. 2019 Apr 2;10(1):1492.

doi: 10.1038/s41467-019-09525-y.

"V体育ios版" Gut microbiota dependent anti-tumor immunity restricts melanoma growth in Rnf5^-/- mice

Yan Li¹, Roberto Tinoco^{1

2}, Lisa Elmén¹, Igor Segota¹, Yibo Xian³, Yu Fujita¹, Avinash Sahu⁴, Raphy Zarecki⁵, Kerrie Marie⁶, Yongmei Feng¹, Ali Khateb⁷, Dennie T Frederick⁸, Shiri K Ashkenazi⁷, Hyungsoo Kim¹, Eva Guijarro Perez⁶, Chi-Ping Day⁶, Rafael S Segura Muñoz³, Robert Schmaltz³, Shibu Yooseph⁹, Miguel A Tam¹⁰, Tongwu Zhang¹¹, Emily Avitan-Hersh^{7

12}, Lihi Tzur¹², Shoshana Roizman¹², Ilanit Boyango¹², Gil Bar-Sela^{7

12}, Amir Orian⁷, Randal J Kaufman¹, Marcus Bosenberg¹³, Colin R Goding¹⁴, Bas Baaten¹, Mitchell P Levesque¹⁵, Reinhard Dummer¹⁵, Kevin Brown¹¹, Glenn Merlino⁶, Eytan Ruppin^{4

5

16}, Keith Flaherty⁸, Amanda Ramer-Tait³, Tao Long¹, Scott N Peterson¹, Linda M Bradley¹, Ze'ev A Ronai^{17

18}

Affiliations

V体育平台登录 - Affiliations

¹ Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, 92037, USA.
² Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, 92697, USA.
³ Department of Food Science and Technology, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA.
⁴ Center for Bioinformatics and Computational Biology, Department of Computer Science, University of Maryland, College Park, MD, 20742, USA.
⁵ School of Computer Sciences and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
⁶ Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
⁷ Technion Integrated Cancer Center, Faculty of Medicine, Technion Israel Institute of Technology, Haifa, 31096, Israel.
⁸ Division of Medical Oncology, Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, MA, 02114, USA.
⁹ Department of Computer Science, College of Engineering and Computer Science, University of Central Florida, Orlando, FL, 32816, USA.
¹⁰ BioLegend, San Diego, CA, 92121, USA.
¹¹ Division of Cancer Epidemiology and Genetics, Laboratory of Translational Genomics, National Cancer Institute, Bethesda, MD, 20892, USA.
¹² Departments of Dermatology and Oncology, Rambam Health Care Campus, Technion Faculty of Medicine, Haifa, 31096, Israel.
¹³ Department of Pathology, Yale University, New Haven, CT, USA.
¹⁴ Ludwig Institute for Cancer Research, Nuffield Department of Medicine, Old Road Campus, Unviversity of Oxford, Headington, Oxford, OX3 7DQ, UK.
¹⁵ Department of Dermatology, University Hospital of Zurich and University of Zurich, 8091, Zurich, Switzerland.
¹⁶ Cancer Data Science Lab, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
¹⁷ Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, 92037, USA. zeev@qiuluzeuv.cn.
¹⁸ Technion Integrated Cancer Center, Faculty of Medicine, Technion Israel Institute of Technology, Haifa, 31096, Israel. zeev@qiuluzeuv.cn.

Gut microbiota dependent anti-tumor immunity restricts melanoma growth in Rnf5^-/- mice

Yan Li et al. Nat Commun. 2019.

. 2019 Apr 2;10(1):1492.

doi: 10.1038/s41467-019-09525-y.

