Unraveling the Anti-Multiple Myeloma Activity of Alisol B 23-Acetate and Its Impact on the P38MAPK Pathway Through Integrated Analysis

Unraveling the Anti-Multiple Myeloma Activity of Alisol B 23-Acetate and Its Impact on the P38MAPK Pathway Through Integrated Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Unraveling the Anti-Multiple Myeloma Activity of Alisol B 23-Acetate and Its Impact on the P38MAPK Pathway Through Integrated Analysis Hui Zhang, Peng Zhao, Jie Geng, Yuntao Zhu, Xuechun Lu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6923004/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Alisol B 23-acetate is a naturally occurring triterpenoid compound derived from the rhizome of the traditional Chinese medicinal herb Alisma orientale,which possesses a variety of physiological activities, including anti-cancer effects.However, its effects on human multiple myeloma (MM) and the underlying mechanisms remain to be elucidated. In this study, we employed an integrated analysis of mRNA, miRNA, and network pharmacology to investigate the role of Alisol B 23-acetate in MM and subsequently validated our findings with cellular experiments.Our data demonstrate that Alisol B 23-acetate treatment significantly suppresses MM cells via the P38MAPK signaling pathway. Specifically, the CCK-8 assay revealed that Alisol B 23-acetate inhibits the proliferation of MM cells, with an IC50 value of 14.24 µM after a 24-hour treatment. Cell cycle analysis indicated that Alisol B 23-acetate treatment increased the percentage of MM.1S cells in the G0/G1 phase (resting/before DNA synthesis) and decreased the proportion in the S/G2 phase (DNA replication/after DNA synthesis). Apoptosis assays showed that Alisol B 23-acetate significantly enhanced apoptosis in MM.1S cells, with the apoptotic cell population increasing to 57.3%. Quantitative real-time PCR (qRT-PCR) results indicated that Alisol B 23-acetate treatment downregulated the expression of the anti-apoptotic gene Bcl2 and upregulated the expression of the pro-apoptotic gene Bax in MM cells, while the expression of the P38 gene remained largely unchanged. Western blotting analysis further confirmed that Alisol B 23-acetate treatment reduced the expression of the anti-apoptotic protein Bcl2 and increased the expression of the pro-apoptotic protein Bax in MM cells, with a concomitant decrease in P38 protein phosphorylation.These findings suggest that Alisol B 23-acetate induces apoptosis in MM cells by inhibiting the phosphorylation of P38, a key target in the P38MAPK signaling pathway. Biological sciences/Cancer/Haematological cancer/Myeloma Biological sciences/Drug discovery/Biomarkers Multiple Myeloma MAPK P38 Integrated analysis Network pharmacology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Multiple myeloma (MM), a hematological malignancy involving plasma cells, is the second most common hematological neoplasm worldwide, with an increasing incidence rate [ 1 ] . Despite the use of targeted myeloma therapies and immunomodulatory agents, which have improved survival rates among MM patients, the disease remains incurable. The mainstay of first-line treatment includes drugs such as bortezomib (BZT) and lenalidomide (LEN) [ 2 ] . Although various new medications are employed in treatment, leading to disease control and enhanced quality of life for many MM patients, a significant number still progress to relapsed/refractory multiple myeloma (RRMM), which is associated with poor clinical outcomes [ 3 ] . Therefore, the investigation of novel anti-MM therapeutic strategies is of paramount importance.In recent years, there has been a surge of interest in the use of Traditional Chinese Medicine (TCM) for treating a variety of diseases. Bioactive components derived from TCM hold significant potential in the development of anticancer drugs. According to reports, active ingredients derived from TCM are expected to play a role in treating MM. These ingredients may help overcome the issues commonly associated with first-line MM treatment regimens, such as drug resistance, relapse, and significant side effects [ 4 ] . Consequently, the search for new effective components against MM from the bioactive constituents of TCM is of great significance. Alisol B 23-acetate is a naturally occurring triterpenoid compound derived from the rhizome of the traditional Chinese herb Alisma orientale, which has been reported to exhibit potent biological activities, including anti-inflammatory, antibacterial, and anti-proliferative effects [ 5 – 7 ] . Modern pharmacological studies have demonstrated that Alisol B 23-acetate can display significant antitumor properties by influencing the PI3K/Akt/mTOR pathway, reactive oxygen species (ROS) generation, and the MAPK signaling pathway [ 8 – 10 ] . However, the impact of Alisol B 23-acetate on MM and its underlying mechanisms remain to be elucidated. Transcriptomics research offers a rapid method for determining changes in mRNA levels following disease or drug perturbations. By establishing transcriptomic differential expression profiles, we can delineate in detail the gene expression changes in patients in response to diseases and drugs, aiding our understanding of disease and drug mechanisms [ 11 ] . In recent years, miRNA research has made significant progress, and miRNA has gradually become an important tool for studying gene expression regulation, drug mechanism research, and functional analysis [ 12 ] . Network pharmacology is emerging as a common method for predicting potential targets and molecular mechanisms of drugs or compounds in the treatment of diseases [ 13 ] . Additionally, molecular docking can calculate ligand-receptor binding energy to assess the binding capacity and relevance of ligands to receptors [ 14 ] . In our study, we integrated transcriptomics, miRNA analysis, network pharmacology, and molecular docking to identify the central genes, core proteins, key pathways, and regulatory networks through which Alisol B 23-acetate acts on MM cells, revealing the potential molecular mechanisms by which Alisol B 23-acetate participates in the inhibition of MM. Furthermore, we validated these central targets and pathways in vitro experiments. The Mitogen-Activated Protein Kinase (MAPK) signaling pathway is intricately linked to apoptosis, playing a dual role in either promoting or inhibiting cell death, depending on the cell type and stimulatory conditions [ 15 ] . The MAPK pathway is composed of three primary families: Extracellular Signal-Regulated Kinases (ERK), c-Jun N-terminal Kinases (JNK), and P38MAPK [ 16 ] .In the context of cancer cells, inhibitors of the ERK pathway can enhance the pro-apoptotic effects of chemotherapeutic drugs. This is because activated ERK is often associated with cell survival and proliferation, and its inhibition can sensitize cancer cells to apoptosis induced by chemotherapy [ 17 ] . The JNK pathway, when activated, can promote apoptosis through the activation of Caspases, which are central executioners in the apoptotic process [ 18 ] . On the other hand, the inhibition of P38MAPK can regulate the balance of Bcl2 family proteins, activating pro-apoptotic Bax while suppressing the activity of anti-apoptotic Bcl2, leading to cell apoptosis [ 19 ] .Thus, the MAPK signaling pathway, through its various kinase family members, exerts a complex influence on apoptosis, with the specific outcome being contingent upon the cellular context and the nature of the stimuli applied. Materials and methods Main material The multiple myeloma cell line MM.1S was derived from lymphoblasts in the peripheral blood of a 42-year-old female patient with myeloma. MM.1S, human peripheral blood mononuclear cells PBMC and lymphoma cell line DOHH2 were purchased from MeisenCTCC (China), and the cell lines were detected using the Mycoplasma detection kit to confirm that there was no mycoplasma contamination before the next experiment. Alisol B 23-acetate (the purity > 98%)and bortezomib (the purity > 99%) was purchased from MedChemExpress (China).Ethical approval was obtained from the Ethics Committee of Zhejiang Xiaoshan Hospital (Approval No. EC-2024062503). This research was conducted in accordance with the principles of the Declaration of Helsinki. All participants provided informed consent prior to their involvement in the study. mRNA analysis From the Gene Expression Omnibus (GEO) database, we curated the MM dataset GSE16558, utilizing 17 MM plasma cell samples as the experimental group and 5 normal plasma cell samples as the control group. The dataset platform is GPL6244. The acquired data and matrices were read and processed using R software version 4.3.1. Following sample stratification, the limma package version 3.49.4 was employed to screen for differentially expressed genes (DEGs) within the dataset, with a threshold set at P 1. The identified DEGs were visualized using the ggplot2 package. Subsequently, the DEGs were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis using the "clusterProfiler" package in R programming language, with data visualization. The filtering criteria for enrichment analysis was P < 0.05, and the top 10 GO terms were selected, encompassing biological processes (BP), cellular component (CC), and molecular function (MF), as well as the top 20 KEGG pathways. Drug prediction We employed EpiMed, connectivity maps, and the L1000 platform for drug prediction [ 20 ] . EpiMed, an original drug prediction platform developed by our research team based on the principle of correcting aberrant gene expression levels, encompasses cellular expression profile data for small molecule chemical drugs and active components of traditional Chinese medicine [ 20 – 22 ] . By comparing gene expression profiles, it reveals potential associations between drugs, genes, and diseases. Utilizing the gene expression profiles of diseases as input data, and leveraging the drug expression profile data within this platform, in conjunction with connectivity maps and the L1000 platform, we can predict potential therapeutic drugs and their targets. miRNA analysis Dataset GSE16558 was curated from the GEO, comprising 17 MM plasma cell samples as the experimental group and 5 normal plasma cell samples as the control group. The platform for this dataset is GPL6244. The data and matrices were read and processed using R software version 4.3.1. After stratification, the limma package version 3.49.4 was applied to screen for differentially expressed miRNAs (DEmiRNAs) within the dataset, with a threshold of P 1. Target genes of DEmiRNAs were identified using the mirDB, miRTarbase, and TargetScan databases. The intersection of targets predicted by upregulated and downregulated miRNAs was determined, and any overlapping target genes between the downregulated and upregulated miRNAs were eliminated, resulting in a refined list of target genes for DEmiRNAs. Subsequently, the "clusterProfiler" package within the R programming language was utilized to conduct GO enrichment and KEGG pathway enrichment analyses. Network pharmacology analysis Using "Alisol B 23-acetate" as the keyword, we collected relevant targets of Alisol B 23-acetate from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) available at http://tcmspw.com/tcmsp.php . Subsequently, the 2D structure of Alisol B 23-acetate was obtained by entering the compound into the PubChem database ( https://pubchem.ncbi.nlm.nih.gov/ ), and this structure was uploaded to both the pharmMapper database and the Swiss Target Prediction database to predict the targets of Alisol B 23-acetate. The targets identified from these three databases were consolidated, and duplicates were removed to establish the final set of targets for Alisol B 23-acetate. The UniProt database ( http://www.uniprot.org/ ) was then utilized to standardize the gene names of the targets of Alisol B 23-acetate.With "Multiple myeloma" as the keyword, we mined potential targets associated with MM from the GeneCards database ( https://www.genecards.org/ ), DisGeNET database ( https://www.disgenet.org/ ), and OMIM database ( https://go.drugbank.com/ ). After merging targets from these three databases and removing duplicates, we used the Venny 2.1.0 online platform ( https://bioinfogp.cnb.csic.es/ ) to find the intersection of effective targets of Alisol B 23-acetate and MM. The intersecting targets are considered the relevant target genes regulated by Alisol B 23-acetate in MM. The R 4.3.1 software with the ClusterProfiler package was used to perform GO functional enrichment and KEGG pathway enrichment analyses on the intersecting targets.The intersecting targets were imported into the STRING database ( https://string-db.org/ ) to construct a protein-protein interaction (PPI) network for the common targets of Alisol B 23-acetate and MM. Further in-depth analysis of the PPI network was conducted using Cytoscape_v3.10.2 software, and key targets regulated by Alisol B 23-acetate in MM were identified based on the degree. Integrated Analysis of mRNA, miRNA, and Network Pharmacology We integrated the DEGs and the targets of DEmiRNAs identified through mRNA and miRNA analyses, along with the targets regulated by Alisol B 23-acetate in MM, as determined by network pharmacology. By taking the intersection of these datasets, we identified the key targets of Alisol B 23-acetate in MM that exhibit enhanced effects. Furthermore, we integrated the KEGG-enriched pathways of the DEGs, DEmiRNA targets, and Alisol B 23-acetate-regulated targets in MM. By taking the intersection of these pathways, we identified the key pathways through which Alisol B 23-acetate exerts its enhanced effects on MM. Molecular docking We employed CB-Dock ( http://cao.labshare.cn/cb-dock/ ) for molecular docking to predict the binding affinity of Alisol B 23-acetate with its core targets. CB-Dock is a molecular docking tool based on AutoDock Vina that can automatically identify the binding sites of a ligand with a receptor and analyze the central location and size of the binding site [ 23 ] . The protein and ligand files were obtained from the Protein Data Bank (PDB) ( https://www.rcsb.org/ ) and PubChem ( https://pubchem.ncbi.nlm.nih.gov/ ), respectively [ 24 – 25 ] . Additionally, Ligand Scout software was utilized to analyze the 3D structural features of the drug ligand compound, generating a pharmacophore model to elucidate the interaction patterns between the drug ligand and protein receptor [ 26 ] . CCK-8 assay PBMCs, MM.1S cells, and DOHH2 cells were seeded into 96-well plates and cultured overnight. Subsequently, the cultures were treated with varying concentrations of Alisol B 23-acetate (0µM, 5µM, 10µM, 20µM, 40µM, 80µM, 120µM, 160µM) and bortezomib (BZT) ( 0nM, 1nM, 2nM, 4nM, 8nM, 16nM, 32nM, 64nM), each in 100µL of culture medium, for durations of 24 and 48 hours.According to the protocol provided by the Cell Counting Kit-8 (CCK-8) (Dojindo, Japan), 10µL of CCK-8 solution was added to each well, and the 96-well plates were incubated at 37℃ for 2 hours. The absorbance was measured using a