Integrating plasma proteomes with genome-wide association data for causal protein identification in multiple myeloma.

BACKGROUND: Multiple myeloma (MM) is a severely debilitating and fatal B-cell neoplastic disease. The discovery of disease-associated proteins with causal genetic evidence offers a chance to uncover novel therapeutic targets. METHODS: First, we comprehensively investigated the causal association between 2994 proteins and MM through two-sample mendelian randomization (MR) analysis using summary-level data from public genome-wide association studies of plasma proteome (N = 3301 healthy individuals) and MM (598 cases and 180,756 controls). Sensitivity analyses were performed for these identified causal proteins. Furthermore, we pursued the exploration of enriched biological pathways, prioritized the therapeutic proteins, and evaluated their druggability using the KEGG pathway analysis, MR-Bayesian model averaging analysis, and cross-reference with current databases, respectively. RESULTS: We identified 13 proteins causally associated with MM risk (false discovery rate corrected P < 0.05). Six proteins were positively associated with the risk of MM, including nicotinamide phosphoribosyl transferase (NAMPT; OR [95% CI]: 1.35 [1.18, 1.55]), tyrosine kinase with immunoglobulin-like and EGF-like domains 1 (TIE1; 1.14 [1.06, 1.22]), neutrophil cytosol factor 2 (NCF2; 1.27 [1.12, 1.44]), carbonyl reductase 1, cAMP-specific 3',5'-cyclic phosphodiesterase 4D (PDE4D), platelet-activating factor acetylhydrolase IB subunit beta (PAFAH1B2). Seven proteins were inversely associated with MM, which referred to suppressor of cytokine signaling 3 (SOCS3; 0.90 [0.86, 0.94]), Fc-gamma receptor III-B (FCGR3B; 0.75 [0.65,0.86]), glypican-1 (GPC1; 0.69 [0.58,0.83]), follistatin-related protein 1, protein tyrosine phosphatase non-receptor type 4 (PTPN4), granzyme B, complement C1q subcomponent subunit C (C1QC). Three of the causal proteins, SOCS3, FCGR3B, and NCF2, were enriched in the osteoclast differentiation pathway in KEGG enrichment analyses while GPC1 (marginal inclusion probability (MIP):0.993; model averaged causal effects (MACE): - 0.349), NAMPT (MIP:0.433; MACE: - 0.113), and NCF2 (MIP:0.324; MACE:0.066) ranked among the top three MM-associated proteins according to MR-BMA analyses. Furthermore, therapeutics targeting four proteins are currently under evaluation, five are druggable and four are future breakthrough points. CONCLUSIONS: Our analysis revealed a set of 13 novel proteins, including six risk and seven protective proteins, causally linked to MM risk. The discovery of these MM-associated proteins opens up the possibility for identifying novel therapeutic targets, further advancing the integration of genome and proteome data for drug development.

Causal relationships between inflammatory factors and multiple myeloma: A bidirectional Mendelian randomization study.

Changes in serum inflammatory factors occur throughout the onset and multiple myeloma (MM) progression, the feedback loops make it harder to distinguish between causes and effects. In the present study, we performed a bidirectional summary-level Mendelian randomization (MR) analysis to elucidate the causal relationships of C-reactive protein (CRP) and inflammatory regulators with MM. Summary-level data of genetic variants associated with inflammation were extracted from two genome-wide association studies (GWASs) on CRP and human cytokines, while data on MM was from large meta-analyses of GWASs among 372 617 UK Biobank participants. The inverse-variance weighted (IVW) method was used as the primary MR analysis and MR-Egger, weighted median, and MR-pleiotropy residual sum and outlier (MR-PRESSO) were used as the sensitivity analyses. Our results suggested that higher levels of monocyte-specific chemokine-3 (IVW estimate odds ratio [ORIVW ] per SD genetic cytokines change: 1.24; 95% confidence interval [CI]: 1.03-1.49; P = .02), vascular endothelial growth factor (1.14, 1.03-1.27; P = .02), interleukin-10 (1.33, 1.01-1.75; P = .04) and interleukin-7 (1.24, 1.03-1.48; P = .02) were associated with increased risk of MM, while lower levels of tumor necrosis factor-ß (0.84, 0.74-0.92; P < .001) was strongly associated with an increased risk of MM. And conversely, genetically predicted MM was related to increased levels of interleukin-17 (IVW estimate ß: 0.051, 95% CI: 0.018-0.085; P = 2.7 × 10-3 ). Besides, we observed no such significant associations for other inflammatory factors in our study. Overall, our study provides genetic evidence on the relationships of CRP and systemic inflammatory regulators with MM. Targeted interventions of specific inflammatory factors may have implications to alleviate MM cancer risk.

