Tissue-associated bacterial alterations in rectal carcinoma patients revealed by 16S rRNA community profiling

Frontiers in Cellular and Infection Microbiology

Volumn 6, Issue DEC, 2016, Pages

  Thomas, Andrew M ^a,b   Jesus, Eliane C ^a   Lopes, Ademar ^a   Aguiar, Samuel ^a   Begnami, Maria D ^a   Rocha, Rafael M ^c   Carpinetti, Paola Avelar ^d   Camargo, Anamaria A ^d   Hoffmann, Christian ^b   Freitas, Helano C ^a   Silva, Israel T ^a   Nunes, Diana N ^a   Setubal, João C ^b,e   Dias Neto, Emmanuel ^a,b  

^a A C CAMARGO CANCER CENTER   (Brazil)

^b UNIVERSITY OF SÃO PAULO   (Brazil)

^c FEDERAL UNIVERSITY OF SÃO PAULO   (Brazil)

^d HOSPITAL SÍRIO LIBANÊS   (Brazil)

^e VIRGINIA BIOINFORMATICS INSTITUTE   (United States)

Author keywords

16S rRNA gene sequencing; Bacterial diversity and community composition; Bacteroides fragilis; Mucosa associated microbiota; Rectal cancer

Indexed keywords

RNA 16S; BACTERIAL DNA; RIBOSOME DNA;

ABDOMINAL PAIN; ADULT; ARTICLE; BACTERIAL FLORA; BACTEROIDES FRAGILIS; BIODIVERSITY; BIOPSY; BLEEDING; CALCULATION; CHRONIC DIARRHEA; CLINICAL ARTICLE; COHORT ANALYSIS; COLONOSCOPY; COMMUNITY ASSESSMENT; CONSTIPATION; CONTROLLED STUDY; DNA EXTRACTION; DNA FINGERPRINTING; ESCHERICHIA COLI; FEMALE; HUMAN; IMMUNOHISTOCHEMISTRY; MALE; MICROBIAL ACTIVITY; MICROBIAL COMMUNITY; MIDDLE AGED; PRINCIPAL COORDINATE ANALYSIS; RECTUM CARCINOMA; RISK FACTOR; SEQUENCE ANALYSIS; SPATIOTEMPORAL ANALYSIS; TUMOR MICROENVIRONMENT; VALIDATION PROCESS; AGED; BACTERIAL GENE; BACTERIUM; BRAZIL; CLASSIFICATION; CLUSTER ANALYSIS; COLON; DNA SEQUENCE; FECES; GASTROINTESTINAL TRACT; GENETICS; MICROBIAL CONSORTIUM; MICROBIOLOGY; MOLECULAR TYPING; PATHOLOGY; PHYLOGENY; PROCEDURES; RECTUM TUMOR;

ADULT; AGED; BACTERIA; BIODIVERSITY; BIOPSY; BRAZIL; CLUSTER ANALYSIS; COLON; COLONOSCOPY; DNA, BACTERIAL; DNA, RIBOSOMAL; FECES; FEMALE; GASTROINTESTINAL TRACT; GENES, BACTERIAL; HUMANS; IMMUNOHISTOCHEMISTRY; MALE; MICROBIAL CONSORTIA; MIDDLE AGED; MOLECULAR TYPING; PHYLOGENY; RECTAL NEOPLASMS; RNA, RIBOSOMAL, 16S; SEQUENCE ANALYSIS, DNA;

EID: 85009754184     PISSN: None     EISSN: 22352988     Source Type: Journal    
DOI: 10.3389/fcimb.2016.00179     Document Type: Article

References (81)

