Loss of the multifunctional RNA-binding protein RBM47 as a source of selectable metastatic traits in breast cancer

1Cancers arise through an evolutionary process that feeds from stochastic genetic alterations and selection. The identities of the alterations that get selected for are rapidly coming to light through large-scale resequencing efforts. For example, several independent studies have characterized the mutational complement of breast cancer, one of the most common human malignancies. Besides confirming previously known cancer genes, such as TP53 and PIK3CA, most studies also report a long tail of rarely mutated genes. While many of these mutations are likely to be passenger events, some of them are potential mediators of tumor phenotypes. How to identify such low-frequency driver mutations remains a challenge.

2In addition to mutations that directly promote tumorigenesis through specific alterations in cell signaling and repair pathways, many aberrations found in cancers do not affect cell signaling pathways directly, but rather, they support the stabilization of altered transcriptomic profiles that facilitate the emergence of pro-tumorigenic and metastatic traits. Mutations in epigenetic regulators fall into this category. The phenotypic output of such alterations would depend on the activity of already existing signaling processes. Indeed, examples of epigenetic alterations that result in a phenotypic trait in the presence of a specific transcriptional program have been described. Analogously, aberrations in the multi-step mRNA processing and turnover cascade could also lock in aberrant transcriptomic states.

3Precise regulation of RNA metabolism is fundamental in the generation of biological complexity in both normal and disease states. The concerted action of multiple RNA binding proteins (RBPs) regulate the spatial, temporal and functional dynamics of the transcriptome via alternative splicing, alternative polyadenylation and transcript stability. While malignancy-associated dysregulation of RNA metabolism via aberrant microRNA expression is relatively well established, a growing body of evidence indicates a prominent role also for RBPs in both the development and progression of cancer. For example, upregulation of the splicing regulator SRSF1 is associated with multiple tumor types, and is necessary for the oncogenic activity of MYC in lung cancer. Conversely, RBM5 has been shown to be tumor suppressive in several cancer models.

4We hypothesized that combining cancer genome resequencing data with gene expression information from both clinical data sets and experimental model systems of metastasis would allow the identification of rarely mutated cancer genes with potential functional significance. This approach identified RNA binding motif protein 47 (RBM47) as a suppressor of breast cancer progression. By analyzing the transcriptome-wide RBM47 binding patterns we demonstrate that RBM47, a previously uncharacterized RNA-binding protein, modulates mRNA splicing and stability. Loss of RBM47 function thus provides a specific example of the power of global RNA modulatory events in the selection of pro-metastatic phenotypic traits.

5We combined gene expression data from triple negative metastatic breast cancer models and a cohort of 368 untreated clinical breast cancer cases with mutational data from a brain metastasis that originated from a basal breast cancer (; Figure 1A). Specifically, we looked for genes that had reduced mRNA expression in functionally metastatic cancer cells, evidence for low mRNA expression associated with poor patient outcome in clinical samples, and an enriched mutation in the brain metastasis sequenced by. RBM47, a gene encoding a previously uncharacterized putative RNA-binding protein was the only one that fulfilled all these criteria. We confirmed the lower expression of RBM47 mRNA in the highly metastatic cells (Figure 1B). This translated into a comparable difference at the protein level (Figure 1C). In the clinical data sets, low RBM47 mRNA expression was significantly associated with relapse to brain and lung (Figure 1D,E) but not to bone (Figure 1F). In multivariate analysis combining RBM47 expression with estrogen, progesterone and HER2 receptor status (ER, PR and HER2), the association with brain metastasis remained statistically significant (Figure 1—figure supplement 1A). We further characterized the expression patterns of RBM47 in the TCGA cohort of 748 breast cancer samples studied by RNA-seq. We found that low RBM47 expression was significantly associated with claudin-low and basal breast cancers (Figure 1G), two subtypes of poor prognosis.

6The RBM47I281fs mutation first reported in a brain metastasis truncates the protein from the third RNA recognition motif (RRM) onwards (Figure 1H). As this mutation was already present in a minority subpopulation of the corresponding primary tumor, we looked for additional evidence of genetic RBM47 aberrations in primary breast cancer cohorts. The catalogue of somatic mutations in cancer (COSMIC) database reported 9 non-synonymous mutations in RBM47, three of which were frameshift mutations truncating one or more of the RRM domains (Figure 1—figure supplement 1B). Furthermore, analysis of the data from the TCGA cohort revealed that in basal breast cancer, RBM47 was targeted by a mutation or homozygous deletion in ∼8% of the cases (Figure 1—figure supplement 1C). Moreover, heterozygous loss of the RBM47 locus was present in 30% of the TCGA cohort. These correlative analyses of multiple different breast cancer data sets, both experimental systems and large clinical patient cohorts, suggested that reduced expression or function of RBM47 is associated with breast cancer progression already within primary tumors, and that clones with reduced RBM47 function may display enhanced lung and brain metastatic fitness.

