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Functional screen identifies RBM42 as a mediator of oncogenic mRNA translation specificity

Nature Cell Biology volume 27, pages 518–529 (2025)Cite this article

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Abstract

Oncogenic protein dosage is tightly regulated to enable cancer formation but how this is regulated by translational control remains unknown. The Myc oncogene is a paradigm of an exquisitely regulated oncogene and a driver of pancreatic ductal adenocarcinoma (PDAC). Here we use a CRISPR interference screen in PDAC cells to identify activators of selective MYC translation. The top hit, the RNA-binding protein RBM42, is highly expressed in PDAC and predicts poor survival. We show that RBM42 binds and selectively regulates the translation of MYC and a precise suite of pro-oncogenic transcripts, including JUN and EGFR. Mechanistically, we find that RBM42 binds and remodels the MYC 5′ untranslated region structure, facilitating the formation of the translation pre-initiation complex. Importantly, RBM42 is necessary for PDAC tumorigenesis in a Myc-dependent manner in vivo. This work transforms the understanding of the translational code in cancer and illuminates therapeutic openings to target the expression of oncogenes.

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Fig. 1: Functional CRISPRi screen identifies regulators of MYC translation.
Fig. 2: The RBP RBM42 regulates MYC translation in pancreatic cancer.
Fig. 3: RBM42 is necessary for pancreatic cancer cell growth through Myc.
Fig. 4: RBM42 directly binds and regulates the translation of a pro-oncogenic programme.
Fig. 5: RBM42 remodels the structure of the MYC 5′ UTR and acts as a ribosome-associated protein to promote efficient translation initiation.
Fig. 6: RBM42 regulates in vivo PDAC tumorigenesis.

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Data availability

Sequencing data that support the findings of this study have been deposited in the Gene Expression Omnibus under the following accession codes: total RNA-seq, GSE255533; polysome sequencing, GSE255702; RBM42 cytoplasmic CLIP-seq, GSE255703; MYC 5′ UTR DMS-seq, GSE255740; and EGFR and JUN 5′ UTR DMS-seq (GSE279023). RBM42 immunoprecipitation mass spectrometry data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD058353. For the mass spectrometry analysis, all generated peak lists were searched against the human subset of the SwissProt database (v.2019.07.31). The Xena browser (https://xenabrowser.net/) was used to retrieve PDAC normal and tumour RNA expression data. Quantitative protein expression of PDAC and normal pancreas was retrieved using the UALCAN Proteomics online tool (https://ualcan.path.uab.edu/analysis-prot.html). Data for the survival analyses were retrieved from https://pancreas.kmplot.com/ and the Gene Expression Omnibus (GSE62452). The comparison of human PDAC RNA and protein expression were retrieved using the cBio Cancer Genomics Portal (http://www.cbioportal.org/). The human PDAC data for the GSEA analyses were derived from the TCGA Research Network (http://cancergenome.nih.gov/). The dataset derived from this resource that supports the findings of this study is available from the TCGA Pan-cancer dataset using the cBio Cancer Genomics Portal (http://www.cbioportal.org/). All other data supporting the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.

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Acknowledgements

We thank all of the members of the Ruggero laboratory, especially D. Kuzuoglu-Öztürk, for critical discussion of the project and for manuscript feedback. We thank H. Karner (UCSF) for technical support for the CLIP experiments and B. Zarnegar (Stanford University) for CLIP advice and irCLIP reagents. Sequencing was performed at the UCSF CAT, supported by UCSF PBBR, RRP IMIA and NIH 1S10OD028511-01 grants. Fluorescence-activated cell sorting and BC43 spinning disk confocal microscopy were conducted in the HDFCCC Laboratory for Cell Analysis Shared Resource Facility through a grant from NIH (P30CA082103). Mass spectrometry was provided by the Mass Spectrometry Resource at UCSF (A. L. Burlingame, Director), supported by the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation. J.R.K. was funded by an American Cancer Society postdoctoral fellowship (133966‐PF‐20‐009‐01‐RMC) and a UCSF Mentored Scientist Award in Pancreas Cancer (RAP 7031426). G.H. was supported by the National Science Foundation Graduate Research Fellowship Program (NSF2034836). H.G. is an Arc Institute Core Investigator. Research in the H.G. laboratory is supported by the Arc Institute. R.M.P. is funded by R01CA240603 (NCI; NIH), an AACR-MPM Oncology Charitable Foundation Transformative Cancer Research Grant and an Ed Marra Passion to Win Fund. D.R. is funded by the NIH (R35CA242986) and the American Cancer Society (American Cancer Society Research Professor Award). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Department of Urology, University of California San Francisco, San Francisco, CA, USA