1. Ahn, J., Sinha, R., Pei, Z., Dominianni, C., Wu, J., Shi, J., et al. (2013). Human gut microbiome and risk for colorectal cancer. JNCI J. Natl. Cancer Inst. 105, 1907-1911. doi: 10.1093/jnci/djt300
2. Allais, L., Kerckhof, F.-M., Verschuere, S., Bracke, K. R., De Smet, R., Laukens, D., et al. (2016). Chronic cigarette smoke exposure induces microbial and inflammatory shifts and mucin changes in the murine gut. Environ. Microbiol. 18, 1352-1363. doi: 10.1111/1462-2920.12934
3. Arthur, J. C., Gharaibeh, R. Z., Mühlbauer, M., Perez-Chanona, E., Uronis, J. M., McCafferty, J., et al. (2014). Microbial genomic analysis reveals the essential role of inflammation in bacteria-induced colorectal cancer. Nat. Commun. 5, 4724. doi: 10.1038/ncomms5724
4. Binefa, G., Rodríguez-Moranta, F., Teule, à., and Medina-Hayas, M. (2014). Colorectal cancer: from prevention to personalized medicine. World J. Gastroenterol. 20, 6786. doi: 10.3748/wjg.v20.i22.6786
5. Bingham, S. A. (2000). Diet and colorectal cancer prevention. Biochem. Soc. Trans. 28, 12-16. doi: 10.1042/bst0280012
6. Boulangé, C. L., Neves, A. L., Chilloux, J., Nicholson, J. K., and Dumas, M.-E. (2016). Impact of the gut microbiota on inflammation, obesity, and metabolic disease. Genome Med. 8:42. doi: 10.1186/s13073-016-0303-2
7. Calinski, T., and Harabasz, J. A. (1974). Dendrite method for cluster analysis. Commun Stat. Simul Comput 3, 1-27. doi: 10.1080/03610917408548446
8. Caporaso, J. G., Bittinger, K., Bushman, F. D., DeSantis, T. Z., Andersen, G. L., and Knight, R. (2010b). PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics 26, 266-267. doi: 10.1093/bioinformatics/btp636
9. Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., et al. (2010a). QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 2010, 335-336. doi: 10.1038/nmeth.f.303
10. Cole, J. R., Wang, Q., Fish, J. A., Chai, B., McGarrell, D. M., Sun, Y., et al. (2014). Ribosomal Database Project: data and tools for high throughput rRNA analysis. Nucleic Acids Res. 42, D633-D642. doi: 10.1093/nar/gkt1244
11. DeSantis, T. Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E. L., Keller, K., et al. (2006). Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72, 5069-5072. doi: 10.1128/AEM.03006-05
12. Duboc, H., Rajca, S., Rainteau, D., Benarous, D., Maubert, M.-A., Quervain, E., et al. (2013). Connecting dysbiosis, bile-acid dysmetabolism and gut inflammation in inflammatory bowel diseases. Gut 62, 531-539. doi: 10.1136/gutjnl-2012-302578
13. Duque, A. L. R. F., Monteiro, M., Adorno, M. A. T., Sakamoto, I. K., and Sivieri, K. (2016). An exploratory study on the influence of orange juice on gut microbiota using a dynamic colonic model. Food Res. Int. 84, 160-169. doi: 10.1016/j.foodres.2016.03.028
14. Durbán, A., Abellán, J. J., Jiménez-Hernández, N., Ponce, M., Ponce, J., Sala, T., et al. (2011). Assessing gut microbial diversity from feces and rectal mucosa. Microb. Ecol. 61, 123-133. doi: 10.1007/s00248-010-9738-y
15. Earley, H., Lennon, G., Balfe, A., Kilcoyne, M., Clyne, M., Joshi, L., et al. (2015). A Preliminary study examining the binding capacity of Akkermansia muciniphila and Desulfovibrio spp., to colonic mucin in health and ulcerative colitis. PLoS ONE 10:e0135280. doi: 10.1371/journal.pone.0135280
