Heterogeneity of the tumor immune microenvironment and clinical interventions
Zheng Jin, Qin Zhou, Jia-Nan Cheng, Qingzhu Jia, Bo Zhu
Heterogeneity of the tumor immune microenvironment and clinical interventions
The tumor immune microenvironment (TIME) is broadly composed of various immune cells, and its heterogeneity is characterized by both immune cells and stromal cells. During the course of tumor formation and progression and anti-tumor treatment, the composition of the TIME becomes heterogeneous. Such immunological heterogeneity is not only present between populations but also exists on temporal and spatial scales. Owing to the existence of TIME, clinical outcomes can differ when a similar treatment strategy is provided to patients. Therefore, a comprehensive assessment of TIME heterogeneity is essential for developing precise and effective therapies. Facilitated by advanced technologies, it is possible to understand the complexity and diversity of the TIME and its influence on therapy responses. In this review, we discuss the potential reasons for TIME heterogeneity and the current approaches used to explore it. We also summarize clinical intervention strategies based on associated mechanisms or targets to control immunological heterogeneity.
tumor immune heterogeneity / clinical intervention / tumor microenvironment
[1] |
Binnewies M, Roberts EW, Kersten K, Chan V, Fearon DF, Merad M, Coussens LM, Gabrilovich DI, Ostrand-Rosenberg S, Hedrick CC, Vonderheide RH, Pittet MJ, Jain RK, Zou W, Howcroft TK, Woodhouse EC, Weinberg RA, Krummel MF. Understanding the tumor immune microenvironment (TIME) for effective therapy. Nat Med 2018; 24(5): 541–550
CrossRef
Google scholar
|
[2] |
Galli F, Aguilera JV, Palermo B, Markovic SN, Nisticò P, Signore A. Relevance of immune cell and tumor microenvironment imaging in the new era of immunotherapy. J Exp Clin Cancer Res 2020; 39(1): 89
CrossRef
Google scholar
|
[3] |
Yarchoan M, Hopkins A, Jaffee EM. Tumor mutational burden and response rate to PD-1 inhibition. N Engl J Med 2017; 377(25): 2500–2501
CrossRef
Google scholar
|
[4] |
Yarchoan M, Albacker LA, Hopkins AC, Montesion M, Murugesan K, Vithayathil TT, Zaidi N, Azad NS, Laheru DA, Frampton GM, Jaffee EM. PD-L1 expression and tumor mutational burden are independent biomarkers in most cancers. JCI Insight 2019; 4(6): e126908
CrossRef
Google scholar
|
[5] |
Ren X, Zhang L, Zhang Y, Li Z, Siemers N, Zhang Z. Insights gained from single-cell analysis of immune cells in the tumor microenvironment. Annu Rev Immunol 2021; 39(1): 583–609
CrossRef
Google scholar
|
[6] |
Gajewski TF, Schreiber H, Fu YX. Innate and adaptive immune cells in the tumor microenvironment. Nat Immunol 2013; 14(10): 1014–1022
CrossRef
Google scholar
|
[7] |
Jia Q, Chu H, Jin Z, Long H, Zhu B. High-throughput single-сell sequencing in cancer research. Signal Transduct Target Ther 2022; 7(1): 145
CrossRef
Google scholar
|
[8] |
Dagogo-Jack I, Shaw AT. Tumour heterogeneity and resistance to cancer therapies. Nat Rev Clin Oncol 2018; 15(2): 81–94
CrossRef
Google scholar
|
[9] |
Isomoto K, Haratani K, Hayashi H, Shimizu S, Tomida S, Niwa T, Yokoyama T, Fukuda Y, Chiba Y, Kato R, Tanizaki J, Tanaka K, Takeda M, Ogura T, Ishida T, Ito A, Nakagawa K. Impact of EGFR-TKI treatment on the tumor immune microenvironment in EGFR mutation-positive non-small cell lung cancer. Clin Cancer Res 2020; 26(8): 2037–2046
CrossRef
Google scholar
|
[10] |
Wang M, Zhao J, Zhang L, Wei F, Lian Y, Wu Y, Gong Z, Zhang S, Zhou J, Cao K, Li X, Xiong W, Li G, Zeng Z, Guo C. Role of tumor microenvironment in tumorigenesis. J Cancer 2017; 8(5): 761–773
CrossRef
Google scholar
|
[11] |
Lamplugh Z, Fan Y. Vascular microenvironment, tumor immunity and immunotherapy. Front Immunol 2021; 12: 811485
CrossRef
Google scholar
|
[12] |
Shah SP, Roth A, Goya R, Oloumi A, Ha G, Zhao Y, Turashvili G, Ding J, Tse K, Haffari G, Bashashati A, Prentice LM, Khattra J, Burleigh A, Yap D, Bernard V, McPherson A, Shumansky K, Crisan A, Giuliany R, Heravi-Moussavi A, Rosner J, Lai D, Birol I, Varhol R, Tam A, Dhalla N, Zeng T, Ma K, Chan SK, Griffith M, Moradian A, Cheng SW, Morin GB, Watson P, Gelmon K, Chia S, Chin SF, Curtis C, Rueda OM, Pharoah PD, Damaraju S, Mackey J, Hoon K, Harkins T, Tadigotla V, Sigaroudinia M, Gascard P, Tlsty T, Costello JF, Meyer IM, Eaves CJ, Wasserman WW, Jones S, Huntsman D, Hirst M, Caldas C, Marra MA, Aparicio S. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 2012; 486(7403): 395–399