MicroRNA-2861 regulates the proliferation and apoptosis of human retinal vascular endothelial cells treated with high glucose by targeting NDUFB7.

Objectives: Although anti-VEGF and retinal laser photocoagulation are two therapeutic modalities that have been used in the clinical treatment of diabetic retinopathy (DR), it is unknown how these modalities target vascular endothelial function in DR. Methods: We first downloaded and analyzed the differential genes in two DR-related datasets, GSE60436 and GSE53257. The differential gene expression was then verified using RT-qPCR, and the most upregulated gene, NDUFB7, was selected for subsequent experiments. Subsequently, the role of NDUFB7 silencing and enforced expression on the proliferation and apoptosis of HRVECs was explored using CCK-8 assay, EDU proliferation assay and apoptotic TUNEL staining. In addition, the upstream potential miRNAs of NDUFB7 were predicted online using the Targetscan website. RT-qPCR, Western blotting (WB), and dual luciferase gene reporter assay were used to confirm the targeting connection between miR-2861 and NDUFB7. Finally, miR-2861 expression after high glucose (HG) treatment and its effect on proliferation and apoptosis of HRVECs under HG were investigated. Results: In this study, we first downloaded and analyzed the differential genes in two DR-related datasets, GSE60436 and GSE53257. We found that TUFM, PRELID1, MRPL32, NDUFB7, MRPL4, MRPL40, HSD17B10 and SLC25A13 were upregulated in DR, and RT-qPCR showed that NDUFB7 was most upregulated. Subsequent CCK-8 assay, EDU proliferation assay and TUNEL staining showed that up-picked NDUFB7 promotes proliferation and inhibits apoptosis of HRVECs. In addition, the upstream potential miRNAs of NDUFB7 were predicted online using the Targetscan website. RT-qPCR, Western blotting (WB), and dual luciferase gene reporter assay confirmed the targeting connection between miR-2861 and NDUFB7. Finally, it was observed that miR-2861 can inhibit the proliferation and promote the apoptosis of HRVECs by targeting NDUFB7. Conclusions: Our findings showed that upregulated NDUFB7 in DR promotes proliferation and inhibits apoptosis of HRVECs, and miR-2861 can rescue the pathogenic effect of NDUFB7 upregulation by targeting NDUFB7.

Systemic inflammatory regulators and proliferative diabetic retinopathy: A bidirectional Mendelian randomization study.

Background: Increasing evidence shows that systemic inflammation is an embedded mechanism of proliferative diabetic retinopathy (PDR). However, the specific systemic inflammatory factors involved in this process remained obscure. The study aimed to identify the upstream and downstream systemic regulators of PDR by using Mendelian randomization (MR) analyses. Methods: We performed a bidirectional two-sample MR analysis implementing the results from genome-wide association studies for 41 serum cytokines from 8,293 Finnish individuals, and PDR from FinnGen consortium (2,025 cases vs. 284,826 controls) and eight cohorts of European ancestry (398 cases vs. 2,848 controls), respectively. The inverse-variance-weighted method was adopted as the main MR method, and four additional MR methods (MR-Egger, weighted-median, MR-pleiotropy residual sum and outlier (MR-PRESSO), and MR-Steiger filtering methods) were used for the sensitivity analyses. Results from FinnGen and eight cohorts were pooled into a meta-analysis. Results: Our results showed that genetically predicted higher stem cell growth factor-ß (SCGFb) and interleukin-8 were positively associated with an elevated risk of PDR, with a combined effect of one standard deviation (SD) increase in SCGFb and interleukin-8 causing 11.8% [95% confidence interval (CI): 0.6%, 24.2%]) and 21.4% [95% CI: 3.8%, 41.9%]) higher risk of PDR, respectively. In contrast, genetically predisposition to PDR showed a positive association with the increased levels of growth-regulated oncogene-α (GROa), stromal cell-derived factor-1 alpha (SDF1a), monocyte chemotactic protein-3 (MCP3), granulocyte colony-stimulating factor (GCSF), interleukin-12p70, and interleukin-2 receptor subunit alpha (IL-2ra). Conclusions: Our MR study identified two upstream regulators and six downstream effectors of PDR, providing opportunities for new therapeutic exploitation of PDR onset. Nonetheless, these nominal associations of systemic inflammatory regulators and PDR require validation in larger cohorts.

