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Autophagy promotes immune evasion of pancreatic cancer by degrading MHC-I

Nature volume 581, pages 100–105 (2020)Cite this article

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Abstract

Immune evasion is a major obstacle for cancer treatment. Common mechanisms of evasion include impaired antigen presentation caused by mutations or loss of heterozygosity of the major histocompatibility complex class I (MHC-I), which has been implicated in resistance to immune checkpoint blockade (ICB) therapy1,2,3. However, in pancreatic ductal adenocarcinoma (PDAC), which is resistant to most therapies including ICB4, mutations that cause loss of MHC-I are rarely found5 despite the frequent downregulation of MHC-I expression6,7,8. Here we show that, in PDAC, MHC-I molecules are selectively targeted for lysosomal degradation by an autophagy-dependent mechanism that involves the autophagy cargo receptor NBR1. PDAC cells display reduced expression of MHC-I at the cell surface and instead demonstrate predominant localization within autophagosomes and lysosomes. Notably, inhibition of autophagy restores surface levels of MHC-I and leads to improved antigen presentation, enhanced anti-tumour T cell responses and reduced tumour growth in syngeneic host mice. Accordingly, the anti-tumour effects of autophagy inhibition are reversed by depleting CD8+ T cells or reducing surface expression of MHC-I. Inhibition of autophagy, either genetically or pharmacologically with chloroquine, synergizes with dual ICB therapy (anti-PD1 and anti-CTLA4 antibodies), and leads to an enhanced anti-tumour immune response. Our findings demonstrate a role for enhanced autophagy or lysosome function in immune evasion by selective targeting of MHC-I molecules for degradation, and provide a rationale for the combination of autophagy inhibition and dual ICB therapy as a therapeutic strategy against PDAC.

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Fig. 1: MHC-I is enriched in lysosomes of PDAC cells and displays reduced cell surface expression.
Fig. 2: NBR1 promotes MHC-I trafficking to the lysosome through an autophagy-dependent pathway.
Fig. 3: Autophagy inhibition enhances anti-tumour T cell response.
Fig. 4: Autophagy inhibition sensitizes PDAC to dual ICB.

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Data availability

RNA-seq data have been deposited to the Gene Expression Omnibus (GEO) data repository with accession number GSE145766. Source Data are provided for all experiments. Other data that support the findings of this study are available on request from the corresponding author upon reasonable request.

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  • 13 May 2020

    Source Data files for figures and extended data figures were uploaded.

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Acknowledgements

This work was supported by National Cancer Institute Grants R01CA157490, R01CA188048, P01CA117969, R35CA232124; ACS Research Scholar Grant RSG-13-298-01-TBG; NIH grant R01GM095567; and the Lustgarten Foundation, and SU2C to A.C.K. R.M.P. is the Nadia’s Gift Foundation Innovator of the Damon Runyon Cancer Research Foundation (DRR-46-17) and is additionally supported by an NIH Director’s New Innovator Award (1DP2CA216364) and the Pancreatic Cancer Action Network Career Development Award. K.Y. was supported by the Uehara Memorial Foundation Research Fellowship. A.V. is supported by a National Science Foundation Graduate Research Fellowship. D.E.B. is supported by a Ruth L. Kirschstein Institutional National Research Service Award, T32 CA009161 (Levy), and the NCI Predoctoral to Postdoctoral Fellow Transition Award (F99/K00) F99 CA245822. M.K. was supported by the Uehara Memorial Foundation Research Fellowship and Postdoctoral Fellowship for Research Abroad (Japan Society for the Promotion of Science). S.J.P. was supported by American Cancer Society grant 132942-PF-18-215-01-TBG. R.S.B. is a Merck Fellow of the Damon Runyon Cancer Research Foundation (DRG-2348-18). We thank H. Ying for providing the HY19636 and HY15549 cells. We thank the New York University (NYU) Langone Health Experimental Pathology Laboratory, Flow Cytometry Core, and Genome Technology Center, each supported in part by the Cancer Center Support grant P30CA016087 at the Laura and Isaac Perlmutter Cancer Center. We thank Z. Dewan for the technical assists on the staining of frozen sections. We acknowledge the UCSF Parnassus Flow Cytometry Core (PFCC) supported in part by the DRC Center Grant P30DK063720 for assistance generating flow cytometry data. We thank J. Olzmann for advice on ubiquitylation experiments. We thank all members of Perera, Kimmelman, Debnath and Pacold laboratories for suggestions.

