Abstract Background Improving the efficacy of anti-programmed death 1 (PD-1) monoclonal antibody (mAb) therapy remains a major challenge for cancer immunotherapy in non-small cell lung cancer (NSCLC). Gut microbial metabolites can influence immunotherapy efficacy. Methods ELISA was used to compare the serum 5-hydroxyindoleacetic acid (5-HIAA) level in patients with NSCLC. Humanized mice were constructed to observe the effect of 5-HIAA on immunotherapy. RNA-seq and flow cytometry were used to analyze the effect of 5-HIAA on tumor-infiltrating lymphocytes. The effects of phenelzine (Phe) and Akkermansia muciniphila (AKK) on 5-HIAA synthesis, antitumor immunity and immunotherapy efficacy were analyzed. Finally, the synergistic effect of Phe combined with AKK on anti-PD-1 mAb was observed. Results Here we found that 5-HIAA, which is regulated by gut microbiota, has increased concentrations in the serum of non-responders to immunotherapy. Supplementation of 5-HIAA inhibited the efficacy of anti-PD-1 mAb and tumor infiltration of CD8^+ T cells. The use of monoamine oxidase inhibitor (MAO-I) Phe inhibited the synthesis of 5-HIAA, then improved the efficacy of anti-PD-1 mAb. In addition, supplementation of AKK can also decrease 5-HIAA in serum. Finally, the combination of Phe and AKK maximally inhibited 5-HIAA synthesis and improved immunotherapy efficacy. Conclusions Our investigations reveal that alterations in gut microbial composition leading to increased 5-HIAA synthesis can negatively impact CD8^+ T cell functionality and the success of immunotherapy. The combination of Phe and AKK supplementation holds potential for optimizing immunotherapy efficacy. Keywords: Immunotherapy, Lung Cancer __________________________________________________________________ WHAT IS ALREADY KNOWN ON THIS TOPIC * Immune checkpoint inhibitors (ICIs), represented by anti-programmed death 1 (PD-1) monoclonal antibody (mAb), prolong the survival of a part of patients with non-small cell lung cancer (NSCLC). However, the response rate of patients with NSCLC to ICIs is less than 25%, and it is necessary to find adjuvant treatment strategies to enhance the response rate of ICIs. The distribution of gut microbes and their metabolites can affect the tumor microenvironment and the effect of ICIs. WHAT THIS STUDY ADDS * Gut microbial metabolite 5-hydroxyindoleacetic acid (5-HIAA) was found to inhibit the activity of tumor-infiltrating CD8^+ T cells and the efficacy of anti-PD-1 mAb. The combination of the monoamine oxidase inhibitor (MAO-I) phenelzine and the probiotic Akkermansia muciniphila minimized serum concentrations of 5-HIAA, while improving tumor CD8^+ T cell infiltration and anti-PD-1 mab treatment. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY * These data based on clinical samples and preclinical experiments fully demonstrate the inhibitory effect of gut microbial metabolite 5-HIAA on the efficacy of ICIs, and provide a feasible adjuvant treatment strategy for anti-PD-1 mAb. Introduction Lung cancer remains one of the most commonly diagnosed cancers, accounting for about 12% of all cancers.[61]^1 Almost 85% of lung cancers are non-small cell lung cancers (NSCLCs).[62]^2 Immune checkpoint inhibitors (ICIs) target tumor cells or tumor-infiltrating T cells to restore antitumor immunity in the tumor microenvironment (TME).[63]^3 As a representative of ICIs, anti-programmed death 1 (PD-1) monoclonal antibodies (mAbs) have been approved for various types of NSCLC since 2015.[64]^4 ICIs therapy has resulted in long-term survival in a subset of patients with advanced NSCLC compared with conventional chemotherapy.[65]^5 Although some anti-PD-1 mAb has been used in first-line treatment of NSCLC, the problem of their low response rate (<25%) remains to be solved.[66]^6 Recent studies increasingly confirm that both the gut microbiota and their metabolites significantly influence the effectiveness of ICIs, either enhancing or diminishing their therapeutic impact.[67]^7 8 Particularly in recent years, extensive research has identified numerous bacterial species and metabolites within patients that are closely linked to the success of ICIs treatments.[68]9,[69]12 In our previous study, patients with NSCLC with mental stress were found to have a poorer response to ICI treatment relative to patients with NSCLC without mental stress. Further microbiomic and metabolomic analyses indicated that mental stress is associated with an increase in Firmicutes bacteria levels in the gut, alongside an increased synthesis of the tryptophan downstream metabolite, 5-hydroxyindoleacetic acid (5-HIAA). These findings suggest that elevated 5-HIAA levels, influenced by stress-induced changes in gut microbiota, may interfere with the effectiveness of anti-PD-1 mAb treatments in patients with NSCLC. The upregulation of 5-HIAA could potentially suppress immune functions critical for the success of immunotherapy, notably impacting the activity of tumor-infiltrating lymphocytes (TILs). Thus, considering this interaction, 5-HIAA can emerge as a promising biomarker for assessing and potentially modulating the therapeutic efficacy of anti-PD-1 mAb in NSCLC. The synthesis of 5-HIAA originates from the metabolism of tryptophan. Tryptophan is metabolized in the gut through three primary pathways: kynurenine, serotonin (5-hydroxytryptamine, or 5-HT), and indole derivatives.[70]^13 In the serotonin pathway, Within the serotonin pathway, the enzyme tryptophan hydroxylase (TPH) first converts tryptophan to 5-hydroxytryptophan (5-HTP). This is quickly followed by the decarboxylation of 5-HTP to 5-HT, catalyzed by the enzyme aromatic amino acid decarboxylase (DDC). Subsequently, 5-HT is converted into 5-HIAA through the action of the mitochondrial enzyme monoamine oxidase (MAO).[71]^14 Given its critical role as a rate-limiting enzyme in the synthesis of 5-HIAA, MAO represents a viable target for controlling the production of 5-HIAA. This understanding led us to assess the impact of MAO inhibitors on the effectiveness of ICIs. The distribution of gut microbiota influences the synthesis of 5-HIAA and induces a range of physiological or disease modifications, including depression, endocrine disorders, and inflammatory responses.[72]15,[73]18 A clinical trial confirmed that Bifidobacterium breva assisted in the treatment of major depressive disorder by altering tryptophan metabolism, mainly inhibiting 5-HT to 5-HIAA metabolism.[74]^15 The gut microbial metabolite butyrate promotes the conversion of serotonin to 5-HIAA, which in turn inhibits regulatory B-cell function and B-cell differentiation through activation of AhR, ultimately ameliorating autoimmune disease.