A TranSNP in the DDIT4 mRNA can impact its translation efficiency and modulate p53-dependent responses in cancer cells

  1. Meriem Hadjer Hamadou
  2. Laura Alunno
  3. Tecla Venturelli
  4. Samuel Valentini
  5. Davide Dalfovo
  6. Francesca Lorenzini
  7. Alessia Mattivi
  8. Vincenza Vigorito
  9. Glenda Paola Grupelli
  10. Alessandro Matte’
  11. Pamela Gatto
  12. Michael Pancher
  13. Chiara Valentini
  14. Veronica De Sanctis
  15. Roberto Bertorelli
  16. Virginie Marcel
  17. Emilio Cusanelli
  18. Stefano Freddi
  19. Giovanni Bertalot
  20. Sara Zaccara
  21. Marina Mione
  22. Luca L. Fava
  23. Alessandro Romanel
  24. Alberto Inga

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Abstract

Relatively few studies have examined the link between SNPs and mRNA translation, despite the established importance of translational regulation in shaping cell phenotypes. We developed a pipeline analyzing the allelic imbalance in total and polysome-bound mRNAs from paired RNA-seq data of HCT116 cells and identified 40 candidate tranSNPs, i.e. SNPs associated with allele-specific translation. Among them, the SNP rs1053639 (T/A) on DNA damage-inducible transcript 4 (DDIT4) 3’UTR was identified, with the reference T allele showing a higher polysome association. rs1053639 TT clones generated by genome editing exhibited significantly higher DDIT4 protein levels than AA ones. The difference in DDIT4 proteins was even greater when cells were treated with Thapsigargin or Nutlin, two perturbations that induce DDIT4 transcription. The RNA-binding protein RBMX influenced these allele-dependent differences in DDIT4 protein expression, as shown by RNA-EMSA, RIP, and smiFISH assays. RBMX depletion reduced DDIT4 protein in TT clones to the AA levels. Functionally, TT clones more effectively repressed mTORC1 under ER stress, while AA clones outcompeted TT clones in vitro or when injected in zebrafish embryos. RBMX depletion increased the fitness of TT cells in co-culture experiments. The rs1053639 AA genotype, under a recessive model, correlates with poor prognosis in TCGA cancer data.

Key points

  • -

    Translatome analysis in HCT116 cells revealed allele-specific mRNA translation for 40 SNPs

  • -

    rs1053639 (T/A) in DDIT4 3’UTR showed allelic differences in mRNA localization & protein expression

  • -

    AA cells showed weaker mTOR inhibition & higher proliferation; AA individuals had poorer prognosis

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      Referee #3

      Evidence, reproducibility and clarity

      Hamadou, Alunno et al. have found evidence for the notion that although translational regulation plays a key role in determining cell behavior, few studies have explored how single nucleotide polymorphisms (SNPs) affect mRNA translation. They developed a method to analyze allele-specific expression in both total and polysome-associated mRNA using RNA-seq data from HCT116 cells. This approach revealed 40 potential "tranSNPs"-SNPs linked to differences in translation between alleles. One SNP, rs1053639 (T/A) in the 3' untranslated region of the DDIT4 gene, was found to influence translation: the T allele was more often associated with polysomes. Cells engineered to carry the TT genotype produced more DDIT4 protein than those with the AA genotype, especially when exposed to stressors like Thapsigargin or Nutlin that boost DDIT4 transcription. The authors found that the RNA-binding protein RBMX mediates this allele-specific protein expression. Knocking down RBMX in TT cells lowered DDIT4 protein levels to those seen in AA cells. Functionally, TT cells suppressed mTORC1 activity more effectively under ER stress, whereas AA cells had a growth advantage in cell culture and in zebrafish models. In human cancer data from TCGA, individuals with the AA genotype had poorer outcomes under a recessive genetic model.

      The manuscript needs major revision due to additional data interpretation, lack of statistical analysis, and lack of mechanistic and causal insights. The paper is overall correlative and descriptive and has not enough data to claim a translation regulation aspect of DDIT4 and the protein product to cause the observed genotypic differences stemming from a SNP in the 3' UTR. The paper reads as a collection of individual findings that do not seem to be very cohesive and ranges from polysome-seq, RBP binding, ER stress, mTOR activity, cellular co-culture tumor models and zebrafish tumor models. I wish the authors would have focused on one aspect and described one finding well. Without addressing these fundamental concerns, the study's core claims regarding p53-dependent responses in cancer remain unsubstantiated. Overall, this reviewer supports the publication in a Review Commons journal dependent on that the points of criticism are adequately addressed in the course of a major revision.

