Molecular precision medicine: Multi-omics-based stratification model for acute myeloid leukemia.

Acute myeloid leukemia (AML), as the most common malignancy of the hematopoietic system, poses challenges in treatment efficacy, relapse, and drug resistance. In this study, we have utilized 151 RNA sequencing datasets, 194 DNA methylation datasets, and 200 somatic mutation datasets from the AML cohort in the TCGA database to develop a multi-omics stratification model. This model enables comparison of prognosis, clinical features, gene mutations, immune microenvironment and drug sensitivity across subgroups. External validation datasets have been sourced from the GEO database, which includes 562 mRNA datasets and 136 miRNA datasets from 984 adult AML patients. Through multi-omics-based stratification model, we classified 126 AML patients into 4 clusters (CS). CS4 had the best prognosis, with the youngest age, highest M3 subtype proportion, fewest copy number alterations, and common mutations in WT1, FLT3, and KIT genes. It showed sensitivity to HDAC inhibitors and BCL-2 inhibitors. Both the M3 subtype and CS4 were identified as independent protective factors for survival. Conversely, CS3 had the worst prognosis due to older age, high copy number alterations, and frequent mutations in RUNX1, DNMT3A, and TP53 genes. Additionally, it showed higher proportions of cytotoxic cells and Tregs, suggesting potential sensitivity to mTOR inhibitors. CS1 had a better prognosis than CS2, with more copy number alterations, while CS2 had higher monocyte proportions. CS1 showed good sensitivity to cytarabine, while CS2 was sensitive to RXR agonists. Both CS1 and CS2, which predominantly featured mutations in FLT3, NPM1, and DNMT3A genes, benefited from FLT3 inhibitors. Using the Kappa test, our stratification model underwent robust validation in the miRNA and mRNA external validation datasets. With advancements in sequencing technology and machine learning algorithms, AML is poised to transition towards multi-omics precision medicine in the future. We aspire for our study to offer new perspectives on multi-drug combination clinical trials and multi-targeted precision medicine for AML.

Vitamin D receptor gene polymorphisms and multiple myeloma: a meta-analysis.

Vitamin D acts through the vitamin D receptor (VDR), and vitamin D level decreases in multiple myeloma (MM) patients. Single nucleotide polymorphisms in VDR alter its functions to affect the vitamin D status. This raises the question of whether VDR gene polymorphisms are associated with MM risk, which has been investigated in case‒control studies, but the results have been inconsistent. This meta-analysis aimed to investigate the relationship between VDR gene polymorphisms and MM risk. The PubMed, Web of Science, Medline, Embase, Chinese National Knowledge Infrastructure (CNKI), Chinese Scientific Journal (VIP), Wanfang Databases (WANFANG) were searched from inception to June 1, 2023, without language restriction or publication preference. Pooled odds ratio (OR) and 95% confidence interval (CI) for each variable were calculated. Leave-one-out sensitivity analysis was performed to determine the source of heterogeneity. Publication bias was assessed using Begg' and Egger's tests, and the trim-and-fill method was used to compensate for publication bias. The correlation meta-analysis was conducted using Comprehensive Meta-Analysis 3.0 and STATA 12.0 software. All the included studies were based on Asian populations and involved four VDR gene polymorphisms, TaqI (rs731236), ApaI (rs7975232), BsmI (rs1544410) and FokI (rs2228570). The results showed that TaqI (C vs. T: OR = 1.487, 95% CI 1.052, 2.104, P = 0.025; CC + CT vs. TT: OR = 1.830, 95% CI 1.138, 2.944, P = 0.013), ApaI (T vs. G: OR = 1.292, 95% CI 1.101, 1.517, P = 0.002; TT vs. GG: OR = 1.600, 95% CI 1.106, 2.314, P = 0.013; TG vs. GG: OR 1.305, 95% CI 1.050, 1.622; P = 0.016; TT + TG vs. GG: OR = 1.353, 95% CI 1.103, 1.662, P = 0.004), BsmI (GG vs. AA: OR = 1.918, 95% CI 1.293, 2.844, P = 0.001; GA vs. AA: OR = 1.333, 95% CI 1.058, 1.679, P = 0.015; G vs. A: OR = 1.398, 95% CI 1.180, 1.657, P = 0.000; GG vs. AA + GA: OR = 1.686, 95% CI 1.174, 2.423, P = 0.005), and FokI (T vs. C: OR = 1.687, 95% CI 1.474, 1.931, P = 0.000; TT vs. CC: OR = 2.829, 95% CI 2.066, 3.872, P = 0.000; TC vs. CC: OR = 1.579, 95% CI 1.304, 1.913, P = 0.000, TT + TC vs. CC: OR = 1.771, 95% CI 1.477, 2.125, P = 0.000; TT vs. CC + TC: OR = 2.409, 95% CI 1.814, 3.200, P = 0.000) are associated with MM risk. VDR gene polymorphisms including ApaI, BsmI, TaqI, and FokI are associated with MM risk in Asian populations. Additional studies with large sample sizes and different ethnicities are needed.