[75]^18 The above studies suggest that gut microbiota can also serve as a target for regulating 5-HIAA synthesis. There are no existing studies that have explored the impact of gut microbe-mediated 5-HIAA on antitumor immunity or the effectiveness of immunotherapy. Thus, addressing the role of 5-HIAA regulation in the context of NSCLC ICI therapy could offer new strategies to improve the typically low response rates observed in NSCLC immunotherapy. Our findings indicate that 5-HIAA levels are elevated in patients who do not respond to immunotherapy (NRs), and that the synthesis of 5-HIAA could be influenced by gut microbes. We found that increased 5-HIAA contributes directly to the suppression of tumor-infiltrating CD8^+ T cells, subsequently reducing the effectiveness of anti-PD-1 mAb treatments. The gut microbiota characteristic of NRs appears to drive this process by increasing MAO expression in intestinal epithelial cells and using the MAO inhibitor phenelzine (Phe) led to decreased synthesis of 5-HIAA, thereby reactivating CD8^+ T cells and enhancing the efficacy of anti-PD-1 mAbs. We also identified key gut microbial species—Akkermansia muciniphila (AKK) that could inhibit 5-HIAA synthesis and used it to enhance tumor-infiltrating CD8^+ T cells and immunotherapy efficacy. The combined use of Phe and AKK was particularly effective, leading to a maximal reduction in 5-HIAA synthesis and significantly enhancing the therapeutic impact of ICIs. These findings underscore the potential of targeting metabolic pathways influenced by gut microbiota to optimize immune responses in cancer therapy. By modulating microbial pathways that affect critical metabolites like 5-HIAA, it may be possible to significantly improve the response rates and outcomes of NSCLC immunotherapy. This approach suggests a promising avenue for personalized medicine, where interventions are tailored based on an individual’s microbiome to maximize therapeutic efficacy. Methods Cell lines and cell culture Lewis lung cancer (LLC) cells and B16-F10 cells were cultured in Dulbecco’s Modified Eagle’s Medium (SH30022, Cytiva, USA), supplemented with 10% fetal bovine serum (FSP500, Excell, China) and 1% penicillin-streptomycin-amphotericin B (C0224, Beyotime, China). The cells were incubated at 37℃ in an atmosphere containing 5% CO[2]. ELISA For the quantification of 5-HIAA in serum, the 5-HIAA ELISA Kit (E-EL-0075, Elabscience, China) was used. Serum samples were analyzed according to the manufacturer’s protocol. 50 µL of the standard product, diluted in a double ratio, was added to the standard hole. 50 µL of the standard product and sample diluent were added to the blank hole, and 50 µL of the sample was added to the remaining holes. Immediately after, 50 µL of the prepared biotinized antibody working solution was added to each well. The substrate was then coated and incubated at 37℃ for 45 min. The wells were drained and patted dry on clean absorbent paper. A washing solution of 350 µL was added to each well, allowed to soak for 1 min, and then the liquid was absorbed or shaken off from the enzyme label plate and patted dry. This cleaning step was repeated three times. Horseradish Peroxidase (HRP) enzyme conjugate working liquid of 100 µL was added to each well, the plate was then coated, and incubated at 37℃ for 30 min. The liquid in the wells was drained, and the board was washed five times. Tetramethylbenzidine (TMB) of 90 µL was added to each well, the enzyme-labeled plate was coated, and incubated at 37℃ for about 15 min in the dark. Once a significant gradient appeared in the standard hole, the process was terminated. The enzyme marker was turned on 15 min before preheating. A termination solution of 50 µL was added to each well to stop the reaction. The optical density of each well was immediately measured using an enzyme-labeled instrument at 450 nm. Fecal microbiota transplantation experiment Fecal microbiota transplantation (FMT) was performed using fresh feces from patients. The collected fresh feces were suspended with phosphate-buffered saline (PBS) containing 30% glycerin and then filtered through a 40 µm cell strainer (15–1040, Biologix, USA). The filtered mixture was centrifuged at 600× g for 5 min. The supernatant after precipitation removal was immediately stored at −80℃ for use. The mice were treated with an antibiotic cocktail (ABX) treatment: ampicillin (MB1507, Meilunbio, China), metronidazole (MB2200, Meilunbio, China), neomycin sulfate (MB1716, Meilunbio, China), and vancomycin hydrochloride (MB1260, Meilunbio, China). After ABX intragastric administration for a week, mice were gavaged with 200 µl fecal suspension three times a week for 2 weeks. In vivo experiments The 4–6 weeks old C57BL/6J mice and BALB/c Nude Mice were purchased from Charles River (Wilmington, USA) and reared in independently vented cages at the animal facility of Henan Experimental Animal Center (Zhengzhou, China). Approximately 1×10^5 LLC cells or B16-F10 cells were subcutaneously inoculated into the right flank of mice. For anti-PD-1 treatment, after a week of LLC implanting, mice were injected with 100 µg of IgG isotype control antibody (HY-P990679, MedChemExpress, USA) or anti-mouse PD-1 mAb (HY-[76]P99144, MedChemExpress, USA). For 5-HIAA treatment, on day 3 after LLC inoculation, each mouse was gavaged 2 mg 5-HIAA (H8876, Sigma, USA) daily. For MAO-Is treatment, on day 3 after LLC inoculation, each mouse was injected with 3 mg/kg Phe (HY-B1018A, MedChemExpress, USA) or Isocarboxazid (HY-13929, MedChemExpress, USA) or Toloxatone (HY-14196, MedChemExpress, USA) per day, the solvents for all three inhibitors were 0.9% saline, and the same volume of 0.9% saline was injected as the control group. For AKK treatment, each mouse was given 200 µl of PBS containing 10^9 Colony-Forming Units (CFU) bacteria per day. When the tumor volume reaches 1,500 mm³ or above, tumor-bearing mice are euthanized. For CD8^+ T cell depletion, each mouse was intraperitoneally injected with 100 µg of anti-mouse CD8α (BE0117, Bio X Cell, USA) or IgG isotype control (BE0090, Bio X Cell, USA) two times a week. Flow cytometry analysis To analyze tumor-infiltrating CD8^+ T cells, we ground the tumor into single cells in a 40 µm cell strainer and used red blood cell lysis buffer (R1010, Solarbio, China) to remove excess red blood cells to obtain a single cell suspension. For cell live/dead staining, cells were stained with Zombie NIR Fixable Viability Kit (423105, BioLegend, USA) at room temperature for 25 min and subsequently blocked with 5% Bovine serum albumin (BSA) Blocking Buffer (SW3015, Solarbio, China) for 5 min. For cell surface staining, cells were stained with surface antibodies CD3, CD8 (100327, 100711, BioLegend, USA) at 4 ℃ for 30 min, and then fixed by 4% paraformaldehyde (PFA) buffer (G1101, Servicebio, China) for 30 min. For intracellular cytokine staining, resuspend