Multiple myeloma(MM) remains incurable with high relapse and chemoresistance rates. Differentially expressed genes(DEGs) between newly diagnosed myeloma and secondary plasma cell leukemia(sPCL) were subjected to a weighted gene co-expression network analysis(WGCNA). Drug resistant myeloma cell lines were established. Seahorse XF analyzer was applied to detect the metabolism reprogramming associated with the hub gene. The metabolic relevance and the underlying mechanism of the hub gene in myeloma resistance were explored via in vitro experiments. A total of 1310 DEGs were used to construct five co-expression modules. Gene function enrichment analysis demonstrated that candidate hub genes were closely related to oxidative phosphorylation. We performed prognostic analysis and identified PSMA4 as the key hub gene related to the extramedullary invasion of myeloma. The in vitro experiments demonstrated bortezomib resistant myeloma cell lines exhibited high PSMA4 expression, improved oxidative phosphorylation activity with increased ROS level. PSMA4 knockdown re-sensitize resistant myeloma cells via suppressing oxidative phosphorylation activity. Further investigation revealed that PSMA4 induced a hypoxia state which activated the HIF-1α signaling pathway. PSMA4 induces metabolic reprogramming by improving oxidative phosphorylation activity which accounts for the hypoxia state in myeloma cell. The activated HIF-1α signaling pathway causes bortezomib resistance via promoting anti-apoptotic activity in myeloma.

Multiple myeloma (MM) is the second most common hematologic malignancy. There are no standard therapeutic guidelines for extramedullary invasion (EM). We performed a retrospective integrated transcriptomic analysis based on GEO, TCGA, and Oncomine datasets with a total of over 2,500 cases enrolled. GSVA analysis was performed on GSE24080. The external validation cohorts include GSE9782, GSE2658, MMRF-COMPASS, and Oncomine. The data of MGUS to relapsed MM were acquired from GSE6477, GSE5900, and Oncomine. The data of EM were acquired from GSE39683 and GSE66291. Single-cell level transcriptome data of MM and EM were acquired from GSE106218. GSVA analysis revealed that 559 cases could be divided into 2 groups based on the expression of oncogenic pathways with prognostic significances. Group 1 with a specific phenotype of YAP1-MYC+ exhibited an unpromising prognosis. The univariate analysis revealed YAP1 as a tumor suppressor in MM. The activity of DNA repair, glycolysis, and oxidative phosphorylation was significantly higher in YAP1-MYC+ MM, which is in concordance with EM myeloma cells based on single-cell analysis. Furthermore, we discovered that YAP1-MYC+ MM patients exhibited an improved response for IMiD treatment. Collectively, YAP1-MYC+MM patients might suffer a worse prognosis and stronger propensity for EM progression.

Dickkopf-1 (DKK1), broadly expressed by tumor cells from human multiple myeloma (MM) and other cancers but absent from most normal tissues, may be an ideal target for immunotherapy. Our previous studies have shown that DKK1 (peptide)-specific cytotoxic T lymphocytes can effectively lyse primary MM cells in vitro. To develop DKK1-based vaccines that can be easily and inexpensively made and used by all patients, we identified a DKK1 long peptide (LP), DKK13-76-LP, that contains 74 amino acids and epitopes that can potentially bind to all major MHC class I and II molecules. Using HLA-A*0201- and HLA-DR*4-transgenic mouse models, we found that DKK1-specific CD4+ and CD8+ T cell responses, detected by DKK1 short peptide (P20 and P66v)-HLA-A*0201 tetramer staining and cytotoxic assay for CD8+ T cells or by CSFE dilution and IFN-a; secretion for CD4+ T cells respectively, can be induced in vivo by immunizing mice with the DKK13-76-LP. In addition, DKK13-76-LP also induced anti-DKK1 humoral immunity in the transgenic mice and the DKK1 antibodies were functional. Finally, DKK13-76-LP stimulated human blood T cells ex vivo to generate DKK1-specific CD4+ and CD8+ T cell responses from eight out of ten MM patients with different MHC backgrounds. The generated DKK1-specific CD8+ cells efficiently lysed autologous MM cells from these patients. Thus, these results confirm the immunogenicity of the DKK13-76-LP in eliciting DKK1-specific CD4+ and CD8+ T cell responses in vitro and in vivo, and suggest that the DKK13-76-LP can be used for immunotherapy of MM and other cancers.