Authors

Affiliations

¹ Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, 92037, USA.
² Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, 92697, USA.
³ Department of Food Science and Technology, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA.
⁴ Center for Bioinformatics and Computational Biology, Department of Computer Science, University of Maryland, College Park, MD, 20742, USA.
⁵ School of Computer Sciences and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
⁶ Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
⁷ Technion Integrated Cancer Center, Faculty of Medicine, Technion Israel Institute of Technology, Haifa, 31096, Israel.
⁸ Division of Medical Oncology, Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, MA, 02114, USA.
⁹ Department of Computer Science, College of Engineering and Computer Science, University of Central Florida, Orlando, FL, 32816, USA.
¹⁰ BioLegend, San Diego, CA, 92121, USA.
¹¹ Division of Cancer Epidemiology and Genetics, Laboratory of Translational Genomics, National Cancer Institute, Bethesda, MD, 20892, USA.
¹² Departments of Dermatology and Oncology, Rambam Health Care Campus, Technion Faculty of Medicine, Haifa, 31096, Israel.
¹³ Department of Pathology, Yale University, New Haven, CT, USA.
¹⁴ Ludwig Institute for Cancer Research, Nuffield Department of Medicine, Old Road Campus, Unviversity of Oxford, Headington, Oxford, OX3 7DQ, UK.
¹⁵ Department of Dermatology, University Hospital of Zurich and University of Zurich, 8091, Zurich, Switzerland.
¹⁶ Cancer Data Science Lab, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
¹⁷ Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, 92037, USA. zeev@qiuluzeuv.cn.
¹⁸ Technion Integrated Cancer Center, Faculty of Medicine, Technion Israel Institute of Technology, Haifa, 31096, Israel. zeev@qiuluzeuv.cn.

PMID: 30940817
PMCID: PMC6445090
DOI: 10.1038/s41467-019-09525-y

Abstract (VSports app下载)

Accumulating evidence points to an important role for the gut microbiome in anti-tumor immunity. Here, we show that altered intestinal microbiota contributes to anti-tumor immunity, limiting tumor expansion. Mice lacking the ubiquitin ligase RNF5 exhibit attenuated activation of the unfolded protein response (UPR) components, which coincides with increased expression of inflammasome components, recruitment and activation of dendritic cells and reduced expression of antimicrobial peptides in intestinal epithelial cells. Reduced UPR expression is also seen in murine and human melanoma tumor specimens that responded to immune checkpoint therapy. Co-housing of Rnf5-/- and WT mice abolishes the anti-tumor immunity and tumor inhibition phenotype, whereas transfer of 11 bacterial strains, including B. rodentium, enriched in Rnf5-/- mice, establishes anti-tumor immunity and restricts melanoma growth in germ-free WT mice. Altered UPR signaling, exemplified in Rnf5-/- mice, coincides with altered gut microbiota composition and anti-tumor immunity to control melanoma growth VSports手机版. .

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures (V体育2025版)

**Fig. 1**
Enhanced antitumor immune responses in *Rnf5*^−/− mice. a Growth of YUMM1.5 (*Braf*^V600E:PTEN^−/−*:Cdkn2a*^−/−) melanoma cells after subcutaneous injection of 10⁶ cells into WT or *Rnf5*^−/− mice (n = 5). b Quantification of tumor-infiltrating effector (CD44^hi) CD4⁺ and CD8⁺ T cells and total CD45⁺ cells on day 24 after tumor injection (n = 5). c Frequencies of tumor-infiltrating TNF-α-, IFN-γ-, and IL-2-producing CD4⁺ and CD8⁺ T cells on day 24 after tumor inoculation (n = 5). d Quantification of tumor-infiltrating total DCs, pDCs, mDCs, and CD8α⁺ DCs on day 24 after tumor inoculation (n = 5). e Expression (mean fluorescence intensity, MFI) of MHC class II, CD40, CD80, and CD86 on tumor-infiltrating DCs (CD45⁺ CD11c⁺) on day 24 after tumor inoculation (n = 5). f Quantification of OT-I CD8⁺ T cells in tumor-draining lymph nodes (TdLN) and non-draining lymph nodes (ndLN) of CD45.1⁺ WT and *Rnf5*^−/− mice injected with B16-OVA melanoma cells (WT, n = 6; *Rnf5*^−/−, n = 5). g, h Growth of YUMM1.5 melanoma cells in mice injected i.p. with control IgG and anti-CD4 (g) or control IgG and anti-CD8 (h) depleting antibodies on days 0, 3, 6, 11, 16 (n = 9). FACS analysis revealed >90% depletion of blood CD4⁺ and CD8⁺ T cells on day 7 after tumor inoculation. i, Growth of YUMM1.5 melanoma cells in lethally irradiated bone marrow-reconstituted WT or *Rnf5*^−/− mice (arrow indicates bone marrow donor → recipient; n = 7). Data are representative of three independent experiments (a–e), two independent experiments (f, i) and one experiment (g, h) ≥5 mice per group. Graphs show the mean ± s.e.m. *P < 0.05, **P < 0.005, ***P < 0.001, ****P < 0.0001 by two-way ANOVA with Sidak’s correction (a, g–i) or by two-tailed t-test or Mann–Whitney U test (b–f)

