Cell Cycle Arrest, An Important Mechanism of Action of Compound Kushen Injection, Prevents Colorectal Cancer: Network Pharmacology Analysis and Experimental Validation

Compound Kushen injection (CKI) is the most widely used traditional Chinese medicine preparation for the comprehensive treatment of colorectal cancer (CRC) in China, but its underlying molecular mechanisms of action are still unclear. The present study employed a network pharmacology approach, in which we constructed a “bioactive compound -target- pathway” network . Experimental RNA sequencing (RNA-Seq) analysis was performed to identify a key “bioactive compound-target- pathway” network for subsequent experimental validation. Cell cycle, proliferation, autophagy, and apoptosis assays and a model of azoxymethane/dextran sodium sulfate-induced colorectal carcinogenesis in mice were employed to detect the biological effect of CKI on CRC. Real-time reverse-transcription polymerase chain reaction, Western blot, and immunohistochemistry were performed to verify the selected targets and pathways. We constructed a predicted network that included 82 bioactive compounds, 34 targets, and 33 pathways and further screened an anti-CRC CKI “ biological compound (hesperetin 7- O -rutinoside, genistein 7- O -rutinoside, and trifolirhizin)-target (p53 and checkpoint kinase 1 [CHEK1] )” network that targeted the “cell cycle pathway” . Validation experiments showed that CKI effectively induced the cell-cycle arrest of CRC cells in vitro and suppressed the development of CRC in vivo by downregulating the expression of p53 and CHEK1. Our findings confirmed that inducing cell-cycle arrest by CKI is an important mechanism of its anti-CRC action, which provides a direct and scientific experimental basis for the clinical application of CKI.


Introduction Compound Kushen injection induces cell cycle arrest of SW480 and SW620 CRC cells in vitro.
To characterize the effect of CKI on the cell cycle arrest of SW480 and SW620 CRC cells, both cell lines were labeled with propidium iodide to detect cell cycle progression by flow cytometry. As shown in Fig. 5A, after CKI treatment, the SW480 cell cycle was significantly inhibited in the G0/G1 phase compared with the control (p < 0.001), and the SW620 cell cycle was arrested in the G2/M phase (p < 0.05).

Compound Kushen injection inhibits the proliferation of SW480 and SW620 CRC cells in vitro.
To determine the effect of CKI on the proliferation of SW480 and SW620 CRC cells, we performed the cholecystokinin-8 (CCK-8) assay to measure cell viability after treatment with CKI (2 mg/ml, based on the total alkaloid concentration in CKI). As shown in Fig. 5B, the proliferation of SW480 and SW620 cells was significantly inhibited by treatment with CKI (both p < 0.05) and fluorouracil (5-Fu; both p < 0.01) compared with untreated cells.

Compound Kushen injection induces autophagy but does not alter the apoptosis of SW480 and SW620 CRC cells in vitro.
To investigate CKI-induced autophagy in SW480 and SW620 CRC cells, we measured vesicles that were labeled with Autophagy Blue TM , a widely used specific autophagosome marker, to analyze the activity of autophagy. As shown in Fig. 6A and B, both SW480 and SW620 cells exhibited significant changes in morphology compared with cells that were cultured in a medium that contained serum after starvation in serum-free medium or CKI incubation for 24 h (both p < 0.001). Cells that were treated with CKI in the culture medium with serum exhibited obvious autophagic vacuoles, indicated by Autophagy Blue TM staining. To further determine the effect of CKI on the apoptosis of SW480 and SW620 cells, we performed apoptosis assays. As shown in Fig. 6C and D, CKI did not affect the apoptosis of SW480 cells and SW620 cells.

Compound Kushen injection prevents the development of AOM/DSS-induced CRC in vivo.