    Joanna R. Kovalski, Goksu Sarioglu, Vishvak Subramanyam, Macey Slota, Nimmy Mohan, Kaylee Yiakis, Isabelle Liu, Sohit Miglani, Hani Goodarzi & Davide Ruggero

  2. Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA

    Joanna R. Kovalski, Goksu Sarioglu, Vishvak Subramanyam, Grace Hernandez, Gilles Rademaker, Macey Slota, Nimmy Mohan, Kaylee Yiakis, Isabelle Liu, Sohit Miglani, Hani Goodarzi, Rushika M. Perera & Davide Ruggero

  3. Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA

    Vishvak Subramanyam, Isabelle Liu, Sohit Miglani & Hani Goodarzi

  4. Department of Anatomy, University of California San Francisco, San Francisco, CA, USA

    Grace Hernandez, Gilles Rademaker & Rushika M. Perera

  5. Department of Pathology, University of California San Francisco, San Francisco, CA, USA

    Grace Hernandez, Gilles Rademaker, Kwun Wah Wen, Grace E. Kim & Rushika M. Perera

  6. Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, USA

    Juan A. Oses-Prieto & Alma L. Burlingame

  7. Arc Institute, Palo Alto, CA, USA

    Hani Goodarzi

  8. Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA

    Davide Ruggero

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  1. Joanna R. Kovalski
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Contributions

The study was designed by J.R.K. and D.R. J.R.K, G.S., M.S., N.M. and K.Y. performed experiments. V.S., I.L. and S.M. conducted the bioinformatic analyses, with supervision and input from H.G. G.H., G.R. and R.M.P. provided human and mouse pancreas cancer specimen sections, aided in tissue staining, imaging and quantification, and contributed conceptually to this project. K.W.W. and G.E.K. provided human pancreas cancer specimens. J.A.O.-P. and A.L.B. performed mass spectrometry analysis. J.R.K., G.S. and D.R. wrote the paper; all other authors contributed to the review and editing of the paper.

Corresponding author

Correspondence to Davide Ruggero.

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Competing interests

D.R. is a shareholder of eFFECTOR Therapeutics, Inc. and is a member of its scientific advisory board. The other authors declare no competing interests.

Peer review

Peer review information

Nature Cell Biology thanks Bruno Amati, Ivan Topisirovic and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Validation and characterization of selective MYC translation screen candidates.