**Fig. 2**
Enhanced inflammasome and pathogen receptor signaling in *Rnf5*^−/− mice. a NanoString analysis of PanCancer Immune Profiling genes in tumors from WT and *Rnf5*^−/− mice. The heatmap shows 47 genes with >1.2-fold (P < 0.05) differences in expression between YUMM1.5 tumors from the two genotypes (n = 5) at 10 days after injection. b Growth of B16F10 melanoma cells after subcutaneous injection of 10⁶ cells into WT, *Rnf5*^−/−, *MyD88*^−/− and *MyD88*^−/−*Rnf5*^−/− mice (WT, *Rnf5*^−/−, n = 6; *MyD88*^−/−, n = 5; *MyD88*^−/− *Rnf5*^−/−, n = 8). c qRT-PCR analysis of pathogen receptor mRNA levels in IECs from tumor-bearing WT or *Rnf5*^−/− mice (n = 4). d qRT-PCR analysis of cytokine and chemokine mRNA levels in IECs isolated from the small intestines of tumor-bearing WT or *Rnf5*^−/− mice (n = 4). Data are representative of three independent experiments (c, d), two independent experiments (b) or one experiment (a) ≥5 mice per group. Graphs show the mean ± s.e.m. *P < 0.05, **P < 0.005, ***P < 0.001, ****P < 0.0001 by two-tailed t test or Mann–Whitney U test (c, d) or two-way ANOVA with Sidak’s correction (b)

**Fig. 3**
Gut microbiota control melanoma growth. a Principal component analysis (PCA) of all taxa enumerated in *Rnf5*^−/− and WT fecal microbiota samples taken before (day 0) and 24 days after injection of YUMM1.5 tumor cells (n = 30). b Elimination of tumor growth suppression in *Rnf5*^−/− mice by treatment with an antibiotic cocktail administered for 2 weeks prior to tumor cell injection (n = 5). c PCA of all taxa showing convergence of gut microbiota in WT and *Rnf5*^−/− mice after co-housing (WT alone, n = 14; *Rnf5*^−/− alone, n = 15; WT mixed, *Rnf5*^−/− mixed, n = 5). d Growth of YUMM1.5 melanoma cells in WT or *Rnf5*^−/− mice housed alone or co-housed (mixed) for 4 weeks prior to tumor inoculation (alone, n = 15; mixed, n = 16). e Quantification of effector (CD44^hi) CD4⁺ and CD8⁺ T cells, total CD45⁺ cells, and frequencies of IFN-γ + TNF-α-producing CD4⁺ and CD8⁺ T cells in tumors from WT or *Rnf5*^−/− mice housed alone or co-housed for 4 weeks prior to tumor inoculation (n = 10). f Quantification of tumor-infiltrating total DCs, pDCs, and mDCs in WT or *Rnf5*^−/− mice housed alone or co-housed for 4 weeks prior to tumor inoculation (n = 10). g A cladogram representation of taxa enriched in *Rnf5*^−/− mice (red) microbiota and taxa enriched in WT mice (green) microbiota (n = 30). The background color indicates phylum; names of phyla are indicated. Data are representative of two independent experiments ≥5 mice per group. Graphs show the mean ± s.e.m. *P < 0.05, **P < 0.005, ***P < 0.001, ****P < 0.0001 by one-way ANOVA with Tukey’s (e, f) or two way ANOVA with Sidak’s (b, d) correction for multiple comparisons

