Elongation factor eEF2 kinase and autophagy jointly promote survival of cancer cells

PPP2CA Inhibition Promotes Ferroptosis Sensitivity Through AMPK/SCD1 Pathway in Colorectal Cancer

PURPOSE

Colorectal cancer (CRC) is a very common malignancy of the digestive system. Despite a variety of treatments including surgery, chemotherapeutic and targeted drugs, the prognosis for patients with CRC is still unsatisfactory and the mortality remains high. Protein phosphorylation plays an essential role in tumorigenesis and progression and is also crucial for protein to act with proper functions. Ferroptosis is found widely involved in various diseases especially tumors as a newly identified programmed cell death.

METHODS

In our study, we aimed at PPP2CA as a prospective target which may play a crucial role in CRC progression. In one hand, knockdown of PPP2CA significantly enhanced the malignant phenotype in HCT116. In the other hand, knockdown of PPP2CA significantly enhanced Erastin-induced ferroptosis as well.

RESULTS

Specifically, knockdown of PPP2CA in HCT116 significantly increased the relative level of malondialdehyde (MDA), reactive oxygen species (ROS) and Fe2+, and decreased GSH/GSSG ratio after the treatment of certain concentration of Erastin. Besides, we found that the inhibition of PPP2CA further led to the suppression of SCD1 expression in CRC cells in a AMPK-dependent way.

CONCLUSION

Ultimately, we conclude that PPP2CA may regulate Erastin-induced ferroptosis through AMPK/SCD1 signaling pathway.

Identification of an Autophagy-Related Signature Based on Whole Bone Marrow Sequencing for the Prognosis and Immune Microenvironment Characterization of Multiple Myeloma

Myeloma (MM) is a malignant plasma cell disorder, which is incurable owing to its drug resistance. Autophagy performs an integral function in homeostasis, survival, and drug resistance in multiple myeloma (MM). Therefore, the purpose of the present research was to identify potential autophagy-related genes (ARGs) in patients with MM. We downloaded the transcriptomic data (GSE136400) of patients with MM, as well as the corresponding clinical data from the Gene Expression Omnibus (GEO); the patients were classified at random into two groups in a ratio of 6: 4, with 212 samples in the training dataset and 142 samples in the test dataset. Both multivariate and univariate Cox regression analyses were performed to identify autophagy-related genes. The univariate Cox regression analysis demonstrated that 26 ARGs had a significant correlation with overall survival (OS). We constructed an autophagy-related risk prognostic model based on six ARGs: EIF2AK2 (ENSG00000055332), KIF5B (ENSG00000170759), MYC (ENSG00000136997), NRG2 (ENSG00000158458), PINK1 (ENSG00000158828), and VEGFA (ENSG00000112715) using LASSO-Cox regression analysis to predict risk outcomes, which revealed substantially shortened OS duration in the high-risk cohort in contrast with that in the low-risk cohort. Therefore, the ARG-based model significantly predicted the MM patients’ prognoses and was verified in an internal test set. Differentially expressed genes were found to be predominantly enriched in pathways associated with inflammation and immune regulation. Immune infiltration of tumor cells resulted in the formation of a strong immunosuppressive microenvironment in high-risk patients. The potential therapeutic targets of ARGs were subsequently analyzed via protein–drug network analysis. Therefore, a prognostic model for MM was established via a comprehensive analysis of ARGs, through using the clinical models; we have further revealed the molecular landscape features of multiple myeloma.