CrossRef
Google scholar
|
[13] |
Shibata D. Cancer. Heterogeneity and tumor history. Science 2012; 336(6079): 304–305
CrossRef
Google scholar
|
[14] |
Buob D, Fauvel H, Buisine MP, Truant S, Mariette C, Porchet N, Wacrenier A, Copin MC, Leteurtre E. The complex intratumoral heterogeneity of colon cancer highlighted by laser microdissection. Dig Dis Sci 2012; 57(5): 1271–1280
CrossRef
Google scholar
|
[15] |
Gerlinger M, Rowan AJ, Horswell S, Math M, Larkin J, Endesfelder D, Gronroos E, Martinez P, Matthews N, Stewart A, Tarpey P, Varela I, Phillimore B, Begum S, McDonald NQ, Butler A, Jones D, Raine K, Latimer C, Santos CR, Nohadani M, Eklund AC, Spencer-Dene B, Clark G, Pickering L, Stamp G, Gore M, Szallasi Z, Downward J, Futreal PA, Swanton C. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 2012; 366(10): 883–892
CrossRef
Google scholar
|
[16] |
McGranahan N, Swanton C. Clonal heterogeneity and tumor evolution: past, present, and the future. Cell 2017; 168(4): 613–628
CrossRef
Google scholar
|
[17] |
Burrell RA, McGranahan N, Bartek J, Swanton C. The causes and consequences of genetic heterogeneity in cancer evolution. Nature 2013; 501(7467): 338–345
CrossRef
Google scholar
|
[18] |
Jia Q, Wang A, Yuan Y, Zhu B, Long H. Heterogeneity of the tumor immune microenvironment and its clinical relevance. Exp Hematol Oncol 2022; 11(1): 24
CrossRef
Google scholar
|
[19] |
Shastry BS. SNPs: impact on gene function and phenotype. Methods Mol Biol 2009; 578: 3–22
CrossRef
Google scholar
|
[20] |
Lifsted T, Le Voyer T, Williams M, Muller W, Klein-Szanto A, Buetow KH, Hunter KW. Identification of inbred mouse strains harboring genetic modifiers of mammary tumor age of onset and metastatic progression. Int J Cancer 1998; 77(4): 640–644
CrossRef
Google scholar
|
[21] |
Hsieh SM, Lintell NA, Hunter KW. Germline polymorphisms are potential metastasis risk and prognosis markers in breast cancer. Breast Dis 2007; 26(1): 157–162
CrossRef
Google scholar
|
[22] |
Hsieh SM, Look MP, Sieuwerts AM, Foekens JA, Hunter KW. Distinct inherited metastasis susceptibility exists for different breast cancer subtypes: a prognosis study. Breast Cancer Res 2009; 11(5): R75
CrossRef
Google scholar
|
[23] |
Peng J, Sun BF, Chen CY, Zhou JY, Chen YS, Chen H, Liu L, Huang D, Jiang J, Cui GS, Yang Y, Wang W, Guo D, Dai M, Guo J, Zhang T, Liao Q, Liu Y, Zhao YL, Han DL, Zhao Y, Yang YG, Wu W. Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma. Cell Res 2019; 29(9): 725–738
CrossRef
Google scholar
|
[24] |
Rosenthal R, Cadieux EL, Salgado R, Bakir MA, Moore DA, Hiley CT, Lund T, Tanić M, Reading JL, Joshi K, Henry JY, Ghorani E, Wilson GA, Birkbak NJ, Jamal-Hanjani M, Veeriah S, Szallasi Z, Loi S, Hellmann MD, Feber A, Chain B, Herrero J, Quezada SA, Demeulemeester J, Van Loo P, Beck S, McGranahan N, Swanton C; TRACERx consortium. Neoantigen-directed immune escape in lung cancer evolution. Nature 2019; 567(7749): 479–485
CrossRef
Google scholar
|
[25] |
Aryee MJ, Liu W, Engelmann JC, Nuhn P, Gurel M, Haffner MC, Esopi D, Irizarry RA, Getzenberg RH, Nelson WG, Luo J, Xu J, Isaacs WB, Bova GS, Yegnasubramanian S. DNA methylation alterations exhibit intraindividual stability and interindividual heterogeneity in prostate cancer metastases. Sci Transl Med 2013; 5(169): 169ra10
CrossRef
Google scholar
|
[26] |
Mazor T, Pankov A, Johnson BE, Hong C, Hamilton EG, Bell RJA, Smirnov IV, Reis GF, Phillips JJ, Barnes MJ, Idbaih A, Alentorn A, Kloezeman JJ, Lamfers MLM, Bollen AW, Taylor BS, Molinaro AM, Olshen AB, Chang SM, Song JS, Costello JF. DNA methylation and somatic mutations converge on the cell cycle and define similar evolutionary histories in brain tumors. Cancer Cell 2015; 28(3): 307–317
CrossRef
Google scholar
|
[27] |
Hao JJ, Lin DC, Dinh HQ, Mayakonda A, Jiang YY, Chang C, Jiang Y, Lu CC, Shi ZZ, Xu X, Zhang Y, Cai Y, Wang JW, Zhan QM, Wei WQ, Berman BP, Wang MR, Koeffler HP. Spatial intratumoral heterogeneity and temporal clonal evolution in esophageal squamous cell carcinoma. Nat Genet 2016; 48(12): 1500–1507
CrossRef
Google scholar
|
[28] |
Flavahan WA, Gaskell E, Bernstein BE. Epigenetic plasticity and the hallmarks of cancer. Science 2017; 357(6348): eaal2380
CrossRef
Google scholar
|
[29] |
Deshwar AG, Vembu S, Yung CK, Jang GH, Stein L, Morris Q. PhyloWGS: reconstructing subclonal composition and evolution from whole-genome sequencing of tumors. Genome Biol 2015; 16(1): 35
CrossRef
Google scholar
|
[30] |
