Lenvatinib Improves the Relative Abundance of Probiotics in Intestinal Flora of Patients with Primary Liver Cancer

Lenvatinib Improves the Relative Abundance of Probiotics in Intestinal Flora of Patients with Primary Liver Cancer | 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 Research Article Lenvatinib Improves the Relative Abundance of Probiotics in Intestinal Flora of Patients with Primary Liver Cancer Xin Chai, Yue Tang, Ximeng Li, Shansi Zou, Xutao Guan, Wenqiao Zang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4024621/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 Background Lenvatinibis commonly used systemic therapeutic drugs for patients with advanced Primary Liver Cancer (PLC). Recent studies have found that gut microbiota can regulate the efficacy of anti-tumor drugs. However, the relationship between antiangiogenic drugs and intestinal flora is not clear, and there is no relevant clinical research. Methods We investigated Lenvatinib's impact on PLC patients' intestinal flora. Fecal samples from pre- and post-treatment PLC patients were analyzed via 16S rRNA Illumina sequencing. Results Notably, Bifidobacterium, Coprococcus, and other genera varied between groups at the genus level. The relative abundance of probiotics (Bifidobacterium, Coprococcus) significantly rose post-treatment. The Lefse analysis revealed significant differences. Following Lenvatinib treatment, PLC patients exhibited 12 biomarkers, including Clostridia, Bifidobacterium, Bifidobacteriaceae, Bifidobacteriales, Faecalibacterium, Butyricicoccus, Butyricicoccaceae, Ruminococcaceae-uncultured, Ruminococcaceae-Incertae_Sedis, Lachnospiraceae_NK4A136_group, Ruminococcaceae, and Lachnospiraceae_UCG_010. Conclusions Lenvatinib increased the relative abundance of probiotics in PLC patients' intestinal flora, suggesting therapeutic implications. gut microbiome primary liver cancer Lenvatinib probiotics 16S rRNA sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The incidence rate of primary liver cancer is high worldwide. The main causes of primary liver cancer in China are chronic hepatitis virus (mainly hepatitis B virus and hepatitis C virus) infection, cirrhosis, long-term drinking, nonalcoholic liver disease, aflatoxin exposure and genetic factors( 1 ). Early symptoms are often atypical, making detection without regular check-ups challenging. Patients typically present with symptoms such as pain, abdominal distension, anorexia, jaundice, and emaciation, indicating advanced stage PLC, severely impacting their quality of life and health. In systemic PLC therapy, Lenvatinib not only inhibits tumor angiogenesis, reducing tumor burden via the VEGR/VEGFR signaling pathway( 2 ) but also acts as an efficient immunomodulator. Due to its efficacy and manageable side effects, Lenvatinib finds widespread clinical use. Studies suggest specific intestinal microorganisms influence tumor occurrence and response to anti-tumor treatments, potentially acting as tumor suppressors or promoters( 3 , 4 ). Intestinal flora modulates the efficacy of antitumor drugs and reduces adverse reactions to treatments like oxaliplatin, cyclophosphamide, and immune checkpoint inhibitors (PD-1/PD-L1 and CTLA4 inhibitors)( 5 ). However, the relationship between targeted antiangiogenic drugs like Lenvatinib and intestinal flora remains unclear, with limited clinical research and reports. This study thus investigates the connection between Lenvatinib and intestinal flora in liver cancer patients, aiming to identify potential microbial markers for predicting Lenvatinib efficacy. Methods Experimental Subject Patients with BCLC stage C PLC who were treated with Lenvatinib in the First Affiliated Hospital of Henan University of traditional Chinese medicine from July 2020 to December 2021 were enrolled as the experimental objects. Clinical research program and informed consent have been approved by the Ethics Management Committee of the First Affiliated Hospital of Henan University of Chinese Medicine (approval number: 2019HL-157). The experimental group was divided into two groups: the control group before Lenvatinib treatment (PV1) and the experimental group after treatment (at least 3 weeks after Lenvatinib treatment) (PV2). 3 weeks is a treatment cycle, 1 cycle of Lenvatinib treatment is Time1 group, and 2 cycles of Lenvatinib treatment is Time2 group. Inclusion criteria ( 1 ) Patients with stage C PLC according to Barcelona clinical liver cancer (BCLC) staging; ( 2 ) Those who have previously received systematic first-line treatment (except for Lenvatinib) or have not received first-line treatment; ( 3 ) Age ≥ 18 years, life expectancy > 3 months; ( 4 ) The PS score was 0–2 points within 7 days before the first administration of the research drug; ( 5 ) Have adequate organ function. Exclusion criteria ( 1 ) have occurred esophageal or gastric varices bleeding or other hemorrhagic diseases and bleeding tendencies in the past six months; ( 2 ) taking antibiotics, probiotics or microbial agents within one month; ( 3 ) Patients with a history of intestinal diseases or diarrhea-prone diseases, combined or concurrent other diseases affecting the results of this study; ( 4 ) Female patients during pregnancy and lactation; ( 5 ) Patients with severe allergy to research intervention and / or any of its accessories (≥ 3 levels). Twenty-two patients with good adherence were selected from the enrolled patients to undergo dynamic testing for 2 cycles of Lenvatinib dosing, and we explored the effect of Lenvatinib on the intestinal flora of PLC patients. Stool samples shall be taken 1–4 days before Lenvatinib treatment and at least 3 weeks after treatment, frozen at − 80℃ and marked. Sequencing and Analysis of Microbial 16s rRNA DNA was extracted from all fecal specimens frozen at − 80°C using nucleic acid extractant (Hangzhou guheinfo: GHFDE100). The DNA concentration was determined using NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and agarose gel electrophoresis was performed. The corresponding primers of 16S V4 region: 515F(GTGCCAGCMGCCGCGGTAA)-806R༈GGACTACHVGGGTWTCTAAT༉ were selected for PCR amplification. The PCR products were purified by AMPure XP Beads (Beckman Coulter, Indianapolis, IN). Qubit was used for library quantification, and Illlumina NovaSeq platform was used for sequencing. After quality control and filtering, the sequences were clustered and annotated. Alpha diversity and Beta diversity were compared, species difference between groups was analyzed, and metagenomic function was predicted. Statistical Analysis The data were processed and analyzed by SPSS 26.0 statistical software. The Alpha diversity index of intestinal flora was tested by rank sum test, and the Beta diversity was analyzed by Anosim and NMDS (Nonmetric Multidimensional Scaling). The species difference between groups was analyzed by Kruskal-Wallis, Var test and one-way ANOVA, and the species markers were analyzed by Lefse. Two-tailed values of P of less than 0.05 and LDA (Linear discriminant analysis) score more than 2 were considered as statistically significant. Results Distribution and Diversity of Intestinal Flora in two groups of Patients with PLC A total of 43 fecal specimens from PLC patients were collected. Based on the Venn Diagram of OUT (operational taxonomic unit), there were 76 unique OTUs in PV1 group and 522 unique OTUs in PV2 group. The overlapping area represented a total of 1127 OTUs in the two groups (Fig. 1 A). The intestinal flora diversity in the group after Lenvatinib treatment was richer than those in the group before treatment (Fig. 1 B). The Shannon, Simpson and Chao indices in the PV2 group were all higher than those in the PV1 group. The Alpha diversity of the intestinal flora in patients with PLC after Lenvatinib treatment was higher than that before treatment, but the difference was not statistically significant( P >0.05). The results of Beta diversity Anosim analysis were consistent (Fig. 1 C, D), with R > 0, indicating that the sample difference between the two groups was greater than that within the group, P > 0.05, indicating that the difference was not statistically significant. The results of NMDS showed that red dots and blue dots were intertwined in the same range, and were not distributed in specific areas, suggesting that the intestinal flora structure of patients before and after treatment with Lenvatinib was similar (Fig. 1 E). Column Diagram of Species Composition between groups Based on the species abundance table, the species composition of two groups of PLC samples was analyzed at phylum, class, order, family, and genus classification levels (Fig. 2 A, B, C, D, E). The composition of intestinal flora in the two groups was similar at each classification level, but the abundance of intestinal flora was different. The differences in flora composition and abundance between the two groups of specimens are described from phylum, family and genus levels (Fig. 2 A, D, E). According to the species composition statistics of the two groups of samples at the phylum level ((Fig. 2 A), the bacteria of the two groups mainly include Firmicutes, Bacteroidota, Proteobacteria, Actinobacteriota, Desulfobacterota,Verrucomicrobiota,Fusobacteriota, etc. Among