16. Eckburg, P. B., Bik, E. M., Bernstein, C. N., Purdom, E., Dethlefsen, L., Sargent, M., et al. (2005). Diversity of the human intestinal microbial flora. Science 308, 1635-1638. doi: 10.1126/science.1110591
17. Edgar, R. C. (2010). Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460-2461. doi: 10.1093/bioinformatics/btq461
18. Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C., and Knight, R. (2011). UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194-2200. doi: 10.1093/bioinformatics/btr381
19. Edgar, R. C. (2013). UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996-998. doi: 10.1038/nmeth.2604
20. Feng, Q., Liang, S., Jia, H., Stadlmayr, A., Tang, L., Lan, Z., et al. (2015). Gut microbiome development along the colorectal adenoma-carcinoma sequence. Nat. Commun. 6:6528. doi: 10.1038/ncomms7528
21. Flemer, B., Lynch, D. B., Brown, J. M., Jeffery, I. B., Ryan, F. J., Claesson, M. J., et al. (2016). Tumour-associated and non-tumour-associated microbiota in colorectal cancer. Gut. doi: 10.1136/gutjnl-2015-309595. [Epub ahead of print].
22. Fuerst, J. A., and Sagulenko, E. (2011). Beyond the bacterium: planctomycetes challenge our concepts of microbial structure and function. Nat. Rev. Microbiol. 9, 403-413. doi: 10.1038/nrmicro2578
23. Galluzzi, L., Buqué, A., Kepp, O., Zitvogel, L., and Kroemer, G. (2015). Immunological effects of conventional chemotherapy and targeted anticancer agents. Cancer Cell 28, 690-714. doi: 10.1016/j.ccell.2015.10.012
24. Gao, Z., Guo, B., Gao, R., Zhu, Q., and Qin, H. (2015). Microbiota disbiosis is associated with colorectal cancer. Front. Microbiol. 6:20. doi: 10.3389/fmicb.2015.00020
25. Gevers, D., Kugathasan, S., Denson, L. A., Vázquez-Baeza, Y., Van Treuren, W., Ren, B., et al. (2014). The treatment-naive microbiome in new-onset crohn's disease. Cell Host Microbe 15, 382-392. doi: 10.1016/j.chom.2014.02.005
26. Gur, C., Ibrahim, Y., Isaacson, B., Yamin, R., Abed, J., Gamliel, M., et al. (2015). Binding of the Fap2 Protein of Fusobacterium nucleatum to human inhibitory receptor TIGIT protects tumors from immune cell attack. Immunity 42, 344-355. doi: 10.1016/j.immuni.2015.01.010
27. Hajishengallis, G., Darveau, R. P., and Curtis, M. A. (2012). The keystone-pathogen hypothesis. Nat. Rev. Microbiol. 10, 717-725. doi: 10.1038/nrmicro2873
28. Hennig, C. (2015). fpc: Flexible Procedures for Clustering:R Package Version 2.1-10.
29. Holmes, I., Harris, K., and Quince, C. (2012). Dirichlet multinomial mixtures: generative models for microbial metagenomics. PLoS ONE 7:e30126. doi: 10.1371/journal.pone.0030126
30. Hong, P.-Y., Croix, J. A., Greenberg, E., Gaskins, H. R., and Mackie, R. I. (2011). Pyrosequencing-based analysis of the mucosal microbiota in healthy individuals reveals ubiquitous bacterial groups and micro-heterogeneity. PLoS ONE 6:e25042. doi: 10.1371/journal.pone.0025042
31. Hou, S., Makarova, K. S., Saw, J. H., Senin, P., Ly, B. V., Zhou, Z., et al. (2008). Complete genome sequence of the extremely acidophilic methanotroph isolate V4, Methylacidiphilum infernorum, a representative of the bacterial phylum Verrucomicrobia. Biol. Direct 3:26. doi: 10.1186/1745-6150-3-26
32. Kelly, B. J., Gross, R., Bittinger, K., Sherrill-Mix, S., Lewis, J. D., Collman, R. G., et al. (2015). Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA. Bioinformatics 31, 2461-2468. doi: 10.1093/bioinformatics/btv183
