MicroRNA Deregulation in Mesenchymal Transformation and Sarcomagenesis
1. Development and Characterization of in vitro SMC Differentiation of Mesenchymal Stem Cells (MSCs)
To characterize the molecular basis of LMS, it is crucial to understand the normal biology of SMC differentiation. To this end, we have developed and characterized an in vitro model of SMC differentiation, identified the miRNA ‘signature’ (Figure 1) of this differentiation and have begun to develop tools to investigate the role that these miRNAs (and their targets) play in SMC differentiation.
We have developed an in vitro smooth-muscle cell (SMC) differentiation system from human mesenchymal stem cells (hMSCs) to SMCs adapting a previously published protocol. Briefly, hMSCs acquired from Dr. Prockop’s Lab (Tulane University) were cultured to near confluency, at which time smooth muscle differentiation medium (SMDM) was added. At various timepoints after induction of differentiation (0, 1, 2, 5, 7, 10, 14, 21, 28, 35, and 42 days) cells are collected for RNA extraction, and glass slides seeded with cells are fixed for future immunofluorescence (IF) studies. To date, we have successfully reproduced and characterized the differentiation of hMSCs to SMCs no less than 5 times. The differentiation state of SMCs is determined by morphology of cells as examined by phase contrast microscopy, as well as reverse transcriptase polymerase chain reaction (RT-PCR), IF, and fluorescence-activated cell sorting (FACS) analysis of specific markers. Additionally, the contractile function of differentiated SMCs was assayed using established protocols.
Our data demonstrates that by 14 days after induction of differentiation, the hMSCs begin to form "hills and valleys" and visible fibers can be seen within the cytoplasm of the cells, both characteristics of cultured SMCs (Figure 2).
This distinct SMC morphology coincides with induction, as assayed by RT-PCR, of multiple SMC markers including SM-MHC and reduced expression of hMSC markers, including CD73 (Figure 3).
Induction of ASMA and loss of CD105 can also be seen by IF (Figure 4). Functional assays indicate that after 21 days in SMDM the cells have acquired the capacity to contract.
To define the miRNA ‘signature’ of SMC differentiation, total RNA was extracted from various timepoints during differentiation and hybridized to ‘early release’ Agilent miRNA microarrays containing the mature miRNA sequences for all miRNAs according to Sanger miRBase Version 9.2. Raw intensity values were obtained from the arrays with Agilent’s Feature Extractor software and translated to ‘total gene signal’ values by subtracting background. Total gene signals found to be less than background were flagged as ‘undetectable’. The preliminary data consists of two independent timecourses. Corresponding timepoints for each timecourse are being used as biological duplicates.
Our collaborator, Dr. Nicholas D. Socci (Computational Biology Center, Memorial Sloan-Kettering Cancer Center) then performed quantile normalization and generalized log transformation to produce normalized values for analysis. At this point, any miRNA found to be ‘undetectable’ in 50% or more of the samples across the timecourse was eliminated from further analysis. To determine which miRNAs are altered during differentiation, a J.T. trend test was performed. A comparison was made between the first timepoint (t=0) and the end timepoint (in this case t=28 for one timecourse and t=35 for the biological duplicate). All trend test results were limited to a false discovery rate (FDR) of less than 0.09. Because of low sample numbers, we have been unable, at this time, to run computational analyses for more dynamic expression patterns, ie, miRNAs with a biphasic expression pattern. Additional samples have been submitted which will allow more complex statistical analyses.
Preliminary data has identified 13 miRNAs either significantly upregulated or downregulated during SMC differentiation. To enhance the significance of our data, two more timecourses have been submitted as additional biological replicates. After defining the subset of miRNAs that are differentially expressed, the next step will be to determine, at the molecular level, which role these miRNAs may play in the process of SMC differentiation. Based on predicted targets (TargetScan.org), literature searches, and comparing the SMC differentiation ‘signature’ to the LMS ‘signature’ we have selected few a miRNAs to begin testing for a functional role in the SMC differentiation process. To this end, we have cloned the pre-miRNA sequences of candidate miRNAs into the inducible lentiviral vector pTRIPZ (Open Biosystems), and we are currently testing their functions.
2. Identification of the LMS miRNA ‘Signature’
The molecular basis of LMS genesis and progression is widely unknown. We have identified a subset of miRNAs dysregulated between normal and tumor samples, and are developing tools to be used to determine the role that these miRNAs and their targets might play in LMS.
Briefly, total RNA was extracted from frozen blocks of 10 normal myometrial samples, 10 fibroid (benign uterine leiomyomas) and 9 LMS tumor samples. The samples were then hybridized to ‘early release’ Agilent miRNA microarray slides and normalized as described above. In this analysis, miRNAs found to be ‘undetectable’ in 25% or more of the samples were eliminated from further analysis. After normalization, a pairwise t-test comparing tumor versus benign and normal samples was performed to determine which miRNAs were significantly dysregulated. The results were limited to an FDR of less than 0.01. Preliminary analysis of the miRNA microarray data has identified a distinct miRNA ‘signature’ for LMS.
Based on hierarchical clustering, the miRNA ‘signature’ of LMS was able to faithfully cluster most of the tumor samples. An unsupervised hierarchical clustering was also performed to investigate the ability of the miRNA signatures of normal and tumor samples to faithfully classify the tissue type (Figure 5).