Patten DK, Corleone G, Győrffy B, Perone Y, Slaven N, Barozzi I, Erdős E, Saiakhova A, Goddard K, Vingiani A, Shousha S, Pongor LS, Hadjiminas DJ, Schiavon G, Barry P, Palmieri C, Coombes RC, Scacheri P, Pruneri G, Magnani L. Enhancer mapping uncovers phenotypic heterogeneity and evolution in patients with luminal breast cancer. Nat Med 2018; 24(9): 1469–1480
CrossRef
Google scholar
|
[31] |
Yang Z, Zhang B, Li D, Lv M, Huang C, Shen GX, Huang B. Mast cells mobilize myeloid-derived suppressor cells and Treg cells in tumor microenvironment via IL-17 pathway in murine hepatocarcinoma model. PLoS One 2010; 5(1): e8922
CrossRef
Google scholar
|
[32] |
Ostrand-Rosenberg S, Sinha P, Beury DW, Clements VK. Cross-talk between myeloid-derived suppressor cells (MDSC), macrophages, and dendritic cells enhances tumor-induced immune suppression. Semin Cancer Biol 2012; 22(4): 275–281
CrossRef
Google scholar
|
[33] |
Yu JL, Rak JW, Carmeliet P, Nagy A, Kerbel RS, Coomber BL. Heterogeneous vascular dependence of tumor cell populations. Am J Pathol 2001; 158(4): 1325–1334
CrossRef
Google scholar
|
[34] |
Ullrich E, Bonmort M, Mignot G, Kroemer G, Zitvogel L. Tumor stress, cell death and the ensuing immune response. Cell Death Differ 2008; 15(1): 21–28
CrossRef
Google scholar
|
[35] |
Bian Y, Li W, Kremer DM, Sajjakulnukit P, Li S, Crespo J, Nwosu ZC, Zhang L, Czerwonka A, Pawłowska A, Xia H, Li J, Liao P, Yu J, Vatan L, Szeliga W, Wei S, Grove S, Liu JR, McLean K, Cieslik M, Chinnaiyan AM, Zgodziński W, Wallner G, Wertel I, Okła K, Kryczek I, Lyssiotis CA, Zou W. Cancer SLC43A2 alters T cell methionine metabolism and histone methylation. Nature 2020; 585(7824): 277–282
CrossRef
Google scholar
|
[36] |
Yost KE, Satpathy AT, Wells DK, Qi Y, Wang C, Kageyama R, McNamara KL, Granja JM, Sarin KY, Brown RA, Gupta RK, Curtis C, Bucktrout SL, Davis MM, Chang ALS, Chang HY. Clonal replacement of tumor-specific T cells following PD-1 blockade. Nat Med 2019; 25(8): 1251–1259
CrossRef
Google scholar
|
[37] |
Peng L, Xiong Y, Wang R, Xiang L, Zhou H, Gu H. Identification of a subpopulation of long-term tumor-initiating cells in colon cancer. Biosci Rep 2020; 40(8): BSR20200437
CrossRef
Google scholar
|
[38] |
Hüsemann Y, Geigl JB, Schubert F, Musiani P, Meyer M, Burghart E, Forni G, Eils R, Fehm T, Riethmüller G, Klein CA. Systemic spread is an early step in breast cancer. Cancer Cell 2008; 13(1): 58–68
CrossRef
Google scholar
|
[39] |
Bernard V, Semaan A, Huang J, San Lucas FA, Mulu FC, Stephens BM, Guerrero PA, Huang Y, Zhao J, Kamyabi N, Sen S, Scheet PA, Taniguchi CM, Kim MP, Tzeng CW, Katz MH, Singhi AD, Maitra A, Alvarez HA. Single-cell transcriptomics of pancreatic cancer precursors demonstrates epithelial and microenvironmental heterogeneity as an early event in neoplastic progression. Clin Cancer Res 2019; 25(7): 2194–2205
CrossRef
Google scholar
|
[40] |
Wu X, Northcott PA, Dubuc A, Dupuy AJ, Shih DJ, Witt H, Croul S, Bouffet E, Fults DW, Eberhart CG, Garzia L, Van Meter T, Zagzag D, Jabado N, Schwartzentruber J, Majewski J, Scheetz TE, Pfister SM, Korshunov A, Li XN, Scherer SW, Cho YJ, Akagi K, MacDonald TJ, Koster J, McCabe MG, Sarver AL, Collins VP, Weiss WA, Largaespada DA, Collier LS, Taylor MD. Clonal selection drives genetic divergence of metastatic medulloblastoma. Nature 2012; 482(7386): 529–533
CrossRef
Google scholar
|
[41] |
Yachida S, Jones S, Bozic I, Antal T, Leary R, Fu B, Kamiyama M, Hruban RH, Eshleman JR, Nowak MA, Velculescu VE, Kinzler KW, Vogelstein B, Iacobuzio-Donahue CA. Distant metastasis occurs late during the genetic evolution of pancreatic cancer. Nature 2010; 467(7319): 1114–1117
CrossRef
Google scholar
|
[42] |
Liu W, Laitinen S, Khan S, Vihinen M, Kowalski J, Yu G, Chen L, Ewing CM, Eisenberger MA, Carducci MA, Nelson WG, Yegnasubramanian S, Luo J, Wang Y, Xu J, Isaacs WB, Visakorpi T, Bova GS. Copy number analysis indicates monoclonal origin of lethal metastatic prostate cancer. Nat Med 2009; 15(5): 559–565
CrossRef
Google scholar
|
[43] |
Zhang L, Yu X, Zheng L, Zhang Y, Li Y, Fang Q, Gao R, Kang B, Zhang Q, Huang JY, Konno H, Guo X, Ye Y, Gao S, Wang S, Hu X, Ren X, Shen Z, Ouyang W, Zhang Z. Lineage tracking reveals dynamic relationships of T cells in colorectal cancer. Nature 2018; 564(7735): 268–272
CrossRef
Google scholar
|
[44] |
