Abstract Background Intratumor-resident bacteria represent an integral component of the tumor microenvironment (TME). Microbial dysbiosis, which refers to an imbalance in the bacterial composition and bacterial metabolic activities, plays an important role in regulating breast cancer development and progression. However, the impact of specific intratumor-resident bacteria on tumor progression and their underlying mechanisms remain elusive. Methods 16S rDNA gene sequencing was used to analyze the cancerous and paracancerous tissues from breast cancer patients. The mouse models of bearing 4T1 cell tumors were employed to assess the influence of bacterial colonization on tumor growth. Tissue infiltration of regulatory T (Treg) cells and CD8^+ T cells was evaluated through immunohistochemistry and flow cytometric analysis. Comparative metabolite profiling in mice tumors was conducted using targeted metabolomics. Differential genes of tumor cells stimulated by bacteria were analyzed by transcriptomics and validated by qPCR assay. Results We found that Sphingobacterium displayed high abundance in cancerous tissues. Intra-tumoral colonization of Sphingobacterium multivorum (S. multivorum) promoted tumor progression in 4T1 tumor-bearing mice. Moreover, S. multivorum diminished the therapeutic efficacy of αPD-1 mAb, which was associated with the increase of regulatory T cell (Treg) infiltration, and decrese of the CD8^+ T cell infiltration. Targeted metabolomics revealed a conspicuous reduction of propionylcarnitine in tumors colonized by S. multivorum Furthermore, the combination of metabolite propionylcarnitine and S. multivorum shown to suppress tumor growth compared that in S. multivorum alone in vivo. Mechanistically, S. multivorum promoted the secretion of chemokines CCL20 and CXCL8 from tumor cells. CCL20 secreted into the TME facilitated the recruitment of Treg cells and reduced CD8^+ T cell infiltration, thus promoting tumor immune escape. Conclusions This study reveals S. multivorum suppresses immune surveillance within the TME, thereby promoting breast cancer progression. Supplementary Information The online version contains supplementary material available at 10.1186/s12943-024-02202-9. Keywords: Breast cance, Sphingobacterium multivorum, Immune escape, Treg cell, Propionylcarnitine Background Breast cancer (BC) is the most common cancer worldwide. The rising incidence of BC especially among the youth population has become a severe threat to women’s health [[35]1]. With the advance of microbial detection techniques and the increased understanding about intratumoral microbes, intratumor-resident bacteria are considered an essential regulator within the tumor microenvironment (TME) [[36]2, [37]3]. These microorganisms typically coexist in equilibrium with the host, influencing physiological processes [[38]4]. Disruption of this balance is implicated in an array of diseases, affecting tumor progression [[39]5, [40]6], drug resistance [[41]7], and treatment response [[42]8], which attracted increasing attention in various scientific research communities. Several studies have shown that intratumoral microorganisms or their metabolites can contribute to cancer progression and metastasis by modifying the proportion and function of tumor-infiltrating lymphocytes (TILs) in the TME. For instance, intratumor-resident F. nucleatum can accelerate breast cancer progression and metastasis via T cell inhibition within the TME [[43]6]. The commensal microbiota-related metabolite trimethylamine N-oxide was also shown to promote CD8^+ T cell-mediated immunity against tumors [[44]9]. However, the influence of other potential microorganisms in the tumor and their mechanisms remain largely elusive. Regulatory T (Treg) cells are physiologically immunosuppressive subpopulations of T cells that play an essential role in maintaining immune tolerance [[45]10]. Treg cells can be divided into natural regulatory T (nTreg) cells and induced regulatory T (iTreg) cells. Both types of Treg cells express the transcription factor FoxP3 [[46]11]. nTreg cells are produced naturally in the thymus, which are mainly responsible for maintaining normal immune tolerance and controlling inflammatory responses [[47]12]. On the other hand, iTreg cells originate from naïve T cells in the periphery. They are induced by signals from the TME, including tumor-derived antigens, cytokines, and other soluble molecules [[48]13]. iTreg cells within the TME can suppress the anti-tumor effects of CD8^+ T cells, natural killer cells, and dendritic cells through multiple mechanisms, thereby promoting tumor progression [[49]14]. We identified Sphingobacterium multivorum (S. multivorum), which showed a high abundance in the tumor tissues of breast cancer patients. Sphingobacterium species are aerobic and Gram-negative bacteria, known as opportunistic human pathogens, implicated in serious infections, including cellulitis, endocarditis, meningitis, and bacteremia [[50]15]. Emerging evidence indicates that Sphingobacterium presents across diverse clinical samples from cancer patients. For example, Sphingobacterium can be detected in the urine of bladder cancer patients [[51]16], fecal samples from colon adenocarcinoma patients [[52]17], the tumor tissues of triple-negative breast cancer [[53]18], intrahepatic cholangiocarcinoma [[54]19], and pancreatic ductal adenocarcinoma [[55]5]. To this end, the effect of S. multivorum on breast cancer growth remains to be elucidated. In this study, we performed 16S rDNA gene sequencing on tumor and paracancerous tissue of breast cancer patients. S. multivorum was identified as one of the most abundant residents in tumor tissues. In 4T1 tumor-bearing mouse model, intra-tumoral injection of S. multivorum diminished the therapeutic efficacy of αPD-1 mAb, increased Treg cells, and reduced the CD8^+ T cell infiltration. Furthermore, targeted metabolomic analysis of tumor tissues showed a substantial decline in the carnitine metabolite propionylcarnitine in the mice injected with S. multivorum. Propionylcarnitine inhibited the proportion of Treg cells in mouse spleen lymphocytes in vitro. Mechanistically, S. multivorum promoted the release of chemokine CCL20, which reduced the ratio of CD8^+ T cells/Treg cells within the TME. Our findings demonstrated that intratumoral S. multivorum could influence the proportion and function of TILs and they played a major role in immune surveillance within the TME. Methods Patients and samples Paracancerous tissues (n = 21) and tumor tissues (n = 20) were collected from breast cancer patients with informed consent. Demographic information and clinical characteristics of the breast cancer patients are shown in Table [56]S1. The investigation complied with pertinent ethical standards governing human participant research. The collection and use of patient-derived tumor specimens for research was approved by Ethics Committee of Yuebei People’s Hospital (Reference KY-2022-057). Culture of bacteria and cancer cell lines S.multivorum was purchased from the BeNa Culture Collection and incubated in LB medium under 30℃ aerobic conditions. Human breast cancer cells (4T1, MDA-MB-231, and BT2) were cultured in DMEM (for MDA-MB-231 cells and BT20 cells) or RPMI 1640 (for 4T1 cells). The cell line cultures were maintained at 37℃ and 5% carbon dioxide. 16S rDNA gene sequencing of human breast samples Tumors were removed surgically, and specimens from the resected breast cancerous tissue and adjacent tissue were harvested under aseptic conditions and placed the specimen on a separate sterile surface. After accurately getting the required tissue, we put the tissue in the preservation tube. All specimens were stored at − 80°C till further use. Sequencing of the cDNA library was conducted by Gene Denovo Biotechnology (Guangzhou, China). DNA was extracted from cancerous tissue (n = 21) and adjacent tissue (n = 20) of breast cancer patients. The quantity and quality of DNA was assessed using a spectrophotometer and agarose gel electrophoresis. Ribosomal 16S rDNA V3-V4 region was amplified with universal primers: forward F (5’-CCTACGGGNGGCWGCAG-3’) and reverse R (5’-GGACTACHVGGGTATCTAAT-3’) [[57]20]. The amplified DNA fragments were visualized by agarose gel electrophoresis in 2% gel and subsequently extracted and purified using the AxyPrep DNA Gel Extraction kit. Sequencing libraries were constructed employing SMRTbellTM template preparation kits from SMRTbell following the manufacturer’s recommendations. In order to obtain high-quality clean reads, the raw data were filtered using FASTP to remove reads containing more than 10% unknown bases (N) and to exclude reads with less than 50% of bases having a quality score below 20 [[58]21]. The UPARSE pipeline was then employed to cluster valid tags into operational taxonomic units (OTUs) based on a similarity threshold of ≥ 97%. The most abundant sequence within each cluster was selected as the representative sequence [[59]22]. Alpha diversity analysis was evaluated by Chao, Simpson, Shannon, and the ACE index. Welcht’s t-test or Wilcoxon rank test was used for statistical analysis. Comparisons of the microbial community structures were made using the Bray-Curtis dissimilarity index, and the results were depicted by Principal Coordinate Analysis (PCoA). The distinctions in beta diversity among the microbial assemblages were quantitatively analyzed using Analysis of Similarities (ANOSIM). Differences in microbial abundance were analyzed by the LEfSe software, and samples were compared between two groups by the Wilcoxon rank test and screened for differences using the results derived from the LDA method (Linear Discriminant Analysis) [[60]23]. The bacteria were considered to differ between the two groups when the LDA score was ≥ 2. Quantitative real-time PCR MDA-MB-231 and BT20 cell was co-cultured with S. multivorum (multiplicity of infection = 100) in DMEM with penicillin and streptomycin withdrawn for 6 h, then washed with PBS for 5 times, and RNA was extracted. For propionylcarnitine treatment experiments, RNA was extracted from MDA-MB-231 and BT20 cells after treatment with different concentrations of propionylcarnitine for 24 h. Total RNA was extracted by Total RNA isolation kit (Foregene China), with procedures adhering to the manufacturer’s protocol. Specific primers are listed in the Supplementary Materials. The conditions for the PCR amplification of cDNA were as follows: an initial denaturation at 95 °C for 2 min, followed by a total of 40 cycles consisting of a 5s denaturation step at 95 °C and an annealing step of 30 s at 60 °C. Data were calculated using the 2^−∆∆Ct method after normalization