(a) Volcano plot showing positive control known activators and negative control genes of MYC translation from Panc-1 CRISPRi reporter screen. eIF5A was previously identified and validated as the sole hit in a MYC translational repressor screen25. Mann–Whitney p-value, two-sided. (b) Gene ontology molecular function enrichment for the 309 candidate repressors of MYC translation in Panc-1 cells. Gene ratio is the fraction of genes identified within the GO term. Fisher’s Exact Test with Bonferroni correction. (c) mRNA expression of UBAP2L, METTL3 and YTHDF2 in healthy pancreas (GTex) versus pancreatic adenocarcinoma (PDAC)62; Welch’s t-test, two-tailed. (d) Protein expression of UBAP2L, METTL3 and YTHDF2 normal versus tumour from CPTAC dataset; two-sided t-test41. Normal/primary tumour UBAP2L maximum: 0.81/2.133, upper quartile: −0.314/0.63, median: −0.678/0.009, lower quartile: −1.052/−0.805 and minimum: −1.933/−2.799. Normal/primary tumour METTL3 maximum: 1.804/1.932, upper quartile: 0.937/0.503, median: 0.308/−0.71, lower quartile: −0.454/−0.71 and minimum: −2.687/−2.486. Normal/primary tumour YTHDF2 maximum: 0.85/2.05, upper quartile: 0.014/0.547, median: −0.47/0.037, lower quartile: −0.912/−0.761 and minimum: −2.097/−2.015. (e) Single guide validation with 2 independent sgRNAs in the Panc-1 MYC translational reporter cell line used for the CRISPRi screen at day 5 doxycycline treatment, positive controls EIF4A1 and EIF4H. sgEIF4A1 n = 18; sgEIF4H, sgRBM42, sgUBAP2L, n = 4; sgMETTL3 and sgYTHDF2 n = 6. (f) qPCR RNA quantification of single guide validation experiments. sgEIF4A1 n = 12; sgEIF4H and sgRBM42 n = 4; sgUBAP2L, sgMETTL3 and sgYTHDF2 n = 2. (g) Single guide validation of negative control genes with 2 independent sgRNAs in the Panc-1 MYC translational reporter cells. sgEIF4A1 n = 18, sgEIF3E and sgMSI1 n = 6, sgRBM23-1 n = 8, sgRBM23-2 and ssgSF3B1 n = 6. (h) qPCR RNA quantification of negative control gene experiments. sgEIF4A1 n = 9, sgEIF3E and sgMSI1 n = 3, sgRBM23-1 n = 4, sgRBM23-2 and sgSF3B1 n = 3. (i) Quantification of RNA from UBAP2L, METTL3 and YTHDF2 knockdown experiments in Panc-1 cells. shCNTL n = 7, shUBAP2L n = 6, shMETTL3 and shYTHDF2 n = 3. (j) qPCR analysis of MYC mRNA from 10–50% sucrose gradient fractionation of control or YTHDF2 knockdown in Panc-1 cells, n = 3. (k) Total RNA quantification from UBAP2L, METTL3 and YTHDF2 knockdown polysome experiments, n = 3. (l) qPCR analysis of control genes, ACTB or B2M, from 10–50% sucrose gradient fractionation of control or YTHDF2 knockdown in Panc-1 cells, n = 3. (m) Correlation of UBAP2L and Myc protein abundance from human pancreatic adenocarcinoma specimens41, n = 17. All graphs mean ± SEM. Total RNA quantification in i,k one-way ANOVA, uncorrected Fisher’s LSD test relative to own shCNTL. Polysome distribution in j two-way ANOVA, uncorrected Fisher’s LSD test. Extended data associated with Fig. 1.

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Extended Data Fig. 2 RBM42 is necessary and sufficient for regulating Myc protein expression.

(a) Western blot analysis and quantification of RNA and protein expression of Myc and RBM42 with RBM42 knockdown in MiaPaca2 pancreatic cancer cells, n = 3. *P = 0.0141, ***P = 0.0003, ****P < 0.0001. (b) qPCR RNA quantification for the knockdown experiments in Fig. 2d. PDAC cell line RNA and protein quantification one-way ANOVA, uncorrected Fisher’s LSD test relative to own shCNTL. *P = 0.0246, ****P < 0.0001. (c) Enriched Hallmarks and transcription factor (TF) targets from gene set enrichment analysis (GSEA) of genes with altered expression in Panc-1 shCNTL vs. shRBM42 RNA-seq data sets, Normalized Enrichment Score (NES). P-value estimation is based on an adaptive multi-level split Monte-Carlo scheme. (d) qPCR quantification of RNA expression of core Myc targets and previously reported Myc targets in PDAC (blue text) in Panc-1 cells with MYC or RBM42 depletion; n = 3, mean ± SEM. Unpaired two-tailed t-test relative to shCNTL. (e) Western blot analysis and quantification of RNA and protein expression of Myc and RBM42 with MYC knockdown in Panc-1 pancreatic cancer cells, n = 3. Unpaired two-tailed t-test. (f) Quantification and representative western blots of RBM42 and Myc RNA and protein levels with exogenous Myc expression in HPDE cells, n = 4. Unpaired two-tailed Welch’s t-test. (g) Quantification and representative western blots of RBM42 and Myc RNA and protein levels with exogenous RBM42 expression in HPDE cells, n = 4. Unpaired two-tailed Welch’s t-test. (h) Representative western blots of puromycin incorporation assay of global translation with RBM42 depletion in additional pancreatic cancer cell lines. Values indicate normalized puromycin incorporation relative to shCNTL. All graphs are mean ± SD unless otherwise indicated. All western blots are representative of 3 experiments. Extended data associated with Fig. 2.

