Exploring the Molecular Targets and Therapeutic Potential of Coptisine in Colon Cancer: A Network Pharmacology Approach.

Solanum nigrum L. (SNL) (Longkui) is a Chinese herb that can be used to treat colon cancer. The present study explored the components and mechanisms of SNL in treating colon cancer by using network pharmacology and molecular docking. The components of SNL were collected from the TCMSP, ETCM, HERB, and NPASS databases. Meanwhile, the target proteins of these ingredients were collected/predicted by the TCMSP, SEA, SwissTargetPrediction, and the STITCH databases colon cancer-related target genes were identified from TCGA and GTEx databases. The interaction networks were established via Cytoscape 3.7.2. Gene Ontology and KEGG pathways were enriched by using the David 6.8 online tool. Finally, the binding of key components and targets was verified by molecular docking, and the cellular thermal shift assay (CETSA) was used to detect the efficiency of apigenin and kaempferol binding to the AURKB protein in CT26 cells. A total of 37 SNL components, 796 SNL targets, 5,356 colon cancer genes, and 241 shared targets of SNL and colon cancer were identified. A total of 43 key targets were obtained through topology analysis. These key targets are involved in multiple biological processes, such as signal transduction and response to drug and protein phosphorylation. At the same time, 104 signaling pathways, such as pathways in cancer, human cytomegalovirus infection, and PI3K-Akt signaling pathway, are also involved. The binding of the four key components (i.e., quercetin, apigenin, kaempferol, and luteolin) and the key targets was verified by molecular docking. The CETSA results showed that apigenin and kaempferol were able to bind to the AURKB protein to exert anti-CRC effects. Quercetin, apigenin, kaempferol, and luteolin are the main components of SNL in treating colon cancer. SNL regulates multiple bioprocesses via signaling pathways, such as pathways in cancer, PI3K-Akt, and cell cycle signaling pathways.

Network pharmacology is a novel approach that uses bioinformatics to predict multitarget drugs and ingredient-target interactions in various diseases. A thorough search of previously published studies revealed that Hedyotis diffusa Willd (HDW) and Astragalus membranaceus (AM) possess anticancer activity. Colon cancer (CC) is one of the most common malignant tumors of the digestive tract and occurs in the colon. Herein, we explored the effect of two drugs in the treatment of CC. The present study aimed to predict and verify the effect of these two drugs in the treatment of CC. To explore the molecular mechanisms of the "HDW-AM" drug in the treatment of CC, we analyzed its principal efficiency in terms of ingredients, target spots, and pathways via network pharmacology, molecular docking, and experimental verification. The ingredients and their gene target sites were searched and screened through the TCMSP platform according to specific filtering conditions. Subsequently, components corresponding to the gene targets were chosen to construct the drug component-target network. The GEO (Gene Expression Omnibus) dataset was used to collect and screen for gene chips under CC and normal conditions, obtain differential genes, and construct a volcano map. The intersection genes between drug and disease targets were screened, the ".tsv" file was downloaded from the STRING platform and imported into Cytoscape 3.8.0 for visualization, a protein-protein interaction (PPI) network was constructed, the core targets were identified, and the common components with core targets were docked through Autodock Tools-1.5.6. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were carried out through the Metascape platform to determine the major pathways. The CCK-8 (Cell Counting Kit-8) assay verified the effect of AKT1 on cell proliferation after treatment with quercetin. After the screening, 3658 DEGs (1841 downregulated and 1817 upregulated) were obtained from the GSE75970 gene chip; 21 active components and 220 targets were identified from the drugs. Subsequently, ten core genes (including AKT1, P53, and CASP3) and six major components were screened. GO functional analysis and KEGG analysis revealed that "HDWAM" regulates cell migration and motility through the combination of a transcription regulator complex, membrane rafts, vesicle lumen, and protein kinases via the MAPK, PI3K-Akt, and IL- 17 signaling pathways. The molecular docking results suggested that quercetin binds to AKT1, TP53, TNF, and CASP3. HDW-AM may exert a therapeutic effect on CC by modulating AKT1, TP53, TNF, and CASP3 and through signaling pathways. A CCK-8 cytotoxicity assay verified that quercetin affects cell viability through AKT1. The current study provides a theoretical basis for an in-depth investigation into the molecular mechanism of the "HDW-AM" drug in CC treatment via network pharmacology, molecular docking, and experimental verification.

