Erratum to: Tumor immune microenvironment characterization in clear cell renal cell carcinoma identifies prognostic and immunotherapeutically relevant messenger RNA signatures [Genome Biology. 17, (2016) (231)] DOI: 10.1186/s13059-016-1092-z;Tumor immune microenvironment characterization in clear cell renal cell carcinoma identifies prognostic and immunotherapeutically relevant messenger RNA signatures

Genome Biology

Volumn 17, Issue 1, 2016, Pages

  Şenbabaoğlu, Yasin ^a   Gejman, Ron S ^a,e   Winer, Andrew G ^a   Liu, Ming ^a   Van Allen, Eliezer M ^b   de Velasco, Guillermo ^b   Miao, Diana ^b   Ostrovnaya, Irina ^a   Drill, Esther ^a   Luna, Augustin ^a   Weinhold, Nils ^a   Lee, William ^a   Manley, Brandon J ^a   Khalil, Danny N ^a   Kaffenberger, Samuel D ^a   Chen, Yingbei ^a   Danilova, Ludmila ^c,d   Voss, Martin H ^a   Coleman, Jonathan A ^a   Russo, Paul ^a   Reuter, Victor E ^a   Chan, Timothy A ^a,e   Cheng, Emily H ^a   Scheinberg, David A ^a,e   Li, Ming O ^a   Choueiri, Toni K ^b   Hsieh, James J ^a   Sander, Chris ^a   Hakimi, A Ari ^a   more..

^a MEMORIAL SLOAN KETTERING CANCER CENTER   (United States)

^b DANA FARBER CANCER INSTITUTE   (United States)

^c JOHNS HOPKINS UNIVERSITY   (United States)

^d VAVILOV INSTITUTE OF GENERAL GENETICS   (Russian Federation)

^e WEILL CORNELL MEDICAL COLLEGE   (United States)

Author keywords

Cancer immunotherapy; Checkpoint blockade; Clear cell renal cell carcinoma (ccRCC); Computational deconvolution; Tumor immune microenvironment

Indexed keywords

MAJOR HISTOCOMPATIBILITY ANTIGEN CLASS 1; MESSENGER RNA; NIVOLUMAB; TUMOR PROTEIN;

ANTIGEN FUNCTION; ANTIGEN PRESENTING MACHINERY EXPRESSION; ARTICLE; CANCER CLASSIFICATION; CANCER IMMUNOTHERAPY; CANCER PROGNOSIS; CD8+ T LYMPHOCYTE; CELL INFILTRATION; GENE EXPRESSION; HUMAN; IMMUNOCOMPETENT CELL; IMMUNOGENICITY; KIDNEY CARCINOMA; PROTEOMICS; REGULATORY T LYMPHOCYTE; T LYMPHOCYTE SUBPOPULATION; TH17 CELL; TH2 CELL; TRANSCRIPTOMICS; TUMOR IMMUNITY MICROENVIRONMENT; TUMOR MICROENVIRONMENT; BIOSYNTHESIS; CARCINOMA, RENAL CELL; COMPUTER SIMULATION; GENE EXPRESSION REGULATION; GENETICS; IMMUNOLOGY; IMMUNOTHERAPY; NUCLEOTIDE MOTIF; PROGNOSIS; TUMOR ASSOCIATED LEUKOCYTE;

CARCINOMA, RENAL CELL; CD8-POSITIVE T-LYMPHOCYTES; COMPUTER SIMULATION; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; IMMUNOTHERAPY; LYMPHOCYTES, TUMOR-INFILTRATING; NEOPLASM PROTEINS; NUCLEOTIDE MOTIFS; PROGNOSIS; PROTEOMICS; RNA, MESSENGER; TUMOR MICROENVIRONMENT;

EID: 85002930854     PISSN: 14747596     EISSN: 1474760X     Source Type: Journal    
DOI: 10.1186/s13059-017-1180-8     Document Type: Erratum

References (85)