microplate reader (Thermo, USA) at 450 nm to determine the optical density (OD) values. The results were normalized against the negative control group, and the half-maximal inhibitory concentration (IC50) was calculated. Cell cycle analysis After treating MM.1S cells with 15µM Alisol B 23-acetate for 24 hours, both the treated and control groups were collected and fixed in 70% cold ethanol. The cells were then stained with a PI-RNase solution (1 mg/mL PI, 0.1% V/V Triton X-100, and 10 mg/mL RNase), and the acquired data were analyzed using FlowJo software. Cell apoptosis detection MM.1S cells treated with 15 µM Alisol B 23-acetate and the corresponding control group were cultured at 37℃ in a 5% CO2 environment for 24 hours. Subsequently, the cells were collected, washed with cold PBS, and stained with Annexin FITC and PI using an apoptosis detection kit (Solarbio, China) according to the manufacturer's instructions. Apoptosis rates of MM.1S cells were then analyzed using the FACSCalibur and FACSMelody cytometry systems (BD Biosciences). Quantitative real-time PCR analysis Total RNA was extracted from MM.1S cells using an RNA extraction kit (Vazyme, China). The purity of the extracted RNA was determined by measuring the A260/A280 ratio with a NanoDrop spectrophotometer (Thermo, USA), where a value between 1.8 and 2.0 indicates a pure RNA preparation. Complementary DNA (cDNA) was synthesized using a thermal cycler (Thermo, USA) and a first-strand cDNA synthesis kit (Thermo, USA). Quantitative analysis was performed using the SYBR Premix Ex Taq Kit (TaKaRa, Japan) and a real-time quantitative PCR (qRT-PCR) system (Thermo, USA), following the manufacturer's instructions. Primers used in the reactions are listed in Table 1 . Table 1 .Primers for qRT-PCR analysis. Primer sequences(5'to3') Bax-Forward: Bax-Reverse: Bcl2-Forward: Bcl2-Reverse: P38-Forward: P38-Reverse: GAPDH-Forward: GAPDH-Reverse: TCTCCCCGAGAGGTCTTTTT TGATGGTCCTGATCAACTCG ATGTGTGTGGAGAGCGTCAA CTAGGGCCATACAGCTCCAC AGCTGTTGACCGGAAGAA GGGCCAGAGACTGAATGTA ACCACAGTCCATGCCATCAC TCCACCACCCTGTTGCTGTA Western blot analysis Following drug treatment, The cellular protein was extracted by lysing the cells in RIPA buffer (Aidlab, China) supplemented with phosphatase and protease inhibitors, and PMSF inhibitors (Solarbio, China).The cell lysates were rotated at 4℃for 15 minutes, then centrifuged at 12,000 rpm for 10 minutes. The supernatant was collected and mixed with loading buffer, and the protein samples were denatured by boiling for 8 minutes. Protein concentrations were quantified using a BCA protein assay kit. The protein samples were separated by electrophoresis on SDS-PAGE and then electrotransferred onto PVDF membranes. The membranes were blocked with TBST containing 5% skim milk at room temperature for 2 hours, followed by incubation with primary antibodies against β-actin, P38, P-P38, Bcl2, and Bax overnight at 4℃. The membranes were then incubated with secondary antibodies for 2 hours, and the immunoreactive signals were detected using a chemiluminescent Fluor Chem FC3 system. The grayscale intensity of the target bands was quantified using Image J software. The antibody brands and configuration proportions used in WB are shown in Table 2 . Table 2 .Brand and configuration ratio of WB primary antibody Name Brand configuration ratio Bax Abcam(USA) 1:1000 Bcl2 Abcam(USA) 1:1000 P38 proteintech(China) 1:1000 P-P38 Proteintech(China) 1:1000 β-actin Abcam(USA) 1:2000 Results Results of mRNA Analysis Results from the mRNA analysis identified 928 differentially expressed genes, with 238 being upregulated and 690 downregulated ( P 1) (Fig. 1 a-b). GO enrichment analysis indicated significant enrichment in biological processes such as immunoglobulin production and B cell receptor signaling pathways (Fig. 1 c). KEGG pathway enrichment analysis revealed significant enrichment in pathways including the MAPK signaling pathway and B cell receptor signaling pathways (Fig. 1 d). Results of drug prediction Based on the differential analysis of MM gene expression profiles, utilizing the EpiMed, connectivity maps, and the L1000 platform, we have predicted the following traditional Chinese medicine active components as detailed in Table 2 . Among them, Alisol B 23-Acetate shows the greatest negative correlation and has the potential to inhibit MM. Table 2 Prediction Results of Active Components from Traditional Chinese Medicine Rank Name Type Correlation Target 1 2 3 4 5 6 7 8 9 10 Alisol B 23-Acetate Astragaloside I Irisflorentin Amygdalin Glycyrrhizic Acid Ginsenoside Rb3 Polydatin Notoginsenoside R2 Curcumol Icariin Herb Herb Herb Herb Herb Herb Herb Herb Herb Herb -0.730734014 -0.711288711 -0.700218457 -0.698648421 -0.680108771 -0.659227921 -0.643997512 -0.643085293 -0.637254902 -0.631864741 VIM,JUND,MAPK14,DDIT3,GPNMB,EGR1,SQLE,PDK4,DIS3,NCF2,et al. ZC3H6,TMEM173,NOC3L,RND3,RARS,TRAPPC6B,TUBD1,LTN1,CRISP3,TTC3,et al. RND3,ZNF860,ATP6V1C1,NFE2L2,MORC3,SUCLA2,PDCD4,NEDD9,VIM,ZNF570et al. VIM,RRP12,MYB,ZFP62,EGR1,CD24,CD36,SOS1,NIPBL,CHD9,et al. RND3,VIM,MYB,ZBTB10,LTN1,RRP12,TOP2B,TTC3,SEC62,UFL1,et al. OGT,LYST,BRCA2,PHIP,EML5,INTS2,UBR5,CHD9,RIF1,ATRX,et al. ESF1,CWC22,ZNF83,CLK4,ZC3H13,ZNF248,ESCO1,ATM,SOCS3,EMP1,et al. BRWD3,CEACAM6,DICER1,PHIP,UBR5,LYST,INTS2,TTC3,CNOT1,MYCBP2,et al. TEAD1,DEK,MPHOSPH9,KNTC1,PUS7L,KLF9,ZNF146,XPO1,SUPT20H,SOS2,et al. BRCA2,FRYL,PHIP,CNOT1,MYCBP2,CKAP5,UBR5,EML5,NUP160,RAD50,et al. Results of miRNA Analysis miRNA Analysis Yields 20 DEmiRNAs, with 11 Upregulated and 9 Downregulated. A total of 20 DEmiRNAs were identified, consisting of 11 upregulated and 9 downregulated miRNAs(Fig. 2 a-b). The upregulated miRNAs targeted 1244 genes (Fig. 2 c), while the downregulated miRNAs targeted 1160 genes (Fig. 2 d). After removing the overlapping genes targeted by both upregulated and downregulated miRNAs, a final set of 2404 DEmiRNA target genes was obtained. GO enrichment analysis of these target genes revealed significant enrichment in biological processes such as miRNA metabolic processes, miRNA transcriptional regulation, and response to hypoxia (Fig. 2 e). KEGG pathway enrichment analysis particularly highlighted the MAPK signaling pathway (Fig. 2 f). Results of network pharmacology analysis Network pharmacology analysis identified 100 drug targets and 1931 disease targets, with an intersection of 31 targets common to both (Fig. 3 a). PPI core protein screening revealed MAPK14 (also known as P38), JAK1, MAPK1, and others (Fig. 3 b-c). GO enrichment highlighted molecular functions such as serine and threonine kinase activity (Fig. 3 d), and KEGG pathway enrichment analysis showed significant enrichment in pathways including Proteoglycans in cancer and the MAPK signaling pathway (Fig. 3 e). Integrated analysis of mRNA, miRNA and Network Pharmacology Upon integrating the results from mRNA, miRNA, and network pharmacology analyses, we discovered that the KEGG pathway enrichment results from all three datasets converged on two common pathways: the MAPK signaling pathway and the FoxO signaling pathway (Fig. 4 a). The MAPK signaling pathway exhibited a lower P -value and a greater number of enriched genes. Concurrently, there was a single common target, MAPK14, identified at the intersection of differential mRNA genes, target genes of DEmiRNAs, and the intersection of drug and disease targets from network pharmacology analysis (Fig. 4 b). This target is also included among the core targets identified in the network pharmacology PPI analysis. Moreover, P38, which is encoded by the MAPK14 gene, is a critical hub in the P38 MAPK pathway. Results of molecular docking To preliminarily predict the binding efficacy of Alisol B 23-acetate with MAPK14, we employed molecular docking to assess the binding energy score between them. The lower the binding energy score, the more effective and stable the binding of the ligand to the receptor. Figure 4 c displays the optimal docking conformation of Alisol B 23-acetate with MAPK14. The molecular docking results indicate that Alisol B 23-acetate has a binding energy of -9.7 kcal/mol with MAPK14, suggesting a strong binding affinity. Figure 4 d illustrates the structure of the Alisol B 23-acetate ligand, its position within the binding pocket, and the pharmacophore features. The Alisol B 23-acetate ligand forms hydrogen bond donors with threonine 106, aspartic acid 168, and asparagine 115 of the MAPK14 receptor, and a hydrogen bond acceptor with serine 154. Alisol B 23-acetate Inhibits the Proliferation of Multiple Myeloma Cells To assess the impact of Alisol B 23-acetate on the proliferation of MM.1S cells, the CCK-8 assay was employed to evaluate cell viability. As shown in Figs. 5 a-d, the calculated IC50 values for Alisol B 23-acetate in MM.1S cells were 14.24 µM at 24 hours and 15.18 µM at 48 hours, while the IC50 values for bortezomib (BZT) were 6.46 nM at 24 hours and 5.22 nM at 48 hours. At the 24-hour IC50 concentration, the inhibition rates of Alisol B 23-acetate and BZT on PBMCs were 1.3% and 3.7%, respectively, and at 48 hours, these rates were 2.6% and 4.3%, respectively. In order to initially explore the selectivity of Alisol B 23-acetate for MM, our experiments were also carried out in lymphoma cell lines. The results showed that in DOHH2, the IC50 of Alisol B 23-acetate was 24.64µM at 24 h and 26.12µM at 48 h, and the IC50 of Alisol B 23-acetate was 26.12µM at 48 h. The IC50 of BZT was 43.32nM at 24h and 48.72nM at 48h. Compared to untreated MM.1S cells, Alisol B 23-acetate significantly inhibited the proliferative capacity of MM.1S cells. Alisol B 23-acetate exhibited a significantly higher inhibition rate against MM.1S than against DOHH2, showing a certain degree of selectivity for MM.1S. At the IC50 concentration, Alisol B 23-acetate demonstrated a lower inhibition rate on PBMCs compared to BZT, indicating lower toxicity than BZT. Alisol B 23-Acetate Promotes Apoptosis in Multiple Myeloma Cells We evaluated the effects of Alisol B 23-acetate on the cell cycle and induction of apoptosis in MM.1S cells using flow cytometry. Cell cycle analysis revealed that, compared to the control group, the percentage of cells in the G0/G1 phase (resting/before DNA synthesis) was increased, while the percentage in the S/G2 phase (DNA replication/after DNA synthesis) was decreased in the Alisol B 23-acetate treated group (Fig. 5 e-g). Apoptosis results indicated that Alisol B 23-acetate significantly enhanced apoptosis in MM.1S cells, with the sum of Q2 and Q3, representing apoptotic cells, reaching 57.3% (Fig. 5 h-j). These data suggest that Alisol B 23-acetate promotes apoptosis in MM.1S cells and slows the transition of cells from the G1 phase to the S phase. Alisol B 23-Acetate Inhibition of the P38MAPK Pathway To determine the mechanism by which Alisol B 23-acetate induces apoptosis in MM.1S cells through the inhibition of the P38MAPK pathway, we utilized qRT-PCR to assess the expression of apoptotic genes and P38 in MM.1S cells. MM.1S cells were treated with 15 µM Alisol B 23-acetate for 24 hours, after which they were lysed and RNA was extracted for qRT-PCR analysis. The results indicate that Alisol B 23-acetate increased the expression of the pro-apoptotic gene Bax (Fig. 5 k), decreased the expression of the anti-apoptotic gene Bcl2 (Fig. 5 l), while the expression of the P38 gene remained essentially unchanged (Fig. 5 m). We further examined the expression changes of apoptotic genes and P38 at the protein level in MM.1S cells treated with Alisol B 23-acetate using western blotting. In MM.1S cells treated with Alisol B 23-acetate, the expression of the anti-apoptotic protein Bcl2 was decreased (Fig. 6 a), while the expression of the pro-apoptotic protein Bax was increased (Fig. 6 a). We also observed a reduction in P38 protein phosphorylation in MM.1S cells treated with Alisol B 23-acetate (Fig. 6 b). Additionally, the Bcl2/Bax ratio and the ratio of P38 protein phosphorylation in Alisol B 23-acetate treated MM.1S cells were more significantly decreased compared to DOHH2 (Fig. 6 c-d), and in Alisol B 23-acetate treated DOHH2, the ratio of P38 protein phosphorylation remained essentially unchanged (Fig. 6 d). In Alisol B 23-acetate treated MM.1S cells, the decrease in the Bcl2/Bax ratio was slightly less compared to bortezomib (BZT) treated MM.1S (Fig. 6 e), and the ratio of P38 protein phosphorylation significantly decreased (Fig. 6 f), while in BZT treated MM.1S, the ratio of P38 protein phosphorylation remained essentially unchanged (Fig. 6 f). In PBMCs, neither Alisol B 23-acetate nor BZT treatment resulted in significant changes in the Bcl2/Bax ratio or the ratio of P38 protein phosphorylation (Fig. 6 e-f). These results suggest that Alisol B 23-acetate induces apoptosis in MM.1S cells by inhibiting the phosphorylation of the core target P38 protein in the P38MAPK pathway. Discussion In this study, we utilized gene expression profiling data from MM to predict drugs and then integrated this with miRNA data and network pharmacology from the same dataset to determine the key pathways and nodes involved in the antitumor effects of the drugs. Our data indicate that Alisol B 23-acetate has a cytotoxic effect on MM.1S cells. Treatment with Alisol B 23-acetate can significantly inhibit the proliferation of MM.1S cells and promote apoptosis through the Bcl-2/Bax and P38MAPK signaling pathways. Moreover, Alisol B 23-acetate has almost no inhibitory effect on normal human PBMC and exhibits significantly lower inhibitory activity against the lymphoma cell line DOHH2 compared with MM. This indicates that Alisol B 23-acetate has low toxicity while showing certain selectivity for MM. Additionally, Alisol B 23-acetate does not inhibit the P38MAPK signaling pathway in PBMC and DOHH2. MM is an incurable hematological malignancy that eventually recurs and leads to the death of the vast majority of patients [ 1 ] . Despite the availability of various new drugs for treatment, many MM patients achieve disease control and improved quality of life, but a significant number still progress to RRMM, which has a poor clinical outcome [ 27 ] . For RRMM patients, chimeric antigen receptor T (CAR-T) cell therapy has demonstrated promising efficacy and safety. While significant advancements have been made in the field of CAR-T therapy, challenges such as antigen escape and therapeutic resistance remain [ 28 ] . Therefore, there is an urgent need to develop effective therapeutic agents with fewer side effects. Based on previous studies, we have predicted that Alisol B 23-acetate has a certain potential for the treatment of MM, but it still needs further discussion and verification. Alisol B 23-acetate is a natural triterpenoid compound from the rhizome of the Chinese herb Alisma orientale, which has been reported to have excellent biological activities, including anti-inflammatory, antibacterial, and anti-proliferation [ 5 – 7 ] . Modern pharmacological studies have shown that Alisol B 23-acetate can exhibit good anti-tumor properties by affecting the MAPK signaling