33. Klindworth, A., Pruesse, E., Schweer, T., Peplies, J., Quast, C., Horn, M., et al. (2013). Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 41:e1. doi: 10.1093/nar/gks808
34. Koren, O., Knights, D., Gonzalez, A., Waldron, L., Segata, N., Knight, R., et al. (2013). A guide to enterotypes across the human body: meta-analysis of microbial community structures in human microbiome datasets. PLoS Comput. Biol. 9:e1002863. doi: 10.1371/journal.pcbi.1002863
35. Kostic, A. D., Chun, E., Robertson, L., Glickman, J. N., Gallini, C. A., Michaud, M., et al. (2013). Fusobacterium nucleatum potentiates intestinal tumorigenesis and modulates the tumor-immune microenvironment. Cell Host Microbe 14, 207-215. doi: 10.1016/j.chom.2013.07.007
36. Kostic, A. D., Gevers, D., Pedamallu, C. S., Michaud, M., Duke, F., Earl, A. M., et al. (2012). Genomic analysis identifies association of Fusobacterium with colorectal carcinoma. Genome Res. 22, 292-298. doi: 10.1101/gr.126573.111
37. Lane, D. J. (1991). "16S/23S rRNA sequencing," in Nucleic Acid Techniques in Bacterial Systematics. ed E. G. M. Stackebrandt (Chichester: John Wiley and Sons), 115-175.
38. Leclercq, S., Matamoros, S., Cani, P. D., Neyrinck, A. M., Jamar, F., Stärkel, P., et al. (2014). Intestinal permeability, gut-bacterial dysbiosis, and behavioral markers of alcohol-dependence severity. Proc. Natl. Acad. Sci.U.S.A. 111, E4485-E4493. doi: 10.1073/pnas.1415174111
39. Lozupone, C., and Knight, R. (2005). UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228-8235. doi: 10.1128/AEM.71.12.8228-8235.2005
40. Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M., and Hornik, K. (2015). Cluster Analysis Basics and Extensions. R package version 2.0.1. CRAN. Available online at: https://cran.r-project.org/web/packages/cluster/citation.html
41. McGarr, S. E., Ridlon, J. M., and Hylemon, P. B. (2005). Diet, anaerobic bacterial metabolism, and colon cancer: a review of the literature. J. Clin. Gastroenterol. 39, 98-109.
42. McMurdie, P. J., and Holmes, S. (2013). phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8:e61217. doi: 10.1371/journal.pone.0061217
43. Mira-Pascual, L., Cabrera-Rubio, R., Ocon, S., Costales, P., Parra, A., Suarez, A., et al. (2015). Microbial mucosal colonic shifts associated with the development of colorectal cancer reveal the presence of different bacterial and archaeal biomarkers. J. Gastroenterol. 50, 167-179. doi: 10.1007/s00535-014-0963-x
44. Moore, W. E., and Moore, L. H. (1995). Intestinal floras of populations that have a high risk of colon cancer. Appl. Environ. Microbiol. 61, 3202-3207.
45. Nakatsu, G., Li, X., Zhou, H., Sheng, J., Wong, S. H., Wu, W. K., et al. (2015). Gut mucosal microbiome across stages of colorectal carcinogenesis. Nat. Commun. 6:8727. doi: 10.1038/ncomms9727
46. Nelson, W. C., and Stegen, J. C. (2015). The reduced genomes of Parcubacteria (OD1) contain signatures of a symbiotic lifestyle. Front. Microbiol. 6:173. doi: 10.3389/fmicb.2015.00713
47. Oksanen, J., Blanchet, F., Kindt, R., Legendre, P., and O'Hara, R. (2016). Vegan: Community Ecology Package. R Package 23-3 2016:Available online at: https://cran.r-project.org/web/packa
48. O'Mahony, L., Feeney, M., O'Halloran, S., Murphy, L., Kiely, B., Fitzgibbon, J., et al. (2001). Probiotic impact on microbial flora, inflammation and tumour development in IL-10 knockout mice. Aliment. Pharmacol. Ther. 15, 1219-1225. doi: 10.1046/j.1365-2036.2001.01027.x