To investigate the preventive effect of CKI on the development of CRC and induction of the cell cycle arrest of CRC cells, we first successfully constructed the AOM/DSS-induced CRC model (Fig. 7A, B), which was histologically confirmed at the endpoint of the experiment (Fig. 7B). For comparison purposes, 5-Fu was used in this study when considering its ability to prevent CRC development and arrest the cell cycle. A time-course observation is shown in Fig. 7A. The length of the colon, which was greatly shortened in AOM/DSS mice compared with normal controls, was significantly restored by 5-Fu and CKI treatment (Fig. 7C). The weight of AOM/DSS mice was significantly reduced compared with normal controls. The weight of mice that were treated with 5-Fu and CKI was significantly higher than AOM/DSS mice but slightly lower than normal controls (Fig. 7D). The total number of tumors was significantly decreased by 5-Fu and CKI treatment compared with AOM/DSS mice (Fig. 7E). As shown in Fig. 7B, AOM/DSS mice exhibited obvious tumor lesions (NaCl group), in which the center of the large intestinal gland was larger and irregular, whereas mice in the 5-Fu and CKI groups exhibited healthy tissue morphology and had no tumor focus. Altogether, these results suggest that CKI exerted comparable antitumor effects and significantly inhibited the AOM/DSS-induced development of CRC.
Compound Kushen injection downregulates the expression of targets that are related to cell cycle arrest in vitro and in vivo. The cell cycle is a common target signaling pathway of CKI against CRC, which was predicted by network pharmacology and verified by RNA-Seq (SW480 and SW620 cells). However, CKI target genes that are involved in the cell cycle are not the same (Supplementary Table S4). Cell cyclerelated CKI targets, verified in SW480 cells, did not overlap with those that were predicted by network pharmacology and verified by SW620 cells. Considering the consistency of the network pharmacology prediction and RNA-Seq verification results of SW620 cells and considering that SW620 cells are more representative of CRC than SW480 cells, we selected p53, CHEK1, CCND1, CDKN2A, MDM2, and p21 as key targets of CKI-induced cell cycle arrest. Among these, p53 and CHEK1 are common CKI targets for SW620 cell verification and network pharmacology prediction. CCND1, CDKN2A, and MDM2 are specific CKI targets of network pharmacology prediction, and p21 is the specific CKI target of SW620 cells.
As shown in Fig. 8, the mRNA expression of p53, CHEK1, CCND1, CDKN2A, and MDM2 was significantly downregulated in both SW480 and SW620 cells after CKI treatment. p21 mRNA and protein expression were significantly downregulated in SW480 cells but upregulated in SW620 cells. These results confirmed the target network pharmacology prediction from the perspective of the in vitro experiments and further showed that CKI plays a pharmacological role in cell cycle arrest in CRC cells by downregulating the expression of these targets, with the exception of p21.
As shown in Fig. 2B and Supplementary Table S2, the size of the p53 node was the largest in the PPI network of CKI targets, representing the highest degree value. This indicates that p53 occupied the most important position in the entire PPI network and plays a decisive role in CKI-induced cell cycle arrest and the prevention of CRC. In the present study, we found that CKI effectively inhibited the mRNA and protein expression of mutant p53 in SW480 and SW620 CRC cells in vitro ( Fig. 8A-D) and inhibited p53 protein expression in colon tissue in the AOM/DSS-induced CRC model in vivo (Fig. 8E). We also detected the expression of ki67, phosphorylated AKT (p-AKT), p-mTOR, and p-CHEK1, which are closely related to p53, cell proliferation, and growth, by immunohistochemistry and found the high expression of ki67, mutant p53, p-CHEK1, p-AKT, and p-mTOR in colorectal tissues in the AOM/DSS group that was treated with NaCl. After treatment with 5-Fu and CKI, the expression and degree of these five proteins in colorectal tissue in AOM/DSS mice (with NaCl treatment) significantly decreased. We further examined expression in colorectal tissue by immunohistochemistry in the normal group and AOM/DSS group (with NaCl treatment) (Fig. 8E). The expression of ki67, mutant p53, p-CHEK1, p-AKT, and p-mTOR positively correlated with the AOM/DSS group that was treated with NaCl. Among these, the effect of 5-Fu was more apparent, which was close to normal tissue. Additionally, although the effect of CKI was slightly weaker than the positive control drug 5-Fu compared with the AOM/DSS group that was treated only with NaCl, the effect of these five proteins was still significantly reduced.