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Author notes

  1. These authors contributed equally: Keisuke Yamamoto, Anthony Venida

Authors and Affiliations

  1. Department of Radiation Oncology, Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA

    Keisuke Yamamoto, Douglas E. Biancur, Albert S. W. Sohn, Subhadip Mukhopadhyay, Elaine Y. Lin, Seth J. Parker, Robert S. Banh & Alec C. Kimmelman

  2. Department of Anatomy, University of California, San Francisco, San Francisco, CA, USA

    Anthony Venida, Julian Yano, Suprit Gupta & Rushika M. Perera

  3. Columbia Center for Translational Immunology, Columbia University College of Physicians and Surgeons, New York, NY, USA

    Miwako Kakiuchi

  4. Columbia Stem Cell Initiative, Columbia University College of Physicians and Surgeons, New York, NY, USA

    Miwako Kakiuchi

  5. Department of Cell Biology, Harvard Medical School, Boston, MA, USA

    Joao A. Paulo

  6. Department of Pathology, University of California, San Francisco, San Francisco, CA, USA

    Kwun Wah Wen, Jayanta Debnath, Grace E. Kim & Rushika M. Perera

  7. Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA

    Jayanta Debnath & Rushika M. Perera

  8. Division of Radiation and Genome Stability, Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA

    Joseph D. Mancias

  9. Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA

    Douglas T. Fearon

  10. Weill Cornell Medicine, New York, NY, USA

    Douglas T. Fearon

  11. Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, UK

    Douglas T. Fearon

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  1. Keisuke Yamamoto
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Contributions

K.Y. and A.V. performed most experiments and wrote the manuscript. J.Y. assisted with cloning and performed the proximity biotinylation and ubiquitylation experiments. D.E.B. and A.S.W.S. assisted with animal studies. S.G. performed immunofluorescence and analysis of patient PDAC specimens. M.K. assisted with the analysis of flow cytometry data and RNA-seq data. S.M. assisted with immunoblotting and preparing shRNAs. E.Y.L. and S.J.P. cloned fluorescent constructs. K.W.W. and G.E.K. provided PDAC patient specimens and analysis. J.D. provided GFP–NBR1 and GFP–NBR1 dUBA constructs. R.S.B. assisted with transcriptome data analysis. J.D.M. and J.A.P. performed proteomics analysis. D.T.F. provided intellectual feedback and support. R.M.P. and A.C.K. conceived the project, supervised the research and wrote and edited the paper.

Corresponding authors

Correspondence to Rushika M. Perera or Alec C. Kimmelman.

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Competing interests

A.C.K. has financial interests in Vescor Therapeutics, LLC. A.C.K. is an inventor on patents pertaining to KRAS-regulated metabolic pathways, redox control pathways in pancreatic cancer, targeting GOT1 as a therapeutic approach, and the autophagic control of iron metabolism. A.C.K. is on the SAB of Rafael/Cornerstone Pharmaceuticals. A.C.K. is a consultant for Deciphera. J.D. is on the Scientific Advisory Board of Vescor Therapeutics, LLC. The other authors declare no competing interests.

Additional information

Peer review information Nature thanks Christian Münz, Andrew Thorburn, Robert H. Vonderheide and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Heterogeneous distribution of MHC-I in KRAS-mutant cancers.

