BACKGROUND: Segregation of the trophectoderm from the inner cell mass of the embryo represents the first cell-fate decision of mammalian development. Transcription factors essential for specifying trophectoderm have been identified, but the role of microRNAs (miRNAs) in modulating this fate-choice has been largely unexplored. We have compared miRNA expression in embryonic stem cell (ESC)-derived trophectoderm and in staged murine embryos to identify a set of candidate miRNAs likely to be involved in trophectoderm specification. RESULTS: We profiled embryonic stem cells (ESCs) as they were induced to differentiate into trophectodermal cells by ectopic expression of HRas/Q61L. We also profiled murine embryos at progressive stages of preimplantation development (zygote, 2-cell, 4-cell, 8-cell, morula, and blastocyst), which includes the time window in which the trophectoderm is specified in vivo Q61L/H. CONCLUSIONS: We describe miRNA expression changes that occur during trophectoderm specification and validate that our in vitro system faithfully recapitulates trophectoderm specification in vivo. By comparing our in vitro and in vivo datasets, we have identified a minimal set of candidate miRNAs likely to play a role in trophectoderm specification. These miRNAs are predicted to regulate a host of development-associated target genes, and many of these miRNAs have previously reported roles in development and differentiation. Additionally, we highlight a number of miRNAs whose tight developmental regulation may reflect a functional role in other stages of embryogenesis. Our embryo profiling data may be useful to investigators studying trophectoderm specification and other stages of preimplantation development.

Multiple members of the let-7 family of miRNAs are often repressed in human cancers, thereby promoting oncogenesis by derepressing targets such as HMGA2, K-Ras and c-Myc. However, the mechanism by which let-7 miRNAs are coordinately repressed is unclear. The RNA-binding proteins LIN28 and LIN28B block let-7 precursors from being processed to mature miRNAs, suggesting that their overexpression might promote malignancy through repression of let-7. Here we show that LIN28 and LIN28B are overexpressed in primary human tumors and human cancer cell lines (overall frequency approximately 15%), and that overexpression is linked to repression of let-7 family miRNAs and derepression of let-7 targets. LIN28 and LIN28b facilitate cellular transformation in vitro, and overexpression is associated with advanced disease across multiple tumor types. Our work provides a mechanism for the coordinate repression of let-7 miRNAs observed in a subset of human cancers, and associates activation of LIN28 and LIN28B with poor clinical prognosis.

Somatic rearrangements of transcription factors are common abnormalities in the acute leukemias. With rare exception, however, the resultant protein products have remained largely intractable as pharmacologic targets. One example is AML1-ETO, the most common translocation reported in acute myeloid leukemia (AML). To identify AML1-ETO modulators, we screened a small molecule library using a chemical genomic approach. Gene expression signatures were used as surrogates for the expression versus loss of the translocation in AML1-ETO-expressing cells. The top classes of compounds that scored in this screen were corticosteroids and dihydrofolate reductase (DHFR) inhibitors. In addition to modulating the AML1-ETO signature, both classes induced evidence of differentiation, dramatically inhibited cell viability, and ultimately induced apoptosis via on-target activity. Furthermore, AML1-ETO-expressing cell lines were exquisitely sensitive to the effects of corticosteroids on cellular viability compared with nonexpressers. The corticosteroids diminished AML1-ETO protein in AML cells in a proteasome- and glucocorticoid receptor-dependent manner. Moreover, these molecule classes demonstrated synergy in combination with standard AML chemotherapy agents and activity in an orthotopic model of AML1-ETO-positive AML. This work suggests a role for DHFR inhibitors and corticosteroids in treating patients with AML1-ETO-positive disease.

The aberrant activation of tyrosine kinases represents an important oncogenic mechanism, and yet the majority of such events remain undiscovered. Here we describe a bead-based method for detecting phosphorylation of both wild-type and mutant tyrosine kinases in a multiplexed, high-throughput and low-cost manner. With the aim of establishing a tyrosine kinase-activation catalog, we used this method to profile 130 human cancer lines. Follow-up experiments on the finding that SRC is frequently phosphorylated in glioblastoma cell lines showed that SRC is also activated in primary glioblastoma patient samples and that the SRC inhibitor dasatinib (Sprycel) inhibits viability and cell migration in vitro and tumor growth in vivo. Testing of dasatinib-resistant tyrosine kinase alleles confirmed that SRC is indeed the relevant target of dasatinib, which inhibits many tyrosine kinases. These studies establish the feasibility of tyrosine kinome-wide phosphorylation profiling and point to SRC as a possible therapeutic target in glioblastoma.