fixed cells in Intracellular Staining Permeabilization Wash Buffer (421002, BioLegend) and centrifuge at 350× g for 5–10 min twice, and then stain with intracellular antibodies interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α) (505829, 506304, BioLegend, USA). Flow cytometry analysis was performed using a FACSCanto II flow cytometer (BD, USA). Bacterial culture AKK (ATCC BAA-835) was purchased from China Center of Industrial Culture Collection (24917, CICC, China). The freeze-dried bacterial powder was inoculated on a brain–heart infusion (BHI) (HB8297, Hopebio, China) plate supplemented with 0.02% mucin (M1778, Sigma, USA) and cultured in an anaerobic environment generated by an anaerobic production bag (Mitsubishi Gas Chemical, Japan). After several days, the colonies were selected and placed in BHI liquid medium (containing 0.02% mucin) for expansion. After 3 days, the OD600 value of bacterial growth reached 0.6∼0.8. The bacterial solution was collected, centrifuged at 5,000 rpm for 5 min, then suspended with PBS. The bacterial concentration was detected by turbidity method, and the PBS was adjusted to the appropriate concentration for use. Immunofluorescence staining Paraffin sections were dewaxed in water through the following steps: the sections were immersed in environmental dewaxing solution for three consecutive 10 min intervals, followed by a series of washes in anhydrous ethanol I, II, and III, each for 5 min, and then rinsed in distilled water. For antigen retrieval, the tissue sections were placed in a repair box filled with EDTA antigen repair buffer and heated in a microwave oven medium heat for 8 min, paused for 8 min, then medium-low heat for 7 min. After cooling naturally, the slides were washed in PBS by shaking on the decolorizing table three times, each for 5 min. Circles were drawn around the tissue with a tissue pen after the sections had slightly dried. For blocking, BSA was added within the circle and the sections were incubated for 30 min. The primary antibody, diluted in PBS, was then gently applied after shaking off the blocking solution, and the slides were incubated overnight in a wet box at 4°C. The next day, after washing the slides in PBS three times for 5 min each on the decolorizing table, the secondary antibody, corresponding to the species of the primary antibody and diluted appropriately, was applied to the tissue and incubated at room temperature for 50 min. Nuclei were stained with 4',6-diamidino-2-phenylindole (DAPI) by drying the sections slightly, adding DAPI staining solution to the circle, and incubating for 10 min at room temperature in the dark. Self-fluorescence was quenched by adding self-fluorescence quenching agent into the circle for 5 min followed by a 10 min water wash. The slides were then sealed after a final set of three 5 min washes in PBS and shaking on the decolorizing table, and dried slightly before sealing with antifluorescence quenching tablets. Microscopic photography was carried out by placing the sections under a scanner for image acquisition or under a fluorescence microscope. Immunohistochemistry and HE staining Tumor, intestinal, liver and kidney tissue were embedded in 4% PFA for 48 hours. Intestinal, liver and kidney tissue were stained with HE for morphological examination. Immunohistochemistry (IHC) was performed to evaluate the expression of CD8 and MAO-A using IHC kits (abs957, absin, China) according to the manufacturer’s protocol. Pathology sections were scanned with a digital pathology section scanner (KF-PRO-005-EX, KonFoong Bioinformation Tech, China) and analyzed with ImageJ software. RNA sequencing Tumor tissue of 5-HIAA and control groups was used for RNA-seq. Subsequent RNA extraction and sequencing process was delegated to Tsingke Biotech (Beijing, China). For analysis of differentially expressed genes, the expression levels of all samples were combined into an expression matrix, and differential expression significance analysis was performed at the gene or transcript level to find functional differential genes or transcripts associated with the sample groups. DESeq2^6 software was used for difference significance analysis. P value less than 0.05 and the ratio of expression volume multiple greater than or equal to 2 (|log2FC|≥1) were used as the criteria for difference significance. For Gene Ontology (GO) functional enrichment analysis, all the differentially expressed genes were entered into the GO database ([77]http://www.geneontology.org/) for each map entry. The difference in the number of genes per item was calculated, followed by statistical tests to identify GO entries that were significantly enriched in the differentially expressed genes compared with the entire genome background. For gene set enrichment analysis (GSEA), all expressed genes had been sorted from the largest to the smallest based on the correlation degree with the phenotype of the two groups of samples. It was then counted whether a gene set with known functions was concentrated above or below the sorted gene list. This approach allowed for the determination of the influence of synergistic changes of genes in this gene set on phenotypic changes. 16S rRNA sequencing Feces were collected from both responders (Rs) (n=5) and NRs (n=5) groups of mice. Subsequent DNA extraction and sequencing process was delegated to Tsingke Biotech (Beijing, China). Line discriminant analysis (LDA) Effect Size (LEfSe) analysis, that is, species analysis with significant differences between groups, uses LDA to estimate the influence of the abundance of each component (species) on the difference effect. This analysis mainly aims to find species with significant differences in abundance between groups. Set the logarithmic LDA score of significant difference to 4.0. Fecal DNA extraction To examine the abundance of AKK in the gut microbes of mice in the Rs and NRs groups. Mice fecal DNA was extracted using the TIANamp Stool DNA Kit (DP328, Tiangen, China) according to the manufacturer’s protocol. Real-time quantitative PCR Real-time quantitative PCR was performed using SYBR Green Premix Pro Taq HS Qpcr Kit (AG11718, Accurate Biology, China). 16S rRNA was used as a loading control. The results were analyzed on the QuantStudio five real-time fluorescence quantitative PCR system (Applied Biosystems, USA), and the data were analyzed using the 2-^ΔΔCT method. The primer sequences are as follows: AKK: F-GTCTCAAGCGTTGTTCGGAATCACT; R-CTACGCATTTCACTGCTACACCGAG. 