Abstract Objective: Curcumae Rhizoma–Sparganii Rhizoma (CR-SR) is a traditional botanical drug pair that can promote blood circulation, remove blood stasis, and treat tumors in clinics. The aim of the present study was to investigate the therapeutic material basis and potential mechanisms of CR-SR, CR, and SR for the treatment of liver cancer. Method: The chemical profile analyses of CR-SR, CR, and SR were performed by molecular networking and UPLC-LTQ-Orbitrap MS^n. The anti-liver cancer activities of CR-SR, CR, and SR were assessed by using a zebrafish xenograft model in vivo for the first time and detected by the HepG2 cell model in vitro. Combining the network analysis and molecular docking, real-time quantitative polymerase chain reaction (RT-qPCR) experiments were undertaken to further explore the mechanisms of CR-SR, CR, and SR for the treatment of liver cancer. Results: In total, 65 components were identified in CR-SR, CR, and SR. Based on the clusters of molecular networking, a total of 12 novel diarylheptanoids were identified from CR-SR and CR. By combining our results with information from the literature, 32 sesquiterpenoids and 21 cyclic dipeptides were identified from CR-SR, CR, and SR. The anti-liver cancer activities were observed in both the drug pair and the single botanical drugs in vitro and in vivo, and the order of activity was CR-SR > CR > SR. They could downregulate the expression of proto-oncogene tyrosine-protein kinase Src (SRC), epidermal growth factor receptor (EGFR), estrogen receptor-α (ESR1), prostaglandin endoperoxide synthase 2 (PTGS2), and amyloid precursor protein (APP). Conclusion: Taken together, the present study provided an experimental basis for the therapeutic material basis and potential molecular mechanisms of CR-SR, CR, and SR. This study provided a novel insight for objective clinical treatment of liver cancer. Keywords: Curcumae Rhizoma - Sparganii Rhizoma , liver cancer, molecular networking, UPLC-LTQ-Orbitrap MS^n , zebrafish xenograft model 1 Introduction A drug pair in traditional Chinese medicine (TCM) refers to two botanical drugs that exhibit synergistic pharmaceutical and/or detoxification activities, playing an important role in the exploration of general botanical drug compatibility ([66]Wang et al., 2012; [67]Yu et al., 2019). The compatibility of CR and SR is a traditional drug pair for promoting blood circulation and removing blood stasis in clinics, which shows a tendency to reinforce each other ([68]Xu et al., 2015). According to traditional Chinese medicine, activating blood circulation and removing blood stasis could dredge the meridians, improve microcirculation, and adjust and strengthen immune function to dampen cancer and shrink the lump ([69]Lu and Li, 2009). Modern pharmacological studies have shown that the occurrence and development of tumors are related to angiogenesis and the abnormal blood coagulation system. The current research and clinical practice mostly focus on anti-liver cancer activities ([70]Xu et al., 2015). Our team has been committed to studying the anti-cancer activities of CR-SR, CR, and SR. The results showed their broad-spectrum anti-tumor activity in vitro. Also, the activity of the drug pair was better than the single drug ([71]Liu et al., 2021). The anti-liver cancer activity in vivo of CR-SR, CR, and SR is still obscure. Zebrafish have been widely used in tumor research because they have highly conserved oncogenes, tumor suppressor genes, and cell cycle regulatory genes with humans. The features of zebrafish in rapid cell division and delayed apoptosis in embryos are similar to those of human tumors ([72]Lu et al., 2011; [73]Shuo et al., 2018). Therefore, zebrafish can test activity evaluation and gene expression in mechanism research. The linear diarylheptanoids of CR-SR, CR, and SR were determined by the UPLC-MS method in previous research ([74]Chang et al., 2020). Molecular networking is a technique used for rapid and massive identification of known compounds, similar compounds, and discovering new compounds in recent years ([75]Le Daré et al., 2021; [76]Zhao et al., 2021). The combination of LC-MS and molecular networking can make the analysis of MS data less time-consuming and difficult. Network analysis is