Ce travail a été financé par le Société canadienne du cancer Institut de recherche, accorder aucune. 019038.

<html> 1. Prélèvement d&#39;échantillons de la prostate <ol><li> Recueillir des échantillons de la prostate au moment de la prostatectomie. L&#39;échantillon est orienté à l&#39;aide des repères anatomiques. La prostate et les vésicules séminales sont peints comme suit: vert à droite, bleu à gauche. </li><li> Un tour de taille aléatoire transversal de la prostate est prélevée perpendiculairement à la surface rectale, congelés dans l&#39;azote liquide, et conservés à -80 ° C 9. </li><li> Tranches en banque de spécimens sont photocopiées, orientée (antérieure, postérieure, droite et gauche), quadrisécable. Les articles sont coupés à l&#39;aide du cryostat. </li><li> Les sections sont colorées avec H &amp; E et examiné par un pathologiste de déterminer et de délimiter les zones tumorales par rapport normale sur les lames colorées et une image correspondante. Les zones marquées sont utilisées en tant que guide pour indiquer les zones à partir de laquelle le tissu tumoral extraire à partir de laquelle l&#39;ARN est extraite dans les étapes ultérieures. </li></ol>casser »&gt; 2. Isolation de l&#39;ARN total, y compris les miARN, dans des échantillons <ol><li> Placer les échantillons de la prostate congelés sur glace sèche et se référant à l&#39;délimité photocopie, découper une petite partie de la tumeur de la prostate (entre 50 et 100 mg). </li><li> Homogénéiser le tissu tumoral de la prostate dans 1 ml de réactif Trizol. Les quantités dans les étapes suivantes sont basées sur l&#39;utilisation de 1 ml de réactif Trizol. </li></ol> Note: Ici nous avons utilisé réactif Trizol pour l&#39;ARN extraction, cependant d&#39;autres kits qui isolent les petits ARN contenant l&#39;ARN total peut également être utilisé. <ol start="3"><li> Incuber les échantillons homogénéisés pour 5 minutes à température ambiante. </li><li> Ajouter 0,2 ml de chloroforme pour les échantillons et agiter vigoureusement pendant 15 secondes. Incuber les échantillons pendant 3 minutes à température ambiante, puis centrifuger à 12 000 xg pendant 15 minutes à 4 ° C. </li><li> Transférer la phase aqueuse supérieure incolore à tubes fraîches, et ajoutez 0,5 ml d&#39;alcool isopropylique.Incuber les échantillons pendant 10 minutes à température ambiante, puis centrifuger à 12 000 xg pendant 10 minutes à 4 ° C. </li><li> Aspirer soigneusement le surnageant sans déranger le culot contenant l&#39;ARN. Laver le culot d&#39;ARN avec 1 ml d&#39;éthanol à 75%. Vortex de l&#39;échantillon et re-sédiments par centrifugation pendant 5 minutes à 7500 xg à 4 ° C. </li><li> Aspirer soigneusement le surnageant et sécher le culot d&#39;ARN pendant 5-10 minutes, en s&#39;assurant que le culot d&#39;ARN n&#39;est pas complètement sèche. Re-dissoudre dans une eau sans nucléase appropriée à la taille des granulés. Mesurer la concentration de l&#39;ARN en utilisant le spectrophotomètre NanoDrop 1000 (absorbance mesure à 260 nm et 280 nm). </li><li> Vérifier la qualité et l&#39;intégrité des échantillons d&#39;ARN à l&#39;aide Agilent Bioanalyzer. </li></ol> 3. Transcription inverse de l&#39;ARN <ol><li> La transcription inverse de l&#39;ARN a été réalisée à l&#39;aide miScript Kit de transcription inverse selon les instructions du fabricant (Qiagen). Ce kit comprend untranscriptase inverse et un poly (A) polymérase. Le tampon miScript RT comprend Mg 2 +, dNTP, d&#39;oligo-dT amorces, et des amorces aléatoires. </li><li> Utilisez entre 10 pg et 1 ug d&#39;ARN pour synthétiser l&#39;ADNc. Si vous utilisez plus de 1 ug d&#39;ARN, intensifier la réaction linéairement au volume approprié. </li><li> Préparer un mélange maître qui contient 5X miScript RT Buffer (4 pi), Mix miScript Reverse Transcription (1 pi), et l&#39;eau sans RNase pour amener les réactions à volume final de 20 ul. Comprennent également la matrice ARN (jusqu&#39;à 1 mg) dans le mélange maître. </li><li> Incuber les échantillons pendant 60 minutes à 37 ° C, suivie immédiatement par une incubation de 5 minutes à 95 ° C. Cette étape peut être réalisée dans une machine à PCR, du bain chauffant bloc, ou de l&#39;eau. Thermocycleurs sont la méthode la plus adaptée et précise. Stocker l&#39;ADNc sur la glace pour le court terme, et -20 ° C pour le stockage à long terme. </li></ol> 4. Génération d&#39;une courbe standard <ol><li> Avant expertiseiment avec miRNAs cibles, une courbe d&#39;étalonnage est générée en utilisant des concentrations connues ADNc de contre leurs points de croisement (CP) (figure 2). </li><li> Préparer une série de dilutions de 2 fois, 10 fois, 50 fois, 250 fois, et 1250 fois l&#39;ADNc d&#39;origine d&#39;un échantillon qui est connu pour avoir une expression importante de votre gène d&#39;intérêt. </li><li> Exécutez le PCR comme spécifié dans la section 5 &quot;PCR en temps réel pour la détection de miARN&quot;, avec la modification que l&#39;ADNc est en dilutions en série n&#39;est pas une dilution statique 40x. </li><li> Effectuer une analyse utilisant un logiciel RelQuant (Roche) pour générer votre courbe standard. </li></ol> Remarque: une nouvelle courbe standard doit être généré pour chaque gène d&#39;intérêt. 