This application addresses Broad Challenge Area (08) Genomics and Specific Challenge Topic 08-CA-103: Micro-RNAs in Cancer. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression by reducing stability and/or translation of fully or partially sequence-complementary target mRNAs (Eulalio et al., 2008;Friedman et al., 2009). Several hundred miRNA gene families have been identified in mammals (Landgraf et al., 2007), many of which are expressed in specific tissues and have been found to be dysregulated in tumors (reviewed in Ventura and Jacks, 2009). miRNA profiles have been correlated to particular tumors, based on their cell of origin, and in some cases to prognosis (Lu et al., 2005;He et al., 2005;Yanaihara et al., 2006). Because miRNAs alter the expression of multiple genes and thereby may be tuning multiple regulatory steps in disease pathways, they represent interesting drug targets;antisense oligonucleotide targeting experiments in mice (Krutzfeldt et al., 2005) and non-human primates (Elmen et al., 2008) have demonstrated the feasibility of manipulating miRNA levels. At the same time, elucidating miRNA target networks may shed important insights for defining regulatory processes contributing to cancer. The overall aim of this proposal is to advance small RNA profiling and small RNA histological methods for cost-effective characterization of large numbers of patient samples. To interpret the alterations observed in miRNA expression patterns, we will apply our recently developed powerful biochemical approach for direct sequencing of miRNA-targeted mRNA networks to relevant tumor cell culture models. Finally, these recent developments will be implemented in breast cancer research analyzing 177 histologically and clinically characterized tumor samples. First, RNA-deep-sequencing-based methods will be to a stage where they are suitable to define miRNA expression patterns and mutational status for large numbers of clinical samples with limited material. Second, alterations detected in miRNA expression patterns will be followed by miRNA in situ hybridization, for which we recently developed new small RNA fixation techniques and overcame the biggest obstacle hindering miRNA histological detection in tissue sections. Third, to gain insights into the biology of miRNA deregulation, we will apply our recently developed Photoreactive-Uridine-Enhanced Crosslinking and Immunoprecipitation (PURE- CLIP) method of miRNA-bound Argonaute protein complexes to identify the miRNA target sites in transcriptomes of tumor cells. In the last aim, we will apply our methods to assess the value of miRNA analysis in a large collection of triple negative (HER2 gene amplification, Estrogen Receptor (ER), and Progesterone Receptor (PR) negative) and other types of breast tumors in collaboration with Marc van de Vijver at the Academic Medical Center in Amsterdam, The Netherlands. The specimen collection includes 80 triple negative, 51 HER2 positive, 26 ER positive, 11 normal and 20 ductal carcinoma in situ (DCIS) samples. These specimens are already characterized histologically, as well as at the mRNA transcript expression level, and patient clinical characteristics and outcome are available. We will determine absolute miRNA content, relative miRNA composition or profile, miRNA mutational status, and miRNA expression patterns and assess correlations with already determined clinical parameters. We will also define the miRNA-target RNA regulatory networks in tumor cells to be able to interpret consequences of miRNA deregulation in breast cancer. Developing miRNA diagnostic methods and identifying miRNA regulatory networks in tumors

Public Health Relevance

miRNAs are recently identified small non-coding RNAs that regulate many developmental and physiological processes including cancer. This proposal aims to develop new small RNA cloning protocols to meet requirements in clinical research, enhance in situ hybridization methods for cellular localization of miRNAs and at the same time adapt these methods for use in automated platforms of diagnostic laboratories, and clarify miRNA regulatory networks in cancer cell lines, by adapting our recently developed method for identification of miRNA mRNA targets.

National Institute of Health (NIH)
National Cancer Institute (NCI)
NIH Challenge Grants and Partnerships Program (RC1)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-GGG-F (58))
Program Officer
Tricoli, James
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Rockefeller University
Other Domestic Higher Education
New York
United States
Zip Code
Farazi, Thalia A; Hoell, Jessica I; Morozov, Pavel et al. (2013) MicroRNAs in human cancer. Adv Exp Med Biol 774:1-20
Farazi, Thalia A; Brown, Miguel; Morozov, Pavel et al. (2012) Bioinformatic analysis of barcoded cDNA libraries for small RNA profiling by next-generation sequencing. Methods 58:171-87
Skalsky, Rebecca L; Corcoran, David L; Gottwein, Eva et al. (2012) The viral and cellular microRNA targetome in lymphoblastoid cell lines. PLoS Pathog 8:e1002484
Scheibe, Marion; Butter, Falk; Hafner, Markus et al. (2012) Quantitative mass spectrometry and PAR-CLIP to identify RNA-protein interactions. Nucleic Acids Res 40:9897-902
Hafner, Markus; Renwick, Neil; Farazi, Thalia A et al. (2012) Barcoded cDNA library preparation for small RNA profiling by next-generation sequencing. Methods 58:164-70
Hafner, Markus; Lianoglou, Steve; Tuschl, Thomas et al. (2012) Genome-wide identification of miRNA targets by PAR-CLIP. Methods 58:94-105
Spitzer, Jessica I; Ugras, Stacy; Runge, Simon et al. (2011) mRNA and protein levels of FUS, EWSR1, and TAF15 are upregulated in liposarcoma. Genes Chromosomes Cancer 50:338-47
Farazi, Thalia A; Spitzer, Jessica I; Morozov, Pavel et al. (2011) miRNAs in human cancer. J Pathol 223:102-15
Farazi, Thalia A; Horlings, Hugo M; Ten Hoeve, Jelle J et al. (2011) MicroRNA sequence and expression analysis in breast tumors by deep sequencing. Cancer Res 71:4443-53
Hafner, Markus; Renwick, Neil; Brown, Miguel et al. (2011) RNA-ligase-dependent biases in miRNA representation in deep-sequenced small RNA cDNA libraries. RNA 17:1697-712

Showing the most recent 10 out of 11 publications