1. Nishikawa H, Sakaguchi S. Regulatory T cells in cancer immunotherapy. Curr Opin Immunol. 2014;27:1-7.
2. Noy R, Pollard JW. Tumor-associated macrophages: from mechanisms to therapy. Immunity. 2014;41:49-61.
3. De Palma M, Lewis CE. Macrophage regulation of tumor responses to anticancer therapies. Cancer Cell. 2013;23:277-86.
4. Galon J, Costes A, Sanchez-Cabo F, Kirilovsky A, Mlecnik B, Lagorce-Pages C, et al. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science. 2006;313:1960-4.
5. Galon J, Fridman WH, Pages F. The adaptive immunologic microenvironment in colorectal cancer: a novel perspective. Cancer Res. 2007;67:1883-6.
6. Pages F, Kirilovsky A, Mlecnik B, Asslaber M, Tosolini M, Bindea G, et al. In situ cytotoxic and memory T cells predict outcome in patients with early-stage colorectal cancer. J Clin Oncol. 2009;27:5944-51.
7. Tumeh PC, Harview CL, Yearley JH, Shintaku IP, Taylor EJ, Robert L, et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature. 2014;515:568-71.
8. Gajewski TF, Schreiber H, Fu Y-X. Innate and adaptive immune cells in the tumor microenvironment. Nat Immunol. 2013;14:1014-22.
9. van Rooij N, van Buuren MM, Philips D, Velds A, Toebes M, Heemskerk B, et al. Tumor exome analysis reveals neoantigen-specific T-cell reactivity in an ipilimumab-responsive melanoma. J Clin Oncol. 2013;31:e439-42.
10. Snyder A, Makarov V, Merghoub T, Yuan J, Zaretsky JM, Desrichard A, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med. 2014;371:2189-99.
11. Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ, et al. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015;348:124-8.
12. Neefjes J, Jongsma ML, Paul P, Bakke O. Towards a systems understanding of MHC class I and MHC class II antigen presentation. Nat Rev Immunol. 2011;11:823-36.
13. Rooney MS, Shukla SA, Wu CJ, Getz G, Hacohen N. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell. 2015;160:48-61.
14. Bindea G, Mlecnik B, Tosolini M, Kirilovsky A, Waldner M, Obenauf AC, et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity. 2013;39:782-95.
15. Yoshihara K, Shahmoradgoli M, Martinez E, Vegesna R, Kim H, Torres-Garcia W, et al. Inferring tumour purity and stromal and immune cell admixture from expression data. Nat Commun. 2013;4:2612.
16. Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12:453-7.
17. Gong T, Szustakowski JD. DeconRNASeq: a statistical framework for deconvolution of heterogeneous tissue samples based on mRNA-Seq data. Bioinformatics. 2013;29:1083-5.
18. Thompson RH, Dong H, Lohse CM, Leibovich BC, Blute ML, Cheville JC, et al. PD-1 is expressed by tumor-infiltrating immune cells and is associated with poor outcome for patients with renal cell carcinoma. Clin Cancer Res. 2007;13:1757-61.
19. Janiszewska AD, Poletajew S, Wasiutynski A. Spontaneous regression of renal cell carcinoma. Contemp Oncol (Pozn). 2013;17:123-7.
20. Atkins MB, Regan M, McDermott D. Update on the role of interleukin 2 and other cytokines in the treatment of patients with stage IV renal carcinoma. Clin Cancer Res. 2004;10:6342s-6.
21. Escudier B. Emerging immunotherapies for renal cell carcinoma. Ann Oncol. 2012;23 Suppl 8:viii35-40.
22. Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC, McDermott DF, et al. Safety, Activity, and Immune Correlates of Anti-PD-1 Antibody in Cancer. N Engl J Med. 2012;366:2443-54.
23. Herbst RS, Soria J-C, Kowanetz M, Fine GD, Hamid O, Gordon MS, et al. Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature. 2014;515:563-7.
