This research is supported by funding from CBCF (to ZW).

1. Canlı Görüntüleme Hücreleri hazırlanması <ol><li> Hücre kültürü ve tohum <ol><li> Dosetaksel (MCF-7 TXT) ve dirençli olmayan ana hücre dizisi (MCF-7 CC) karşı direnç için seçilir MCF-7 göğüs kanseri hücreleri kullanır. Ayrıntılı seçim süreci ve bu seçilen hücre hatları özellikleri daha önce 24 tarif edildi. </li><li> Dulbecco tadil edilmiş Eagle ortamı (DMEM) ve fetal sığır serumu (FBS), 10%, 90% oluşan ve temel olmayan amino asitler ile takviye edilmiş bir ortam içinde, 37 ° C&#39;de 10 cm kültür tabaklarında tüm hücreleri büyütün. % 5 CO2 atmosferinde ortam muhafaza edin. 5 nM dosetaksel de MCF-7 TXT hücreleri korumak. </li><li> canlı görüntüleme için lamelleri Tohum hücreleri. Gecede UV onları teşhir sonra% 70 alkol ile durulama ve 24 mm poli-L-lizin kaplı cam lamelleri sterilize edin. 35 mm&#39;lik bir 6-yuvalı kültür plakasına lamelleri yerleştirin. plHer iyi bir lamel ace. </li><li> 10 cm&#39;lik bir kültür kabı orta çıkarın ve hücreler PBS ile yıkayın. çanak hücreleri ayırmak için çanak tripsin-EDTA 0.5 mL ekleyin. Hücrelerin dekolmanı aşağıdaki tripsin nötralize etmek çanak kültür ortamı 5 ml ekleyin. </li><li> Birim hacim başına hücre sayısını belirlemek için bir hemasitometre ile hücre sayımı. </li><li> Her bir birim hacmi başına hücre sayısı göre yaklaşık olarak 10 5 hücre ekleyin. hafifçe sallayarak sonra, hücreler lamelleri eklemek için izin inkübatör geri tabak koydu. </li></ol></li><li> GFP etiketli α-tubulin ekspresyonu <ol><li> Mikrotübül dinamiklerinin tahlil üreticinin protokolüne göre, ticari GFP transdüksiyon kontrolü (ör BacMam) GFP-etiketli α-tubulin ile hücreleri nakletmek için. </li><li> 37 ° C hücre kültürü inkübatöründe 36 saat bir gözdeki hücrelerin com izin vermek için, kültürkomplet yapışma ve% 60 izdiham. </li><li> aşağıdaki denkleme göre, her bir oyuğa ilave GFP-etiketli α-tubulin uygun hacimde hesaplayın: <img alt="Denklem" src="/files/ftp_upload/55027/55027eq1.jpg" /> hücrelerin sayısı etiketleme sırasında bir gözdeki hücrelerin sağ tahmini toplam sayısıdır ve istenen PPC hücre başına parçacıkların sayısıdır. Not: MCF-7 hücreleri tohumlama 20 arzu edilen bir PPC 10 5 5 10 ila 2 x hücre sayısı iki gereken her bir lamel için gerekli hacmi dolayısıyla 40 ml. farklı hücreler için, hacim en iyi olmayabilir yukarıda verilen formüle göre hesaplanacaktır. Kesin hacmin GFP tubulin gerçek ifade seviyesine göre ayarlanmalıdır. </li><li> homojen bir çözelti sağlamak için ters çevirme ile GFP etiketli α-tübülin birkaç kez karıştırılır. vorteks etmeyin. NOT: kontrolü için, boş (kontrol) reaktif herhangi bir memeli genetik yoksunelemanları ve potansiyel bakulovirüs dolayımlı etkileri ve arka plan floresanı belirlenmesine yardımcı olmak için kullanılabilir. Olmayan hedefli GFP transdüksiyon kontrolü de tüm hücre yanacaktır, hangi kullanılabilir. </li><li> taze ortam ile kültür ortamı değiştirin. Her bir oyuğa GFP etiketli α-tubulin, yeni orta 2 mL 40 uL ekleyin. </li><li> kültür ortamı ile GFP etiketli α-tubulin tamamen karışmanın sağlanması için hafifçe plakayı sallayın. Kültür Plakaları kuluçka makinesine geri dönün ve GFP-tubulin ekspresyonunu sağlamak için 24 saat boyunca inkübe edilir. </li></ol></li><li> Dosetaksel ile muamele hücreleri Not: Bu deney mikrotübül dinamik istikrarsızlık üzerinde dosetaksel etkisini test etmektir. Bu durumda, hücreler, dosetaksel istenen konsantrasyona ile muamele edilir. <ol><li> Orta DMEM% 90 FBS ve% 10 oluşur ve temel olmayan amino asitler ile takviye hazırlayın. fenol kırmızısı flüoresan etkileyebilir çünkü fenol kırmızısı olmadan DMEM kullanınGFP-tubulin CE. (10 nM ila 10 uM arasında) doketaksel istenilen konsantrasyonu ekleyin. dosetaksel stok solüsyonları dimetil sülfoksitte (DMSO) içinde 10 mM&#39;dir. </li><li> Ön sıcak doku kültürü kuluçka makinesi içinde 37 ° C docetaksel içeren ortam. </li><li> docetaksel içeren ortam ile normal kültür ortamı yerine ve doku kültürü kuluçka makinesi içinde 30 dakika