Altogether, these results demonstrate that cell cycle arrest that is induced by p53 and CHEK1 is an important mechanism by which CKI prevents CRC development. We successfully constructed a "bioactive compound (genistein, hesperetin, lanceolarin, and trifolirhizin)-target (p53 and CHEK1)-cell cycle pathway" network for the anti-CRC effect of CKI.

Discussion
As an anti-tumor TCM preparation that was approved by the Chinese Food and Drug Administration in 1995, CKI has been widely used for the clinical treatment of various malignant tumors, including CRC, in China, with a remarkable curative effect 6,9,12 . However, because of a lack of evidence from basic research, the potential mechanism of action of CKI for cancer treatment is still not understood. In recent years, the application of network pharmacology, RNA-Seq technology, and bioinformatics has become a good research tool for screening bioactive ingredients with anti-cancer properties and predicting target genes and related signaling pathways. The application of in vitro cells and in vivo animal models has also provided robust technical support for verifying the biological effects of CKI [16][17][18][19][20][21][22][23][24][25][26][27] .
Recently, several research groups have successfully constructed CKI anti-cancer "compound-protein target-pathway" networks using network pharmacology.
Compound Kushen injection was shown to play an anti-cancer role through multiple components, targets, and pathways. These anti-cancer mechanisms of action of CKI have demonstrated its anti-pan-cancer activities and specificity for some cancer types 16,[17][18][19][20] . For pan-cancers, He et al. constructed a pharmacological network that was composed of 33 active components, 113 protein targets (including IL6, EGFR, CASP3, VEGFA, MYC, and ESR1), and a list of the top 20 signaling pathways (including the PI3K/AKT signaling pathway, p53 signaling pathway, apoptosis, proteoglycans in cancer, and pathways in cancer). These authors speculated that the potential molecular mechanism of action of CKI's anti-pan-cancer actions involves promotion of the p53and PI3K/Akt-mediated apoptosis of tumor cells 16 . For individual cancers, Zhou et al. constructed a pharmacological "active ingredient-protein target-signaling pathway" network for gastric cancer, esophageal cancer, lung cancer, and breast cancer [17][18][19][20] . Zhou et al. reported that CKI has a therapeutic effect on gastric cancer by synergistically regulating some biological pathways, such as the cell cycle, pathways in cancer, the PI3K-AKT signaling pathway, the mTOR signaling pathway, and the FoxO signaling pathway. Moreover, molecular docking simulation indicated that the CKI compounds had good binding activity to PIK3CA, AKT1, MAPK1, ERBB2, and MMP2 in vivo 18 . Zhou et al. also showed that potential hub targets (including EGFR, ErbB2, CCND1, and IGF1R) were therapeutic targets of CKI for the treatment of esophageal cancer and were significantly enriched in many pathways that are related to cancer and signaling pathways, such as the PI3K-Akt signaling pathway and ErbB signaling pathway 17 . Meng et al. showed that CKI might target CHRNA3, DRD2, PRKCA, CDK1, CDK2, MMP1, and MMP9 and play a therapeutic role in lung cancer by regulating some important pathways, such as pathways in cancer, proteoglycans in cancer, the PI3K-Akt signaling pathway, non-small-cell lung cancer, and small-cell lung cancer.