a, Immuno-isolation of intact lysosomes from HPDE and PDAC cell lines showing absence of non-lysosome markers as indicated. EE, early endosome; ER, endoplasmic reticulum; lyso, lysosome; mito, mitochondria. b, High-power images showing MHC-I-positive/LAMP1-positive (arrowheads), MHC-I-positive/LAMP1-negative (arrows) and MHC-I-negative/LAMP1-positive (asterisk) puncta. Scale bars, 5 μm. c, d, Top, localization of MHC-I (green) relative to LAMP1-positive (red) lysosomes (BEAS-2B, n = 14; A549, n = 17; H441, n = 15; H358, n = 13; HCT116, n = 13) (c) or LC3B-positive (red) autophagosomes (BEAS-2B, n = 18; A549, n = 17; H441, n = 20; H358, n = 12; HCT116, n = 15) (d) in the indicated cell lines. Bottom, quantification of percentage co-localization. Cell lines indicated in red show significantly increased co-localization relative to BEAS-2B cells, and cell lines indicated in blue show a modest increase (H358) or no difference (HCT116). Data are mean ± s.d. (c, d). Scale bars, 20 μm and 10 μm (inset). e, Flow cytometry-based analysis of surface MHC-I (H-2) in mouse normal pancreas (C57Bl/6) and mouse PDAC cells grown as organoids. Top, isotype-subtracted geometric MFI. Each dot represents different mice/lines (n = 4). Data are mean ± s.e.m. Middle, representative flow cytometry plots. Bottom, representative images of organoids. f, Immunofluorescent staining images from a patient in Fig. 1g showing intracellular localization of MHC-I (green) in CK19-positive (red) ducts. Scale bar, 20 μm. A representative of at least two independent experiments is shown in a and e. P values determined by unpaired two-tailed t-tests (c–e). See Supplementary Fig. 1 for gel source data.

Source Data

Extended Data Fig. 2 Inhibition of autophagy and lysosomes restores MHC-I levels and plasma membrane localization.

a, Immunofluorescence staining of MHC-I after shRNA-mediated ATG3 knockdown. Scale bars, 50 μm. b, Representative flow cytometry plots for PaTu8902 cells after knockdown of ATG3 (related to Fig. 2b) and ATG7 (see also d). Representative plots from d and Fig. 2b are shown. c, Effect of ATG7 knockdown on MHC-I (HLA-A, -B, -C) expression in PaTu8902 cells. d, Flow cytometry-based quantification of plasma membrane levels of MHC-I (HLA-A, -B, -C) after ATG7 knockdown (n = 9 replicates from three independent experiments). e, Immunofluores-cence staining of MHC-I following ATG7 knockdown. Scale bars, 50 μm. f, g, Surface MHC-I levels after knockdown of ATG3 (f) or ATG7 (g) in mouse PDAC cells. Left, knockdown efficiency was confirmed by immunoblots. Middle, cell surface levels of MHC-I (H-2Kb/Db) measured by flow cytometry (n = 8 replicates from two independent experiments). Right, representative flow cytometry plots are shown. h, Treatment of KP4 cells with 150 nM BafA1 for the indicated times causes an increase in levels of HLA-A, -B. i, Flow cytometry-based quantification of plasma membrane MHC-I in the indicated cell lines after treatment with BafA1 for 16 h (n = 9 replicates from three independent experiments). j, Surface MHC-I (H-2) levels measured by flow cytometry. Mouse PDAC organoids were established from Atg5+/+ and Atg5−/− KPC cells. n = 4 biological replicates. Data are representative of three independent experiments. Right, representative flow cytometry plots. k, Effect of BafA1 treatment on the expression levels of antigen presentation machinery. l, Quantitative proteomics analysis of Panc1 cells that were treated with chloroquine (10 μM) for the indicated periods. n = 3 biological replicates. m, Effect of BafA1 treatment on expression levels of MHC-I in the indicated cell lines. Cell lines denoted in green show a significant change across all HLA isoforms after BafA1 treatment. n, o, Effect of ATG3 knockdown in H441 cells on total MHC-I (n) and plasma membrane MHC-I (o) as measured by flow cytometry-based quantification (n = 9 replicates from three independent experiments). A representative of at least two independent experiments is shown in a–c, e–h, j, k, m, n. Data are mean ± s.d. P values were determined by unpaired two-tailed t-tests. See Supplementary Fig. 1 for gel source data.

Source Data

Extended Data Fig. 3 Inhibition of macroautophagy, but not LAP/LANDO, restores MHC-I levels.

