Osteosarcoma remains a leading cause of cancer death in adolescents. Treatment paradigms and survival rates have not improved in two decades. Driving the lack of therapeutic inroads, the molecular etiology of osteosarcoma remains elusive. MicroRNAs (miRNAs) have demonstrated far-reaching effects on the cellular biology of development and cancer. Their role in osteosarcomagenesis remains largely unexplored. Here we identify for the first time an miRNA signature reflecting the pathogenesis of osteosarcoma from surgically procured samples from human patients. The signature includes high expression of miR-181a,miR-181b, and miR-181c as well as reduced expression of miR-16, miR-29b, and miR-142-5p. We also demonstrate that miR-181b and miR-29b exhibit restricted expression to distinct cell populations in the tumor tissue. Further, higher expression of miR-27a and miR-181c* in pre-treatment biopsy samples characterized patients who developed clinical metastatic disease. In addition, higher expression of miR-451 and miR-15b in pre-treatment samples correlated with subsequent positive response to chemotherapy. In vitro and in vivo functional validation in osteosarcoma cell lines confirmed the tumor suppressive role of miR-16 and the pro-metastatic role of miR-27a. Furthermore, predicted target genes for miR-16 and miR-27a were confirmed as down-regulated by real-time PCR. Affymetrix array profiling of cDNAs from the osteosarcoma specimens and controls were interrogated according to predicted targets of miR-16, miR142-5p, miR-29b, miR-181a/b, and miR-27a. This analysis revealed positive and negative correlations highlighting pathways of known importance to osteosarcoma, as well as novel genes. Thus, our findings establish a miRNA signature associated with pathogenesis of osteosarcoma as well as critical pre-treatment biomarkers of metastasis and responsiveness to therapy. Cancer Res; 72(7); 1865–77. ©2012 AACR.
Osteosarcoma (OS) is the most common primary sarcoma of bone and a leading cause of cancer death among adolescents and young adults (1). The cellular events that initiate and propagate osteosarcomagenesis remain poorly understood (2). Most OSs (approximately 90%) are termed “conventional” and have osteoblastic and/or fibroblastic histologic patterns with consistently high-grade nuclear morphologies. Two common alternate histologic subtypes, chondroblastic, characterized by cartilaginous tissues in the tumor, and telangiectatic, characterized by abundant vascular and cystic spaces in the tumor, are also often high grade. When these other subtypes are high grade, they are treated with conventional OS treatment regimens (3).
The genetic and cytogenetic complexity intrinsic to OS make deciphering the origins of its very patterned clinical phenotype especially difficult. Inability to determine which, among the many genetic derangements present in OS, such as aneuploidy, rampant mutations, and manifold copy number variations, are causative of and which are resultant from oncogenic transformation remains a major impediment to progress in understanding its etiology (2). Nonetheless, the consistent clinical pattern of osteosarcomagenesis, characterized by rapid onset of high-grade neoplasms in young people, suggests that some yet undetected, but consistent etiologic event or group of events defines the neoplasm.
miRNAs are short noncoding RNAs that posttranscriptionally modify gene expression in eukaryotic cells. Expression of a single miRNA can silence a large number of genes, granting these molecules extensive control over many cellular functions (4). Knowledge of individual miRNAs effecting developmental biology, cellular differentiation programs, and oncogenesis continues to grow (reviewed in ref. 5). Although specific miRNAs have been functionally evaluated in a few OS cell lines (6–9), and miRNA expression profiled in formalin-fixed, paraffin-embedded OS specimens (10), high quality total RNA from primary OS tissues has been collected prospectively in few centers (11). Appreciating the vast effects possible from oncogenic and other miRNAs, we surveyed a well-characterized group of OSs with array-based technologies. Differential expression profiles were validated with quantitative reverse transcriptase PCR (qRT-PCR), in situ hybridization, and functional validation in human OS cell lines both in vitro and in vivo. Our studies have shown profiles including differential expression of oncogenic and tumor suppressor miRNAs, reflecting OS status.