In the present study, 34 protein targets, which mapped to 82 compounds, were selected to construct the "herb-compound-protein target" network, and 33 signaling pathways were predicted to be targets of anti-CRC CKI (Fig. 3B, Supplementary Table  S4). In addition to various cancer-related pathways, the predicted pathways mainly included adherens junction, transcriptional misregulation in cancer, signaling pathways regulating pluripotency of stem cells, Wnt, focal adhesion, Happo, PI3K-Akt, central carbon metabolism in cancer, cell cycle, HIF1, ErbB, FoxO, CRC, microRNAs in cancer, proteoglycans in cancer, p53, and pathways in cancer (Supplementary Table  S4). The PPI analysis suggested that these predicted pathways are mainly associated with multiple hub protein targets, such as TP53, CCND1, CDKN2A, MDM2, CTNNB1, EGF, MTOR, CHEK1, and IGF1 (Fig. 2C). By integrating the findings of other research groups [17][18][19][20] and our present findings, we found that different cancers have many common CKI target pathways (such as HIF1, PI3K-Akt, ErbB, FoxO, and p53; Supplementary Table S5). Although there may be some overlap, the hub protein targets were quite different. Therefore, the predicted hub protein targets and pathways of anti-CRC CKI were validated by primary (SW480) and metastatic (SW620) isogenic CRC cell lines 28 . mRNA expression of the TP53, CHEK1, DNMT1, ANP32A, DHFR, TOP1, MMP1, DICER1 genes was confirmed by RNA-Seq, and the results were consistent with the predicted network pharmacology results. As shown in Fig. 4 and Supplementary Table S4, we enriched 23 and 32 KEGG pathways of CKI in SW480 and SW620 cells, respectively. The CKI target pathways that were enriched in SW480 cells were significantly different from those that were predicted by network pharmacology and enriched in SW620 cells. The cell cycle was the only CKI target pathway that was enriched in network pharmacology, SW480 cells, and SW620 cells. Among the CKI target pathways (except the cell cycle) enriched in SW620 cells, 16 were consistent with our network pharmacology prediction results, and most of them were also consistent with the prediction results of gastric cancer, esophageal cancer, lung cancer, and pan-cancer (Supplementary Table S5). This type of experimental sequencing verification illustrates the reliability of the network pharmacology analysis but also indicates that we need to combine differences of different tumors and heterogeneity of the same tumor to study the anti-cancer effects and mechanism of action of CKI.
As mentioned above, preliminary verification by RNA-Seq at the cell level showed that the cell cycle, p53 signaling pathway, FoxO signaling pathway, ErbB signaling pathway, Viral carcinogenesis, and proteoglycans in cancer were key signaling pathways that are targeted by CKI, and most of them are involved in cell cycle progression, proliferation, apoptosis, autophagy, and growth of CRC cells. RNA-Seq also showed that p53 and CHEK1 are key target proteins of CKI in inhibiting CRC and inducing SW620 cell cycle arrest. We also found that CKI induced the cell cycle arrest (Fig. 5A) and autophagy (Fig. 6A, B) of SW480 and SW620 cells, inhibited their proliferation in vitro (Fig. 5B), and effectively inhibited AOM/DSS-induced carcinogenesis and the development of CRC in vivo (Fig. 7).
Cell cycle control is one of the major regulatory mechanisms of cell growth, and abnormal regulation of the cell cycle is a notable characteristic of cancer cells 29 . Cell proliferation is regulated primarily by regulation of the cell cycle to monitor DNA integrity, which consists of four distinct sequential phases (G0/G1, S, G2, and M) 30 . In the present study, we utilized a human CRC cell model and AOM/DSS-induced mouse colorectal carcinogenesis model to validate predicted potential key markers that are associated with the cell cycle in vitro and in vivo. The present study showed that CKI significantly inhibited the growth and induced the autophagy of tumor cells. After CKI treatment, the SW480 cell cycle was significantly inhibited in the G0/G1 phase, and the SW620 cell cycle was arrested in the G2/M phase. The discrepancy in CKI-mediated cell cycle control between SW480 and SW620 cells may be attributable to differences in genetic backgrounds or signaling networks between the two cell lines. The SW480 cell line was originally established from primary adenocarcinoma of the colon. It has a G→A mutation in codon 273 of the p53 gene, resulting in an Arg→His substitution, and a C→T mutation in codon 309 results in a Pro→Ser substitution. By comparison, the SW620 cell line was established from a lymph node in the same manner that the SW480 cell line was initiated from primary adenocarcinoma the previous year 31 . The quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) results indicated that mRNA levels of CCND1, CHEK1, p53, CDKN2A, and MDM2 were significantly downregulated in SW480 and SW620 cells, but the mRNA level of p21 was upregulated in SW620 cells and downregulated in SW480 cells. In response to various cellular signals, p53 becomes activated to function as a transcription factor that transcribes a genetic program to accomplish a number of different functions, such as activating DNA repair, inducing cell cycle arrest, and initiating autophagy 32,33 . The upregulation of p53 protein can initiate p21-dependent cellular growth arrest. P21CIPI/WAF1 protein inhibitor binds to and inhibits the activity of cyclin-CDK2 complexes, thereby functioning as a regulator of cell cycle progression. The expression of this gene is tightly controlled by the tumor suppressor protein p53 34 . Thus, the p53-p21 axis is regarded as a classic pathway for G2/M phase arrest that is induced by DNAdamaging agents 35 . However, when p53 mutates, the original function of p53 is inhibited. This was supported by the present findings in SW480 and SW620 cells, which expressed high levels of mutant p53 protein. Consistent with the qRT-PCR data, the expression levels of TP53 and p21 proteins were downregulated in SW480 cells after CKI treatment, the expression levels of TP53 were downregulated in SW620 cells, and the expression levels of p21 were upregulated in SW620 cells. One explanation for this differential effect of p21 with CKI treatment is that p53 has multiple downstream target genes, in addition to p21, following CKI treatment. We found that CKI may inhibit CRC proliferation by downregulating mutant p53 protein expression, thereby regulating cell cycle progression.