16s: F- CGGCAACGAGCGCAACCC; R- CCATTGTAGCACGTGTGTAGCC. Clinical samples 14 patients with NSCLC (cohort 1) receiving anti-PD-1 mAb immunotherapy at the First Affiliated Hospital of Zhengzhou University during 2021–2023 were studied. Fecal and serum samples were collected at baseline in patients with NSCLC before receiving anti-PD-1 mAb therapy and stored at −80℃. Patients whose samples were collected were assessed according to iRECIST (Immune-related Response Evaluation Criteria in Solid Tumors) criteria and divided into Rs and non-responders (NRs). In addition, 21 patients with NSCLC (cohort 2) who received anti-PD-1 therapy in the First Affiliated Hospital of Zhengzhou University from 2022 to 2024 were collected for validation study. Statistical analysis Statistical analysis was performed using GraphPad Prism V.9.5 (GraphPad Software, USA). All data are presented as the mean±SEM. The differences between groups were analyzed by two-way analysis of variance (ANOVA) or one-way ANOVA. The critical p value was set to 0.05 for significant differences. Results Elevated serum 5-HIAA was associated with reduced anti-PD-1 mAb efficacy in NSCLC To explore the role of gut microbial metabolite 5-HIAA in NSCLC immunotherapy, we collected serum and feces from patients with clinical NSCLC (cohort 1) receiving anti-PD-1 mAb immunotherapy and divided the patients into responders (Rs) and NRs groups based on immunotherapy efficacy. The serum 5-HIAA concentration of the two groups was detected by ELISA. Since some foods can affect the serum concentration of 5-HIAA, we ensured that there was no difference in the intake of these foods between the two groups of patients within 24 hours before blood drawing ([78]online supplemental table 1). The results showed that NRs had higher concentrations of 5-HIAA in their serum than Rs ([79]figure 1A). To verify this finding, we further tested the serum 5-HIAA concentrations of clinical patients in cohort 2. The results also showed that the 5-HIAA level in the Rs group was significantly lower than NRs ([80]online supplemental figure S1A). We then observed the Computed Tomography (CT) images of patients (cohort 1) with high and low 5-HIAA concentrations before and after receiving anti-PD-1 mAb treatment. The results showed that patients with high 5-HIAA levels had tumor progression after immunotherapy, while patients with low 5-HIAA levels had a better response to immunotherapy ([81]figure 1B). Overall, these findings suggest that elevated serum 5-HIAA concentrations are associated with decreased anti-PD-1 mAb efficacy. Figure 1. Serum 5-HIAA concentration is associated with anti-PD-1 mAb efficacy in patients with NSCLC. (A) The serum 5-HIAA level in Rs group (n=7) and NRs group (n=7) was compared by ELISA assay. (B) CT images of 5-HIAA low (Rs) patients and 5-HIAA high (NRs) patients before and after receiving anti-PD-1 mAb therapy. (C) The gut microbiota of patients was transplanted into mice by FMT to obtain humanized mice, and subcutaneous tumors were inoculated to observe the anti-PD-1 mAb effect. (D, E) Tumor growth curve from day 3 to day 15 and tumor volume of day 15 (n=5/group). (F) Serum 5-HIAA concentration of mice in NRs group and Rs group (n=3/group). (G) Proportion of tumor-infiltrating CD8^+ T cells in CD3^+ T cells (n=5/group). (H) Proportion of tumor-infiltrating CD4^+ T cells in CD3^+ T cells (n=5/group). Data are shown as mean±SEM. P values were determined by two-way ANOVA or one-way ANOVA, *p<0.05, **p<0.01, ***p<0.001, ns=not significant. ABX, antibiotic cocktail; ANOVA, analysis of variance; FMT, fecal microbiota transplantation; 5-HIAA, 5-hydroxyindoleacetic acid; LLC, Lewis lung cancer; mAb, monoclonal antibody; NRs, non-responders; NSCLC, non-small cell lung cancer; PD-1, programmed death 1; Rs, responders. [82]Figure 1 [83]Open in a new tab The synthesis of 5-HIAA is affected by the gut microbiota,[84]^19 so we hypothesized that the elevated serum 5-HIAA of NRs is caused by the specific gut microbiota distribution of patients. We used FMT to transplant the gut microbiota of two groups of patients into mice to obtain humanized mice at the gut microbiota level. At the same time, the mice were inoculated with LLC and treated with anti-PD-1 mAb to observe their response to immunotherapy and changes in 5-HIAA metabolism ([85]figure 1C). By monitoring tumor size, we found that mice that received the gut microbiota of the Rs were significantly inhibited in tumor growth after receiving anti-PD-1 mAb treatment, while mice that transplanted the gut microbiota of NRs did not show a good response to anti-PD-1 mAb treatment ([86]figure 1D and E). The survival of mice in the Rs group was significantly longer than that of mice in the NRs group after receiving anti-PD-1 mAb treatment ([87]online supplemental figure S1B). Serum concentration of 5-HIAA was measured in both groups of mice by ELISA, and not surprisingly, the mice that received NRs’ gut microbiota had higher levels of 5-HIAA compared with the mice that received Rs ([88]figure 1F). Flow cytometry was used to detect tumor-infiltrating CD8^+ T cells and CD4^+ T cells in several groups of mice. The results showed that compared with the Rs group, the proportion of tumor-infiltrating CD8^+ T cells to CD3^+ T cells was significantly decreased in the NRs group ([89]figure 1G, [90]online supplemental figure S1C), but there was no significant difference in CD4^+ T cells between Rs and NRs groups ([91]figure 1H, [92]online supplemental figure S1D). These results demonstrated that 5-HIAA produced by NRs’ characteristic gut microbiota is associated with a diminished anti-PD-1 mAb efficacy in NSCLC. 5-HIAA reduced anti-PD-1 mAb efficacy by inhibiting tumor-infiltrating CD8^+ T cells In order to further investigate the effects of 5-HIAA on antitumor immunity and immunotherapy, 5-HIAA was directly administered to mice, and the anti-PD-1 mAb efficacy and the function of CD8^+ T cells were observed ([93]figure 2A). The results showed that 5-HIAA increased tumor growth and significantly inhibited the anti-PD-1 mAb efficacy ([94]figure 2B). In order to observe the effects of 5-HIAA on the TME, especially TILs, we performed RNA-seq on tumor tissues of both 5-HIAA treated and control group mice. The differential gene expression results showed that the expression of genes related to CD8^+ T cell function, such as Cd8a (which encodes CD8 transmembrane glycoprotein, CD8 is mainly expressed on the surface of cytotoxic T cells, and plays a role in the development of T cells and the activation of mature T cells), Tnf (which encodes TNF, TNF is a multifunctional proinflammatory cytokine that plays a key role in the tumor-killing effect mediated by CD8^+ T cells) and Ifngr2 (which encodes IFN-γ receptor 2 (IFN-γ R2) that is one of the subunits of the receptor for IFN-γ, and IFN-γ is a cytokine that is crucial for adaptive immunity to resist tumor), were downregulated in the 5-HIAA group compared with the control group ([95]figure 2C). GO analysis showed significant enrichment in pathways such as “immune response”, “adaptive immune response” and “positive regulation of T cell proliferation”, indicating that 5-HIAA has an impact on antitumor immunity, especially T cell immune function ([96]figure 2D). In addition, GSEA pathway enrichment analysis showed a significant downregulation of the TNF signaling pathway in the 5-HIAA group, suggesting that 5-HIAA has an inhibitory effect on T cell activation ([97]figure 2E). The NF-κB signaling pathway was similarly enriched in response to 5-HIAA ([98]figure 2E), which is considered an important regulator of adaptive immune responses.