depth analyses of cancer cell proteomes are needed to elucidate oncogenic pathomechanisms, as well as to identify potential drug targets and diagnostic biomarkers. However, methods for quantitative proteomic characterization of patient-derived tumors and in particular their cellular subpopulations are largely lacking. Here we describe an experimental set-up that allows quantitative analysis of proteomes of cancer cell subpopulations derived from either liquid or solid tumors. This is achieved by combining cellular enrichment strategies with quantitative Super-SILAC-based mass spectrometry followed by bioinformatic data analysis. To enrich specific cellular subsets, liquid tumors are first immunophenotyped by flow cytometry followed by FACS-sorting; for solid tumors, laser-capture microdissection is used to purify specific cellular subpopulations. In a second step, proteins are extracted from the purified cells and subsequently combined with a tumor-specific, SILAC-labeled spike-in standard that enables protein quantification. The resulting protein mixture is subjected to either gel electrophoresis or Filter Aided Sample Preparation (FASP) followed by tryptic digestion. Finally, tryptic peptides are analyzed using a hybrid quadrupole-orbitrap mass spectrometer, and the data obtained are processed with bioinformatic software suites including MaxQuant. By means of the workflow presented here, up to 8,000 proteins can be identified and quantified in patient-derived samples, and the resulting protein expression profiles can be compared among patients to identify diagnostic proteomic signatures or potential drug targets.

In-depth analyses of cancer cell proteomes facilitate identification of novel drug targets and diagnostic biomarkers. We describe an experimental workflow for quantitative analysis of (phospho-)proteomes in cancer cell subpopulations derived from liquid and solid tumors. This is achieved by combining cellular enrichment strategies with quantitative Super-SILAC-based mass spectrometry.

Mass quantitativa spettrometrica Profiling di proteomi cancro-cellulari derivate da liquido e tumori solidi

In-depth analyses of cancer cell proteomes are needed to elucidate oncogenic pathomechanisms, as well as to identify potential drug targets and diagnostic ...

Spatial Measurements of Perfusion, Interstitial Fluid Pressure and Liposomes Accumulation in Solid Tumors

The heterogeneous intra-tumoral accumulation of liposomes is a critical determinant of their efficacy. Both the chaotic tumor microcirculation and elevated IFP are linked to the heterogeneous intra-tumoral distribution of nanotechnology-based drug delivery systems such as liposomes. In the present study, the relationship between tumor microcirculation, elevated IFP, and accumulation of nanoparticles was investigated through in vivo experimentation. This was accomplished by evaluation of the tumor microcirculation using dynamic contrast enhanced computed tomography (DCE-CT) and measurement of tumor IFP using a novel image-guided robotic needle placement system connected to the micro-CT scanner. The intra-tumoral accumulation of liposomes was determined by CT image-based assessment of a nanoparticle liposomal formulation that stably encapsulate the contrast agent iohexol (CT-liposomes). CT imaging allowed for co-localization of the spatial distribution of tumor hemodynamics, IFP and CT-liposome accumulation in an individual subcutaneous xenograft mouse model of breast cancer. Measurements led to the discovery that perfusion and plasma volume fraction are strong mediators of the intra-tumoral distribution of liposomes. Furthermore, the results suggest that IFP plays an indirect role in mediating liposome distribution through modulating blood flow.

The heterogeneous intra-tumoral accumulation of liposomes has been linked to an abnormal tumor microenvironment. Herein methods are presented to measure tumor microcirculation by perfusion imaging and elevated interstitial fluid pressure (IFP) using an image-guided robotic system. Measurements are compared to the intra-tumoral accumulation of liposomes, determined using volumetric micro-CT imaging.

Le misurazioni spaziali di perfusione, interstiziale pressione del fluido e liposomi accumulo nei tumori solidi

The heterogeneous intra-tumoral accumulation of liposomes is a critical determinant of their efficacy. Both the chaotic tumor microcirculation and ...

Multicolor 3D Printing of Complex Intracranial Tumors in Neurosurgery

Three-dimensional (3D) printing technologies offer the possibility of visualizing patient-specific pathologies in a physical model of correct dimensions. The model can be used for planning and simulating critical steps of a surgical approach. Therefore, it is important that anatomical structures such as blood vessels inside a tumor can be printed to be colored not only on their surface, but throughout their whole volume. During simulation this allows for the removal of certain parts (e.g., with a high-speed drill) and revealing internally located structures of a different color. Thus, diagnostic information from various imaging modalities (e.g., CT, MRI) can be combined in a single compact and tangible object.
However, preparation and printing of such a fully colored anatomical model remains a difficult task. Therefore, a step-by-step guide is provided, demonstrating the fusion of different cross-sectional imaging data sets, segmentation of anatomical structures, and creation of a virtual model. In a second step the virtual model is printed with volumetrically colored anatomical structures using a plaster-based color 3D binder jetting technique. This method allows highly accurate reproduction of patient-specific anatomy as shown in a series of 3D-printed petrous apex chondrosarcomas. Furthermore, the models created can be cut and drilled, revealing internal structures that allow for simulation of surgical procedures.

The protocol describes the fabrication of fully colored three-dimensional prints of patient-specific, anatomical skull models to be used for surgical simulation. The crucial steps of combining different imaging modalities, image segmentation, three-dimensional model extraction, and production of the prints are explained.

Stampa 3D multicolore di tumori intracranici complessi in neurochirurgia

Three-dimensional (3D) printing technologies offer the possibility of visualizing patient-specific pathologies in a physical model of correct dimensions. ...