5. PCR en temps réel pour la détection de miRNA <ol><li> PCR en temps réel pour les miARN a été réalisée à l&#39;aide miScript SYBR Green PCR Kit de dosage et de Primer miScript selon les instructions du fabricant (Qiagen). Préparer un mélange maître contenant2x QuantiTect SYBR Green PCR Master Mix, 10x miScript Universal Primer, 10x Assay Primer miScript, et l&#39;eau sans RNase. Préparer un mélange maître pour une réaction un volume de 20 ul. </li><li> Le dosage apprêt est spécifique à l&#39;miARN d&#39;intérêt. Pour reconstituer miScript Primer dosage 10x, centrifuger brièvement le flacon, et ajouter 550 ul de tampon TE, pH 8,0. Vortex brièvement le flacon pour mélanger, amorces aliquotes à des volumes plus petits, et conserver à -20 ° C. Deux amorces sont nécessaires:. Amorces pour le gène cible et le gène de référence RNU6B est utilisé tel quel le gène de référence. </li><li> Diluer les ADNc 40x et entreposer des portions supplémentaires à -20 ° C. </li><li> ADNc sert de modèle pour la PCR. Utilisez 2 pi de 40x ADNc dilué et de dispenser à la 20 pi Light Cycler capillaires (Roche). </li><li> Ajouter 18 ul du mélange maître à chaque capillaire, et centrifuger à l&#39;aide d&#39;un adaptateur capillaire. </li><li> Placez les capillaires dans un capillaire en temps réel basé cycleur, comme LightCycler 3.5 Real-Time System PCR avec un format carrousel 32-capillaire. </li><li> Exécutez le programme du cyclisme sur la PCR comme suit: Pour activer la polymérase HotStarTaq qui est dans le 2x QuantiTect SYBR Green PCR Master Mix, pré-incuber à 95 ° C pendant 15 minutes. Suivi par 50 cycles de: Dénaturation, 15 s, 94 ° C; Recuit, 30 s, 55 ° C; Extension, 30 s, 70 ° C. </li><li> Sélectionner un échantillon d&#39;être le calibrateur, et définir sa valeur cible normalisée à 1. Comparer l&#39;expression relative de la miARN dans tous les autres échantillons à l&#39;étalonneur. </li></ol> Remarque: Dans une étude, le même échantillon de calibrage doit être utilisé pour maintenir la cohérence des résultats. 6. Analyse des données <ol><li> Courbes d&#39;amplification pour les réactions de PCR sont représentées graphiquement et numériquement par la version du logiciel biochimiques moléculaire LightCycler 3.5 (Roche). Quantifier les réactions dans le &quot;Quantification&quot; onglet, une exporter les données vers un fichier texte. </li><li> Importez les données vers le logiciel d&#39;analyse RelQuant (Roche) pour générer des résultats de quantification. Importez des fichiers séparés pour le gène cible, gène de référence, et les données de la courbe standard. </li><li> Spécifiez la position de l&#39;étalon à la fois pour cible et gène de référence. Précisez également la position des échantillons. Les données sont exprimées en tant que cible pour référencer ratio de différents échantillons, divisé par le ratio de référence cible du calibrateur. La courbe standard généré précédemment pour un miRNA particulier et gène de ménage est utilisé comme norme de référence pour l&#39;extrapolation des données quantitatives pour cibles des miRNA de concentrations inconnues. </li><li> Trois répliques d&#39;échantillons sont analysés en tant que groupe et les concentrations moyennes et les écarts types de la triple est calculé. Si l&#39;un des triplets est incompatible avec le reste de l&#39;ensemble, il sera exclu par le programme. </li></ol> 7. Les résultats représentatifs &lt;p class = &quot;jove_content&quot;&gt; Un exemple d&#39;analyse qPCR sur des échantillons de la prostate est illustré à la figure 3. Les résultats sont représentés numériquement, ainsi que sous forme graphique. Les graphiques montrant les niveaux d&#39;expression du gène de référence, U6, commencer une amplification exponentielle à environ cycle de 20, tandis que l&#39;expression du gène cible, miR-98, a montré l&#39;amplification retardé à peu près au cycle de 25. Les données de cette expérience a été exportés dans un fichier texte et analysées par un logiciel d&#39;analyse RelQuant. Positions des capillaires contenant le calibrateur et des échantillons sont précisées. La figure 4 illustre la façon dont le calibrateur est fixé à 1, et l&#39;expression d&#39;autres échantillons par rapport à l&#39;étalon. <img src="/files/ftp_upload/3874/3874fig1.jpg" alt="Figure 1"/> Figure 1. Diverses mesures dans miScript transcription inverse et PCR en temps réel. <img src="/files/ftp_upload/3874/3874fig2.jpg" alt="Figure 2"/> Figure 2. Une courbe standard est générée en utilisant une série de dilutions de 2 fois, 10 fois, 50 fois, 250 fois, et 1250 fois l&#39;échantillon initial d&#39;ADNc. <img src="/files/ftp_upload/3874/3874fig3.jpg" alt="Figure 3"/> Figure 3. Roche LightCycler Software moléculaire biochimiques montre toute l&#39;information de l&#39;expérience graphique et par le texte. Quantitative en temps réel des parcelles d&#39;amplification par PCR indiquent une augmentation de la fluorescence à partir d&#39;échantillons différents. <img src="/files/ftp_upload/3874/3874fig4.jpg" alt="Figure 4"/> Les données Figure 4. Ont été quantifiés à l&#39;aide des logiciels d&#39;analyse LightCycler RelQuant. Habituellement, trois répétitions des échantillons sont analysés en tant que groupe et les échantillons qui donnent des résultats manifestement incompatible sont exclus et les concentrations moyennes et les écarts types de la triple est calculé.