7In order to test the role of RBM47 as a suppressor of breast cancer progression, we stably introduced both wild type RBM47 and RBM47I281fs in the lung metastatic (LM2) and brain metastatic (BrM2) derivatives of the MDA-MB-231 triple negative breast cancer cells (MDA231 for short), respectively (Figure 2—figure supplement 1A;; ). Of note, despite robust mRNA expression, the mutant RBM47I281fs protein levels were low, indicating that the mutant protein was unstable and therefore inactive (Figure 2—figure supplement 1B). As determined by in vivo bioluminescence in experimental metastasis assays, wild type RBM47 inhibited lung colonization by the MDA231-LM2 cells, when compared to RBM47I281fs (Figure 2A–B). Similarly, we observed extended brain metastasis free survival in mice inoculated with the MDA231-BrM2 cells expressing RBM47 when compared to those expressing RBM47I281fs (Figure 2C). This difference translated into reduced brain metastatic burden as determined by ex vivo imaging (Figure 2D,E, Figure 2—figure supplement 1C). We then tested the effects of inhibiting endogenous RBM47 in the metastatic colonization of the parental MDA231 cells. With comparable effects of RBM47 re-expression seen in both the lung and brain metastasis models (Figure 2A,E), we chose the lung colonization assay for loss-of-function studies as this allowed the simultaneous analysis of a greater number of tumor re-initiation events. Two RBM47-targeting shRNA constructs significantly shortened the lung metastasis free survival in mice when compared to controls (Figure 2F, Figure 2—figure supplement 1D), as determined by bioluminescence imaging (Figure 2G,H). This result was confirmed with a second more indolent cancer cell clone (Figure 2—figure supplement 1E–G).

8The initial functional experiments suggested that the tumor suppressive effect of RBM47 on the overall population of metastatic cancer cells was modest. This could reflect either weak tumor suppressive function of RBM47 in general, heterogeneity in the sensitivity to RBM47 among different cancer cell subpopulations, or in the case of RBM47 reintroduction, loss of transgene expression. In order to distinguish between these possibilities, we used immunohistochemistry to assess RBM47 expression in the lung nodules formed either by wild type RBM47 or RBM47I281fs expressing cells. This revealed that some cancer clones were able to form robust lung metastasis even in the presence of RBM47 (Figure 3A, Figure 3—figure supplement 1A), but that many of the metastases formed after the inoculation of wild type RBM47-expressing cells had avoided or suppressed the expression of RBM47 (Figure 3B, Figure 3A—figure supplement 1A). As expected, the RBM47I281fs-expressing tumors contained only weakly staining cancer cells intermingled with small cells with strong RBM47 expression (Figure 3C), similar to those seen in normal lung parenchyma (Figure 3D). The rate of proliferation as determined by Ki67 immunohistochemistry did not correlate with the level of RBM47 expression (Figure 3—figure supplement 1A). This was in line with the idea that some clones were more sensitive to RBM47 than others, but also that a strong selective pressure led metastatic cells to lose RBM47, a finding consistent with the initial observation of RBM47 loss in metastatic cell populations (Figure 1C).

9In order to allow better experimental control over RBM47 expression we utilized a conditional expression system. By focusing on the two brain metastatic cell lines that expressed the lowest levels of endogenous RBM47 (Figure 1C) we generated single cell-derived clones with doxycycline-inducible expression of either wild type RBM47 (henceforth WT10 and WT6, respectively) or the patient-derived mutant RBM47I281fs (henceforth MUT3). All clones exhibited dose-dependent RBM47 mRNA upregulation upon doxycycline induction (Figure 3—figure supplement 2A–C) that translated into increased RBM47 protein expression in the wild type-expressing clones (Figure 3—figure supplement 2D,E). Cancer cells also tolerated RBM47 in vitro (Figure 3—figure supplement 2F). After confirming the feasibility of doxycycline-mediated conditional gene activation in metastatic brain lesions (Figure 3—figure supplement 2G), we inoculated WT6, WT10 and MUT3 cells into immunocompromized mice and assessed their brain-metastatic phenotype. All clones formed robust brain metastases under doxycycline-free conditions (Figure 3E–J). The induction of RBM47 expression with doxycycline in the diet inhibited robustly brain colonization of both metastatic cell clones, WT6 and WT10 (Figure 3E–G). However, the patient-derived mutant RBM47I281fs did not show any tumor suppressive effects (Figure 3H–J). Collectively, these results demonstrated that RBM47 was able to strongly inhibit metastatic functions of some cancer clones, whereas other clones were able to form metastasis despite the presence of RBM47.