pathway [ 10 ] . In one study, Alisol B 23-acetate inhibited the activation of the MAPK pathway in gastric cancer cells, resulting in cell cycle arrest and mitochondrial pathway induced cell apoptosis, accompanied by MAPK signaling cascades and reduced phosphorylation of P38, ERK and JNK [ 29 ] . Another study showed that the intervention of Alisol B 23-acetate in mice with colon cancer resulted in a significant reduction in MAPK activation and a significant reduction in the phosphorylation of p38, ERK and JNK [ 30 ] . However, the effects of Alisol B 23-acetate on MM and the underlying mechanisms remain unclear. In the present study, it was found that Alisol B 23-acetate inhibited the proliferation of MM cells in a dose-dependent manner, and the IC50 value of MM cells was significantly reduced after 24h and 48h of treatment with Alisol B 23-acetate. In addition, Alisol B 23-acetate was not significantly toxic to PBMC, which maintained high cell viability even at higher doses. Meanwhile, the inhibitory effect of Alisol B 23-acetate on lymphoma DOHH2 cells is significantly lower than that on MM cells. Alisol B 23-acetate selectively inhibits the proliferation of MM cells and has low toxicity on normal cells, which has potential therapeutic value. Through the comprehensive analysis of mRNA, miRNA and network pharmacology, we found that Alisol B 23-acetate acted on the key pathway of MM, P38MAPK signaling pathway, and the key target, P38, suggesting that Alisol B 23-acetate may play an important role in the pathogenesis of MM. Based on these analysis results, our study validated the effects of Alisol B 23-acetate on MM cell apoptosis, cell proliferation, cell cycle regulation and P38MAPK signaling pathway. Apoptosis maintains physiological balance and eliminates cancer cells in response to external stimuli, such as small molecule drugs [ 31 ] . Apoptosis pathways can be divided into exogenous and endogenous pathways [ 32 ] . Upon stimulation, Bcl-2 family proteins activate MMPs, leading to the release of cytochrome c from mitochondria into the cytoplasm, which triggers the release of the caspase cascade. Through this series of effects, it will lead to cell apoptosis [ 33 ] . In the experiments, we found that Alisol B 23-acetate inhibited the expression of Bcl-2 and increased the level of Bcl-2, indicating that Alisol B 23-acetate was involved in the endogenous apoptotic pathway. The significant increase in Bax and decrease in Bcl-2 levels in MM.1S cells treated with 15 µM Alisol B 23-acetate highlight the role of Alisol B 23-acetate in inducing apoptosis through the endogenous pathway. Bcl-2 and Bax are important markers of apoptosis [ 34 ] . Reduced Bcl-2 levels and increased Bax levels mark the activation of the endogenous apoptotic pathway, confirming the role of Alisol B 23-acetate in the induction of apoptosis. Our results showed that Alisol B 23-acetate could induce significant cell cycle arrest in G0/G1 phase of MM cells. The G0/G1 phase is a critical phase in the cell cycle where cells decide whether to continue dividing or enter quiescence [ 35 ] . Alisol B 23-acetate is able to interfere with this process, especially the arrest in the G0/G1 phase, which is normally a cellular defense response to stress or injury. When a cell is stressed or injured, it usually stops its cycle progression to allow enough time for repair or to wait for further signals. If this damage cannot be repaired, cells may choose to initiate programmed death or enter a state of senescence [ 36 , 37 ] . The G0/G1 phase arrest induced by Alisol B 23-acetate suggests that the drug may inhibit further proliferation by activating the stress response mechanism of the cells and preventing them from entering the S phase. Secondly, Alisol B 23-acetate may also act by inhibiting the expression and activity of specific cell cycle proteins in G1 phase, such as D1/D3 [ 38 ] . These cyclins are key regulators required for cells to transition from G1 to S phase [ 39 ] . Alisol B 23-acetate effectively prevents cells from entering S phase by reducing the levels of these proteins and preventing their binding to cell cycle-dependent kinase (CDK4/6) [ 40 ] . P38MAPK signaling pathway plays a crucial role in the pathogenesis of MM [ 41 ] .P38 is a member of the MAPK family, which plays a crucial role in cellular activities such as the cell cycle, apoptosis, and autophagy [ 42 ] . The MAPK family consists of three major subgroups and their respective pathways: P38, ERK, and JNK [ 43 ] . Despite the diversity in function and upstream signaling events, MAPKs are activated by a highly conserved mechanism involving the phosphorylation of threonine and tyrosine residues catalyzed by MAPK kinases [ 44 ] . In a study, Alisol B 23-acetate was found to inhibit the activation of the MAPK pathway in gastric cancer cells, leading to cell cycle arrest and the induction of apoptosis via the mitochondrial pathway, accompanied by a decrease in the phosphorylation of P38, ERK, and JNK within the MAPK signaling cascade [ 10 ] . Another study demonstrated that the intervention of Alisol B 23-acetate in a mouse model of colon cancer resulted in a significant reduction in the activation of the MAPK pathway, with a notable decrease in the phosphorylation of p38, ERK, and JNK [ 45 ] . In a study, it was discovered that P38MAPK inhibitors can enhance the sensitivity of MM cells to bortezomib, Hsp90 inhibitors, and dexamethasone, thereby augmenting their cytotoxic effects on MM cells [ 46 ] . Another study indicated that P38MAPK is constitutively activated in MM, and high expression of its primary substrate, MAPKAPK2 (MK2), is associated with poorer prognosis in MM patients, with MK2 inhibitors capable of suppressing MM cell growth and colony formation [ 47 ] . Furthermore, a clinical study demonstrated that the activation of the MAPK pathway has a negative impact on the prognosis of MM patients [ 48 ] . In this study, we have unveiled the antitumor effects of Alisol B 23-acetate on MM and its impact on the key signaling pathway, the P38MAPK pathway, providing a foundation for the development of new therapeutic strategies and potential for improving the prognosis of patients with RRMM. However, although our data provide experimental evidence that Alisol B 23-acetate has an anti-MM effect by inhibiting the P38MAPK signaling pathway, it is still necessary to further clarify the mechanism of Alisol B 23-acetate through P38MAPK pathway inhibitors. And to verify the validity of these findings in mammalian models. Declarations Competing interests The authors declare no competing interests. Funding National Key Research and Development Program of China(2021YFC2701703) Author Contribution Hui Zhang made contributions to article writing, bioinformatics analysis, conducting experiments, and data analysis. Jie Geng and Peng Zhao provided guidance in bioinformatics. Yuntao Zhu and Xuechun Lu contributed to revising the manuscript.All authors have reviewed the manuscript. Acknowledgements We appreciated the contributions made by all authors. Data Availability The supporting data for the conclusions drawn in this research can be accessed within the methods section or supplementary materials provided alongside this article. References Malard, F. et al. Multiple myeloma. Nat. Rev. Dis. Primers . 10 (1), 45. 10.1038/s41572-024-00529-7 (2024). Published 2024 Jun 27. Dimopoulos, M. A. et al. Multiple myeloma: EHA-ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 32 (3), 309–322. 10.1016/j.annonc.2020.11.014 (2021). Caers, J. et al. European Myeloma Network recommendations on tools for the diagnosis and monitoring of multiple myeloma:what to use and when. Haematologica 103 (11), 1772–1784. 10.3324/haematol.2018.189159 (2018). Yu, C. C. et al. Active Components of Traditional Chinese Medicinal Material for Multiple Myeloma: Current Evidence and Future Directions. Front. Pharmacol. 13 , 818179. 10.3389/fphar.2022.818179 (2022). Published 2022 Jan 27. Du, Q. et al. Alisol B 23-acetate broadly inhibits coronavirus through blocking virus entry and suppresses proinflammatory T cells responses for the treatment of COVID-19. J. Adv. Res. 62 , 273–290. 10.1016/j.jare.2023.10.002 (2024). Li, C. et al. Anti-bacterial effect of phytoconstituents isolated from Alimatis rhizoma. Appl. Biol. Chem. 64 , 9. 10.1186/s13765-020-00583-1 (2021). Xia, J. et al. Alisol B 23-acetate-induced HepG2 hepatoma cell death through mTOR signaling-initiated G1 cell cycle arrest and apoptosis: A quantitative proteomic study. Chin. J. Cancer Res. 31 (2), 375–388. 10.21147/j.issn.1000-9604.2019.02.12 (2019). Liu, Y. et al. Alisol B 23acetate inhibits the viability and induces apoptosis of nonsmall cell lung cancer cells via PI3K/AKT/mTOR signal pathway. Mol. Med. Rep. 20 (2), 1187–1195. 10.3892/mmr.2019.10355 (2019). Xia, F. et al. Alisol B 23-Acetate Ameliorates Lipopolysaccharide-Induced Intestinal Barrier Dysfunction by Inhibiting TLR4-NOX1/ROS Signaling Pathway in Caco-2 Cells. Front. Pharmacol. 13 , 911196. 10.3389/fphar.2022.911196 (2022). Published 2022 Jun 14. Kwon, M. J. et al. Apoptotic effects of alisol B 23acetate on gastric cancer cells. Mol. Med. Rep. 23 (4), 248. 10.3892/mmr.2021.11887 (2021). Cerneckis, J. et al. The rise of epitranscriptomics: recent developments and future directions. Trends Pharmacol. Sci. 45 (1), 24–38. 10.1016/j.tips.2023.11.002 (2024). Shang, R. et al. microRNAs in action: biogenesis, function and regulation. Nat. Rev. Genet. 24 (12), 816–833. 10.1038/s41576-023-00611-y (2023). Nogales, C. et al. Network pharmacology: curing causal mechanisms instead of treating symptoms. Trends Pharmacol. Sci. 43 (2), 136–150. 10.1016/j.tips.2021.11.004 (2022). Paggi, J. M., Pandit, A. & Dror, R. O. The Art and Science of Molecular Docking. Annu. Rev. Biochem. 93 (1), 389–410. 10.1146/annurev-biochem-030222-120000 (2024). Zhang, W. & Liu, H. T. MAPK signal pathways in the regulation of cell proliferation in mammalian cells. Cell. Res. 12 (1), 9–18. 10.1038/sj.cr.7290105 (2002). Yuan, J., Dong, X., Yap, J. & Hu, J. The MAPK and AMPK signalings: interplay and implication in targeted cancer therapy. J. Hematol. Oncol. 13 (1), 113. 10.1186/s13045-020-00949-4 (2020). Published 2020 Aug 17. Tang, X. et al. Combined intermittent fasting and ERK inhibition enhance the anti-tumor effects of chemotherapy via the GSK3β-SIRT7 axis. Nat Commun. ;12(1):5058. Published 2021 Aug 25. (2021). 10.1038/s41467-021-25274-3 Mahalingam, D. et al. Heightened JNK Activation and Reduced XIAP Levels Promote TRAIL and Sunitinib-Mediated Apoptosis in Colon Cancer Models. Cancers (Basel) . 11 (7), 895. 10.3390/cancers11070895 (2019). Published 2019 Jun 26. Owens, T. W. et al. Apoptosis commitment and activation of mitochondrial Bax during anoikis is regulated by p38MAPK. Cell. Death Differ. 16 (11), 1551–1562. 10.1038/cdd.2009.102 (2009). Zhang, J. et al. Quantitative transcriptome-based analysis predicts a combination therapy for severe haemophilia B: A case report. Br. J. Haematol. 204 (3), 1105–1108. 10.1111/bjh.19261 (2024). Alharbi, H. et al. Identification of Potential Biomarkers and Pathways in Acute Myeloid Leukemia: Correlation Between the Calcineurin Signaling Pathway and Vascular Brittleness in Acute Myeloid Leukemia. Int. J. Lab. Hematol. Published online Dec. 5 10.1111/ijlh.14410 (2024). Zhang, J. D. et al. Zhongguo Shi Yan Xue Ye Xue Za Zhi. ;29(3):975–982. (2021). 10.19746/j.cnki.issn.1009-2137.2021.03.051 Liu, Y. et al. CB-Dock: a web server for cavity detection-guided protein-ligand blind docking. Acta Pharmacol. Sin . 41 (1), 138–144. 10.1038/s41401-019-0228-6 (2020). Happy anniversary, P. D. B. Nat. Struct. Mol. Biol. ; 28 (5):399. doi: 10.1038/s41594-021-00598-2 (2021). Kim, S. et al. PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Res. 49 (D1), D1388–D1395. 10.1093/nar/gkaa971 (2021). Vuorinen, A. et al. Ligand-based pharmacophore modeling and virtual screening for the discovery of novel 17β-hydroxysteroid dehydrogenase 2 inhibitors. J. Med. Chem. 57 (14), 5995–6007. 10.1021/jm5004914 (2014). van de Donk, N. W. C. J., Pawlyn, C. & Yong, K. L. Multiple myeloma. Lancet 397 (10272), 410–427. 10.1016/S0140-6736(21)00135-5 (2021). Parikh, R. H. & Lonial, S. Chimeric antigen receptor T-cell therapy in multiple myeloma: A comprehensive review of current data and implications for clinical practice. CA Cancer J. Clin. 73 (3), 275–285. 10.3322/caac.21771 (2023). Kwon, M. J. et al. Apoptotic effects of alisol B 23acetate on gastric cancer cells. Mol. Med. Rep. 23 (4), 248 (2021). Zhu, H. C. et al. Alisol B 23-Acetate Ameliorates Azoxymethane/Dextran Sodium Sulfate-Induced Male Murine Colitis-Associated Colorectal Cancer via Modulating the Composition of Gut Microbiota and Improving Intestinal Barrier. Front. Cell. Infect. Microbiol. 11 , 640225 (2021). Published 2021 Apr 29. Morana, O. et al. The apoptosis paradox in cancer[J]. Int. J. Mol. Sci. 23 (3), 1328 (2022). Goldar, S. et al. Molecular mechanisms of apoptosis and roles in cancer development and treatment[J]. Asian Pac. J. Cancer Prev. 16 (6), 2129–2144 (2015). Eskandari, E. et al. Paradoxical roles of caspase-3 in regulating cell survival, proliferation, and tumorigenesis[J]. J. Cell. Biol. 221 (6), e202201159 (2022). Tettenborn, D. Toxicity of clotrimazole[J]. Postgrad. Med. J. 50 (1), 17–20 (1974). Wang, Z. et al. Cell Cycle Progression and Synchronization: An Overview. Methods Mol. Biol. 66 (12), 3–23 (2022). Qie, S. et al. Cyclin D1, cancer progression, and opportunities in cancer treatment. J. Mol. Med. (Berl) . 66 (12), 1313–1326 (2016). Tchakarska, G. et al. The double dealing of cyclin D1. Cell. Cycle . 66 (12), 163–178 (2020). Martínez-Limón, A., Joaquin, M., Caballero, M., Posas, F. & de Nadal, E. The p38 Pathway: From Biology to Cancer Therapy. Int. J. Mol. Sci. 21 (6), 1913. 10.3390/ijms21061913 (2020). Published 2020 Mar 11. Braicu, C. et al. A Comprehensive Review on MAPK: A Promising Therapeutic Target in Cancer. Cancers (Basel). ;11(10):1618. Published 2019 Oct 22. (2019). 10.3390/cancers11101618 González-Rubio, G., Sellers-Moya, Á., Martín, H. & Molina, M. Differential Role of Threonine and Tyrosine Phosphorylation in the Activation and Activity of the Yeast MAPK Slt2. Int J Mol Sci. ;22(3):1110. Published 2021 Jan 23. (2021). 10.3390/ijms22031110 Sui, X. et al. p38 and JNK MAPK pathways control the balance of apoptosis and autophagy in response to chemotherapeutic agents. Cancer Lett. 344 (2), 174–179. 10.1016/j.canlet.2013.11.019 (2014). Yuan, W. et al. Modulating p38 MAPK signaling by proteostasis mechanisms supports tissue integrity during growth and aging. Nat Commun. ;14(1):4543. Published 2023 Jul 28. (2023). 10.1038/s41467-023-40317-7 Canovas, B. & Nebreda, A. R. Diversity and versatility of p38 kinase signalling in health and disease. Nat. Rev. Mol. Cell. Biol. 22 (5), 346–366. 10.1038/s41580-020-00322-w (2021). Yasui, H. et al. BIRB 796 enhances cytotoxicity triggered by bortezomib, heat shock protein (Hsp) 90 inhibitor, and dexamethasone via inhibition of p38 mitogen-activated protein kinase/Hsp27 pathway in multiple myeloma cell lines and inhibits paracrine tumour growth. Br. J. Haematol. 