<ol>
	<li>Reinhart, B. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNAs+in+plants.">MicroRNAs in plants.</a> Genes Dev. 16, 1616-1616 (2002).</li><li>Xu, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Drosophila+microRNA+Mir-14+suppresses+cell+death+and+is+required+for+normal+fat+metabolism.">The Drosophila microRNA Mir-14 suppresses cell death and is required for normal fat metabolism.</a> Curr. Biol. 13, 790 (2003).</li><li>Bueno, M. J., Perez, d. e. C. a. s. t. r. o., I, ., Malumbres, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Control+of+cell+proliferation+pathways+by+microRNAs.">Control of cell proliferation pathways by microRNAs.</a> Cell Cycle. 7, 3143-3143 (2008).</li><li>Friedman, R. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Most+mammalian+mRNAs+are+conserved+targets+of+microRNAs.">Most mammalian mRNAs are conserved targets of microRNAs.</a> Genome Res. 19, 92 (2009).</li><li>Bartel, D. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNAs:+genomics,+biogenesis,+mechanism,+and+function.">MicroRNAs: genomics, biogenesis, mechanism, and function.</a> Cell. 116, 281-281 (2004).</li><li>Croce, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Causes+and+consequences+of+microRNA+dysregulation+in+cancer.">Causes and consequences of microRNA dysregulation in cancer.</a> Nat. Rev. Genet. 10, 704 (2009).</li><li>Coppola, V., De, M. R., Bonci, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNAs+and+prostate+cancer.">MicroRNAs and prostate cancer.</a> Endocr. Relat. Cancer. 17, 1-1 (2010).</li><li>Gordanpour, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=miR-221+Is+down-regulated+in+TMPRSS2:ERG+fusion-positive+prostate+cancer.">miR-221 Is down-regulated in TMPRSS2:ERG fusion-positive prostate cancer.</a> Anticancer Res. 31, 403-403 (2011).</li><li>Nam, R. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Expression+of+the+TMPRSS2:ERG+fusion+gene+predicts+cancer+recurrence+after+surgery+for+localised+prostate+cancer.">Expression of the TMPRSS2:ERG fusion gene predicts cancer recurrence after surgery for localised prostate cancer.</a> Br. J. Cancer. 97, 1690 (2007).</li><li>Ambs, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genomic+profiling+of+microRNA+and+messenger+RNA+reveals+deregulated+microRNA+expression+in+prostate+cancer.">Genomic profiling of microRNA and messenger RNA reveals deregulated microRNA expression in prostate cancer.</a> Cancer Res. 68, 6162 (2008).</li><li>Liu, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+microRNA+miR-34a+inhibits+prostate+cancer+stem+cells+and+metastasis+by+directly+repressing+CD44.">The microRNA miR-34a inhibits prostate cancer stem cells and metastasis by directly repressing CD44.</a> Nat. Med. 17, 211 (2011).</li></ol>

Pas de conflits d&#39;intérêt déclarés.

Expressions aberrantes de certains miARN ont été constamment trouvé dans des tumeurs de la prostate par rapport au tissu normal 10, et quelques-uns de ces miARN ont été nommés comme nouveaux agents thérapeutiques potentiels contre le cancer de la prostate 11. Par conséquent, les niveaux d&#39;expression aberrants de miARN peuvent être utiles biomarqueurs diagnostiques et / ou pronostique. La méthodologie qPCR en temps réel vous est présenté ici un essai pour la quantification précise ...