**Fig. 4**
Oral administration of select bacterial strains enriched in *Rnf5*^−/− mice to gnotobiotic mice enhances antitumor immune response. a YUMM1.5 tumor growth in germ-free (GF) mice undergoing oral gavage with WT or *Rnf5*^−/− cecal contents 2 weeks prior to tumor implantation (n = 10). b Quantification of tumor-infiltrating CD45⁺ cells, effector (CD44^hi) CD4⁺ and CD8⁺ T cells, total CD45⁺ cells, and frequencies of IFN-γ⁺TNF-α⁺-producing CD4⁺ and CD8⁺ T cells on day 24 after tumor injection in recipients treated as in (a) (n = 10). c YUMM1.5 tumor growth in GF mice undergoing oral gavage with either Altered Schaedler Flora (ASF) or ASF plus bacterial cocktail prior to tumor inoculation (ASF, n = 12; ASF + bacterial cocktail, n = 14). d Quantification of tumor-infiltrating effector (CD44^hi) CD4⁺ and CD8⁺ T cells and frequencies of IFN-γ⁺TNF-α⁺-producing CD4⁺ and CD8⁺ T cells on day 21 after tumor injection in mice treated as in (c) (n = 8). e YUMM1.5 tumor growth in GF mice undergoing oral gavage with ASF or ASF plus *B. rodentium* prior to tumor inoculation (n = 15). f Quantification of tumor-infiltrating effector (CD44^hi) CD4⁺ and CD8⁺ T cells and frequencies of IFN-γ⁺TNF-α⁺-producing CD8⁺ T cells on day 24 after tumor injection in mice treated as in (e) (n = 8). Data are one experiment ≥8 mice per group.Graphs are the mean ± s.e.m. *P < 0.05, **P < 0.005, ****P < 0.0001 by two-way ANOVA with Tukey’s or Sidak’s correction for multiple comparisons (a, c, e) or two-tailed t test or Mann–Whitney U test (b, d, f)

**Fig. 5**
IEC of *Rnf5*^−/− mice activate immune response and change anti-microbial peptide (AMP) expression. a Villi length and crypt depth calculated from H&E-stained sections of intestines from WT or *Rnf5*^−/− mice (WT, n = 30; *Rnf5*^−/−, n = 32). b qRT-PCR analysis of AMPs mRNA levels in IECs from small intestine of naive WT or *Rnf5*^−/− mice (n = 6). c Representative images (left) and quantification (right) of cleaved caspase-3 immunostained small intestine organoids from tumor-bearing WT or *Rnf5*^−/− mice (n = 3). Scale bar = 100μm. Graph shows percentage of cleaved caspase-3 ⁺ cells per immunostained organoid (n = 12 fields). d Intracellular IFN-γ and TNF-α staining of p14 CD8⁺ T cells incubated for 72 h with 2 μg/ml GP33 peptide recognized by the TCR of P14 and bone marrow-derived dendritic cells (BMDCs) that were incubated with medium alone (no stimulation) or with conditioned medium (CM) from shControl or shRNF5 MODE-K cells. e Representative images (left) and quantification (right) of CD11c⁺ cell immunostaining in the small intestine of WT or *Rnf5*^−/− mice on day 24 after injection of YUMM1.5 cells. Scale bar = 50μm (n = 4). f Frequencies of total DCs and pDCs in Peyer’s patches from WT and *Rnf5*^−/− mice on day 10 after YUMM1.5 cell injection (n = 6). g 10 days after tumor injection, DCs from GALT, dLN, and ndLN were isolated, pooled per group (n = 10 mice/group), and were incubated with OT-1 CD8⁺ T cells stimulated with 2 μg/ml OVA peptide (SINFEKL). Intracellular IFN-γ and TNF-α of OT-1 CD8⁺ T cells were detected. Data are representative of three independent experiments (b, d) and two independent experiments (a, c, e, f, g) ≥3 mice per group. Graphs show the mean ± s.e.m. *P < 0.05, **P < 0.005, ***P < 0.001, ****P < 0.0001 by two-tailed t test or Mann–Whitney U test (a, b, c, e, f) or one-way ANOVA with Tukey’s (d) correction for multiple comparisons