49. Pitt, J. M., Marabelle, A., Eggermont, A., Soria, J.-C., Kroemer, G., and Zitvogel, L. (2016). Targeting the tumor microenvironment: removing obstruction to anticancer immune responses and immunotherapy. Ann. Oncol. 8, 1482-1492. doi: 10.1093/annonc/mdw168
50. Price, M. N., Dehal, P. S., and Arkin, A. P. (2009). FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol. Biol. Evol. 26, 1641-1650. doi: 10.1093/molbev/msp077
51. Reid, G., Howard, J., and Gan, B. S. (2001). Can bacterial interference prevent infection? Trends Microbiol. 9, 424-428. doi: 10.1016/S0966-842X(01)02132-1
52. R Foundation (2011). R Foundation for Statistical Computing. Vienna AI 3-900051-07-0: R Development Core Team.
53. Ridlon, J. M., Kang, D.-J., Hylemon, P. B., and Bajaj, J. S. (2014). Bile acids and the gut microbiome. Curr. Opin. Gastroenterol. 30, 332-338. doi: 10.1097/MOG.0000000000000057
54. Riley, D. R., Sieber, K. B., Robinson, K. M., White, J. R., Ganesan, A., Nourbakhsh, S., et al. (2013). Bacteria-human somatic cell lateral gene transfer is enriched in cancer samples. PLoS Comput. Biol. 9:e1003107. doi: 10.1371/journal.pcbi.1003107
55. Rousseeuw, P. J. (1987). Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20, 53-65.
56. Rubinstein, M. R., Wang, X., Liu, W., Hao, Y., Cai, G., Han, Y. W., et al. (2013). Fusobacterium nucleatum promotes colorectal carcinogenesis by modulating E-cadherin/ß-catenin signaling via its FadA adhesin. Cell Host Microbe 14, 195-206. doi: 10.1016/j.chom.2013.07.012
57. Sabino, J., Vieira-Silva, S., Machiels, K., Joossens, M., Falony, G., Ballet, V., et al. (2016). Primary sclerosing cholangitis is characterised by intestinal dysbiosis independent from IBD. Gut. 10, 1681-1689. doi: 10.1136/gutjnl-2015-311004
58. Sanapareddy, N., Legge, R. M., Jovov, B., McCoy, A., Burcal, L., Araujo-Perez, F., et al. (2012). Increased rectal microbial richness is associated with the presence of colorectal adenomas in humans. ISME J. 6, 1858-1868. doi: 10.1038/ismej.2012.43
59. Sears, C. L., Geis, A. L., and Housseau, F. (2014). Bacteroides fragilis subverts mucosal biology: from symbiont to colon carcinogenesis. J. Clin. Invest. 124, 4166-4172. doi: 10.1172/JCI72334
60. Shannon, C. E. (1948). The mathematical theory of communication. 1963. MD Comput. 14, 306-317.
61. Shapiro, H., Thaiss, C. A., Levy, M., and Elinav, E. (2014). The cross talk between microbiota and the immune system: metabolites take center stage. Curr. Opin. Immunol. 30, 54-62. doi: 10.1016/j.coi.2014.07.003
62. Simpson, E. H. (1949). Measurement of diversity. Nature 163, 688-688. doi: 10.1038/163688a0
63. Sonnenburg, J. L., and Bäckhed, F. (2016). Diet-microbiota interactions as moderators of human metabolism. Nature 535, 56-64. doi: 10.1038/nature18846
64. Soo, R. M., Skennerton, C. T., Sekiguchi, Y., Imelfort, M., Paech, S. J., Dennis, P. G., et al. (2014). An expanded genomic representation of the phylum cyanobacteria. Genome Biol. Evol. 6, 1031-1045. doi: 10.1093/gbe/evu073
65. Tamas, K., Walenkamp, A. M. E., De Vries, E. G. E., Van Vugt, M. A. T. M., Beets-Tan, R. G., Van Etten, B., et al. (2015). Rectal and colon cancer: not just a different anatomic site. Cancer Treat. Rev. 41, 671-679. doi: 10.1016/j.ctrv.2015.06.007