<table border="1"><tbody><tr><td> Nom du réactif </td><td> Entreprise </td><td> Numéro de catalogue </td></tr><tr><td> Réactif TRIzol </td><td> Invitrogen </td><td> 15596 </td></tr><tr><td> Kit miScript Reverse Transcription </td><td> Qiagen </td><td> 218061 </td></tr><tr><td> Les dosages d&#39;amorces miScript </td><td> Qiagen </td><td> Expérience spécifique </td></tr><tr><td> miScript SYBR Green PCR Kit </td><td> Qiagen </td><td> 218073 </td></tr><tr><td> LightCycler 3.5 Real-Time System PCR </td><td> Roche </td><td></td></tr><tr><td> Light Cycler capillaires </td><td> Roche </td><td> 04929292001 </td></tr><tr><td> NanoDrop 1000 spectrophotomètre </td><td> Thermo Scientific </td><td> 2538 </td></tr><tr><td> Agilent 2100 Bioanalyzer </td><td> G2943CA </td><td></td></tr></tbody></table>

microrna detection in prostate tumors by quantitative real-time pcr (qpcr)

Les microARN (miARN) sont simple brin, 18-24 nucléotides de long, non codantes des molécules d&#39;ARN. Ils sont impliqués dans pratiquement tous les processus cellulaires, y compris le développement 1, l&#39;apoptose 2, et la régulation du cycle cellulaire 3. MiARN sont estimés à réguler l&#39;expression de 30% à 90% des gènes humains 4 en se liant à leurs ARN messagers (ARNm cibles) 5. Dérèglement généralisé des miARN a été rapporté dans diverses maladies et sous-types de cancer 6. En raison de leur prévalence et de la structure unique, ces petites molécules sont susceptibles d&#39;être la prochaine génération de biomarqueurs, des agents thérapeutiques et / ou des cibles. Les méthodes utilisées pour enquêter sur l&#39;expression du miARN comprennent colorant SYBR Green I-base ainsi que Taqman-sonde qPCR base. Si miARN sont pour être utilisés efficacement dans le contexte clinique, il est impératif que leur détection dans de nouvelles et / ou archivés des échantillons cliniques être fiables, reproductibles, et spS PROPRES. qPCR a été largement utilisé pour valider l&#39;expression des miARN dans les analyses du génome entier, comme les études microarray 7. Les échantillons utilisés dans ce protocole étaient des patients ayant subi une prostatectomie radicale pour cancer de la prostate cliniquement localisé, mais d&#39;autres tissus et des lignées cellulaires peuvent être substitués po spécimens de la prostate étaient composant logiciel enfichable congelés dans l&#39;azote liquide après résection. Les variables cliniques et de suivi d&#39;information pour chaque patient ont été recueillies pour une analyse ultérieure 8. Quantification des niveaux miRNA dans des échantillons de tumeurs de la prostate. Les principales étapes de l&#39;analyse qPCR des tumeurs sont: Total extraction de l&#39;ARN, la synthèse d&#39;ADNc, et la détection des produits qPCR utilisant des amorces spécifiques de miARN. L&#39;ARN total, qui comprend l&#39;ARNm, miRNA, et d&#39;autres petits ARN ont été extraits à partir d&#39;échantillons à l&#39;aide du réactif Trizol. Système de Qiagen miScript a été utilisé pour synthétiser l&#39;ADNc et d&#39;effectuer qPCR (figure 1). MiARN endogènes ne sont pas polyadenylated, donc pendant le processus de transcription inverse, un poly (A) polymérase polyadenylates miRNA. Le miARN est utilisé comme modèle pour synthétiser l&#39;ADNc en utilisant l&#39;oligo-dT et la transcriptase inverse. Séquence d&#39;étiquette universel sur l&#39;extrémité 5 &#39;de l&#39;oligo-dT amorces facilite l&#39;amplification de l&#39;ADNc dans l&#39;étape de PCR. D&#39;amplification du produit de PCR est détectée par le niveau de fluorescence émise par SYBR Green, un colorant qui s&#39;intercale dans l&#39;ADN double brin. Amorces spécifiques miRNA, ainsi que d&#39;une amorce universelle qui se lie à la séquence de balises universel amplifier des séquences spécifiques miRNA. Les dosages d&#39;amorces miScript sont disponibles pour plus d&#39;un millier spécifiques à l&#39;homme miARN et des centaines de souris spécifiques miARN. Méthode de quantification relative a été utilisée ici pour quantifier l&#39;expression des miARN. À corriger des variations entre les différents échantillons, les niveaux d&#39;expression d&#39;un miARN cible est normalisée à des niveaux d&#39;expression d&#39;un gène de référence. Le choix d&#39;un gesur lequel ne pour normaliser l&#39;expression de cibles est critique dans Procédé quantification relative de l&#39;analyse. Des exemples de gènes de référence généralement utilisés dans cette capacité sont les RNU6B petits ARN, RNU44, et RNU48 car ils sont considérés être exprimé de façon stable dans la plupart des échantillons. Dans ce protocole, RNU6B est utilisé en tant que gène de référence.

Watch this Scientific Journal Video about MicroRNA Detection in Prostate Tumors by Quantitative Real-time PCR qPCR at JoVE.com

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

Quantitative de réaction en chaîne polymérase en temps réel (qPCR) est une méthode rapide et sensible pour enquêter sur les niveaux d&#39;expression de microARN (miARN différents) des molécules dans des échantillons tumoraux. En utilisant cette expression méthode de centaines de molécules différentes miARN peuvent être amplifiés, quantifiés, analysés et partir du même modèle d&#39;ADNc.