Acupuncture in Multiple Myeloma Peripheral Neuropathy: A Systematic Review.

Background: Peripheral neuropathy (PN) is a prevalent complication of multiple myeloma (MM), due to the disease itself or its treatment. Despite extensive research, the optimal treatment for multiple myeloma peripheral neuropathy (MMPN) remains unclear. Clinical practice has shown the potential efficacy of acupuncture in managing MMPN. This study aimed to conduct a comprehensive analysis of the literature to assess the effectiveness and safety of acupuncture as a treatment for MMPN. Methods: The PubMed, Web of Science, MEDLINE, Cochrane Library, and Embase databases were comprehensively searched from inception to November 1, 2023 to identify relevant studies pertaining to the use of acupuncture to treat MMPN. Results: A total of five studies, encompassing 97 patients diagnosed with drug-related PN, were ultimately included in this analysis. The literature lacks any reports pertaining to the utilization of acupuncture for disease-related PN. ST36, LI4, SP6, and EX-LE-10 were found to be the most frequently chosen acupoints. Following acupuncture treatment, there was a consistent reduction in scores on the Visual Analogue Scale (VAS), Neuropathic Pain Scale (NPS), Brief Pain Inventory-Short Form (BPI-SF), and Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity (FACT/GOG-Ntx) among MMPN patients. The results of Nerve Conduction Velocity (NCV) tests yielded conflicting results. No severe adverse effects were reported. Conclusion: The use of acupuncture for disease-related PN has not been studied to date. Acupuncture is safe for drug-related PN and is helpful for relieving pain. But uncertainty exists regarding the efficacy of this approach because there is substantial heterogeneity with respect to acupuncture treatment regimens, and more high-quality studies on this topic are warranted.

Zinc Oxide Nanoparticles Trigger Autophagy in the Human Multiple Myeloma Cell Line RPMI8226: an In Vitro Study.

Multiple myeloma (MM) is a malignant clonal proliferative plasma cell tumor. Zinc oxide nanoparticles (ZnO NPs) are used for antibacterial and antitumor applications in the biomedical field. This study investigated the autophagy-induced effects of ZnO NPs on the MM cell line RPMI8226 and the underlying mechanism. After RPMI8226 cells were exposed to various concentrations of ZnO NPs, the cell survival rate, morphological changes, lactate dehydrogenase (LDH) levels, cell cycle arrest, and autophagic vacuoles were monitored. Moreover, we investigated the expression of Beclin 1 (Becn1), autophagy-related gene 5 (Atg5), and Atg12 at the mRNA and protein levels, as well as the level of light chain 3 (LC3). The results showed that ZnO NPs could effectively inhibit the proliferation and promote the death of RPMI8226 cells in vitro in a dose- and time-dependent manner. ZnO NPs increased LDH levels, enhanced monodansylcadaverine (MDC) fluorescence intensity, and induced cell cycle arrest at the G2/M phases in RPMI8226 cells. Moreover, ZnO NPs significantly increased the expression of Becn1, Atg5, and Atg12 at the mRNA and protein levels and stimulated the production of LC3. We further validated the results using the autophagy inhibitor 3-methyladenine (3­MA). Overall, we observed that ZnO NPs can trigger autophagy signaling in RPMI8226 cells, which may be a potential therapeutic approach for MM.

The Role of Regulatory Cell Death in Vitiligo.