them, Bacteroidota, Proteobacteria, Desulfobacterota, Verrucomicrobiota decreased the relative abundance of bacteria in patients after treatment compared with those before treatment. Firmicutes and Actinobacteriota were the bacteria with higher relative abundance in the intestinal flora of patients in the post-medication group than those in the pre-medication group. At family level ((Fig. 2 D), the relative abundance of Bacteroidaceae, Lachnospiraceae, Ruminococcaceae, Streptococcaceae, Selenomonadaceae, Bifidobacteriaceae and Lactobacillaceae in PV2 group was higher than that in PV1 group. The relative abundance of Enterobacteriaceae, Veillonellacese and Prevotellaceae in PV2 group was lower than that in PV1 group. At genus level (Fig. 2 E), the top ten species with relative abundance in the two groups were:Bacteroides,Veillonella,Escherichia – Shigella,Prevotella,Streptococcus,Megamonas,Faecalibacterium,Subdoligranulum,Bifidobacterium,Eisenbergiella.Among them, Bacteroides, Veillonella, Escherichia – Shigella, Prevotella and eisenbergiella in PV2 group were lower than those in PV1 group Streptococcus, megamonas, faecalibacterium, subdoligranulum and Bifidobacterium were higher in PV2 group than in PV1 group. Species Difference Analysis and Biomarkers between two groups At the genus level, Bifidobacterium, Coprococcus, Lachnospiraceae _ NK4A136 _ group, Lachnospiraceae _ UCG-010, Butyricicoccus, and Faecalibacterium were the different intestinal flora of PLC patients (Fig. 3 A). The relative abundance of Bifidobacterium and Faecalibacterium in the PV2 group was significantly higher than that in the PV1 group, and the difference was statistically significant (Fig. 3 B). Lefse results showed significant differences. Biomarkers in PLC group after Lenvatinib treatment were Clostridia, Bifidobacterium, Bifidobacteriaceae, Bifidobacteriales, Faecalibacterium, Butyricicoccus, Butyricicoccaceae, Ruminococcaceae-uncultured, Ruminococcaceae-Incertae_Sedis, Lachnospiraceae_NK4A136_group, Ruminococcaceae, Lachnospiraceae_UCG_010 12 kinds in total (Fig. 3 C, D). Picrust2 Functional Prediction Analysis and Random Forest inter group Prediction By analyzing the metagenomic function of intestinal flora in PLC Patients, there was significant difference in KEGG function between the two groups of PLC samples, that is, the relative abundance of ko00121 Secondary bile acid biosynthesis and ko00120 Primary bile acid biosynthesis increased after Lenvatinib treatment (Fig. 4 A). At the family level, it reflects the characteristics that play a major role in the classification effect in the classifier, from large to small according to importance. The area under ROC curve was 75% (Fig. 4 B). Dynamic monitoring of intestinal flora changes in PLC patients treated with Lenvatinib Twenty-two patients with good adherence were selected from the enrolled patients to undergo dynamic testing for 2 cycles of Lenvatinib dosing, and we explored the effect of Lenvatinib on the intestinal flora of PLC patients. 3 weeks is a treatment cycle, 1 cycle of Lenvatinib treatment is Time1 group, and 2 cycles of Lenvatinib treatment is Time2 group. The Venn diagram of OUT illustrates the intersection of microbial categories between the two groups (Fig. 5 A). Comparative analysis revealed 149 unique OTUs in the Time1 group and 133 unique OTUs in the Time2 group, with a total of 1606 OTUs shared between the two groups. The microbial categories in the Time1 group were slightly more diverse than those in the Time2 group. The alpha diversity indices between the two groups showed the following results (Fig. 5 B). All three indices had P-values greater than 0.05, indicating no statistically significant differences in the alpha diversity of gut microbiota between the two treatment cycles of Lenvatinib in patients with PLC. In NMDS analysis (Fig. 5 C), each point represents a sample, where red indicates samples from the Time1 group and blue represents samples from the Time2 group. With a stress value of 0.0815, red and blue points intermingle within the same region, without distinct separation into specific areas. This suggests that the intestinal microbiota structure between patients undergoing two cycles of Lenvatinib treatment remains similar. The taxonomic composition of the two groups of samples was analyzed at the genus level (Fig. 5 D). The top ten species based on relative abundance in both groups were identified as follows: Bacteroides, Veillonella, Escherichia – Shigella, Prevotella, Akkermansia, Faecalibacterium, Subdoligranulum, Eisenbergiella, Agathobacter, and Bifidobacterium. Among these, the relative abundance of Akkermansia, Escherichia – Shigella, and Subdoligranulum decreased in the Time2 group compared to the Time1 group. Conversely, the relative abundance of Veillonella, Eisenbergiella, and Agathobacter increased in the Time2 group compared to the Time1 group. Tukey test is one of the multiple comparison methods applicable to situations with k treatment groups and equal sample sizes. It results achieve a confidence level of 95%. At the genus level, there is a statistically significant increase in the relative abundance of Veillonella in the Time2 group compared to the Time1 group (Fig. 5 E), a finding consistent with the results (Fig. 5 F). Each color represents a patient. The data suggest a significant increase in the relative abundance of Veillonella in the Time2 group compared to the Time1 group within the same patient. Discussion The gastrointestinal tract and liver exhibit close anatomical and functional connections, forming the intestinal-liver axis characterized by bidirectional interactions between intestinal microorganisms, their derivatives, and the liver. Intestinal flora plays a crucial role in human health and disease. Imbalances in intestinal flora, influenced by the gut-liver axis, significantly contribute to liver cancer pathogenesis. This imbalance is primarily associated with reduced populations of short-chain fatty acid (SCFA)-producing bacteria( 6 ), alterations in bile acid composition( 7 , 8 ), activation of alcohol-induced immune responses, lipopolysaccharide responses, choline deficiency, and other related factors( 9 ). Gut microbiota metabolites may play a role in regulating liver inflammation and immunity, thereby influencing the progression of hepatocellular carcinoma (HCC) induced by nonalcoholic steatohepatitis (NASH)( 10 ) and hepatitis virus infections( 11 ). Pathogens and probiotics exert influence on the human immune microenvironment through complex metabolic mechanisms and interactions with the host, potentially serving as biomarkers in anti-tumor therapy. Fecal samples collected from hepatocellular carcinoma (HCC) patients across East, Central, and Northwest China revealed decreased levels of butyrate-producing and lipopolysaccharide (LPS)-producing bacteria in early HCC patients, suggesting gut microbes could serve as non-invasive biomarkers for early HCC detection( 12 ). However, further research across diverse patient groups and underlying conditions is necessary.Studies have shown increased abundance of Bacteroides and Rumenococcus, and decreased levels of Bifidobacterium in liver cancer patients( 13 ). Notably, as HCC progresses, Bifidobacterium levels decrease significantly while Enterococcus levels rise. Bifidobacterium, a Gram-positive anaerobic bacterium and a physiological probiotic, helps maintain intestinal microecological balance, enhances host immune responses against tumors, and boosts immune function. In our study, the abundance of Bifidobacterium in PLC patients post-Lenvatinib treatment was higher than pre-treatment levels, suggesting its potential as a microbial marker for Lenvatinib efficacy. This highlights Lenvatinib's regulatory effect on intestinal microecology and its anti-tumor properties. Bifidobacterium, a key component of probiotics, is widely used both clinically and in daily life. Probiotic mixtures containing Bifidobacterium demonstrate anti-inflammatory effects on HT-29 cells by regulating JAK/STAT and NF-κB pathways( 1 ), hinting at its potential in treating neonatal cholestasis( 14 ). In our study, we observed an increase in the abundance of Faecalibacterium in liver cancer patients after treatment with Lenvatinib. Faecalibacterium prausnitzii, a significant butyrate-producing strain within the genus Fecalibacterium, was particularly noted. Butyrate, a short-chain fatty acid, plays a crucial role in enhancing the integrity and immunity of the intestinal mucosal epithelial barrier. Research( 15 ) indicates that the butyrate produced through F. prausnitzii metabolism helps maintain the balance between Th17 and Treg cells, exerting an intrinsic anti-inflammatory effect in animal models of colorectal colitis. This effect occurs through the inhibition of HDAC1, which promotes Foxp3 expression and blocks the downstream IL-6/STAT3/IL-17 signaling pathway. These findings suggest that F. prausnitzii may offer novel avenues for further investigation into the treatment of inflammatory bowel disease. The targeted butyrate-HDAC1-T cell axis emerges as a promising approach for the treatment of inflammatory diseases. The abundance of F. prausnitzii in the intestinal flora of patients