inkübe edilir. Her bir dosetaksel konsantrasyonu için oyuk başına en az 3 lamelleri olmalıdır. </li></ol></li></ol> 2. Canlı Görüntüleme Mikrotubul dinamik dengesizlik incelemek için <ol><li> Sistem kurma <ol><li> 37 ° C&#39;de ve% 5 CO2 de muhafaza edilen bir oda içinde deneyleri gerçekleştirmek. Bir 60X, ters floresan mikroskop ve bir CCD kamera ile 1.42 NA petrol objektif lens ile donatılmış bir mikroskobik sistemi ile zaman atlamalı tarafından floresan görüntü kazanır. </li><li> canlı görüntüleme için hücreler ayarlayın. Pre-sıcak numune tutucu hem de37 ° C&#39;ye kadar ortam. incelemek için lamel seçin. Bir numune tutucu üzerinde ilgi lamel monte ve aşama 1.3.1 hazırlanan docetaksel içeren ortam 1 ml ile inkübe edin. </li></ol></li><li> Mikrotübül dinamik istikrarsızlık Canlı görüntüleme <ol><li> görüntüleme için kullanılacak hücrelerin belirlenmesi. Bunlar, düz GFP-tubulin yüksek floresan yoğunluğunu, ve açık bir mikrotübül yapılarının sahip olmalıdır. </li><li> İlk incelemek için aşama 2.2.1 üzerinden tanımlanmıştır hücre grubundan bir ölçeri seçin. belirlenen hücrenin çevresel alana odaklanmak. maruz kalma süresi için program ve görüntü alımı sıklığını ayarlayın. Pozlama süresi genellikle 0,5 s gibi görüntüleri her iki s satın alınacak. </li><li> 1.33 den 2.2.3 adımları için ek bir 20 dakika bekleyin. Aşama 1.3.3 tarif edildiği gibi nedenle, tam 50 dakika dosetaksel ilave edildikten sonra (bu standardizasyon için) görüntüleme başlar. </li><li> mikrotübül d kaydedindinamiği çalışmaları 2 dakika süreyle, bir Fotoğrafa her 2 sn alarak. Toplamda, tespit hücre için 60 görüntü kazanır. </li><li> Bir sonraki tanımlanmış hücreye taşımak ve tekrar 2.2.4 için 2.2.2 adımları. 5 hücreleri görüntülü kadar aynı işlemi tekrarlayın. Adım 1.3.3 de açıklandığı gibi zaman, dosetaksel eklenmesinden sonra 70 dakika ulaşmadan önce bunu yapmak zorunludur. </li><li> Her tedavi koşulu için tekrarlayın 3 farklı lamelleri için 2.2.5 için 2.2.1 adımları. Toplamda, görüntü 15 hücreleri, yeterli veri mikrotübül dinamik istikrarsızlık ölçmek için hangi. </li></ol></li></ol> 3. Görüntü İşleme ve Veri Analizi <ol><li> Görüntülerin Dekonvolüsyon <ol><li> yüksek kalitede elde etmek için elde edilen görüntüleri Deconvolve. mikroskop sistemi ile donatılmış Dekonvolüsyonun programını açın. </li><li> &quot;Süreç&quot; tıklayın ve &quot;Deconvolve.&quot; &quot;Giriş&quot; penceresinde görüntü dosyasını sürükleyin ve tıklayın &quot;Do.&quot; görüntü dosyası deconvolved ve olacakdeconvolved dosya otomatik olarak yeni bir dosya olarak kaydedilir. </li></ol></li><li> Videoları Üretimi <ol><li> donanımlı yazılımla açmak için deconvolved görüntü dosyasını tıklatın. </li><li> &quot;Dosya&quot; tıklayın ve &quot;film olarak kaydedin.&quot; olarak &quot;AV&quot; ve &quot;Animasyon tarzı&quot; olarak &quot;Film formatı&quot; Seç &quot;İlet.&quot; &quot;100%&quot; ve &quot;Çerçeve oranı&quot; için &quot;Sıkıştırma kalitesi&quot; Set &quot;5 / saniye.&quot; </li><li> &quot;Zaman içinde canlandırın&quot; ve tıklayın kutusunu işaretleyin &quot;Do it.&quot; Video oluşacaktır. </li></ol></li><li> Mikrotübül kısalma ve büyüme hızının ölçülmesi <ol><li> ölçümü için kullanılacak mikrotübül belirleyin. her bir hücre için, sadece bir kaç mikrotübüller bunların yağ ya da büyüme açık ve tam olarak takip olması mümkün olur. </li><li> mikrotübül a başlangıç ​​uzunluğunu gösterir çerçeveyi belirlemek için videonun her karesini inceleyinnd en uzatılabilir veya kısaltılabilir mikrotübül ile çerçeve. İki mikrotübül ve iki kare arasında geçen süre arasındaki uzunluk değişimi ölçün. </li><li> zaman uzunluğu değişimi bölerek büyüme veya kısalma oranını hesaplamak (birim mm / s). Her bir tedavi durumu için, en az 10 hücrelerin takip ve en az 20 mikrotübülleri ölçer. </li><li> Her bir tedavi durumu için ortalama ve standart hata hesaplanır. Öğrenci testi kullanılarak koşulları arasındaki istatistiksel fark analiz eder. tablo ve / veya bir grafik veri rapor edin. </li></ol></li></ol>