10To determine whether RBM47 can directly bind RNA in vivo, we made use of the ability of UV-irradiation at 254 nm to induce chemical crosslinks between RNA and proteins that are in direct contact. γ-32P-labeled RNA was detected by autoradiogram at ∼76 kD, the predicted size of Flag-RBM47, in Flag-immunoprecipitates from UV-irradiated, doxycycline-treated MDA231-BrM2 WT Flag-RBM47 cells, but not doxycycline-treated empty vector control or non-irradiated WT Flag-RBM47 expressing cells (Figure 4A). To identify directly bound RBM47 targets, a modified version of the high throughput sequencing and cross-linking immunoprecipitation (HITS-CLIP) protocol was carried out in duplicate on Flag-RBM47 expressing MDA231-BrM2 cells treated with doxycycline. (Figure 4B, see 'Materials and methods'). RBM47-bound HITS-CLIP reads were mapped to the human genome, yielding ∼7.7 × 106 and ∼2.0 × 106 unique reads (tags) per replicate. 75% of the tags mapped to regions corresponding to UCSC/Refseq genes, with a high degree of reproducibility of binding observed between replicates (Spearmann correlation coefficient R2 = 0.998, total tags per gene, Figure 4C).

11To identify robust and reproducible RBM47-binding sites, tags were clustered to return regions with evidence of binding in both replicates (biological complexity, BC = 2) with increasingly stringent filters (Figure 4D): tags per cluster (tags ≥2, 617,026 clusters; tags ≥10, 94,966 clusters), a previously described significant peak threshold (significant peak height ≥10, 29,562 clusters), and a ranked reproducibility chi-squared score (p≤0.01, 19,433 clusters). As has been previously described for the n-ELAV proteins, identification of the most robust binding through increased stringency of cluster definition led to an increase in proportional binding in 3′UTR regions. For RBM47 this occurred due to loss of the majority of reproducible, yet relatively small intronic binding sites (Figure 4E), which may reflect the relative abundance of pre- and mature RNA message. Motif analysis (MEME, ) failed to identify an enriched RBM47-binding sequence in ±10 nt footprints centered on the top 3000 significant peaks (data not shown), but revealed a polyU sequence enriched in RBM47-binding sites containing cross-link induced mutations (deletion CIMS,, Figure 4F). The apparent lack of an enriched RBM47-binding motif within robust CLIP-derived binding sites may reflect the broad binding patterns observed, as exemplified by the predominantly 3′UTR binding in DKK1 and IL8 (Figure 4G).

12Reproducible binding of RBPs in intronic regions has proven to be predictive of a role in pre-mRNA processing for multiple proteins. To explore the relationship between RBM47 intronic binding and alternative splicing, RNA-seq was carried out in triplicate to compare MDA231-BrM2 cells and RBM47-expressing WT10 cells. Reads were mapped to cassette (CA) exon junctions as described previously for Mbnl2, and an average inclusion rate (IR) calculated for each cell type to allow for the identification of reciprocal splicing changes while normalizing for changes in RNA stability (; Figure 5A). The average change in inclusion rate (ΔI) was then calculated such that positive ΔI indicates RBM47-dependent cassette exon inclusion. This analysis revealed 121 and 140 CA exons with significant RBM47-dependent inclusion and exclusion, respectively. To assess whether RBM47-binding occurred in the vicinity of these splice sites, HITS-CLIP tags in BC2 tags ≥5 clusters (to account for lower levels of intronic binding seen in Figure 4E) in the region of the alternative splice were calculated. Forty-eight RBM47-bound included and 49 RBM47-bound excluded CA exons were identified in a total of 84 genes (Figure 5B; Supplementary file 1). RBM47-dependent splicing changes were confirmed via RT-PCR as shown for SLK, MDM4, LIMCH1, MBNL1 and SEC31A (Figure 5C, Figure 5—figure supplement 1).

13By mapping normalized RBM47 CLIP tags associated with RBM47-dependent splicing changes on a composite transcript we generated an RNA binding map of consensus binding sites within 1 kb of exon-intron boundaries, with respect to exon inclusion or exclusion (Figure 5D). The resulting normalized complexity map reveals enriched RBM47 binding in the vicinity of splice acceptor sites of the CA exon and 3′ CE for included alternative isoforms, while relative enrichment of RBM47 binding was seen at the 5′ CE splice donor and 3′CE splice acceptor of excluded isoforms.