Knockdown mediated by shRNA (a–j) or siRNA (k, l) of FIP200, ATG14, ATG13 and ULK1, but not RUBICON, increased MHC-I levels in PDAC cells. a, d, g, i, k, Knockdown efficiency was confirmed by immunoblot (a, i, k) and qPCR (d, g). Data are mean ± s.d. from three biological replicates per group (d, g). a, e, Whole-cell abundance of MHC-I was assessed by immunoblot. c, Immunofluorescence staining of MHC-I (green) and LAMP2 (red). Scale bars, 50 μm. b, f, h, j, l, Cell-surface MHC-I levels were measured by flow cytometry (b, f, n = 9; h, j, n = 12; l, n = 16). Data are pooled from at least three independent experiments. Data are mean ± s.d. a–f, PaTu8902 cells (human). g–l, HY15549 cells (mouse). A representative of at least two independent experiments is shown in a, c, e, i and k. P values determined by unpaired two-tailed t-tests. See Supplementary Fig. 1 for gel source data.

Source Data

Extended Data Fig. 4 The UBA domain of NBR1 is required for interaction with MHC-I.

a, Proximity-dependent biotinylation catalysed by HLA-A–TrID. After addition of biotin, TurboID catalyses the formation of biotin-5′-AMP anhydride, which enables covalent tagging of endogenous proteins with biotin within a few nanometres of the ligase. Related to Fig. 2c. b, HLA-A–TrID was stably expressed in KP4 cells. Cells were treated with 10 μM of exogenous biotin for 30 min. After labelling, cells were lysed and biotinylated proteins were enriched with streptavidin conjugated beads. Biotinylated proteins were detected using streptavidin–HRP (b) or with antibodies against the indicated proteins (see Fig. 2c). Asterisks indicates ligase self-biotinylation. c, Endogenous ubiquitylated proteins were affinity captured from PaTu8902 cells with UBQLN1 UBA conjugated beads. Treatment of affinity captured samples for 1 h with purified Usp2-cc (+) to induce deubiquitylation leads to loss of ubiquitylation. Related to Fig. 2e. d, PaTu8902 cells stably expressing wild-type NBR1 (GFP–NBR1, n = 19 fields) or lacking the UBA domain (GFP–NBR1 dUBA, n = 16 fields) were co-stained for endogenous LC3B. Graph shows quantification of the percentage co-localization. Box-and-whisker plots as in Fig. 1. Scale bars, 20 μm (inset 10 μm). Related to Fig. 2f. e, Effect of NBR1 knockdown on respective HLA-A, -B and -C levels in PaTu8902 cells. Note that blotting images for NBR1 and tubulin are the same as in Fig. 2g. f, Immunofluorescence staining of MHC-I after NBR1 knockdown. Scale bars, 50 μm. A representative of at least three independent experiments is shown in b, c, e, f. See Supplementary Fig. 1 for gel source data.

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Extended Data Fig. 5 Autophagy inhibition restores MHC-I expression, leading to enhanced anti-tumour T cell response in vitro.

a, b, Autophagy flux (a) and cell-surface MHC-I levels (b) in PDAC cells measured by flow cytometry. Mouse PDAC cells expressing the GFP–LC3–RFP reporter and Dox-inducible mTurquoise2-ATG4B(C74A) were grown as organoids for 8 days and treated with Dox (1 μg ml−1) for the indicated hours. a, Autophagy flux represented by GFP/RFP ratio. Note that increased GFP/RFP ratio indicates reduced autophagy flux. b, Cell surface MHC-I (H-2Kb) levels. Representative flow cytometry plots are shown. Data are mean ± s.d. n = 3 biological replicates. Data are representative of at least four independent experiments. c, Fold changes of respective molecules on the cell surface quantified by flow cytometry. HY15549 cells expressing Dox-inducible mTurquoise2-tagged ATG4B(C74A) were grown as organoids for 8 days and treated with or without Dox (1 μg ml−1) for 72 h. Positive surface expression of each molecule was confirmed using respective isotype controls. Molecules found in immunological synapses are underlined. TFRC, transferrin receptor. Data are mean ± s.d. n = 4 biological replicates. Representative data from two independent experiments are shown. d–f, Mouse PDAC cells expressing OVA and carrying Dox-inducible mTurquoise2-ATG4B(C74A) were grown as organoids and treated with or without Dox (1 μg ml−1) for 96 h. Related to Fig. 3a, b. d, Autophagy inhibition was confirmed by immunoblot. mTurquoise2-ATG4B(C74A) or endogenous ATG4B were detected by anti-ATG4B antibody. e, f, Flow cytometry plots for H-2Kb (e) and H-2Kb-SIINFEKL (f). Representative plots from Fig. 3a, b are shown. Grey, isotype control. g, Representative flow cytometry plots of the OT-I cells co-cultured with mouse PDAC cells from Fig. 3c. h, Quantitative reverse transcription PCR (qRT–PCR) analysis of OT-I cells that were co-cultured with PDAC cells for 48 h. Related to Fig. 3c. Data are mean ± s.d. n = 3 biological replicates. For g and h, Dox(+) or Dox(−) indicates that PDAC cells were grown with or without Dox (1 μg ml−1) before co-culture. Dox was not added in co-culture. A representative of at least three independent experiments is shown in d–g. ****P < 0.0001, unpaired two-tailed t-tests. See Supplementary Fig. 1 for gel source data.