Recombinant human p53 adenovirus injection combined with Bortezomib inhibits proliferation and promotes apoptosis in multiple myeloma.

BACKGROUND: Multiple myeloma (MM) is a B-cell malignancy characterized by abnormal proliferation of clonal plasma cells in the bone marrow, the incidence of which has further increased in recent years. In multiple myeloma, wild-type functional p53 is often inactivated or dysregulated. Therefore, this study aimed to investigate the role of p53 knockdown or overexpression in multiple myeloma and the therapeutic effect of recombinant adenovirus-p53 (rAd-p53) in combination with Bortezomib. METHODS: SiRNA p53 and rAd-p53 were used to knock down and overexpress p53. RT-qPCR was used to detect gene expression, and western blotting (WB) was used to detect protein expression levels. We also constructed wild-type multiple myeloma cell line-MM1S cell xenograft tumor models and explored the effects of siRNA-p53, rAd-p53, and Bortezomib on multiple myeloma in vivo and in vitro. H&E staining and KI67 immunohistochemical staining were used to assess the anti-myeloma effects of recombinant adenovirus and Bortezomib in vivo. RESULTS: The designed siRNA p53 effectively led to the knockdown of the p53 gene, while rAd-p53 could significantly achieve p53 overexpression. p53 gene inhibited MM1S cell proliferation and promoted apoptosis of wild-type multiple myeloma cell line MM1S. P53 gene inhibited tumor proliferation in vitro by promoting p21 expression and reducing cell cycle protein B1 expression of MM1S. P53 gene overexpression could inhibit tumor growth in vivo. Injection of rAd-p53 in tumor models inhibited tumor development through p21- and cyclin B1-mediated cell proliferation and apoptosis regulation. CONCLUSIONS: We found that overexpression of p53 inhibits MM tumor cell survival and proliferation in vivo and in vitro. Furthermore, the combination of rAd-p53 and Bortezomib significantly improved the efficacy, which provides a new possibility for more effective treatment of MM.

Identification of Immune-Related Genes for Risk Stratification in Multiple Myeloma Based on Whole Bone Marrow Gene Expression Profiling.

Background: Multiple myeloma (MM) is characterized by abnormal proliferation of bone marrow clonal plasma cells. Tumor immunotherapy, a new therapy that has emerged in recent years, offers hope to patients, and studying the expression characteristics of immune-related genes (IRGs) based on whole bone marrow gene expression profiling (GEP) in MM patients can help guide personalized immunotherapy. Methods: In this study, we explored the potential prognostic value of IRGs in MM by combining GEP and clinical data from the GEO database. We identified hub IRGs and transcription factors (TFs) associated with disease progression by Weighted Gene Co-expression Network Analysis (WGCNA), and modeled immune-related prognostic signature by univariate and multivariate Cox and least absolute shrinkage and selection operator (LASSO) regression analysis. Subsequently, the prognostic ability of signature was verified by multiple statistical methods. Moreover, ssGSEA and GSEA algorithm reveled different immunological characteristics and biological function variation in different risk groups. We mapped the hub IRGs by protein-protein interaction network (PPI) and extracted the top 10 ranked genes. Finally, we conducted vitro assays on two alternative IRGs. Results: Our study identified a total of 14 TFs and 88 IRGs associated with International Staging System (ISS). Ten IRGs were identified by Cox -LASSO regression analysis, and used to develop optimal prognostic signature for overall survival (OS) in MM patients. The 10-IRGs were BDNF, CETP, CD70, LMBR, LTBP1, NENF, NR1D1, NR1H2, PTK2B and SEMA4. In different groups, risk signatures showed excellent survival prediction ability, and MM patients also could be stratified at survival risk. In addition, IRF7 and SHC1 were hub IRGs in PPI network, and the vitro assays proved that they could promote tumor progression. Notably, ssGSEA and GSEA results confirmed that different risk groups could accurately indicate the status of tumor microenvironment (TME) and activation of biological pathways. Conclusion: Our study suggested that immune-related signature could be used as prognostic markers in MM patients.