14To further study the functional consequences of RBM47-mRNA binding events, we determined global steady state mRNA levels in the RBM47 expressing brain metastatic cells by RNA-seq. We took advantage of the clonal doxycycline-inducible cell line systems, which facilitated the analysis of RBM47 dose-dependence. First, genome-wide analyses showed that the mRNA level of several more genes correlated significantly with increasing concentrations of doxycycline in both cell lines expressing the wild type RBM47 (WT6 and WT10), when compared to cells expressing the mutant (Figure 6A). This result indicated that RBM47 elicits dose-dependent changes in mRNA levels. The correlation coefficients followed a pattern that suggested the existence of mRNA species that correlated both positively and negatively with wild type, but not mutant, RBM47 expression, that is few genes in MUT3 cells had correlation coefficients close to 1 or −1, whereas in WT6 and WT10 cells such genes were abundant (Figure 6B). Encouraged by these observations, we looked for mRNAs that fulfilled the following criteria: (i) p-value of correlation less than 0.01 in both WT6 and WT10 cells, (ii) mRNA expression change detectable already at the lowest levels of RBM47 expression in both cell clones and (iii) no significant correlation with RBM47I281fs expression. This revealed a set of 102 mRNAs that were upregulated and 92 that were downregulated, respectively, in cells expressing the wild type RBM47 (Figure 6C, Figure 6—figure supplement 1A,B; Supplementary file 2). Importantly, these changes were observed already with the lowest expression level of RBM47 that was comparable or lower than those detected in endogenously RBM47 expressing cells (Figure 3—figure supplement 2D,E).

15To determine whether the 194 RBM47-responsive genes displayed clinically meaningful expression patterns, we conducted an unsupervised hierarchical clustering analysis of the TCGA cohort of breast cancer specimens. Two main clusters emerged, one of which harbored characteristics of the RBM47-low phenotype (‘Cluster 2’, Figure 6—figure supplement 1C). First, this subgroup, Cluster 2, had significantly lower RBM47 expression levels when compared to Cluster 1 (Figure 6D). Second, the genes that were induced upon RBM47 reintroduction tended to have lower expression in Cluster 2, whereas genes with reduced expression level in the RBM47-expressing cells tended to show higher expression in Cluster 2 (Figure 6E). These observations validated in clinical tumor samples the RBM47-dependent gene expression correlations identified in vitro.

16To identify directly regulated targets of RBM47, we combined the mRNA expression data with the HITS-CLIP-derived RBM47 transcriptome-wide binding data. Of the 2498 strongest binding partners with >100 tags per transcript (total tags in BC2 tags ≥10 clusters; Supplementary file 3), 25 were among the 102 RBM47-upregulated genes and 17 among the 92 RBM47-downregulated genes (Figure 6F), indicating no significant binding preference for either groups. This was reflected in the similar overall RBM47 binding profiles in both the up- and down-regulated genes (Figure 6G). Two of the top-scoring RBM47 binding mRNAs, IL8 and DKK1 (17,079 and 16,208 tags in clusters per gene, respectively, Figure 4G), were among the upregulated genes. This increase in mRNA levels was associated with increased protein secretion as determined by ELISA, whereas VEGFA, the mRNA of which was bound but not upregulated by RBM47, showed no change in protein secretion (Figure 6H).

17Nuclear RNA binding proteins typically function in large multiprotein complexes that regulate mRNA biogenesis. Our data from both genome-wide HITS-CLIP and RNA-seq analysis was compatible with RBM47 being a member of these RNA chaperone units. This suggested that RBM47 may not necessarily have a direct tumor suppressive signaling function. Rather, it raised the possibility that loss of RBM47, leading to subtle changes in multiple mRNAs, either through stabilization, destabilization or alternative splicing, could be selected for if the net effect of both growth-promoting and growth-inhibiting changes would be beneficial for cancer cells under the stress of dissemination to and colonizing distant organs. In line with this, both the up- and down-regulated target genes of RBM47, as well as the genes that were targets of RBM47-mediated alternative splicing, contain genes that have previously been shown to either promote or inhibit tumor phenotypes (Supplementary file 1 and Supplementary file 3). For example, DKK1, HTATIP2, HBP1, MXI1 and CASP7, all bound by RBM47 and upregulated upon RBM47 reintroduction, have known tumor suppressive functions. Similarly, RBM47-induced splicing changes were seen in genes such as SLK, MDM4 and TNC, all of which are genes with known functions in cancer.

18Focusing on DKK1, one of the most robustly bound RBM47 target transcripts identified by HITS-CLIP, we investigated the possible role of RBM47 as a modulator of mRNA abundance. As predicted by our results in WT6 and WT10 cells, knockdown of RBM47 in two additional breast cancer cell lines expressing high levels of endogenous RBM47, SKBR3 and ZR-75-30, reduced DKK1 mRNA levels (Figure 7A, Figure 7—figure supplement 1A). This validated RBM47 as a modulator of DKK1 mRNA level in breast cancer cells.