[99]^20 To further explore the effect of 5-HIAA on TIL, CD8^+ T cells in mouse tumors were analyzed by flow cytometry. We observed that 5-HIAA reduced the proportion of CD8^+ T cells in CD3^+ T cells ([100]figure 2F and G). The expression of cytokines TNF-α and including IFN-γ, which represent CD8^+ T cell antitumor activation, was significantly reduced under the action of 5-HIAA, while the upregulation of cytokines by anti-PD-1 mAb was also counteracted by 5-HIAA ([101]figure 2H and I, [102]online supplemental figure S1E and F). To confirm whether 5-HIAA plays the same role in other cancers, we observed the effect of 5-HIAA on anti-PD-1 treatment of melanoma in mice ([103]online supplemental figure S1G). The results were consistent with the above results. 5-HIAA weakened the efficacy of anti-PD-1 mAb ([104]online supplemental figure S1H) and inhibited the infiltration of CD8^+ T cells in the tumor ([105]online supplemental figure S1I and J). Figure 2. 5-HIAA reduces anti-PD-1 mAb efficacy by inhibiting tumor-infiltrating CD8^+ T cells. (A) After 3 days of LLC implantation, 5-HIAA was administered daily, and after 7 days, αPD-1 mAb or isotype was injected every 3 days. (B) The tumor growth curves of each group of mice were measured every 3 days starting on day 3 and tumor volume of each group of mice on day 15 (n=5/group). (C) Differentially expressed genes between 5-HIAA treatment and control group. (D) GO pathway enrichment analysis of RNA-seq of mouse tumors from control and 5-HIAA groups. (E) GSEA enrichment analysis of mouse tumors in control group and 5-HIAA group. (F, G) The proportion of tumor-infiltrating CD8^+ T cells to CD3^+ T cells in each group (n=5/group). (H, I) The frequencies of tumor-infiltrating IFN-γ and TNF-α CD8^+ T cells (n=5/group). (J) Effect of 5-HIAA treatment on tumor growth in subcutaneous tumor BALB/c Nude Mice (n=5/group). (K) Effect of 5-HIAA treatment on tumor growth in CD8^+ T cell depletion mice (n=5/group). Data are shown as mean±SEM. P values were determined by two-way ANOVA or one-way ANOVA, *p<0.05, **p<0.01, ****p<0.0001. ANOVA, analysis of variance; FPKM, Fragments Per Kilobase of exon model per Million mapped fragments; GO, Gene Ontology; GSEA, gene set enrichment analysis; SSC, Side Scatter; 5-HIAA, 5-hydroxyindoleacetic acid; IFN-γ, interferon-γ; LLC, Lewis lung cancer; mAb, monoclonal antibody; ns, not significant; PD-1, programmed death 1; TNF-α, tumor necrosis factor-alpha. [106]Figure 2 [107]Open in a new tab To further validate that 5-HIAA exerts a tumor-promoting effect by inhibiting tumor-infiltrating CD8^+ T cells, we supplemented BALB/c Nude Mice, a T-cell-deficient mouse, with 5-HIAA and found that the tumor volume did not further increase relative to the control group ([108]figure 2J, [109]online supplemental figure S1K). Then, in C57 mice, we first used αCD8 mAb to eliminate CD8^+ T cells in mice ([110]online supplemental figure S1L and M). We then administered 5-HIAA to αCD8 mAb-treated C57 mice and observed the tumor growth, suggesting that in CD8^+ T cell-depleted mice, 5-HIAA did not further increase the tumor volume compared with the control group ([111]figure 2K, [112]online supplemental figure S1N). Together, these data indicate that 5-HIAA can inhibit antitumor immunity and anti-PD-1 mAb efficacy by inhibiting CD8^+ T cells infiltrating tumors. Phe enhanced tumor-infiltrating CD8^+ T cells and efficacy of anti-PD-1 mAb by inhibiting 5-HIAA synthesis The production of 5-HIAA is dependent on the catalytic metabolism of 5-HT by MAOA.[113]^14 We therefore looked at the expression status of MAO in the intestinal epithelial cells of mice in the NRs and R groups and found that the characteristic gut microbiota of NRs caused elevated MAO expression in intestinal epithelial cells ([114]figure 3A and B). So, we explored whether MAO-Is can inhibit 5-HIAA metabolism and restore antitumor immunity. We selected several clinically common MAO-Is, including Isocarboxazid (Iso), Toloxatone (Tol), and Phe, to explore their effects on 5-HIAA level and antitumor immunity ([115]figure 3C). The use of several MAO-Is significantly inhibited the growth of tumors, among which Phe played the most obvious antitumor effect ([116]figure 3D). MAO-Is had a reducing effect on 5-HIAA levels, with Phe having the most significant effect ([117]figure 3E). Flow cytometry examined the effect of MAO-Is on CD8^+ T cells, and the results showed that they all increased the proportion of CD8^+ T cells in CD3^+ T cells, and Phe had the most significant effect ([118]figure 3F and G). TNF-α and IFN-γ expression exhibited the same trend as CD8 expression ([119]figure 3H and I, [120]online supplemental figure S2A and B). Figure 3. MAO-I Phe enhances tumor CD8^+ T cell infiltration and anti-PD-1 mAb effect by inhibiting 5-HIAA production. (A, B) MAO expression in intestinal epithelial cells as reflected by IHC assay (n=3/group). (C) The mice received several MAO-I treatments 3 days after inoculation with LLC tumor cells. (D) Growth curves of subcutaneous tumors and tumor volume on day 15 in mice treated with different MAO-I treatments (n=5/group). (E) Serum 5-HIAA concentration in mice after several MAO-I treatments (n=3/group). (F, G) The proportion of CD8^+ T cells in the tumor of mice in different groups after different MAO-I treatments (n=5/group). (H, I) TNF-α and IFN-γ expression of CD8^+ T cell (n=5/group). (J) After LLC cell injection, Phe or saline was injected daily from the 3rd day, and anti-PD-1 mAb or isotype was injected two times from the 7th day. (K) Phe and anti-PD-1 mAb treated mice tumor growth curve and tumor volume on day 15 (n=5/group). (L) The frequencies of CD8^+ T cells to CD3^+ T cells in the tumor of mice in each group (n=5/group). (M, N) The frequencies of tumor-infiltrating TNF-α and IFN-γ CD8^+ T cells (n=5/group). Data are shown as mean±SEM. P values were determined by two-way ANOVA or one-way ANOVA, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. ANOVA, analysis of variance; 5-HIAA, 5-hydroxyindoleacetic acid; IFN-γ, interferon-gamma; IHC, immunohistochemistry; Iso, Isocarboxazid; LLC, Lewis lung cancer; mAb, monoclonal antibody; MAO, monoamine oxidase inhibitor; NRs, non-responders; PD-1, programmed death 