136 (3), 414–423. 10.1111/j.1365-2141.2006.06443.x (2007). Gu, C. et al. MK2 is a therapeutic target for high-risk multiple myeloma. Haematologica 106 (6), 1774–1777. 10.3324/haematol.2017.182121 (2021). Published 2021 Jun 1. Perroud, C. et al. Effect of MAPK activation via mutations in NRAS, KRAS and BRAF on clinical outcome in newly diagnosed multiple myeloma. Hematol. Oncol. 41 (5), 912–921. 10.1002/hon.3208 (2023). Harris, M. H. & Thompson, C. B. The role of the Bcl-2 family in the regulation of outer mitochondrial membrane permeability. Cell. Death Differ. 7 (12), 1182–1191. 10.1038/sj.cdd.4400781 (2000). Lee, M. L. et al. KMUP-1 Ameliorates Ischemia-Induced Cardiomyocyte Apoptosis through the NO⁻cGMP⁻MAPK Signaling Pathways. Molecules. ;24(7):1376. Published 2019 Apr 8. (2019). 10.3390/molecules24071376 Additional Declarations No competing interests reported. Supplementary Files Supplementaryfile.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6923004","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":489058229,"identity":"a4226524-535a-4366-a46b-545c9fa23678","order_by":0,"name":"Hui Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIie3RMYvCMBTA8SeBuDyv6ysG/Qo5hE4Fv0pKxamCY4cOQsUO1ru1H8PxxhMhXdK9o34D3ZyO6660ve2G/KY35E9eCIBl/UN8ei4fChN0hp/Xi4qT7uSNuKKb0MLNDZMXo7uTCaF0C5/5so64e92yHouNcznDiCOYSsfBhoOT7VV7IvQ6RCNwkH0s6+BLAJnq2J5AeDyPco4Mv706MBwkrboS9Z6OfhhyUt462LEeCS1mg6K5AynyoF+Cegk31EioQ1KmGbreMs1SDc1Xzudlero/4mTiZIf25An+7bhlWZb10i/VAkZABqSyTQAAAABJRU5ErkJggg==","orcid":"","institution":"Jiangnan University","correspondingAuthor":true,"prefix":"","firstName":"Hui","middleName":"","lastName":"Zhang","suffix":""},{"id":489058230,"identity":"469f85a1-3bc7-44d6-b5b8-7c99b552b279","order_by":1,"name":"Peng Zhao","email":"","orcid":"","institution":"Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Peng","middleName":"","lastName":"Zhao","suffix":""},{"id":489058231,"identity":"7f913c80-58a6-402f-b944-c628664c2740","order_by":2,"name":"Jie Geng","email":"","orcid":"","institution":"Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Geng","suffix":""},{"id":489058232,"identity":"f9f5c83e-7632-4030-a77b-57b47d140c2a","order_by":3,"name":"Yuntao Zhu","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Yuntao","middleName":"","lastName":"Zhu","suffix":""},{"id":489058233,"identity":"fc90c250-aa0d-42b8-baf5-5c727495f083","order_by":4,"name":"Xuechun Lu","email":"","orcid":"","institution":"Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xuechun","middleName":"","lastName":"Lu","suffix":""}],"badges":[],"createdAt":"2025-06-18 12:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6923004/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6923004/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87523353,"identity":"23cbf1a2-3a35-40c7-8825-bde904c56c69","added_by":"auto","created_at":"2025-07-24 18:33:51","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":146202,"visible":true,"origin":"","legend":"\u003cp\u003emRNA Analysis Results. (a) Volcano plot of mRNA differential expression analysis, where red circles represent upregulated genes and blue\u003cdel\u003egreen\u003c/del\u003e circles represent downregulated genes. (b) Heatmap of mRNA differential expression analysis, with red indicating upregulated gene expression and blue\u003cdel\u003egreen\u003c/del\u003eindicating downregulated gene expression. (c) Bar chart of GO enrichment analysis for DEGs. (d) Bubble chart of KEGG enrichment analysis for DEGs.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6923004/v1/485832b47c811b6fc74d9c77.jpeg"},{"id":87523351,"identity":"850f7688-3c6a-4d33-b5c6-5442b08bb042","added_by":"auto","created_at":"2025-07-24 18:33:51","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":819237,"visible":true,"origin":"","legend":"\u003cp\u003emiRNA Analysis Results. (a) Volcano plot of differential miRNA expression, where red indicates upregulated miRNAs and blueindicates downregulated miRNAs. (b) Heatmap of differential miRNA expression, with red representing upregulated miRNAs and bluerepresenting downregulated miRNAs. (c) Venn diagram of target genes for upregulated miRNAs. (d) Venn diagram of target genes for downregulated miRNAs. (e) Bar chart of GO enrichment analysis for DEmiRNA target genes. (f) Bubble chart of KEGG enrichment analysis for DEmiRNA target genes.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6923004/v1/3e0a2bdbda91eb1e5b694152.jpeg"},{"id":87523785,"identity":"38745705-ffe3-45f3-a8ff-65350a95e9a5","added_by":"auto","created_at":"2025-07-24 18:41:51","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":207203,"visible":true,"origin":"","legend":"\u003cp\u003eResults of Network Pharmacology Analysis. (a) Venn diagram representing the intersection of targets for Alisol B 23-acetate and MM. (b) PPI network of the intersecting targets. (c) Identification of core targets within the PPI network. (d) Bar chart of GO enrichment analysis for the intersecting targets. (e) Bubble chart of KEGG enrichment analysis for the intersecting targets.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6923004/v1/e3cb74c06b24be0f7c5b504c.jpeg"},{"id":87523950,"identity":"533d1fc7-cde4-4695-a185-4d37c28b9730","added_by":"auto","created_at":"2025-07-24 18:49:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":783201,"visible":true,"origin":"","legend":"\u003cp\u003eIntegrated Analysis and Molecular Docking Results. (a) KEGG intersection from mRNA, miRNA, and network pharmacology analyses. (b) Intersection of DEGs, target genes of DEmiRNAs, and targets from network pharmacology. (c) The 3D conformation of the molecular docking between Alisol B 23-acetate and MAPK14 can be visualized using PyMOL (version 2.5.2, https://pymol.org/). (d) Using LigandScout (version 4.5, https://www.inteligand.com/) to perform pharmacophore analysis of the binding mode between Alisol B 23-acetate and MAPK14, with hydrophobic interactions represented by yellow spheres, hydrogen bond donors by green arrows, and hydrogen bond acceptors by red arrows.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6923004/v1/973191a0176be6866aa9ef76.png"},{"id":87523357,"identity":"7609ea3d-4994-4978-8b2f-98e5aa81ab37","added_by":"auto","created_at":"2025-07-24 18:33:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":502738,"visible":true,"origin":"","legend":"\u003cp\u003eThe Pro-apoptotic Effects of Alisol B 23-acetate on MM. (a-d) Cell viability of Alisol B 23-acetate and BZT treated for 24 or 48 hours. (e-g) Cell cycle distribution of Alisol B 23-acetate treated and control MM.1S cells. (h-j) Apoptosis distribution of Alisol B 23-acetate treated and control MM.1S cells. (k-m) Expression levels of Bax (k), Bcl-2 (l), and P38 (m) genes in Alisol B 23-acetate treated and control MM.1S cells.*\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05，**\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01，***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001，ns Indicates no statistically significant difference(\u003cem\u003eP\u003c/em\u003e ≥ 0.05).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6923004/v1/d40b4a2686874010ba6e503e.png"},{"id":87523363,"identity":"aa9c96db-6481-4906-a0c9-7ddf7878a1a9","added_by":"auto","created_at":"2025-07-24 18:33:51","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":414525,"visible":true,"origin":"","legend":"\u003cp\u003eInhibition of P38MAPK by Alisol B 23-acetate. (a-b) Protein expression levels of Bcl2/Bax (a) and P-P38/P38 (b) in MM.1S cells treated with varying concentrations of Alisol B 23-acetate. (c-d) Protein expression levels of Bcl2/Bax (c) and P-P38/P38 (d) in MM.1S and DOHH2 cells, comparing Alisol B 23-acetate treated groups with untreated controls. (e-f) Protein expression levels of Bcl2/Bax (e) and P-P38/P38 (f) in MM.1S and PBMC cells, comparing Alisol B 23-acetate treated groups, BZT treated groups, and untreated controls.(Original blots/gels are presented in Supplementary information).*\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05，**\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01，***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001，ns Indicates no statistically significant difference(\u003cem\u003eP\u003c/em\u003e ≥ 0.05).\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6923004/v1/b9e80aa5bb3bacb15d9a90ff.png"},{"id":103015518,"identity":"2bd37ee9-08d8-431d-a6d5-9f41c8578721","added_by":"auto","created_at":"2026-02-19 16:26:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3433029,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6923004/v1/83270470-3927-4a5f-ab0c-5898a755b998.pdf"},{"id":87523354,"identity":"99fe9548-2172-4967-993b-e12616fee25a","added_by":"auto","created_at":"2025-07-24 18:33:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":959136,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6923004/v1/97d983bf6bdf8f52eaea6e11.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unraveling the Anti-Multiple Myeloma Activity of Alisol B 23-Acetate and Its Impact on the P38MAPK Pathway Through Integrated Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMultiple myeloma (MM), a hematological malignancy involving plasma cells, is the second most common hematological neoplasm worldwide, with an increasing incidence rate\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Despite the use of targeted myeloma therapies and immunomodulatory agents, which have improved survival rates among MM patients, the disease remains incurable. The mainstay of first-line treatment includes drugs such as bortezomib (BZT) and lenalidomide (LEN)\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Although various new medications are employed in treatment, leading to disease control and enhanced quality of life for many MM patients, a significant number still progress to relapsed/refractory multiple myeloma (RRMM), which is associated with poor clinical outcomes\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Therefore, the investigation of novel anti-MM therapeutic strategies is of paramount importance.In recent years, there has been a surge of interest in the use of Traditional Chinese Medicine (TCM) for treating a variety of diseases. Bioactive components derived from TCM hold significant potential in the development of anticancer drugs. According to reports, active ingredients derived from TCM are expected to play a role in treating MM. These ingredients may help overcome the issues commonly associated with first-line MM treatment regimens, such as drug resistance, relapse, and significant side effects\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Consequently, the search for new effective components against MM from the bioactive constituents of TCM is of great significance.\u003c/p\u003e\u003cp\u003eAlisol B 23-acetate is a naturally occurring triterpenoid compound derived from the rhizome of the traditional Chinese herb Alisma orientale, which has been reported to exhibit potent biological activities, including anti-inflammatory, antibacterial, and anti-proliferative effects\u003csup\u003e[\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Modern pharmacological studies have demonstrated that Alisol B 23-acetate can display significant antitumor properties by influencing the PI3K/Akt/mTOR pathway, reactive oxygen species (ROS) generation, and the MAPK signaling pathway\u003csup\u003e[\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. However, the impact of Alisol B 23-acetate on MM and its underlying mechanisms remain to be elucidated.\u003c/p\u003e\u003cp\u003eTranscriptomics research offers a rapid method for determining changes in mRNA levels following disease or drug perturbations. By establishing transcriptomic differential expression profiles, we can delineate in detail the gene expression changes in patients in response to diseases and drugs, aiding our understanding of disease and drug mechanisms\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. In recent years, miRNA research has made significant progress, and miRNA has gradually become an important tool for studying gene expression regulation, drug mechanism research, and functional analysis\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Network pharmacology is emerging as a common method for predicting potential targets and molecular mechanisms of drugs or compounds in the treatment of diseases\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Additionally, molecular docking can calculate ligand-receptor binding energy to assess the binding capacity and relevance of ligands to receptors\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. In our study, we integrated transcriptomics, miRNA analysis, network pharmacology, and molecular docking to identify the central genes, core proteins, key pathways, and regulatory networks through which Alisol B 23-acetate acts on MM cells, revealing the potential molecular mechanisms by which Alisol B 23-acetate participates in the inhibition of MM. Furthermore, we validated these central targets and pathways in vitro experiments.\u003c/p\u003e\u003cp\u003eThe Mitogen-Activated Protein Kinase (MAPK) signaling pathway is intricately linked to apoptosis, playing a dual role in either promoting or inhibiting cell death, depending on the cell type and stimulatory conditions\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. The MAPK pathway is composed of three primary families: Extracellular Signal-Regulated Kinases (ERK), c-Jun N-terminal Kinases (JNK), and P38MAPK\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e.In the context of cancer cells, inhibitors of the ERK pathway can enhance the pro-apoptotic effects of chemotherapeutic drugs. This is because activated ERK is often associated with cell survival and proliferation, and its inhibition can sensitize cancer cells to apoptosis induced by chemotherapy \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. The JNK pathway, when activated, can promote apoptosis through the activation of Caspases, which are central executioners in the apoptotic process\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. On the other hand, the inhibition of P38MAPK can regulate the balance of Bcl2 family proteins, activating pro-apoptotic Bax while suppressing the activity of anti-apoptotic Bcl2, leading to cell apoptosis\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e.Thus, the MAPK signaling pathway, through its various kinase family members, exerts a complex influence on apoptosis, with the specific outcome being contingent upon the cellular context and the nature of the stimuli applied.