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Extended Data Fig. 6 Autophagy inhibition modulates anti-tumour immunity in both orthotopic tumours and liver metastasis.

a, Immunoblots showing autophagy inhibition in mSt-ATG4B(C74A)-expressing cells. Mouse PDAC cells carrying Dox-inducible mSt or 4B were treated with Dox (1 μg ml−1) for the indicated days. mSt or mSt-ATG4B(C74A) was detected by anti-RFP antibody. A representative of two independent experiments is shown. b–j, Related to Fig. 3e–h. Mouse PDAC cells shown in a were orthotopically transplanted into syngeneic (C57BL/6) mice. HY15549 cells (mSt, n = 8; 4B, n = 7) and HY19636 cells (n = 8 per group) were injected. b, Study design. c, Images of tumours at end point. d–g, HY19636 tumour weight (d), cell surface MHC-I levels (e) and PD-L1 levels (f) on PDAC cells and tumour-infiltrating CD8+ T cells (g) measured by flow cytometry. h, i, Representative H&E staining (h) and immunofluorescent staining (i) of HY15549 tumours (mSt, n = 8; 4B, n = 7). Scale bars, 100 μm. j, Quantification of tumour-infiltrating immune cells by flow cytometry (HY15549, n = 8 and 7; HY19636, n = 8 per group). Gating strategies are shown in Extended Data Fig. 7k and Supplementary Table 2. MDSC, myeloid-derived suppressor cells; Treg, T regulatory cells; TAM, tumour-associated macrophages. k–o, Autophagy-inhibition by shRNA-mediated ATG7 knockdown elicits similar anti-tumour T cell responses. k, Immunoblots for ATG7, LC3 and β-actin in PDAC cells (HY15549) expressing shRNAs against GFP or ATG7. A representative of at least two independent experiments is shown. l–o, Mouse PDAC cells shown in k were orthotopically transplanted into syngeneic mice (n = 7 per group). l, Images of tumours collected on day 22. m, Tumour weight. n, Tumour-infiltrating immune cells as measured by flow cytometry. o, Correlation between CD8+ T cell frequency among CD45+ cells and tumour weight. p–t, Related to Fig. 3i–l. Autophagy inhibition modulates anti-tumour immunity in metastatic tumours in the liver. Mouse PDAC cells (HY15549) carrying Dox-inducible mSt or 4B were injected into the spleen of syngeneic (C57BL/6) mice that were pre-fed with a Dox-containing diet (n = 4 per group). PDAC cells were pre-treated with Dox (1 μg ml−1) for 7 days before injection. p, Study design. q, Images of the liver. r, s, Representative images of H&E staining (r) and immunofluorescent staining (s) (n = 4 per group). Scale bars, 200 μm (r) and 100 μm (s). t, Quantification of immune cells in the liver metastasis as measured by flow cytometry. Data are mean ± s.e.m. n indicates individual mice. P values were determined by unpaired two-tailed t-tests (d–g, j, m, n, t) and Pearson correlation analysis (o). See Supplementary Fig. 1 for gel source data.