with the GAPDH expression level in each sample. RNA-sequencing and analysis MDA-MB-231 cell was co-cultured with S. multivorum (multiplicity of infection = 100) in DMEM with penicillin and streptomycin withdrawn for 6 h. Approximately 10^7 cells were harvested, and total RNA was extracted with TRIzol reagent (Thermo Fisher Scientific). After assessing the integrity and quality of the RNA, further verification was performed by RNAase-free agarose gel electrophoresis. After isolation, mRNA was enriched and then fragmented using fragmentation buffer and subsequently reverse transcribed to cDNA. The resulting cDNA library was sequenced by Gene Denovo Biotechnology (Guangzhou, China). Targeted metabolomics analysis Targeted metabolomics analysis was performed by Metabo-Profile (Shanghai, China). The tumor tissues of mice in the model group and S. multivorum group were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). Briefly, resected tissue specimens were mixed with zirconium oxide beads, deionized water, and methanol inclusive of internal calibrators to facilitate metabolite solubilization. Following several minutes of homogenization, the homogenate was centrifuged, and the resulting supernatant was transferred into a 96-well plate, which was subsequently sealed and subjected to LC-MS analysis [[61]24]. Based on the results of the OPLS-DA model, reliable metabolic markers were screened by Volcano plot. The value of variable influence on projection (VIP) ≥ 1.0 is regarded as significantly different within the tumor [[62]25]. Differential metabolites among mouse tumor tissues were identified using univariate statistical analysis (Student’s t-test or Mann-Whitney U-test). Thresholds in the volcano diagram plots were set at p < 0.05 and |log2FC| ≥ 0. Pathway enrichment analysis of differential metabolites was conducted using the Pathway-associated metabolite sets (SMPDB) library. In vivo experiments BALB/c mice were purchased from Charles River (Beijing). Breast cancer 4T1 cells (8 × 10^4 cells/mouse) were subcutaneously injected into the lower right flank of mice. When the tumor size reached 50-100mm^3, the mice were assorted into two cohorts randomly: (1) control group and (2) experimental group injected with S. multivorum. The tumor was injected with normal saline or S. multivorum (2 × 10^7 CFU) twice a week. Tumor sizes and body weight were also measured twice a week. For PD-1 antibody treatment experiments, 4T1 cells (8 × 10^4 cells/mouse) were subcutaneously injected into the lower right flank of mice. S. multivorum (intra-tumorally) with or without PD-1 antibody (intra-peritoneally) was administered to the tumor-bearing mice after the tumor volume reached 50-100mm^3. 2 × 10^7 CFU S. multivorum or the same volume of saline was intra-tumorally injected twice a week. Meanwhile, IgG2α isotype control (BioXcell) or PD-1 antibody (BioXcell) was administered intraperitoneally once a week. Group of mice was administered i.p. with 10 µg of αPD-1 mAb and IgG isotype antibody. For CD8^+ T cell depletion experiments, BALB/c mice were injected with CD8 neutralizing antibody (BioXCell) or isotype Control (BioXCell) once a week. Group of mice was administered i.p. with 10 µg of αCD8 mAb and IgG isotype antibody. 2 × 10^7 CFU S. multivorum or the same volume of saline was intra-tumorally injected twice a week. For 4T1 tumor-bearing mouse model, 2 × 10^7 CFU of S. multivorum were injected into subcutaneous tumors as described above. 150 mg/kg propionylcarnitine was injected into the tumor twice a week. When the tumor volume reached 1500 mm^3, the treatment was terminated, and the mice were euthanized. The volume of the tumors was determined using the formula: Volumn (mm^3) = 0.5 × longest diameter (mm) × shortest diameter^2(mm). Immunohistochemistry Mouse tumor tissues were preserved using 4% paraformaldehyde fixation, embedded within paraffin, and sectioned to a nominal thickness of 4 micrometers. The paraffin-embedded sections were incubated with primary antibodies (CD8, 1:1000 Servicebio, Foxp3, 1:250, Bioss) at 4℃ overnight, followed by incubation with the second antibody at room temperature with protection from light for 1 h. DAB staining and hematoxylin staining were performed on sections following the corresponding standard protocols. Tissue staining was observed under a microscope. Image J was used to score the number of positive cells in the image. Fluorescence in situ hybridization The S. multivorum probe (5’- TCTCACCGTCTTCGAGCAAGCTCTCCG-3’) conjugated with the Cy3 fluorophore (Future Biotech) was used to identify S. multivorum colonization within in the mouse tumors. Adhering to the protocols stipulated by the supplier, the tissue samples were dewaxed and soaked in hydrochloric acid, triton, and lysozyme and then blocked with a blocking buffer at 55℃ for 2 h. Afterwards, the tissue samples were incubated with the diluted probe (in 1:100 Hybridization Buffer), allowed to denature at 88℃ for 3 min, equilibrate at 37℃ for 5 min, and hybridize at 37℃ for 48 h. After washing, the probe was stained with DAPI and photographed using a fluorescence microscope. ELISA assay MDA-MB-231 or BT20 cells were co-cultured with S. multivorum (multiplicity of infection = 100) in DMEM with penicillin and streptomycin withdrawn for 6 h. The culture medium was subjected to centrifugation