Vitiligo is one of the common chronic autoimmune skin diseases in clinic, which is characterized by localized or generalized depigmentation and seriously affects the physical and mental health of patients. At present, the pathogenesis of vitiligo is not clear; mainly, heredity, autoimmunity, oxidative stress, melanocyte (MC) self-destruction, and the destruction, death, or dysfunction of MCs caused by various reasons are always the core of vitiligo. Regulatory cell death (RCD) is an active and orderly death mode of cells regulated by genes, which widely exists in various life activities, plays a pivotal role in maintaining the homeostasis of the organism, and is closely related to the occurrence and development of many diseases. With the deepening of the research and understanding of RCD, people gradually found that there are many different forms of RCD in the lesions and perilesional skin of vitiligo patients, such as apoptosis, autophagy, pyroptosis, ferroptosis, and so on. Different cell death modes have different mechanisms in vitiligo, and different RCDs can interact and regulate each other. In this article, the mechanism related to RCD in the pathogenesis of vitiligo is reviewed, which provides new ideas for exploring the pathogenesis and targeted treatment of vitiligo.

Exploration of 2D and 3D-QSAR analysis and docking studies for novel dihydropteridone derivatives as promising therapeutic agents targeting glioblastoma.

Background: Dihydropteridone derivatives represent a novel class of PLK1 inhibitors, exhibiting promising anticancer activity and potential as chemotherapeutic drugs for glioblastoma. Objective: The aim of this study is to develop 2D and 3D-QSAR models to validate the anticancer activity of dihydropteridone derivatives and identify optimal structural characteristics for the design of new therapeutic agents. Methods: The Heuristic method (HM) was employed to construct a 2D-linear QSAR model, while the gene expression programming (GEP) algorithm was utilized to develop a 2D-nonlinear QSAR model. Additionally, the CoMSIA approach was introduced to investigate the impact of drug structure on activity. A total of 200 novel anti-glioma dihydropteridone compounds were designed, and their activity levels were predicted using chemical descriptors and molecular field maps. The compounds with the highest activity were subjected to molecular docking to confirm their binding affinity. Results: Within the analytical purview, the coefficient of determination (R2) for the HM linear model is elucidated at 0.6682, accompanied by an R2 cv of 0.5669 and a residual sum of squares (S2) of 0.0199. The GEP nonlinear model delineates coefficients of determination for the training and validation sets at 0.79 and 0.76, respectively. Empirical modeling outcomes underscore the preeminence of the 3D-QSAR model, succeeded by the GEP nonlinear model, whilst the HM linear model manifested suboptimal efficacy. The 3D paradigm evinced an exemplary fit, characterized by formidable Q2 (0.628) and R2 (0.928) values, complemented by an impressive F-value (12.194) and a minimized standard error of estimate (SEE) at 0.160. The most significant molecular descriptor in the 2D model, which included six descriptors, was identified as "Min exchange energy for a C-N bond" (MECN). By combining the MECN descriptor with the hydrophobic field, suggestions for the creation of novel medications were generated. This led to the identification of compound 21E.153, a novel dihydropteridone derivative, which exhibited outstanding antitumor properties and docking capabilities. Conclusion: The development of 2D and 3D-QSAR models, along with the innovative integration of contour maps and molecular descriptors, offer novel concepts and techniques for the design of glioblastoma chemotherapeutic agents.

Zinc oxide nanoparticles induce toxicity in diffuse large B-cell lymphoma cell line U2932 via activating PINK1/Parkin-mediated mitophagy.

Diffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma. Zinc oxide (ZnO) nanoparticles have excellent anti-tumor properties in the biomedical field. The present study aimed to explore the underlying mechanism by which ZnO nanoparticles induce toxicity in DLBCL cells (U2932) via the PINK1/Parkin-mediated mitophagy pathway. After U2932 cells were exposed to various concentrations of ZnO nanoparticles, the cell survival rate, reactive oxygen species (ROS) generation, cell cycle arrest, and changes in the expression of PINK1, Parkin, P62, and LC3 were monitored. Moreover, we investigated monodansylcadaverine (MDC) fluorescence intensity and autophagosome and further validated the results using the autophagy inhibitor 3-methyladenine (3-MA). The results showed that ZnO nanoparticles could effectively inhibit the proliferation of U2932 cells and induce cell cycle arrest at the G0/G1 phases. Moreover, ZnO nanoparticles significantly increased ROS production, MDC fluorescence intensity, autophagosome formation, and the expression of PINK1, Parkin, and LC3, and decreased the expression of P62 in U2932 cells. In contrast, the autophagy level was reduced after the intervention of the 3-MA. Overall, ZnO nanoparticles can trigger PINK1/Parkin-mediated mitophagy signaling in U2932 cells, which may be a potential therapeutic approach for DLBCL.