with colorectal cancer, Crohn's disease, and ulcerative colitis was found to be lower than that of healthy controls ( P < 0.001)( 16 ). Studies( 17 ) have demonstrated a decrease in the abundance of fecal bacilli in breast cancer patients. F. prausnitzii has been shown to inhibit the proliferation and invasion of breast cancer (BC) cells by suppressing the IL-6/STAT3 pathway and promoting apoptosis of breast cancer cells. Additionally, F. prausnitzii may serve as a prognostic biomarker for evaluating overall survival (OS) in breast cancer patients. Patients with a high abundance of F. prausnitzii in colorectal cancer tend to have longer overall survival after surgery. Conversely, high abundance of F. nucleatum and B. fragilis serves as independent indicators of poor prognosis in colorectal cancer patients( 18 ). The presence of F. prausnitzii has been associated with enhanced efficacy of immune checkpoint inhibitors in patients with melanoma( 19 ). We observed a significant difference in KEGG function between the two groups of PLC samples, specifically, the relative abundance of ko00121 Secondary bile acid biosynthesis and ko00120 Primary bile acid biosynthesis increased after Lenvatinib treatment. Bile acids (BAs) are primarily synthesized through cholesterol metabolism in the liver. The classical pathway involves the production of primary bile acids (PBAs), such as chenodeoxycholic acid (CDCA) and cholic acid (CA), through a series of enzymatic reactions involving cytochrome P450 family 7 subfamily A member 1 (CYP7A1). PBAs are stored in the gallbladder with bile and enter the intestine following food stimulation, where they are converted by microorganisms into secondary bile acids (SBAs), including deoxycholic acid (DCA) and lithocholic acid (LCA). Over 95% of bile acids are reabsorbed at the terminal ileum and transported back to the liver through the portal vein( 20 ), constituting the gut-liver cycle of bile acids( 20 ). Bile acid metabolism involves intricate interactions between host and microbial communities. In a mouse model of ulcerative colitis( 21 ), a significant reduction in Ruminococcaceae was observed, along with lower levels of deoxycholic acid (DCA) and lithocholic acid (LCA) compared to the control group. Ruminococcaceae and Lachnospiraceae can convert primary bile acids into secondary bile acids through 7α-dehydroxylation. The decrease in Ruminococcus is believed to be significantly associated with the decrease in secondary bile acid (SBA) levels. Intestinal microbiota disorders in inflammatory bowel disease can lead to SBA deficiency and promote intestinal inflammation, which can be addressed by supplementing exogenous SBAs.Butyricicoccaceae emerged as a potential microbial marker of Lenvatinib in this experimental group and was found to be associated with bile acid metabolism( 22 ). In a study( 23 ) analyzing bile acid-related metabolomics and metagenomics in diarrhea-predominant irritable bowel syndrome (IBS-D) group, it was revealed that microbial communities rich in Clostridia were closely linked to excessive bile acid biosynthesis and excretion. Furthermore, through a series of animal and cell experiments, it was clarified that Clostridium-rich microbial groups could induce excessive bile acid excretion by targeting intestinal feedback mechanisms to regulate bile acid synthesis. Based on the literature and the results of this experiment, Clostridia, as one of the differential intestinal microbes in PLC after Lenvatinib treatment, may be associated with the adverse reactions of diarrhea caused by Lenvatinib. The balance of intestinal flora is intricately linked to health and disease. Flora imbalance can promote tumor occurrence, while tumor progression can exacerbate the imbalance, creating a vicious cycle. The composition of human gut microbiota is influenced by various factors including diet, lifestyle, antibiotics, environment, and disease( 24 ). Regulation of gut microbiota for cancer therapy can be achieved through interventions such as antibiotics( 25 ), probiotics( 26 ), prebiotics( 27 ), fecal microbiota transplantation (FMT)( 28 ), and microbiota metabolites. These approaches hold promise in modulating the gut microbiota to improve cancer treatment outcomes. In this study, it was observed that Lenvatinib could influence the intestinal flora of patients with liver cancer. The administration of Lenvatinib led to an increase in the abundance of beneficial bacteria in the intestinal flora while reducing the abundance of certain pathogenic bacteria. This suggests an interaction between Lenvatinib, alterations in the intestinal flora of liver cancer patients, and anti-tumor immune regulation. These associations may offer insights into the efficacy and safety of Lenvatinib monotherapy or combination therapy for liver cancer, presenting a novel adjuvant treatment option. Declarations Ethics approval and consent to participate Clinical research program and informed consent have been approved by the Ethics Management Committee of the First Affiliated Hospital of Henan University of Chinese Medicine (approval number: 2019HL-157). Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Conflicts of Interest The authors declare no conflicts of interest. Funding This research was funded by BEIJING MEDICAL AND HEALTH FOUNDATION (grant number YWJKJJHKYJJ-F10148) and Beijing Xisike Clinical Oncology Research Foundation (grant number Y-XD2019-038). Authors’ Contributions X.C. participated in the experimental design and was responsible for the collection of specimens and data from patients and mice, laboratory analysis, data analysis, and writing. Y.T. participated in the collection of specimens and data from patients and mice and laboratory analysis. X.L. contributed to data analysis and writing. S.Z. and X.G. participated in the experimental design and assisted the experiments. W.Z. and T.W. participated in the experimental design and writing—review and editing. All authors contributed to the article and approved the submitted version. Acknowledgments We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript. We are grateful to the patients who participated in this study for their invaluable support through allowing the use of their samples. References Aghamohammad S, Sepehr A, Miri ST, Najafi S, Rohani M, Pourshafiea MR. The effects of the probiotic cocktail on modulation of the NF-kB and JAK/STAT signaling pathways involved in the inflammatory response in bowel disease model. BMC Immunol. 2022;23(1):8. Rehman O, Jaferi U, Padda I, Khehra N, Atwal H, Mossabeh D, et al. Overview of lenvatinib as a targeted therapy for advanced hepatocellular carcinoma. Clinical and experimental hepatology. 2021;7(3):249-57. Bingula R, Filaire M, Radosevic-Robin N, Bey M, Berthon JY, Bernalier-Donadille A, et al. Desired Turbulence? Gut-Lung Axis, Immunity, and Lung Cancer. J Oncol. 2017;2017:5035371. Pagliari D, Saviano A, Newton EE, Serricchio ML, Dal Lago AA, Gasbarrini A, et al. Gut Microbiota-Immune System Crosstalk and Pancreatic Disorders. Mediators Inflamm. 2018;2018:7946431. Chen W, Wang S, Wu Y, Shen X, Guo Z, Li Q, et al. Immunogenic cell death: A link between gut microbiota and anticancer effects. Microbial pathogenesis. 2020;141:103983. Luu M, Monning H, Visekruna A. Exploring the Molecular Mechanisms Underlying the Protective Effects of Microbial SCFAs on Intestinal Tolerance and Food Allergy. Front Immunol. 2020;11:1225. Grüner N, Mattner J. Bile Acids and Microbiota: Multifaceted and Versatile Regulators of the Liver-Gut Axis. International journal of molecular sciences. 2021;22(3). Shen R, Ke L, Li Q, Dang X, Shen S, Shen J, et al. Abnormal bile acid-microbiota crosstalk promotes the development of hepatocellular carcinoma. Hepatol Int. 2022. Schwenger KJ, Clermont-Dejean N, Allard JP. The role of the gut microbiome in chronic liver disease: the clinical evidence revised. JHEP Rep. 2019;1(3):214-26. Schwabe RF, Greten TF. Gut microbiome in HCC - Mechanisms, diagnosis and therapy. Journal of hepatology. 2020;72(2):230-8. Zeng Y, Chen S, Fu Y, Wu W, Chen T, Chen J, et al. Gut microbiota dysbiosis in patients with hepatitis B virus-induced chronic liver disease covering chronic hepatitis, liver cirrhosis and hepatocellular carcinoma. J Viral Hepat. 2020;27(2):143-55. Ren Z, Li A, Jiang J, Zhou L, Yu Z, Lu H, et al. Gut microbiome analysis as a tool towards targeted non-invasive biomarkers for early hepatocellular carcinoma. Gut. 2019;68(6):1014-23. Ponziani FR, Gerardi V, Pecere S, D'Aversa F, Lopetuso L, Zocco MA, et al. Effect of rifaximin on gut microbiota composition in advanced liver disease and its complications. World J Gastroenterol. 2015;21(43):12322-33. Zhou S, Wang Z, He F, Qiu H, Wang Y, Wang H, et al. Association of serum bilirubin in newborns affected by jaundice with gut microbiota dysbiosis. J Nutr Biochem. 2019;63:54-61. Zhou L, Zhang M, Wang Y, Dorfman RG, Liu H, Yu T, et al. Faecalibacterium prausnitzii Produces Butyrate to Maintain Th17/Treg Balance and to Ameliorate Colorectal Colitis by Inhibiting Histone Deacetylase 1. Inflamm Bowel Dis. 2018;24(9):1926-40. Lopez-Siles M, Martinez-Medina M, Suris-Valls R, Aldeguer X, Sabat-Mir M, Duncan SH, et al. Changes in the Abundance of Faecalibacterium prausnitzii Phylogroups I and II in the Intestinal Mucosa of Inflammatory Bowel Disease and Patients with Colorectal Cancer. Inflamm Bowel Dis. 2016;22(1):28-41. Ma J, Sun L, Liu Y, Ren H, Shen Y, Bi F, et al. Alter between gut bacteria and blood metabolites and the anti-tumor effects of Faecalibacterium prausnitzii in breast cancer. BMC microbiology. 