19The fact that RBM47 bound to DKK1 mRNA 3′UTR and increased DKK1 mRNA levels suggested the possibility that RBM47 had the capability of stabilizing DKK1 mRNA. We tested this by treating cancer cells with actinomycin D, a general inhibitor of transcription, and measuring DKK1 mRNA levels in the following hours. This demonstrated that wild type RBM47, but not the RBM47I281fs mutant, was able to increase the half-life of DKK1 mRNA by up to fourfold (Figure 7B).

20As RBM47 binding to DKK1 was concentrated on the 3′UTR, a known region of regulatory activity, we considered the possibility that RBM47 could compete with microRNAs or other mRNA destabilizing factors that target the 3′UTR. To test this experimentally, we generated miR-30-based shRNA-miR constructs that targeted different regions of the DKK1 transcript, two at the 5′ end with minimal RBM47 binding and three at the 3′ end with abundant RBM47 signal (Figure 7C; ). All constructs knocked the DKK1 transcript level down by 65–80% in the WT6 cells when no doxycycline was present (Figure 7D). The induction of RBM47 expression did not have a significant effect on the efficiency on the 5′-targeting shRNA-miRs (Figure 7E). In contrast, RBM47 inhibited the capability of the 3′-targeting shRNA-miRs to keep the DKK1 mRNA level down (Figure 7E). Similar observations were made with the WT10 cells (Figure 7F,G). Argonaute HITS-CLIP in the MDA231-BrM2 cells (CBM et al., unpublished data) indicates robust binding to the DKK1 3′UTR, supporting the regulatory role of this region. We conclude that the effects of RBM47 on DKK1 mRNA levels may be due to the ability of RBM47 to protect this mRNA from destabilizing factors, possibly through direct interaction with the DKK1 mRNA.

21DKK1 is an inhibitor of Wnt signaling, a pathway with a well-established role in regulating stem cell characteristics in both normal and malignant cells. Indeed, DKK1 as well as other Wnt antagonists have been shown to inhibit breast cancer progression. The fact that RBM47 was able to increase DKK1 secretion therefore suggested that RBM47 may also inhibit Wnt signaling and consequently reduce the tumorigenic fitness of metastatic breast cancer cells. We first tested the effects of RBM47 on cancer cell Wnt responsiveness by treating WT6 cells with recombinant Wnt3A and subsequently measuring the expression of AXIN2, a common TCF/β-catenin target gene and a general marker of Wnt activity. Doxycycline-induced expression of RBM47 in WT6 cells led to a dampened Wnt3A-dependent AXIN2 induction (Figure 8A). This inhibition of AXIN2 expression was at least partially dependent on DKK1 (Figure 8B). In agreement with these results, human breast cancers with low RBM47 expression had in general higher levels of Wnt transcriptomic activity when compared to tumors with high RBM47 expression in the TCGA cohort (Figure 8C).

22We then tested the possibility that RBM47 would suppress tumorigenesis by implanting low numbers of WT6 cells at the orthotopic site. The induction of RBM47 by doxycycline was able to significantly delay the emergence of mammary tumors (Figure 8D), and the tumors that formed were smaller in size (Figure 8E). This observation was confirmed in WT10 cells (Figure 8—figure supplement 1A). In line with this, inhibition of DKK1 expression in the MDA231-BrM2 cells promoted tumor formation in the orthotopic site (Figure 8F, Figure 8—figure supplement 1B). Finally, we used the two exon 1 DKK1 shRNAmiR constructs (Figure 7C) to reduce DKK1 levels in the WT6 cells (Figure 8—figure supplement 1C) and tested how this affected the brain metastatic ability of these cells in the presence of RBM47. Only 1/9 mice (16%) injected with control cells developed brain metastasis, whereas 8/17 mice (47%) inoculated with DKK1 RNAi construct transduced cells developed metastasis (Figure 8G,H). Taken together, these observations suggested that RBM47-dependent suppression of tumor progression was partially mediated by its ability to increase the production of the Wnt antagonist DKK1, a secreted protein that can inhibit tumor phenotypes in metastatic cancer cells.

23Cancer genomes contain numerous genes with low-frequency mutations of unknown functional significance. We have studied one such gene, the previously uncharacterized RBM47, and demonstrate that it has tumor suppressive functions in breast cancer. RBM47 acts as a multifunctional RBP modulating alternative splicing and the abundance of several mRNAs, which can lead to inhibition of cancer progression (Figure 8I,J). These results highlight the significance of infrequent mutations in cancer, the importance of integrated experimental approaches to identify such functionally relevant mutations, and the role of broadly targeted mRNA chaperones as determinants of cancer progression.