a very promising approach for finding potential drug targets ([77]Tao et al., 2013). Constructing a multi-level network through omics data analysis and computer simulation methods provides a new idea for the systematic research of the complex system of TCM ([78]Li and Zhang, 2013). Molecular docking is a method of designing drugs by simulating the interaction between receptors and drugs and plays an important role in revealing the mechanism of action between active components and body targets ([79]Yuan et al., 2021). It is a common strategy to explore the potential mechanism of action of drugs on diseases by combining network analysis and molecular docking. The introduction of molecular networking provided an opportunity to discover novel compounds in this study. The novel diarylheptanoids were deduced from a cluster of the network map structures of molecular networking. At the same time, the chemical components of CR-SR, CR, and SR water extracts were subjected to a comprehensive analysis. The cyclic dipeptide and sesquiterpenoid components were analyzed in detail using UPLC-LTQ-Orbitrap MS^n technology. The zebrafish xenograft HepG2 model was used for the first time to study the anti-liver cancer activities of CR-SR, CR, and SR in vivo, and the mechanism of action was explored by combining network pharmacology, molecular docking, and RT-qPCR technology. This study provided a solid foundation on the therapeutic material basis and mechanism of action for the anti-liver cancer activities of CR-SR, CR, and SR. A flow chart of the study process is shown in [80]Figure 1. FIGURE 1. [81]FIGURE 1 [82]Open in a new tab Flow chart of the study process. 2 Materials and methods 2.1 General experimental procedures The UPLC-MS was carried out on a Thermo Dionex UltiMate 3000 system (Thermo Fisher Scientific, United States ) using an Agilent XDB-C[18] column (4.6 × 150 mm, 3.6 μm) and a Thermo LTQ-Orbitrap Velos Pro Hybrid (Thermo Fisher Scientific, United States ) equipped with an ESI source operating in the auto-MS^n mode. Trichloromethane, isopropyl alcohol, and anhydrous ethanol were provided by Fuchen Chemical Reagent Co., Ltd. (Tianjin, China). NaCl, KCl, CaCl[2], NaHCO[3], Na[2]HPO[4], KH[2]PO[4], and MgSO[4].7H[2]O (analytical reagent grade) were purchased from Beijing Chemical Plant Co., Ltd. (Beijing, China). RPMI 1640 and fetal bovine serum (FBS) were ordered from Biological Industries. Pancreatin was obtained from Servicebio. Penicillin and streptomycin were purchased from Shanghai Yuanye Biotechnology Co., Ltd. (Beijing, China). Cell-Counting Kit-8 was purchased from LABLEAD. DiO fluorescent dye was purchased from Beyotime Biotechnology (Beyotime, China). The tissue Total RNA Isolation Kit, RNase free, 4 × gDNA wiper Mix, 5 × HiScript III qRT SuperMix, ChamQ SYBR Color qPCR Master Mix, and HiScript III-RT SuperMix for qPCR were purchased from Vazyme Biotech Co., Ltd. (Nanjing, China). 2.2 Plant material CR and SR were provided by Hebei Anguo Medical Materials Corporation (Anguo, China) and identified as Curcuma kwangsiensis S.G. Lee et C.F. Liang and Sparganium stoloniferum Buch.-Ham., respectively, by Professor Jing-Juan Wang from the Beijing University of Chinese Medicine, China. The voucher specimens (20180327 and 170201001) were stored in laboratory B417 at the Beijing University of Chinese Medicine. 2.3 Extraction The botanical drug pair (200 g, CR-SR = 1:1) was decocted with deionized water three times for 2 h each. Then, the supernatant was concentrated under reduced pressure, and finally, a dried extract was obtained. The single botanical drugs CR (200 g) and SR (200 g) were treated in the same way. 2.4 Chemical profiling 2.4.1 Molecular networking analysis All instruments were controlled by the Xcalibur data system. The data acquired from the previous research were carried out by analyst software Xcalibur 2.1 (Thermo Fisher Scientific, Bremen, Germany) ([83]Chang et al., 2020). The mass spectral data were converted from the raw format to the mzXML format using the msConvert. Then, the file was uploaded to the Global Natural Products Social Networking (GNPS) analysis platform ([84]https://gnps.ucsd.edu) to build a molecular network ([85]Xue et al., 2021). In the (GNPS) web-based platform, the basic parameters were modified to m/z 0.02 for the mass tolerance of precursor and fragment ions used in the MS/MS spectral library. Furthermore, the cosine fraction threshold was set to 0.6, and the results were visualized by Cytoscape 3.8.2 software. 