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Extended Data Fig. 3 RBM42 loss does not alter Myc protein stability or RNA splicing.

(a) Myc protein cycloheximide (CHX) stability assay quantification and representative western blots in Panc-1 cells, n = 3 independent experiments. Both bands were quantified for Myc protein levels. P-value of the difference between the slopes of a simple linear regression. Values under blot indicate normalized Myc protein expression relative to shCNTL; mean ± SD. (b) qPCR quantification of retained introns for MYC and control mRNA B2M, n = 3. Two-way ANOVA, uncorrected Fisher’s LSD test. (c) Panc-1 shCNTL and shRBM42 RNA-seq global splicing analysis (rMATS) collapsed to gene level, graphing the event with the highest ΔPSI, (n = 3 replicates/condition). Table events FDR < 0.05 and |ΔPSI| > 0.1. (d) Additional human patient PDAC specimen RBM42 immunohistochemistry (IHC). Disease grade (G) and stage, where reported, are listed. Representative image of at least 3 fields per patient. Scale bars, 50 μm. (e) Representative western blots of cytoplasmic and nuclear fractionation of pancreatic cancer cell lines. Western blot representative of 3 independent experiments. Graphs are mean ± SEM unless otherwise noted. Extended data associated with Fig. 2.

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Extended Data Fig. 4 RBM42 and Myc RNA and protein expression in phenotyping experiments and validation of RBM42 necessity for PDAC cell growth.

(a,b) Myc and RBM42 protein and RNA expression levels corresponding to the experiments in Fig. 3, n = 3. Graphs are mean ± SD; one-way ANOVA, uncorrected Fisher’s LSD test relative to own shCNTL. ****P < 0.0001. (c) Representative western blots demonstrating for the PDAC cell line growth with RBM42 depletion. Representative of at least two independent experiments. Extended data associated with Fig. 3.

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Extended Data Fig. 5 RBM42 regulates the translation of a broad suite of pro-oncogenic mRNAs.

a) Endogenous RBM42 irCLIP control RNA ligation blot −/+ UV crosslinking with titration of RNase I treatment. (b) Endogenous cytoplasmic or nuclear RBM42 CLIP-qPCR for mature MYC mRNA (lacking intron 2) fold over IgG control; n = 5. Ratio paired two-tailed t-test. (c) Nuclear RBM42 CLIP-qPCR positive control binding to known nuclear RNA interactions with U4 and U6 for the samples in (b); mean ± SEM, n = 5. Ratio paired two-tailed t-test compared to IgG control. (d) KEGG functional enrichment of genes bound in their 5′UTRs by RBM42. Terms related to cancer highlighted in red. Fisher’s Exact Test with Bonferroni correction. (e) Polysome qPCR analysis of PAK4, EZR or SRF mRNA from 10–50% sucrose gradient fractionation of control or RBM42 knockdown in Panc-1 cells; n = 3, mean ± SEM. Two-way ANOVA, uncorrected Fisher’s LSD test. (f) Total RNA quantification for the RBM42-knockdown polysomes; n = 3. Paired two-tailed t-test. (g) Representative western blots and protein quantification for PAK4, Ezrin (EZR), and SRF with RBM42 depletion in Panc-1 cells, n = 6. One-way ANOVA, uncorrected Fisher’s LSD test, *P = 0.0369, **P = 0.0052, ***P = 0.0004, ****P < 0.0001. (h) Dual luciferase assays (DLA) with the 5′ UTRs of additional RBM42 translational target genes with control or RBM42 depletion in Panc-1 cells. Renilla (RLuc) and firefly (FLuc) luciferase values normalized to RNA expression. RNA quantification validating RBM42 depletion in the DLA samples; 5′ UTR EGFR, JUN, PAK4 and EZR n = 4, and 5′ UTR SRF n = 6, mean ± SEM. Unpaired two-tailed t-tests, ****P < 0.000001. All graphs mean ± SD unless noted. Extended data associated with Fig. 4.