Détection MicroRNA dans les tumeurs prostatiques par quantitative PCR en temps réel (qPCR)

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

microrna-detection-prostate-tumors-quantitative-real-time-pcr

Research

JoVE Journal

Medicine

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

24.4K vues.  University of Toronto. Quantitative de réaction en chaîne polymérase en temps réel (qPCR) est une méthode rapide et sensible pour enquêter sur les niveaux d'expression de microARN (miARN différents) des molécules dans des échantillons tumoraux. En utilisant cette expression méthode de centaines de molécules différentes miARN peuvent être amplifiés, quantifiés, analysés et partir du même modèle d'ADNc.

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

Multispectral Real-time Fluorescence Imaging for Intraoperative Detection of the Sentinel Lymph Node in Gynecologic Oncology

The prognosis in virtually all solid tumors depends on the presence or absence of lymph node metastases.1-3 Surgical treatment most often combines radical excision of the tumor with a full lymphadenectomy in the drainage area of the tumor. However, removal of lymph nodes is associated with increased morbidity due to infection, wound breakdown and lymphedema.4,5 As an alternative, the sentinel lymph node procedure (SLN) was developed several decades ago to detect the first draining lymph node from the tumor.6 In case of lymphogenic dissemination, the SLN is the first lymph node that is affected (Figure 1). Hence, if the SLN does not contain metastases, downstream lymph nodes will also be free from tumor metastases and need not to be removed. The SLN procedure is part of the treatment for many tumor types, like breast cancer and melanoma, but also for cancer of the vulva and cervix.7 The current standard methodology for SLN-detection is by peritumoral injection of radiocolloid one day prior to surgery, and a colored dye intraoperatively. Disadvantages of the procedure in cervical and vulvar cancer are multiple injections in the genital area, leading to increased psychological distress for the patient, and the use of radioactive colloid.
Multispectral fluorescence imaging is an emerging imaging modality that can be applied intraoperatively without the need for injection of radiocolloid. For intraoperative fluorescence imaging, two components are needed: a fluorescent agent and a quantitative optical system for intraoperative imaging. As a fluorophore we have used indocyanine green (ICG). ICG has been used for many decades to assess cardiac function, cerebral perfusion and liver perfusion.8 It is an inert drug with a safe pharmaco-biological profile. When excited at around 750 nm, it emits light in the near-infrared spectrum around 800 nm. A custom-made multispectral fluorescence imaging camera system was used.9.
The aim of this video article is to demonstrate the detection of the SLN using intraoperative fluorescence imaging in patients with cervical and vulvar cancer. Fluorescence imaging is used in conjunction with the standard procedure, consisting of radiocolloid and a blue dye. In the future, intraoperative fluorescence imaging might replace the current method and is also easily transferable to other indications like breast cancer and melanoma.

Fluorescence imaging is a promising innovative modality for image-guided surgery in surgical oncology. In this video we describe the technical procedure for detection of the sentinel lymph node using fluorescence imaging as showcased in gynecologic oncologicy. A multispectral fluorescence camera system, together with the fluorescent agent indocyanine green, is applied.

Multispectrale en temps réel d&#39;imagerie par fluorescence pour la détection peropératoire du ganglion sentinelle en oncologie gynécologique

The prognosis in virtually all solid tumors depends on the presence or absence of lymph node metastases.1-3 Surgical treatment most often combines radical ...

Recherche

Médecine

A Real-time Electrical Impedance Based Technique to Measure Invasion of Endothelial Cell Monolayer by Cancer Cells

Metastatic dissemination of malignant cells requires degradation of basement membrane, attachment of tumor cells to vascular endothelium, retraction of endothelial junctions and finally invasion and migration of tumor cells through the endothelial layer to enter the bloodstream as a means of transport to distant sites in the host1-3. Once in the circulatory system, cancer cells adhere to capillary walls and extravasate to the surrounding tissue to form metastatic tumors4,5. The various components of tumor cell-endothelial cell interaction can be replicated in vitro by challenging a monolayer of human umbilical vein endothelial cells (HUVEC) with cancer cells. Studies performed with electron and phase-contrast microscopy suggest that the in vitro sequence of events fairly represent the in vivo metastatic process6. Here, we describe an electrical-impedance based technique that monitors and quantifies in real-time the invasion of endothelial cells by malignant tumor cells.
Giaever and Keese first described a technique for measuring fluctuations in impedance when a population of cells grow on the surface of electrodes7,8. The xCELLigence instrument, manufactured by Roche, utilizes a similar technique to measure changes in electrical impedance as cells attach and spread in a culture dish covered with a gold microelectrode array that covers approximately 80% of the area on the bottom of a well. As cells attach and spread on the electrode surface, it leads to an increase in electrical impedance9-12. The impedance is displayed as a dimensionless parameter termed cell-index, which is directly proportional to the total area of tissue-culture well that is covered by cells. Hence, the cell-index can be used to monitor cell adhesion, spreading, morphology and cell density.
The invasion assay described in this article is based on changes in electrical impedance at the electrode/cell interphase, as a population of malignant cells invade through a HUVEC monolayer (Figure 1). The disruption of endothelial junctions, retraction of endothelial monolayer and replacement by tumor cells lead to large changes in impedance. These changes directly correlate with the invasive capacity of tumor cells, i.e., invasion by highly aggressive cells lead to large changes in cell impedance and vice versa. This technique provides a two-fold advantage over existing methods of measuring invasion, such as boyden chamber and matrigel assays: 1) the endothelial cell-tumor cell interaction more closely mimics the in vivo process, and 2) the data is obtained in real-time and is more easily quantifiable, as opposed to end-point analysis for other methods.