Materials and Methods
Patients, sample procurement, and isolation of total RNA
With approval of the Institutional Review Board and in compliance with all legal and ethical considerations for human subject research, patients presenting with suspected sarcomas and scheduled for incisional biopsies provided informed consent to have their tissue banked for RNA extraction. Specimens were obtained during these open surgical biopsies, gently washed with normal saline to remove excess blood, and placed immediately into RNAlater (Ambion) by the surgeon. Specimens were kept at 4°C in RNAlater for up to 1 week, then stored at −80°C. When formal pathologic interpretation of histology from other portions of the biopsy specimen rendered a diagnosis of OS, the RNA-preserving tissue specimens were banked and annotated. In preparation for these specific experiments, total RNA was extracted from banked specimens with the TRIzol reagent and method (Invitrogen). Control samples were derived from to-be-discarded bone fragments obtained from similarly consented patients undergoing debridement surgeries for acute, traumatic injuries to the long bones.
Microarray profiling of miRNA and mRNA expression
miRNA microarray was conducted as previously described (12). The integrity of these total RNAs was assessed with an Agilent 2100 bioanalyzer. Total RNA (5 μg) was hybridized on the custom microarray chip (OSUCCC miRNA microchip, version 3.0). This array contains approximately 1,100 probes (including 345 human and 249 mouse miRNA genes spotted in duplicate). Normalized microarray data were managed and analyzed by BRB-ArrayTools, version 3.8.1 (13). Genes whose expression differed by at least 1.5-fold from the median, in at least 20% of the arrays were used. A stringent significance threshold was used to limit the number of false positive findings. The result of this approach was determined by 2 sample t test with nominal significance level at 0.01. The false discovery rate (FDR) is the expected proportion of positive results that are false positives at the various levels of significance and was controlled using the step-up method of Benjamini and Hochberg. In this analysis, at any selected FDR level, the expected proportion of false positives was determined. Class prediction algorithms determined whether miRNA expression patterns could accurately differentiate between OS samples and normal human bone controls. We developed models based on the compound covariate predictor, nearest neighbor classification, and support vector machine. The models incorporated genes that were differentially expressed among genes at the significance level (0.05) as assessed by the random variance t test. We used the prediction test to identify the classifier signature with the lowest misclassification error.
For the mRNA profiling, 14 of the cohort's OS and 4 of the control samples were hybridized with the Affymetrix Human Genome U133 Plus 2.0 Array. The CEL files were imported and robust multi-array averaging normalized. Genes whose expression differed by at least 1.5-fold from the median in at least 20% of the arrays were used. We carried out class comparisons algorithms in BRB-ArrayTools with the paired t test (P < 0.05). The union of the target mRNAs was used as an input to DAVID EASE, using the David Bioinformatics Resources system (http://david.abcc.ncifcrf.gov). We compared the list of terms related to the predicted targeted mRNAs. The terms were evaluated by P value (P < 0.05) and Benjamini–Hochberg correction for multiple testing controlled the P values. Target genes selection was carried out by Target Scan software. We evaluated Gene Ontology (http://www.geneontology.org/) and PATHWAY (http://www.genome.jp/kegg/) terms.
TaqMan miRNA assays were used to detect and quantify mature miRNAs as previously described (14) using ABI Prism 7900HT sequence detection systems (Applied Biosystems). Normalization was carried out with RNA U6. Samples were run in triplicate, including no-template controls. Relative expression was calculated by the comparative Ct method. qRT-PCR to confirm expression levels in cell lines following transfection with lentiviral vectors was carried out according to a previously described protocol (15). Primers used are noted Supplementary Table S6.
In situ hybridization
Detection of miRNAs by in situ hybridization was conducted as previously published (16, 17). Locked nucleic acid (LNA)-modified probes were 5′ labeled with digoxigenin (Exiqon). After protease digestion to expose the target, 2 pmoles/μL of the probe was hybridized to the tissue section for 15 hours, then subjected to a low stringency wash. The probe-target complex was visualized by alkaline phosphatase activity on the chromogen nitroblue tetrazolium and bromochloroindolyl phosphate (Roche Diagnostics) after nuclear fast red counterstain. Coexpression analyses was conducted with the Nuance system as previously published (17).