Colon cancer (CC) is a malignant tumor in the colon. Despite some progress in the early detection and treatment of CC in recent years, some patients still experience recurrence and metastasis. Therefore, it is urgent to better predict the prognosis of CC patients and identify new biomarkers. Recent studies have shown that anoikis-related genes (ARGs) play a significant role in the progression of many tumors. Hence, it is essential to confirm the role of ARGs in the development and treatment of CC by integrating scRNA-seq and transcriptome data. This study integrated transcriptome and single-cell sequencing (scRNA-seq) data from CC samples to evaluate patient stratification, prognosis, and ARG expression in different cell types. Specifically, differential expression of ARGs was identified through consensus clustering to classify CC subtypes. Subsequently, a CC risk model composed of CDKN2A, NOX4, INHBB, CRYAB, TWIST1, CD36, SERPINE1, and MMP3 was constructed using prognosis-related ARGs. Finally, using scRNA-seq data of CC, the expression landscape of prognostic genes in different cell types and the relationship between important immune cells and other cells were explored. Through the above analysis, two CC subtypes were identified, showing significant differences in prognosis and clinical factors. Subsequently, a risk model comprising aforementioned genes successfully categorized all CC samples into two risk groups, which also exhibited significant differences in prognosis, clinical factors, involved pathways, immune landscape, and drug sensitivity. Multiple pathways (cell adhesion molecules (CAMs), and extracellular matrix (ECM) receptor interaction) and immune cells/immune functions (B cell naive, dendritic cell activate, plasma cells, and T cells CD4 memory activated) related to CC were identified. Furthermore, it was found that prognostic genes were highly expressed in various immune cells, and B cells exhibited more and stronger interaction pathways with other cells. The results of this study may provide references for personalized treatment and potential biomarker identification in CC.

Objective: Here, we aimed to explore the effect of LBP in combination with Oxaliplatin (OXA) on reversing drug resistance in colon cancer cells through in vitro and in vivo experiments. We also aimed to explore the possible mechanism underlying this effect. Finally, we aimed to determine potential targets of Lycium barbarum polysaccharide (LBP) in colon cancer (CC) through network pharmacology and molecular docking.Methods: The invasion ability of colon cancer cells was assessed using the invasion assay. The migration ability of these cells was assessed using the migration assay and wound healing assay. Cell cycle analysis was carried out using flow cytometry. The expression levels of phosphomannose isomerase (PMI) and ATP-binding cassette transport protein of G2 (ABCG2) proteins were determined using immunofluorescence and western blotting. The expression levels of phosphatidylinositol3-kinase (PI3K), protein kinase B (AKT), B-cell lymphoma 2 (Bcl-2), and BCL2-Associated X (Bax) were determined using western blotting. Forty BALB/c nude mice purchased from Weitong Lihua, Beijing, for the in vivo analyses. The mice were randomly divided into eight groups. They were administered HCT116 and HCT116-OXR cells to prepare colon cancer xenograft models and then treated with PBS, LBP (50 mg/kg), OXA (10 mg/kg), or LBP + OXA (50 mg/kg + 10 mg/kg). The tumor weight and volume of treated model mice were measured, and organ toxicity was evaluated using hematoxylin and eosin staining. The expression levels of PMI, ABCG2, PI3K, and AKT proteins were then assessed using immunohistochemistry. Moreover, PMI and ABCG2 expression levels were analyzed using immunofluorescence and western blotting. The active components and possible targets of LBP in colon cancer were explored using in silico analysis. GeneCards was used to identify CC targets, and an online Venn analysis tool was used to determine intersection targets between these and LBP active components. The PPI network for intersection target protein interactions and the PPI network for interactions between the intersection target proteins and PMI was built using STRING and Cytoscape. To obtain putative targets of LBP in CC, we performed GO function enrichment and KEGG pathway enrichment analyses.Results: Compared with the HCT116-OXR blank treatment group, both invasion and migration abilities of HCT116-OXR cells were inhibited in the LBP + OXA (2.5 mg/mL LBP, 10 μΜ OXA) group (p < 0.05). Cells in the LBP + OXA (2.5 mg/mL LBP, 10 μΜ OXA) group were found to arrest in the G1 phase of the cell cycle. Knockdown of PMI was found to downregulate PI3K, AKT, and Bcl-2 (p < 0.05), while it was found to upregulate Bax (p < 0.05). After treatment with L. barbarum polysaccharide, 40 colon cancer subcutaneous tumor models showed a decrease in tumor size. There was no difference in the liver index after LBP treatment (p > 0.05). However, the spleen index decreased in the OXA and LBP + OXA groups (p < 0.05), possibly as a side effect of oxaliplatin. Immunohistochemistry, immunofluorescence, and western blotting showed that LBP + OXA treatment decreased PMI and ABCG2 expression levels (p < 0.05). Moreover, immunohistochemistry showed that LBP + OXA treatment decreased the expression levels of PI3K and AKT (p < 0.05). Network pharmacology analysis revealed 45 active LBP components, including carotenoids, phenylpropanoids, quercetin, xanthophylls, and other polyphenols. It also revealed 146 therapeutic targets of LBP, including AKT, SRC, EGFR, HRAS, STAT3, and MAPK3. KEGG pathway enrichment analysis showed that the LBP target proteins were enriched in pathways, including cancer-related signaling pathways, PI3K/AKT signaling pathway, and IL-17 signaling pathways. Finally, molecular docking experiments revealed that the active LBP components bind well with ABCG2 and PMI.conclusion: Our in vitro experiments showed that PMI knockdown downregulated PI3K, AKT, and Bcl-2 and upregulated Bax. This finding confirms that PMI plays a role in drug resistance by regulating the PI3K/AKT pathway and lays a foundation to study the mechanism underlying the reversal of colon cancer cell drug resistance by the combination of LBP and OXA. Our in vivo experiments showed that LBP combined with oxaliplatin could inhibit tumor growth. LBP showed no hepatic or splenic toxicity. LBP combined with oxaliplatin could downregulate the expression levels of PMI, ABCG2, PI3K, and AKT; it may thus have positive significance for the treatment of advanced metastatic colon cancer. Our network pharmacology analysis revealed the core targets of LBP in the treatment of CC as well as the pathways they are enriched in. It further verified the results of our in vitro and in vivo experiments, showing the involvement of multi-component, multi-target, and multi-pathway synergism in the drug-reversing effect of LBP in CC. Overall, the findings of the present study provide new avenues for the future clinical treatment of CC.