This article describes an in vitro technique for monitoring cancer cells invading through a monolayer of endothelial cells. The data is acquired in real-time as a function of changes in impedance on the surface of electrodes at the well bottom.

Une technique basée Impédance électrique en temps réel pour mesurer Invasion de monocouche de cellules endothéliales par les cellules cancéreuses

Metastatic dissemination of malignant cells requires degradation of basement membrane, attachment of tumor cells to vascular endothelium, retraction of ...

Evaluation of Nanoparticle Uptake in Tumors in Real Time Using Intravital Imaging

Current technologies for tumor imaging, such as ultrasound, MRI, PET and CT, are unable to yield high-resolution images for the assessment of nanoparticle uptake in tumors at the microscopic level1,2,3, highlighting the utility of a suitable xenograft model in which to perform detailed uptake analyses. Here, we use high-resolution intravital imaging to evaluate nanoparticle uptake in human tumor xenografts in a modified, shell-less chicken embryo model. The chicken embryo model is particularly well-suited for these in vivo analyses because it supports the growth of human tumors, is relatively inexpensive and does not require anesthetization or surgery 4,5. Tumor cells form fully vascularized xenografts within 7 days when implanted into the chorioallantoic membrane (CAM) 6. The resulting tumors are visualized by non-invasive real-time, high-resolution imaging that can be maintained for up to 72 hours with little impact on either the host or tumor systems. Nanoparticles with a wide range of sizes and formulations administered distal to the tumor can be visualized and quantified as they flow through the bloodstream, extravasate from leaky tumor vasculature, and accumulate at the tumor site. We describe here the analysis of nanoparticles derived from Cowpea mosaic virus (CPMV) decorated with near-infrared fluorescent dyes and/or polyethylene glycol polymers (PEG) 7, 8, 9,10,11. Upon intravenous administration, these viral nanoparticles are rapidly internalized by endothelial cells, resulting in global labeling of the vasculature both outside and within the tumor7,12. PEGylation of the viral nanoparticles increases their plasma half-life, extends their time in the circulation, and ultimately enhances their accumulation in tumors via the enhanced permeability and retention (EPR) effect 7, 10,11. The rate and extent of accumulation of nanoparticles in a tumor is measured over time using image analysis software. This technique provides a method to both visualize and quantify nanoparticle dynamics in human tumors.

We present a novel approach to quantify nanoparticle localization in the vasculature of human xenografted tumors using dynamic, real-time intravital imaging in an avian embryo model.

Evaluation de la fixation des nanoparticules dans les tumeurs en temps réel par imagerie intravitale

Current technologies for tumor imaging, such as ultrasound, MRI, PET and CT, are unable to yield high-resolution images for the assessment of nanoparticle ...

Detection and Genogrouping of Noroviruses from Children's Stools By Taqman One-step RT-PCR

Noroviruses (NoVs) are the leading cause of outbreaks of sporadic acute gastroenteritis worldwide in humans of all ages. They are important cause of hospitalizations in children with a public health impact similar to that of Rotavirus. NoVs are RNA viruses of great genetic diversity and there is a continuous appearance of new strains. Five genogroups are recognized; GI and GII with their many genotypes and subtypes being the most important for human infection. However, the diagnosis of these two genotypes remains problematic, delaying diagnosis and treatment. 1, 2, 3
For RNA extraction from stool specimens the most commonly used method is the QIAmp Viral RNA commercial kit from Qiagen. This method combines the binding properties of a silica gel membrane, buffers that control RNases and provide optimum binding of the RNA to the column together with the speed of microspin. This method is simple, fast and reliable and is carried out in a few steps that are detailed in the description provided by the manufacturer. 
 Norovirus is second only to rotavirus as the most common cause of diarrhea. Norovirus diagnosis should be available in all studies on pathogenesis of diarrhea as well as in outbreaks or individual diarrhea cases. At present however norovirus diagnosis is restricted to only a few centers due to the lack of simple methods of diagnosis. This delays diagnosis and treatment 1, 2, 3. In addition, due to costs and regulated transportation of corrosive buffers within and between countries use of these manufactured kits poses logistical problems. As a result, in this protocol we describe an alternative, economic, in-house method which is based on the original Boom et al. method4 which uses the nucleic acid binding properties of silica particles together with the anti-nuclease properties of guanidinium thiocyanate.
For the detection and genogrouping (GI and GII) of NoVs isolates from stool specimens, several RT-PCR protocols utilizing different targets have been developed. The consensus is that an RT-PCR using TaqMan chemistry would be the best molecular technique for diagnosis, because it combines high sensitivity, specificity and reproducibility with high throughput and ease of use. Here we describe an assay targeting the open reading frame 1 (ORF1)-ORF2 junction region; the most conserved region of the NoV genome and hence most suitable for diagnosis. For further genetic analysis a conventional RT-PCR that targets the highly variable N-terminal-shell from the major protein of the capsid (Region C) using primers originally described by Kojima et al. 5 is detailed. Sequencing of the PCR product from the conventional PCR enables the differentiation of genotypes belonging to the GI and GII genogroups.

