PREreview of Dual regulation of the unfolded protein response by IGF2BP3 during ER stress

PREreview of “Dual regulation of the unfolded protein response by IGF2BP3 during ER stress”

C. Philippe, M. Lodé of the Proteostasis and Cancer Team, INSERM U1242.

Summary of the article

In this article by Anisimova et al. (https://doi.org/10.1101/2025.03.29.646117), the authors investigate the role of IGF2BP3 in regulating the Unfolded Protein Response (UPR) during endoplasmic reticulum (ER) stress. They demonstrate that IGF2BP3 participates in a dual regulatory mechanism of its bound-mRNAs. During ER stress, it destabilizes many mRNAs targets, including UPR-associated genes, to reduce the protein folding load while simultaneously stabilizing mRNAs encoding transcriptional regulators, creating a feedback loop that finely tune the UPR response genes.

General comments

The article is well-written and concise which makes the research accessible and informative for a broad audience. We appreciate the valuable scientific contributions that advance our understanding of ER stress response. After carefully reading the manuscript and figures, we believe this manuscript could be improved on some key points detailed below.

Figure 1

2A- The authors could present the input fraction for the IP experiment like they did for the data presented in Supplementary figure 1A. Also, they could add the molecular weight for all proteins on all western blot figures throughout the paper.

2H- It would be a good thing to add the binding scores (log2(PAR-CLIP/transcriptome)) for each selected mRNA.

Figure 2

2A- It is mentioned that multiple KO clones have been generated, the authors could clarify which ones have been used for this figure.

 2C,2D- The subsets of genes are different between C and D. What is the intersect between each set of genes of a given category (either IGF2BP3-bound or IGF2BP3-bound UPR targets)?

2G - This panel is referenced in the text but does not exist (line 228).

Figure 3

3A,3C- We would recommend more consistency in the axis of the volcano plots. In panel A, the Y scales are different and the threshold represented as a dashed line on the Y-axis seems different between the two figures. Also, the titles of the Y-axis are inconsistent with panel C (either P.value or P value adj.), could the authors clarify?

Figure 4

4C- How do the authors link the “TC conversion rate” with mRNAs stability? We think more context on this particular point could improve the message and the TC conversion rate calculation should appear in the materials and methods.

 4E- The observed differences between siControl and siIGF2BP3 are on a relative scale and do not seem very strong. Which biological significance does such differences imply? Also, it could be convincing to add a curve for all 24 IGF2BP3-bound UPR targets presented in panel D.

Figure 6

6A- Many interactions are identified, and we can imagine some of them are false positives. We think that an experimental validation of some of them would add great value to this result. In addition, the colors of the dots are not easy to visualize and the color legend is not displayed on the graph.

 6A,6B,6C- As in figure 3, the p.value used is inconsistent between panels.

 6D- We would recommend displaying the significance levels of statistical tests. Additionally, we did not find any information regarding the peptides used for quantification, nor details on the normalization making it hard to understand the results presented here. We think it is necessary to provide more information on how it was performed.

Competing Interests

The authors declare that they have no competing interests.

Competing interests

The authors declare that they have no competing interests.