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eMain material\u003c/p\u003e\u003cp\u003eThe multiple myeloma cell line MM.1S was derived from lymphoblasts in the peripheral blood of a 42-year-old female patient with myeloma. MM.1S, human peripheral blood mononuclear cells PBMC and lymphoma cell line DOHH2 were purchased from MeisenCTCC (China), and the cell lines were detected using the Mycoplasma detection kit to confirm that there was no mycoplasma contamination before the next experiment. Alisol B 23-acetate (the purity\u0026thinsp;\u0026gt;\u0026thinsp;98%)and bortezomib (the purity\u0026thinsp;\u0026gt;\u0026thinsp;99%) was purchased from MedChemExpress (China).Ethical approval was obtained from the Ethics Committee of Zhejiang Xiaoshan Hospital (Approval No. EC-2024062503). This research was conducted in accordance with the principles of the Declaration of Helsinki. All participants provided informed consent prior to their involvement in the study.\u003c/p\u003e\u003cp\u003emRNA analysis\u003c/p\u003e\u003cp\u003eFrom the Gene Expression Omnibus (GEO) database, we curated the MM dataset GSE16558, utilizing 17 MM plasma cell samples as the experimental group and 5 normal plasma cell samples as the control group. The dataset platform is GPL6244. The acquired data and matrices were read and processed using R software version 4.3.1. Following sample stratification, the limma package version 3.49.4 was employed to screen for differentially expressed genes (DEGs) within the dataset, with a threshold set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log2FoldChange| \u0026gt;1. The identified DEGs were visualized using the ggplot2 package. Subsequently, the DEGs were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis using the \"clusterProfiler\" package in R programming language, with data visualization. The filtering criteria for enrichment analysis was \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and the top 10 GO terms were selected, encompassing biological processes (BP), cellular component (CC), and molecular function (MF), as well as the top 20 KEGG pathways.\u003c/p\u003e\u003cp\u003eDrug prediction\u003c/p\u003e\u003cp\u003eWe employed EpiMed, connectivity maps, and the L1000 platform for drug prediction\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. EpiMed, an original drug prediction platform developed by our research team based on the principle of correcting aberrant gene expression levels, encompasses cellular expression profile data for small molecule chemical drugs and active components of traditional Chinese medicine\u003csup\u003e[\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. By comparing gene expression profiles, it reveals potential associations between drugs, genes, and diseases. Utilizing the gene expression profiles of diseases as input data, and leveraging the drug expression profile data within this platform, in conjunction with connectivity maps and the L1000 platform, we can predict potential therapeutic drugs and their targets.\u003c/p\u003e\u003cp\u003emiRNA analysis\u003c/p\u003e\u003cp\u003eDataset GSE16558 was curated from the GEO, comprising 17 MM plasma cell samples as the experimental group and 5 normal plasma cell samples as the control group. The platform for this dataset is GPL6244. The data and matrices were read and processed using R software version 4.3.1. After stratification, the limma package version 3.49.4 was applied to screen for differentially expressed miRNAs (DEmiRNAs) within the dataset, with a threshold of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log2FoldChange| \u0026gt;1. Target genes of DEmiRNAs were identified using the mirDB, miRTarbase, and TargetScan databases. The intersection of targets predicted by upregulated and downregulated miRNAs was determined, and any overlapping target genes between the downregulated and upregulated miRNAs were eliminated, resulting in a refined list of target genes for DEmiRNAs. Subsequently, the \"clusterProfiler\" package within the R programming language was utilized to conduct GO enrichment and KEGG pathway enrichment analyses.\u003c/p\u003e\u003cp\u003eNetwork pharmacology analysis\u003c/p\u003e\u003cp\u003eUsing \"Alisol B 23-acetate\" as the keyword, we collected relevant targets of Alisol B 23-acetate from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://tcmspw.com/tcmsp.php\u003c/span\u003e\u003cspan address=\"http://tcmspw.com/tcmsp.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Subsequently, the 2D structure of Alisol B 23-acetate was obtained by entering the compound into the PubChem database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and this structure was uploaded to both the pharmMapper database and the Swiss Target Prediction database to predict the targets of Alisol B 23-acetate. The targets identified from these three databases were consolidated, and duplicates were removed to establish the final set of targets for Alisol B 23-acetate. The UniProt database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.uniprot.org/\u003c/span\u003e\u003cspan address=\"http://www.uniprot.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was then utilized to standardize the gene names of the targets of Alisol B 23-acetate.With \"Multiple myeloma\" as the keyword, we mined potential targets associated with MM from the GeneCards database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genecards.org/\u003c/span\u003e\u003cspan address=\"https://www.genecards.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), DisGeNET database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.disgenet.org/\u003c/span\u003e\u003cspan address=\"https://www.disgenet.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and OMIM database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://go.drugbank.com/\u003c/span\u003e\u003cspan address=\"https://go.drugbank.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). After merging targets from these three databases and removing duplicates, we used the Venny 2.1.0 online platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioinfogp.cnb.csic.es/\u003c/span\u003e\u003cspan address=\"https://bioinfogp.cnb.csic.es/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to find the intersection of effective targets of Alisol B 23-acetate and MM. The intersecting targets are considered the relevant target genes regulated by Alisol B 23-acetate in MM. The R 4.3.1 software with the ClusterProfiler package was used to perform GO functional enrichment and KEGG pathway enrichment analyses on the intersecting targets.The intersecting targets were imported into the STRING database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://string-db.org/\u003c/span\u003e\u003cspan address=\"https://string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to construct a protein-protein interaction (PPI) network for the common targets of Alisol B 23-acetate and MM. Further in-depth analysis of the PPI network was conducted using Cytoscape_v3.10.2 software, and key targets regulated by Alisol B 23-acetate in MM were identified based on the degree.\u003c/p\u003e\u003cp\u003eIntegrated Analysis of mRNA, miRNA, and Network Pharmacology\u003c/p\u003e\u003cp\u003eWe integrated the DEGs and the targets of DEmiRNAs identified through mRNA and miRNA analyses, along with the targets regulated by Alisol B 23-acetate in MM, as determined by network pharmacology. By taking the intersection of these datasets, we identified the key targets of Alisol B 23-acetate in MM that exhibit enhanced effects. Furthermore, we integrated the KEGG-enriched pathways of the DEGs, DEmiRNA targets, and Alisol B 23-acetate-regulated targets in MM. By taking the intersection of these pathways, we identified the key pathways through which Alisol B 23-acetate exerts its enhanced effects on MM.\u003c/p\u003e\u003cp\u003eMolecular docking\u003c/p\u003e\u003cp\u003eWe employed CB-Dock (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://cao.labshare.cn/cb-dock/\u003c/span\u003e\u003cspan address=\"http://cao.labshare.cn/cb-dock/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for molecular docking to predict the binding affinity of Alisol B 23-acetate with its core targets. CB-Dock is a molecular docking tool based on AutoDock Vina that can automatically identify the binding sites of a ligand with a receptor and analyze the central location and size of the binding site\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. The protein and ligand files were obtained from the Protein Data Bank (PDB) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.rcsb.org/\u003c/span\u003e\u003cspan address=\"https://www.rcsb.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and PubChem (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), respectively\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Additionally, Ligand Scout software was utilized to analyze the 3D structural features of the drug ligand compound, generating a pharmacophore model to elucidate the interaction patterns between the drug ligand and protein receptor\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eCCK-8 assay\u003c/p\u003e\u003cp\u003ePBMCs, MM.1S cells, and DOHH2 cells were seeded into 96-well plates and cultured overnight. Subsequently, the cultures were treated with varying concentrations of Alisol B 23-acetate (0\u0026micro;M, 5\u0026micro;M, 10\u0026micro;M, 20\u0026micro;M, 40\u0026micro;M, 80\u0026micro;M, 120\u0026micro;M, 160\u0026micro;M) and bortezomib (BZT) ( 0nM, 1nM, 2nM, 4nM, 8nM, 16nM, 32nM, 64nM), each in 100\u0026micro;L of culture medium, for durations of 24 and 48 hours.According to the protocol provided by the Cell Counting Kit-8 (CCK-8) (Dojindo, Japan), 10\u0026micro;L of CCK-8 solution was added to each well, and the 96-well plates were incubated at 37℃ for 2 hours. The absorbance was measured using a microplate reader (Thermo, USA) at 450 nm to determine the optical density (OD) values. The results were normalized against the negative control group, and the half-maximal inhibitory concentration (IC50) was calculated.\u003c/p\u003e\u003cp\u003eCell cycle analysis\u003c/p\u003e\u003cp\u003eAfter treating MM.1S cells with 15\u0026micro;M Alisol B 23-acetate for 24 hours, both the treated and control groups were collected and fixed in 70% cold ethanol. The cells were then stained with a PI-RNase solution (1 mg/mL PI, 0.1% V/V Triton X-100, and 10 mg/mL RNase), and the acquired data were analyzed using FlowJo software.\u003c/p\u003e\u003cp\u003eCell apoptosis detection\u003c/p\u003e\u003cp\u003eMM.1S cells treated with 15 \u0026micro;M Alisol B 23-acetate and the corresponding control group were cultured at 37℃ in a 5% CO2 environment for 24 hours. Subsequently, the cells were collected, washed with cold PBS, and stained with Annexin FITC and PI using an apoptosis detection kit (Solarbio, China) according to the manufacturer's instructions. Apoptosis rates of MM.1S cells were then analyzed using the FACSCalibur and FACSMelody cytometry systems (BD Biosciences).\u003c/p\u003e\u003cp\u003eQuantitative real-time PCR analysis\u003c/p\u003e\u003cp\u003eTotal RNA was extracted from MM.1S cells using an RNA extraction kit (Vazyme, China). The purity of the extracted RNA was determined by measuring the A260/A280 ratio with a NanoDrop spectrophotometer (Thermo, USA), where a value between 1.8 and 2.0 indicates a pure RNA preparation. Complementary DNA (cDNA) was synthesized using a thermal cycler (Thermo, USA) and a first-strand cDNA synthesis kit (Thermo, USA). Quantitative analysis was performed using the SYBR Premix Ex Taq Kit (TaKaRa, Japan) and a real-time quantitative PCR (qRT-PCR) system (Thermo, USA), following the manufacturer's instructions. Primers used in the reactions are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e.Primers for qRT-PCR analysis.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimer\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003esequences(5'to3')\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBax-Forward:\u003c/p\u003e\u003cp\u003eBax-Reverse:\u003c/p\u003e\u003cp\u003eBcl2-Forward:\u003c/p\u003e\u003cp\u003eBcl2-Reverse:\u003c/p\u003e\u003cp\u003eP38-Forward:\u003c/p\u003e\u003cp\u003eP38-Reverse:\u003c/p\u003e\u003cp\u003eGAPDH-Forward:\u003c/p\u003e\u003cp\u003eGAPDH-Reverse:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTCTCCCCGAGAGGTCTTTTT\u003c/p\u003e\u003cp\u003eTGATGGTCCTGATCAACTCG\u003c/p\u003e\u003cp\u003eATGTGTGTGGAGAGCGTCAA\u003c/p\u003e\u003cp\u003eCTAGGGCCATACAGCTCCAC\u003c/p\u003e\u003cp\u003eAGCTGTTGACCGGAAGAA\u003c/p\u003e\u003cp\u003eGGGCCAGAGACTGAATGTA\u003c/p\u003e\u003cp\u003eACCACAGTCCATGCCATCAC\u003c/p\u003e\u003cp\u003eTCCACCACCCTGTTGCTGTA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWestern blot analysis\u003c/p\u003e\u003cp\u003eFollowing drug treatment, The cellular protein was extracted by lysing the cells in RIPA buffer\u003c/p\u003e\u003cp\u003e(Aidlab, China) supplemented with phosphatase and protease inhibitors, and PMSF inhibitors (Solarbio, China).The cell lysates were rotated at 4℃for 15 minutes, then centrifuged at 12,000 rpm for 10 minutes. The supernatant was collected and mixed with loading buffer, and the protein samples were denatured by boiling for 8 minutes. Protein concentrations were quantified using a BCA protein assay kit. The protein samples were separated by electrophoresis on SDS-PAGE and then electrotransferred onto PVDF membranes. The membranes were blocked with TBST containing 5% skim milk at room temperature for 2 hours, followed by incubation with primary antibodies against β-actin, P38, P-P38, Bcl2, and Bax overnight at 4℃. The membranes were then incubated with secondary antibodies for 2 hours, and the immunoreactive signals were detected using a chemiluminescent Fluor Chem FC3 system. The grayscale intensity of the target bands was quantified using Image J software. The antibody brands and configuration proportions used in WB are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e.Brand and configuration ratio of WB primary antibody\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eName\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBrand\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003econfiguration ratio\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBax\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbcam(USA)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1:1000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBcl2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbcam(USA)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1:1000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eproteintech(China)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1:1000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP-P38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProteintech(China)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1:1000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ-actin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbcam(USA)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1:2000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eResults of mRNA Analysis\u003c/p\u003e\u003cp\u003eResults from the mRNA analysis identified 928 differentially expressed genes, with 238 being upregulated and 690 downregulated (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log2FoldChange| \u0026gt;1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea-b). GO enrichment analysis indicated significant enrichment in biological processes such as immunoglobulin production and B cell receptor signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). KEGG pathway enrichment analysis revealed significant enrichment in pathways including the MAPK signaling pathway and B cell receptor signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eResults of drug prediction\u003c/p\u003e\u003cp\u003eBased on the differential analysis of MM gene expression profiles, utilizing the EpiMed, connectivity maps, and the L1000 platform, we have predicted the following traditional Chinese medicine active components as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Among them, Alisol B 23-Acetate shows the greatest negative correlation and has the potential to inhibit MM.