Cell lines and cell culture
Cell lines (HOS, KHOS, SaOS2, U2OS, and MG-63) were obtained from the American Type Culture Collection and hOB from PromoCell. LM7 is a gift from Dr. Dennis Hughes (The University of Texas MD Anderson). Each line was authenticated as to genotype and phenotype by the source company. Cells were used at low passage for experiments, always less than 6 months of passaging postprocurement.
In vitro viral transduction
Lenti-miR-16 was a gift from Dr. Yinon Ben-Neriah (Hebrew University, Jerusalem) and Lenti-miR-27a was described elsewhere (18). HEK293 cells with pCMV-VSVG and pHR82R packaging plasmids were used to produce the lenti-miRs. OS cells at subconfluent density (70%) were incubated with the lentivirus for 4 to 5 hours. Selection with 0.5 μg/mL puromycin began the next day. Stable clones were then isolated and verified by qRT-PCR and GFP fluorescence.
Cell proliferation analysis
Cells (1.5 × 103) were plated in 96-well plate and analyzed by a 2,3-bis[2-methoxy-4-nitro-S-sulfophenynl]H-tetrazolium-5 carboxanilide inner salt (XTT) proliferation assay according to the manufacturer's instructions.
Colony formation assay
Cells were plated at a density of 500 cells per well in a 6-well plate in triplicate. After 1 to 2 weeks, the cells were fixed with 70% ethanol, stained with Giemsa and counted.
Matrigel invasion assay
Blind well chemotaxis chambers with 13 mm diameter filters were used for this assay. Polyvinylpyrrolidone-free polycarbonate filters, 8-μm pore size (Costar Scientific Co.), were coated with basement membrane Matrigel (25 μg/filter). Cells (2 × 105) suspended in Dulbecco's Modified Eagle's Medium containing 0.1% bovine serum albumin were added to the upper chamber. Conditioned medium of NIH3T3 fibroblasts was placed in the lower chamber. Assays were carried out at 37°C in 5% CO2. More than 90% of the cells attached to the filter after incubation for 7 hours. After incubation, the upper surface of the filter was freed of cells with a cotton swab. Cells that passed through the filter to bottom side were fixed with methanol and stained with Giemsa. Each triplicate assay was conducted twice. Invasive cells were counted in 10 representative light microscopy fields.
All animals were housed in the Hebrew University animal facility and the experiments with live animals were approved by our institute animal committee and conducted in accordance with NIH guidelines. HOS cells expressing miR-control, miR16, or miR-27a were injected s.c. (5 × 106 cells) or i.v. (1 × 106 cells), respectively, into nonobese diabetic/severe combined immunodeficient (NOD/SCID) mice. For SC experiments, tumor volume was evaluated weekly and tumor mass measured at the end of the experiment. For i.v. experiments, 6 weeks after injecting cells expressing miR-27a-GFP or control-miR-GFP, mice were sacrificed and lungs as well as legs and forearms were examined for micro- and macrometastases, respectively, using a fluorescent stereomicroscope (Olympus).
Immunohistochemistry was carried out on formalin-fixed, paraffin-embedded specimens with the following antibodies: polyclonal antiactive caspase-3 (Cell Signaling; dilution 1:100), polyclonal anti-BCL2 (Abcam ab7973-1; dilution 1:100), and polyclonal anti-NFAT5 (Abcam ab110995; dilution 1:100). Detection was carried out by ABC kit (BA-1000, VECTOR Laboratories) according to manufacturer's specifications. Slides were reviewed in blinded fashion and ranked according to density of immunostain. Five bone marrow core biopsy controls were used, assessing immunostaining on trabecular bone rimming osteoblasts.
miRNA expression signature for osteosarcomagenesis
To identify differentially expressed miRNAs common in osteosarcomagenesis, we compared miRNA expression profiles from 18 pretreatment biopsy samples from conventional (osteoblastic/fibroblastic) OSs to control samples from healthy bone tissue (Supplementary Table S1). A total of 34 miRNAs were significantly deregulated (P < 0.01); of those, 11 had higher expression among the conventional OS group and 23 lower expression (Table 1, Fig. 1A). The most upregulated miRNAs in OS were miR-181a and miR-181b. MiR-29b, miR-451, and miR-16 were among the most downregulated. Discrimination by profile between the 2 groups was strong. The cross-validation receiver operator characteristic (ROC) curve from the Bayesian compound covariate predictor had an area under the curve (AUC) of 0.986. This shows an extremely strong capacity for the relative expression levels of these 34 miRNAs to place a given sample into its correct group, OS or control.