2020;20(1):82. Wei Z, Cao S, Liu S, Yao Z, Sun T, Li Y, et al. Could gut microbiota serve as prognostic biomarker associated with colorectal cancer patients' survival? A pilot study on relevant mechanism. Oncotarget. 2016;7(29):46158-72. Gopalakrishnan V, Spencer CN, Nezi L, Reuben A, Andrews MC, Karpinets TV, et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science. 2018;359(6371):97-103. Long SL, Gahan CGM, Joyce SA. Interactions between gut bacteria and bile in health and disease. Molecular aspects of medicine. 2017;56:54-65. Sinha SR, Haileselassie Y, Nguyen LP, Tropini C, Wang M, Becker LS, et al. Dysbiosis-Induced Secondary Bile Acid Deficiency Promotes Intestinal Inflammation. Cell Host Microbe. 2020;27(4):659-70 e5. Guo Y, Huang S, Zhao L, Zhang J, Ji C, Ma Q. Pine (Pinus massoniana Lamb.) Needle Extract Supplementation Improves Performance, Egg Quality, Serum Parameters, and the Gut Microbiome in Laying Hens. Front Nutr. 2022;9:810462. Zhao L, Yang W, Chen Y, Huang F, Lu L, Lin C, et al. A Clostridia-rich microbiota enhances bile acid excretion in diarrhea-predominant irritable bowel syndrome. J Clin Invest. 2020;130(1):438-50. Zhang C, Yang M, Ericsson AC. The Potential Gut Microbiota-Mediated Treatment Options for Liver Cancer. Front Oncol. 2020;10:524205. Vallianou N, Dalamaga M, Stratigou T, Karampela I, Tsigalou C. Do Antibiotics Cause Obesity Through Long-term Alterations in the Gut Microbiome? A Review of Current Evidence. Current obesity reports. 2021;10(3):244-62. Gui Q, Wang A, Zhao X, Huang S, Tan Z, Xiao C, et al. Effects of probiotic supplementation on natural killer cell function in healthy elderly individuals: a meta-analysis of randomized controlled trials. Eur J Clin Nutr. 2020;74(12):1630-7. Kazmierczak-Siedlecka K, Daca A, Fic M, van de Wetering T, Folwarski M, Makarewicz W. Therapeutic methods of gut microbiota modification in colorectal cancer management - fecal microbiota transplantation, prebiotics, probiotics, and synbiotics. Gut Microbes. 2020;11(6):1518-30. Baruch EN, Youngster I, Ben-Betzalel G, Ortenberg R, Lahat A, Katz L, et al. Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients. Science. 2021;371(6529):602-9. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial.docx supplementaryfile.docx 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. 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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-4024621","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":282923581,"identity":"5563cbac-5d8e-4a5f-b0c6-d548fdc37a6e","order_by":0,"name":"Xin Chai","email":"","orcid":"","institution":"Henan University of Chinese medicine","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Chai","suffix":""},{"id":282923583,"identity":"0ab26e52-a044-4b31-a799-332e03f3f332","order_by":1,"name":"Yue Tang","email":"","orcid":"","institution":"Henan University of Chinese medicine","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Tang","suffix":""},{"id":282923586,"identity":"52776f5f-4ccc-4552-947d-4c90772b4054","order_by":2,"name":"Ximeng Li","email":"","orcid":"","institution":"Henan University of Chinese medicine","correspondingAuthor":false,"prefix":"","firstName":"Ximeng","middleName":"","lastName":"Li","suffix":""},{"id":282923590,"identity":"5777d150-8be8-4a32-92d5-1a4b3cc613fd","order_by":3,"name":"Shansi Zou","email":"","orcid":"","institution":"The First Affiliated Hospital of Henan University of Chinese medicine","correspondingAuthor":false,"prefix":"","firstName":"Shansi","middleName":"","lastName":"Zou","suffix":""},{"id":282923591,"identity":"b25eecaa-ad27-4133-9628-5969804baf89","order_by":4,"name":"Xutao Guan","email":"","orcid":"","institution":"The First Affiliated Hospital of Henan University of Chinese medicine","correspondingAuthor":false,"prefix":"","firstName":"Xutao","middleName":"","lastName":"Guan","suffix":""},{"id":282923592,"identity":"ecbd7f0d-f1f4-48fc-91b5-db6cb396d4a1","order_by":5,"name":"Wenqiao Zang","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Wenqiao","middleName":"","lastName":"Zang","suffix":""},{"id":282923593,"identity":"ade8245f-5658-471c-a278-37d712145f78","order_by":6,"name":"Tao Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYJADxgcJFTUkqOdhYGA2eHDmGGla2CQftjATVmlwI/2ZNE/NHbv97IePVSQ2sDHwt3cnENCSkCbNc+xZcg9PWtqNxB0yDBJnzm4gpOWYdA7b4WQehhyzG4ln2BgMJHIJaUlsk875B9TC/8asILGNmRgtyWzSuW2H7XgkcswYiNIieeYZs/XfvsMJPDeeJUsknDnGQ9AvfMfTH96c8e2wPXt/8sGPPypq5Pjbe/FrUTjAwCIBpBMboAI8eJWDgHwDA/MHIG1PUOUoGAWjYBSMXAAASB1L3rHz8wEAAAAASUVORK5CYII=","orcid":"","institution":"The First Affiliated Hospital of Henan University of Chinese medicine","correspondingAuthor":true,"prefix":"","firstName":"Tao","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-03-07 13:15:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4024621/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4024621/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53658486,"identity":"6f3f6752-2e9a-4029-b115-06cf6977a63c","added_by":"auto","created_at":"2024-03-28 15:58:48","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":263690,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution and diversity of intestinal flora in patients with PLC. (A) Venn Diagram. Different 16S rRNA gene sequence data with similarity higher than 97% are classified as one OTU. Each OTU represents a different bacterium. (B) Alpha diversity reflects the heterogeneity of intestinal flora. Shannon index: \u003cem\u003eP\u003c/em\u003e = 0.0929; Simpson index: \u003cem\u003eP \u003c/em\u003e= 0.1843; Chao index: \u003cem\u003eP\u003c/em\u003e = 0.2267. (C, D, E) Beta diversity. (C) Non-weighted distance Anosim analysis results: R = 0.093,\u003cem\u003e P\u003c/em\u003e= 0.114. (D) Weighted distance Anosim analysis results: R = 0.11, \u003cem\u003eP\u003c/em\u003e = 0.119. (E) NMDS analysis. It is mainly used to compare the differences between groups. The farther the distance between the two points, the greater the difference in the composition of flora between the two samples. NMDS analysis can calculate a total stress function value, that is, the stress value on the header, which is generally not greater than 0.2. The ranking results are evaluated with reference to the Tess value.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4024621/v1/ce7f578b2fbacdacc2e8833e.jpg"},{"id":53660340,"identity":"9357432c-7126-42c7-9b3d-4e2bb93bac23","added_by":"auto","created_at":"2024-03-28 16:06:48","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":287727,"visible":true,"origin":"","legend":"\u003cp\u003eColumn diagram of Species Composition between groups. A, B, C, D and E were the column diagram of species composition of two groups of PLC patients at phylum, class, order, family and genus classification levels, respectively. Take the top ten species with relative abundance, and the rest are classified as other.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4024621/v1/be1f1dec5f2e1e0f8f3b7f02.jpg"},{"id":53658488,"identity":"0c26b762-d58a-4d51-a7de-59e16787d170","added_by":"auto","created_at":"2024-03-28 15:58:48","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":325731,"visible":true,"origin":"","legend":"\u003cp\u003eSpecies difference analysis and biomarkers between PLC groups. (A, B) Box diagram of species difference between groups. (C) Evolutionary branch graph. The circle radiating from inside to outside in the figure represents the taxonomic level from phylum to genus (the innermost yellow circle is the boundary). Each small circle at different classification levels represents a classification at that level, and the diameter of the small circle represents the size of relative abundance. (D) Histogram of LDA value distribution in PV2 group. The Lefse analysis compared the two groups of specimens, and the difference results in the group after medication were only shown in the figure, indicating that the Lefse analysis only found the differential markers in the PV2 group in the case of this grouping, while there was no differential marker in the PV1 group (There was no obvious dominant species compared with the PV2 group).\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4024621/v1/26f3b3048d0e0e9c21882dc3.jpg"},{"id":53658489,"identity":"5368694e-e40b-4467-bb9c-8b24ad686851","added_by":"auto","created_at":"2024-03-28 15:58:48","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":180185,"visible":true,"origin":"","legend":"\u003cp\u003ePicrust2 functional prediction analysis and random forest inter group prediction. (A) Differences between the two groups of samples in KEGG function. (B) ROC curve. The area under the curve can reflect the accuracy of diagnosis.