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePrediction Results of Active Components from Traditional Chinese Medicine\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRank\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eName\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eType\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCorrelation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTarget\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003cp\u003e2\u003c/p\u003e\u003cp\u003e3\u003c/p\u003e\u003cp\u003e4\u003c/p\u003e\u003cp\u003e5\u003c/p\u003e\u003cp\u003e6\u003c/p\u003e\u003cp\u003e7\u003c/p\u003e\u003cp\u003e8\u003c/p\u003e\u003cp\u003e9\u003c/p\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAlisol B 23-Acetate\u003c/p\u003e\u003cp\u003eAstragaloside I\u003c/p\u003e\u003cp\u003eIrisflorentin\u003c/p\u003e\u003cp\u003eAmygdalin\u003c/p\u003e\u003cp\u003eGlycyrrhizic Acid\u003c/p\u003e\u003cp\u003eGinsenoside Rb3\u003c/p\u003e\u003cp\u003ePolydatin\u003c/p\u003e\u003cp\u003eNotoginsenoside R2\u003c/p\u003e\u003cp\u003eCurcumol\u003c/p\u003e\u003cp\u003eIcariin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHerb\u003c/p\u003e\u003cp\u003eHerb\u003c/p\u003e\u003cp\u003eHerb\u003c/p\u003e\u003cp\u003eHerb\u003c/p\u003e\u003cp\u003eHerb\u003c/p\u003e\u003cp\u003eHerb\u003c/p\u003e\u003cp\u003eHerb\u003c/p\u003e\u003cp\u003eHerb\u003c/p\u003e\u003cp\u003eHerb\u003c/p\u003e\u003cp\u003eHerb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.730734014\u003c/p\u003e\u003cp\u003e-0.711288711\u003c/p\u003e\u003cp\u003e-0.700218457\u003c/p\u003e\u003cp\u003e-0.698648421\u003c/p\u003e\u003cp\u003e-0.680108771\u003c/p\u003e\u003cp\u003e-0.659227921\u003c/p\u003e\u003cp\u003e-0.643997512\u003c/p\u003e\u003cp\u003e-0.643085293\u003c/p\u003e\u003cp\u003e-0.637254902\u003c/p\u003e\u003cp\u003e-0.631864741\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eVIM,JUND,MAPK14,DDIT3,GPNMB,EGR1,SQLE,PDK4,DIS3,NCF2,et al.\u003c/p\u003e\u003cp\u003eZC3H6,TMEM173,NOC3L,RND3,RARS,TRAPPC6B,TUBD1,LTN1,CRISP3,TTC3,et al.\u003c/p\u003e\u003cp\u003eRND3,ZNF860,ATP6V1C1,NFE2L2,MORC3,SUCLA2,PDCD4,NEDD9,VIM,ZNF570et al.\u003c/p\u003e\u003cp\u003eVIM,RRP12,MYB,ZFP62,EGR1,CD24,CD36,SOS1,NIPBL,CHD9,et al.\u003c/p\u003e\u003cp\u003eRND3,VIM,MYB,ZBTB10,LTN1,RRP12,TOP2B,TTC3,SEC62,UFL1,et al.\u003c/p\u003e\u003cp\u003eOGT,LYST,BRCA2,PHIP,EML5,INTS2,UBR5,CHD9,RIF1,ATRX,et al.\u003c/p\u003e\u003cp\u003eESF1,CWC22,ZNF83,CLK4,ZC3H13,ZNF248,ESCO1,ATM,SOCS3,EMP1,et al.\u003c/p\u003e\u003cp\u003eBRWD3,CEACAM6,DICER1,PHIP,UBR5,LYST,INTS2,TTC3,CNOT1,MYCBP2,et al.\u003c/p\u003e\u003cp\u003eTEAD1,DEK,MPHOSPH9,KNTC1,PUS7L,KLF9,ZNF146,XPO1,SUPT20H,SOS2,et al.\u003c/p\u003e\u003cp\u003eBRCA2,FRYL,PHIP,CNOT1,MYCBP2,CKAP5,UBR5,EML5,NUP160,RAD50,et al.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eResults of miRNA Analysis\u003c/p\u003e\u003cp\u003emiRNA Analysis Yields 20 DEmiRNAs, with 11 Upregulated and 9 Downregulated. A total of 20 DEmiRNAs were identified, consisting of 11 upregulated and 9 downregulated miRNAs(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-b). The upregulated miRNAs targeted 1244 genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec), while the downregulated miRNAs targeted 1160 genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). After removing the overlapping genes targeted by both upregulated and downregulated miRNAs, a final set of 2404 DEmiRNA target genes was obtained. GO enrichment analysis of these target genes revealed significant enrichment in biological processes such as miRNA metabolic processes, miRNA transcriptional regulation, and response to hypoxia (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). KEGG pathway enrichment analysis particularly highlighted the MAPK signaling pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eResults of network pharmacology analysis\u003c/p\u003e\u003cp\u003eNetwork pharmacology analysis identified 100 drug targets and 1931 disease targets, with an intersection of 31 targets common to both (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). PPI core protein screening revealed MAPK14 (also known as P38), JAK1, MAPK1, and others (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb-c). GO enrichment highlighted molecular functions such as serine and threonine kinase activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed), and KEGG pathway enrichment analysis showed significant enrichment in pathways including Proteoglycans in cancer and the MAPK signaling pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIntegrated analysis of mRNA, miRNA and Network Pharmacology\u003c/p\u003e\u003cp\u003eUpon integrating the results from mRNA, miRNA, and network pharmacology analyses, we discovered that the KEGG pathway enrichment results from all three datasets converged on two common pathways: the MAPK signaling pathway and the FoxO signaling pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). The MAPK signaling pathway exhibited a lower \u003cem\u003eP\u003c/em\u003e-value and a greater number of enriched genes. Concurrently, there was a single common target, MAPK14, identified at the intersection of differential mRNA genes, target genes of DEmiRNAs, and the intersection of drug and disease targets from network pharmacology analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). This target is also included among the core targets identified in the network pharmacology PPI analysis. Moreover, P38, which is encoded by the MAPK14 gene, is a critical hub in the P38 MAPK pathway.\u003c/p\u003e\u003cp\u003eResults of molecular docking\u003c/p\u003e\u003cp\u003eTo preliminarily predict the binding efficacy of Alisol B 23-acetate with MAPK14, we employed molecular docking to assess the binding energy score between them. The lower the binding energy score, the more effective and stable the binding of the ligand to the receptor. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec displays the optimal docking conformation of Alisol B 23-acetate with MAPK14. The molecular docking results indicate that Alisol B 23-acetate has a binding energy of -9.7 kcal/mol with MAPK14, suggesting a strong binding affinity. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed illustrates the structure of the Alisol B 23-acetate ligand, its position within the binding pocket, and the pharmacophore features. The Alisol B 23-acetate ligand forms hydrogen bond donors with threonine 106, aspartic acid 168, and asparagine 115 of the MAPK14 receptor, and a hydrogen bond acceptor with serine 154.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAlisol B 23-acetate Inhibits the Proliferation of Multiple Myeloma Cells\u003c/p\u003e\u003cp\u003eTo assess the impact of Alisol B 23-acetate on the proliferation of MM.1S cells, the CCK-8 assay was employed to evaluate cell viability. As shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-d, the calculated IC50 values for Alisol B 23-acetate in MM.1S cells were 14.24 \u0026micro;M at 24 hours and 15.18 \u0026micro;M at 48 hours, while the IC50 values for bortezomib (BZT) were 6.46 nM at 24 hours and 5.22 nM at 48 hours. At the 24-hour IC50 concentration, the inhibition rates of Alisol B 23-acetate and BZT on PBMCs were 1.3% and 3.7%, respectively, and at 48 hours, these rates were 2.6% and 4.3%, respectively. In order to initially explore the selectivity of Alisol B 23-acetate for MM, our experiments were also carried out in lymphoma cell lines. The results showed that in DOHH2, the IC50 of Alisol B 23-acetate was 24.64\u0026micro;M at 24 h and 26.12\u0026micro;M at 48 h, and the IC50 of Alisol B 23-acetate was 26.12\u0026micro;M at 48 h. The IC50 of BZT was 43.32nM at 24h and 48.72nM at 48h. Compared to untreated MM.1S cells, Alisol B 23-acetate significantly inhibited the proliferative capacity of MM.1S cells. Alisol B 23-acetate exhibited a significantly higher inhibition rate against MM.1S than against DOHH2, showing a certain degree of selectivity for MM.1S. At the IC50 concentration, Alisol B 23-acetate demonstrated a lower inhibition rate on PBMCs compared to BZT, indicating lower toxicity than BZT.\u003c/p\u003e\u003cp\u003eAlisol B 23-Acetate Promotes Apoptosis in Multiple Myeloma Cells\u003c/p\u003e\u003cp\u003eWe evaluated the effects of Alisol B 23-acetate on the cell cycle and induction of apoptosis in MM.1S cells using flow cytometry. Cell cycle analysis revealed that, compared to the control group, the percentage of cells in the G0/G1 phase (resting/before DNA synthesis) was increased, while the percentage in the S/G2 phase (DNA replication/after DNA synthesis) was decreased in the Alisol B 23-acetate treated group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee-g). Apoptosis results indicated that Alisol B 23-acetate significantly enhanced apoptosis in MM.1S cells, with the sum of Q2 and Q3, representing apoptotic cells, reaching 57.3% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eh-j). These data suggest that Alisol B 23-acetate promotes apoptosis in MM.1S cells and slows the transition of cells from the G1 phase to the S phase.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAlisol B 23-Acetate Inhibition of the P38MAPK Pathway\u003c/p\u003e\u003cp\u003eTo determine the mechanism by which Alisol B 23-acetate induces apoptosis in MM.1S cells through the inhibition of the P38MAPK pathway, we utilized qRT-PCR to assess the expression of apoptotic genes and P38 in MM.1S cells. MM.1S cells were treated with 15 \u0026micro;M Alisol B 23-acetate for 24 hours, after which they were lysed and RNA was extracted for qRT-PCR analysis. The results indicate that Alisol B 23-acetate increased the expression of the pro-apoptotic gene Bax (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ek), decreased the expression of the anti-apoptotic gene Bcl2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003el), while the expression of the P38 gene remained essentially unchanged (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003em).\u003c/p\u003e\u003cp\u003eWe further examined the expression changes of apoptotic genes and P38 at the protein level in MM.1S cells treated with Alisol B 23-acetate using western blotting. In MM.1S cells treated with Alisol B 23-acetate, the expression of the anti-apoptotic protein Bcl2 was decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea), while the expression of the pro-apoptotic protein Bax was increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). We also observed a reduction in P38 protein phosphorylation in MM.1S cells treated with Alisol B 23-acetate (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). Additionally, the Bcl2/Bax ratio and the ratio of P38 protein phosphorylation in Alisol B 23-acetate treated MM.1S cells were more significantly decreased compared to DOHH2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec-d), and in Alisol B 23-acetate treated DOHH2, the ratio of P38 protein phosphorylation remained essentially unchanged (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed). In Alisol B 23-acetate treated MM.1S cells, the decrease in the Bcl2/Bax ratio was slightly less compared to bortezomib (BZT) treated MM.1S (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee), and the ratio of P38 protein phosphorylation significantly decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ef), while in BZT treated MM.1S, the ratio of P38 protein phosphorylation remained essentially unchanged (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ef). In PBMCs, neither Alisol B 23-acetate nor BZT treatment resulted in significant changes in the Bcl2/Bax ratio or the ratio of P38 protein phosphorylation (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee-f). These results suggest that Alisol B 23-acetate induces apoptosis in MM.1S cells by inhibiting the phosphorylation of the core target P38 protein in the P38MAPK pathway.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we utilized gene expression profiling data from MM to predict drugs and then integrated this with miRNA data and network pharmacology from the same dataset to determine the key pathways and nodes involved in the antitumor effects of the drugs. Our data indicate that Alisol B 23-acetate has a cytotoxic effect on MM.1S cells. Treatment with Alisol B 23-acetate can significantly inhibit the proliferation of MM.1S cells and promote apoptosis through the Bcl-2/Bax and P38MAPK signaling pathways. Moreover, Alisol B 23-acetate has almost no inhibitory effect on normal human PBMC and exhibits significantly lower inhibitory activity against the lymphoma cell line DOHH2 compared with MM. This indicates that Alisol B 23-acetate has low toxicity while showing certain selectivity for MM. Additionally, Alisol B 23-acetate does not inhibit the P38MAPK signaling pathway in PBMC and DOHH2.\u003c/p\u003e\u003cp\u003eMM is an incurable hematological malignancy that eventually recurs and leads to the death of the vast majority of patients\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Despite the availability of various new drugs for treatment, many MM patients achieve disease control and improved quality of life, but a significant number still progress to RRMM, which has a poor clinical outcome\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. For RRMM patients, chimeric antigen receptor T (CAR-T) cell therapy has demonstrated promising efficacy and safety. While significant advancements have been made in the field of CAR-T therapy, challenges such as antigen escape and therapeutic resistance remain\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Therefore, there is an urgent need to develop effective therapeutic agents with fewer side effects. Based on previous studies, we have predicted that Alisol B 23-acetate has a certain potential for the treatment of MM, but it still needs further discussion and verification.