Hemochromatosis is a highly prevalent genetic disease associated with excessive iron accumulation in a variety of tissues in an age-dependent manner. In a majority of patients (&amp;gt;85%) with hemochromatosis, mutations in the iron-regulatory gene HFE are the cause. Iron, when present in excess, is an inducer of oxidative stress and suppresses mitochondrial function. Patients with hemochromatosis show evidence of colonic inflammation. Further, some studies have shown increased risk for colon cancer associated with genetic mutations known to cause hemochromatosis. Based on these findings in the literature, we hypothesized that hemochromatosis is an important determinant of disease progression in patients with colitis and colon cancer. We tested this hypothesis by comparing progression of experimentally induced colitis and colon cancer between wild type mice and Hfe-null mice, a model for hemochromatosis. We also compared the transcriptome profile between wild type and Hfe-null colonic epithelial cells. In addition, we analyzed fecal bacteria in wild type mice and Hfe-null mice because colonic microbiome is an important determinant of colonic inflammation and colon cancer. With dextran sulfate sodium-induced colitis, Hfe-null mice suffered more weight loss and exhibited more severe bleeding and diarrhea scores than wild type mice. With ApcMin-driven colon and intestinal cancer, Hfe-null mice had more polyps in the small intestine and colon than wild type mice. Transcriptome analysis showed that Hfe-null colonic epithelial cells, compared to wild type cells, had increased expression of the cytokines Ccl3 and Ccl5 and the interferon-stimulated gene 15 (ISG15 or Usp18), which are all known to promote inflammation and cancer. Hfe-null colonic epithelial cells also had decreased expression of Erdr1 (erythroid differentiation regulator 1), whose expression is known to suppress tumor cell proliferation, invasion, migration and metastasis. Analysis of fecal microbiome indicated that the prevalence of Bacteroidetes and Firmicutes decreased while that of Proteobacteria increased in Hfe-null mice compared to wild type mice, a finding particularly striking in male mice. These studies demonstrate that hemochromatosis enhances the progression of colonic inflammation and colon carcinogenesis. This conclusion is further supported by xenograft studies using the colon cancer cell line HCT116 with and without shRNA-induced downregulation of HFE. When HFE was silenced, there was a significant increase in the growth of HCT116 cells in mouse xenografts, demonstrating that inactivation of HFE promotes colon cancer progression. Based on these data, we conclude that the iron-overload disease hemochromatosis is a promoter of disease progression in colitis and colon cancer, and that use of iron chelators might have a logical basis for inclusion in therapeutic modalities in the treatment of colonic inflammation and colon cancer. Citation Format: Vadivel Ganapathy, Ashish Gurav, Jaya P. Gnanaprakasam, Ellappan Babu, Yangzom D. Bhutia, Cynthia Reinoso Webb, Matthew B. Grisham. The iron-overload genetic disease hemochromatosis potentiates colonic inflammation and colon carcinogenesis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1557. doi:10.1158/1538-7445.AM2015-1557