<ol>
	<li>Kamangar, F., Dores, G. M., Anderson, W. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Patterns+of+cancer+incidence,+mortality,+and+prevalence+across+five+continents:+defining+priorities+to+reduce+cancer+disparities+in+different+geographic+regions+of+the+world.">Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world.</a> J Clin Oncol. 24 (14), 2137-2150 (2006).</li><li>Yardley, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Drug+resistance+and+the+role+of+combination+chemotherapy+in+improving+patient+outcomes.">Drug resistance and the role of combination chemotherapy in improving patient outcomes.</a> Int J Breast Cancer. 2013, 137414 (2013).</li><li>Jassem, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Doxorubicin+and+paclitaxel+versus+fluorouracil,+doxorubicin,+and+cyclophosphamide+as+first-line+therapy+for+women+with+metastatic+breast+cancer:+final+results+of+a+randomized+phase+III+multicenter+trial.">Doxorubicin and paclitaxel versus fluorouracil, doxorubicin, and cyclophosphamide as first-line therapy for women with metastatic breast cancer: final results of a randomized phase III multicenter trial.</a> J Clin Oncol. 19 (6), 1707-1715 (2001).</li><li>Nabholtz, J. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Docetaxel+and+doxorubicin+compared+with+doxorubicin+and+cyclophosphamide+as+first-line+chemotherapy+for+metastatic+breast+cancer:+results+of+a+randomized,+multicenter,+phase+III+trial.">Docetaxel and doxorubicin compared with doxorubicin and cyclophosphamide as first-line chemotherapy for metastatic breast cancer: results of a randomized, multicenter, phase III trial.</a> J Clin Oncol. 21 (6), 968-975 (2003).</li><li>Zelnak, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Overcoming+taxane+and+anthracycline+resistance.">Overcoming taxane and anthracycline resistance.</a> Breast J. 16 (3), 309-312 (2010).</li><li>Rivera, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Implications+of+anthracycline-resistant+and+taxane-resistant+metastatic+breast+cancer+and+new+therapeutic+options.">Implications of anthracycline-resistant and taxane-resistant metastatic breast cancer and new therapeutic options.</a> Breast J. 16 (3), 252-263 (2010).</li><li>Longley, D. B., Johnston, P. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+mechanisms+of+drug+resistance.">Molecular mechanisms of drug resistance.</a> J Pathol. 205 (2), 275-292 (2005).</li><li>Downing, K. H., Nogales, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Crystallographic+structure+of+tubulin:+implications+for+dynamics+and+drug+binding.">Crystallographic structure of tubulin: implications for dynamics and drug binding.</a> Cell Struct.Funct. 24 (5), 269-275 (1999).</li><li>McGrogan, B. T., Gilmartin, B., Carney, D. N., McCann, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Taxanes,+microtubules+and+chemoresistant+breast+cancer.">Taxanes, microtubules and chemoresistant breast cancer.</a> Biochim.Biophys.Acta. 1785 (2), 96-132 (2008).</li><li>Kamath, K., Oroudjev, E., Jordan, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Determination+of+microtubule+dynamic+instability+in+living+cells.">Determination of microtubule dynamic instability in living cells.</a> Methods Cell Biol. 97, 1-14 (2010).</li><li>Dumontet, C., Jordan, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microtubule-binding+agents:+a+dynamic+field+of+cancer+therapeutics.">Microtubule-binding agents: a dynamic field of cancer therapeutics.</a> Nat Rev Drug Discov. 9 (10), 790-803 (2010).</li><li>Jordan, M. A., Wilson, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microtubules+as+a+target+for+anticancer+drugs.">Microtubules as a target for anticancer drugs.</a> Nat.Rev.Cancer. 4 (4), 253-265 (2004).</li><li>Gascoigne, K. E., Taylor, S. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+do+anti-mitotic+drugs+kill+cancer+cells?.">How do anti-mitotic drugs kill cancer cells?.</a> J.Cell Sci. 122 (15), 2579-2585 (2009).</li><li>Kavallaris, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microtubules+and+resistance+to+tubulin-binding+agents.">Microtubules and resistance to tubulin-binding agents.</a> Nat.Rev.Cancer. 10 (3), 194-204 (2010).</li><li>Diaz, J. F., Valpuesta, J. M., Chacon, P., Diakun, G., Andreu, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Changes+in+microtubule+protofilament+number+induced+by+Taxol+binding+to+an+easily+accessible+site.+Internal+microtubule+dynamics.">Changes in microtubule protofilament number induced by Taxol binding to an easily accessible site. Internal microtubule dynamics.</a> J.Biol.Chem. 273 (50), 33803-33810 (1998).</li><li>Abal, M., Andreu, J. M., Barasoain, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Taxanes:+microtubule+and+centrosome+targets,+and+cell+cycle+dependent+mechanisms+of+action.">Taxanes: microtubule and centrosome targets, and cell cycle dependent mechanisms of action.</a> Curr Cancer Drug Targets. 3 (3), 193-203 (2003).</li><li>Wang, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiple+mechanisms+underlying+acquired+resistance+to+taxanes+in+selected+docetaxel-resistant+MCF-7+breast+cancer+cells.">Multiple mechanisms underlying acquired resistance to taxanes in selected docetaxel-resistant MCF-7 breast cancer cells.</a> BMC Cancer. 14 (37), (2014).</li><li>Lal, S., Mahajan, A., Chen, W. N., Chowbay, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pharmacogenetics+of+target+genes+across+doxorubicin+disposition+pathway:+a+review.">Pharmacogenetics of target genes across doxorubicin disposition pathway: a review.</a> Curr. Drug Metab. 11 (1), 115-128 (2010).</li><li>Murray, S., Briasoulis, E., Linardou, H., Bafaloukos, D., Papadimitriou, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Taxane+resistance+in+breast+cancer:+mechanisms,+predictive+biomarkers+and+circumvention+strategies.">Taxane resistance in breast cancer: mechanisms, predictive biomarkers and circumvention strategies.</a> Cancer Treat.Rev. 38 (7), 890-903 (2012).</li><li>Kamath, K., Wilson, L., Cabral, F., Jordan, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BetaIII-tubulin+induces+paclitaxel+resistance+in+association+with+reduced+effects+on+microtubule+dynamic+instability.">BetaIII-tubulin induces paclitaxel resistance in association with reduced effects on microtubule dynamic instability.</a> J.Biol.Chem. 280 (13), 12902-12907 (2005).</li><li>Banerjee, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Increased+levels+of+tyrosinated+alpha-,+beta(III)-,+and+beta(IV)-tubulin+isotypes+in+paclitaxel-resistant+MCF-7+breast+cancer+cells.">Increased levels of tyrosinated alpha-, beta(III)-, and beta(IV)-tubulin isotypes in paclitaxel-resistant MCF-7 breast cancer cells.</a> Biochem.Biophys.Res.Commun. 293 (1), 598-601 (2002).</li><li>Wiesen, K. M., Xia, S., Yang, C. P., Horwitz, S. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Wild-type+class+I+beta-tubulin+sensitizes+Taxol-resistant+breast+adenocarcinoma+cells+harboring+a+beta-tubulin+mutation.">Wild-type class I beta-tubulin sensitizes Taxol-resistant breast adenocarcinoma cells harboring a beta-tubulin mutation.</a> Cancer Lett. 257 (2), 227-235 (2007).</li><li>Iseri, O. D., Kars, M. D., Arpaci, F., Gunduz, U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gene+expression+analysis+of+drug-resistant+MCF-7+cells:+implications+for+relation+to+extracellular+matrix+proteins.">Gene expression analysis of drug-resistant MCF-7 cells: implications for relation to extracellular matrix proteins.</a> Cancer Chemother.Pharmacol. 65 (3), 447-455 (2010).</li><li>Hembruff, S. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Role+of+drug+transporters+and+drug+accumulation+in+the+temporal+acquisition+of+drug+resistance.">Role of drug transporters and drug accumulation in the temporal acquisition of drug resistance.</a> BMC.Cancer. 8, 318 (2008).</li><li>Yenjerla, M., Lopus, M., Wilson, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+dynamic+instability+of+steady-state+microtubules+in+vitro+by+video-enhanced+differential+interference+contrast+microscopy+with+an+appendix+by+Emin+Oroudjev.">Analysis of dynamic instability of steady-state microtubules in vitro by video-enhanced differential interference contrast microscopy with an appendix by Emin Oroudjev.</a> Methods Cell Biol. 95, 189-206 (2010).</li><li>Sammak, P. J., Gorbsky, G. J., Borisy, G. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microtubule+dynamics+in+vivo:+a+test+of+mechanisms+of+turnover.">Microtubule dynamics in vivo: a test of mechanisms of turnover.</a> J Cell Biol. 104 (3), 395-405 (1987).</li><li>Walker, R. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dynamic+instability+of+individual+microtubules+analyzed+by+video+light+microscopy:+rate+constants+and+transition+frequencies.">Dynamic instability of individual microtubules analyzed by video light microscopy: rate constants and transition frequencies.</a> J Cell Biol. 107 (4), 1437-1448 (1988).</li><li>Desai, A., Mitchison, T. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microtubule+polymerization+dynamics.">Microtubule polymerization dynamics.</a> Annu Rev Cell Dev Biol. 13, 83-117 (1997).</li><li>Walczak, C. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microtubule+dynamics+and+tubulin+interacting+proteins.">Microtubule dynamics and tubulin interacting proteins.</a> Curr Opin Cell Biol. 12 (1), 52-56 (2000).</li></ol>