For validation, we conducted qRT-PCR for a subset of the samples (Fig. 1B). Specifically, qRT-PCR confirmed differential expression for 9 of the 34 significant OS (shown in Fig. 1A) miRNAs among a random sampling of 7 specimens from OSs and 4 from controls. In particular, we confirmed the downregulation of miR-29b, miR-16, miR-142-5p, miR-26b, let7g, miR-223, and miR-451 in OS samples as compared with controls. By contrast, miR-181a and miR-181b showed significant upregulation in OS cases (Fig. 1B). In addition, miR-29a, expressed from the same locus as miR-29b, was checked by qRT-PCR as a separate validation of the same locus. Other than 1 sample in each of 2 of the qRT-PCR experiments, all OS samples and control samples had distinct expression ranges, with no overlapping means.
Conventional, chondroblastic, and telangiectatic histologic subtypes of OS have distinct pathologic features. To interrogate the potential contribution of miRNA expression to the development of these different high-grade OS histologic subtypes, miRNA profiles from 18 conventional, 4 telangiectatic, 5 chondroblastic, 1 recurrent chondroblastic, 1 recurrent conventional, and 1 soft tissue OSs were subjected to unsupervised hierarchical clustering. Conventional, telangiectatic, chondroblastic, and even soft tissue OSs all clustered together in intermingled fashion (Fig. 1C). All 4 telangiectatic OSs clustered to 1 side of the highest hierarchy division, characterized by elevated expression of miR-142-5p, miR-15a, miR-486-5p, and miR-488. Small sample size makes statistical resolution of this finding unfeasible. Both conventional and chondroblastic OSs clustered with those 4 telangiectatic OSs. The overall coclustering of different subtypes suggests that with regard to miRNA expression, these tumors share more in common than not, which suggests that the miRNA expression represents more a shared oncogenic program than a differentiation profile alone, as these tumors are distinctly dissimilar in cell differentiation state. miRNA profiling therefore may not be helpful in defining histologically based OS subtype classifications.
To validate against an alternate data set, the publicly available S-MED database (19) was queried for the 34 miRNAs highlighted by our OS signature. The 15 OS samples (not subtyped) and 6 control bone samples recorded in the S-MED database had raw expression data for 26 of these miRNAs. Expression of 17 corroborated the differential expression in our samples (8 were significant with Student t test P values ranging from 0.006 to 5 × 10−8.) These statistically significant and concordant expression data included higher expression of miR-181c and miR-190 in S-MED OS specimens and lower expression of miR-16, miR-126*, miR-150, miR-195, miR-657, and miR-340. Although the S-MED database includes fewer OS specimens than our primary data and lacks any clinical or pathologic annotation, it provides validation of the most important members of our OS miRNA signature profile from an alternate sample source and profiling platform.
miR-181b is inversely correlated with miR-29b in OS
To confirm deregulation of miRNA expression within tumor cells specifically, in situ hybridization of probes antisense to the differentially expressed miR-181b and 29b was carried out with formalin-fixed, paraffin-embedded tissue sections processed from 9 of the same pretreatment biopsy specimens from which fresh tissue for total RNA isolation had been initially banked. As shown in Fig. 2, in situ hybridization with LNA-modified anti–miR-181b (panel B) or anti-miR-29b (panel C) probes showed results consistent with qRT-PCR (panel D). No signal was detected with scrambled oligo showing probe specificity (data not shown). Some tissues showed positive hybridization for the downregulated miRNA-29b (Fig. 2D). Although downregulation is not tantamount to absence, this nonetheless prompted further investigation. Using double labeling for miR-29b and miR-181b, it was confirmed that expression did not colocalize to the same cells (Fig. 2E, F), suggesting that the pro-osteoblast differentiation miR-29b was specifically absent in cells with the most robust oncogenic program of miR-181b expression. Additional in situ hybridization validation was carried out using a bone cancer tissue microarray (US Biomax, Inc.) that included 8 core tissue sections from 4 OSs. Two of the OS specimens showed strong staining for miR-181b and minimal miR-29b staining (data not shown), further evidence for miRNAs that may differentiate tumor versus normal bone.