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Extended Data Fig. 7 Tumour regression after autophagy inhibition is rescued by depletion of CD8+ T cells or ablation of cell surface MHC-I.

a–c, Related to Fig. 3m. HY15549 cells with Dox-inducible mSt or 4B were orthotopically injected into C57BL/6 mice and fed with Dox-containing diet starting on day 5, and then received intraperitoneal injection of anti-CD8 or isotype control IgG (n = 7 per group). a, Study design. b, Images of tumours. c, Tumour-infiltrating leukocytes as quantified by flow cytometry. d–f, Related to Fig. 3n, o. HY15549 cells with Dox-inducible mSt or 4B were orthotopically injected into C57BL/6 mice (WT) or Batf3−/− mice (KO) (n = 8, 4, 8 and 5). d, Study design. e, Images of tumours. f, Quantification of tumour-infiltrating leukocytes by flow cytometry. g–j, Related to Fig. 3p–r. HY15549 cells carrying Dox-inducible mSt or 4B were stably transfected with lentiviral vectors expressing control shRNA (shScr, solid line) or shRNA against B2m (shB2m, dashed line). g, Cell surface MHC-I as measured by flow cytometry. Cells were treated with IFNγ (200 U ml−1) for 24 h before flow cytometry analysis. Representative data from three independent experiments are shown. h–j, Cells shown in g (4 × 104 cells) were orthotopically transplanted into syngeneic (C57BL/6) mice that were pre-fed with Dox diet (n = 8 per group). h, Study design. i, Images of tumours. j, Tumour-infiltrating leukocytes as quantified by flow cytometry. k, Gating strategies for flow cytometry analysis of tumours used in this study. See also Supplementary Table 2. Data are mean ± s.e.m. n indicates individual mice. P values determined by unpaired two-tailed t-tests.

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Extended Data Fig. 8 Separation of PDAC cells with distinct autophagy flux using the GFP–LC3–RFP reporter.

Heterogeneity in basal autophagy flux was explored using mouse PDAC cells (HY15549) expressing the GFP–LC3–RFP reporter. a, b, HY15549 cells were grown as organoids or transplanted into C57BL/6 mice to form orthotopic tumours. a, Autophagy flux, as represented by GFP/RFP ratio, was measured by flow cytometry. Atg5−/− mouse embryonic fibroblasts (MEF) with the GFP–LC3–RFP reporter (black) was used as a control. Representative flow plots from three independent experiments are shown. b, Representative fluorescent images of orthotopic tumours. Cells with high autophagy flux show GFP–LC3 puncta formation (inset, arrowhead) and a decrease in total GFP-fluorescent signals, displaying red appearance in the merged image. Scale bars, 100 μm. c–h, Mouse PDAC organoids were dissociated into single cells and sorted into autophagy-high (AThi) or -low (ATlo) cells according to the GPF/RFP ratio. c, Sorting strategies. d, Top KEGG pathways enriched in AThi cells compared to ATlo cells. Gene set enrichment analysis (GSEA) was performed using RNA sequencing (RNA-seq) data from sorted AThi and ATlo cells (n = 2 and 3 biologically independent samples), showing enrichment of the autophagy–lysosome gene signatures in AThi cells as compared with the ATlo cells. FDR, false discovery rate; NES, normalized enrichment score; Nom., nominal. e, f, Relative mRNA expression of autophagy/lysosome-related genes in the respective populations sorted from pooled populations (e) or a single-cell derived clone (f). n = 3 technical replicates. Representative results from four (e) and two (f) independent sorting experiments are shown. g–i, Clonogenic potential of sorted AThi and ATlo cells (g, h) and PDAC cells with Dox-inducible ATG4B(C74A) (AY6284) (i). Representative data from at least two independent experiments are shown. n = 4 (g) and n = 3 (i) per group. Data are mean ± s.d. (e–i). P values were determined by unpaired two-tailed t-tests.

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Extended Data Fig. 9 Basal autophagy flux determines immunogenicity of PDAC cells.