Objective: Colon cancer is a malignant neoplastic disease that seriously endangers the health of patients. Pulsatilla decoction (PD) has some therapeutic effects on colon cancer. This study is based on the analytical methods of network pharmacology and molecular docking to study the mechanism of PD in the treatment of colon cancer. Methods: Based on the Traditional Chinese Medicine Systems Pharmacology Database, the main targets and active ingredients in PD were filtered, and then, the colon cancer-related targets were screened using Genecards, OMIM, PharmGKB, and Drugbank databases. Then, the screened drug and disease targets were Venn analyzed to obtain the intersection targets. Cytoscape software was used to construct the “Components–Targets–Pathway” map, and the String database was used to analyze the protein interaction network of the intersecting targets and screen the core targets, and then, the core targets were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Molecular docking was implemented using AutoDockTools to predict the binding capacity for the core targets and the active components in PD. Results: Sixty-five ingredients containing 188 nonrepetitive targets were screened and 180 potential targets of PD anticolon cancer were identified, including 10 core targets, namely, MAPK1, JUN, AKT1, TP53, TNF, RELA, MAPK14, CXCL8, ESR1, and FOS. The results of GO analysis showed that PD anticolon cancer may be related to cell proliferation, apoptosis, energy metabolism, immune regulation, signal transduction, and other biological processes. The results of KEGG analysis indicated that the PI3K-Akt signaling pathway, MAPK signaling pathway, proteoglycans in cancer, IL-17 signaling pathway, cellular senescence, and TNF signaling pathway were mainly involved in the regulation of tumor cells. We further selected core targets with high degree values as receptor proteins for molecular docking with the main active ingredients of the drug, including MAPK1, JUN, and AKT1. The docking results showed good affinity, especially quercetin. Conclusion: This study preliminarily verified that PD may exert its effect on the treatment of colon cancer through multi-ingredients, multitargets, and multipathways. This will deepen our understanding of the potential mechanisms of PD anticolon cancer and establish a foundation for further basic experimental research.

Traditional Chinese medicine (TCM) has been utilized for the treatment of colon cancer. Qizhen decoction (QZD), a potential compound prescription of TCM, possesses multiple biological activities. It has been proven clinically effective in the treatment of colon cancer. However, the molecular mechanism of anticolon cancer activity is still not clear. This study aimed to identify the chemical composition of QZD. Furthermore, a collaborative analysis strategy of network pharmacology and cell biology was used to further explore the critical signaling pathway of QZD anticancer activity. First, ultraperformance liquid chromatography–quadrupole time-of-flight/mass spectrometry (UPLC–Q-TOF/MS) was performed to identify the chemical composition of QZD. Then, the chemical composition database of QZD was constructed based on a systematic literature search and review of chemical constituents. Moreover, the common and indirect targets of chemical components of QZD and colon cancer were searched by multiple databases. A protein–protein interaction (PPI) network was constructed using the String database (https://www.string-db.org/). All of the targets were analyzed by Gene Oncology (GO) bioanalysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and the visual network topology diagram of “Prescription–TCM–Chemical composition–Direct target–Indirect target–Pathway” was constructed by Cytoscape software (v3.7.1). The top molecular pathway ranked by statistical significance was further verified by molecular biology methods. The results of UPLC–Q-TOF/MS showed that QZD had 111 kinds of chemical components, of which 103 were unique components and 8 were common components. Ten pivotal targets of QZD in the treatment of colon cancer were screened by the PPI network. Targets of QZD involve many biological processes, such as the signaling pathway, immune system, gene expression, and so on. QZD may interfere with biological pathways such as cell replication, oxygen-containing compounds, or organic matter by protein binding, regulation of signal receptors or enzyme binding, and affect cytoplasm and membrane-bound organelles. The main antitumor core pathways were the apoptosis metabolic pathway, the PI3K–Akt signal pathway, and so on. Expression of the PI3K–Akt signal pathway was significantly downregulated after the intervention of QZD, which was closely related to the inhibition of proliferation and migration of colon cancer cells by cell biology methods. The present work may facilitate a better understanding of the effective components, therapeutic targets, biological processes, and signaling pathways of QZD in the treatment of colon cancer and provide useful information about the utilization of QZD.