Cell-based screening can facilitate the rapid identification of compounds inducing complex cellular phenotypes. Advancing a compound toward the clinic, however, generally requires the identification of precise mechanisms of action. We previously found that epidermal growth factor receptor (EGFR) inhibitors induce acute myeloid leukemia (AML) differentiation via a non-EGFR mechanism. In this report, we integrated proteomic and RNAi-based strategies to identify their off-target, anti-AML mechanism. These orthogonal approaches identified Syk as a target in AML. Genetic and pharmacological inactivation of Syk with a drug in clinical trial for other indications promoted differentiation of AML cells and attenuated leukemia growth in vivo. These results demonstrate the power of integrating diverse chemical, proteomic, and genomic screening approaches to identify therapeutic strategies for cancer.

Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, and prior attempts to develop genomic-based classification for HCC have yielded highly divergent results, indicating difficulty in identifying unified molecular anatomy. We performed a meta-analysis of gene expression profiles in data sets from eight independent patient cohorts across the world. In addition, aiming to establish the real world applicability of a classification system, we profiled 118 formalin-fixed, paraffin-embedded tissues from an additional patient cohort. A total of 603 patients were analyzed, representing the major etiologies of HCC (hepatitis B and C) collected from Western and Eastern countries. We observed three robust HCC subclasses (termed S1, S2, and S3), each correlated with clinical parameters such as tumor size, extent of cellular differentiation, and serum alpha-fetoprotein levels. An analysis of the components of the signatures indicated that S1 reflected aberrant activation of the WNT signaling pathway, S2 was characterized by proliferation as well as MYC and AKT activation, and S3 was associated with hepatocyte differentiation. Functional studies indicated that the WNT pathway activation signature characteristic of S1 tumors was not simply the result of beta-catenin mutation but rather was the result of transforming growth factor-beta activation, thus representing a new mechanism of WNT pathway activation in HCC. These experiments establish the first consensus classification framework for HCC based on gene expression profiles and highlight the power of integrating multiple data sets to define a robust molecular taxonomy of the disease.

Calcium signaling is a central regulator of cardiomyocyte growth and function. Calmodulin is a critical mediator of calcium signals. Because the amount of calmodulin within cardiomyocytes is limiting, the precise control of calmodulin expression is important for the regulation of calcium signaling. In this study, we show for the first time that calmodulin levels are regulated posttranscriptionally in heart failure. The cardiomyocyte-restricted microRNA miR-1 inhibited the translation of calmodulin-encoding mRNAs via highly conserved target sites within their 3' untranslated regions. In keeping with its effect on calmodulin expression, miR-1 downregulated calcium-calmodulin signaling through calcineurin to NFAT. miR-1 also negatively regulated the expression of Mef2a and Gata4, key transcription factors that mediate calcium-dependent changes in gene expression. Consistent with the downregulation of these hypertrophy-associated genes, miR-1 attenuated cardiomyocyte hypertrophy in cultured neonatal rat cardiomyocytes and in the intact adult heart. Our data indicate that miR-1 regulates cardiomyocyte growth responses by negatively regulating the calcium signaling components calmodulin, Mef2a, and Gata4.

While the global down-regulation of microRNAs (miRNAs) is a common feature of human tumors, its genetic basis is largely undefined. To explore this question, we analyzed the consequences of conditional Dicer1 mutation (Dicer1 "floxed" or Dicer1(fl)) on several mouse models of cancer. Here we show Dicer1 functions as a haploinsufficient tumor suppressor gene. Deletion of a single copy of Dicer1 in tumors from Dicer1(fl/+) animals led to reduced survival compared with controls. These tumors exhibited impaired miRNA processing but failed to lose the wild-type Dicer1 allele. Moreover, tumors from Dicer1(fl/fl) animals always maintained one functional Dicer1 allele. Consistent with selection against full loss of Dicer1 expression, enforced Dicer1 deletion caused inhibition of tumorigenesis. Analysis of human cancer genome copy number data reveals frequent deletion of DICER1. Importantly, however, the gene has not been reported to undergo homozygous deletion, suggesting that DICER1 is haploinsufficient in human cancer. These findings suggest Dicer1 may be an important haploinsufficient tumor suppressor gene and, furthermore, that other factors controlling miRNA biogenesis may also function in this manner.

BACKGROUND: Advances in mass spectrometry-based proteomics have enabled the incorporation of proteomic data into systems approaches to biology. However, development of analytical methods has lagged behind. Here we describe an empirical Bayes framework for quantitative proteomics data analysis. The method provides a statistical description of each experiment, including the number of proteins that differ in abundance between 2 samples, the experiment's statistical power to detect them, and the false-positive probability of each protein. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed 2 types of mass spectrometric experiments. First, we showed that the method identified the protein targets of small-molecules in affinity purification experiments with high precision. Second, we re-analyzed a mass spectrometric data set designed to identify proteins regulated by microRNAs. Our results were supported by sequence analysis of the 3' UTR regions of predicted target genes, and we found that the previously reported conclusion that a large fraction of the proteome is regulated by microRNAs was not supported by our statistical analysis of the data. CONCLUSIONS/SIGNIFICANCE: Our results highlight the importance of rigorous statistical analysis of proteomic data, and the method described here provides a statistical framework to robustly and reliably interpret such data.