High Expression of ACOT2 Predicts Worse Overall Survival and Abnormal Lipid Metabolism: A Potential Target for Acute Myeloid Leukemia.

Acyl-CoA thioesterase (ACOT) plays a considerable role in lipid metabolism, which is closely related to the occurrence and development of cancer, nevertheless, its role has not been fully elucidated in acute myeloid leukemia (AML). To explore the role of ACOT2 in AML and to provide a potential therapeutic target for AML, the expression pattern of ACOT was investigated based on the TNMplot, Gene Expression Profiling Interactive Analysis (GEPIA), and Cancer Cell Line Encyclopedia (CCLE) database, and diagnostic value, prognostic value, and clinical phenotype of ACOT were explored based on data from The Cancer Genome Atlas (TCGA). Functional annotation and enrichment analysis of the common targets between ACOT2 coexpressed and AML-related genes were further performed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) analyses. The protein-protein interaction (PPI) network of ACOT2 coexpressed genes and functional ACOT2-related metabolites association network were constructed based on GeneMANIA and Human Metabolome Database. Among ACOTs, ACOT2 was highly expressed in AML compared to normal control subjects according to TNMplot, GEPIA, and CCLE database, which was significantly associated with poor overall survival (OS) in AML (P=0.003). Moreover, ACOT2 exhibited excellent diagnostic efficiency for AML (AUC: 1.000) and related to French-American-British (FAB) classification and cytogenetics. GO, KEGG, and GSEA analyses of 71 common targets between ACOT2 coexpressed and AML-related genes revealed that ACOT2 is closely related to ACOT1, ACOT4, enoyl-acyl carrier protein reductase, mitochondrial (MECR), puromycin-sensitive aminopeptidase (NPEPPS), SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily B member 1 (SMARCB1), and long-chain fatty acid-CoA ligase 1 (ACSL1) in PPI network, and plays a significant role in lipid metabolism, that is, involved in fatty acid elongation and biosynthesis of unsaturated fatty acids. Collectively, the increase of ACOT2 may be an important characteristic of worse OS and abnormal lipid metabolism, suggesting that ACOT2 may become a potential therapeutic target for AML.

Clinical significance and potential mechanism of heat shock factor 1 in acute myeloid leukemia.

BACKGROUND: Heat shock factor 1 (HSF1) is now considered to have the potential to be used as a prognostic biomarker in cancers. However, its clinical significance and potential function in acute myeloid leukemia (AML) remain underexplored. METHODS: In this study, the expression pattern and clinical significance of HSF1 in AML were examined by integrating data from databases including The Cancer Genome Atlas (TCGA), The Genotype-Tissue Expression (GTEx), Vizome, Cancer Cell Line Encyclopedia (CCLE) and Gene Expression Omnibus (GEO). Linkedomics was applied to collect HSF1-related genes in AML. GeneMANIA was applied to outline HSF1-related functional networks. CancerSEA analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA) were performed to mine the potential mechanism of HSF1 in leukemogenesis. Single-sample Gene Set Enrichment Analysis (ssGSEA) was applied to explore the correlation between HSF1 and infiltrating immune cells in AML. RESULTS: HSF1 expression was elevated in AML compared to healthy controls and indicate a poor overall survival. HSF1 expression was significantly correlated with patients age, associated with patient survival in subgroup of bone marrow blasts (%) >20. Functional analyses indicated that HSF1 plays a role in the metastatic status of AML, and is involved in inflammation-related pathways and biological processes. HSF1 expression was significantly correlated with the immune infiltration of nature killer cells and T cell population. CONCLUSION: HSF1 plays a vital role in the molecular network of AML pathogenesis, and has the potential to be a biomarker for prognosis prediction.

Induced effect of zinc oxide nanoparticles on human acute myeloid leukemia cell apoptosis by regulating mitochondrial division.