Using the same means as outlined in the preliminary data for Aim 1, several miRNAs from the LMS ‘signature’ have been chosen for investigation into their functional role in LMS. Higher significance is given to miRNAs that demonstrated a trend during SMC differentiation in addition to being dysregulated in LMS. We have successfully cloned the pre-miRNA sequences of some miRNA candidates into the inducible lentiviral vector pTRIPZ (Open Biosystems), and are starting to test their function in LMS-genesis and progression, by using primary SMCs and LMS cell lines.
Experimental work has been conducted by Laura Danielson (Graduate Student) assisted by Silvia Menendez (Research Technician), under the supervision of Dr. Eva Hernando. This study was done in collaboration with Dr. Douglas Levine and Dr. Nicholas D. Socci (Memorial Sloan-Kettering Cancer Center).
By Eva Hernando, PhD
Assistant Professor and Co-Director MD/PhD Program
Department of Pathology
New York University School of Medicine
NYU Langone Medical Center
V5N3 ESUN Copyright © 2008 Liddy Shriver Sarcoma Initiative.
Leiomyosarcoma Study Announcement
The Liddy Shriver Sarcoma Initiative and the Leiomyosarcoma Direct Research Foundation (a.k.a., LMSdr and LMSarcoma Direct Research Foundation) are pleased to announce the joint funding of a research project to be undertaken by Eva Hernando, PhD of the Experimental Pathology Program in the Department of Pathology and her team at the NYU School of Medicine. The $50,000 year long grant, which is titled, "MicroRNA Deregulation in Mesenchymal Transformation and Sarcoma-genesis" will begin shortly. The specific sarcoma under investigation is leiomyosarcoma.
MicroRNAs (miRNAs) are endogenous small RNAs that interfere with the translation of coding messenger RNAs (mRNAs) in a sequence specific manner, playing a critical role in the regulation of gene expression during development and tissue homeostasis. Certain miRNAs have been shown to tightly modulate the expression of oncogenes (e.g. MYC and RAS) or tumor suppressors, and have been found deregulated in different tumor types. Recently, miRNAs have been revealed as useful tools for the molecular classification of tumors. However, to date, miRNA expression has not been analyzed in sarcomas. This project represents the first attempt to classify leiomyosarcomas based on their miRNA profile, and to explore the contribution of miRNAs to the smooth-muscle oncogenic transformation process.
It is usually believed that sarcomas derive from mature mesenchymal cells. Thus, the transformation of chondrocytes would originate a chondrosarcoma, adipocytes would be the cell of origin of liposarcomas, and smooth-muscle cells of leiomyosarcoma. However, many sarcomas of a certain subtype vary in their differentiation features. For instance, liposarcomas can be subclassified in de-differentiated, myxoid, pleomorphic, well-differentiated, depending on how close they resemble adypocitic features. Even different areas in the same tumor can contain more or less mature cells. Therefore, our view of the sarcoma "cell of origin" has changed. Instead of a mature cell that "de-differentiates" during the neoplastic process, it is now believed that a mesenchymal progenitor becomes a tumor cell before it is fully mature. According to this model, the leiomyosarcoma cell of origin could be a myoblast rather than a smooth muscle cell.
Recently a new type of small RNAs has been identified that do not codify for proteins, but control the expression of other RNAs that do encode proteins (messenger RNAs or mRNAs). This new group of small RNAs, called microRNAs, have the ability to repress or silence many genes during critical processes, such as development. It is being shown that certain microRNAs can control gene expression during mesenchymal differentiation. Dr. Hernando and her team hypothesize that specific microRNAs can regulate the maturation of functional smooth muscle cells from myoblasts and that alterations in these miRNAs can contribute to the transformation of these myoblasts into tumor cells, contributing to sarcoma-genesis.
Evidence for a contribution of miRNA deregulation to the oncogenic process has been obtained in other tumor types. For instance, let-7 has been found down-regulated in lung cancer. Let-7 usually represses the oncogene RAS; thus, low levels of let-7 will lead to RAS-mediated transformation. Moreover, different tumor types are characterized by a specific set of altered miRNAs. More importantly, these "miRNA expression signatures" seem able to predict outcome. For instance, let-7 downregulation correlates with poor prognosis in lung cancer patients. Overall, these data strongly indicate that miRNAs play an important role in human cancer.
Dr. Hernando and her team have received human mesenchymal stem cells from Tulane University and cultured them in vitro following the recommendations of Dr. Prockop’s laboratory. They are able to differentiate human mesenchymal stem cells into smooth muscle cells, confirmed by the expression of markers and contraction under appropriate stimuli. First, they will analyze the microRNA expression profile of mesenchymal stem cells differentiating into smooth muscle cells and define a ‘smooth muscle miRNA differentiation signature’: a subset of microRNAs whose expression changes during the normal smooth muscle differentiation process. Then, they will compare these with the miRNAs expressed by leiomyosarcomas, in order to identify miRNAs abnormally expressed in LMS compared to normal smooth muscle progenitors. Moreover, they will attempt to identify miRNAs whose expression associates with different clinical/pathological parameters, particularly with patient survival. These miRNAs could be used as prognostic markers, which will be confirmed in an independent set of tumors.
In the future, Dr. Hernando and her team will test the ability of candidate microRNAs to transform smooth muscle progenitors. They will also identify the target genes of the microRNAs of interest, as potentially directly responsible for sarcoma-genesis. It is hoped that this research will lead to: 1) a more accurate patient classification and the identification of prognostic biomarkers; 2) a better understanding of the pathogenesis of leiomyosarcoma; and, 3) unraveling potential new targets for future therapeutic intervention. Finally, their experimental approach should also offer a solid basis for similar studies in other sarcoma subtypes.
V4N3 ESUN Copyright © 2007 Liddy Shriver Sarcoma Initiative.