2.4.2 UPLC-LTQ-Orbitrap MS^n analysis The separation of analytes was achieved using the gradient elution system consisting of acetonitrile (A) and 0.05% aqueous formic acid (B) at a flow rate of 0.3 ml/min. The gradient program was as follows: 0–5 min, 3%–12% A; 5–11 min, 12%–20% A; 11–14 min, 20%–25% A; 14–17 min, 25%–30% A; 17–19 min, 30% A; 19–20 min, 30%–35% A; 20–22 min, 35% A; 22–25 min, 35%–40% A; 25–28 min, 40%–48% A; 28–30 min, 48%–52% A; 30–35 min, 52%–80% A; and 35–40 min, 80% A. Then, 1 µL aliquot of each sample was injected into the column, which was maintained at 35°C. Data acquisition of the mode scan was performed from m/z 50 to m/z 1000 at a resolution of 30,000 in both positive and negative modes. The following ESI parameters in the negative ion mode were optimized and used: a capillary temperature of 350°C, sheath gas flow rate of 40 arb, auxiliary gas flow rate of 10 arb, electrospray voltage of −3.5 V, and tube lens voltage of −120 V. The electrospray voltage was 3.4 V, and the tube lens voltage was 120 V in the positive ion mode. Other parameters were the same as those of the negative ion mode. The most intense ions detected in the full-scan spectrum were selected for the data-independent scan. The relative collision energy for collision-induced dissociation was set to 35% of the maximum. 2.5 Network analysis and molecular docking 2.5.1 Target prediction The compounds collected from the identification of chemical components by molecular networking and UPLC-MS^n analysis included 59 diarylheptanoids, 32 sesquiterpenoids, 21 cyclic dipeptides, and 40 phenols and organic acids ([86]Chang et al., 2020; [87]Wang et al., 2020). The active compounds were further screened based on oral bioavailability (OB) ≥ 30 and drug-like properties (DL) ≥ 0.18, and their predicted targets were obtained by TCM Systems Pharmacology (TCMSP) ([88]https://old.tcmsp-e.com/tcmsp.php) and the Swiss target prediction database ([89]http://swisstargetprediction.ch/). The disease targets were collected by searching for the keywords “liver cancer” in the Gene Expression Omnibus database ([90]https://www.ncbi.nlm.nih.gov/geo/), DrugBank ([91]https://go.drugbank.com/), and Online Mendelian Inheritance in Man (OMIM, [92]http://www.omim.org/). All predicted targets were standardized into official gene symbols using the UniProt database ([93]https://www.uniprot.org/). 2.5.2 Network construction Network construction was performed as follows: 1) the active compound–target network; 2) protein–protein interaction (PPI) network. We constructed a Venn diagram to determine the overlapping targets between the active compound targets and disease targets using Venny online ([94]https://bioinfogp.cnb.csic.es/tools/venny/). These overlapping targets might play an important role when CR-SR, CR, and SR treat liver cancer. The intersection was considered as the potential targets and inputted to the STRING ([95]https://string-db.org/) database to construct the relationship between proteins. The TSV format of the PPI network was downloaded and visualized by Cytoscape 3.8.2 software ([96]Lan et al., 2020). 2.5.3 Pathway enrichment The key targets were put into the Metascape database, and the species were set as “Homo sapiens,” with p < 0.01 from the results of PPI analysis. GO annotations of targets and KEGG pathways were enriched and analyzed through the Metascape ([97]http://metascape.org) database platform, which could analyze the biological processes and pathways of genes ([98]Yu et al., 2021). In addition, the correspondence was established among active compounds, key targets, and the top 20 pathways of the KEGG pathway enrichment analysis results and visualized by Cytoscape 3.8.2 software. 