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4024621/v1/af4e4775231a60cbeea2f09b.jpg"},{"id":53658491,"identity":"7f47332a-4198-4f73-a2d2-8f63f119f9fc","added_by":"auto","created_at":"2024-03-28 15:58:48","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":281687,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution and diversity of flora in patients with Time1 and Time2 group. (A) Venn Diagram. (B) Alpha diversity. Shannon index: \u003cem\u003eP \u003c/em\u003e= 0.9875; Simpson index: \u003cem\u003eP \u003c/em\u003e= 0.7666; Chao index: \u003cem\u003eP \u003c/em\u003e= 0.9626. (C) NMDS analysis. stess=0.0815. (D, E, F) Differential analysis of intestinal microbiota between groups at the genus level. (D) Column diagram of Species Composition. (E) Tukey test. (F) \u003cem\u003e\u0026nbsp;P\u003c/em\u003e=0.0104.\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4024621/v1/a4cc1e4793cc325001e9fcfd.jpg"},{"id":65235528,"identity":"40475e1a-96be-4148-8504-4ea7837b32e7","added_by":"auto","created_at":"2024-09-25 05:32:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1798886,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4024621/v1/3d1a6b93-4096-479c-9c24-254f5b69a6f3.pdf"},{"id":53660341,"identity":"16ebcf66-8923-4579-b51b-320f011f63a0","added_by":"auto","created_at":"2024-03-28 16:06:49","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":158546,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-4024621/v1/cea04c35dcb1c612dfcf2240.docx"},{"id":53658492,"identity":"8d5929c9-5254-470e-b0ea-32858e9a3104","added_by":"auto","created_at":"2024-03-28 15:58:48","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":1060534,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-4024621/v1/1e0ad326869cbfc3c0a87aae.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Lenvatinib Improves the Relative Abundance of Probiotics in Intestinal Flora of Patients with Primary Liver Cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe incidence rate of primary liver cancer is high worldwide. The main causes of primary liver cancer in China are chronic hepatitis virus (mainly hepatitis B virus and hepatitis C virus) infection, cirrhosis, long-term drinking, nonalcoholic liver disease, aflatoxin exposure and genetic factors(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Early symptoms are often atypical, making detection without regular check-ups challenging. Patients typically present with symptoms such as pain, abdominal distension, anorexia, jaundice, and emaciation, indicating advanced stage PLC, severely impacting their quality of life and health.\u003c/p\u003e \u003cp\u003eIn systemic PLC therapy, Lenvatinib not only inhibits tumor angiogenesis, reducing tumor burden via the VEGR/VEGFR signaling pathway(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) but also acts as an efficient immunomodulator. Due to its efficacy and manageable side effects, Lenvatinib finds widespread clinical use. Studies suggest specific intestinal microorganisms influence tumor occurrence and response to anti-tumor treatments, potentially acting as tumor suppressors or promoters(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Intestinal flora modulates the efficacy of antitumor drugs and reduces adverse reactions to treatments like oxaliplatin, cyclophosphamide, and immune checkpoint inhibitors (PD-1/PD-L1 and CTLA4 inhibitors)(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). However, the relationship between targeted antiangiogenic drugs like Lenvatinib and intestinal flora remains unclear, with limited clinical research and reports. This study thus investigates the connection between Lenvatinib and intestinal flora in liver cancer patients, aiming to identify potential microbial markers for predicting Lenvatinib efficacy.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExperimental Subject\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003ePatients with BCLC stage C PLC who were treated with Lenvatinib in the First Affiliated Hospital of Henan University of traditional Chinese medicine from July 2020 to December 2021 were enrolled as the experimental objects. Clinical research program and informed consent have been approved by the Ethics Management Committee of the First Affiliated Hospital of Henan University of Chinese Medicine (approval number: 2019HL-157). The experimental group was divided into two groups: the control group before Lenvatinib treatment (PV1) and the experimental group after treatment (at least 3 weeks after Lenvatinib treatment) (PV2). 3 weeks is a treatment cycle, 1 cycle of Lenvatinib treatment is Time1 group, and 2 cycles of Lenvatinib treatment is Time2 group. Inclusion criteria (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Patients with stage C PLC according to Barcelona clinical liver cancer (BCLC) staging; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Those who have previously received systematic first-line treatment (except for Lenvatinib) or have not received first-line treatment; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Age\u0026thinsp;\u0026ge;\u0026thinsp;18 years, life expectancy\u0026thinsp;\u0026gt;\u0026thinsp;3 months; (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) The PS score was 0\u0026ndash;2 points within 7 days before the first administration of the research drug; (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Have adequate organ function. Exclusion criteria (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) have occurred esophageal or gastric varices bleeding or other hemorrhagic diseases and bleeding tendencies in the past six months; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) taking antibiotics, probiotics or microbial agents within one month; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Patients with a history of intestinal diseases or diarrhea-prone diseases, combined or concurrent other diseases affecting the results of this study; (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) Female patients during pregnancy and lactation; (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Patients with severe allergy to research intervention and / or any of its accessories (\u0026ge;\u0026thinsp;3 levels). Twenty-two patients with good adherence were selected from the enrolled patients to undergo dynamic testing for 2 cycles of Lenvatinib dosing, and we explored the effect of Lenvatinib on the intestinal flora of PLC patients. Stool samples shall be taken 1\u0026ndash;4 days before Lenvatinib treatment and at least 3 weeks after treatment, frozen at \u0026minus;\u0026thinsp;80℃ and marked.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSequencing and Analysis of Microbial 16s rRNA\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eDNA was extracted from all fecal specimens frozen at \u0026minus;\u0026thinsp;80\u0026deg;C using nucleic acid extractant (Hangzhou guheinfo: GHFDE100). The DNA concentration was determined using NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and agarose gel electrophoresis was performed. The corresponding primers of 16S V4 region: 515F(GTGCCAGCMGCCGCGGTAA)-806R༈GGACTACHVGGGTWTCTAAT༉ were selected for PCR amplification. The PCR products were purified by AMPure XP Beads (Beckman Coulter, Indianapolis, IN). Qubit was used for library quantification, and Illlumina NovaSeq platform was used for sequencing. After quality control and filtering, the sequences were clustered and annotated. Alpha diversity and Beta diversity were compared, species difference between groups was analyzed, and metagenomic function was predicted.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe data were processed and analyzed by SPSS 26.0 statistical software. The Alpha diversity index of intestinal flora was tested by rank sum test, and the Beta diversity was analyzed by Anosim and NMDS (Nonmetric Multidimensional Scaling). The species difference between groups was analyzed by Kruskal-Wallis, Var test and one-way ANOVA, and the species markers were analyzed by Lefse. Two-tailed values of P of less than 0.05 and LDA (Linear discriminant analysis) score more than 2 were considered as statistically significant.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eDistribution and Diversity of Intestinal Flora in two groups of Patients with PLC\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eA total of 43 fecal specimens from PLC patients were collected. Based on the Venn Diagram of OUT (operational taxonomic unit), there were 76 unique OTUs in PV1 group and 522 unique OTUs in PV2 group. The overlapping area represented a total of 1127 OTUs in the two groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The intestinal flora diversity in the group after Lenvatinib treatment was richer than those in the group before treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). The Shannon, Simpson and Chao indices in the PV2 group were all higher than those in the PV1 group. The Alpha diversity of the intestinal flora in patients with PLC after Lenvatinib treatment was higher than that before treatment, but the difference was not statistically significant(\u003cem\u003eP\u003c/em\u003e\u0026gt;0.05). The results of Beta diversity Anosim analysis were consistent (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, D), with R\u0026thinsp;\u0026gt;\u0026thinsp;0, indicating that the sample difference between the two groups was greater than that within the group, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, indicating that the difference was not statistically significant. The results of NMDS showed that red dots and blue dots were intertwined in the same range, and were not distributed in specific areas, suggesting that the intestinal flora structure of patients before and after treatment with Lenvatinib was similar (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eColumn Diagram of Species Composition between groups\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBased on the species abundance table, the species composition of two groups of PLC samples was analyzed at phylum, class, order, family, and genus classification levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, B, C, D, E). The composition of intestinal flora in the two groups was similar at each classification level, but the abundance of intestinal flora was different. The differences in flora composition and abundance between the two groups of specimens are described from phylum, family and genus levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, D, E).