24RBM47 contains three classical RNA recognition motifs (RRM domains). The closest homologs of RBM47 are Apobec1 complementation factor (A1CF) and hnRNP-Q, which regulate RNA editing and splicing and transcript stability, respectively. In general, RBPs bind to and influence the function and fate of both pre-mRNAs and mRNAs. They can operate in large multiprotein complexes that dynamically regulate all the steps of mRNA biogenesis, nuclear export, stability and translation. Individual subunits of these complexes can therefore have diverse phenotypic roles depending on the exact protein complex they are in. Our observations on RBM47 are in line with these known general principles of RBP function.

25Our data demonstrate widespread and reproducible RBM47 binding to target mRNAs predominantly in introns and 3′UTRs, with the most robust binding occurring in 3′UTRs. Recent RNA-compete studies have proposed a binding motif for RBM47 in vitro. Our in vivo HITS-CLIP data does not suggest a clear nucleotide binding specificity for exogenous Flag-tagged RBM47, although some preference was observed for polyU stretches around CIMS sites. It has been shown that the presence of a canonical motif is neither necessary nor sufficient to predict HITS-CLIP binding sites of FUS in both mouse and human brain, while specific sites suggested by in vitro RNA selection experiments are not enriched in HITS-CLIP derived FMRP binding sites in vivo. This would suggest that other factors such as RNA accessibility, secondary structure or protein–protein interactions may modulate RBM47 target choice. Further work is therefore needed for a comprehensive understanding of the determinants of RBM47-mRNA interactions.

26We find that RBM47 binds robustly to ∼2500 gene transcripts in human breast cancer cells, with only a subset showing steady state level change or alternative splicing upon RBM47 reintroduction. Given the stringent criteria used to define RBM47-bound and regulated targets and the generally low level of intronic RNA in a cell, it is likely that this subset is an underestimation of the number of RBM47-regulated transcripts, and does not take into account the potential for regulatory events, such as re-localization, that may not alter steady state transcript levels. The complex interplay of RBPs in agonistic and antagonistic modulation of mRNA is becoming increasingly apparent. For example, the RRM-domain containing protein HuR modulates the destabilizing effects of miRNAs and AUF1 on common target transcripts. The data presented here suggest that target-specific RBM47 regulation may arise through modulation of accessibility of other factors to a common mRNA transcript.

27RBM47 binds and regulates transcripts that encode for proteins of several different biological functions. The effects of reduced RBM47 activity on cancer cell fitness, determined by the sum phenotypic output of all regulated target transcripts, may therefore vary depending on the context. Such pleiotropic effects could target multiple steps of cancer progression. Indeed, even though RBM47 loss was associated with metastatic cancer clones in our model systems, evidence for selection against RBM47 was detected already in primary breast cancers. One of the most highly bound RBM47 mRNA targets, the secreted Wnt inhibitor DKK1, is stabilized by RBM47 and partially mediates RBM47 tumor suppressive function. Interestingly, rbm47 knockdown in zebra fish embryos leads to a headless phenotype mediated via up-regulation of the wnt8a pathway. In addition to DKK1, our analysis identified a number of potential mediators of RBM47 effects for future studies.

28From a general perspective, the present findings illuminate two concepts. First, we show that low-frequency cancer mutations can give rise to tumorigenic phenotypes. Our work highlights the power of orthogonal approaches for the analysis of cancer genome resequencing data. Second, we show that loss of a broadly targeted and multifunctional RBP can increase the fitness of certain cancer cell clones in support of metastasis. This complements previous findings of RNA-binding proteins as mediators of oncogenic phenotypes. Deregulation of RNA-binding proteins is thus emerging as a prominent source of complex transcriptomic diversity that can serve as a platform for the selection of metastatic traits during tumor progression.

29The metastatic breast cancer cell lines have been previously described. SKBR3, ZR-75-30 and HCC1954 cells were obtained from ATCC (Manassas, VA). For retrovirus and lentivirus production, GPG29 and 293T cells, respectively, were utilized. All cell lines were maintained under standard tissue culture conditions. Single cell-derived clones were isolated utilizing fluorescence-activated cell sorting from genetically engineered 231-BrM2 (WT10, MUT3) and CN34-BrM2 (WT6) cells.

30For RBM47 restoration, RBM47 was cloned into the pBABE-puro retroviral expression vector. The RBM47I281fs was generated by site-directed mutagenesis. Virus was generated in the GPG29 packaging cells. For the generation of doxycycline-inducible expression constructs, both wild type and mutant FLAG-RBM47 were cloned into the pRetroX-Tight-Pur expression system (Clontech, Mountain View, CA).