at 3000×g for 5 min, and the resultant supernatant was filtered. CCL20 and CXCL8 expression were detected by ELISA kit (Abclonal) following the manufacturer recommended procedures. Tissue pieces were weighed and then homogenized in PBS, maintaining a ratio of 1g of tissue to 9 mL of PBS. The resulting homogenates were then centrifuged at 5000×g at 4℃. The quantities of IFN-γ, CCL20, and CXCL8 in the supernatant was detected by the corresponding ELISA kit (Elabscience) following the manufacturer’s instructions. Flow cytometry To analyze the tumor-infiltrating lymphocytes (TILs), mice tumor tissue was digested using the Tumor Dissociation Kit (Cat#130-096-730, Miltenyi Biotec) and dissociated with gentleMACS in accordance with the manufacturer’s protocol. The resulting sample was passed through a 70 μm cell filter and washed with PBS. Single tumor cells were then resuspended in 5 mL of a 40% Percoll gradient solution (Cat#P8370, Solarbio), carefully layered onto 5 mL of an 80% Percoll solution, and centrifuged at 325 g for 25 min at room temperature. The TILs were collected from the interface between the 40% and 80% Percoll layers. For mouse spleen lymphocyte extraction, the BALB/c mice were euthanized, and their spleens were promptly removed. Each spleen was placed on a 200-mesh nylon net in a petri dish and gently ground with a syringe while PBS solution was continuously added during the grinding process. The resulting splenic cell suspension was transferred to a centrifuge tube and centrifuged at 350 g for 5 min, after which the supernatant was discarded. Subsequently, 1 mL of ACK red blood cell lysate was added, and the mixture was gently agitated and left at room temperature for 2 min to facilitate lysis. The sample was then centrifuged again at 350 g for 5 min, resuspended in RPMI 1640 complete medium, and counted. Similarly, in blood sample preparation, 4 mL of PBS diluted blood was added to the Ficoll layer. Centrifuge 400 g for 30 to 40 min at 18℃-20℃. The middle white membrane (lymphocyte) was sucked into a new centrifuge tube and incubated with flow antibodies. Cell samples, mouse tumor tissues, and blood samples were incubated with flow antibodies (CD3 FITC, CD4 PE cy7, or CD25 PE, Elabscience) at 4℃ and protected from light. Cell samples were fixed and permeabilized following the manufacturer’s instructions by Foxp3 / Transcription Factor Staining Buffer Set (cat#00-5523-00, eBioscience). Cellular specimens were further incubated at room temperature for 30 min with the FoxP3 V450 antibody. Cell samples were assayed by flow cytometry, and data were statistically analyzed by FlowJo software. Statistical analysis GraphPad Prism 8 was used for statistical analyses. The samples were tested for normality. If the data were normally distributed, the independent sample t-test was used to compare the measured data between the two groups. A univariate analysis of variance (ANOVA) was performed for comparisons among three or more groups. For data that were not normally distributed, the non-parametric Mann-Whitney test was used for comparison and the Wilcoxon signed-rank test was used for matched data. Data are expressed as mean ± standard deviation (SD). p values < 0.05 were considered statistically significant. Results S.multivorum was enriched in cancerous tissues from breast cancer patients To evaluate the correlation between different tumor-resident bacteria and breast cancer development, we performed 16S rDNA gene sequencing analysis on cancerous tissues (n = 21) and paracancerous tissues (n = 20) from each breast cancer patient. α-diversity analysis was carried out to investigate the complexity of species in the microbial community for each sample, using the Chao1, ACE, Shannon and Simpson indices. The Chao1 and ACE value reflect the species richness of the bacterial community. On the other hand, the Shannon and Simpson value are associated with the species diversity of the bacterial community, which are influenced by both species richness and species evenness. There were statistically significant differences in Chao and ACE indices, whereas the Simpson and Shannon indices were not significantly different between the tumor and adjacent tissue groups (Fig. [63]1A). Principal Coordinate Analysis (PCoA) was used to compare the microbial communities of paracancerous and cancerous tissues (Fig. [64]1B). Notably, Sphingobacterium was found in the paracancerous and cancerous tissues of breast cancer patients in genus level. In this cohort, the relative abundance of Sphingobacterium was ranked 11th out of 170 bacterial genera (Fig. [65]1C). Furthermore, the linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed that Staphylococcus, Lactococcus, Sphingobacterium, and Edaphobacter were abundant in tumor tissues whereas Sediminibacterium, Tepidiphilus, Ralstonia, and Bacteroides were relatively more abundant in the paracancerous tissues (Fig. [66]1D, E). Intriguingly, we also confirmed the colonization of Sphingobacterium at the genus level (Fig. [67]1F) and the colonization of S. multivorum in the paracancerous and cancerous tissues (Fig. [68]1G), suggesting that S. multivorum may represent a prominent intra-tumor resident bacteria in breast cancer. Fig. 1. [69]Fig. 1 [70]Open in a new tab 16S rDNA gene sequencing analysis of tumor and paracancerous tissues of breast