Yazarlar hiçbir rakip mali çıkarları olduğunu beyan ederim.

In vitro ve in vivo: mikrotübül Dinamik dengesizlik ölçmek için iki ana yöntem vardır. In vitro yöntemde, saflaştırılmış tubulin bilgisayar destekli zaman atlamalı diferansiyel girişim kontrast mikroskobu ile mikrotübül dinamik istikrarsızlık ölçmek için kullanılır. In vivo metodunda, floresan tubulin mikroenjeksiyon ya da GFP-tubulin ifade mikrotübüllere dahil edilir. Mikrotübül dinamikleri (büyüme ve kısalma) sonra fazlar arası hücrelerinin ...

<html> Meme kanseri ölümlerinin önde gelen nedenidir metastazı 1, 2 geçer. Birinci basamak metastatik meme kanseri, 2, 3, 4, 5, 6 tedavisinde rejimleri gibi dosetaksel ve paklitaksel gibi taksanlarm kendilerine hidrofobik şu anda kullanılmaktadır. Onlar mikrotübül dinamiklerini bozabilir mikrotübül hedefleme ajanları (MTAs) bir grubun parçasıdır. Ancak, küratif tedavi taksan kullanarak en büyük sorunlardan biri nüks 7 neden kanser hücrelerinde taksan direnci, geliştirilmesidir. İlaç direnci metastatik meme kanseri 7 olan hastalarda, tüm ölümlerin% 90&#39;dan fazla sorumludur. Mikrotübüller α- ve β-tübülin heterodimerlerinin polimerizasyonuyla oluşurclass = &quot;xref&quot;&gt; 8, 9. mikrotubul dinamiği kesin düzenlemesi, hücre polarizasyon, hücre döngüsü ilerlemesinin, hücre içi ulaşım ve hücre sinyalizasyon dahil olmak üzere birçok hücre fonksiyonları için önemlidir. Mikrotübüllerin ve dinamikleri bozulması hücre fonksiyonunu bozabilir ve hücre ölümü 10, 11 neden olur. Bu sistem bozukluğu neden bağlı olarak, MTA ilaçlar mikrotübül stabilize edici ajanlar (örneğin, taksanlar) ya da mikrotübül destabalizing maddeler (örneğin, vinka alkaloidler ve kolşisin yerinde bağlama maddeleri), 20, ya da sınıflandırılabilir. Mikrotübül kütlesi üzerindeki zıt etkilerine rağmen, yeterli dozda, hem sınıflar mikrotübül dinamiklerine 21 üzerindeki etkileri yoluyla kanser hücrelerini öldürür. Taksan yol açan mikrotübül mili 12 dengeleyici öncelikle işlevkromozomal hiza. mili montaj kontrol noktasında (SAC) sonraki sürekli aktivasyon mitoz hücreyi tutuklamalar. Uzamış mitotik tutuklama daha sonra apoptoz 13, 14 olur. Taksan monte tubulin 16 sadece mevcut olan β-tubulin 8, 15, ilgili taksan bağlanma sitesi üzerinden mikrotübüller ile etkileşime girer. Taksan direnç çok mekanizma 17 9 önerilmiştir. Bu mekanizmalar sayesinde ilaç akış proteinler ve taksan özgü direnci 5, 9, 18, 19 aşın hem genel hem de çoklu ilaç direncini kapsamaktadır. Örneğin, taksan dirençli kanser hücreleri, bazı β-küvet ekspresyonu ve fonksiyonunu değiştirmiş olabilirUlin 5, 9, 19, 20, 21, 22, 23 izotipleri. Mikrotübül Dinamik dengesizlik ölçmek için bir in vivo yöntem kullanarak, dirençli olmayan ebeveyn MCF-7 hücreleri CC 17 ile karşılaştırıldığında, dosetaksel dayanıklı MCF-7 TXT hücrelerin mikrotübül dinamiklerinin dosetaksel tedaviye duyarlı olduğunu göstermektedir. Daha iyi MTAs işlevini ve kanserli hücrelerde taksan direnci tam mekanizmasını anlamak için, mikrotübül dinamiklerini ölçmek için esastır. Burada, bu sayede, bir in vivo yöntem sunulmaktadır. Hücrelerinde GFP-etiketli tubulin sentezlenmesi ile birlikte canlı görüntüleme kullanarak, MCF-7 TXT ve MCF-7 hücreleri CC ve wi mikrotübül dinamiklerinin ölçebilirthout dosetaksel tedavisi. Sonuçlar bize taksan direncini aşmak için daha etkili ilaçlar tasarlamaya yardımcı olabilir.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Dulbecco&#39;s Modified Eagle&#39;s Medium (DMEM)</td>
			<td>Sigma-Aldrich</td>
			<td>D5796</td>
			<td></td>
		</tr>
		<tr>
			<td>Non-essential amino acids</td>
			<td>Life Technologies, Invitrogen</td>
			<td>11140-050</td>
			<td></td>
		</tr>
		<tr>
			<td>FBS</td>
			<td>Gibco, Invitrogen</td>
			<td>12483</td>
			<td></td>
		</tr>
		<tr>
			<td>Anti-Anti (100x)</td>
			<td>Life Technologies, Invitrogen</td>
			<td>15240-062</td>
			<td></td>
		</tr>
		<tr>
			<td>docetaxel</td>
			<td>Sigma-Aldrich</td>
			<td>01885-5mg-F</td>
			<td></td>
		</tr>
		<tr>
			<td>DMEM phenol red-free</td>
			<td>Gibco, Invitrogen</td>
			<td>21063</td>
			<td></td>
		</tr>
		<tr>
			<td>CellLight Reagent *BacMam 2.0* GFP-tubulin</td>
			<td>ThermoFisher Scientific</td>
			<td>C10613</td>
			<td>Key reagent for expressing GFP tubulin in cells</td>
		</tr>
		<tr>
			<td>CellLight Reagent *BacMam 2.0* GFP</td>
			<td>ThermoFisher Scientific</td>
			<td>B10383</td>
			<td>Control</td>
		</tr>
		<tr>
			<td>Dimethyl Sulfoxide (DMSO)</td>
			<td>Sigma-Aldrich+B9:AA9</td>
			<td>472301</td>
			<td>for dissoving decetaxel</td>
		</tr>
		<tr>
			<td>22-mm glass coveslip</td>
			<td>Fisher Scientifics</td>
			<td>12-545-101</td>
			<td></td>
		</tr>
		<tr>
			<td>6-well culture plate</td>
			<td>Greiner Bio-One International</td>
			<td>6 Well Celi Culture Plate</td>
			<td></td>
		</tr>
		<tr>
			<td>DeltaVision Microscopy Imaging Systems</td>
			<td>GE Health</td>
			<td></td>
			<td>This system is equipped with weather station for controlling temperature and CO2. It also equipped with Worx Software for deconvolution and time lapse control.</td>
		</tr>
		<tr>
			<td>Trypsin-EDTA (0.25%), phenol red</td>
			<td>ThermoFisher Scientific</td>
			<td>25200056</td>
			<td></td>
		</tr>
		<tr>
			<td>Bright-Line Hemacytometer Set, Hausser Scientific</td>
			<td>Hausser Scientific, Distributed by VWR</td>
			<td>Supplier No.: 1492 VWR No.:15170-172</td>
			<td></td>
		</tr>
	</tbody>
</table>