Izar B, Tirosh I, Stover EH, Wakiro I, Cuoco MS, Alter I, Rodman C, Leeson R, Su MJ, Shah P, Iwanicki M, Walker SR, Kanodia A, Melms JC, Mei S, Lin JR, Porter CBM, Slyper M, Waldman J, Jerby-Arnon L, Ashenberg O, Brinker TJ, Mills C, Rogava M, Vigneau S, Sorger PK, Garraway LA, Konstantinopoulos PA, Liu JF, Matulonis U, Johnson BE, Rozenblatt-Rosen O, Rotem A, Regev A. A single-cell landscape of high-grade serous ovarian cancer. Nat Med 2020; 26(8): 1271–1279
CrossRef
Google scholar
|
[45] |
Winterhoff B, Talukdar S, Chang Z, Wang J, Starr TK. Single-cell sequencing in ovarian cancer: a new frontier in precision medicine. Curr Opin Obstet Gynecol 2019; 31(1): 49–55
CrossRef
Google scholar
|
[46] |
Asselin MC, O’Connor JP, Boellaard R, Thacker NA, Jackson A. Quantifying heterogeneity in human tumours using MRI and PET. Eur J Cancer 2012; 48(4): 447–455
CrossRef
Google scholar
|
[47] |
Berglund E, Maaskola J, Schultz N, Friedrich S, Marklund M, Bergenstråhle J, Tarish F, Tanoglidi A, Vickovic S, Larsson L, Salmén F, Ogris C, Wallenborg K, Lagergren J, Ståhl P, Sonnhammer E, Helleday T, Lundeberg J. Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity. Nat Commun 2018; 9(1): 2419
CrossRef
Google scholar
|
[48] |
Moncada R, Barkley D, Wagner F, Chiodin M, Devlin JC, Baron M, Hajdu CH, Simeone DM, Yanai I. Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas. Nat Biotechnol 2020; 38(3): 333–342
CrossRef
Google scholar
|
[49] |
Brannon AR, Vakiani E, Sylvester BE, Scott SN, McDermott G, Shah RH, Kania K, Viale A, Oschwald DM, Vacic V, Emde AK, Cercek A, Yaeger R, Kemeny NE, Saltz LB, Shia J, D’Angelica MI, Weiser MR, Solit DB, Berger MF. Comparative sequencing analysis reveals high genomic concordance between matched primary and metastatic colorectal cancer lesions. Genome Biol 2014; 15(8): 454
CrossRef
Google scholar
|
[50] |
Galon J, Costes A, Sanchez-Cabo F, Kirilovsky A, Mlecnik B, Lagorce-Pagès C, Tosolini M, Camus M, Berger A, Wind P, Zinzindohoué F, Bruneval P, Cugnenc PH, Trajanoski Z, Fridman WH, Pagès F. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science 2006; 313(5795): 1960–1964
CrossRef
Google scholar
|
[51] |
Ji AL, Rubin AJ, Thrane K, Jiang S, Reynolds DL, Meyers RM, Guo MG, George BM, Mollbrink A, Bergenstråhle J, Larsson L, Bai Y, Zhu B, Bhaduri A, Meyers JM, Rovira-Clavé X, Hollmig ST, Aasi SZ, Nolan GP, Lundeberg J, Khavari PA. Multimodal analysis of composition and spatial architecture in human squamous cell carcinoma. Cell 2020; 182(2): 497–514.e22
CrossRef
Google scholar
|
[52] |
Zhang L, Zhao Y, Dai Y, Cheng JN, Gong Z, Feng Y, Sun C, Jia Q, Zhu B. Immune landscape of colorectal cancer tumor microenvironment from different primary tumor location. Front Immunol 2018; 9: 1578
CrossRef
Google scholar
|
[53] |
Barbie DA, Tamayo P, Boehm JS, Kim SY, Moody SE, Dunn IF, Schinzel AC, Sandy P, Meylan E, Scholl C, Fröhling S, Chan EM, Sos ML, Michel K, Mermel C, Silver SJ, Weir BA, Reiling JH, Sheng Q, Gupta PB, Wadlow RC, Le H, Hoersch S, Wittner BS, Ramaswamy S, Livingston DM, Sabatini DM, Meyerson M, Thomas RK, Lander ES, Mesirov JP, Root DE, Gilliland DG, Jacks T, Hahn WC. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature 2009; 462(7269): 108–112
CrossRef
Google scholar
|
[54] |
Angelova M, Charoentong P, Hackl H, Fischer ML, Snajder R, Krogsdam AM, Waldner MJ, Bindea G, Mlecnik B, Galon J, Trajanoski Z. Characterization of the immunophenotypes and antigenomes of colorectal cancers reveals distinct tumor escape mechanisms and novel targets for immunotherapy. Genome Biol 2015; 16(1): 64
CrossRef
Google scholar
|
[55] |
Govindan R, Ding L, Griffith M, Subramanian J, Dees ND, Kanchi KL, Maher CA, Fulton R, Fulton L, Wallis J, Chen K, Walker J, McDonald S, Bose R, Ornitz D, Xiong D, You M, Dooling DJ, Watson M, Mardis ER, Wilson RK. Genomic landscape of non-small cell lung cancer in smokers and never-smokers. Cell 2012; 150(6): 1121–1134
CrossRef
Google scholar
|
[56] |
Ogino S, Nowak JA, Hamada T, Phipps AI, Peters U, Milner DA Jr, Giovannucci EL, Nishihara R, Giannakis M, Garrett WS, Song M. Integrative analysis of exogenous, endogenous, tumour and immune factors for precision medicine. Gut 2018; 67(6): 1168–1180
CrossRef
Google scholar
|
[57] |
Inamura K, Hamada T, Bullman S, Ugai T, Yachida S, Ogino S. Cancer as microenvironmental, systemic and environmental diseases: opportunity for transdisciplinary microbiomics science. Gut 2022; 71: 2107–2122
CrossRef
Google scholar
|
[58] |
Cao Y, Nishihara R, Qian ZR, Song M, Mima K, Inamura K, Nowak JA, Drew DA, Lochhead P, Nosho K, Morikawa T, Zhang X, Wu K, Wang M, Garrett WS, Giovannucci EL, Fuchs CS, Chan AT, Ogino S. Regular aspirin use associates with lower risk of colorectal cancers with low numbers of tumor-infiltrating lymphocytes. Gastroenterology 2016; 151(5): 879–892.e4