1; Phe, phenelzine; Rs, responders; SSC, Side Scatter; TNF-α, tumor necrosis factor-alpha; Tol, Toloxatone. [121]Figure 3 [122]Open in a new tab Based on the above results, we further selected Phe to observe its enhancement effect on anti-PD-1 mAb treatment ([123]figure 3J). Not surprisingly, the tumor volume was significantly reduced under the combined action of the two drugs, indicating that Phe significantly enhanced the antitumor effect of anti-PD-1 mAb ([124]figure 3K). We further explored the changes of CD8^+ T cells in the tumor. Flow cytometry showed that the combination of Phe and anti-PD-1 mAb significantly increased the frequency of CD8^+ T cells in CD3^+ cells ([125]figure 3L, [126]online supplemental figure S2C). In addition, the release of cytokines IFN-γ and TNF-α in CD8^+ T cells also increased significantly ([127]figure 3M and N, [128]online supplemental figure S2D and E). These data all support that MAO-Is Phe reduces the metabolic production of 5-HIAA by inhibiting MAO-A, thereby enhancing the activity of CD8^+ T cells, and ultimately improving the immunotherapy effect of anti-PD-1 mAb. AKK reduced 5-HIAA synthesis and thus augmented antitumor immunity Much evidence suggests that the distribution of gut microbiota influences 5-HIAA synthesis by then causing a range of physiological and disease changes such as psychiatric disorders, endocrine disorders, and inflammation-related responses.[129]15,[130]18 Therefore, we examined the distribution of bacteria in the feces of humanized mice in the Rs and NRs groups by 16s rRNA sequencing. LEfSe analysis indicated that AKK is the most important component of Rs group (LDA score=4.27, p=0.0011) ([131]figure 4A). Histograms of the distribution of LDA values show that AKK abundance is significantly upregulated in Rs ([132]figure 4B). The histogram of abundance between marker groups demonstrates the individual differences between the two groups, and it can be seen that AKK is upregulated in individuals in the Rs group ([133]figure 4C). Based on the findings in mouse samples, we further validated the results in clinical cohort 1, using real-time PCR to detect the content of AKK in the fecal DNA of Rs and NRs patients, and the results still suggested that the abundance of AKK in the Rs group was higher than that in the NRs group ([134]figure 4D). Real-time PCR analysis of humanized mice feces showed the same result ([135]online supplemental figure S3A). The above results suggested that AKK is enriched in the intestines of Rs, which may be the key factor causing the reduction of 5-HIAA concentration in the serum of Rs. It has been shown that AKK can affect the production of 5-HT, the upstream metabolite of 5-HIAA.[136]^21 22 Figure 4. AKK enhances tumor-infiltrating CD8^+ T cells and anti-PD-1 mAb efficacy by inhibiting 5-HIAA synthesis. (A) Circles radiating from inside to outside of the LEfSe evolutionary branching diagram represent taxonomic levels from phylum to species. Species without significant differences are uniformly colored yellow, circles of different colors indicate different subgroups, and nodes of different colors indicate microbiota that play an important role in the subgroup represented by that color (n=10/group). (B) Histogram of the distribution of LDA showing the taxonomic units with higher abundance and significant differences between the two groups of samples, with the significantly higher species in the Rs group being AKK (n=10/group). (C) Marker intergroup abundance histograms show the relative abundance of AKK for different individuals in each group, with solid and dashed lines identifying the mean and median relative abundance of that taxonomic unit in each subgroup (n=10/group). (D) Real-time PCR demonstrating fecal AKK abundance in the Rs and NRs patients (n=10/group). (E) The correlation between the abundance of fecal AKK and the concentration of serum 5-HIAA (n=14 patients). (F) LLC-bearing mice were given AKK supplementation plus anti-PD-1 mAb treatment to observe the effect of AKK on immunotherapy. (G) Tumor growth curves and tumor volume at day 15 (n=5/group). (H) Serum 5-HIAA concentration of mice in each group (n=3/group). (I–L) The proportion of CD8^+ T cells to CD3^+ T cells in the tumor and the expression of IFN-γ and TNF-α in CD8^+ T cells (n=5/group). Data are shown as mean±SEM. P values were determined by one-way ANOVA, *p<0.05, **p<0.01, ***p<0.001. AKK, Akkermansia muciniphila; ANOVA, analysis of variance; 5-HIAA, 5-hydroxyindoleacetic acid; IFN-γ, interferon-gamma; LDA, line discriminant analysis; LEfSe, Line Discriminant Analysis Effect Size; LLC, Lewis lung cancer; mAb, monoclonal antibody; NRs, no-responders; PD-1, programmed death 1; Rs, responders; SSC, Side Scatter; TNF-α, tumor necrosis factor-alpha. [137]Figure 4 [138]Open in a new tab The correlation analysis combining the serum 5-HIAA concentrations of humans showed that the abundance of AKK was significantly negatively correlated with the 5-HIAA concentration ([139]figure 4E). The data of humanized mice samples obtained the same result ([140]online supplemental figure S3B). We therefore attempted to explore the effect of AKK on 5-HIAA concentration and on antitumor immunity ([141]figure 4F). The results showed that supplementation of AKK significantly enhanced the tumor inhibition effect of anti-PD-1 mAb ([142]figure 4G). We then tested the effect of AKK on serum 5-HIAA concentration and found that AKK reduced 5-HIAA production ([143]figure 4H). Flow cytometry was employed to observe the content of tumor infiltration CD8^+ T cells, and it was found that the CD8^+ T cell infiltration increased significantly under the combined action of AKK and anti-PD-1 mAb ([144]figure 4I and J). The activation of CD8^+ T cells by AKK+anti-PD-1 mAb was observed, because the expression of cytokines IFN-γ and TNF-α was significantly upregulated ([145]figure 4K and L, [146]online supplemental figure S3C and D). These results confirm that AKK is a key gut microbiota responsible for the difference in serum 5-HIAA concentrations between NRs and Rs, and that supplementation of AKK reduces 5-HIAA synthesis and enhances tumor-infiltrating CD8^+ T cells and anti-PD-1 mAb efficacy. Phe combined with AKK reduced 5-HIAA concentration and activated tumor-infiltrating CD8^+ T cells To further explore whether AKK combined with Phe can further reduce 5-HIAA metabolism and enhance CD8^+ T cell function. We used Phe combined with AKK to observe the effect on tumor-bearing mice ([147]figure 5A). As expected, Phe combined with AKK significantly inhibited tumor growth compared with either Phe or AKK alone ([148]figure 5B). Their effects on 5-HIAA concentration were examined, and ELISA results confirmed that Phe combined with AKK further reduced the metabolic production of 5-HIAA ([149]figure 5C). Flow