      Major comments:

      1. Fig.1: The presentation of the location of the tranSNPs in the target mRNAs from polysome data should be presented in a schematic in Fig.1. It should be emphasized; what fold change was considered relevant to select mRNA targets. Do SNPs overlap other regulatory element in the 3' UTRs of the mRNA targets?
      2. Fig.2: If mRNA steady-state levels and protein levels are not affected by the SNP, what mechanism can be assumed for translation? Can you perform luciferase reporter mRNA experiments with the different SNPS under ER/thapsigargin stress conditions? Can you isolate the region that has the SNP and show that the effect on translation is local?
      3. Fig.3: Given the subtle differences in polysome association of mRNA distributions in the mutants, the polysomes need quantifications of the area under the curve in 3 categories: sub-polysomal, light and heavy polysomes. The overall decreased translation of all 3 mRNAs in tg-stress cells of the AA SNPs needs to be explained. This effect is not specific to DDIT4.
      4. Fig.4: The cherry-picking based on CLIP data of RBMX needs to be addressed more. A pulldown of all 3 identified RBPs needs to be done to determine if RBMX is the strongest regulator of DDIT4 via the 3' UTR. The EMSA in (A) needs to be quantified to determine the Kd. In (C) the RBMX is mainly nuclear which does not align with the translation effect on DDIT4 mRNA. Please explain. The effect on localization upon RBMX on DDIT4 protein seems subtle. Are there more dominant mechanisms at play for translation regulation other than via RBMX?
      5. Fig.5: How do you interpret the TT-specific effect on mTOR activity? Is there a link between RBMX binding, DDIT4 protein levels/activity and mTOR? The stats in (F) are missing.
      6. Fig.6: The rationale for these sets of experiments is not clear. Is it expected that the DDIT4 protein alone and its regulation through the AA phenotype is affecting global translation? Thapsigargin is a global ER stress but the expectation is not that DDIT4 itself is such a strong global regulator. This figure can move to the supplement.
      7. Fig.7: The data in (A) is very clear, can you expand a bit on that how translation regulation of the genotypes in co-culture can have such a strong effect? The data in (C) needs to be reevaluated with stats as there does not seem to be a strong difference.
      8. Fig.8: How much is the AA-induced tumor growth in zebrafish comparable to a co-culture tumour model? Again, how are the DDIT4 proteins levels derived from AA related and responsible for this?

      Minor comment:

      1. The manuscript is littered with non-intuitive abbreviations that make the figures less accessible without reading all main text. Please simplify and reduce abbreviations.

      Significance

      The manuscript needs major revision due to additional data interpretation, lack of statistical analysis, and lack of mechanistic and causal insights. The paper is overall correlative and descriptive and has not enough data to claim a translation regulation aspect of DDIT4 and the protein product to cause the observed genotypic differences stemming from a SNP in the 3' UTR. The paper reads as a collection of individual findings that do not seem to be very cohesive and ranges from polysome-seq, RBP binding, ER stress, mTOR activity, cellular co-culture tumor models and zebrafish tumor models. I wish the authors would have focused on one aspect and described one finding well. Without addressing these fundamental concerns, the study's core claims regarding p53-dependent responses in cancer remain unsubstantiated. Overall, this reviewer supports the publication in a Review Commons journal dependent on that the points of criticism are adequately addressed in the course of a major revision.

    3. Review Commons

      Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons

      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      In this manuscript, Hamadou et al. describe the functional characterization of a 3'UTR SNP (rs1053639) in the DDIT4 gene that influences mRNA localization and translation. The authors use polysome profiling, isogenic HCT116 clones, and molecular assays to link the SNP to allele-specific protein expression, proposing a mechanistic role for RBMX and potentially m6A. The manuscript is clearly written and presents compelling evidence to support the authors conclusion.

      Major Comments:

      1. The comparison between TT and AA clones relies on a very limited number of HCT116-derived edited lines. The possibility that the observed differences in DDIT4 translation are due to clonal artifacts cannot be excluded. The authors could partially address this by transfecting the luciferase reporters carrying the A or T allele into both AA and TT clones to assess whether genotype-specific effects persist independently of clone background.
      2. All functional assays are restricted to HCT116 cells. It is essential that key findings, such as especially allele-specific effects on protein levels and mRNA localization, are validated in at least one additional cell line to generalize the findings.
      3. While TT and AA clones show differences in DDIT4 protein levels, the downstream biological effects (e.g., in co-culture or zebrafish xenografts) are modest and not clearly attributable to DDIT4 expression. The authors should strengthen this connection by manipulating DDIT4 expression (e.g., knockdown or overexpression) in both genotypic backgrounds to determine whether the observed growth or localization phenotypes are DDIT4-dependent.

      Minor Comments:

      1. Fig4B: IgG controls for the RIP-qPCR are missing.
      2. Figure 7C is not properly aligned and the total proportion of cells is not 100%.
      3. The discussion section, while informative, is overly long and could be more concise and focused to improve readability and impact.

      Significance

      The authors present a novel and sound pipeline to identify SNPs that regulate mRNA translation using allelic differences in polysome association. Using this approach, they focus on rs1053639 in the 3'UTR of DDIT4 and provide convincing evidence of its impact on mRNA localization and protein expression in HCT116 cells. While the molecular findings are robust, the biological consequences appear relatively modest, and the proposed clinical relevance remains speculative at this stage.