Detection and Genogrouping of Noroviruses from Children&#039;s Stools By Taqman One-step RT-PCR

A One-Step RT-PCR assay for detection and genogroup identification of Norovirus isolates from children&#x2019;s stools, that utilizes primers and TaqMan probes specific to the open reading frame 1 (ORF1)-ORF2 junction region, the most conserved region of the Norovirus genome is described. A non-commercial, cost-effective RNA extraction method is detailed.

Détection et Genogrouping des norovirus dans les selles des enfants en Taqman en une seule étape de RT-PCR

Noroviruses (NoVs) are the leading cause of outbreaks of sporadic acute gastroenteritis worldwide in humans of all ages. They are important cause of ...

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.

Cartographie hétérogénéité d&#39;expression des protéines dans les tumeurs par immunofluorescence quantitative

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

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

Genomic, proteomic, transcriptomic, and epigenomic analyses of human tumors indicate that there are thousands of anomalies within each cancer genome compared to matched normal tissue. Based on these analyses it is evident that there are many undiscovered genetic drivers of cancer1. Unfortunately these drivers are hidden within a much larger number of passenger anomalies in the genome that do not directly contribute to tumor formation. Another aspect of the cancer genome is that there is considerable genetic heterogeneity within similar tumor types. Each tumor can harbor different mutations that provide a selective advantage for tumor formation2. Performing an unbiased forward genetic screen in mice provides the tools to generate tumors and analyze their genetic composition, while reducing the background of passenger mutations. The Sleeping Beauty (SB) transposon system is one such method3. The SB system utilizes mobile vectors (transposons) that can be inserted throughout the genome by the transposase enzyme. Mutations are limited to a specific cell type through the use of a conditional transposase allele that is activated by Cre Recombinase. Many mouse lines exist that express Cre Recombinase in specific tissues. By crossing one of these lines to the conditional transposase allele (e.g. Lox-stop-Lox-SB11), the SB system is activated only in cells that express Cre Recombinase. The Cre Recombinase will excise a stop cassette that blocks expression of the transposase allele, thereby activating transposon mutagenesis within the designated cell type. An SB screen is initiated by breeding three strains of transgenic mice so that the experimental mice carry a conditional transposase allele, a concatamer of transposons, and a tissue-specific Cre Recombinase allele. These mice are allowed to age until tumors form and they become moribund. The mice are then necropsied and genomic DNA is isolated from the tumors. Next, the genomic DNA is subjected to linker-mediated-PCR (LM-PCR) that results in amplification of genomic loci containing an SB transposon. LM-PCR performed on a single tumor will result in hundreds of distinct amplicons representing the hundreds of genomic loci containing transposon insertions in a single tumor4. The transposon insertions in all tumors are analyzed and common insertion sites (CISs) are identified using an appropriate statistical method5. Genes within the CIS are highly likely to be oncogenes or tumor suppressor genes, and are considered candidate cancer genes. The advantages of using the SB system to identify candidate cancer genes are: 1) the transposon can easily be located in the genome because its sequence is known, 2) transposition can be directed to almost any cell type and 3) the transposon is capable of introducing both gain- and loss-of-function mutations6. The following protocol describes how to devise and execute a forward genetic screen using the SB transposon system to identify candidate cancer genes (Figure 1).

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

A method of identifying unknown drivers of carcinogenesis using an unbiased approach is described. The method uses the Sleeping Beauty transposon as a random mutagen directed to specific tissues. Genomic mapping of transposon insertions that drive tumor formation identifies novel oncogenes and tumor suppressor genes

Identification des<em&gt; Belle au Bois Dormant</em&gt; Insertions de transposons dans les tumeurs solides en utilisant l&#39;éditeur de liens médiée par PCR

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

Movement Retraining using Real-time Feedback of Performance

Any modification of movement - especially movement patterns that have been honed over a number of years - requires re-organization of the neuromuscular patterns responsible for governing the movement performance. This motor learning can be enhanced through a number of methods that are utilized in research and clinical settings alike. In general, verbal feedback of performance in real-time or knowledge of results following movement is commonly used clinically as a preliminary means of instilling motor learning. Depending on patient preference and learning style, visual feedback (e.g. through use of a mirror or different types of video) or proprioceptive guidance utilizing therapist touch, are used to supplement verbal instructions from the therapist. Indeed, a combination of these forms of feedback is commonplace in the clinical setting to facilitate motor learning and optimize outcomes.
Laboratory-based, quantitative motion analysis has been a mainstay in research settings to provide accurate and objective analysis of a variety of movements in healthy and injured populations. While the actual mechanisms of capturing the movements may differ, all current motion analysis systems rely on the ability to track the movement of body segments and joints and to use established equations of motion to quantify key movement patterns. Due to limitations in acquisition and processing speed, analysis and description of the movements has traditionally occurred offline after completion of a given testing session.
This paper will highlight a new supplement to standard motion analysis techniques that relies on the near instantaneous assessment and quantification of movement patterns and the display of specific movement characteristics to the patient during a movement analysis session. As a result, this novel technique can provide a new method of feedback delivery that has advantages over currently used feedback methods.