Zinc oxide nanoparticles (ZnO NPs) have exhibited excellent anti-tumor properties; the present study aimed to elucidate the underlying mechanism of ZnO NPs induced apoptosis in acute myeloid leukemia (AML) cells by regulating mitochondrial division. THP-1 cells, an AML cell line, were first incubated with different concentrations of ZnO NPs for 24 hr. Next, the expression of Drp-1, Bcl-2, Bax mRNA, and protein was detected, and the effects of ZnO NPs on the levels of reactive oxygen species (ROS), mitochondrial membrane potential (Δψm), apoptosis, and ATP generation in THP-1 cells were measured. Moreover, the effect of Drp-1 inhibitor Mdivi-1 and ZnO NPs on THP-1 cells was also detected. The results showed that the THP-1 cells survival rate decreased with the increment of ZnO NPs concentration and incubation time in a dose- and time-dependent manner. ZnO NPs can reduce the cell Δψm and ATP levels, induce ROS production, and increase the levels of mitochondrial division and apoptosis. In contrast, the apoptotic level was significantly reduced after intervention of Drp-1 inhibitor, suggesting that ZnO NPs can induce the apoptosis of THP-1 cells by regulating mitochondrial division. Overall, ZnO NPs may provide a new basis and idea for treating human acute myeloid leukemia in clinical practice.

Integrated analysis on mRNA microarray and microRNA microarray to screen immune-related biomarkers and pathways in myelodysplastic syndrome.

BACKGROUND: Myelodysplastic syndrome (MDS) is a haematopoietic malignancy that is characterized by a heterogeneous clinical course and dysplastic maturation of blood lineages. Immune dysregulation has gained attention as one of the fundamental mechanisms responsible for the development of MDS. This study aimed to screen immune-related biomarkers and pathways in MDS. METHODS: Differentially expressed mRNAs (DE-mRNAs) and differentially expressed microRNAs (DE-miRNAs) in different subtypes of MDS were sourced from the Gene Expression Omnibus (GEO) database. DE-mRNAs were intersected with immune-related gene sets to collect immune-related mRNAs, which were put into the Search Tool for the Retrieval of Interacting Genes (STRING) to construct protein-protein interaction (PPI) networks. Target mRNAs of DE-miRNAs were predicted using the miRDB database and intersected with screened immune-related mRNAs to construct miRNA-mRNA interaction networks. Topological analysis of constructed networks was applied to screen key molecules, which were assessed in independent datasets and previous literature. Enrichment analysis was applied to screen dysregulated pathways in MDS. RESULTS: Screened key mRNAs were mainly from the Toll-like receptor (TLR) family, including TLR2, TLR4, TLR7, and from the chemokine family, including C-X-C motif chemokine ligand 10 (CXCL10) and CC chemokine ligand 4 (CCL4). Cytokine-cytokine receptor interactions were among the major pathways in the enrichment analysis results. Hsa-miR-30b, hsa-miR-30e and hsa-miR-221 were validated as key miRNAs and modulate cytokine-cytokine receptor interactions by targeting immune-related mRNAs. CONCLUSION: Dysregulated cytokines reflect the immunization status in MDS. Immune-related miRNA-mRNA interactions not only provide a perspective to our understanding of immunologic derangement in the pathogenesis of MDS but also provide new therapeutic opportunities.

A drug-biomarker interaction model to predict the key targets of Scutellaria barbata D. Don in adverse-risk acute myeloid leukaemia.

A poor prognosis, relapse and resistance are burning issues during adverse-risk acute myeloid leukaemia (AML) treatment. As a natural medicine, Scutellaria barbata D. Don (SBD) has shown impressive antitumour activity in various cancers. Thus, SBD may become a potential drug in adverse-risk AML treatment. This study aimed to screen the key targets of SBD in adverse-risk AML using the drug-biomarker interaction model through bioinformatics and network pharmacology methods. First, the adverse-risk AML-related critical biomarkers and targets of SBD active ingredient were obtained from The Cancer Genome Atlas database and several pharmacophore matching databases. Next, the protein-protein interaction network was constructed, and topological analysis and pathway enrichment were used to screen key targets and main pathways of intervention of SBD in adverse-risk AML. Finally, molecular docking was implemented for key target verification. The results suggest that luteolin and quercetin are the main active components of SBD against adverse-risk AML, and affected drug resistance, apoptosis, immune regulation and angiogenesis through the core targets AKT1, MAPK1, IL6, EGFR, SRC, VEGFA and TP53. We hope the proposed drug-biomarker interaction model provides an effective strategy for the research and development of antitumour drugs.