24. Gubin MM, Zhang X, Schuster H, Caron E, Ward JP, Noguchi T, et al. Checkpoint blockade cancer immunotherapy targets tumour-specific mutant antigens. Nature. 2014;515:577-81.
25. Igarashi T, Takahashi H, Tobe T, Suzuki H, Mizoguchi K, Nakatsu HO, et al. Effect of tumor-infiltrating lymphocyte subsets on prognosis and susceptibility to interferon therapy in patients with renal cell carcinoma. Urol Int. 2002;69:51-6.
26. Yadav M, Jhunjhunwala S, Phung QT, Lupardus P, Tanguay J, Bumbaca S, et al. Predicting immunogenic tumour mutations by combining mass spectrometry and exome sequencing. Nature. 2014;515:572-6.
27. Lawrence MS, Stojanov P, Polak P, Kryukov GV, Cibulskis K, Sivachenko A, et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. 2013;499:214-8.
28. The Cancer Genome Atlas Research Network. Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature. 2013;499:43-9.
29. Sato Y, Yoshizato T, Shiraishi Y, Maekawa S, Okuno Y, Kamura T, et al. Integrated molecular analysis of clear-cell renal cell carcinoma. Nat Genet. 2013;45:860-7.
30. Barbie DA, Tamayo P, Boehm JS, Kim SY, Moody SE, Dunn IF, et al. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature. 2009;462:108-12.
31. Chtanova T, Newton R, Liu SM, Weininger L, Young TR, Silva DG, et al. Identification of T cell-restricted genes, and signatures for different T cell responses, using a comprehensive collection of microarray datasets. J Immunol. 2005;175:7837-47.
32. Hyrcza MD, Kovacs C, Loutfy M, Halpenny R, Heisler L, Yang S, et al. Distinct transcriptional profiles in ex vivo CD4+ and CD8+ T cells are established early in human immunodeficiency virus type 1 infection and are characterized by a chronic interferon response as well as extensive transcriptional changes in CD8+ T cells. J Virol. 2007;81:3477-86.
33. Wendt K, Wilk E, Buyny S, Buer J, Schmidt RE, Jacobs R. Gene and protein characteristics reflect functional diversity of CD56dim and CD56bright NK cells. J Leukoc Biol. 2006;80:1529-41.
34. Wu Z, Irizarry RA, Gentleman R, Martinez-Murillo F, Spencer F. A model-based background adjustment for oligonucleotide expression arrays. J Am Stat Assoc. 2004;99:909-17.
35. Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics. 2007;8:118-27.
36. Carter SL, Cibulskis K, Helman E, McKenna A, Shen H, Zack T, et al. Absolute quantification of somatic DNA alterations in human cancer. Nat Biotechnol. 2012;30:413-21.
37. Brown SD, Raeburn LA, Holt RA. Profiling tissue-resident T cell repertoires by RNA sequencing. Genome Med. 2015;7:125.
38. Matsushita H, Vesely MD, Koboldt DC, Rickert CG, Uppaluri R, Magrini VJ, et al. Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting. Nature. 2012;482:400-4.
39. Mlecnik B, Bindea G, Angell HK, Maby P, Angelova M, Tougeron D, et al. Integrative analyses of colorectal cancer show immunoscore is a stronger predictor of patient survival than microsatellite instability. Immunity. 2016;44:698-711.
40. Dunn GP, Old LJ, Schreiber RD. The three Es of cancer immunoediting. Annu Rev Immunol. 2004;22:329-60.
41. Masiero M, Simões Filipa C, Han Hee D, Snell C, Peterkin T, Bridges E, et al. A core human primary tumor angiogenesis signature identifies the endothelial orphan receptor ELTD1 as a key regulator of angiogenesis. Cancer Cell. 2013;24:229-41.
42. Folkman J. Angiogenesis in cancer, vascular, rheumatoid and other disease. Nat Med. 1995;1:27-30.
43. Baldewijns MM, van Vlodrop IJH, Vermeulen PB, Soetekouw PMMB, van Engeland M, de Bruïne AP. VHL and HIF signalling in renal cell carcinogenesis. J Pathol. 2010;221:125-38.