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Extended Data Fig. 6 RBM42 alters MYC mRNA structure, interacts directly with 43S pre-initiation complex members in the cytoplasm and regulates MYC translation efficiency.

(a) DMS-Seq-determined full-length MYC 5′ UTR RNA structure in Panc-1 cells with RBM42 depletion. Red arrow indicates the RBM42 binding site. (b) MYC 5′UTR Stem III from shRBM42 structure showing the changes in DMS reactivity shRBM42 relative to shCNTL. (c) qPCR quantification of RBM42 mRNA levels in the dual luciferase assay experiments in Fig. 5c. One-way ANOVA, uncorrected Fisher’s LSD test to WT shCNTL, ****P < 0.0001. WT shCNTL and WT shRBM42 n = 12, deletion and compensatory mutants shRBM42 n = 6. (d) DMS-Seq-determined full-length EGFR 5′ UTR RNA structure in Panc-1 cells. Red arrow indicates the RBM42 binding site. (e) DMS-Seq-determined full-length JUN 5′ UTR RNA structure in Panc-1 cells. Red arrows indicate the RBM42 binding sites. (f) Cytoplasmic and nuclear fraction blot to confirm proper fractionation for co-IP blots in Fig. 5f. Total RNA gel to confirm RNase A digestion. (g) Representative IP-western blots of eGFP–HA or RBM42–HA from the nuclear fraction confirming known RBM42 interaction with SNRNP200 and PRPF8, but lack of interaction with 40S ribosomal components (corresponding fractionation blot in (f)). (h) Representative IP-western blots of eGFP–HA or RBM42–HA from the cytoplasmic fraction probing for IP negative controls (EGFR, HSP90 and GAPDH) and initiation factors previously implicated in MYC translation initiation (eIF4A1, eIF5A and eIF4E). (i) 48S PIC assembly assay with control mRNA TUBB and quantification of decreased RBM42 and Myc protein levels for the experiment in Fig. 5j. Paired two-tailed t-tests, n = 4. All graphs mean ± SD. All western blot images are representative of 3 experiments. Extended data associated with Fig. 5.

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Extended Data Fig. 7 RBM42 regulates in vivo PDAC tumorigenesis through Myc.

(a) Gene set enrichment analysis (GSEA) top 5 hallmarks comparing top quartile vs. bottom quartile of RBM42 RNA expression in TGCA PAAD RNA-sequencing data (n = 45 patients/quartile), Normalized Enrichment Score (NES). P-value estimation is based on an adaptive multi-level split Monte-Carlo scheme. (b) Additional representative Myc and RBM42 immunofluorescence co-staining in human PDAC tissue. Location of higher magnification images shown in Fig. 6e indicated. Higher magnification images scale bar, 5 μm. Images representative of at least 3 fields per patient, n = 11 patients analysed. (c) Quantification of RBM42 low protein expression and Myc expression per cell overlap/patient; n = 6–48 ducts/patient, mean ± SEM. (d) MiaPaca2 and (e) BxPC3 Myc and RBM42 protein expression levels in the cells injected into subcutaneously into mice. Western blots from one experiment per cell type. Extended data associated with Fig. 6.

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Supplementary information

Supplementary Information

Single figure illustrating the gating strategy for the flow screen and follow-up validation experiments.