Autophagy is an evolutionarily conserved lysosomal self-digestion process that plays a dual role in tumorigenesis and cancer therapy. With regard to cancer, many links exist between autophagy and p53. Wildtype p53-mediated adenosine monophosphateactivated protein kinase activation resulted in cytoprotective autophagy in response to the DNA-damaging drug topotecan in human colon cancer cells. Autophagy-sensitized colon cancer cells with wildtype p53 were inhibited by topotecan treatment. Autophagy inhibition attenuated the anti-tumor effect of topotecan treatment in p53 mutant or knockout colon cancer cells both in vitro and in vivo 36 . In the present study, we found that the human CRC cell lines with mutant p53 (i.e., SW480 and SW620 cells) underwent autophagic cell death following treatment with CKI. These findings suggest that p53 may modulate autophagy and that p53 status could determine cell fate following anti-cancer drug-induced autophagy and help maintain autophagic homeostasis.
Compound Kushen injection is mainly used for the comprehensive treatment of advanced CRC. Our results in SW480 cells suggest that although its mechanism of action is different from SW620 cells, CKI could be used for the treatment of early carcinoma in situ, based on its effect of inducing cell cycle arrest. 5-Fluorouracil is frequently used for CRC treatment because of its ability to induce CRC cell cycle arrest 43 . Thus, 5-Fu was used as a positive control drug in the present study. Both the in vitro and in vivo studies showed that CKI exerted similar anti-CRC effects as 5-FU, thus providing a good experimental basis for the clinical use of CKI alone for the treatment of CRC. Additionally, mutant p53 is overexpressed in patients with CRC and promotes tumor growth in vivo. Therefore, the inhibition of mutant p53 may be a useful strategy for the treatment of mutant p53-overexpressing CRC in patients.
In conclusion, based on network pharmacology analyses, the active components of CKI for the treatment of CRC and their corresponding targets and pathways were screened. Our results were verified both in vivo and in vitro using advanced molecular biology and RNA-Seq approaches. Our data demonstrate potential pharmacological mechanisms of action of CKI. Considering the diversity of effective components, targets, and pathways of CKI, further research and validation are needed to clarify its anti-CRC activity.

Materials and Methods
Active Ingredients in CKI. The ingredients of Kushen and Baituling were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database (http://tcmspw.com/tcmsp.php) 44 , the Traditional Chinese Medicine Information (TCMID) database (http://119.3.41.228:8000/tcmid/search/) 45 , and the literature. To screen components with high biological activity in the human body, we employed an important ADME (Absorption, Distribution, Metabolism, Excretion)-related property of injection, Drug-Likeness (DL), to explore the potential bioactive compounds in CKI 46 . Ingredients with DL < 0.18 were removed from the study.