44. da Huang W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4:44-57.
45. Zhu Q, Kim YH, Wang D, Oh SP, Luo K. SnoN facilitates ALK1-Smad1/5 signaling during embryonic angiogenesis. J Cell Biol. 2013;202:937-50.
46. Icli B, Wara AK, Moslehi J, Sun X, Plovie E, Cahill M, et al. MicroRNA-26a regulates pathological and physiological angiogenesis by targeting BMP/SMAD1 signaling. Circ Res. 2013;113:1231-41.
47. Sun L, Hui A-M, Su Q, Vortmeyer A, Kotliarov Y, Pastorino S, et al. Neuronal and glioma-derived stem cell factor induces angiogenesis within the brain. Cancer Cell. 2006;9:287-300.
48. Elmasri H, Ghelfi E, Yu C-W, Traphagen S, Cernadas M, Cao H, et al. Endothelial cell-fatty acid binding protein 4 promotes angiogenesis: role of stem cell factor/c-kit pathway. Angiogenesis. 2012;15:457-68.
49. Patruno R, Marech I, Zizzo N, Ammendola M, Nardulli P, Gadaleta C, et al. C-Kit expression, angiogenesis, and grading in canine mast cell tumour: a unique model to study C-Kit driven human malignancies. Biomed Res Int. 2014;2014:8.
50. Bindea G, Mlecnik B, Hackl H, Charoentong P, Tosolini M, Kirilovsky A, et al. ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics. 2009;25:1091-3.
51. Ren G, Zhao X, Wang Y, Zhang X, Chen X, Xu C, et al. CCR2-dependent recruitment of macrophages by tumor-educated mesenchymal stromal cells promotes tumor development and is mimicked by TNFα. Cell Stem Cell. 2012;11:812-24.
52. Kryczek I, Banerjee M, Cheng P, Vatan L, Szeliga W, Wei S, et al. Phenotype, distribution, generation, and functional and clinical relevance of Th17 cells in the human tumor environments. Blood. 2009;114:1141-9.
53. Li L, Yang C, Zhao Z, Xu B, Zheng M, Zhang C, et al. Skewed T-helper (Th)1/2- and Th17/T regulatorycell balances in patients with renal cell carcinoma. Mol Med Rep. 2015;11:947-53.
54. Tatsumi T, Kierstead LS, Ranieri E, Gesualdo L, Schena FP, Finke JH, et al. Disease-associated bias in T helper type 1 (Th1)/Th2 CD4(+) T cell responses against MAGE-6 in HLA-DRB10401(+) patients with renal cell carcinoma or melanoma. J Exp Med. 2002;196:619-28.
55. Zou W, Restifo NP. T(H)17 cells in tumour immunity and immunotherapy. Nat Rev Immunol. 2010;10:248-56.
56. Brannon AR, Reddy A, Seiler M, Arreola A, Moore DT, Pruthi RS, et al. Molecular stratification of clear cell renal cell carcinoma by consensus clustering reveals distinct subtypes and survival patterns. Genes Cancer. 2010;1:152-63.
57. Gerlinger M, Horswell S, Larkin J, Rowan AJ, Salm MP, Varela I, et al. Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing. Nat Genet. 2014;46:225-33.
58. Gerlinger M, Quezada SA, Peggs KS, Furness AJ, Fisher R, Marafioti T, et al. Ultra-deep T cell receptor sequencing reveals the complexity and intratumour heterogeneity of T cell clones in renal cell carcinomas. J Pathol. 2013;231:424-32.
59. McGranahan N, Furness AJ, Rosenthal R, Ramskov S, Lyngaa R, Saini SK, et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science. 2016;351:1463-9.
60. Miller CA, White BS, Dees ND, Griffith M, Welch JS, Griffith OL, et al. SciClone: inferring clonal architecture and tracking the spatial and temporal patterns of tumor evolution. PLoS Comput Biol. 2014;10:e1003665.
61. DuPage M, Mazumdar C, Schmidt LM, Cheung AF, Jacks T. Expression of tumour-specific antigens underlies cancer immunoediting. Nature. 2012;482:405-9.
62. Szolek A, Schubert B, Mohr C, Sturm M, Feldhahn M, Kohlbacher O. OptiType: precision HLA typing from next-generation sequencing data. Bioinformatics. 2014;30:3310-6.