miRNA expression signatures for OS metastasis and chemotherapeutic response
Ten OS patients either presented with or later developed clinically apparent metastatic disease. Their biologically aggressive tumors clustered together on unsupervised hierarchical clustering, loosely separate from the comparison 19 localized OSs (Fig. 3A). Differentially expressed miRNAs included 1.75- and 4.53-fold increased expression of miR-181c* and miR-27a, respectively, in metastatic OSs. The class prediction analysis with these 2 miRNAs yielded a relatively strong ROC curve with an AUC of 0.805, indicating that the expression level of these 2 miRNAs alone discriminated between tumors that would and would not develop clinical metastases.
As OS patients typically receive chemotherapy after biopsy, but before resection, the percentage necrosis or treatment effect noted by the pathologist in the resection specimen has been found to be a powerful prognostic tool (20). All OS patients with pretreatment sample miRNA profiles available and who received neoadjuvant chemotherapy followed by resection and histopathologic grading of necrosis (n = 27, Supplementary Table S1), were analyzed for a correlation between differentially expressed pretreatment miRNAs and the percentage necrosis following chemotherapy. Spearman correlation, which measures the correlation of rank ordering between 2 values, identified expression of 8 miRNAs positively correlated with percentage necrosis at less than 0.01 stringency and 1 negatively correlated (Supplementary Table S2A; Fig. 3B shows unsupervised clustering by Spearman-identified miRNAs). Pearson correlation, which identifies linear relationships rather than rankings, identified 7 miRNAs positively correlated with necrosis at less than 0.01 stringency (Supplementary Table S2B; Fig. 3C shows unsupervised clustering by Pearson-identified miRNAs). miR-451 and miR-15b, with the 2 highest Spearman correlation coefficients of 0.64 and 0.619, respectively, were also highlighted by the Pearson correlation list, having correlation coefficients of 0.533 and 0.539, respectively. Thus, increased expression of miR-15b (from the miR-15/16 family) and miR-451 in pretreatment samples was the most stringent predictor of good response to chemotherapy. RT-PCR validated expression levels of miR-451 and miR-15b in a subset of chemosensitive and chemoresistant OS samples (Supplementary Fig. S1).
Functional validation of miR-16 as tumor suppressive and miR-27a as prometastatic in OS cells
To determine the functional relevance of miRNA deregulation in OS, we studied the effect of miR-16 and miR-27a manipulation on OS cells. We first checked the endogenous miR-16 and miR-27a levels by qRT-PCR in 1 human osteoblast and 6 human OS cell lines. Three OS cell lines (HOS, KHOS, and U2OS) exhibited significantly low levels of miR-16 as compared with hOB (Supplementary Fig. S2). Similarly, miR-27a expression levels were lower in these cells while the MG-63 cells, capable of metastasis and the highly metastatic LM-7 cells displayed higher levels (Supplementary Fig. S2).
Next, we set to determine whether reintroduction of these miRs affected the tumorigenic traits of OS cells (Supplementary Fig. S3 and S4). Using XTT test, we observed significant growth inhibition in U2OS and hOB cells (Supplementary Fig. S5). In contrast, we did not detect this effect in HOS, KHOS, and SaOS2 cells (Fig. 4A, Supplementary Fig. S5). Nevertheless, overexpression of miR-16 in OS cells displaying low levels of endogenous miR-16 was associated with significant reduction in colony formation ability (Fig. 4B and Supplementary Fig. S5). Moreover, HOS-expressing miR-16 displayed increased apoptosis in the presence of doxorubicin (Fig. 4C).