\u003c/p\u003e \u003cp\u003eAccording to the species composition statistics of the two groups of samples at the phylum level ((Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), the bacteria of the two groups mainly include Firmicutes, Bacteroidota, Proteobacteria, Actinobacteriota, Desulfobacterota,Verrucomicrobiota,Fusobacteriota, etc. Among them, Bacteroidota, Proteobacteria, Desulfobacterota, Verrucomicrobiota decreased the relative abundance of bacteria in patients after treatment compared with those before treatment. Firmicutes and Actinobacteriota were the bacteria with higher relative abundance in the intestinal flora of patients in the post-medication group than those in the pre-medication group. At family level ((Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD), the relative abundance of Bacteroidaceae, Lachnospiraceae, Ruminococcaceae, Streptococcaceae, Selenomonadaceae, Bifidobacteriaceae and Lactobacillaceae in PV2 group was higher than that in PV1 group. The relative abundance of Enterobacteriaceae, Veillonellacese and Prevotellaceae in PV2 group was lower than that in PV1 group. At genus level (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE), the top ten species with relative abundance in the two groups were:Bacteroides,Veillonella,Escherichia \u0026ndash; Shigella,Prevotella,Streptococcus,Megamonas,Faecalibacterium,Subdoligranulum,Bifidobacterium,Eisenbergiella.Among them, Bacteroides, Veillonella, Escherichia \u0026ndash; Shigella, Prevotella and eisenbergiella in PV2 group were lower than those in PV1 group Streptococcus, megamonas, faecalibacterium, subdoligranulum and Bifidobacterium were higher in PV2 group than in PV1 group.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSpecies Difference Analysis and Biomarkers between two groups\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAt the genus level, Bifidobacterium, Coprococcus, Lachnospiraceae _ NK4A136 _ group, Lachnospiraceae _ UCG-010, Butyricicoccus, and Faecalibacterium were the different intestinal flora of PLC patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The relative abundance of Bifidobacterium and Faecalibacterium in the PV2 group was significantly higher than that in the PV1 group, and the difference was statistically significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Lefse results showed significant differences. Biomarkers in PLC group after Lenvatinib treatment were Clostridia, Bifidobacterium, Bifidobacteriaceae, Bifidobacteriales, Faecalibacterium, Butyricicoccus, Butyricicoccaceae, Ruminococcaceae-uncultured, Ruminococcaceae-Incertae_Sedis, Lachnospiraceae_NK4A136_group, Ruminococcaceae, Lachnospiraceae_UCG_010 12 kinds in total (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, D).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePicrust2 Functional Prediction Analysis and Random Forest inter group Prediction\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e By analyzing the metagenomic function of intestinal flora in PLC Patients, there was significant difference in KEGG function between the two groups of PLC samples, that is, the relative abundance of ko00121 Secondary bile acid biosynthesis and ko00120 Primary bile acid biosynthesis increased after Lenvatinib treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). At the family level, it reflects the characteristics that play a major role in the classification effect in the classifier, from large to small according to importance. The area under ROC curve was 75% (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDynamic monitoring of intestinal flora changes in PLC patients treated with Lenvatinib\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTwenty-two patients with good adherence were selected from the enrolled patients to undergo dynamic testing for 2 cycles of Lenvatinib dosing, and we explored the effect of Lenvatinib on the intestinal flora of PLC patients. 3 weeks is a treatment cycle, 1 cycle of Lenvatinib treatment is Time1 group, and 2 cycles of Lenvatinib treatment is Time2 group.\u003c/p\u003e \u003cp\u003eThe Venn diagram of OUT illustrates the intersection of microbial categories between the two groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Comparative analysis revealed 149 unique OTUs in the Time1 group and 133 unique OTUs in the Time2 group, with a total of 1606 OTUs shared between the two groups. The microbial categories in the Time1 group were slightly more diverse than those in the Time2 group. The alpha diversity indices between the two groups showed the following results (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). All three indices had P-values greater than 0.05, indicating no statistically significant differences in the alpha diversity of gut microbiota between the two treatment cycles of Lenvatinib in patients with PLC. In NMDS analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC), each point represents a sample, where red indicates samples from the Time1 group and blue represents samples from the Time2 group. With a stress value of 0.0815, red and blue points intermingle within the same region, without distinct separation into specific areas. This suggests that the intestinal microbiota structure between patients undergoing two cycles of Lenvatinib treatment remains similar. The taxonomic composition of the two groups of samples was analyzed at the genus level (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). The top ten species based on relative abundance in both groups were identified as follows: Bacteroides, Veillonella, Escherichia \u0026ndash; Shigella, Prevotella, Akkermansia, Faecalibacterium, Subdoligranulum, Eisenbergiella, Agathobacter, and Bifidobacterium. Among these, the relative abundance of Akkermansia, Escherichia \u0026ndash; Shigella, and Subdoligranulum decreased in the Time2 group compared to the Time1 group. Conversely, the relative abundance of Veillonella, Eisenbergiella, and Agathobacter increased in the Time2 group compared to the Time1 group. Tukey test is one of the multiple comparison methods applicable to situations with k treatment groups and equal sample sizes. It results achieve a confidence level of 95%. At the genus level, there is a statistically significant increase in the relative abundance of Veillonella in the Time2 group compared to the Time1 group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE), a finding consistent with the results (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). Each color represents a patient. The data suggest a significant increase in the relative abundance of Veillonella in the Time2 group compared to the Time1 group within the same patient.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe gastrointestinal tract and liver exhibit close anatomical and functional connections, forming the intestinal-liver axis characterized by bidirectional interactions between intestinal microorganisms, their derivatives, and the liver. Intestinal flora plays a crucial role in human health and disease. Imbalances in intestinal flora, influenced by the gut-liver axis, significantly contribute to liver cancer pathogenesis. This imbalance is primarily associated with reduced populations of short-chain fatty acid (SCFA)-producing bacteria(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), alterations in bile acid composition(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), activation of alcohol-induced immune responses, lipopolysaccharide responses, choline deficiency, and other related factors(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGut microbiota metabolites may play a role in regulating liver inflammation and immunity, thereby influencing the progression of hepatocellular carcinoma (HCC) induced by nonalcoholic steatohepatitis (NASH)(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) and hepatitis virus infections(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePathogens and probiotics exert influence on the human immune microenvironment through complex metabolic mechanisms and interactions with the host, potentially serving as biomarkers