CrossRef
Google scholar
|
[59] |
Hanyuda A, Ogino S, Qian ZR, Nishihara R, Song M, Mima K, Inamura K, Masugi Y, Wu K, Meyerhardt JA, Chan AT, Fuchs CS, Giovannucci EL, Cao Y. Body mass index and risk of colorectal cancer according to tumor lymphocytic infiltrate. Int J Cancer 2016; 139(4): 854–868
CrossRef
Google scholar
|
[60] |
Ogino S, Nowak JA, Hamada T, Milner DA Jr, Nishihara R. Insights into pathogenic interactions among environment, host, and tumor at the crossroads of molecular pathology and epidemiology. Annu Rev Pathol 2019; 14(1): 83–103
CrossRef
Google scholar
|
[61] |
Akimoto N, Ugai T, Zhong R, Hamada T, Fujiyoshi K, Giannakis M, Wu K, Cao Y, Ng K, Ogino S. Rising incidence of early-onset colorectal cancer—a call to action. Nat Rev Clin Oncol 2021; 18(4): 230–243
CrossRef
Google scholar
|
[62] |
Ogino S, Chan AT, Fuchs CS, Giovannucci E. Molecular pathological epidemiology of colorectal neoplasia: an emerging transdisciplinary and interdisciplinary field. Gut 2011; 60(3): 397–411
CrossRef
Google scholar
|
[63] |
Ugai T, Liu L, Tabung FK, Hamada T, Langworthy BW, Akimoto N, Haruki K, Takashima Y, Okadome K, Kawamura H, Zhao M, Kahaki SMM, Glickman JN, Lennerz JK, Zhang X, Chan AT, Fuchs CS, Song M, Wang M, Yu KH, Giannakis M, Nowak JA, Meyerhardt JA, Wu K, Ogino S, Giovannucci EL. Prognostic role of inflammatory diets in colorectal cancer overall and in strata of tumor-infiltrating lymphocyte levels. Clin Transl Med 2022; 12(11): e1114
CrossRef
Google scholar
|
[64] |
Wang F, Ugai T, Haruki K, Wan Y, Akimoto N, Arima K, Zhong R, Twombly TS, Wu K, Yin K, Chan AT, Giannakis M, Nowak JA, Meyerhardt JA, Liang L, Song M, Smith-Warner SA, Zhang X, Giovannucci EL, Willett WC, Ogino S. Healthy and unhealthy plant-based diets in relation to the incidence of colorectal cancer overall and by molecular subtypes. Clin Transl Med 2022; 12(8): e893
CrossRef
Google scholar
|
[65] |
Lee B, Lee J, Woo MY, Lee MJ, Shin HJ, Kim K, Park S. Modulation of the gut microbiota alters the tumour-suppressive efficacy of Tim-3 pathway blockade in a bacterial species- and host factor-dependent manner. Microorganisms 2020; 8(9): 1395
CrossRef
Google scholar
|
[66] |
Baruch EN, Youngster I, Ben-Betzalel G, Ortenberg R, Lahat A, Katz L, Adler K, Dick-Necula D, Raskin S, Bloch N, Rotin D, Anafi L, Avivi C, Melnichenko J, Steinberg-Silman Y, Mamtani R, Harati H, Asher N, Shapira-Frommer R, Brosh-Nissimov T, Eshet Y, Ben-Simon S, Ziv O, Khan MAW, Amit M, Ajami NJ, Barshack I, Schachter J, Wargo JA, Koren O, Markel G, Boursi B. Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients. Science 2021; 371(6529): 602–609
CrossRef
Google scholar
|
[67] |
Davar D, Dzutsev AK, McCulloch JA, Rodrigues RR, Chauvin JM, Morrison RM, Deblasio RN, Menna C, Ding Q, Pagliano O, Zidi B, Zhang S, Badger JH, Vetizou M, Cole AM, Fernandes MR, Prescott S, Costa RGF, Balaji AK, Morgun A, Vujkovic-Cvijin I, Wang H, Borhani AA, Schwartz MB, Dubner HM, Ernst SJ, Rose A, Najjar YG, Belkaid Y, Kirkwood JM, Trinchieri G, Zarour HM. Fecal microbiota transplant overcomes resistance to anti-PD-1 therapy in melanoma patients. Science 2021; 371(6529): 595–602
CrossRef
Google scholar
|
[68] |
Cheung AH, Chow C, To KF. Latest development of liquid biopsy. J Thorac Dis 2018; 10(S14 Suppl 14): S1645–S1651
CrossRef
Google scholar
|
[69] |
Giannopoulou L, Zavridou M, Kasimir-Bauer S, Lianidou ES. Liquid biopsy in ovarian cancer: the potential of circulating miRNAs and exosomes. Transl Res 2019; 205: 77–91
CrossRef
Google scholar
|
[70] |
Crowley E, Di Nicolantonio F, Loupakis F, Bardelli A. Liquid biopsy: monitoring cancer-genetics in the blood. Nat Rev Clin Oncol 2013; 10(8): 472–484
CrossRef
Google scholar
|
[71] |
Chan HT, Nagayama S, Otaki M, Chin YM, Fukunaga Y, Ueno M, Nakamura Y, Low SK. Tumor-informed or tumor-agnostic circulating tumor DNA as a biomarker for risk of recurrence in resected colorectal cancer patients. Front Oncol 2023; 12: 1055968
CrossRef
Google scholar
|
[72] |
Liu AP, Northcott PA, Robinson GW, Gajjar A. Circulating tumor DNA profiling for childhood brain tumors: technical challenges and evidence for utility. Lab Invest 2022; 102(2): 134–142
CrossRef
Google scholar
|
[73] |
Pantel K, Alix-Panabières C. Real-time liquid biopsy in cancer patients: fact or fiction?. Cancer Res 2013; 73(21): 6384–6388
CrossRef
Google scholar