We next evaluated the tumor suppressor function of miR-16 in vivo. HOS cells overexpressing control miR or miR-16 were xenografted into the flanks of NOD/SCID mice and monitored for tumor formation. We found that overexpressing miR-16 produced tumors of smaller volume and smaller final mass (Fig. 4D–F). Furthermore, miR-16 overexpressing HOS xenografts exhibited increased activated caspase-3 staining (Fig. 4G), an indicator of enhanced apoptosis in the absence of cytotoxic treatment.
To interrogate the impact of miR-27a overexpression on the metastatic potential of OS cells, we infected HOS cells with a lentiviral vector that expresses either miR-27a or control miR along with a GFP reporter. In vitro, a wound healing assay found increased migration with overexpression of miR-27a versus control miR (Fig. 4H). Similarly, Matrigel invasion assay showed that miR-27a increased invasiveness (Fig. 4I). miR-27a–expressing cells were next injected i.v. into NOD/SCID mice to evaluate the metastatic potential of these cells. Six weeks later, the animals were scarified and dissected to look for both microscopic and macroscopic metastases. We found that overexpression of miR-27a is associated with increased ability to form metastatic foci compared with control miR. The number and size of pulmonary metastases was significantly increased as well as the presence of macroscopic metastatic disease in the bones of the legs and forearms (Fig. 4J–N). Additional functional validation in other cell lines confirmed promigration and invasion effects of miR-27a (Supplementary Fig. S5).
Predicted targets of differentially expressed miRNAs reflected in OS
MiRNAs are known to have downregulatory effects at the level of transcript longevity and translational control. Expression levels of TargetScan-predicted target genes of miR-16 were found to be reduced in OS and osteoblast cell lines following overexpression of miR-16 (Fig. 5A). Similarly, expression levels of predicted target genes of miR-27a were found to be reduced in OS cell lines following overexpression of miR-27a (Fig. 5B).
We expanded the analysis of expression of target genes by profiling gene expression by Affymetrix array in 14 of the OS samples in our cohort and 4 of the normal bone control samples. Our data revealed differential changes in a significant number of genes (data not shown). The miRNA and mRNA expression profiles were then integrated to identify functional relationships that may contribute to OS. Instead of correlating gene expression with all miRNAs, we focused on miRNAs in which differential expression was most significant in OS; miR-16, miR-142-5p, miR-29b as downregulated miRNAs in OS and miR-181 and miR-27a as upregulated miRNAs in OS. Positive and negative correlations were found. However, we focused on the differentially expressed genes that followed the directional change predicted by the miRNA; increased expression in OS for genes targeted by miR-16, miR-142-5p, and miR-29b and decreased expression of genes targeted by miR-181 and miR-27a (Supplementary Tables S3A and S3B). We found that several known OS genes are indeed targeted by these different miRNA classes. Gene ontologies and Kegg pathways analyses of these predicted target genes highlighted significant changes in transcriptional regulation, cell-cycle control, and known cancer signaling pathways (Table 2 and Supplementary Tables S4 and S5).
To further investigate 1 miRNA as an example, miR-15b from the miR-15/16 family was selected due to the fact that it showed differential expression within the cohort of OSs and predicted chemosensitivity. The expression level of miR-15b from each specimen was plotted against the Affymetrix mRNA level in the same sample for 6 of the prominent differentially expressed genes that are predicted targets and responsive in cell line experiments (Fig. 5C). A linear regression trend line for each series showed the predicted direction of correlation with increasing level of miR-15b linked to decreasing levels of each gene's mRNA.
Because miRNAs can have more profound effects on translation than transcription, we carried out immunohistochemistry in tissue sections from a subset of the OS samples. We selected 2 genes, one a well-known gene in OS, BCL2, the other a gene not previously associated with OS, but also a target of the miR-15/16 family, NFAT5. For both, immunohistochemistry confirmed increased protein presence in the cohort OSs than in the osteoblasts of bone marrow controls (Supplementary Fig. S6). The BCL2 immunohistochemically stained sections were blindly ranked from least to most positive for staining. This ranking was then plotted against the expression level of miR-15b (Fig. 5D) and against the expected clinical parameter of percentage necrosis as measured from later resection surgery to quantify chemoresponsiveness (Fig. 5E). Linear regressions strongly followed the expected correlation in each. Although these correlations only consider 1 example, they suggest that the differentially expressed miRNAs play a direct role in controlling transcript levels and translational success of predicted target genes in OS.