in anti-tumor therapy. Fecal samples collected from hepatocellular carcinoma (HCC) patients across East, Central, and Northwest China revealed decreased levels of butyrate-producing and lipopolysaccharide (LPS)-producing bacteria in early HCC patients, suggesting gut microbes could serve as non-invasive biomarkers for early HCC detection(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). However, further research across diverse patient groups and underlying conditions is necessary.Studies have shown increased abundance of Bacteroides and Rumenococcus, and decreased levels of Bifidobacterium in liver cancer patients(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Notably, as HCC progresses, Bifidobacterium levels decrease significantly while Enterococcus levels rise. Bifidobacterium, a Gram-positive anaerobic bacterium and a physiological probiotic, helps maintain intestinal microecological balance, enhances host immune responses against tumors, and boosts immune function. In our study, the abundance of Bifidobacterium in PLC patients post-Lenvatinib treatment was higher than pre-treatment levels, suggesting its potential as a microbial marker for Lenvatinib efficacy. This highlights Lenvatinib's regulatory effect on intestinal microecology and its anti-tumor properties. Bifidobacterium, a key component of probiotics, is widely used both clinically and in daily life. Probiotic mixtures containing Bifidobacterium demonstrate anti-inflammatory effects on HT-29 cells by regulating JAK/STAT and NF-κB pathways(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), hinting at its potential in treating neonatal cholestasis(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our study, we observed an increase in the abundance of Faecalibacterium in liver cancer patients after treatment with Lenvatinib. Faecalibacterium prausnitzii, a significant butyrate-producing strain within the genus Fecalibacterium, was particularly noted. Butyrate, a short-chain fatty acid, plays a crucial role in enhancing the integrity and immunity of the intestinal mucosal epithelial barrier. Research(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) indicates that the butyrate produced through F. prausnitzii metabolism helps maintain the balance between Th17 and Treg cells, exerting an intrinsic anti-inflammatory effect in animal models of colorectal colitis. This effect occurs through the inhibition of HDAC1, which promotes Foxp3 expression and blocks the downstream IL-6/STAT3/IL-17 signaling pathway. These findings suggest that F. prausnitzii may offer novel avenues for further investigation into the treatment of inflammatory bowel disease. The targeted butyrate-HDAC1-T cell axis emerges as a promising approach for the treatment of inflammatory diseases. The abundance of F. prausnitzii in the intestinal flora of patients with colorectal cancer, Crohn's disease, and ulcerative colitis was found to be lower than that of healthy controls (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001)(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Studies(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) have demonstrated a decrease in the abundance of fecal bacilli in breast cancer patients. F. prausnitzii has been shown to inhibit the proliferation and invasion of breast cancer (BC) cells by suppressing the IL-6/STAT3 pathway and promoting apoptosis of breast cancer cells. Additionally, F. prausnitzii may serve as a prognostic biomarker for evaluating overall survival (OS) in breast cancer patients. Patients with a high abundance of F. prausnitzii in colorectal cancer tend to have longer overall survival after surgery. Conversely, high abundance of F. nucleatum and B. fragilis serves as independent indicators of poor prognosis in colorectal cancer patients(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The presence of F. prausnitzii has been associated with enhanced efficacy of immune checkpoint inhibitors in patients with melanoma(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe observed a significant difference in KEGG function between the two groups of PLC samples, specifically, the relative abundance of ko00121 Secondary bile acid biosynthesis and ko00120 Primary bile acid biosynthesis increased after Lenvatinib treatment. Bile acids (BAs) are primarily synthesized through cholesterol metabolism in the liver. The classical pathway involves the production of primary bile acids (PBAs), such as chenodeoxycholic acid (CDCA) and cholic acid (CA), through a series of enzymatic reactions involving cytochrome P450 family 7 subfamily A member 1 (CYP7A1). PBAs are stored in the gallbladder with bile and enter the intestine following food stimulation, where they are converted by microorganisms into secondary bile acids (SBAs), including deoxycholic acid (DCA) and lithocholic acid (LCA). Over 95% of bile acids are reabsorbed at the terminal ileum and transported back to the liver through the portal vein(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), constituting the gut-liver cycle of bile acids(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBile acid metabolism involves intricate interactions between host and microbial communities. In a mouse model of ulcerative colitis(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), a significant reduction in Ruminococcaceae was observed, along with lower levels of deoxycholic acid (DCA) and lithocholic acid (LCA) compared to the control group. Ruminococcaceae and Lachnospiraceae can convert primary bile acids into secondary bile acids through 7α-dehydroxylation. The decrease in Ruminococcus is believed to be significantly associated with the decrease in secondary bile acid (SBA) levels. Intestinal microbiota disorders in inflammatory bowel disease can lead to SBA deficiency and promote intestinal inflammation, which can be addressed by supplementing exogenous SBAs.Butyricicoccaceae emerged as a potential microbial marker of Lenvatinib in this experimental group and was found to be associated with bile acid metabolism(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In a study(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) analyzing bile acid-related metabolomics and metagenomics in diarrhea-predominant irritable bowel syndrome (IBS-D) group, it was revealed that microbial communities rich in Clostridia were closely linked to excessive bile acid biosynthesis and excretion. Furthermore, through a series of animal and cell experiments, it was clarified that Clostridium-rich microbial groups could induce excessive bile acid excretion by targeting intestinal feedback mechanisms to regulate bile acid synthesis. Based on the literature and the results of this experiment, Clostridia, as one of the differential intestinal microbes in PLC after Lenvatinib treatment, may be associated with the adverse reactions of diarrhea caused by Lenvatinib.\u003c/p\u003e \u003cp\u003eThe balance of intestinal flora is intricately linked to health and disease. Flora imbalance can promote tumor occurrence, while tumor progression can exacerbate the imbalance, creating a vicious cycle. The composition of human gut microbiota is influenced by various factors including diet, lifestyle, antibiotics, environment, and disease(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Regulation of gut microbiota for cancer therapy can be achieved through interventions such as antibiotics(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), probiotics(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), prebiotics(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), fecal microbiota transplantation (FMT)(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), and microbiota metabolites. These approaches hold promise in modulating the gut microbiota to improve cancer treatment outcomes. In this study, it was observed that Lenvatinib could influence the intestinal flora of patients with liver cancer. The administration of Lenvatinib led to an increase in the abundance of beneficial bacteria in the intestinal flora while reducing the abundance of certain pathogenic bacteria. This suggests an interaction between Lenvatinib, alterations in the intestinal flora of liver cancer patients, and anti-tumor immune regulation. These associations may offer insights into the efficacy and safety of Lenvatinib monotherapy or combination therapy for liver cancer, presenting a novel adjuvant treatment option.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical research program and informed consent have been approved by the Ethics Management Committee of the First Affiliated Hospital of Henan University of Chinese Medicine (approval number: 2019HL-157).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by BEIJING MEDICAL AND HEALTH FOUNDATION (grant number YWJKJJHKYJJ-F10148) and Beijing Xisike Clinical Oncology Research Foundation (grant number Y-XD2019-038).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eX.C. participated in the experimental design and was responsible for the collection of specimens and data from patients and mice, laboratory analysis, data analysis, and writing. Y.T. participated in the collection of specimens and data from patients and mice and laboratory analysis. X.L. contributed to data analysis and writing. S.Z. and X.G. participated in the experimental design and assisted the experiments. W.Z. and T.W. participated in the experimental design and writing\u0026mdash;review and editing. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript. We are grateful to the patients who participated in this study for their invaluable support through allowing the use of their samples.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAghamohammad S, Sepehr A, Miri ST, Najafi S, Rohani M, Pourshafiea MR. The effects of the probiotic cocktail on modulation of the NF-kB and JAK/STAT signaling pathways involved in the inflammatory response in bowel disease model. BMC Immunol. 2022;23(1):8.\u003c/li\u003e\n\u003cli\u003eRehman O, Jaferi U, Padda I, Khehra N, Atwal H, Mossabeh D, et al. Overview of lenvatinib as a targeted therapy for advanced hepatocellular carcinoma. Clinical and experimental hepatology. 2021;7(3):249-57.\u003c/li\u003e\n\u003cli\u003eBingula R, Filaire M, Radosevic-Robin N, Bey M, Berthon JY, Bernalier-Donadille A, et al. Desired Turbulence? Gut-Lung Axis, Immunity, and Lung Cancer. J Oncol. 2017;2017:5035371.\u003c/li\u003e\n\u003cli\u003ePagliari D, Saviano A, Newton EE, Serricchio ML, Dal Lago AA, Gasbarrini A, et al. Gut Microbiota-Immune System Crosstalk and Pancreatic Disorders. Mediators Inflamm. 2018;2018:7946431.\u003c/li\u003e\n\u003cli\u003eChen W, Wang S, Wu Y, Shen X, Guo Z, Li Q, et al. Immunogenic cell death: A link between gut microbiota and anticancer effects. Microbial pathogenesis. 2020;141:103983.\u003c/li\u003e\n\u003cli\u003eLuu M, Monning H, Visekruna A. Exploring the Molecular Mechanisms Underlying the Protective Effects of Microbial SCFAs on Intestinal Tolerance and Food Allergy. Front Immunol. 2020;11:1225.\u003c/li\u003e\n\u003cli\u003eGr\u0026uuml;ner N, Mattner J. Bile Acids and Microbiota: Multifaceted and Versatile Regulators of the Liver-Gut Axis. International journal of molecular sciences. 2021;22(3).\u003c/li\u003e\n\u003cli\u003eShen R, Ke L, Li Q, Dang X, Shen S, Shen J, et al. Abnormal bile acid-microbiota crosstalk promotes the development of hepatocellular carcinoma. Hepatol Int. 2022.\u003c/li\u003e\n\u003cli\u003eSchwenger KJ, Clermont-Dejean N, Allard JP. The role of the gut microbiome in chronic liver disease: the clinical evidence revised. JHEP Rep. 2019;1(3):214-26.\u003c/li\u003e\n\u003cli\u003eSchwabe RF, Greten TF. Gut microbiome in HCC - Mechanisms, diagnosis and therapy. Journal of hepatology. 2020;72(2):230-8.\u003c/li\u003e\n\u003cli\u003eZeng Y, Chen S, Fu Y, Wu W, Chen T, Chen J, et al. Gut microbiota dysbiosis in patients with hepatitis B virus-induced chronic liver disease covering chronic hepatitis, liver cirrhosis and hepatocellular carcinoma. J Viral Hepat. 2020;27(2):143-55.\u003c/li\u003e\n\u003cli\u003eRen Z, Li A, Jiang J, Zhou L, Yu Z, Lu H, et al. Gut microbiome analysis as a tool towards targeted non-invasive biomarkers for early hepatocellular carcinoma. Gut. 2019;68(6):1014-23.\u003c/li\u003e\n\u003cli\u003ePonziani FR, Gerardi V, Pecere S, D\u0026apos;Aversa F, Lopetuso L, Zocco MA, et al. Effect of rifaximin on gut microbiota composition in advanced liver disease and its complications. World J Gastroenterol. 2015;21(43):12322-33.\u003c/li\u003e\n\u003cli\u003eZhou S, Wang Z, He F, Qiu H, Wang Y, Wang H, et al. Association of serum bilirubin in newborns affected by jaundice with gut microbiota dysbiosis. J Nutr Biochem. 2019;63:54-61.\u003c/li\u003e\n\u003cli\u003eZhou L, Zhang M, Wang Y, Dorfman RG, Liu H, Yu T, et al. Faecalibacterium prausnitzii Produces Butyrate to Maintain Th17/Treg Balance and to Ameliorate Colorectal Colitis by Inhibiting Histone Deacetylase 1. Inflamm Bowel Dis. 2018;24(9):1926-40.\u003c/li\u003e\n\u003cli\u003eLopez-Siles M, Martinez-Medina M, Suris-Valls R, Aldeguer X, Sabat-Mir M, Duncan SH, et al. Changes in the Abundance of Faecalibacterium prausnitzii Phylogroups I and II in the Intestinal Mucosa of Inflammatory Bowel Disease and Patients with Colorectal Cancer. Inflamm Bowel Dis. 2016;22(1):28-41.\u003c/li\u003e\n\u003cli\u003eMa J, Sun L, Liu Y, Ren H, Shen Y, Bi F, et al. Alter between gut bacteria and blood metabolites and the anti-tumor effects of Faecalibacterium prausnitzii in breast cancer. BMC microbiology. 2020;20(1):82.\u003c/li\u003e\n\u003cli\u003eWei Z, Cao S, Liu S, Yao Z, Sun T, Li Y, et al. Could gut microbiota serve as prognostic biomarker associated with colorectal cancer patients\u0026apos; survival? A pilot study on relevant mechanism. Oncotarget. 2016;7(29):46158-72.\u003c/li\u003e\n\u003cli\u003eGopalakrishnan V, Spencer CN, Nezi L, Reuben A, Andrews MC, Karpinets TV, et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science. 2018;359(6371):97-103.\u003c/li\u003e\n\u003cli\u003eLong SL, Gahan CGM, Joyce SA. Interactions between gut bacteria and bile in health and disease. Molecular aspects of medicine. 2017;56:54-65.\u003c/li\u003e\n\u003cli\u003eSinha SR, Haileselassie Y, Nguyen LP, Tropini C, Wang M, Becker LS, et al. Dysbiosis-Induced Secondary Bile Acid Deficiency Promotes Intestinal Inflammation. Cell Host Microbe. 2020;27(4):659-70 e5.\u003c/li\u003e\n\u003cli\u003eGuo Y, Huang S, Zhao L, Zhang J, Ji C, Ma Q. Pine (Pinus massoniana Lamb.) Needle Extract Supplementation Improves Performance, Egg Quality, Serum Parameters, and the Gut Microbiome in Laying Hens. Front Nutr. 2022;9:810462.\u003c/li\u003e\n\u003cli\u003eZhao L, Yang W, Chen Y, Huang F, Lu L, Lin C, et al. A Clostridia-rich microbiota enhances bile acid excretion in diarrhea-predominant irritable bowel syndrome. J Clin Invest. 2020;130(1):438-50.\u003c/li\u003e\n\u003cli\u003eZhang C, Yang M, Ericsson AC. The Potential Gut Microbiota-Mediated Treatment Options for Liver Cancer. Front Oncol. 2020;10:524205.\u003c/li\u003e\n\u003cli\u003eVallianou N, Dalamaga M, Stratigou T, Karampela I, Tsigalou C. Do Antibiotics Cause Obesity Through Long-term Alterations in the Gut Microbiome? A Review of Current Evidence. Current obesity reports. 2021;10(3):244-62.\u003c/li\u003e\n\u003cli\u003eGui Q, Wang A, Zhao X, Huang S, Tan Z, Xiao C, et al. Effects of probiotic supplementation on natural killer cell function in healthy elderly individuals: a meta-analysis of randomized controlled trials. Eur J Clin Nutr. 2020;74(12):1630-7.\u003c/li\u003e\n\u003cli\u003eKazmierczak-Siedlecka K, Daca A, Fic M, van de Wetering T, Folwarski M, Makarewicz W. Therapeutic methods of gut microbiota modification in colorectal cancer management - fecal microbiota transplantation, prebiotics, probiotics, and synbiotics. Gut Microbes. 2020;11(6):1518-30.\u003c/li\u003e\n\u003cli\u003eBaruch EN, Youngster I, Ben-Betzalel G, Ortenberg R, Lahat A, Katz L, et al. Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients. Science. 2021;371(6529):602-9.\u003c/li\u003e\n\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":"gut microbiome, primary liver cancer, Lenvatinib, probiotics, 16S rRNA sequencing","lastPublishedDoi":"10.21203/rs.3.rs-4024621/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4024621/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLenvatinibis commonly used systemic therapeutic drugs for patients with advanced Primary Liver Cancer (PLC). Recent studies have found that gut microbiota can regulate the efficacy of anti-tumor drugs. However, the relationship between antiangiogenic drugs and intestinal flora is not clear, and there is no relevant clinical research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe investigated Lenvatinib's impact on PLC patients' intestinal flora. Fecal samples from pre- and post-treatment PLC patients were analyzed via 16S rRNA Illumina sequencing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNotably, Bifidobacterium, Coprococcus, and other genera varied between groups at the genus level. The relative abundance of probiotics (Bifidobacterium, Coprococcus) significantly rose post-treatment. The Lefse analysis revealed significant differences. Following Lenvatinib treatment, PLC patients exhibited 12 biomarkers, including Clostridia, Bifidobacterium, Bifidobacteriaceae, Bifidobacteriales, Faecalibacterium, Butyricicoccus, Butyricicoccaceae, Ruminococcaceae-uncultured, Ruminococcaceae-Incertae_Sedis, Lachnospiraceae_NK4A136_group, Ruminococcaceae, and Lachnospiraceae_UCG_010.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLenvatinib increased the relative abundance of probiotics in PLC patients' intestinal flora, suggesting therapeutic implications.\u003c/p\u003e","manuscriptTitle":"Lenvatinib Improves the Relative Abundance of Probiotics in Intestinal Flora of Patients with Primary Liver Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-28 15:58:43","doi":"10.21203/rs.3.rs-4024621/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":"14625c37-54eb-455e-b611-f26acb3ceed1","owner":[],"postedDate":"March 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-09-25T05:24:07+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-28 15:58:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4024621","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4024621","identity":"rs-4024621","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}