cancer patients. (A) Chao, ACE, Shannon, and Simpson indices were used to evaluate the relative abundance and homogeneity of microbial communities in cancerous and para-cancerous tissues. (B) Differences in microbial communities were compared using principal coordinate analysis (PCoA), and statistical differences were evaluated by analysis of similarities (ANOSIM). (C) The bar graph plots each patient’s relative abundance of the top 15 enriched genus taxonomies in paracancerous (n = 21) and cancerous tissues (n = 20). (D, E) LEfSe analysis facilitated the calculation of linear discriminant analysis (LDA) scores to quantify the bacterial abundance at the genus level in cancerous and paracancerous tissues from breast cancer patients. The LDA score > 2 was shown. (F) The relative abundance of Sphingobacterium in breast cancer patients at the genus level using Wilcoxon nonparametric test. (G) The relative abundance of S. multivorum from breast cancer patients at the species level. Statistical analysis using Wilcoxon nonparametric test. Significance levels are denoted as *p < 0.05; **p < 0.01 Tissue-resident S. Multivorum accelerated tumor growth in vivo Given that S. multivorum was one of the most abundant bacteria residing in tumor tissues of breast cancer patients, we hypothesized that S. multivorum may promote breast cancer progression. Using the 4T1 tumor-bearing mouse model, we investigated the influence of tissue-resident S. multivorum on tumor growth in vivo (Fig. [71]2A). Compared with the control group, 4T1 tumor-bearing mice receiving twice weekly intratumoral injections of 2 × 10^7 colony-forming units (CFU) of S. multivorum exhibited a significant augmentation in tumor size (Fig. [72]2B) and tumor weight (Fig. [73]2C). To confirm the colonization of S. multivorum within the TME, we detected S. multivorum by fluorescence in situ hybridization assay on paraffin sections of mouse tumors. Positive signals were only observed in the tumor paraffin sections from the S. multivorum-injected mice, indicating the presence of the S. multivorum in the tumor, but not from the control mice (Fig. [74]2D). These data suggest that colonization of S. multivorum within tumors accelerated breast tumorigenesis. Fig. 2. [75]Fig. 2 [76]Open in a new tab Tissue-resident S. multivorum accelerated tumor growth in vivo. (A) Saline or 2 × 10^7 CFU of S. multivorum was administered intratumorally twice per week to mice bearing 4T1 tumor. (B) Tumor growth curve in BALB/c mice (n = 6). (C) Tumor weight in BALB/c mice (n = 6). (D) Fluorescence in situ hybridization staining for DAPI (Blue) and CY3-labeled S. multivorum (Red) fluorescent probes for detecting tumor-resident S. multivorum in mice, scale bar = 50 μm. (E) Immunohistochemical analysis of FoxP3 within mouse tumors, scale bar = 10 μm. (F) Immunohistochemical analysis of CD8 within mouse tumors, scale bar = 10 μm. (G) Representative flow cytometric contour plot showing tumor-infiltrating Treg cells in 4T1 tumor-bearing mice. (H) Representative flow cytometric contour plot showing tumor-infiltrating CD8^+ T cells in 4T1 tumor-bearing mice. (I) The image represented tumor sizes in the presence or absence of S. multivorum alone or CD8 neutralizing antibody or combination. (J) Tumor growth curve in BALB/c mice. (K) Tumor weight in BALB/c mice. Statistical significance was determined by an unpaired two-tailed Student’s t-test for (C-F) and ANOVA statistical test with a Tukey’s post-hoc analysis for (J, K). Significance levels are denoted as *p < 0.05; **p < 0.01 Tumor-infiltrating lymphocytes (TIL) are an important component of the TME. Changes in TILs during tumor progression could be used as a measure of tumor aggressiveness and response to anticancer therapy. We used immunohistochemical staining to detect FoxP3, a specific marker for Treg cells in paraffin sections of tumor tissue. FoxP3^+ cells were significantly increased (Fig. [77]2E) whereas CD8^+ T cells were decreased in tumors of mice colonized by S. multivorum (Fig. [78]2F). Data from multi-color flow cytometric analysis further confirmed these findings. We found a similar increase of CD25^+ FoxP3^+ Treg cells (Fig. [79]2G) but a reduced infiltration of CD8^+ T cells in 4T1 tumor-bearing mice colonized by S. multivorum, compared with the control group (Fig. [80]2H). In addition, the 4T1 tumor-bearing mice were administered with either S. multivorum or saline directly into the tumor, in conjunction with a CD8 neutralizing antibody for CD8 in vivo depletion once a week. We found that the depletion of CD8^+ T cells increased the tumor promotion of S. multivorum (Fig. [81]2I-K). Collectively, these data suggest that intra-tumoral S. multivorum may promote tumor growth in 4T1 tumor-bearing mice by modulating Treg cells and CD8^+ T cells. S. Multivorum inhibited the anti-tumor effect of PD-1 antibody The tumor-promoting effect of S. multivorum was further confirmed in mice treated with αPD-1 mAb. In the 4T1 tumor-bearing model, when the tumor size reached 50-100mm^3, the mice were administered with either S. multivorum (2 × 10^7 CFU) or saline directly into the tumor, in conjunction with biweekly intraperitoneal injections of an isotype control IgG or αPD-1 mAb (Fig. [82]3A). S. multivorum was shown to remarkably diminish the therapeutic efficacy of αPD-1 mAb (Fig. [83]3B-D). To this