AbstractQuantitative reverse transcription-polymerase chain reaction (qRT-PCR) is a valuable tool for measuring gene expression in biological samples. However, unique challenges are encountered when studies are performed on cells microdissected from tissues derived from animal models or the clinic, including specimen-related issues, variability of RNA template quality and quantity, and normalization. qRT-PCR using small amounts of mRNA derived from dissected cell populations requires adaptation of standard methods to allow meaningful comparisons across sample sets. The protocol described here presents the rationale, technical steps, normalization strategy and data analysis necessary to generate reliable gene expression measurements of transcripts from dissected samples. The entire protocol from tissue microdissection through qRT-PCR analysis requires 鈭?/span>
16 h. Subscription info for Chinese customersWe have a dedicated website for our Chinese customers. Please go to naturechina.com to subscribe to this journal.Go to naturechina.comRent or Buy articleGet time limited or full article access on ReadCube.from$8.99Rent or BuyAll prices are NET prices. Figure 1: Tissue sectioning and staining flowchart.Figure 2: Frozen prostate epithelium laser capture microdissection (LCM) procurement sequence.Figure 3: qRT-PCR from microdissected tissue process flowchart.Figure 4: Dedicated RT-PCR hood setup.Figure 5: Example qPCR 96-well setup.Figure 6: Typical TaqMan qPCR amplification plots for 96-well setup. References1Best, C.J. et al. Molecular differentiation of high- and moderate-grade human prostate cancer by cDNA microarray analysis. Diagn. Mol. Pathol. 12, 63鈥?0 (2003).Article聽 CAS聽Google Scholar聽 2Best, C.J. et al. Molecular alterations in primary prostate cancer after androgen ablation therapy. Clin. 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R.F.C. and M.R.E.-B. are Federal employee inventors on NIH patents covering LCM and xMD technologies and are entitled to receive royalty payments through the NIH Technology Transfer program. This research was supported by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research.Author informationAffiliationsPathogenetics Unit, Laboratory of Pathology and Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USAHeidi S Erickson,聽Jaime Rodriguez-Canales,聽Rodrigo F Chuaqui聽 聽Michael R Emmert-BuckDivision of Cancer Treatment and Diagnosis, Biometric Research Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USAPaul S Albert SAIC-Frederick Inc., National Cancer Institute at Frederick, Frederick, Maryland, USA John W GillespieUrologic Oncology Branch, National Cancer Institute, National Institutes of Health, Maryland, USAW Marston Linehan聽 聽Peter A PintoAuthorsHeidi S EricksonView author publicationsYou can also search for this author in PubMed聽Google ScholarPaul S AlbertView author publicationsYou can also search for this author in PubMed聽Google ScholarJohn W GillespieView author publicationsYou can also search for this author in PubMed聽Google ScholarJaime Rodriguez-CanalesView author publicationsYou can also search for this author in PubMed聽Google ScholarW Marston LinehanView author publicationsYou can also search for this author in PubMed聽Google ScholarPeter A PintoView author publicationsYou can also search for this author in PubMed聽Google ScholarRodrigo F ChuaquiView author publicationsYou can also search for this author in PubMed聽Google ScholarMichael R Emmert-BuckView author publicationsYou can also search for this author in PubMed聽Google ScholarCorresponding authorCorrespondence to Michael R Emmert-Buck.Rights and permissionsReprints and PermissionsAbout this articleCite this articleErickson, H., Albert, P., Gillespie, J. et al. Quantitative RT-PCR gene expression analysis of laser microdissected tissue samples. Nat Protoc 4, 902鈥?22 (2009). https://doi.org/10.1038/nprot.2009.61Download citationPublished: 21 May 2009Issue Date: June 2009DOI: https://doi.org/10.1038/nprot.2009.61 Xiaofei Liu, Yu Zheng, Gefu Wang-Pruski, Yun Gan, Bo Zhang, Qiyong Hu, Yixin Du, Jianwei Zhao Lihua Liu European Journal of Plant Pathology (2019) Parisa Amini, Julia Ettlin, Lennart Opitz, Elena Clementi, Alexandra Malbon Enni Markkanen BMC Molecular Biology (2017) Elisabeth Letellier, Martine Schmitz, Aur茅lien Ginolhac, Fabien Rodriguez, Pit Ullmann, Komal Qureshi-Baig, Sonia Frasquilho, Laurent Antunes Serge Haan British Journal of Cancer (2017) CommentsBy submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate. 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