31For RNAi-mediated gene silencing, RBM47 pGIPZ shRNA constructs (clones V2LHS_176331 and V3LHS_393928, respectively) were obtained from Open Biosystems (Lafayette, CO). The DKK1 shRNAmiR constructs were designed based on the rules described by and cloned into the pGIPZ vector as described using the following oligonucleotide templates:DKK1miRm: TGCTGTTGACAGTGAGCGACGGGTCTTTGTCGCGATGGTATAGTGAAGCCACAGATGTATACCATCGCGACAAAGACCCGGTGCCTACTGCCTCGGADKK1miRn: TGCTGTTGACAGTGAGCGACACCTTGAACTCGGTTCTCAATAGTGAAGCCACAGATGTATTGAGAACCGAGTTCAAGGTGGTGCCTACTGCCTCGGADKK1miRo: TGCTGTTGACAGTGAGCGCCAACTCAATCCTAAGGATATATAGTGAAGCCACAGATGTATATATCCTTAGGATTGAGTTGATGCCTACTGCCTCGGADKK1miRp: TGCTGTTGACAGTGAGCGACAGTAAATTACTGTATTGTAATAGTGAAGCCACAGATGTATTACAATACAGTAATTTACTGCTGCCTACTGCCTCGGADKK1miRq: TGCTGTTGACAGTGAGCGAAACGGAAGTGTGATATGTTTATAGTGAAGCCACAGATGTATAAACATATCACACTTCCGTTCTGCCTACTGCCTCGGA

32DKK1miRm: TGCTGTTGACAGTGAGCGACGGGTCTTTGTCGCGATGGTATAGTGAAGCCACAGATGTATACCATCGCGACAAAGACCCGGTGCCTACTGCCTCGGA

33DKK1miRn: TGCTGTTGACAGTGAGCGACACCTTGAACTCGGTTCTCAATAGTGAAGCCACAGATGTATTGAGAACCGAGTTCAAGGTGGTGCCTACTGCCTCGGA

34DKK1miRo: TGCTGTTGACAGTGAGCGCCAACTCAATCCTAAGGATATATAGTGAAGCCACAGATGTATATATCCTTAGGATTGAGTTGATGCCTACTGCCTCGGA

35DKK1miRp: TGCTGTTGACAGTGAGCGACAGTAAATTACTGTATTGTAATAGTGAAGCCACAGATGTATTACAATACAGTAATTTACTGCTGCCTACTGCCTCGGA

36DKK1miRq: TGCTGTTGACAGTGAGCGAAACGGAAGTGTGATATGTTTATAGTGAAGCCACAGATGTATAAACATATCACACTTCCGTTCTGCCTACTGCCTCGGA

37The pGIPZ empty vector was used as a control.

38All animal experiments were performed in accordance with a protocol approved by MSKCC Institutional Animal Care and Use Committee. Lung metastasis assays were conducted in 5–7 week old female NOD/SCID mice. Brain metastasis and mammary tumor assays were carried out using 5–7 week old female athymic nude mice. In vivo bioluminescence imaging was performed using the IVIS Spectrum Xenogen machine (Caliper Life Sciences, Hopkinton, MA). For orthotopic mammary tumor assays, cells were mixed with Matrigel. Injections were confirmed and tumor growth was followed by bioluminescent imaging. Statistical significance of tumor and metastasis free survival was assessed by the log-rank test. Differences in raw and normalized bioluminescence signal was assessed by the Student's t test and Wilcoxon rank-sum test, respectively. Brain images were acquired with a Leica SP5 up-right confocal microscope and Zeiss AxioVert 200 M using 20X and 5X objectives. Image analysis was performed with Metamorph and ImageJ softwares.

39Total RNA was extracted using PrepEase RNA spin kit (USB, Cleveland, OH). We used Transcriptor First Strand cDNA Synthesis Kit (Roche, Indianapolis, IN) for cDNA synthesis. Quantitative PCR was performed using predesigned Taqman gene expression assays (Life Technologies, Carlsbad, CA) and the 7900HT or ViiA 7 real-time PCR systems (Applied Biosystems/Life Technologies). TBP was used as a housekeeping control gene. mRNA stability was assessed by performing quantitative PCR after actinomycin D treatment. For immunoblotting, antibodies recognizing RBM47 (HPA006347; Sigma, St. Luis, MO), α-tubulin (11H10; Cell Signaling, Danvers, MA) and ACTB (Sigma) were utilized. Secondary antibodies were HRP (Pierce, Rockford, IL) or fluorescence (LiCor, Lincoln, NE) conjugated. Immunostaining for RBM47 (HPA006347; Sigma) was performed according to standard protocols in the MSKCC Molecular Cytology Core Facility on paraffin embedded tissue blocks. Secreted protein was detected by ELISA (R&D, Minneapolis, MN).