end, an upregulation of FoxP3 expression (a Treg marker) was detected in the tumor colonized by S. multivorum, compared with the control, by immunohistochemical assay (Fig. [84]3F). Meanwhile, compared with mice that were administered with αPD-1 mAb alone, significantly less CD8^+ T cells and lower IFN-γ level were detected in the mice tumors injected with S. multivorum and αPD-1 mAb (Fig. [85]3E, G). In conclusion, intra-tumoral colonization of S. multivorum not only accelerated breast cancer growth but also impaired the therapeutic response to αPD-1 mAb. Fig. 3. [86]Fig. 3 [87]Open in a new tab S. multivorum inhibited the anti-tumor effect of PD-1 antibody. (A) Schematic diagram showing the experimental design (n = 6 per group). (B) When the tumor volume of mice reached 50-100mm^3, mice were injected intra-tumorally with saline or 2 × 10^7 CFU S. multivorum, in conjunction with intraperitoneal injections of αPD-1 mAb twice a week. (C) Tumor growth curve in BALB/c mice. (D) Tumor weight in BALB/c mice. (E) Levels of IFN-γ in tumor tissues of BALB/c mice. (F) Immunohistochemical staining for CD8^+ T cell infiltration, scale bar = 10 μm. (G) Immunohistochemical staining for FoxP3 expression, scale bar = 10 μm. Statistics for this entire figure were performed using an ANOVA statistical test with a Tukey’s post-hoc analysis. Significance levels are denoted as *p < 0.05; **p < 0.01; ***p < 0.001 Propionylcarnitine which was decreased by S. Multivorum inhibits tumor growth in vivo Abundant evidence has shown that tumor-resident bacteria could regulate the host immune system through microbial metabolites [[88]26–[89]28]. To further investigate the effects of S. multivorum on the TME, targeted metabolomics analysis was performed in tumor tissues from the 4T1 tumor-bearing mouse model. A total of 451 distinct metabolites were identified. Compared with the control mice, there were twenty differential metabolites found in tumor tissues from the S. multivorum-injected mice (Fig. [90]4A). The abundance of seven metabolites was remarkably increased and that of the other thirteen metabolites was significantly reduced in tumors of mice colonized with S. multivorum (Fig. [91]4B, C). Notably, three carnitine compounds, propionylcarnitine, hexanylcarnitine, and butyrylcarnitine, were decreased in the S. multivorum group (Fig. [92]4D-F). This attenuation suggests a potential regulatory role of S. multivorum on carnitine metabolism within the TME. Fig. 4. [93]Fig. 4 [94]Open in a new tab Propionylcarnitine which was decreased by S. multivorum inhibits tumor growth in vivo. (A) Heatmap showing potential biomarker levels in mouse tumors. The screening criteria were p < 0.05 and |log2FC| ≥ 0 for unidimensional analysis, and VIP value > 1 for multidimensional analysis. (B) Pathway enrichment analysis of differential metabolites using pathway-associated metabolite sets (SMPDB). (C) Volcano plot showing the differential metabolites based on one-dimensional statistical screening. Differential metabolites were considered significant at a threshold of p < 0.05 and |log2FC| ≥ 0. (D-F) Concentration of short-chain acylcarnitine metabolites in mouse tumors. (G) The effect of propionylcarnitine on cell viability of MDA-MB-231, BT20, and 4T1 cell lines in vitro. (H) The effect of propionylcarnitine on spleen lymphocyte viability in BALB/c mice. (I) The number of Treg cells in splenic lymphocytes of BALB/c mice by flow cytometry analysis. (L) Images of representative 4T1 subcutaneous tumors after the intra-tumoral injection of the S. multivorum in BALB/c mice. PBS served as a negative control. 2 × 10^7 CFU of S. multivorum were injected into subcutaneous tumors as described above. 150 mg/kg propionylcarnitine was injected into the tumor twice a week. After 26 days, the subcutaneous tumors were isolated and shown. (M) Tumor growth curve in BALB/c mice. (N) Tumor weight in BALB/c mice. (O) Body weight of BALB/c mice. Statistical significance was determined by an unpaired two-tailed Student’s t-test for (D-F) and ANOVA statistical test with a Tukey’s post-hoc analysis for (H-K, N). Significance levels are denoted as *p < 0.05; **p < 0.01; ***p < 0.001 The biological activities of carnitine metabolites were investigated in breast cancer cells. We found that propionylcarnitine, hexanylcarnitine, and butyrylcarnitine did not promote 4T1 cell proliferation directly in vitro (Fig. [95]4G). The effects of these carnitine metabolites on BALB/c mice spleen lymphocytes were examined. Interestingly, propionylcarnitine did not affect the viability of lymphocytes (Fig. [96]4H) but decreased the proportion of Treg cells in vitro (Fig. [97]4I). However, hexanylcarnitine and butyrylcarnitine did not inhibit the proportion of Treg cells (Fig. [98]4J, K). To investigate whether S. multivorum or/and propionylcarnitine confer to trigger cancer growth, the model of 4T1 mice breast cancer cells-bearing mice was established and divided 4 groups: control (saline, 5 ml/kg, q3d, intratumoral injections), S. multivorum alone (2 × 10^7 CFU, q3d, intratumoral injections), propionylcarnitine alone (150 mg/kg, q3d, intratumoral injections), combination of S. multivorum and propionylcarnitine. The results showed the tumor growth was promoted in the presence of S. multivorum, while the tumor growth did not significantly change in the group