      Overall, the study will be of primary interest to a specialized audience of researchers in the fields of post-transcriptional regulation, RNA biology, and functional genomics. The proof-of-concept framework may also attract broader interest for its potential applications in understanding non-coding genetic variation in cancer biology.

      Reviewer expertise: p53 biology, molecular cancer biology

    4. Review Commons

      Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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      Referee #1

      Evidence, reproducibility and clarity

      This study investigates the role of a 3'UTR SNP variant in DDIT4 mRNA on allele specific expression at post transcriptional level. The authors have previously developed an experimental approach to identify differences in allele specific transcript distribution in polysomes vs. This was done using polysome profiling combined with RNA-seq analysis of polysome associated and total RNA fractions. This systematic approach identified 40 candidate transcripts exhibiting differential polysome association between reference and variant alleles, indicating post transcriptional effects. Focusing on DDIT4, the study demonstrated that the SNP variant alters subcellular mRNA localization patterns between cytoplasm and nucleus through an impaired interaction with a specific RNA binding protein. Since DDIT4 functions as a negative regulator of mTORC1 signalling, the study examined the mTOR pathway status in homozygous reference and variant genotypes. Using genome-edited cell lines revealed enhanced proliferative capacity of the homozygous AA variant in both co-culture assays and zebrafish xenograft models. I agree with the authors that we don't know much about allele specific effects on mRNA translation mechanisms. However this study doesn't provide much evidence for translational effects either because the differences appear to be mostly due to the impaired export of the variant RNA from the nucleus. Irrespective, the findings are very important as they show how genetic variants in non-coding regions can result in changes of expression at posttranscriptional level.
      A comprehensive suite of experimental approaches was utilized to systematically assess both the SNP's impact on mRNA translation and the gene specific functional consequences for DDIT4. The manuscript is well written and presents the work with great clarity.

      Major comments

      "HCT116, about 11% of genes with analyzable heterozygous SNPs show a difference in AF between paired total and polysome-bound mRNAs, suggesting allele-specific post-transcriptional and translational control." For the remaining candidate transcripts that did not undergo targeted experimental validation like DDIT4, it remains possible that the observed allele specific translational effects could be attributed to other SNPs located elsewhere within these transcripts or to combinatorial effects involving multiple variants. Have the authors considered this possibility? The authors employed RNA probes designed to mimic the secondary structures of the T and A alleles of endogenous DDIT4 mRNA. Could you clarify the exact composition of these probes, do they contain a partial DDIT4 3'UTR sequence? Is it possible that the probes lack critical sequences required for complete protein recognition? Figure 3A - the authors suggest that "in the mock condition, AA cells showed a slight reduction in translation efficiency for the DDIT4 mRNA, as revealed by higher relative abundance in lighter polysomes (fraction 9)" I am not convinced that this is the case, first because the number of ribosomes per mRNA doesn't necessarily reflect translation efficiency and also the TT seems to have increased monosome fraction, and overall to me the profile suggests of slightly reduced translation for TT. Was the nucleotide sequence of the binding site of RBMX determined and if so is this sequence present within the DDIT4 3'UTR?

      Minor

      Could the authors maybe define what is meant by "analyzable" SNPs or genes? What was the rationale for the selection of HCT116 cells, from a quick search it appears that DDIT4 effects on mTORC1 inhibition could be cell type specific ("mediates mTORC1 inhibition in fibroblasts and thymocytes, but not in hepatocytes"), have the authors considered other cell types Results section 2: Editing of HCT116 cell... I appreciate the clear methodological explanations provided in this section; however, the manuscript might benefit from more concise organization with substantial portions of this descriptive content relocated to the Methods section. Regarding statistical presentation, I recommend reporting exact significance values rather than using threshold indicators (ns, *, **, etc.). This approach provides more informative and transparent statistical reporting as differences between "non-significant" and "significant" designations can be minimal neighbouring p-values that fall on opposite sides of arbitrary thresholds and may be misleadingly interpreted. For instance in Figure 2D, the comparison between TT and AA genotypes may approach statistical significance, and displaying the actual p-values would allow readers to better assess the strength of evidence. Fig 3 What is the significance of the control mRNAs? According to the plots it seems as if these also have variants TT/AA? Figure 5A why does AA clone 6 look so different on the gel? "rs1053639 genotype, a relatively common SNP" - what is the estimated frequency of the SNP?

      Significance

      It is a substantial study and a very interesting story. The findings will be of interest for a broad audience, because it combines elements of basic research and clinical significance. The work allows for interpretation of an allele specific genomic variant outside of the coding region and it reveals the importance of similar characterisation of other SNPs.

    5. Version published to 10.1101/2025.04.02.646512 on bioRxiv