We report unique OS signatures of miRNA expression related to the OS character and pathogenesis, to clinical metastasis, and to chemotherapy response. The deregulation of miR-181b specifically in the malignant cells in OS tissues by in situ hybridization provides a potential OS marker. Furthermore, miR-181b and miR-29b expression inversely correlate in subpopulations of cells in the tumors. Significantly, our in vitro and in vivo functional experiments validate miR-16 as a tumor suppressor and miR-27a as prometastatic in OS and osteoblast cell lines. These data suggest potential targets for future therapeutic strategies. Furthermore, our study indicates that by correlating genome-wide gene and miRNA expression profiles, putative functional miRNA–mRNA interactions could be identified in OS.
The conventional OS miRNA expression signature we report here, showed strong statistical significance even in a relatively small sample size. This suggests profile consistency across the samples. Given the genetic and cytogenetic complexity inherent to OS (2), this consistency raises the possibility that miRNAs play a central role in osteosarcomagenesis. That the miRNA profile differed little even among histologically disparate samples from chondroblastic and telangiectatic OSs further suggests a role for these miRNAs in development of OS generally. Validation against another patient group confirmed the differential expression of the critical members of this (19). A final validation of our signature derives from our observation that some of the prominent signature miRNAs are also highlighted by OS metastasis and chemotherapy responsiveness signatures (Supplementary Fig. S7).
As we qualitatively evaluate these signature OS miRNAs, downregulated miRNAs are most striking. MiR-29b figured prominently in this list. We also showed its localization to a distinct cell subpopulation within the tumors. This fits the powerful role of miR-29b as a prodifferentiation miRNA in normal osteoblasts (21). Other signature downregulated miRNAS have known prodifferentiation roles in other tissues, miR-223 in myeloid (22) and miR-451 in erythroid differentiation (23). miR-29b is also known as a tumor suppressor miRNA (24). The tumor suppressor category also encompasses other prominently downregulated members of the signature profile, including miR-142-5p (25), miR-340 (26), breast cancer metastasis suppressing miR-335 (27), BCL-2 targeting miR-16/16-2* (reviewed in ref. 28), miR-126/126* (reviewed in ref. 29), and miR-195 (30), an miR-15/16-related miRNA. Together with our in vitro functional validation for miR-16, these findings highlight critical tumor suppressor functions of the miR-15/16 family in OS.
Most upregulated miRNAs in the OS signature are known as oncomiRs, such as miR-190 (31), miR-10b [(32) and references therein], miR-7 [(33) and references therein], miR-214 [(34) and references therein], and miR-210 (35). Although miR-574-3p is not well characterized in the literature, it is predicted to target disabled homolog 2 interacting protein, which is silenced in a number of cancers (36–38), retinoid X receptor alpha, which is associated with vitamin D metabolism and polymorphism-based cancer risk (39), and FOS-like antigen 2 (Fosl2/Fra2), which is a prodifferentiation gene in osteoblasts (40). Most prominently, 3 of the 4 miRNAs from the miR-181 group were highly upregulated in OS samples. miR-181 has been associated with stemness and poor prognosis in other cancers [(41) and references therein]. Furthermore, miR-181 activates Wnt signaling (42), important in OS pathogenesis (43). Together with our in situ hybridization confirmation that miR-181 identifies a subgroup of cells within OS tissues that lack miR-29b–driven differentiation, these data highlight miR-181 as a critical OS oncomiR.