40231BrM2 tet-on FLAG-RBM47 cells were treated with 1 ng/ml doxycycline for 3 days before 254 nm UV crosslinking at 400 mJ/cm2 on a bed of ice (Stratalinker2400; Stratagene, La Jolla, CA). Samples were processed for HITS-CLIP as previously described using an anti-Flag antibody (F3165; Sigma), and omitting 3′ linker ligation in favor of direct labeling of protein-bound RNA with 32P-γ-ATP. Non-crosslinked cells were used as a negative control, with IPed Flag-RBM47 protein detected using a second anti-Flag antibody (F7425; Sigma). Purified RBM47-bound RNA fragments were polyA tailed (E-PAP; NEB), and reverse transcribed (Superscript III; Invitrogen, Carlsbad, CA) in the presence of Br-dUTP (Sigma). Unique polydT-NV RT-primers were used per replicate, containing Solexa sequences separated by an abasic furan (that serves as an ApeI cut site), a 6 nt degenerate region and a 6 nt index sequence to allow for multiplexing during sequencing.RT Primer 1pGCACTGTTN6GATCGTCGGACTGTAGAACTCT/idSp/CAAGCAGAAGACGGCATACGAT20VNRT Primer 2pGCGAAACTN6GATCGTCGGACTGTAGAACTCT/idSp/CAAGCAGAAGACGGCATACGAT20VN

41RT Primer 1pGCACTGTTN6GATCGTCGGACTGTAGAACTCT/idSp/CAAGCAGAAGACGGCATACGAT20VN

42RT Primer 2pGCGAAACTN6GATCGTCGGACTGTAGAACTCT/idSp/CAAGCAGAAGACGGCATACGAT20VN

43BrdU-cDNA was stringently purified by IP (sc-32323; Santa Cruz, Dallas, TX) using ProteinG dynabeads (Invitrogen), eluted from the beads via BrdU competitive elution (Sigma), and re-immunoprecipitated. cDNA was circularized on bead (CircLigase ssDNA Ligase II, Epicentre, Madison, WI), washed and digested with ApeI (NEB, Ipswich, MA) to relinearize. cDNAs were eluted from the beads by heating to 98C in Phusion HF Buffer (NEB), then PCR amplified using Phusion DNA polymerase (NEB) and SYBR Green I (Invitrogen) in an iQ5 real-time PCR machine in order to monitor amplification, with the samples being removed when the RFU signal reached ∼1000.

44P5—aatgatacggcgaccaccgacaggttcagagttctacagtccgacg

45P3—caagcagaagacggcata

46PCR products were purified using MinElute columns (Qiagen, Valencia, CA) as per manufacturer's instructions and quantified using Quant-It (Invitrogen). cDNA was multiplexed and sequenced using Illumina Hi-Seq (small RNA sequencing primer—cgacaggttcagagttctacagtccgacgatc). All data analysis was done using the Galaxy platform, as previously described.

47RT-PCR validiation was carried out using total RNA from MDA231-BrM2 (Control) and WT10 cells (iScript, Bio-Rad, Accuprime Pfx Supermix 1, Life Technologies) as previously described. In all cases lanes 1–3 contain an equal mixture of control and WT10 cell cDNA amplified at n-1, n and n+1 cycles, lane 4 contains an absence of reverse transcriptase control (−RT), with all other lanes corresponding to replicate samples of the indicated cell type amplified to n cycles. IR and ΔI calculated using ImageJ.

48All analyses were conducted using R. Microarray data from human untreated tumor data sets (GSE2603 and GSE2034) were preprocessed as described. For the RNA-seq TCGA data set, normalized mRNA z-scores were downloaded from the TCGA cBio portal. The microarray data from metastatic cell lines were processed with GCRMA together with updated probe set definitions using R packages affy, gcrma and hs133ahsentrezgcdf (version 10). Unsupervised hierarchical clustering was performed using the function heatmap.2 with Pearson's correlation coefficient as the similarity metric. For survival analysis, a Cox proportional hazards model was utilized as implemented in the coxph function in the R-package survival. For RNA-seq analysis of the cell lines, raw paired-end sequencing data were mapped to human genome (hg19 build) with STAR2.3.0 using standard options. Reads mapped to each transcript were counted by HTSeq v0.5.4 with default settings. The read count table was normalized to library size by DESeq. Correlation with RBM47 expression was assessed by Pearson's correlation coefficient utilizing the R functions cor and cor.test. Wnt pathway activity in clinical tumors was assessed utilizing a curated list of Wnt target genes in breast cancer and calculating sums of z-scores for each tumor.

49RNA-seq and HITS-CLIP data have been deposited to the Gene Expression Omnibus under the accession numbers GSE53779 and GSE58381.