cytometry was used to determine the effect of the two drugs on antitumor immunity, and the results showed that the combination of Phe and AKK increased the number of CD3^+ CD8^+ T cells in the tumor ([150]figure 5D and F). Immunohistochemistry (IHC) of tumor tissue for CD8^+ T cells showed the same results ([151]figure 5E and G). Flow cytometry further detected cytokines that reflect the activation state of CD8^+ T cells, and it was found that the expressions of IFN-γ and TNF-α were also significantly upregulated under the simultaneous action of Phe and AKK ([152]figure 5H and I, [153]online supplemental figure S3E and F). CD4^+ and CD8^+ immunofluorescence staining were performed on tumor tissues to observe the proportion of CD4^+ T cells and CD8^+ T cells. The results showed that Phe combined with AKK significantly enhanced the infiltration of CD8^+ T cells, but had no effect on CD4^+ T cells compared with single treatment ([154]figure 5J–L). HE staining of liver, kidney and intestinal tissue showed no tissue damage after treatment with Phe and AKK ([155]online supplemental figure S3G). Collectively, these findings confirmed that Phe combined with AKK could inhibit the synthesis of 5-HIAA to a greater extent and further enhance the function of tumor-infiltrating CD8^+ T-cells without significant toxic side effects. Figure 5. Phe combined with AKK decreased 5-HIAA concentration and activated tumor-infiltrating CD8^+ T cells. (A) LLC-bearing mice were given AKK and Phe treatments. (B) Tumor growth curves of day 3 to day 15 and tumor volume at day 15 (n=5/group). (C) Serum 5-HIAA concentration of mice in each group (n=5/group). (D, F) Percentage of CD3^+ CD8^+ T cells infiltrating the tumor (n=5/group). (E, G) Representative IHC results of CD8^+ T cells in tumor tissues and the percentage of positive cells in the area (n=5/group). (H, I) The expression of IFN-γ and TNF-α in CD8^+ T cells (n=5/group). (J) Representative immunofluorescence images of tumor tissues for CD8^+, CD4^+ cells in each group (n=5/group). (K, L) The proportions of CD4^+ and CD8^+ T cells in DAPI respectively. Data are shown as mean±SEM. P values were determined by one-way ANOVA, *p<0.05, **p<0.01, ns=not significant. AKK, Akkermansia muciniphila; ANOVA, analysis of variance; DAPI, 4',6-diamidino-2-phenylindole; 5-HIAA, 5-hydroxyindoleacetic acid; IFN-γ, interferon-gamma; IHC, immunohistochemistry; LLC, Lewis lung cancer; Phe, phenelzine; TNF-α, tumor necrosis factor-alpha. [156]Figure 5 [157]Open in a new tab AKK combined with Phe augmented the anti-PD-1 mAb efficacy We further observed whether Phe combined with AKK further enhanced anti-PD-1 mAb efficacy in LLC mice. We carried out anti-PD-1 mAb treatment on tumor-bearing mice on the basis of Phe combined with AKK ([158]figure 6A). The results showed that simultaneous treatment of AKK and Phe maximized the therapeutic effect of anti-PD-1 mAb compared with using them alone ([159]figure 6B–D). The combination of AKK and Phe with anti-PD-1 mAb also significantly prolonged the survival of the mice ([160]online supplemental figure S3H). Comparing the body weights of the mice in each group, no significant differences were found, indicating that our combined treatment does not cause weight-related adverse effects such as gastrointestinal side effects in mice ([161]figure 6E). The proportion of CD3^+ CD8^+ T cells in the tumor of mice in each group was compared, and the results showed that the proportion of CD3^+ CD8^+ T cells was the highest when Phe combined with AKK assisted anti-PD-1 mAb ([162]figure 6F). The above results demonstrated the effects of Phe and AKK on anti-PD-1 mAb efficacy in a common mouse model, and we thought to establish a humanized mouse model of NRs to simulate the effects of coadministration in humans. After FMT, LLC was injected subcutaneously and given each of the combination therapy as usual ([163]figure 6G). The results showed that under the combined action of Phe and AKK, the response of NRs mice to anti-PD-1 mAb treatment was significantly improved ([164]figure 6H and I). The survival time of the mice in the combined treatment group was longer than that of the mice in any of the groups that used the two drugs in combination ([165]online supplemental figure S3I). Moreover, the combined treatment also significantly increased the number of tumor-infiltrating CD8^+ T cells in NRs mice ([166]online supplemental figure S3J). The above results illustrate that the adjuvant treatment strategy of Phe combined with AKK maximized anti-PD-1 immunotherapy efficacy, including increased sensitivity to immunotherapy in NRs mice. Figure 6. AKK combined with Phe enhanced the anti-PD-1 mAb efficacy. (A) LLC-bearing mice were given AKK, Phe and anti-PD-1 mAb treatments. (B, C) Tumor growth curves of day 3 to day 15 and tumor volume at day 15 in different groups (n=5/group). (D) Tumor weight in each group of mice (n=5/group). (E) Weight of mice in each group (n=5/group). (F) CD8 expression in CD3^+ cells in tumors of mice in each group (n=5/group). (G) NRs humanized mice were treated with AKK, Phe and anti-PD-1 mAb after inoculation with LLC. (H, I) Tumor growth curves of day 3 to day 15 and tumor volume at day 15 in different groups (n=5/group). Data are shown as mean±SEM. P values were determined by two-way ANOVA or one-way ANOVA, *p<0.05, **p<0.01, ***p<0.001. ABX, antibiotic cocktail; AKK, Akkermansia muciniphila; ANOVA, analysis of variance; FMT, fecal microbiota transplantation; LLC, Lewis lung cancer; mAb, monoclonal antibody; NRs, non-responders; ns, not significant; PD-1, programmed death 1; Phe, phenelzine. [167]Figure 6 [168]Open in a new tab Discussion ICIs represented by anti-PD-1 mAb have improved the survival of many patients with NSCLC.[169]^23 However, improving response rates is a major issue that needs to be addressed in the current treatment of ICIs.[170]^24 Thus, determining the various factors that can influence the effectiveness of immunotherapy is critical. Up to now, a large number of studies have pointed out that gut microbiota and their metabolites are related to antitumor immunity and ICIs efficacy.[171]1012 25,[172]27 One of the most important pathways in gut microbial metabolites, tryptophan metabolism pathway, represented by the tryptophan–kynurenine pathway, plays multiple roles in antitumor immunity.[173]^28 A clinical single-cohort study collected serum from 53 patients with NSCLC receiving anti-PD-1 mAb therapy and analyzed free amino acids and tryptophan metabolites in the serum. Cox proportional hazard analysis showed that higher tryptophan levels and lower kynurenine levels were positively associated with overall survival and antitumor immunity.[174]^29 In addition to being metabolized primarily into kynurenine, about 1–2% of tryptophan is metabolized into 5-HT.