live imaging to study microtubule dynamic instability in taxane-resistant breast cancers

Taxanes such as docetaxel belong to a group of microtubule-targeting agents (MTAs) that are commonly relied upon to treat cancer. However, taxane resistance in cancerous cells drastically reduces the effectiveness of the drugs' long-term usage. Accumulated evidence suggests that the mechanisms underlying taxane resistance include both general mechanisms, such as the development of multidrug resistance due to the overexpression of drug-efflux proteins, and taxane-specific mechanisms, such as those that involve microtubule dynamics. 
Because taxanes target cell microtubules, measuring microtubule dynamic instability is an important step in determining the mechanisms of taxane resistance and provides insight into how to overcome this resistance. In the experiment, an in vivo method was used to measure microtubule dynamic instability. GFP-tagged &#945;-tubulin was expressed and incorporated into microtubules in MCF-7 cells, allowing for the recording of the microtubule dynamics by time lapse using a sensitive camera. The results showed that, as opposed to the non-resistant parental MCF-7CC cells, the microtubule dynamics of docetaxel-resistant MCF-7TXT cells are insensitive to docetaxel treatment, which causes the resistance to docetaxel-induced mitotic arrest and apoptosis. This paper will outline this in vivo method of measuring microtubule dynamic instability.

Burada sunulan protokolü kullanarak, (MCF-7 TXT) meme kanseri hücrelerinde (MCF-7 CC), normal ve dosetaksel dayanıklı mikrotübül dinamiklerine dosetaksel etkilerini inceledi. Görüntü iki takım MCF-7 CC ve MCF-7 TXT hücreleri (Şekil 1A) mikrotübül büyüme ve katı üzerine dosetaksel (0.5 uM) etkilerini göstermektedir. Ayrıca, iki hücre hatları içi...

Watch this Scientific Journal Video about Live Imaging to Study Microtubule Dynamic Instability in Taxane-resistant Breast Cancers at JoVE.com

Live Imaging to Study Microtubule Dynamic Instability in Taxane-resistant Breast Cancers

In this paper, we report a protocol describing an in vivo method to measure microtubule dynamic instability in docetaxel-resistant breast cancer cells (MCF-7TXT). In this method, a deconvolution microscopy imaging system is used to detect the expression of GFP-tubulin in target cells.

Canlı Görüntüleme taksan dirençli Meme Kanserlerinde Mikrotubul dinamik dengesizlik Eğitim için

Taxanes such as docetaxel belong to a group of microtubule-targeting agents (MTAs) that are commonly relied upon to treat cancer. However, taxane ...

live-imaging-to-study-microtubule-dynamic-instability-taxane

Education

Research

JoVE Core

JoVE Journal

Cell Biology

Molecular Biology

Cancer Research

Unit 2

Unit 1

Cell Division

The Cytoskeleton II: Microtubules and Intermediate Filaments

SCIENTISTS IN ACTION

7.5K Görüntüleme.  University of Alberta. In this paper, we report a protocol describing an in vivo method to measure microtubule dynamic instability in docetaxel-resistant breast cancer cells (MCF-7TXT). In this method, a deconvolution microscopy imaging system is used to detect the expression of GFP-tubulin in target cells. 