Background: Multiple myeloma (MM) is the second most common hematological malignancy, and the treatments markedly elevate the survival rate of the patients in recent years. However, the prevalence of cardiovascular adverse events (CVAEs) in MM had been increasing recently. CVAEs in MM patients are an important problem that we should focus on. Clinical tools for prognostication and risk-stratification are needed.Patients and methods: This is a retrospective study that included patients who were newly diagnosed with multiple myeloma (NDMM) in Shanghai Changzheng Hospital and Affiliated Jinhua Hospital, Zhejiang University School of Medicine from June 2018 to July 2020. A total of 253 patients from two medical centers were divided into training cohort and validation cohort randomly. Univariable analysis of the baseline factors was performed using CVAEs endpoints. Multivariable analysis identified three factors for a prognostic model that was validated in internal validation cohorts.Results: Factors independently associated with CVAEs in NDMM were as follows: age>61 years old, high level of baseline office blood pressure, and left ventricular hypertrophy (LVH). Age contributed 2 points, and the other two factors contributed 1 point to a prognostic model. The model distinguished the patients into three groups: 3–4 points, high risk; 2 points, intermediate risk; 0–1 point, low risk. These groups had significant difference in CVAEs during follow-up days in both training cohort (p<0.0001) and validation cohort (p=0.0018). In addition, the model had good calibration. The C-indexes for the prediction of overall survival of CVAEs in the training and validation cohorts were 0.73 (95% CI, 0.67–0.79) and 0.66 (95% CI, 0.51–0.81), respectively. The areas under the receiver operating characteristic curve (AUROCs) of the 1-year CVAEs probability in the training and validation cohorts were 0.738 and 0.673, respectively. The AUROCs of the 2-year CVAE probability in the training and validation cohorts were 0.722 and 0.742, respectively. The decision-curve analysis indicated that the prediction model provided greater net benefit than the default strategies of providing assessment or not providing assessment for all patients.Conclusion: A prognostic risk prediction model for predicting CVAEs risk of NDMM patients was developed and internally validated. Patients at increased risk of CVAEs can be identified at treatment initiation and be more focused on cardiovascular protection in the treatment plan.

Background: Patients with diffuse large B cell lymphoma (DLBCL) may experience depression. Growing evidence shows that depression interacts with immunity. However, the relationship between depression and immunity among DLBCL patients has not been investigated, despite reports indicating that patients with DLBCL often suffer from depression. Methods: To accurately investigate the relationship between depression and immunity, 82 primarily diagnosed middle-aged patients with DLBCL who received standard chemotherapy were enrolled. The patients were divided into depressed and nondepressed groups according to Zung Self-rating Depression Scale (SDS) scores. Prozac was used to treat patients with depression until their symptoms were alleviated. The concentration of immunosuppressive acidic protein (IAP); percentages of cluster of differentiation (CD)3+, CD4+, and CD8+ T lymphocytes and CD56+ natural killer (NK) cells; absolute lymphocyte count (ALC); and neutrophil-–lymphocyte ratio (NLR) were calculated at enrollment and after treatment. Results: A higher score on the depression test was positively associated with serum IAP levels and NLR, and negatively associated with ALC. The levels of NLR and serum IAP in the depressed patients were significantly higher compared to those in the nondepressed patients. Conclusions: Our results suggest for the first time that IAP and the NLR are closely correlated with depression and may be parameters for predicting depression.