Mouse PDAC cells (HY15549) expressing the GFP–LC3–RFP reporter were sorted into AThi and ATlo cells (Extended Data Fig. 8c) and injected into the pancreas (a–g) or the spleen (h–k) of C57BL/6 mice (a–f, h–k) or nude mice (g). Cells were sorted from pooled populations except for (b). a, b, Tumour weight on day 21. AThi and ATlo cells were sorted from either pooled populations (a) (n = 9 and 10) or a single-cell derived clone (b) (n = 10 per group). c–e, Tumours shown in a were analysed. c, Cell surface MHC-I levels on PDAC cells measured by flow cytometry. d, Correlation between MHC-I levels on PDAC cells and tumour weight. e, Representative images of H&E (left) and immunofluorescent staining (right). Scale bars, 100 μm. f, Quantification of tumour-infiltrating immune cells by flow cytometry (n = 8 per group). Orthotopic tumours obtained on day 21 were analysed. g, Orthotopic tumours in nude mice obtained on day 19 (n = 8 and 7). h–k, Liver metastasis model. h, Study design. i, j, Weight of livers (i) and cell surface MHC-I levels on PDAC cells measured by flow cytometry (j) on day 17 (n = 5 per group). k, Representative immunofluorescence images of livers obtained on day 9 (n = 3 per group). Frozen sections were stained with anti-CD8a antibody and DAPI. In these merged images, cells with high autophagy flux appear as red, reflecting the relative loss of GFP-fluorescence and lower GFP/RFP ratio, whereas cells with low autophagy flux appear as yellow to green, reflecting high GFP/RFP ratio. In the enlarged images, CD8a+ cells were indicated by white arrowheads. Scale bars, 100 μm. For a, c–f and i–k, experiments were performed at least twice and representative data of one experiment are shown. Data are mean ± s.e.m. (a–c, f, g, i, j). n indicates individual mice. P values were determined by unpaired two-tailed t-tests (a–c, f, g, i, j) and Pearson correlation analysis (d).

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Extended Data Fig. 10 Autophagy inhibition synergizes with dual ICB.

a–c, Anti-PD1 antibody treatment did not affect tumour growth in either control or autophagy-inhibited tumours. Mice bearing orthotopic PDAC tumours (HY15549) carrying Dox-inducible mSt or 4B were treated with Dox beginning on day 5 and received either isotype control IgG or anti-PD1 antibody (n = 7, 8, 8 and 7 per group). a, Study design. b, c, Images (b) and weight (c) of tumours. d–g, Related to Fig. 4a–d. Mice bearing orthotopic PDAC tumours (HY15549) expressing Dox-inducible mSt or 4B were treated with Dox beginning on day 5 and received either isotype control IgG or dual ICB (anti-PD1/CTLA4 antibodies) (n = 7 per group). d, e, Representative images of immunofluorescence staining (d) and H&E staining (e). Scale bars, 100 μm. f, g, Quantification of tumour-infiltrating immune cells by flow cytometry. h, Cell surface MHC-I (H-2Kb/Db) levels measured by flow cytometry. Mouse PDAC cells were treated with chloroquine or BafA1 at the indicated concentrations for 48 h (n = 4). Mouse PDAC cells were grown in 2D culture (chloroquine) or as organoids (BafA1). Representative results from at least three independent experiments are shown. i–m, Mice bearing orthotopic PDAC tumours expressing the GFP–LC3–RFP reporter were treated with PBS or chloroquine beginning on day 5 (n = 7 vs 6 for HY15549 and n = 8 vs 8 for HY19636). i, Study design. j, Images of tumours. k, Cell-surface MHC-I and PD-L1 levels on PDAC cells measured by flow cytometry. l, Tumour weight. m, Quantification of tumour-infiltrating immune cells by flow cytometry. n, Representative fluorescence images of tumours expressing the GFP–LC3–RFP reporter from Fig. 4j. Numerical values represent mean fluorescent intensity of each field. o, Quantification of tumour-infiltrating immune cells by flow cytometry (n = 8, 8, 8 and 5; left to right). Tumours in Fig. 4k were analysed. Data are mean ± s.e.m. (c, f, g, k–m, o) or ± s.d. (h). n indicates individual mice (c, f, g, k–m, o) or biological replicates (h). Except for the orthotopic implantation of HY19636 cells (j–m), all experiments were performed at least twice and representative data of one experiment are shown. ****P < 0.0001, unpaired two-tailed t-tests.

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The file contains Supplementary Tables 1-4, which provide detailed information on the materials and analysis, and Supplementary Figure 1, which contains gel source data.

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Yamamoto, K., Venida, A., Yano, J. et al. Autophagy promotes immune evasion of pancreatic cancer by degrading MHC-I. Nature 581, 100–105 (2020). https://doi.org/10.1038/s41586-020-2229-5

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