combination of S. multivorum and propionylcarnitine compared with the control group (Fig. [99]4L-O). Overall, these findings indicate that S. multivorum may deplete propionylcarnitine within the TME, thereby modulating the Treg cell population in BALB/c mice and inhibiting tumor progression. S. multivorum induced immunosuppression through enhancements of CCL20 and CXCL8 expression To investigate the molecular mechanisms by which S. multivorum promoted breast cancer growth, we next performed RNA-seq analysis in MDA-MB-231 cells stimulated by S. multivorum (Multiplicity of infection = 100) for 6 h. Previous studies have reported that inflammatory signaling pathways are critical for tumor suppression and tumor immune surveillance [[100]29, [101]30]. Our investigation revealed a significant up-regulation of genes integral to the IL-17 signaling pathway (Fig. [102]5A), which was also supported by data from the Gene set enrichment analysis (GSEA) (Fig. [103]5B). Transcription factors, including Jun, Fos, IL-1β, CXCL8, MMP99, and CCL20, were significantly up-regulated (Fig. [104]5C). The increased expression of these transcription factors were also validated by qPCR assay in both MDA-MB231 and BT20 cells (Fig. [105]5D, E). Tumor cell-derived CCL20 has been implicated in recruiting Treg cells to the TME via CCR6 and inhibiting IFN-γ secretion by CD8^+ T cells [[106]31–[107]33]. On the other hand, tumor-derived CXCL8 is known to recruit neutrophils to enhance tumor cell proliferation and promotes angiogenesis by activating endothelial cells [[108]13]. It has been reported that Cxcl8 plays an important role in establishing an immunosuppressive TME by decreasing the infiltration of CD8^+ T cell and up-regulating PD-L1 expression on macrophages [[109]34]. Interestingly, S. multivorum was found to increase the secretion of CCL20 and CXCL8 from MDA-MB-231 and BT20 cells by ELISA assay (Fig. [110]5F, G). Moreover, in the 4T1 tumor-bearing mouse model, CCL20 levels in the tumor (Fig. [111]5H) and abundance of Treg cells (Fig. [112]5I) in peripheral blood were found to be significantly higher in mice injected with S. multivorum than the control. We further investigated the metabolite propionylcarnitine, which was significantly reduced after S.multivorum colonization within the TME, our study revealed propionylcarnitine inhibited chemokines CCL20 and CXCL8 expressions (Fig. [113]5J, K). Overall, our data suggested that S. multivorum recruited Treg cells to the TME by activating the IL-17 signaling pathway and stimulating the secretion of the chemokine CCL20 from the tumor. Fig. 5. [114]Fig. 5 [115]Open in a new tab S. multivorum induced immunosuppression through enhancements of CCL20 and CXCL8 expression. (A) Total RNA samples were harvested from MDA-MD-231 cells after stimulation by S. multivorum (multiplicity of infection = 100) on 6 h, and subjected for RNA sequencing analysis. KEGG pathway enrichment analysis revealed that the IL-17 signaling pathway was significantly activated in the S. multivorum group. (B) Gene set enrichment analysis (GSEA) of transcriptomic data showing activation of the IL-17 signaling pathway; p < 0.05, NES = 1.84. (C) The fold change of differentially expressed genes within IL-17 signaling pathway. (D) Relative mRNA expression of IL-17 signaling pathway-related genes in MDA-MB-231 cells and S. multivorum co-culture systems by qPCR analysis. (E) Relative mRNA expression of IL-17 signaling pathway-related genes in BT20 cells and S. multivorum co-culture systems by qPCR analysis. (F, G) Chemokine CCL20 and CXCL8 levels in MDA-MB-23, and BT20 and S. multivorum co-culture systems by ELISA assay. (H) CCL20 level in the TME of 4T1 tumor-bearing mice by ELISA assay. (I) The proportion of Treg cells in peripheral blood of 4T1 tumor-bearing mice by flow cytometric analysis. (J, K) The relative mRNA expression levels of CXCL8 and CCL20 in BT20 and MDA-MB-231 cells treated with different concentrations of propionylcarnitine were measured by qPCR. Statistical significance was determined by an unpaired two-tailed Student’s t-test for (B-I) and ANOVA statistical test with a Tukey’s post-hoc analysis for (J, K). Significance levels are denoted as *p < 0.05; **p < 0.01; ***p < 0.001 In summary, we revealed that intra-tumoral S. multivorum promotes tumorigenesis and diminishes the therapeutic efficacy of αPD-1 mAb by decreasing the ratio of CD8^+ T cells/Treg cells in the TME (Fig. [116]6). Mechanistically, S. multivorum promotes the secretion of chemokine CCL20 from tumor cells. The secreted CCL20 recruits Treg cells and reduces CD8^+ T cell infiltration into the tumors. The findings deepen our insight about the influence of intratumor-resident microbes on the TME, which interact with the host immune system to regulate cancer progression. Fig. 6. [117]Fig. 6 [118]Open in a new tab Potential biological mechanisms of S. multivorum for breast cancer growth. S. multivorum promotes the secretion of chemokines CCL20 and CXCL8 from tumor cells. Tumor-derived CCL20 recruits Treg cells into the TME and reduces CD8^+ T cell infiltration, thereby leading to an immunosuppressive TME Discussion There is increasing evidence showing the presence of a unique microbial colonization in breast tissue, which was previously thought to be sterile. Moreover, the microbial profiles in the tumors