Reporting Summary

Supplementary Tables

Supplementary Table 1. Selective translational reporter CRISPRi screen. The output of the analysis for the whole-genome CRISPRi screen for regulators of MYC translation through its 5′ UTR. The table contains the individual data for reach replicate and the average, including the gene name, which transcript it targets, P value and average phenotype score, that is, log2[fold change (top/bottom sgRNA counts)]. It also includes the discrimination score (DS). Supplementary Table 2. RNA expression changes with RBM42 depletion. Differential gene expression with RBM42 depletion (shRBM42-1) in Panc-1 cells. The table shows the gene name, log2(fold change shRBM42) compared with control, the P value and the adjusted P. Supplementary Table 3. RBM42 depletion splicing analysis in Panc-1 cells. Differential splicing analysis with RBM42 depletion using rMATS. The table shows gene name, feature type (SE, skipped exon; A5SS, alternative 5′ splice site; A3SS, alternative 3′ splice site; MXE, mutually exclusive exons; RI, retained intron), chromosome coordinates, strand, statistics, the difference in PSI between RBM42 depletion and control (dPSI), read counts for the event per sample and per cent spliced in (PSI) per sample. Supplementary Table 4. RBM42 cytoplasmic 5′ UTR RNA-binding events identified by CLIP analysis. Output from CIMS analysis of RBM42 CLIP data for annotated 5′ UTRs of coding genes. The table contains CIMS genome coordinates, strand, number of reads (tagNumber(k)), number of mutations detected (mutationFreq(m)), the number of clustered mutation sites with k tags that have ≥m mutation frequency (count(=>m, k)), FDR, transcript ID and gene name. Genes used for the overlapping analyses shown in Fig. 4 are listed in the last column (FDR < 0.05). Supplementary Table 5. RBM42 depletion polysome sequencing quantification of translation-efficiency changes. Polysome sequencing analysis of translation efficiency in control or RBM42 knockdown. EdgeR was used to quantify and statistically evaluate the difference in translational efficiency (TE = (high translation) / (untranslated + low translation)) between control and RBM42 depletion. logFC, log2-transformed fold change of shRBM42 over shCNTL; AveExpr, average expression across all samples, in log2(CPM); t, logFC divided by its standard error; P value, raw P value (based on t) from test that logFC differs from zero; and adjusted P, Benjamini–Hochberg FDR-adjusted P value. ‘5UTR_RBM42_Bound’ indicates the genes that are significantly bound by RBM42 in the 5′ UTR and ‘Overlap’ indicates the genes that are both significantly bound by RBM42 and translationally downregulated with RBM42 loss (Y, yes). Supplementary Table 6. DMS-sequencing reactivity values and base-pairing probabilities for the MYC 5′ UTR. The table contains the per-base DMS reactivities and probabilities for base pairing that underlie the data and structures in Fig. 5a,b and Extended Fig. 6a,b for the MYC 5′ UTR sequence in shCNTL, shRBM42-1 or shRBM42-2 generated using the rnaframework toolkit. Supplementary Table 7. DMS-sequencing reactivity values and base-pairing probabilities for the EGFR and JUN 5′ UTRs. The table contains the per-base DMS reactivities and probabilities for base pairing that underlie the data and structures in Extended Data Fig. 6e,f generated using the rnaframework toolkit. Supplementary Table 8. Proteins interacting with cytoplasmic RBM42. Proteomics data from the mass spectrometry analysis of IgG or endogenous RBM42 immunoprecipitation from the cytoplasmic fraction of Panc-1 PDAC cells. Supplementary Table 9. List of oligonucleotide sequences used in this study. This list includes the DNA sequences for the sgRNAs, shRNAs and qPCR primers used for all experiments in the article.

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Kovalski, J.R., Sarioglu, G., Subramanyam, V. et al. Functional screen identifies RBM42 as a mediator of oncogenic mRNA translation specificity. Nat Cell Biol 27, 518–529 (2025). https://doi.org/10.1038/s41556-024-01604-7

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