Potential Targets of CKI. To identify potential targets of CKI, one drug target prediction using the PharmMapper database (http://lilab.ecust.edu.cn/pharmmapper/) was used. It was designed to identify potential targets for small molecules using a reverse pharmacophore mapping approach 47 . Structural information for the compounds was first obtained from the National Center for Biotechnology Information PubChem database (https://pubchem.ncbi.nlm.nih.gov/). An SDF file of compounds was then uploaded into PharmMapper database, and the Human Protein Targets Only database was selected 48 . The top 30 potential targets for each compound were obtained and sorted by the normalized fit score. Official genes names were taken from UniProt (http://www.uniprot.org/) by confining the species to "Homo sapiens." concentration of 2 mg/ml (based on the total alkaloid concentration in CKI 57 ). Optical densities were obtained by reading plates at 450 nm using a 96-well micro test spectrophotometer (Bio-Rad, Hercules, CA, USA). Autophagy Assays. Autophagy was analyzed using the Cell Meter Autophagy assay. SW480 and SW620 cells were seeded in 96-well plates at a density of 2 × 10 4 cells/ml in 100 μl DMSO overnight. A non-induced negative control cell population at the same density as the induced population was cultured for every labeling condition. The medium was then removed, and 100 μl of Autophagy Blue working solution (AAT Bioquest, Sunnyvale, CA, USA) was added to each well. The cells were then incubated at 37°C in a 5% CO2 incubator for 1 h. After three washes, fluorescent intensity was monitored with a fluorescence microscope using the DAPI channel.
Animal Model Experiments. All animal care and handling guidelines were approved by the Animal Care Committee of Peking University People's Hospital. Time-course observations of AOM/DSS-induced colorectal carcinogenesis were conducted in mice 58 . Five-week-old male ICR mice were kept under specific-pathogen-free conditions and received a single intraperitoneal injection of AOM (10 mg/kg body weight; Sigma-Aldrich, St. Louis, MO, USA), followed by 1 week of 2% DSS supplementation (MP Biomedicals, Irvine, CA, USA) in drinking water, after which the mice were maintained on regular water for 28 days. The mice in the AOM-DSS group were then randomly divided into three subgroups (n = 6/group). At week 7, these three groups of mice were injected intraperitoneally with 200 µl of NaCl (original injection), 200 µl of 5-Fu (4 mg/ml), or 200 µl of CKI (original injection). At approximately 4 weeks after the drug intervention, the mice were sacrificed, and colorectal tissues were sectioned for histological analysis.

Validation of Results by Real-Time qRT-PCR.
qRT-PCR was performed as described previously 59 . The primers are listed in the Supplementary Materials (Supplementary Table S6). Amplification was conducted and analyzed using a CFX96 analyzer (Bio-Rad, Hercules, CA, USA).
Western Blot Analysis. Western blot and immunoprecipitation were performed as described previously 59 . The antibodies are listed in the Supplementary Materials (Supplementary Table S7).
Immunohistochemistry. Colorectal tissues from AOM/DSS mice were deparaffinized in xylene and then rehydrated in a decreasing series of ethanol. The specimens were retrieved by a water bath at 95℃ for 15 min in 0.01 M citrate buffer (pH 6.0), and then endogenous peroxidase was deactivated by incubating with 3% hydrogen peroxide for 15 min, after which the sections were washed with phosphate-buffered saline (PBS). Nonspecific binding was blocked by incubating with 10% normal goat serum (ZSGB, Beijing, China) for 60 min. The sections were then incubated with a working solution of p53, p-CHEK1, ki67, p-AKT, or p-mTOR primary antibody. After washing with PBS, the sections were incubated with horseradish peroxidase-conjugated rabbit antigoat immunoglobulin G and stained with 3,3'-diaminobenzidine and then counterstained with hematoxylin. As negative controls, PBS was used instead of the primary antibody. Digital images were acquired using a Zeiss AXIO Scope A1 digital camera microscope (Zeiss, Jena, Germany). The antibodies and dyes are listed in the Supplement Materials (Supplementary Table S7). The immunohistochemistry staining intensity and extent of the staining area were classified as the following 60 : 1 (no or weak staining), 2 (moderate staining), and 3 (strong staining). The percentage of positive cells was defined as the following: 0 (0%), 1 (1-24%), 2 (25-49%), 3 (50-74%), 4 (75-100%). The final immunoreactive score (0 to 12) was determined by multiplying the intensity score by the percentage of staining score.