Video: Live Imaging to Study Microtubule Dynamic Instability in Taxane-resistant Breast Cancers

Utilizing Functional Genomics Screening to Identify Potentially Novel Drug Targets in Cancer Cell Spheroid Cultures

The identification of functional driver events in cancer is central to furthering our understanding of cancer biology and indispensable for the discovery of the next generation of novel drug targets. It is becoming apparent that more complex models of cancer are required to fully appreciate the contributing factors that drive tumorigenesis in vivo and increase the efficacy of novel therapies that make the transition from pre-clinical models to clinical trials.
Here we present a methodology for generating uniform and reproducible tumor spheroids that can be subjected to siRNA functional screening. These spheroids display many characteristics that are found in solid tumors that are not present in traditional two-dimension culture. We show that several commonly used breast cancer cell lines are amenable to this protocol. Furthermore, we provide proof-of-principle data utilizing the breast cancer cell line BT474, confirming their dependency on amplification of the epidermal growth factor receptor HER2 and mutation of phosphatidylinositol-4,5-biphosphate 3-kinase (PIK3CA) when grown as tumor spheroids. Finally, we are able to further investigate and confirm the spatial impact of these dependencies using immunohistochemistry.

Identifying novel drug targets that transition from pre-clinical testing to human trials is a scientific priority. To that end, here we describe a functional genomics approach for examining the impact of gene depletion on cancer cell line spheroids, which more appropriately model human cancers in vivo.

İşlevsel Genomik Tarama kullanılması Kanser Hücre Sfero Kültürleri Potansiyel Yeni İlaç Hedefleri Belirlemek İçin

The identification of functional driver events in cancer is central to furthering our understanding of cancer biology and indispensable for the discovery ...

Kanser Araştırmaları

A Portal Vein Injection Model to Study Liver Metastasis of Breast Cancer

Breast cancer is the leading cause of cancer-related mortality in women worldwide. Liver metastasis is involved in upwards of 30% of cases with breast cancer metastasis, and results in poor outcomes with median survival rates of only 4.8 - 15 months. Current rodent models of breast cancer metastasis, including primary tumor cell xenograft and spontaneous tumor models, rarely metastasize to the liver. Intracardiac and intrasplenic injection models do result in liver metastases, however these models can be confounded by concomitant secondary-site metastasis, or by compromised immunity due to removal of the spleen to avoid tumor growth at the injection site. To address the need for improved liver metastasis models, a murine portal vein injection method that delivers tumor cells firstly and directly to the liver was developed. This model delivers tumor cells to the liver without complications of concurrent metastases in other organs or removal of the spleen. The optimized portal vein protocol employs small injection volumes of 5 - 10 &#956;l, &#8805; 32 gauge needles, and hemostatic gauze at the injection site to control for blood loss. The portal vein injection approach in Balb/c female mice using three syngeneic mammary tumor lines of varying metastatic potential was tested; high-metastatic 4T1 cells, moderate-metastatic D2A1 cells, and low-metastatic D2.OR cells. Concentrations of &#8804; 10,000 cells/injection results in a latency of ~ 20 - 40 days for development of liver metastases with the higher metastatic 4T1 and D2A1 lines, and &#62; 55 days for the less aggressive D2.OR line. This model represents an important tool to study breast cancer metastasis to the liver, and may be applicable to other cancers that frequently metastasize to the liver including colorectal and pancreatic adenocarcinomas.

A surgical procedure was developed to deliver mammary tumor cells to the murine liver via portal vein injection. This model permits investigation of late stages of liver metastasis in a fully immune competent host, including tumor cell extravasation, seeding, survival, and metastatic outgrowth in the liver.

Bir Portal Ven Enjeksiyon Modeli Karaciğer Metastazı Meme Kanseri Eğitim için

Breast cancer is the leading cause of cancer-related mortality in women worldwide. Liver metastasis is involved in upwards of 30% of cases with breast ...

Live-imaging of Breast Epithelial Cell Migration After the Transient Depletion of TIP60

The wound-healing assay is efficient and one of the most economical ways to study cell migration in vitro. Conventionally, images are taken at the beginning and end of an experiment using a phase-contrast microscope, and the migration abilities of cells are evaluated by the closure of wounds. However, cell movement is a dynamic phenomenon, and a conventional method does not allow for tracking single-cell movement. To improve current wound-healing assays, we use live-cell imaging techniques to monitor cell migration in real time. This method allows us to determine the cell migration rate based on a cell tracking system and provides a clearer distinction between cell migration and cell proliferation. Here, we demonstrate the use of live-cell imaging in wound-healing assays to study the different migration abilities of breast epithelial cells influenced by the presence of TIP60. As cell motility is highly dynamic, our method provides more insights into the processes of wound healing than a snapshot of wound closure taken with the traditional imaging techniques used for wound-healing assays.

Here, we present the real-time monitoring of cell migration in a wound-healing assay using TIP60-depleted MCF10A breast epithelial cells. The implementation of live-cell imaging techniques in our protocol allows us to analyze and visualize single-cell movement in real time and across time.

Meme epitel hücre göç TIP60 geçici tükenmesi sonra canlı görüntüleme

The wound-healing assay is efficient and one of the most economical ways to study cell migration in vitro. Conventionally, images are taken at the ...

Long-term Live-cell Imaging to Assess Cell Fate in Response to Paclitaxel

Live-cell imaging is a powerful technique that can be used to directly visualize biological phenomena in single cells over extended periods of time. Over the past decade, new and innovative technologies have greatly enhanced the practicality of live-cell imaging. Cells can now be kept in focus and continuously imaged over several days while maintained under 37 &#176;C and 5% CO2 cell culture conditions. Moreover, multiple fields of view representing different experimental conditions can be acquired simultaneously, thus providing high-throughput experimental data. Live-cell imaging provides a significant advantage over fixed-cell imaging by allowing for the direct visualization and temporal quantitation of dynamic cellular events. Live-cell imaging can also identify variation in the behavior of single cells that would otherwise have been missed using population-based assays. Here, we describe live-cell imaging protocols to assess cell fate decisions following treatment with the anti-mitotic drug paclitaxel. We demonstrate methods to visualize whether mitotically arrested cells die directly from mitosis or slip back into interphase. We also describe how the fluorescent ubiquitination-based cell cycle indicator (FUCCI) system can be used to assess the fraction of interphase cells born from mitotic slippage that are capable of re-entering the cell cycle. Finally, we describe a live-cell imaging method to identify nuclear envelope rupture events.