|
[74] |
Elazezy M, Joosse SA. Techniques of using circulating tumor DNA as a liquid biopsy component in cancer management. Comput Struct Biotechnol J 2018; 16: 370–378
CrossRef
Google scholar
|
[75] |
Paweletz CP, Sacher AG, Raymond CK, Alden RS, O’Connell A, Mach SL, Kuang Y, Gandhi L, Kirschmeier P, English JM, Lim LP, Jänne PA, Oxnard GR. Bias-corrected targeted next-generation sequencing for rapid, multiplexed detection of actionable alterations in cell-free DNA from advanced lung cancer patients. Clin Cancer Res 2016; 22(4): 915–922
CrossRef
Google scholar
|
[76] |
Rodríguez J, Avila J, Rolfo C, Ruíz-Patiño A, Russo A, Ricaurte L, Ordóñez-Reyes C, Arrieta O, Zatarain-Barrón ZL, Recondo G, Cardona AF. When tissue is an issue the liquid biopsy is nonissue: a review. Oncol Ther 2021; 9(1): 89–110
CrossRef
Google scholar
|
[77] |
Wong SQ, Fellowes A, Doig K, Ellul J, Bosma TJ, Irwin D, Vedururu R, Tan AY, Weiss J, Chan KS, Lucas M, Thomas DM, Dobrovic A, Parisot JP, Fox SB. Assessing the clinical value of targeted massively parallel sequencing in a longitudinal, prospective population-based study of cancer patients. Br J Cancer 2015; 112(8): 1411–1420
CrossRef
Google scholar
|
[78] |
Dang DK, Park BH. Circulating tumor DNA: current challenges for clinical utility. J Clin Invest 2022; 132(12): e154941
CrossRef
Google scholar
|
[79] |
Uchida J, Kato K, Kukita Y, Kumagai T, Nishino K, Daga H, Nagatomo I, Inoue T, Kimura M, Oba S, Ito Y, Takeda K, Imamura F. Diagnostic accuracy of noninvasive genotyping of EGFR in lung cancer patients by deep sequencing of plasma cell-free DNA. Clin Chem 2015; 61(9): 1191–1196
CrossRef
Google scholar
|
[80] |
Alix-Panabières C, Pantel K. Liquid biopsy: from discovery to clinical application. Cancer Discov 2021; 11(4): 858–873
CrossRef
Google scholar
|
[81] |
Alix-Panabières C, Pantel K. Clinical applications of circulating tumor cells and circulating tumor dna as liquid biopsy. Cancer Discov 2016; 6(5): 479–491
CrossRef
Google scholar
|
[82] |
Jia Q, Chiu L, Wu S, Bai J, Peng L, Zheng L, Zang R, Li X, Yuan B, Gao Y, Wu D, Li X, Wu L, Sun J, He J, Robinson BWS, Zhu B. Tracking neoantigens by personalized circulating tumor DNA sequencing during checkpoint blockade immunotherapy in non-small cell lung cancer. Adv Sci (Weinh) 2020; 7(9): 1903410
CrossRef
Google scholar
|
[83] |
Chu D, Paoletti C, Gersch C, VanDenBerg DA, Zabransky DJ, Cochran RL, Wong HY, Toro PV, Cidado J, Croessmann S, Erlanger B, Cravero K, Kyker-Snowman K, Button B, Parsons HA, Dalton WB, Gillani R, Medford A, Aung K, Tokudome N, Chinnaiyan AM, Schott A, Robinson D, Jacks KS, Lauring J, Hurley PJ, Hayes DF, Rae JM, Park BH. ESR1 mutations in circulating plasma tumor DNA from metastatic breast cancer patients. Clin Cancer Res 2016; 22(4): 993–999
CrossRef
Google scholar
|
[84] |
Zhang Y, Yao Y, Xu Y, Li L, Gong Y, Zhang K, Zhang M, Guan Y, Chang L, Xia X, Li L, Jia S, Zeng Q. Pan-cancer circulating tumor DNA detection in over 10,000 Chinese patients. Nat Commun 2021; 12(1): 11
CrossRef
Google scholar
|
[85] |
Hedlund E, Deng Q. Single-cell RNA sequencing: technical advancements and biological applications. Mol Aspects Med 2018; 59: 36–46
CrossRef
Google scholar
|
[86] |
Luecken MD, Theis FJ. Current best practices in single-cell RNA-seq analysis: a tutorial. Mol Syst Biol 2019; 15(6): e8746
CrossRef
Google scholar
|
[87] |
Stubbington MJT, Lönnberg T, Proserpio V, Clare S, Speak AO, Dougan G, Teichmann SA. T cell fate and clonality inference from single-cell transcriptomes. Nat Methods 2016; 13(4): 329–332
CrossRef
Google scholar
|
[88] |
Klein AM, Mazutis L, Akartuna I, Tallapragada N, Veres A, Li V, Peshkin L, Weitz DA, Kirschner MW. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 2015; 161(5): 1187–1201
CrossRef
Google scholar
|
[89] |
Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, Tirosh I, Bialas AR, Kamitaki N, Martersteck EM, Trombetta JJ, Weitz DA, Sanes JR, Shalek AK, Regev A, McCarroll SA. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 2015; 161(5): 1202–1214
CrossRef
Google scholar
|
[90] |
Guo X, Zhang Y, Zheng L, Zheng C, Song J, Zhang Q, Kang B, Liu Z, Jin L, Xing R, Gao R, Zhang L, Dong M, Hu X, Ren X, Kirchhoff D, Roider HG, Yan T, Zhang Z. Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing. Nat Med 2018; 24(7): 978–985
CrossRef
Google scholar
|
[91] |
Zheng L, Qin S, Si W, Wang A, Xing B, Gao R, Ren X, Wang L, Wu X, Zhang J, Wu N, Zhang N, Zheng H, Ouyang H, Chen K, Bu Z, Hu X, Ji J, Zhang Z. Pan-cancer single-cell landscape of tumor-infiltrating T cells. Science 2021; 374(6574): abe6474