2.5.4 Molecular docking The docking was carried out by the CDOCKER module in the Discovery Studio 2016 package. The key targets were imported into the Protein Data Bank ([99]https://www.rcsb.org/) database to download protein in the PDB format. The 3D structures of the active compounds downloaded from the PubChem database ([100]https://pubchem.ncbi.nlm.nih.gov/) were dealt with ChemDraw software. The docking results were evaluated with a threshold of 80% docking score for the original ligand and receptor after determining the docking pocket coordinates. Generally, the binding capacity is stronger when the docking score values are higher than the threshold value ([101]Yuan et al., 2021). 2.6 Cell culture and zebrafish husbandry The HepG2 cell line was purchased from the Cell Resource Center, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, and Peking Union Medical College, Beijing, China. The cells were maintained in RPMI 1640 with 10% fetal bovine serum, 1% penicillin, and 1% streptomycin at 37°C in an air–5% CO[2] incubator at constant humidity ([102]Chen et al., 2018). The wild-type (AB stain) zebrafish was purchased from the laboratory of Bo Zhang at Peking University. The zebrafish were maintained and raised in a continuous flow system (ESEN, Beijing, China) on a 14-h light/10-h dark cycle at 28.5°C and fed brine shrimp three times daily. The zebrafish embryos were obtained from spawning adults with a sex ratio of 1:1 (5–8 months old) and raised at 28.5°C in embryo water (5.4 mmol/L KCl, 0.137 mol/L NaCl, 1.3 mmol/L CaCl[2], 0.25 mmol/L Na[2]HPO4, 0.44 mmol/L K[2]HPO[4], 1.0 mmol/L MgSO[4], and 4.2 mmol/L NaHCO[3]) ([103]Zhao et al., 2020)[.] 2.7 CCK8 for cell proliferation detection Cells in the logarithmic growth phase were seeded into a 96-well plate at a density of 4 × 10^4/ml (100 μL/well) and cultured for 24 h. Cells treated with the medium containing 0.1% DMSO were used as a negative control. CR-SR, CR, and SR extracts were well dissolved in the medium containing 0.1% DMSO, respectively, followed by ultrasonic vibration. The samples (100 μL) of CR-SR, CR, and SR at different concentrations were added to adherent cells with three wells for each group and repeated three times. After 48 h, the fluid was removed, and CCK8 (100 μL) was added to each well and cultured for 2 h. The absorbance was measured at 450 nm in a microplate reader (Beijing Perlong New Technology Co., Ltd., Beijing, China). The data were expressed as percentage inhibition compared with a vehicle (DMSO) control ([104]Chen et al., 2018). 2.8 Anti-liver cancer activity of CR-SR, CR, and SR extracts in a zebrafish HepG2 xenograft model To determine the maximum non-lethal concentration (MNLC) of these drugs, 3 days postfertilization (3 dpf) zebrafish were treated with the testing drugs in 12-well culture plates (20 larvae/well) for 72 h, and mortality was recorded at the end of treatment. The dead larvae were counted daily. Therefore, HepG2 cell suspension was stained by 10 μM DiO for 30 min at 4°C, re-suspended in a medium, and kept at 4°C before injection. Cells were injected into zebrafish embryos at 2 dpf using a microinjector, with approximately 200 cells/embryo. The larvae with the same amount of fluorescence were randomly divided into different groups and transferred to 12-well culture plates (20 per sample, n = 3) at 3 dpf. The groups in this experiment included the normal group, the HepG2 xenograft model group, the positive control group (100 ng ml^−1 cisplatin), and the drug groups at different concentrations. A total of 10 zebrafish larvae were randomly selected at 6 dpf and photographed in each group using an Axio Zoom V16 fluorescence microscope (Zeiss, Germany), and the relative fluorescence area was calculated. Then, the inhibitory effect of each antitumor drug was quantitatively evaluated ([105]Zhao et al., 2020). 2.9 Detection of the zebrafish mRNA expression level by the real-time quantitative polymerase chain reaction The mRNA expression levels of the key genes were measured using RT-qPCR. The zebrafish HepG2 xenograft model was built. Then, 3 dpf zebrafish embryos were transferred into 12-well plates (20 embryos/well) and incubated with CR-SR (500 μg/ml), CR (300 μg/ml), and SR (1,000 μg/ml) at 72 hpf. The total RNA (1 μg) was converted to first-strand cDNAs using a PrimeScript™ RT reagent Kit for reverse transcription. In 20 μL reactions with each of the forward and reverse primers, cDNA, and SYBR Green Mix, RT-qPCR was performed. Thermal cycling was set at 95°C for 5 s and 60°C for 30 s with 40 cycles. Gene