Nanoparticles are materials having one of the dimensions in the range of 1–100 nm (Hussain et al., 2016). The development of efficient green chemistry methods using plants for synthesis of well-characterized nanoparticles has become a major focus of researchers. Nanoparticles produced by plants are more stable and more various in shape and size (Iravani, 2011). It has been shown that silver nanoparticles (AgNPs) preparation by green synthesis have significant advantages over conventional methods by chemical agents that are toxic to environment (Sharma, et al., 2009). AgNPs have significant place in nanotechnology because of their exceptional biological properties, and hence applications (Rafique et al., 2017). Various plant extracts have been used to synthesize AgNPs (Li et al., 2007; Srikar et al., 2016; Mussin et al., 2021). Although various plant components have been used as potential agents for green synthesis of AgNPs, synthesizing stable and widely applicable AgNPs is a challenge to the researchers (Srikar et al., 2016).Colon cancer is one of the leading tumors worldwide and the numbers of new cases of colon cancer is increasing rapidly. The incidence and mortality of colon cancer have been increasing during recent years even in the young adults below the age of 50 (Ahmed, 2020). Colon cancer is a neoplasm of an epithelial origin that increases exponentially with age (Jensen, 2019). Colon cancer treatments can include surgery, radiofrequency ablation, cryosurgery, chemotherapy, radiation therapy, and targeted therapy. Newer cytotoxic chemotherapies and novel biologic agents have been investigated to be applied for colon cancer treatment. Despite significant advanced in colon cancer treatment, it still causes considerable morbidity and mortality due to unsuccessful therapy (Segal and Saltz, 2009; Chakrabarti et al., 2020).Recently AgNPs have gained considerable attention for use in cancer therapy. It has been shown that AgNPs have suppressive effects against colon tumor mediated by cell apoptosis and mitochondrial dysfunction (Gurunathan et al., 2018). AgNPs synthesized from leaf extract of Vitex negundo L. has been reported to have cytotoxic effects of on human colon cancer cell line HCT15 (Prabhu et al., 2013). Green synthesized AgNPs have also anticancer effects on human neonatal skin stromal cells (hSSCs) and colon cancer cells (HT115) in vitro (AlSalhi et al., 2016). In this study we investigated the cytotoxic effects of green synthesized AgCl2 nanoparticles on colon cancer (SW480) cells in vitro. Onopordum acanthium extract was used to synthesize AgCl2 nanoparticles. Onopordum acanthium was applied traditionally as bactericide and antitumor agent (Al-Snafi, 2020). Colon cancer (SW480) cell line was purchased from Pasteur Institute of Iran and cultured growth medium until they reached 80-90% confluence. The cells were then treated with different concentrations (1.5625, 3.125, 6.25, 12.5, 25 and 50 μg/ml) of AgCl2 nanoparticle for 24 hours. MTT assay was used to measure cytotoxicity of AgCl2 nanoparticles against SW480 cells. Cell viability significantly decreased in SW40 cells treated with 6.25, 12.5, 25 and 50 μg/ml of AgCl2 nanoparticle. Our findings indicated that green synthesized AgCl2 nanoparticles have cytotoxic effects against colon cancer (SW480) cells in vitro.