\u003c/p\u003e\u003cp\u003eAlisol B 23-acetate is a natural triterpenoid compound from the rhizome of the Chinese herb Alisma orientale, which has been reported to have excellent biological activities, including anti-inflammatory, antibacterial, and anti-proliferation \u003csup\u003e[\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Modern pharmacological studies have shown that Alisol B 23-acetate can exhibit good anti-tumor properties by affecting the MAPK signaling pathway \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. In one study, Alisol B 23-acetate inhibited the activation of the MAPK pathway in gastric cancer cells, resulting in cell cycle arrest and mitochondrial pathway induced cell apoptosis, accompanied by MAPK signaling cascades and reduced phosphorylation of P38, ERK and JNK \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. Another study showed that the intervention of Alisol B 23-acetate in mice with colon cancer resulted in a significant reduction in MAPK activation and a significant reduction in the phosphorylation of p38, ERK and JNK \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. However, the effects of Alisol B 23-acetate on MM and the underlying mechanisms remain unclear.\u003c/p\u003e\u003cp\u003eIn the present study, it was found that Alisol B 23-acetate inhibited the proliferation of MM cells in a dose-dependent manner, and the IC50 value of MM cells was significantly reduced after 24h and 48h of treatment with Alisol B 23-acetate. In addition, Alisol B 23-acetate was not significantly toxic to PBMC, which maintained high cell viability even at higher doses. Meanwhile, the inhibitory effect of Alisol B 23-acetate on lymphoma DOHH2 cells is significantly lower than that on MM cells. Alisol B 23-acetate selectively inhibits the proliferation of MM cells and has low toxicity on normal cells, which has potential therapeutic value. Through the comprehensive analysis of mRNA, miRNA and network pharmacology, we found that Alisol B 23-acetate acted on the key pathway of MM, P38MAPK signaling pathway, and the key target, P38, suggesting that Alisol B 23-acetate may play an important role in the pathogenesis of MM. Based on these analysis results, our study validated the effects of Alisol B 23-acetate on MM cell apoptosis, cell proliferation, cell cycle regulation and P38MAPK signaling pathway.\u003c/p\u003e\u003cp\u003eApoptosis maintains physiological balance and eliminates cancer cells in response to external stimuli, such as small molecule drugs \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. Apoptosis pathways can be divided into exogenous and endogenous pathways \u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Upon stimulation, Bcl-2 family proteins activate MMPs, leading to the release of cytochrome c from mitochondria into the cytoplasm, which triggers the release of the caspase cascade. Through this series of effects, it will lead to cell apoptosis \u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. In the experiments, we found that Alisol B 23-acetate inhibited the expression of Bcl-2 and increased the level of Bcl-2, indicating that Alisol B 23-acetate was involved in the endogenous apoptotic pathway. The significant increase in Bax and decrease in Bcl-2 levels in MM.1S cells treated with 15 \u0026micro;M Alisol B 23-acetate highlight the role of Alisol B 23-acetate in inducing apoptosis through the endogenous pathway. Bcl-2 and Bax are important markers of apoptosis \u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. Reduced Bcl-2 levels and increased Bax levels mark the activation of the endogenous apoptotic pathway, confirming the role of Alisol B 23-acetate in the induction of apoptosis.\u003c/p\u003e\u003cp\u003eOur results showed that Alisol B 23-acetate could induce significant cell cycle arrest in G0/G1 phase of MM cells. The G0/G1 phase is a critical phase in the cell cycle where cells decide whether to continue dividing or enter quiescence \u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. Alisol B 23-acetate is able to interfere with this process, especially the arrest in the G0/G1 phase, which is normally a cellular defense response to stress or injury. When a cell is stressed or injured, it usually stops its cycle progression to allow enough time for repair or to wait for further signals. If this damage cannot be repaired, cells may choose to initiate programmed death or enter a state of senescence \u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. The G0/G1 phase arrest induced by Alisol B 23-acetate suggests that the drug may inhibit further proliferation by activating the stress response mechanism of the cells and preventing them from entering the S phase. Secondly, Alisol B 23-acetate may also act by inhibiting the expression and activity of specific cell cycle proteins in G1 phase, such as D1/D3 \u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e. These cyclins are key regulators required for cells to transition from G1 to S phase \u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e. Alisol B 23-acetate effectively prevents cells from entering S phase by reducing the levels of these proteins and preventing their binding to cell cycle-dependent kinase (CDK4/6) \u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eP38MAPK signaling pathway plays a crucial role in the pathogenesis of MM \u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e.P38 is a member of the MAPK family, which plays a crucial role in cellular activities such as the cell cycle, apoptosis, and autophagy\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e. The MAPK family consists of three major subgroups and their respective pathways: P38, ERK, and JNK\u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e. Despite the diversity in function and upstream signaling events, MAPKs are activated by a highly conserved mechanism involving the phosphorylation of threonine and tyrosine residues catalyzed by MAPK kinases\u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn a study, Alisol B 23-acetate was found to inhibit the activation of the MAPK pathway in gastric cancer cells, leading to cell cycle arrest and the induction of apoptosis via the mitochondrial pathway, accompanied by a decrease in the phosphorylation of P38, ERK, and JNK within the MAPK signaling cascade\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Another study demonstrated that the intervention of Alisol B 23-acetate in a mouse model of colon cancer resulted in a significant reduction in the activation of the MAPK pathway, with a notable decrease in the phosphorylation of p38, ERK, and JNK\u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn a study, it was discovered that P38MAPK inhibitors can enhance the sensitivity of MM cells to bortezomib, Hsp90 inhibitors, and dexamethasone, thereby augmenting their cytotoxic effects on MM cells\u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e. Another study indicated that P38MAPK is constitutively activated in MM, and high expression of its primary substrate, MAPKAPK2 (MK2), is associated with poorer prognosis in MM patients, with MK2 inhibitors capable of suppressing MM cell growth and colony formation\u003csup\u003e[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/sup\u003e. Furthermore, a clinical study demonstrated that the activation of the MAPK pathway has a negative impact on the prognosis of MM patients\u003csup\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn this study, we have unveiled the antitumor effects of Alisol B 23-acetate on MM and its impact on the key signaling pathway, the P38MAPK pathway, providing a foundation for the development of new therapeutic strategies and potential for improving the prognosis of patients with RRMM. However, although our data provide experimental evidence that Alisol B 23-acetate has an anti-MM effect by inhibiting the P38MAPK signaling pathway, it is still necessary to further clarify the mechanism of Alisol B 23-acetate through P38MAPK pathway inhibitors. And to verify the validity of these findings in mammalian models.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eNational Key Research and Development Program of China(2021YFC2701703)\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eHui Zhang made contributions to article writing, bioinformatics analysis, conducting experiments, and data analysis. Jie Geng and Peng Zhao provided guidance in bioinformatics. Yuntao Zhu and Xuechun Lu contributed to revising the manuscript.All authors have reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eWe appreciated the contributions made by all authors.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe supporting data for the conclusions drawn in this research can be accessed within the methods section or supplementary materials provided alongside this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMalard, F. et al. Multiple myeloma. \u003cem\u003eNat. Rev. Dis. Primers\u003c/em\u003e. \u003cb\u003e10\u003c/b\u003e (1), 45. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41572-024-00529-7\u003c/span\u003e\u003cspan address=\"10.1038/s41572-024-00529-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024). Published 2024 Jun 27.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDimopoulos, M. A. et al. Multiple myeloma: EHA-ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. \u003cem\u003eAnn. Oncol.\u003c/em\u003e \u003cb\u003e32\u003c/b\u003e (3), 309\u0026ndash;322. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.annonc.2020.11.014\u003c/span\u003e\u003cspan address=\"10.1016/j.annonc.2020.11.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCaers, J. et al. European Myeloma Network recommendations on tools for the diagnosis and monitoring of multiple myeloma:what to use and when. \u003cem\u003eHaematologica\u003c/em\u003e \u003cb\u003e103\u003c/b\u003e (11), 1772\u0026ndash;1784. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3324/haematol.2018.189159\u003c/span\u003e\u003cspan address=\"10.3324/haematol.2018.189159\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYu, C. C. et al. Active Components of Traditional Chinese Medicinal Material for Multiple Myeloma: Current Evidence and Future Directions. \u003cem\u003eFront. Pharmacol.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e, 818179. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fphar.2022.818179\u003c/span\u003e\u003cspan address=\"10.3389/fphar.2022.818179\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022). Published 2022 Jan 27.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDu, Q. et al. Alisol B 23-acetate broadly inhibits coronavirus through blocking virus entry and suppresses proinflammatory T cells responses for the treatment of COVID-19. \u003cem\u003eJ. Adv. Res.\u003c/em\u003e \u003cb\u003e62\u003c/b\u003e, 273\u0026ndash;290. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jare.2023.10.002\u003c/span\u003e\u003cspan address=\"10.1016/j.jare.2023.10.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi, C. et al. Anti-bacterial effect of phytoconstituents isolated from Alimatis rhizoma. \u003cem\u003eAppl. Biol. Chem.\u003c/em\u003e \u003cb\u003e64\u003c/b\u003e, 9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13765-020-00583-1\u003c/span\u003e\u003cspan address=\"10.1186/s13765-020-00583-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXia, J. et al. Alisol B 23-acetate-induced HepG2 hepatoma cell death through mTOR signaling-initiated G1 cell cycle arrest and apoptosis: A quantitative proteomic study. \u003cem\u003eChin. J. Cancer Res.\u003c/em\u003e \u003cb\u003e31\u003c/b\u003e (2), 375\u0026ndash;388. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.21147/j.issn.1000-9604.2019.02.12\u003c/span\u003e\u003cspan address=\"10.21147/j.issn.1000-9604.2019.02.12\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu, Y. et al. Alisol B 23acetate inhibits the viability and induces apoptosis of nonsmall cell lung cancer cells via PI3K/AKT/mTOR signal pathway. \u003cem\u003eMol. Med. Rep.\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e (2), 1187\u0026ndash;1195. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3892/mmr.2019.10355\u003c/span\u003e\u003cspan address=\"10.3892/mmr.2019.10355\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXia, F. et al. Alisol B 23-Acetate Ameliorates Lipopolysaccharide-Induced Intestinal Barrier Dysfunction by Inhibiting TLR4-NOX1/ROS Signaling Pathway in Caco-2 Cells. \u003cem\u003eFront. Pharmacol.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e, 911196. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fphar.2022.911196\u003c/span\u003e\u003cspan address=\"10.3389/fphar.2022.911196\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022). Published 2022 Jun 14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKwon, M. J. et al. Apoptotic effects of alisol B 23acetate on gastric cancer cells. \u003cem\u003eMol. Med. Rep.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e (4), 248. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3892/mmr.2021.11887\u003c/span\u003e\u003cspan address=\"10.3892/mmr.2021.11887\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCerneckis, J. et al. The rise of epitranscriptomics: recent developments and future directions. \u003cem\u003eTrends Pharmacol. Sci.\u003c/em\u003e \u003cb\u003e45\u003c/b\u003e (1), 24\u0026ndash;38. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tips.2023.11.002\u003c/span\u003e\u003cspan address=\"10.1016/j.tips.2023.11.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShang, R. et al. microRNAs in action: biogenesis, function and regulation. \u003cem\u003eNat. Rev. Genet.\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e (12), 816\u0026ndash;833. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41576-023-00611-y\u003c/span\u003e\u003cspan address=\"10.1038/s41576-023-00611-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNogales, C. et al. Network pharmacology: curing causal mechanisms instead of treating symptoms. \u003cem\u003eTrends Pharmacol. Sci.\u003c/em\u003e \u003cb\u003e43\u003c/b\u003e (2), 136\u0026ndash;150. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tips.2021.11.004\u003c/span\u003e\u003cspan address=\"10.1016/j.tips.2021.11.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePaggi, J. M., Pandit, A. \u0026amp; Dror, R. O. The Art and Science of Molecular Docking. \u003cem\u003eAnnu. Rev. Biochem.\u003c/em\u003e \u003cb\u003e93\u003c/b\u003e (1), 389\u0026ndash;410. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1146/annurev-biochem-030222-120000\u003c/span\u003e\u003cspan address=\"10.1146/annurev-biochem-030222-120000\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang, W. \u0026amp; Liu, H. T. MAPK signal pathways in the regulation of cell proliferation in mammalian cells. \u003cem\u003eCell. Res.\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e (1), 9\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/sj.cr.7290105\u003c/span\u003e\u003cspan address=\"10.1038/sj.cr.7290105\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2002).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYuan, J., Dong, X., Yap, J. \u0026amp; Hu, J. The MAPK and AMPK signalings: interplay and implication in targeted cancer therapy. \u003cem\u003eJ. Hematol. Oncol.