[175]^14 Although 5-HT is generally thought of as a neurotransmitter that plays a role in the brain, more than 90% of 5-HT is actually produced in the gut through tryptophan metabolism.[176]^13 Our prior microbiomic and metabolomic research on patients with NSCLC undergoing anti-PD-1 mAb treatment has shown that chronic stress can disrupt gut microbiota and lead to disturbances in tryptophan metabolism. This disruption was primarily characterized by the upregulation of the tryptophan–5-HT–5-HIAA metabolic pathway, which in turn contributes to tumor-related immune suppression and the failure of immunotherapy. Based on these findings, we explored the possibility that elevated levels of 5-HIAA might be a contributing factor to the low response rates observed in patients with NSCLC treated with anti-PD-1 therapy in the current study. In the tryptophan–5-HT–5-HIAA metabolic pathway, tryptophan is first hydroxylated to 5-HTP by TPH, then rapidly decarboxylated to 5-HT by DDC, and finally further metabolized to 5-HIAA by MAO.[177]^14 Inhibition of MAO might inhibit 5-HIAA synthesis and block the inhibition of TIL and immunotherapy efficacy by 5-HIAA. Up to now, a variety of MAO-Is have been developed and have been used in the treatment of depression for a long time, the main pharmacological effect is to inhibit the excessive oxidation of MAO to monoamines such as 5-HT and reduce their secondary metabolites content.[178]^30 31 MAO-Is have been in the clinic for many years, mainly for the treatment of depression and anxiety by inhibiting the conversion of 5-HT to 5-HIAA and then increasing the synaptic gap 5-HT concentration in the brain.[179]^32 However, our study used MAO-Is for the first time in the adjuvant treatment of anti-PD-1 mAb, and found a novel application of MAO-Is in the field of tumor therapy. Direct manipulation of the distribution of gut microbiota to influence tryptophan metabolic pathways is an effective strategy to regulate 5-HIAA synthesis. B. breva has been clinically shown to alleviate major depression by modulating tryptophan metabolism, particularly the shift from 5-HT to 5-HIAA.[180]^15 Burkholderia spp-mediated conversion of tryptophan to 5-HIAA induces elevated 5-HIAA to activate AhR and promote hepatic insulin signaling, resulting in improved insulin sensitivity and alleviation of type 2 diabetes.[181]^16 These studies prompted us to explore the gut microbiota that cause differences in serum 5-HIAA concentrations and to use it to modulate 5-HIAA synthesis and antitumor immunity. By comparing clinical samples and humanized mice, we found that elevated serum 5-HIAA concentrations correlated with failure of anti-PD-1 mAb efficacy and that 5-HIAA synthesis was regulated by specific gut microbiota. In addition, we demonstrated that 5-HIAA led to decreased immunotherapy efficacy by inhibiting tumor-infiltrating CD8^+ T cells. Supplementation of MAO-I Phe reduced 5-HIAA synthesis thereby increasing CD8^+ T cell activation in tumors and anti-PD-1 mAb efficacy. 16s rRNA sequencing identified the key gut microbiota, AKK, that caused differences in 5-HIAA concentrations. Supplementation of AKK in vivo exerted inhibition of 5-HIAA synthesis as well as enhanced anti-PD-1 mAb efficacy. The combination of Phe and AKK maximally inhibited 5-HIAA synthesis and further enhanced tumor-infiltrating CD8^+ T cell activity, ultimately enhancing the efficacy of anti-PD-1 mAb. In conclusion, our current findings reveal an association between specific gut microbe-mediated elevations in serum 5-HIAA concentrations and immunotherapy failure in patients with NSCLC treated with anti-PD-1 mAb. These observations suggest that serum 5-HIAA could serve as a promising biomarker for forecasting the effectiveness of anti-PD-1 immunotherapy. This potential biomarker provides a measurable indicator that may help predict patient responsiveness to therapy, allowing for more personalized and potentially more effective treatment plans. Moreover, we observed that using MAO-Is or supplementing with AKK to reduce 5-HIAA concentrations could be a viable therapeutic strategy to enhance the efficacy of immunotherapy. By targeting and modulating this specific metabolic pathway, we can potentially reverse the immunosuppressive environment fostered by high 5-HIAA levels, thus improving patient outcomes. This approach not only underscores the significance of the gut microbiome in cancer therapy but also highlights innovative avenues for enhancing immunotherapy efficacy through microbiome and metabolic interventions. Overall, such strategies could pave the way for breakthroughs in clinical practice, offering new hope for patients with low initial responsiveness to current treatments. Study Limitations Given the intricate crosstalk among gut microbiota, metabolites, and the host immune system, the role of 5-HIAA is unlikely to be the sole pathway through which Phe combined with AKK enhances the efficacy of anti-PD-1 mAb. Other factors, such as neurotransmitters or other tryptophan metabolites, may also contribute to the observed therapeutic effect. In some flow cytometry analyses, the cell count per sample ranged from 500 to 1,000, which may affect analytical precision. Future studies will address this limitation through improved analytical methods and gating strategies. Furthermore, the clinical validation in this study is constrained by a relatively small sample size and its single-center design. Future multi-center studies with larger cohorts are warranted to confirm our findings. Supplementary material online supplemental file 1 [182]jitc-13-9-s001.pdf^ (13.4MB, pdf) DOI: 10.1136/jitc-2025-011831 Footnotes Funding: This work was supported by grants from the Scientific Research and Innovation Team of The First Affiliated Hospital of Zhengzhou University (ZYCXTD2023005), the National Natural Science Foundation of China (32370976), the Key Research and Development Projects in Henan Province (241111314000), the Collaborative Innovation Major Project of Zhengzhou (20XTZX08017), Science and Technology Project of Henan Provincial Department of Education (21A320036), State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia Fund (SKL-HIDCA-2022-JZ5), Wu Jieping Medical Foundation Special Fund for Targeted Cancer Research (320.6750.2023-02-1), Key scientific research project plan of colleges and universities in Henan Province (22A416012). The funders were not involved in, for example, study design, data collection, analysis, report writing, decision to submit the paper for publication. Provenance and peer review: Not commissioned; externally peer reviewed. Patient consent for publication: Not applicable. Ethics approval: Not applicable. Data availability statement Data are available upon reasonable request. References