CrossRef
Google scholar
|
[92] |
Liu Y, Zhang Q, Xing B, Luo N, Gao R, Yu K, Hu X, Bu Z, Peng J, Ren X, Zhang Z. Immune phenotypic linkage between colorectal cancer and liver metastasis. Cancer Cell 2022; 40(4): 424–437.e5
CrossRef
Google scholar
|
[93] |
Xue R, Zhang Q, Cao Q, Kong R, Xiang X, Liu H, Feng M, Wang F, Cheng J, Li Z, Zhan Q, Deng M, Zhu J, Zhang Z, Zhang N. Liver tumour immune microenvironment subtypes and neutrophil heterogeneity. Nature 2022; 612(7938): 141–147
CrossRef
Google scholar
|
[94] |
Lewis SM, Asselin-Labat ML, Nguyen Q, Berthelet J, Tan X, Wimmer VC, Merino D, Rogers KL, Naik SH. Spatial omics and multiplexed imaging to explore cancer biology. Nat Methods 2021; 18(9): 997–1012
CrossRef
Google scholar
|
[95] |
Rao A, Barkley D, França GS, Yanai I. Exploring tissue architecture using spatial transcriptomics. Nature 2021; 596(7871): 211–220
CrossRef
Google scholar
|
[96] |
Ke R, Mignardi M, Pacureanu A, Svedlund J, Botling J, Wählby C, Nilsson M. In situ sequencing for RNA analysis in preserved tissue and cells. Nat Methods 2013; 10(9): 857–860
CrossRef
Google scholar
|
[97] |
Ståhl PL, Salmén F, Vickovic S, Lundmark A, Navarro JF, Magnusson J, Giacomello S, Asp M, Westholm JO, Huss M, Mollbrink A, Linnarsson S, Codeluppi S, Borg Å, Pontén F, Costea PI, Sahlén P, Mulder J, Bergmann O, Lundeberg J, Frisén J. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 2016; 353(6294): 78–82
CrossRef
Google scholar
|
[98] |
Rodriques SG, Stickels RR, Goeva A, Martin CA, Murray E, Vanderburg CR, Welch J, Chen LM, Chen F, Macosko EZ. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 2019; 363(6434): 1463–1467
CrossRef
Google scholar
|
[99] |
Wu SZ, Al-Eryani G, Roden DL, Junankar S, Harvey K, Andersson A, Thennavan A, Wang C, Torpy JR, Bartonicek N, Wang T, Larsson L, Kaczorowski D, Weisenfeld NI, Uytingco CR, Chew JG, Bent ZW, Chan CL, Gnanasambandapillai V, Dutertre CA, Gluch L, Hui MN, Beith J, Parker A, Robbins E, Segara D, Cooper C, Mak C, Chan B, Warrier S, Ginhoux F, Millar E, Powell JE, Williams SR, Liu XS, O’Toole S, Lim E, Lundeberg J, Perou CM, Swarbrick A. A single-cell and spatially resolved atlas of human breast cancers. Nat Genet 2021; 53(9): 1334–1347
CrossRef
Google scholar
|
[100] |
Wu Y, Yang S, Ma J, Chen Z, Song G, Rao D, Cheng Y, Huang S, Liu Y, Jiang S, Liu J, Huang X, Wang X, Qiu S, Xu J, Xi R, Bai F, Zhou J, Fan J, Zhang X, Gao Q. Spatiotemporal immune landscape of colorectal cancer liver metastasis at single-cell level. Cancer Discov 2022; 12(1): 134–153
CrossRef
Google scholar
|
[101] |
Giesen C, Wang HA, Schapiro D, Zivanovic N, Jacobs A, Hattendorf B, Schüffler PJ, Grolimund D, Buhmann JM, Brandt S, Varga Z, Wild PJ, Günther D, Bodenmiller B. Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry. Nat Methods 2014; 11(4): 417–422
CrossRef
Google scholar
|
[102] |
Chang Q, Ornatsky OI, Siddiqui I, Loboda A, Baranov VI, Hedley DW. Imaging mass cytometry. Cytometry A 2017; 91(2): 160–169
CrossRef
Google scholar
|
[103] |
Baharlou H, Canete NP, Cunningham AL, Harman AN, Patrick E. Mass cytometry imaging for the study of human diseases-applications and data analysis strategies. Front Immunol 2019; 10: 2657
CrossRef
Google scholar
|
[104] |
Bodenmiller B. Multiplexed epitope-based tissue imaging for discovery and healthcare applications. Cell Syst 2016; 2(4): 225–238
CrossRef
Google scholar
|
[105] |
Moldoveanu D, Ramsay L, Lajoie M, Anderson-Trocme L, Lingrand M, Berry D, Perus LJM, Wei Y, Moraes C, Alkallas R, Rajkumar S, Zuo D, Dankner M, Xu EH, Bertos NR, Najafabadi HS, Gravel S, Costantino S, Richer MJ, Lund AW, Del Rincon SV, Spatz A, Miller WH Jr, Jamal R, Lapointe R, Mes-Masson AM, Turcotte S, Petrecca K, Dumitra S, Meguerditchian AN, Richardson K, Tremblay F, Wang B, Chergui M, Guiot MC, Watters K, Stagg J, Quail DF, Mihalcioiu C, Meterissian S, Watson IR. Spatially mapping the immune landscape of melanoma using imaging mass cytometry. Sci Immunol 2022; 7(70): eabi5072
CrossRef
Google scholar
|
[106] |
Martinez-Morilla S, Villarroel-Espindola F, Wong PF, Toki MI, Aung TN, Pelekanou V, Bourke-Martin B, Schalper KA, Kluger HM, Rimm DL. Biomarker discovery in patients with immunotherapy-treated melanoma with imaging mass cytometry. Clin Cancer Res 2021; 27(7): 1987–1996
CrossRef
Google scholar
|
[107] |