expression for each sample was expressed as a threshold cycle (Ct), normalized to the reference gene β-actin (△Ct). The experiment was conducted in triplicate ([106]Lan et al., 2020). Proto-oncogene tyrosine-protein kinase Src (SRC), epidermal growth factor receptor (EGFR), estrogen receptor-α (ESR1), prostaglandin endoperoxide synthase 2 (PTGS2), and amyloid precursor protein (APP) genes were determined, as described previously. The primer sequences of the genes are shown in [107]Table 1 ([108]Carnevali et al., 2010; [109]Lu et al., 2013; [110]Liu et al., 2014; [111]Pashay Ahi et al., 2016; [112]Gu et al., 2020). TABLE 1. Primer sequence used for PCR analysis. Gene Forward Reverse EGFR 5′-ACG​CAG​ACG​AGT​ATT​TAG​TGC​CCA-3′ 5′-AGT​TTC​CAA​AGC​TGC​TGT​TCA​GGC-3′ ESR1 5′-ACT​GTG​GCT​CGA​TTT​CGG​AGT-3′ 5′-TCC​ACT​GGA​CTG​GAG​CAG​AAT​G-3′ PTGS2 5′-TGG​ATC​TTT​CCT​GGG​TGA​AGG-3′ 5′-GAA​GCT​CAG​GGG​TAG​TGC​AG-3′ APP 5′-GGA​GTT​TGT​GTG​CTG​CCC​AA-3′ 5′-ACC​GTC​ACC​GTC​TTC​ATC​GT-3′ SRC 5′-ACA​CAG​CCC​AAC​ATC​ATC​AA-3′ 5′-TAT​CCG​CTC​TCT​CCT​GTC​GT-3′ β-actin 5′-TCC​CCT​TGT​TCA​CAA​TAA​CC-3′ 5′-TCT​GTT​GGC​TTT​GGG​ATT​C-3′ [113]Open in a new tab 2.10 Statistical analysis All the assays were carried out in triplicate, and results were expressed as mean values ± standard deviation (mean ± SD). All statistical analyses were carried out by SPSS (Version 25.0) and Origin 2021. The one-way analysis of variance (ANOVA) test was used to check for significant differences among the groups. Differences between models were considered significant when the p-value was less than 0.05. 2.11 Ethics statement Zebrafish experiments were conducted according to the Regulation on the Administration of Laboratory Animals (2013 Revision, document number: order no. 638 of the State Council) for experimental care and usage of animals. 3 Result and discussion 3.1 Chemical profiling 3.1.1 Study on molecular networking of mass spectrometry of CR-SR, CR, and SR decoction Previously, our laboratory has identified 47 linear diarylheptanoids in CR-SR ([114]Chang et al., 2020). On the basis of this study, we further explored the MS data through the GNPS platform. The MS data were visualized by Cytoscape 3.8.2. The spectral similarities were expressed as the cosine score (cos θ), and the larger the cos θ score, the higher the similarity of the MS/MS fragments ([115]Xue et al., 2021). Also, the structurally similar compounds were inferred by using the differences in secondary mass spectra from related nodes. Each node represented a secondary mass spectral map. A total of 1,120 nodes were incorporated into the MS/MS molecular networking of the CR-SR decoction in the positive mode, resulting in 18 molecular clusters and 809 unconnected nodes ([116]https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=078b8a6443d540a8 8720ff67cc3b06a2). Meanwhile, a total of 1,079 nodes were incorporated into the MS/MS molecular networking of the CR decoction in the positive mode, resulting in 22 molecular clusters and 801 unconnected nodes ([117]https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=87f347a0948e4b92 b78cf433b111803a). Based on the clusters in the molecular networking, a total of 12 diarylheptanoids were tentatively identified from CR-SR and CR for the first time in the positive mode. In our previous research, diarylheptanoids were the main compounds of CR-SR ([118]Chang et al., 2020). In this molecular map, 25 and 23 diarylheptanoids had been identified in the largest clusters from CR-SR and SR, respectively. Taking m/z 311.163 as an example, the compound dissociated into fragment ions [M + H-C[7]H[8]O[2]]^+ at m/z 187, [M + H-C[10]H[12]O]^+ at m/z 163, [M + H-C[7]H[8]O[2]-C[2]H[2]]^+ at m/z 161, [M + H-C[7]H[8]O[2]-C[2]H[4]]^+ at m/z 159, [M + H-C[10]H[12]O[2]]^+ at m/z 147, and [M + H-C[12]H[14]O]^+ at m/z 137 by comparison with the reported literature ([119]Cheng et al., 2018). Its adjacent node at m/z 327.158 gave an MS/MS spectrum showing the same characteristic fragments at m/z 147. Therefore, the compound was plausibly characterized as 7-(4-hydroxy-3-methoxyphenyl)-1-phenyl-4-hepten-3-one, and its proposed fragmentation pathway is shown in [120]Supplementary Figure S1. According to references, the cracking pathways of other diarylheptanoid