Live-cell imaging provides a wealth of information on single cells or whole populations that is unattainable by fixed cell imaging alone. Here, live-cell imaging protocols to assess cell fate decisions following treatment with the anti-mitotic drug paclitaxel are described.

Uzun vadeli canlı hücre kader Paklitaksel karşılık olarak değerlendirmek için Imaging hücreli

Live-cell imaging is a powerful technique that can be used to directly visualize biological phenomena in single cells over extended periods of time. Over ...

Live-Cell Imaging Assays to Study Glioblastoma Brain Tumor Stem Cell Migration and Invasion

Glioblastoma (GBM) is an aggressive brain tumor that is poorly controlled with the currently available treatment options. Key features of GBMs include rapid proliferation and pervasive invasion into the normal brain. Recurrence is thought to result from the presence of radio- and chemo-resistant brain tumor stem cells (BTSCs) that invade away from the initial cancerous mass and, thus, evade surgical resection. Hence, therapies that target BTSCs and their invasive abilities may improve the otherwise poor prognosis of this disease. Our group and others have successfully established and characterized BTSC cultures from GBM patient samples. These BTSC cultures demonstrate fundamental cancer stem cell properties such as clonogenic self-renewal, multi-lineage differentiation, and tumor initiation in immune-deficient mice. In order to improve on the current therapeutic approaches for GBM, a better understanding of the mechanisms of BTSC migration and invasion is necessary. In GBM, the study of migration and invasion is restricted, in part, due to the limitations of existing techniques which do not fully account for the in vitro growth characteristics of BTSCs grown as neurospheres. Here, we describe rapid and quantitative live-cell imaging assays to study both the migration and invasion properties of BTSCs. The first method described is the BTSC migration assay which measures the migration toward a chemoattractant gradient. The second method described is the BTSC invasion assay which images and quantifies a cellular invasion from neurospheres into a matrix. The assays described here are used for the quantification of BTSC migration and invasion over time and under different treatment conditions.

Here, we describe live-cell imaging techniques to quantitatively measure the migration and invasion of glioblastoma brain tumor stem cells over time and under multiple treatment conditions.

Canlı hücre görüntüleme deneyleri için çalışma Glioblastoma Beyin tümör kök hücre göç ve işgali

Glioblastoma (GBM) is an aggressive brain tumor that is poorly controlled with the currently available treatment options. Key features of GBMs include ...

Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited therapeutic options. When compared to patients with less aggressive breast tumors, the 5-year survival rate of TNBC patients is 77% due to their characteristic drug-resistant phenotype and metastatic burden. Toward this end, murine models have been established aimed at identifying novel therapeutic strategies limiting TNBC tumor growth and metastatic spread. This work describes a practical guide for the TNBC orthotopic model where MDA-MB-231 breast cancer cells suspended in a basement membrane matrix are implanted in the fourth mammary fat pad, which closely mimics the cancer cell behavior in humans. Measurement of tumors by caliper, lung metastasis assessment via in vivo and ex vivo imaging, and molecular detection are discussed. This model provides an excellent platform to study therapeutic efficacy and is especially suitable for the study of the interaction between the primary tumor and distal metastatic sites.

This work presets an advanced protocol to accurately assess tumor loading by detection of green fluorescent protein and bioluminescence signals as well as the integration of quantitative molecular detection technique.

Ortotopik Meme Kanseri Modeli Kullanarak Üçlü Negatif Meme Kanseri Eğitimi

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited therapeutic options. When compared to patients with less ...

Using the Chicken Chorioallantoic Membrane In Vivo Model to Study Gynecological and Urological Cancers

Mouse models are the benchmark tests for in vivo cancer studies. However, cost, time, and ethical considerations have led to calls for alternative in vivo cancer models. The chicken chorioallantoic membrane (CAM) model provides an inexpensive, rapid alternative that permits direct visualization of tumor development and is suitable for in vivo imaging. As such, we sought to develop an optimized protocol for engrafting gynecological and urological tumors into this model, which we present here. Approximately 7 days postfertilization, the air cell is moved to the vascularized side of the egg, where an opening is created in the shell. Tumors from murine and human cell lines and primary tissues can then be engrafted. These are typically seeded in a mixture of extracellular matrix and medium to avoid cellular dispersal and provide nutrient support until the cells recruit a vascular supply. Tumors may then grow for up to an additional 14 days prior to the eggs hatching. By implanting cells stably transduced with firefly luciferase, bioluminescence imaging can be used for the sensitive detection of tumor growth on the membrane and cancer cell spread throughout the embryo. This model can potentially be used to study tumorigenicity, invasion, metastasis, and therapeutic effectiveness. The chicken CAM model requires significantly less time and financial resources compared to traditional murine models. Because the eggs are immunocompromised and immune tolerant, tissues from any organism can potentially be implanted without costly transgenic animals (e.g., mice) required for implantation of human tissues. However, many of the advantages of this model could potentially also be limitations, including the short tumor generation time and immunocompromised/immune tolerant status. Additionally, although all tumor types presented here engraft in the chicken chorioallantoic membrane model, they do so with varying degrees of tumor growth.

We present the chicken chorioallantoic membrane model as an alternative, transplantable, in vivo model for the engraftment of gynecological and urological cancer cell lines and patient-derived tumors.

Jinekolojik ve Ürolojik Kanserleri Incelemek Için Vivo Modelinde Tavuk Chorioallantoic Membran Kullanma

Mouse models are the benchmark tests for in vivo cancer studies. However, cost, time, and ethical considerations have led to calls for alternative in vivo ...

