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eIF2α phosphorylation is pathognomonic for immunogenic cell death

Abstract

The phosphorylation of eIF2α is essential for the endoplasmic reticulum (ER) stress response, the formation of stress granules, as well as macroautophagy. Several successful anticancer chemotherapeutics have the property to induce immunogenic cell death (ICD), thereby causing anticancer immune responses. ICD is accompanied by the translocation of calreticulin (CALR) from the ER lumen to the plasma membrane, which facilitates the transfer of tumor-associated antigens to dendritic cells. Here we systematically investigated the capacity of anticancer chemotherapeutics to induce signs of ER stress. ICD inducers including anthracyclines and agents that provoke tetraploidization were highly efficient in enhancing the phosphorylation of eIF2α, yet failed to stimulate other signs of ER stress including the transcriptional activation of activating transcription factor 4 (ATF4), the alternative splicing of X-box binding protein 1 (XBP1s) mRNA and the proteolytic cleavage of activating transcription factor 6 (ATF6) both in vitro and in cancers established in mice. Systematic analyses of clinically used anticancer chemotherapeutics revealed that only eIF2α phosphorylation, but none of the other signs of ER stress, correlated with CALR exposure. eIF2α phosphorylation induced by mitoxantrone, a prototype ICD-inducing anthracyline, was mediated by eIF2α kinase-3 (EIF2AK3). Machine-learning approaches were used to determine the physicochemical properties of drugs that induce ICD, revealing that the sole ER stress response relevant to the algorithm is eIF2α phosphorylation with its downstream consequences CALR exposure, stress granule formation and autophagy induction. Importantly, this approach could reduce the complexity of compound libraries to identify ICD inducers based on their physicochemical and structural characteristics. In summary, it appears that eIF2α phosphorylation constitutes a pathognomonic characteristic of ICD.

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Edited by S. Fulda

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Acknowledgements

We thank David Enot for his help in mathematical modeling and Gautier Stoll for his help in statistical analysis in hyperploid experiments, Prof. Dr. Claudio Hetz for help with the XPB1 reverse transcription PCR, Prof. Dr. John E. Dick for sharing the pSMALB-ATF4.5rep plasmid [52] and Dr. Silke Nock and Prof. Dr. Peter Walter for the U2OS GFP-ATF6 cell line. GK is supported by the Ligue contre le Cancer (équipe labelisée); Agence National de la Recherche (ANR) – Projets blancs; ANR under the frame of E-Rare-2, the ERA-Net for Research on Rare Diseases; Association pour la recherche sur le cancer (ARC); Cancéropôle Ile-de-France; Institut National du Cancer (INCa); Institut Universitaire de France; Fondation pour la Recherche Médicale (FDM20140630126 and FDM 40739); the European Commission (ArtForce); the European Research Council (ERC); the LeDucq Foundation; the LabEx Immuno-Oncology; the RHU Torino Lumière, the SIRIC Stratified Oncology Cell DNA Repair and Tumor Immune Elimination (SOCRATE); the SIRIC Cancer Research and Personalized Medicine (CARPEM); and the Paris Alliance of Cancer Research Institutes (PACRI). PL is supported by the Chinese Scholarship Council and LZ by la Ligue contre le cancer. LS is supported by Fondation ARC projects. JH owns a Fondation Philantropia’s fellowship. LG is supported by Fundação para a Ciência e a Tecnologia (FCT).

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Conflict of interest

The authors declare that they have no conflict of interest.

Correspondence to Oliver Kepp or Guido Kroemer.

Electronic supplementary material

Figure S1. Original matrix of correlation

Figure S2. Protein translation

Figure S3. GRP78 but not both Calreticulin and PDIA3 increases during ER stress

Figure S4. Calreticulin and PDIA3 but not GRP78 translocate to the cell surface

Figure S5. Calreticulin, PDIA3 translocate to the cell surface

Figure S6.EIF2AK3/PERK is essential to eIF2α phosphorylation and calreticulin exposure

Figure S7. No eIF2α phosphorylation affects autophagy induction but not HMGB1 release

Figure S8. Validation of the predicting model

Figure S9. Calculation of a predicted ICD score

Table S1. Raw Data

Table S2. Raw Data

Table S3. Model Matrix Coefficients

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Further reading

Fig. 1: Anthracyclines induce the phosphorylation of eIF2α yet fail to induce other markers of ER stress
Fig. 2: Differential stress patterns evoked by immunogenic cell death-inducing and autophagy-inducing drugs
Fig. 3: Partial split of ER stress responses in vivo induced by ICD drugs
Fig. 4: Correlation of cell stress and cell death parameters
Fig. 5: CALR exposure depends on eIF2α phosphorylation yet is independent of the ER stress
Fig. 6: Mutually exclusive induction of ER stress and calreticulin exposure
Fig. 7: Hyperploidy-associated signs of ER stress
Fig. 8: Chemical descriptors and immunogenic cell death prediction