Retraining abnormal movement patterns following injury or disease is a key component of physical rehabilitation. Recent advances in technology have permitted accurate assessment of movement during a variety of tasks, with near instantaneous quantification of results. This provides new opportunities for modification of faulty movement patterns in real time.

Mouvement recyclage en utilisant rétroaction en temps réel de la performance

Any modification of movement - especially movement patterns that have been honed over a number of years - requires re-organization of the neuromuscular ...

Using Quantitative Real-time PCR to Determine Donor Cell Engraftment in a Competitive Murine Bone Marrow Transplantation Model

Murine bone marrow transplantation models provide an important tool in measuring hematopoietic stem cell (HSC) functions and determining genes/molecules that regulate HSCs. In these transplant model systems, the function of HSCs is determined by the ability of these cells to engraft and reconstitute lethally irradiated recipient mice. Commonly, the donor cell contribution/engraftment is measured by antibodies to donor- specific cell surface proteins using flow cytometry. However, this method heavily depends on the specificity and the ability of the cell surface marker to differentiate donor-derived cells from recipient-originated cells, which may not be available for all mouse strains. Considering the various backgrounds of genetically modified mouse strains in the market, this cell surface/ flow cytometry-based method has significant limitations especially in mouse strains that lack well-defined surface markers to separate donor cells from congenic recipient cells. Here, we reported a PCR-based technique to determine donor cell engraftment/contribution in transplant recipient mice. We transplanted male donor bone marrow HSCs to lethally irradiated congenic female mice. Peripheral blood samples were collected at different time points post transplantation. Bone marrow samples were obtained at the end of the experiments. Genomic DNA was isolated and the Y chromosome specific gene, Zfy1, was amplified using quantitative Real time PCR. The engraftment of male donor-derived cells in the female recipient mice was calculated against standard curve with known percentage of male vs. female DNAs. Bcl2 was used as a reference gene to normalize the total DNA amount. Our data suggested that this approach reliably determines donor cell engraftment and provides a useful, yet simple method in measuring hematopoietic cell reconstitution in murine bone marrow transplantation models. Our method can be routinely performed in most laboratories because no costly equipment such as flow cytometry is required.

Determining donor cell engraftment presents a challenge in mouse bone marrow transplant models that lack well-defined phenotypical markers. We described a methodology to quantify male donor cell engraftment in female transplant recipient mice. This method can be used in all mouse strains for the study of HSC functions.

Utilisation quantitative PCR en temps réel pour déterminer prise de greffe de donneurs de cellules dans un modèle murin concurrentiel greffe de moelle osseuse

Murine bone marrow transplantation models provide an important tool in measuring hematopoietic stem cell (HSC) functions and determining genes/molecules ...

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.

Liquide céphalo-rachidien profilage de microARN Utilisation quantitative PCR en temps réel

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

Real-time Cytotoxicity Assays in Human Whole Blood

A live cell-based whole blood cytotoxicity assay (WCA) that allows access to temporal information of the overall cell cytotoxicity is developed with high-throughput cell positioning technology. The targeted tumor cell populations are first preprogrammed to immobilization into an array format, and labeled with green fluorescent cytosolic dyes. Following the cell array formation, antibody drugs are added in combination with human whole blood. Propidium iodide (PI) is then added to assess cell death. The cell array is analyzed with an automatic imaging system. While cytosolic dye labels the targeted tumor cell populations, PI labels the dead tumor cell populations. Thus, the percentage of target cancer cell killing can be quantified by calculating the number of surviving targeted cells to the number of dead targeted cells. With this method, researchers are able to access time-dependent and dose-dependent cell cytotoxicity information. Remarkably, no hazardous radiochemicals are used. The WCA presented here has been tested with lymphoma, leukemia, and solid tumor cell lines. Therefore, WCA allows researchers to assess drug efficacy in a highly relevant ex&#160;vivo condition.

The whole blood cytotoxicity assay (WCA) is a cytotoxicity assay developed by incorporating high-throughput cell positioning technology with fluorescence microscopy and automated image processing. Here, we describe how lymphoma cells treated with an anti-CD20 antibody can be analyzed real-time in human whole blood to provide quantitative cellular cytotoxicity analysis.

En temps réel cytotoxicité dans le sang total humain

A live cell-based whole blood cytotoxicity assay (WCA) that allows access to temporal information of the overall cell cytotoxicity is developed with ...