Background: Proteasome inhibitors (PIs) are one of the most important classes of drugs for the treatment of multiple myeloma (MM). However, almost all patients with MM develop PI resistance, resulting in therapeutic failure. Therefore, the mechanisms underlying PI resistance in MM require further investigation. Methods: We used several MM cell lines to establish PI-resistant MM cell lines. We performed RNA microarray and EccDNA-seq in MM cell lines and collected human primary MM samples to explore gene profiles. We evaluated the effect of MUC20 on cuproptosis of PI-resistant MM cells using Co-immunoprecipitation (Co-IP), Seahorse bioenergetic profiling and in vivo assay. Results: This study revealed that the downregulation of Mucin 20 (MUC20) could predict PI sensitivity and outcomes in MM patients. Besides, MUC20 attenuated PI resistance in MM cells by inducing cuproptosis via the inhibition of cyclin-dependent kinase inhibitor 2 A expression (CDKN2A), which was achieved by hindering MET proto-oncogene, receptor tyrosine kinase (MET) activation. Moreover, MUC20 suppressed MET activation by repressing insulin-like growth factor receptor-1 (IGF-1R) lactylation in PI-resistant MM cells. This study is the first to perform extrachromosomal circular DNA (eccDNA) sequencing for MM, and it revealed that eccDNA induced PI resistance by amplifying kinesin family member 3 C (KIF3C) to reduce MUC20 expression in MM. Conclusion: Our findings indicated that MUC20 regulated by eccDNA alleviates PI resistance of MM by modulating cuproptosis, which would provide novel strategies for the treatment of PI-resistant MM.

Objective: In order to enhance the detection rate of multiple myeloma and execute an early and more precise disease management, an artificial intelligence assistant diagnosis system is developed. Methods: 4,187 routine blood and biochemical examination records were collected from Shengjing Hospital affiliated to China Medical University from January 2010 to January 2020, which include 1,741 records of multiple myeloma (MM) and 2,446 records of non-myeloma (infectious diseases, rheumatic immune system diseases, hepatic diseases and renal diseases). The data set was split into training and test subsets with the ratio of 4:1 while connecting hemoglobin, serum creatinine, serum calcium, immunoglobulin (A, G and M), albumin, total protein, and the ratio of albumin to globulin data. An early assistant diagnostic model of MM was established by Gradient Boosting Decision Tree (GBDT), Support Vector Machine (SVM), Deep Neural Networks (DNN), and Random Forest (RF). Out team calculated the precision and recall of the system. The performance of the diagnostic model was evaluated by using the receiver operating characteristic (ROC) curve. Results: By designing the features properly, the typical machine learning algorithms SVM, DNN, RF and GBDT all performed well. GBDT had the highest precision (92.9%), recall (90.0%) and F1 score (0.915) for the myeloma group. The maximized area under the ROC (AUROC) was calculated, and the results of GBDT (AUC: 0.975; 95% confidence interval (CI): 0.963–0.986) outperformed that of SVM, DNN and RF. Conclusion: The model established by artificial intelligence derived from routine laboratory results can accurately diagnose MM, which can boost the rate of early diagnosis.

Diffuse large B cell lymphoma (DLBCL) is a common hematologic malignancy. NFS1 cysteine desulfurase, as a rate-limiting enzyme in the iron-sulfur cluster (ISC) biogenesis, has been reported to be associated with tumor progression. However, the role of NFS1 in DLBCL remains elusive. Here, we showed an upregulation of NFS1 in DLBCL tumor tissues. Knockdown of NFS1 decreased the cell viability and enhanced LDH levels in DLBCL cells. Animal experiments further indicated that downregulation of NFS1 suppresses tumor growth in vivo. NFS1 knockdown increased the lipid reactive oxygen species (ROS) level in cells, and this promotional effect was reversed by ferroptosis inhibitors, but not influenced by other types of cell death inhibitors. This result suggested that NFS1 depletion-impaired cell viability is associated with ferroptosis. Silenced NFS1 aggravated ferroptosis inducers caused cell viability inhibition, lactate dehydrogenase (LDH), and lipid ROS levels enhancement, while the addition of ferroptosis inhibitors abated these trends. Moreover, catalytic residue mutation of NFS1 did not affect its protein expression but decreased the cell viability, which was promoted by NFS1 upregulation, indicating that the protective effect of NFS1 in DLBCL cells was related to its catalytic activity. Further results showed that frataxin (FXN), the upstream activator of NFS1, reduced the cell viability in NFS1 upregulated cells. Consistent with NFS1, FXN silencing aggravated erastin-induced cell viability inhibition and LDH level enhancement. Silencing NFS1 or FXN inhibited the level of iron ions storage-related proteins but promoted the level of transport-related proteins. In addition, silenced NFS1 or FXN displayed an inhibition effect on protein expression of DNA polymerases, but a promotion trend in the phosphorylation of DNA damage markers. In conclusion, we demonstrated that ISC-related proteins NFS1 and FXN protect DLBCL cells from ferroptosis and DNA damage, thus exhibiting an essential role in DLBCL progression.

Leukemia ranks as the one of most common causes of death from tumor. 51.4% of patients with leukemia are over 65 years old. However, the median overall survival (OS) of elderly leukemia patients is less than one year. It is urgent to explore more effective treatments for elderly patients with leukemia. Our recent prospective phase II single-arm study has revealed that combination regimen of granulocyte colony-stimulating factor (G-CSF) and recombinant human thrombopoietin (rhTPO) could improve the curative effect on elderly patients with leukemia, yet the precise mechanism remains unknown. This study demonstrated that combination of G-CSF and rhTPO showed greater effect on suppressing leukemia growth than G-CSF or rhTPO alone in vitro and in vivo. Mechanistically, G-CSF induced pyroptosis through ELANE in leukemia cells. Besides, rhTPO triggered ferroptosis by EP300 in leukemia cells. Moreover, rhTPO suppressed glutathione peroxidase 4 (GPX4) expression to induce ferroptosis through blocking the interaction between EP300 and GPX4 gene promoter via associating with EP300. In summary, this study illuminated that combination regimen of G-CSF and rhTPO improved the curative effect on elderly patients with leukemia through inducing pyroptosis and ferroptosis of leukemia cells. Therefore, our results provided a theoretical basis for combination regimen of G-CSF and rhTPO treating leukemia and potential therapeutic targets for leukemia.