Using Computer-based Image Analysis to Improve Quantification of Lung Metastasis in the 4T1 Breast Cancer Model

Breast cancer is a devastating malignancy, accounting for 40,000 female deaths and 30% of new female cancer diagnoses in the United States in 2019 alone. The leading cause of breast cancer related deaths is the metastatic burden. Therefore, preclinical models for breast cancer need to analyze metastatic burden to be clinically relevant. The 4T1 breast cancer model provides a spontaneously-metastasizing, quantifiable mouse model for stage IV human breast cancer. However, most 4T1 protocols quantify the metastatic burden by manually counting stained colonies on tissue culture plates. While this is sufficient for tissues with lower metastatic burden, human error in manual counting causes inconsistent and variable results when plates are confluent and difficult to count. This method offers a computer-based solution to human counting error. Here, we evaluate the protocol using the lung, a highly metastatic tissue in the 4T1 model. Images of methylene blue-stained plates are acquired and uploaded for analysis in Fiji-ImageJ. Fiji-ImageJ then determines the percentage of the selected area of the image that is blue, representing the percentage of the plate with metastatic burden. This computer-based approach offers more consistent and expeditious results than manual counting or histopathological evaluation for highly metastatic tissues. The consistency of Fiji-ImageJ results depends on the quality of the image. Slight variations in results between images can occur, thus it is recommended that multiple images are taken and results averaged. Despite its minimal limitations, this method is an improvement to quantifying metastatic burden in the lung by offering consistent and rapid results.

We describe a more consistent and expeditious method to quantify lung metastasis in the 4T1 breast cancer model by using Fiji-ImageJ.

4T1 Meme Kanseri Modelinde Akciğer Metastazının Nicelleştirilmesini Geliştirmek Için Bilgisayar Tabanlı Görüntü Analizinin Kullanılması

Breast cancer is a devastating malignancy, accounting for 40,000 female deaths and 30% of new female cancer diagnoses in the United States in 2019 alone. ...

Modeling Breast Cancer in Human Breast Tissue using a Microphysiological System

Breast cancer (BC) remains a leading cause of death for women. Despite more than $700 million invested in BC research annually, 97% of candidate BC drugs fail clinical trials. Therefore, new models are needed to improve our understanding of the disease. The NIH Microphysiological Systems (MPS) program was developed to improve the clinical translation of basic science discoveries and promising new therapeutic strategies. Here we present a method for generating MPS for breast cancers (BC-MPS). This model adapts a previously described approach of culturing primary human white adipose tissue (WAT) by sandwiching WAT between adipose-derived stem cell sheets (ASC)s. Novel aspects of our BC-MPS include seeding BC cells into non-diseased human breast tissue (HBT) containing native extracellular matrix, mature adipocytes, resident fibroblasts, and immune cells; and sandwiching the BC-HBT admixture between HBT-derived ASC sheets. The resulting BC-MPS is stable in culture ex vivo for at least 14 days. This model system contains multiple elements of the microenvironment that influence BC including adipocytes, stromal cells, immune cells, and the extracellular matrix. Thus BC-MPS can be used to study the interactions between BC and its microenvironment. 
We demonstrate the advantages of our BC-MPS by studying two BC behaviors known to influence cancer progression and metastasis: 1) BC motility and 2) BC-HBT metabolic crosstalk. While BC motility has previously been demonstrated using intravital imaging, BC-MPS allows for high-resolution time-lapse imaging using fluorescence microscopy over several days. Furthermore, while metabolic crosstalk was previously demonstrated using BC cells and murine pre-adipocytes differentiated into immature adipocytes, our BC-MPS model is the first system to demonstrate this crosstalk between primary human mammary adipocytes and BC cells in vitro.

This protocol describes the construction of an in vitro microphysiological system for studying breast cancer using primary human breast tissue with off the shelf materials.

Mikrofizyolojik Sistem Kullanarak İnsan Meme Dokusunda Meme Kanseri Modellemesi

Breast cancer (BC) remains a leading cause of death for women. Despite more than $700 million invested in BC research annually, 97% of candidate BC drugs ...

A Murine Ommaya Xenograft Model to Study Direct-Targeted Therapy of Leptomeningeal Disease

Leptomeningeal disease (LMD) is an uncommon type of central nervous system (CNS) metastasis to the cerebral spinal fluid (CSF). The most common cancers that cause LMD are breast and lung cancers and melanoma. Patients diagnosed with LMD have a very poor prognosis and generally survive for only a few weeks or months. One possible reason for the lack of efficacy of systemic therapy against LMD is the failure to achieve therapeutically effective concentrations of drug in the CSF because of an intact and relatively impermeable blood-brain barrier (BBB) or blood-CSF barrier across the choroid plexus. Therefore, directly administering drugs intrathecally or intraventricularly may overcome these barriers. This group has developed a model that allows for the effective delivery of therapeutics (i.e., drugs, antibodies, and cellular therapies) chronically and the repeated sampling of CSF to determine drug concentrations and target modulation in the CSF (when the tumor microenvironment is targeted in mice). The model is the murine equivalent of a magnetic resonance imaging-compatible Ommaya reservoir, which is used clinically. This model, which is affixed to the skull, has been designated as the &#34;Murine Ommaya.&#34; As a therapeutic proof of concept, human epidermal growth factor receptor 2 antibodies (clone 7.16.4) were delivered into the CSF via the Murine Ommaya to treat mice with LMD from human epidermal growth factor receptor 2-positive breast cancer. The Murine Ommaya increases the efficiency of drug delivery using a miniature access port and prevents the wastage of excess drug; it does not interfere with CSF sampling for molecular and immunological studies. The Murine Ommaya is useful for testing novel therapeutics in experimental models of LMD.

Here, we describe a murine xenograft model that functionally resembles an Ommaya reservoir in patients. We developed the Murine Ommaya to study novel therapeutics for the universally fatal leptomeningeal disease.

Leptomeningeal Hastalığın Doğrudan Hedefli Tedavisini Incelemek için Bir Murine Ommaya Xenograft Modeli

Leptomeningeal disease (LMD) is an uncommon type of central nervous system (CNS) metastasis to the cerebral spinal fluid (CSF). The most common cancers ...