**Fig. 6**
IEC of *Rnf5*^−/− mice activate immune responses and changes AMPs expression by IRE1α/sXBP1 signaling. a Western blot analysis of the indicated proteins in lysates of MODE-K-shCon and MODE-K-shRNF5 cells treated with thapsigargin (TG, 1 μM) for indicated time. b qRT-PCR analysis of mRNA levels of sXBP1, XBP1 and target genes in small intestine-derived IECs from naive WT or *Rnf5*^−/− mice (n = 4). c Representative micrographs of immunohistochemical (IHC) staining of BiP in the jejunum, ileum, and colon of YUMM1.5 tumor-bearing WT or *Rnf5*^−/− mice (scale bar = 25 μm). Lower graphs show quantification of IHC staining (n = 12 fields per group). Staining was scored semi-quantitatively based on staining intensity (0, 1, 2, or 3) multiplied by the percentage of positively stained cells (0–100), to give a maximum IHC score of 300. d Quantification of BiP and CHOP IHC staining in ileum sections from WT and *Rnf5*^−/− mice co-housed for 4 weeks prior to tumor inoculation (n = 12). e qRT-PCR analysis of sXBP1 mRNA levels in MODE-K-shCon and MODE-K-shRNF5 cells treated with the indicated concentration of MKC-4485 for 24 h (n = 3). f MFI of MHC class I and II on bone marrow-derived dendritic cells (BMDCs) incubated with media alone (no stimulation), conditioned media (CM) from shControl or shRNF5 MODE-K cells treated with MKC-4485 (n = 4). g qRT-PCR analysis of Defa1 mRNA levels in MODE-K-shCon and MODE-K-shRNF5 cells (n = 3). h qRT-PCR analysis of AMPs mRNA levels in IECs in MODE-K-shCon and MODE-K-shXBP1 cells (n = 3). i, qRT-PCR analysis of Defa1 mRNA levels in MODE-K cells treated with 2 μM MKC-4485 for 24 h (n = 3). Data are representative of three independent experiments (b, e–i) and two independent experiments (a, c, d) ≥3 mice per group. Graphs show the mean ± s.e.m. *P < 0.05, **P < 0.005, ***P < 0.001, ****P < 0.0001 by two-tailed t test or Mann–Whitney U test (b, c, g–i) or one-way ANOVA with Tukey’s correction for multiple comparisons (d–f)

**Fig. 7**
Altered UPR in melanoma responders of anti-CTLA-4 immune therapy. a Analysis of ER stress markers genes in non-responders (NR) (n = 16) and responders (R) (n = 14) to immune checkpoint therapy in melanoma samples from MGH/DFCC (USA). b Analysis of ER stress markers genes in NR (n = 16) and R (n = 9) to anti-CTLA-4 immunotherapy in melanoma samples from Zurich Hospital (Switzerland). c Kaplan–Meier curves for progression-free survival probability in melanoma patients demonstrating low (n = 15 patients) versus high sXBP1(n = 14 patients) in tumor specimens obtained before immune checkpoint therapy at MGH/DFCC. d Kaplan–Meier estimates of progression-free survival probability in melanoma patients demonstrating low (n = 14 patients) versus high ATF4 (n = 16 patients) in tumor specimens obtained before immune checkpoint therapy in melanoma samples at MGH/DFCC. e Representative micrographs of IHC staining of BiP after anti-PD-1 immunotherapy in melanoma samples obtained at Rambam Health Care Center (Israel) (scale bar = 25 μm). f IHC score of BiP staining in NR (n = 10) and R (n = 11) to anti-PD-1 immunotherapy in melanoma samples from Rambam Health Care Center (Israel). g, h Kaplan–Meier estimates of (g) overall survival and (h) disease-free survival probability in melanoma patients demonstrating low (<25%, n = 12 patients) versus high melanoma cell expression of BiP (>25%, n = 9 patients) in tumor biospecimens obtained before initiation of systemic anti-PD-1 antibody treatment in melanoma samples from Rambam Health Care Center (Israel). i IHC staining of BiP in melanoma samples from select patients prior to, on and after immunotherapy treatment from MGH/DFCC (USA). Scale bar = 50 μm. Graphs show the mean ± s.e.m. *P < 0.05, **P < 0.005, ***P < 0.001, ****P < 0.0001 by two-tailed t-test or Mann–Whitney U test (a, b, f) or log-rank test (c, d, g, h)

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"V体育ios版" Gut microbiota dependent anti-tumor immunity restricts melanoma growth in Rnf5^-/- mice

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Gut microbiota dependent anti-tumor immunity restricts melanoma growth in Rnf5^-/- mice

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Abstract (VSports app下载)

Conflict of interest statement

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