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e (1), 113. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13045-020-00949-4\u003c/span\u003e\u003cspan address=\"10.1186/s13045-020-00949-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020). Published 2020 Aug 17.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTang, X. et al. Combined intermittent fasting and ERK inhibition enhance the anti-tumor effects of chemotherapy via the GSK3β-SIRT7 axis. Nat Commun. ;12(1):5058. Published 2021 Aug 25. (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41467-021-25274-3\u003c/span\u003e\u003cspan address=\"10.1038/s41467-021-25274-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMahalingam, D. et al. Heightened JNK Activation and Reduced XIAP Levels Promote TRAIL and Sunitinib-Mediated Apoptosis in Colon Cancer Models. \u003cem\u003eCancers (Basel)\u003c/em\u003e. \u003cb\u003e11\u003c/b\u003e (7), 895. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/cancers11070895\u003c/span\u003e\u003cspan address=\"10.3390/cancers11070895\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019). Published 2019 Jun 26.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOwens, T. W. et al. Apoptosis commitment and activation of mitochondrial Bax during anoikis is regulated by p38MAPK. \u003cem\u003eCell. Death Differ.\u003c/em\u003e \u003cb\u003e16\u003c/b\u003e (11), 1551\u0026ndash;1562. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/cdd.2009.102\u003c/span\u003e\u003cspan address=\"10.1038/cdd.2009.102\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang, J. et al. Quantitative transcriptome-based analysis predicts a combination therapy for severe haemophilia B: A case report. \u003cem\u003eBr. J. Haematol.\u003c/em\u003e \u003cb\u003e204\u003c/b\u003e (3), 1105\u0026ndash;1108. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/bjh.19261\u003c/span\u003e\u003cspan address=\"10.1111/bjh.19261\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlharbi, H. et al. Identification of Potential Biomarkers and Pathways in Acute Myeloid Leukemia: Correlation Between the Calcineurin Signaling Pathway and Vascular Brittleness in Acute Myeloid Leukemia. \u003cem\u003eInt. J. Lab. Hematol. Published online Dec.\u003c/em\u003e \u003cb\u003e5\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/ijlh.14410\u003c/span\u003e\u003cspan address=\"10.1111/ijlh.14410\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang, J. D. et al. Zhongguo Shi Yan Xue Ye Xue Za Zhi. ;29(3):975\u0026ndash;982. (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.19746/j.cnki.issn.1009-2137.2021.03.051\u003c/span\u003e\u003cspan address=\"10.19746/j.cnki.issn.1009-2137.2021.03.051\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu, Y. et al. CB-Dock: a web server for cavity detection-guided protein-ligand blind docking. \u003cem\u003eActa Pharmacol. Sin\u003c/em\u003e. \u003cb\u003e41\u003c/b\u003e (1), 138\u0026ndash;144. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41401-019-0228-6\u003c/span\u003e\u003cspan address=\"10.1038/s41401-019-0228-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHappy anniversary, P. D. B. \u003cem\u003eNat. Struct. Mol. Biol.\u003c/em\u003e ;\u003cb\u003e28\u003c/b\u003e(5):399. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41594-021-00598-2\u003c/span\u003e\u003cspan address=\"10.1038/s41594-021-00598-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim, S. et al. PubChem in 2021: new data content and improved web interfaces. \u003cem\u003eNucleic Acids Res.\u003c/em\u003e \u003cb\u003e49\u003c/b\u003e (D1), D1388\u0026ndash;D1395. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/nar/gkaa971\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkaa971\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVuorinen, A. et al. Ligand-based pharmacophore modeling and virtual screening for the discovery of novel 17β-hydroxysteroid dehydrogenase 2 inhibitors. \u003cem\u003eJ. Med. Chem.\u003c/em\u003e \u003cb\u003e57\u003c/b\u003e (14), 5995\u0026ndash;6007. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1021/jm5004914\u003c/span\u003e\u003cspan address=\"10.1021/jm5004914\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan de Donk, N. W. C. J., Pawlyn, C. \u0026amp; Yong, K. L. Multiple myeloma. \u003cem\u003eLancet\u003c/em\u003e \u003cb\u003e397\u003c/b\u003e (10272), 410\u0026ndash;427. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(21)00135-5\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(21)00135-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eParikh, R. H. \u0026amp; Lonial, S. Chimeric antigen receptor T-cell therapy in multiple myeloma: A comprehensive review of current data and implications for clinical practice. \u003cem\u003eCA Cancer J. Clin.\u003c/em\u003e \u003cb\u003e73\u003c/b\u003e (3), 275\u0026ndash;285. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3322/caac.21771\u003c/span\u003e\u003cspan address=\"10.3322/caac.21771\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKwon, M. J. et al. Apoptotic effects of alisol B 23acetate on gastric cancer cells. \u003cem\u003eMol. Med. Rep.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e (4), 248 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu, H. C. et al. Alisol B 23-Acetate Ameliorates Azoxymethane/Dextran Sodium Sulfate-Induced Male Murine Colitis-Associated Colorectal Cancer via Modulating the Composition of Gut Microbiota and Improving Intestinal Barrier. \u003cem\u003eFront. Cell. Infect. Microbiol.\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e, 640225 (2021). Published 2021 Apr 29.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMorana, O. et al. The apoptosis paradox in cancer[J]. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e (3), 1328 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoldar, S. et al. Molecular mechanisms of apoptosis and roles in cancer development and treatment[J]. \u003cem\u003eAsian Pac. J. Cancer Prev.\u003c/em\u003e \u003cb\u003e16\u003c/b\u003e (6), 2129\u0026ndash;2144 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEskandari, E. et al. Paradoxical roles of caspase-3 in regulating cell survival, proliferation, and tumorigenesis[J]. \u003cem\u003eJ. Cell. Biol.\u003c/em\u003e \u003cb\u003e221\u003c/b\u003e (6), e202201159 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTettenborn, D. Toxicity of clotrimazole[J]. \u003cem\u003ePostgrad. Med. J.\u003c/em\u003e \u003cb\u003e50\u003c/b\u003e (1), 17\u0026ndash;20 (1974).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang, Z. et al. Cell Cycle Progression and Synchronization: An Overview. \u003cem\u003eMethods Mol. Biol.\u003c/em\u003e \u003cb\u003e66\u003c/b\u003e (12), 3\u0026ndash;23 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQie, S. et al. Cyclin D1, cancer progression, and opportunities in cancer treatment. \u003cem\u003eJ. Mol. Med. (Berl)\u003c/em\u003e. \u003cb\u003e66\u003c/b\u003e (12), 1313\u0026ndash;1326 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTchakarska, G. et al. The double dealing of cyclin D1. \u003cem\u003eCell. Cycle\u003c/em\u003e. \u003cb\u003e66\u003c/b\u003e (12), 163\u0026ndash;178 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMart\u0026iacute;nez-Lim\u0026oacute;n, A., Joaquin, M., Caballero, M., Posas, F. \u0026amp; de Nadal, E. The p38 Pathway: From Biology to Cancer Therapy. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e (6), 1913. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms21061913\u003c/span\u003e\u003cspan address=\"10.3390/ijms21061913\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020). Published 2020 Mar 11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBraicu, C. et al. A Comprehensive Review on MAPK: A Promising Therapeutic Target in Cancer. Cancers (Basel). ;11(10):1618. Published 2019 Oct 22. (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/cancers11101618\u003c/span\u003e\u003cspan address=\"10.3390/cancers11101618\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGonz\u0026aacute;lez-Rubio, G., Sellers-Moya, \u0026Aacute;., Mart\u0026iacute;n, H. \u0026amp; Molina, M. Differential Role of Threonine and Tyrosine Phosphorylation in the Activation and Activity of the Yeast MAPK Slt2. Int J Mol Sci. ;22(3):1110. Published 2021 Jan 23. (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms22031110\u003c/span\u003e\u003cspan address=\"10.3390/ijms22031110\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSui, X. et al. p38 and JNK MAPK pathways control the balance of apoptosis and autophagy in response to chemotherapeutic agents. \u003cem\u003eCancer Lett.\u003c/em\u003e \u003cb\u003e344\u003c/b\u003e (2), 174\u0026ndash;179. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.canlet.2013.11.019\u003c/span\u003e\u003cspan address=\"10.1016/j.canlet.2013.11.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYuan, W. et al. Modulating p38 MAPK signaling by proteostasis mechanisms supports tissue integrity during growth and aging. Nat Commun. ;14(1):4543. Published 2023 Jul 28. (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41467-023-40317-7\u003c/span\u003e\u003cspan address=\"10.1038/s41467-023-40317-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCanovas, B. \u0026amp; Nebreda, A. R. Diversity and versatility of p38 kinase signalling in health and disease. \u003cem\u003eNat. Rev. Mol. Cell. Biol.\u003c/em\u003e \u003cb\u003e22\u003c/b\u003e (5), 346\u0026ndash;366. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41580-020-00322-w\u003c/span\u003e\u003cspan address=\"10.1038/s41580-020-00322-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYasui, H. et al. BIRB 796 enhances cytotoxicity triggered by bortezomib, heat shock protein (Hsp) 90 inhibitor, and dexamethasone via inhibition of p38 mitogen-activated protein kinase/Hsp27 pathway in multiple myeloma cell lines and inhibits paracrine tumour growth. \u003cem\u003eBr. J. Haematol.\u003c/em\u003e \u003cb\u003e136\u003c/b\u003e (3), 414\u0026ndash;423. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1365-2141.2006.06443.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-2141.2006.06443.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGu, C. et al. MK2 is a therapeutic target for high-risk multiple myeloma. \u003cem\u003eHaematologica\u003c/em\u003e \u003cb\u003e106\u003c/b\u003e (6), 1774\u0026ndash;1777. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3324/haematol.2017.182121\u003c/span\u003e\u003cspan address=\"10.3324/haematol.2017.182121\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021). Published 2021 Jun 1.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePerroud, C. et al. Effect of MAPK activation via mutations in NRAS, KRAS and BRAF on clinical outcome in newly diagnosed multiple myeloma. \u003cem\u003eHematol. Oncol.\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e (5), 912\u0026ndash;921. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/hon.3208\u003c/span\u003e\u003cspan address=\"10.1002/hon.3208\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarris, M. H. \u0026amp; Thompson, C. B. The role of the Bcl-2 family in the regulation of outer mitochondrial membrane permeability. \u003cem\u003eCell. Death Differ.\u003c/em\u003e \u003cb\u003e7\u003c/b\u003e (12), 1182\u0026ndash;1191. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/sj.cdd.4400781\u003c/span\u003e\u003cspan address=\"10.1038/sj.cdd.4400781\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2000).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee, M. L. et al. KMUP-1 Ameliorates Ischemia-Induced Cardiomyocyte Apoptosis through the NO⁻cGMP⁻MAPK Signaling Pathways. Molecules. ;24(7):1376. Published 2019 Apr 8. (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/molecules24071376\u003c/span\u003e\u003cspan address=\"10.3390/molecules24071376\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Multiple Myeloma, MAPK, P38, Integrated analysis, Network pharmacology","lastPublishedDoi":"10.21203/rs.3.rs-6923004/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6923004/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAlisol B 23-acetate is a naturally occurring triterpenoid compound derived from the rhizome of the traditional Chinese medicinal herb Alisma orientale,which possesses a variety of physiological activities, including anti-cancer effects.However, its effects on human multiple myeloma (MM) and the underlying mechanisms remain to be elucidated. In this study, we employed an integrated analysis of mRNA, miRNA, and network pharmacology to investigate the role of Alisol B 23-acetate in MM and subsequently validated our findings with cellular experiments.Our data demonstrate that Alisol B 23-acetate treatment significantly suppresses MM cells via the P38MAPK signaling pathway. Specifically, the CCK-8 assay revealed that Alisol B 23-acetate inhibits the proliferation of MM cells, with an IC50 value of 14.24 \u0026micro;M after a 24-hour treatment. Cell cycle analysis indicated that Alisol B 23-acetate treatment increased the percentage of MM.1S cells in the G0/G1 phase (resting/before DNA synthesis) and decreased the proportion in the S/G2 phase (DNA replication/after DNA synthesis). Apoptosis assays showed that Alisol B 23-acetate significantly enhanced apoptosis in MM.1S cells, with the apoptotic cell population increasing to 57.3%. Quantitative real-time PCR (qRT-PCR) results indicated that Alisol B 23-acetate treatment downregulated the expression of the anti-apoptotic gene Bcl2 and upregulated the expression of the pro-apoptotic gene Bax in MM cells, while the expression of the P38 gene remained largely unchanged. Western blotting analysis further confirmed that Alisol B 23-acetate treatment reduced the expression of the anti-apoptotic protein Bcl2 and increased the expression of the pro-apoptotic protein Bax in MM cells, with a concomitant decrease in P38 protein phosphorylation.These findings suggest that Alisol B 23-acetate induces apoptosis in MM cells by inhibiting the phosphorylation of P38, a key target in the P38MAPK signaling pathway.\u003c/p\u003e","manuscriptTitle":"Unraveling the Anti-Multiple Myeloma Activity of Alisol B 23-Acetate and Its Impact on the P38MAPK Pathway Through Integrated Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-24 18:33:46","doi":"10.21203/rs.3.rs-6923004/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1d004b28-aea0-45ec-89ea-a0cce6ac21d8","owner":[],"postedDate":"July 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51918666,"name":"Biological sciences/Cancer/Haematological cancer/Myeloma"},{"id":51918667,"name":"Biological sciences/Drug discovery/Biomarkers"}],"tags":[],"updatedAt":"2026-02-19T16:25:42+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-24 18:33:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6923004","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6923004","identity":"rs-6923004","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}