Increased expression of miR-181c* and miR-27a at pretreatment biopsy was found to be prognostic of metastatic disease. This punctuates the importance of the miR-181 family to OS. miR27a is a known oncomiR, associated with metastasis in gastric cancer (44) and poor prognosis in ovarian carcinoma (45). Our in vitro and in vivo experiments confirmed that miR-27a overexpression enhances migration, invasion, and proliferation in metastatic sites. These findings correlate with the recently described inhibition of osteoblast differentiation by miR-27a (18). Targeted therapies against miR-27a are emerging (46, 47).
Expression levels of miR-451 and miR-15b in pretreatment specimens both correlated positively with percentage necrosis following neoadjuvant chemotherapy. Reduced expression of miR-451 was also prominent in the general OS signature. Although miR-15b itself was not highlighted in the general OS signature, miR-16, miR16-2*, and miR-195, all from the same miR-15/16 family, were. Apparently, reduced expression of these miRNAs characterizes OS generally, but among OSs, further reduced expression correlates with resistance to chemotherapy. MiR-15b and other family members target Bcl-2, which could explain their downregulation in chemoresistant tumors (48). We confirmed by immunohistochemistry the increased presence of BCL-2 in the OS histologic specimens compared with controls. Furthermore, increased apoptosis was identified both in untreated xenografts and doxorubicin-treated cultures of OS cells driven to overexpress miR-16. Our findings did not corroborate any of the specific miRNAs reported to predict chemotherapeutic response in a series of formalin-fixed, paraffin-embedded OS specimens (10). This other study differed in source and method of RNA isolation. It also focused on ifosfamide, an infrequent neoadjuvant chemotherapy for OS in the United States and received by only one of our patients. Furthermore, our findings did not highlight any of the previously investigated individual miRNAs noted to have roles in OS cell lines (6–9).
The profound effects of miR-16, miR-142-5p, miR-29b, miR-181, and miR-27a on the microarray-defined expression of their predicted target genes, with statistically significant differences in the predicted direction, suggest that these miRNAs play central roles in defining the expression identity of OS. Our study reveals many potential functional miRNA–mRNA relationships that will need to be further explored mechanistically for their involvement in OS pathogenesis. Gain and loss of function studies are needed to investigate further the role of these miRNAs that have correlated with transcriptional regulation, cell-cycle control, and known cancer signaling pathways. Finally, the discovery of previously unidentified functional relationships may lead to the development of novel therapeutic approaches. Further investigation into the potentially more poignant effects on translation of their targets may yield additional insights into this newly recognized method of an OS cell defining itself.
Making clear sense of how the genetic chaos that defines OS derives such a patterned clinical disease remains a distant goal, but these data strongly recommend the pursuit of osteosarcomiRs and silenced OS tumor suppressor miRNAs as critically associated with development of OS. The statistical strength of the OS signature we report, the consistency across multiple histologic subtypes, and especially the overlap of the general OS signature with signatures predictive of metastasis and predictive of response to chemotherapy, all highlight the central role of these dysregulated miRNAs in osteosarcomagenesis. Our validation studies for key signature OS miRNAs and integration of miRNA expression with mRNA expression, together with existing literature provide models for future study.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed.
This work was supported, in part, by the Alex's Lemonade Stand Foundation (ALSF) “A” Award to R.I. Aqeilan, and Israeli Cancer Research Funds (ICRF) to R.I. Aqeilan and Z. Salah. K.B. Jones is supported by the NIH K08CA138764 and the Huntsman Cancer Foundation. R.L. Randall is supported by the Huntsman Cancer Foundation. G.S. Stein and J.B. Lian are supported by NIH/NIAMS AR039588-19. S. Volinia is supported by AIRC (IG 8588) and PRIN MIUR 2008.
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
The authors thank Saleh Khwaled and Suhaib Abdeen from Hebrew University for assistance with mice work; John J. Wixted from the University of Massachusetts, Worcester, for assistance in procuring control bone specimens; David LaPointe, also from the University of Massachusetts, Worcester, for assistance with bioinformatics analysis; and Huifeng Jin and Mohamed Salama from the University of Utah for assistance with immunohistochemistry.
Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).
K.B. Jones and Z. Salah are first coauthors.
- Received August 10, 2011.
- Revision received December 14, 2011.
- Accepted January 7, 2012.
- ©2012 American Association for Cancer Research.