Introduction: The prevalence of colon cancer remains high across the world. The early diagnosis of colon cancer is challenging. Moreover, patients with colon cancer frequently suffer from poor prognoses. Methods: Differentially expressed genes (DEGs) in colon cancer were acquired based on TCGA-COAD dataset screening. DEGs were input into the Connectivity Map (CMap) database to screen small molecule compounds with the potential to reverse colon cancer pathological function. Glycitein ranked first among the screened small-molecule compounds. We downloaded the main targets of glycitein from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database and constructed protein-protein interaction (PPI) networks of those which were closely related to targets by the Search Tool for the Retrieval of Interaction Gene/Proteins (STRING). Five potential targets of glycitein for treating colon cancer were identified (CCNA2, ESR1, ESR2, MAPK14, and PTGS2). These targets were used as seeds for random walk with restart (RWR) analysis of PPI networks. Then, the interaction network of glycitein-colon cancer-related genes was constructed based on the top 50 genes in affinity coefficients. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on the potential genes targeted by glycitein in colon cancer treatment and those that were closely bound up with targets. Results: GO analysis demonstrated that the enrichment of these genes was primarily discovered in biological functions including regulation of fibroblast proliferation, response to oxygen levels, and epithelial cell proliferation. The KEGG analysis results illustrated that the signaling pathways where these genes were mostly involved consisted of the mitogen-activated protein kinase signaling pathway, the phosphatidylinositol-3-kinase-Akt signaling pathway, and the p53 signaling pathway. Finally, stable binding of glycitein to five potential targets in colon cancer was verified by molecular docking. Conclusion: This study elucidated the key targets and main pathways of glycitein on the basis of network pharmacology and preliminarily analyzed molecular mechanisms in the treatment of colon cancer. A scientific basis is provided for glycitein application in treating colon cancer.

Sishen Wan suppresses colon cancer through dual inhibition of PI3K/AKT/mTOR and STAT3-mitophagy pathways: Network pharmacology and experimental validation.

Objective To explore the mechanisms of ursolic acid for treating colon cancer based on network pharmacology. Method In this study, the potential targets of ursolic acid against colon cancer were predicted and screened through the TCMSP, SYMMAP, Drug Bank, UNI-PROT, and DISGENET databases. The protein interaction (PPI) network was constructed based on the STRING database, and graphs were drawn with the help of Cytoscape software. GO and KEGG enrichment analyses were performed on the targets by using the DAVID database for biological information annotation. Results Ursolic acid has 113 targets in the treatment of colon cancer. The core targets included interleukin-6 (IL-6), mitogen-activated protein kinase 3 (MAPK3), vascular endothelial growth factor receptor (VEGFA), prostaglandin endoperoxide synthase 2 (PTGS2), caspase-3 (CASP3), mitogen-activated protein kinase 8 (MAPK8), tumor necrosis factor (TNF), cyclin D1 (CCND1), JUN, signal transducer and transcriptional activator 3 (STAT3), and other targets. The first 10 pathways related to colon cancer were screened out. The main signaling pathways included the TNF signaling pathway and the AGE-RAGE signaling pathway in diabetic complications and human colon cancer infections. Conclusion This study revealed that ursolic acid played a multitarget and multichannel antitumor role by inhibiting the proliferation of tumor cells, inducing apoptosis, and enhancing antiangiogenesis.

According to a recent report by GLOBOCAN, colorectal cancer is the third most common and second most deadly cancer in 2020. In our previous proteomic study, we found that the expression of GSTM2 in colon tissues was significantly lower than that in para-cancer tissues, and its lower expression was associated with reduced overall survival rate of patients, suggesting that this gene might play a role in the occurrence of colon cancer. As a member of the detoxifying enzyme family, GSTM2 is likely to play an important role in the initiation of tumors. Whereas, the functions of GSTM2 in colon cancer are barely known. In this study, using the RNA-Seq datasets of colon cancer patients from public database (ntumor = 457, nnormal = 41), we confirmed the reduced expression of GSTM2 and its prognostic value in colon cancer. Furthermore, we used our own Chinese cohort (ntumor = 100, nnormal = 72) verified the lower GSTM2 expression in colon cancer, and also its effects on patient prognosis. Subsequently, we uncovered two potential reasons for the lower expression of GSTM2 in colon cancer tissues, including the deep deletion of GSTM2 on genome, and the up-regulation of RAD21 or SP1. Moreover, we disclosed that GSTM2 might be involved in several immune-related pathways in colon cancer, such as chemokine signaling and leukocyte transendothelial migration. Finally, we revealed that the GSTM2 expression was closely related to the immune-related scores of colon cancer and the infiltration ratios of various immune cells, suggesting that GSTM2 might regulate the development of colon cancer by modulating immune microenvironment. In conclusion, we uncovered the prognostic value of GSTM2 based on the public data and our own data, revealed its potential regulatory role in tumor immune microenvironment, and disclosed the probable reasons for its lower expression in colon cancer. The findings of our study provide a potential prognostic biomarker and drug target for clinical diagnosis and treatment of colon cancer.