Statistical Analysis. The statistical analysis was performed using GraphPad Prism 5.0 software. All of the experiments were repeated at least three times. Student's t-test was used to evaluate differences between two groups. Two-tailed values of p < 0.05 were considered statistically significant.     Values at different stages of the cell cycle represent the mean ± SD from three independent experiments. B. SW480 and SW620 cell viability was measured under different treatment conditions using CCK-8. Each data point represents the mean ± SD from three independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001, compared with control.    SW480 and SW620 cells. A, B. mRNA levels of CCND1, MDM2, CHEK1, CDKN2A, p53, and p21 were analyzed by RT-qPCR in SW480 and SW620 cells. C, D. Western blot analysis of p53 and p21 in SW480 and SW620 cells. All Western blot bands were quantified using a custom ImageJ script. The results are expressed as the mean ± standard deviation (SD) from three independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001, compared with untreated group. E. Immunohistochemical staining of ki67, p53, p-CHEK1, p-AKT, and p-mTOR in colorectal tissue from mice in the normal group and AOM/DSS group (400 magnification) and total immunohistochemistry score for ki67, p53, p-CHEK1, p-AKT, and p-mTOR in colorectal tissue from mice in the normal group and AOM/DSS group. *p < 0.05, **p < 0.01, ***p < 0.001, compared with each group. Figure 1 Work ow of network pharmacology and experimental validation analyses.    Functional analysis of CKI against SW480 and SW620 cells based on RNA-seq data. A. Enrichment analysis of Gene Ontology (GO) biological processes of CKI against SW480 cells. B. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to CKI against SW480 cells. C. Enrichment analysis of GO biological processes of CKI against SW620 cells. D. KEGG pathways related to CKI against SW620 cells. E. Venn diagram of pathways that were enriched based on RNA-Seq data and predicted by network pharmacology.

Figure 5
Compound Kushen injection induces the arrest of cell cycle progression and inhibits CRC cell proliferation in vitro. A. Flow cytometry assays were performed to analyze the cell cycle in SW480 and SW620 cells after CKI treatment. Values at different stages of the cell cycle represent the mean ± SD from three independent experiments. B. SW480 and SW620 cell viability was measured under different treatment conditions using CCK-8. Each data point represents the mean ± SD from three independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001, compared with control. Compound Kushen injection induces autophagy but does not alter the apoptosis of SW480 and SW620 CRC cells in vitro. SW480 and SW620 cells were incubated in regular DMEM as a negative control and in serum-depleted medium as a positive control for 24 h. Both control cells and CKI-treated cells were incubated with a working solution of Autophagy Blue for 30 min at 37°C in a 5% CO2 incubator and then washed four times with wash buffer. A. Cells were imaged under white light under a microscope. B. Cells were imaged under a uorescence microscope with a DAPI channel. Autophagy is indicated by the bright blue dot staining of autophagic vacuoles. Each data point represents the mean ± SD from three independent experiments. ***p < 0.001, compared with negative control. C, D. Cell apoptosis was assessed by the Annexin-V assay.  Compound Kushen injection alters the expression of targets related to cell cycle arrest in SW480 and SW620 cells. A, B. mRNA levels of CCND1, MDM2, CHEK1, CDKN2A, p53, and p21 were analyzed by RT-qPCR in SW480 and SW620 cells. C, D. Western blot analysis of p53 and p21 in SW480 and SW620 cells.
All Western blot bands were quanti ed using a custom ImageJ script. The results are expressed as the mean ± standard deviation (SD) from three independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001, compared with untreated group. E. Immunohistochemical staining of ki67, p53, p-CHEK1, p-AKT, and p-mTOR in colorectal tissue from mice in the normal group and AOM/DSS group (400 magni cation) and total immunohistochemistry score for ki67, p53, p-CHEK1, p-AKT, and p-mTOR in colorectal tissue from mice in the normal group and AOM/DSS group. *p < 0.05, **p < 0.01, ***p < 0.001, compared with each group.

Supplementary Files
This is a list of supplementary les associated with this preprint. Click to download.