63. Curiel TJ, Cheng P, Mottram P, Alvarez X, Moons L, Evdemon-Hogan M, et al. Dendritic cell subsets differentially regulate angiogenesis in human ovarian cancer. Cancer Res. 2004;64:5535-8.
64. Chen DS, Mellman I. Oncology meets immunology: the cancer-immunity cycle. Immunity. 2013;39:1-10.
65. Beuselinck B, Job S, Becht E, Karadimou A, Verkarre V, Couchy G, et al. Molecular subtypes of clear cell renal cell carcinoma are associated with sunitinib response in the metastatic setting. Clin Cancer Res. 2015;21:1329-39.
66. Webster WS, Lohse CM, Thompson RH, Dong H, Frigola X, Dicks DL, et al. Mononuclear cell infiltration in clear-cell renal cell carcinoma independently predicts patient survival. Cancer. 2006;107:46-53.
67. Cline MS, Craft B, Swatloski T, Goldman M, Ma S, Haussler D, et al. Exploring TCGA Pan-Cancer Data at the UCSC Cancer Genomics Browser. Sci Rep. 2013;3:2652.
68. Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009;25:1105-11.
69. DeLuca DS, Levin JZ, Sivachenko A, Fennell T, Nazaire MD, Williams C, et al. RNA-SeQC: RNA-seq metrics for quality control and process optimization. Bioinformatics. 2012;28:1530-2.
70. Gao J, Aksoy BA, Dogrusoz U, Dresdner G, Gross B, Sumer SO, et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal. 2013;6:pl1.
71. Hanzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinformatics. 2013;14:7.
72. Wu C, Orozco C, Boyer J, Leglise M, Goodale J, Batalov S, et al. BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources. Genome Biol. 2009;10:R130.
73. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15-21.
74. Engstrom PG, Steijger T, Sipos B, Grant GR, Kahles A, Ratsch G, et al. Systematic evaluation of spliced alignment programs for RNA-seq data. Nat Methods. 2013;10:1185-91.
75. Anders S, Pyl PT, Huber W. HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31:166-9.
76. Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11:R106.
77. Mason DY, Cordell JL, Gaulard P, Tse AG, Brown MH. Immunohistological detection of human cytotoxic/suppressor T cells using antibodies to a CD8 peptide sequence. J Clin Pathol. 1992;45:1084-8.
78. Schol DJ, Mooi WJ, van der Gugten AA, Wagenaar SS, Hilgers J. Monoclonal antibody 123C3, identifying small cell carcinoma phenotype in lung tumours, recognizes mainly, but not exclusively, endocrine and neuron-supporting normal tissues. Int J Cancer Suppl. 1988;2:34-40.
79. Tan B, Anaka M, Deb S, Freyer C, Ebert LM, Chueh AC, et al. FOXP3 over-expression inhibits melanoma tumorigenesis via effects on proliferation and apoptosis. Oncotarget. 2014;5:264-76.
80. Hakimi AA, Reznik E, Lee CH, Creighton CJ, Brannon AR, Luna A, et al. An integrated metabolic atlas of clear cell renal cell carcinoma. Cancer Cell. 2016;29:104-16.
81. Reinius LE, Acevedo N, Joerink M, Pershagen G, Dahlen SE, Greco D, et al. Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility. PLoS One. 2012;7:e41361.
82. Durinck S, Spellman PT, Birney E, Huber W. Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Nat Protoc. 2009;4:1184-91.
83. Weese D, Holtgrewe M, Reinert K. RazerS 3: faster, fully sensitive read mapping. Bioinformatics. 2012;28:2592-9.
84. Hoof I, Peters B, Sidney J, Pedersen LE, Sette A, Lund O, et al. NetMHCpan, a method for MHC class I binding prediction beyond humans. Immunogenetics. 2009;61:1-13.
85. Svetnik V, Liaw A, Tong C, Culberson JC, Sheridan RP, Feuston BP. Random forest: a classification and regression tool for compound classification and QSAR modeling. J Chem Inf Comput Sci. 2003;43:1947-58.