SH3 and multiple ankyrin repeat domains protein 1 (SHANK1) belongs to a family of postsynaptic scaffolding proteins. In this study, we found that SHANK1 was abnormally high expressed in colon cancer tissues compared to normal tissues. Colon cancer patients with low SHANK1 expression had better prognosis. Furthermore, the expression of SHANK1 was knocked down in human colon cancer cell lines HCT116 and HT29 and the role of SHANK1 was investigated in colon cancer tumorigenesis. Our results showed that the knockdown of SHANK1 inhibited the survival and proliferation of both cells. The migration of these two cell lines was significantly reduced and the apoptosis was induced compared with control cells. The Bax/Bcl-2 ratio in both cell lines that SHANK1 was knocked down was increased, which is a signal that the mitochondrial apoptotic pathway was triggered. In addition, we observed that knockdown of SHANK1 reduced the expression of phosphorylated forms of AKT and mTOR. These data suggested that loss of SHANK1 inhibited viability and induced apoptosis of HCT116 and HT29 cells through the AKT/mTOR signaling pathway. Our data revealed that SHANK1 played important roles in the growth of colon cancer cells and may be used as a novel strategy for colon cancer therapy. SIGNIFICANCE OF THE STUDY: Herein, we reported that SHANK1 was abnormally high expressed in colon cancer tissues and associated with worse prognosis of patients. In addition, knockdown of SHANK1 inhibited viability and induced apoptosis in colon cancer cell lines through AKT/mTOR signaling pathways. These data suggest that SHANK1 may be a new oncogene in colon cancer. This study reveals the role of SHANK1 in addition to neuronal development and cognitive development. And it provides a new potential target for the prediction and treatment of colon cancer.

The lncRNA MALAT1 has multiple biological functions, including influencing RNA processing, miRNA sponging, and cancer development. It is acknowledged that miR663a and its targets are inflammation-related genes frequently deregulated in many cancers. The associations between MALAT1 and miR663a and their target genes remain unknown. In this study, it was found that in colon cancer (CC) cells, MALAT1 and miR663a were reciprocally repressed in cDNA array screening and qRT-PCR analysis. However, MALAT1 was significantly upregulated in CC tissues, and miR663a was significantly downregulated relative to the corresponding surgical margin (SM) tissues. An inverse relationship between MALAT1 and miR663a expression was detected among CC tissue samples (n = 172, r = −0.333, p < 0.0001). The RNA-pulldown results showed MALAT1 lncRNA–miR663a binding. The results of luciferase-reporter analysis further revealed that the MALAT1 7038–7059 nt fragment was the miR663a seed sequence. Both miR663a knockdown and MALAT1 activation alone significantly upregulated the expression levels of miR663a targets, including TGFB1, PIK3CD, P53, P21, and JUND, in the CC cell lines HCT116 and SW480. A positive relationship was also observed between the expression levels of MALAT1 and these miR663a targets in the above 172 CC samples and 160 CC samples in publicly available databases. In addition, reciprocal abolishment of the effects of miR663a overexpression and MALAT1 activation on the proliferation, migration, and invasion of cancer cells was also observed, while miR663a upregulation and MALAT1 activation alone inhibited and promoted the behaviors of these CC cell lines, respectively. All these suggested that, as a competing endogenous lncRNA, MALAT1 maybe a dominant protector for the degradation of miR663a targets. miR663a and MALAT1 may consist of a negative feedback loop to determine their roles in CC development.

The treatment of colon cancer (CC) with chemotherapeutics presents significant burden for the patients due to high toxicity and relatively low response. The present review introduces recent updates on global incidence, mortality, screen approaches and adjuvant regimens as well as medicinal plant extracts and their marker compounds as adjuvants for CC. We present the cellular mechanisms and pathways that promote metastasis of CC cells and their colonization in the liver and lungs. This review describes a regulatory loop between the Wnt, Myc, and long non-coding RNAs in promoting metastasis of CC cells. It also identifies the anticancer effects of promising natural compounds mainly on CC cell lines, tumor-bearing animal models and in a clinical trial. This review describes the mechanisms of action of promising polyphenols, flavonoids, terpenes, and alkaloids in the modulation of the metastasis of CC cells to the liver and lung. We also present promising natural compounds that target the Wnt signaling and its target genes in CC. We report few animal and human clinical trials on natural compounds that are evaluated for mitigating CC. The relevance of natural compounds as an adjuvant in monotherapy or combination therapy of CC is discussed. Overall, we provide an overview of natural compounds in CC therapy with future directions.