from breast cancer patients were found to be distinct from the normal mammary tissue of healthy individuals [[119]35]. Within this intricate nexus, tumor-resident microbiota has been reported to remodel the TME or stimulate the recruitment and activation of immune cells, thereby exerting a crucial role in cancer development, treatment, and prognosis [[120]36, [121]37]. S. multivorum is ubiquitous in nature and the biological significance of its residence inside tumors is poorly studied. In this study, we found that S. multivorum showed a high relative abundance in cancerous tissues of breast cancer patients. Intriguingly, increasing relative abundance of Sphingobacterium has been reported in patients with triple-negative breast cancer, colon adenocarcinomas, and bladder cancer [[122]16–[123]18], indicating a potential link between S. multivorum and an increased risk of tumorigenesis. Moreover, intratumor colonization by S. multivorum was shown to stimulate tumor development and increased the ratio of tumor-infiltrating CD8^+ T cells/Treg cells. Our findings suggest that tumor-resident microbiota may have distinct functions in the TME and they could interact with the host immune system to regulate antitumor response. It follows that some tumor-resident microbiota may serve as prospective targets for cancer immunotherapy. Data from the metabolomic profiling studies revealed a significant reduction of propionylcarnitine concentration in tumors of mice colonized with S. multivorum. As a prevalent form of short-chain acylcarnitine, propionylcarnitine constitutes a substantial proportion of acylcarnitine content, accounting for over half of these compounds in human tissue matrices and body fluids [[124]38]. Originating from the metabolism of specific amino acids, such as lysine and valine, into propionyl coenzyme A (PCoA), propionylcarnitine is synthesized via the enzymatic action of carnitine acetyltransferase (CrAT) [[125]39]. To this end, the reduction of propionylcarnitine in hepatocellular carcinoma tissues has been recognized as a biomarker for identifying hepatitis and hepatocellular carcinoma [[126]40]. Reduced PCoA has also been reported to contribute to metabolic remodeling and promote hepatocellular carcinoma [[127]41]. Our results indicate that the diminished levels of propionylcarnitine within the TME, specifically in mice injected with S. multivorum, could play a role in cancer progression, given its capacity to reduce Treg cell viability in vitro. Intratumoral microorganisms often influence the levels of chemokines within the TME. Elucidating the influence of intratumoral microorganisms on chemokines in tumors is beneficial to our further understanding of tumor progression. We also showed that Treg cells were remarkably increased in mice injected with S. multivorum. This finding lends weight to the hypothesis that S. multivorum might recruit Treg cells or induce the differentiation of naïve CD4^+ T cells into Treg cells within the tumor. Our qPCR and ELISA assay results indicate that S. multivorum induced the secretion of chemokines such as CCL20 and CXCL8 from tumor cells. CCL20, also known as macrophage inflammatory protein 3α (MIP-3α), is a member of the CC chemokine family [[128]42, [129]43]. The production of CCL20 is attributed to tumor cells and tumor-associated macrophages, exerting the principal role in recruiting Treg and Th17 cells into the TME [[130]44, [131]45]. Meanwhile, the cognate chemokine receptor for CCL20 is identified as CCR6 [[132]46]. High infiltration of CCR6^+ Treg within tumors can promote immune tolerance and breast cancer progression by inhibiting the activity of IFN-γ in CD8^+ T cells [[133]33]. Some microorganisms, such as F. nucleatum, can promote tumor invasion by recruiting Treg cells with the chemokine CCL20 [[134]47]. On the other hand, CXCL8 plays different roles in the TME, such as suppressing the immune response to promote tumor angiogenesis and metastasis [[135]48–[136]50]. The present findings have significant implications for the clinical management of breast cancer patients undergoing immunotherapy. The abundance of S.multivorum and the concentration of propionylcarnitine are closely associated with the efficacy of immunotherapy. Consequently, S. multivorum and propionylcarnitine may serve as potential biomarkers to predict the therapeutic efficacy of immunotherapy. Limitations of the study Due to the complexity of the crosstalk between tumor-resident bacteria and the host immune system, S.multivorum is unlikely to be the sole microbiota that can diminish the immunotherapy efficacy in breast cancer. More specifically, in the study of IFN-γ level within the tumor microenvironment, ELISA assay only provided the total concentration of IFN-γ in the tumor tissue homogenate and cannot distinguish which cell subsets are secreting IFN-γ. Although our study demonstrated that S.multivorum promotes breast tumor growth by influencing the tumor microenvironment, it remains possible that S. multivorum may also contribute to tumor metastasis. More in-depth research and precise analysis are still required to address this aspect fully. Electronic supplementary material Below is the link to the electronic supplementary material. [137]Supplementary Material 1^ (15.3KB, docx) [138]Supplementary Material 2^ (25.2KB, docx) Acknowledgements