66. Tibshirani, R., and Walther, G. (2005). Cluster validation by prediction strength. J. Comput. Graph. Stat. 14, 511-528. doi: 10.1198/106186005X59243
67. Tong, J., Liu, C., Summanen, P., Xu, H., and Finegold, S. M. (2011). Application of quantitative real-time PCR for rapid identification of Bacteroides fragilis group and related organisms in human wound samples. Anaerobe 17, 64-68. doi: 10.1016/j.anaerobe.2011.03.004
68. Torre, L. A., Bray, F., Siegel, R. L., Ferlay, J., Lortet-tieulent, J., and Jemal, A. (2015). Global cancer statistics, 2012. CA Cancer J. Clin. 65, 87-108. doi: 10.3322/caac.21262
69. Turnbaugh, P. J., Ridaura, V. K., Faith, J. J., Rey, F. E., Knight, R., and Gordon, J. I. (2009). The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Sci. Transl. Med. 1, 6ra14. doi: 10.1126/scitranslmed.3000322
70. Vétizou, M., Pitt, J. M., Daillere, R., Lepage, P., Waldschmitt, N., Flament, C., et al. (2015). Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota. Science 350, 1079-1084. doi: 10.1126/science.aad1329
71. Wang, Q., Garrity, G. M., Tiedje, J. M., and Cole, J. R. (2007). Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261-5267. doi: 10.1128/AEM.00062-07
72. Wang, T., Cai, G., Qiu, Y., Fei, N., Zhang, M., Pang, X., et al. (2012). Structural segregation of gut microbiota between colorectal cancer patients and healthy volunteers. ISME J. 6, 320-329. doi: 10.1038/ismej.2011.109
73. Warren, R. L., Freeman, D. J., Pleasance, S., Watson, P., Moore, R. A., Cochrane, K., et al. (2013). Co-occurrence of anaerobic bacteria in colorectal carcinomas. Microbiome 1:16. doi: 10.1186/2049-2618-1-16
74. Wick, E. C., Rabizadeh, S., Albesiano, E., Wu, X., Wu, S., Chan, J., et al. (2014). Stat3 activation in murine colitis induced by enterotoxigenic Bacteroides fragilis. Inflamm. Bowel Dis. 20, 821-834. doi: 10.1097/MIB.0000000000000019
75. Wu, N., Yang, X., Zhang, R., Li, J., Xiao, X., Hu, Y., et al. (2013). Dysbiosis signature of fecal microbiota in colorectal cancer patients. Microb. Ecol. 66, 462-470. doi: 10.1007/s00248-013-0245-9
76. Wu, S., Rhee, K.-J., Albesiano, E., Rabizadeh, S., Wu, X., Yen, H.-R., et al. (2009). A human colonic commensal promotes colon tumorigenesis via activation of T helper type 17 T cell responses. Nat. Med. 15:1016-1022. doi: 10.1038/nm.2015
77. Yang, L., and Pei, Z. (2006). Bacteria, inflammation, and colon cancer. World J. Gastroenterol. 12, 6741-6746. doi: 10.3748/wjg.v12.i42.6741
78. Yu, H., Guo, Z., Shen, S., and Shan, W. (2016). Effects of taurine on gut microbiota and metabolism in mice. Amino Acids 48, 1601-1617. doi: 10.1007/s00726-016-2219-y
79. Zeller, G., Tap, J., Voigt, A. Y., Sunagawa, S., Kultima, J. R., Costea, P. I., et al. (2014). Potential of fecal microbiota for early-stage detection of colorectal cancer. Mol. Syst. Biol. 10, 766-766. doi: 10.15252/msb.20145645
80. Zhang, Z., Geng, J., Tang, X., Fan, H., Xu, J., Wen, X., et al. (2014). Spatial heterogeneity and co-occurrence patterns of human mucosal-associated intestinal microbiota. ISME J. 8, 881-893. doi: 10.1038/ismej.2013.185
81. Zitvogel, L., Galluzzi, L., Smyth, M. J., and Kroemer, G. (2013). Mechanism of action of conventional and targeted anticancer therapies: reinstating immunosurveillance. Immunity 39, 74-88. doi: 10.1016/j.immuni.2013.06.014