Jang HJ, Lee HS, Yu W, Ramineni M, Truong CY, Ramos D, Splawn T, Choi JM, Jung SY, Lee JS, Wang DY, Sederstrom JM, Pietropaolo M, Kheradmand F, Amos CI, Wheeler TM, Ripley RT, Burt BM. Therapeutic targeting of macrophage plasticity remodels the tumor-immune microenvironment. Cancer Res 2022; 82(14): 2593–2609
CrossRef
Google scholar
|
[108] |
Zarella MD, Bowman D, Aeffner F, Farahani N, Xthona A, Absar SF, Parwani A, Bui M, Hartman DJ. A Practical Guide to Whole Slide Imaging: A White Paper from the Digital Pathology Association. Arch Pathol Lab Med 2019; 143(2): 222–234
CrossRef
Google scholar
|
[109] |
Gifford AJ, Colebatch AJ, Litkouhi S, Hersch F, Warzecha W, Snook K, Sywak M, Gill AJ. Remote frozen section examination of breast sentinel lymph nodes by telepathology. ANZ J Surg 2012; 82(11): 803–808
CrossRef
Google scholar
|
[110] |
Pantanowitz L. Digital images and the future of digital pathology. J Pathol Inform 2010; 1: 15
CrossRef
Google scholar
|
[111] |
Baxi V, Edwards R, Montalto M, Saha S. Digital pathology and artificial intelligence in translational medicine and clinical practice. Mod Pathol 2022; 35(1): 23–32
CrossRef
Google scholar
|
[112] |
Indu M, Rathy R, Binu MP. “Slide less pathology”: fairy tale or reality?. J Oral Maxillofac Pathol 2016; 20(2): 284–288
CrossRef
Google scholar
|
[113] |
Ghaznavi F, Evans A, Madabhushi A, Feldman M. Digital imaging in pathology: whole-slide imaging and beyond. Annu Rev Pathol 2013; 8(1): 331–359
CrossRef
Google scholar
|
[114] |
Feng Z, Puri S, Moudgil T, Wood W, Hoyt CC, Wang C, Urba WJ, Curti BD, Bifulco CB, Fox BA. Multispectral imaging of formalin-fixed tissue predicts ability to generate tumor-infiltrating lymphocytes from melanoma. J Immunother Cancer 2015; 3(1): 47
CrossRef
Google scholar
|
[115] |
Bera K, Schalper KA, Rimm DL, Velcheti V, Madabhushi A. Artificial intelligence in digital pathologynew tools for diagnosis and precision oncology. Nat Rev Clin Oncol 2019; 16(11): 703–715
CrossRef
Google scholar
|
[116] |
Tumeh PC, Hellmann MD, Hamid O, Tsai KK, Loo KL, Gubens MA, Rosenblum M, Harview CL, Taube JM, Handley N, Khurana N, Nosrati A, Krummel MF, Tucker A, Sosa EV, Sanchez PJ, Banayan N, Osorio JC, Nguyen-Kim DL, Chang J, Shintaku IP, Boasberg PD, Taylor EJ, Munster PN, Algazi AP, Chmielowski B, Dummer R, Grogan TR, Elashoff D, Hwang J, Goldinger SM, Garon EB, Pierce RH, Daud A. Liver metastasis and treatment outcome with anti-PD-1 monoclonal antibody in patients with melanoma and NSCLC. Cancer Immunol Res 2017; 5(5): 417–424
CrossRef
Google scholar
|
[117] |
Taube JM, Akturk G, Angelo M, Engle EL, Gnjatic S, Greenbaum S, Greenwald NF, Hedvat CV, Hollmann TJ, Juco J, Parra ER, Rebelatto MC, Rimm DL, Rodriguez-Canales J, Schalper KA, Stack EC, Ferreira CS, Korski K, Lako A, Rodig SJ, Schenck E, Steele KE, Surace MJ, Tetzlaff MT, von Loga K, Wistuba II, Bifulco CB; Society for Immunotherapy of Cancer (SITC) Pathology Task Force. The Society for Immunotherapy of Cancer statement on best practices for multiplex immunohistochemistry (IHC) and immunofluorescence (IF) staining and validation. J Immunother Cancer 2020; 8(1): e000155
CrossRef
Google scholar
|
[118] |
Carstens JL, Correa de Sampaio P, Yang D, Barua S, Wang H, Rao A, Allison JP, LeBleu VS, Kalluri R. Spatial computation of intratumoral T cells correlates with survival of patients with pancreatic cancer. Nat Commun 2017; 8(1): 15095
CrossRef
Google scholar
|
[119] |
Coudray N, Ocampo PS, Sakellaropoulos T, Narula N, Snuderl M, Fenyö D, Moreira AL, Razavian N, Tsirigos A. Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning. Nat Med 2018; 24(10): 1559–1567
CrossRef
Google scholar
|
[120] |
Kather JN, Pearson AT, Halama N, Jäger D, Krause J, Loosen SH, Marx A, Boor P, Tacke F, Neumann UP, Grabsch HI, Yoshikawa T, Brenner H, Chang-Claude J, Hoffmeister M, Trautwein C, Luedde T. Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer. Nat Med 2019; 25(7): 1054–1056
CrossRef
Google scholar
|
[121] |
Park S, Ock CY, Kim H, Pereira S, Park S, Ma M, Choi S, Kim S, Shin S, Aum BJ, Paeng K, Yoo D, Cha H, Park S, Suh KJ, Jung HA, Kim SH, Kim YJ, Sun JM, Chung JH, Ahn JS, Ahn MJ, Lee JS, Park K, Song SY, Bang YJ, Choi YL, Mok TS, Lee SH. Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes as complementary biomarker for immune checkpoint inhibition in non-small-cell lung cancer. J Clin Oncol 2022; 40(17): 1916–1928
CrossRef
Google scholar
|
[122] |
Saillard C, Schmauch B, Laifa O, Moarii M, Toldo S, Zaslavskiy M, Pronier E, Laurent A, Amaddeo G, Regnault H, Sommacale D, Ziol M, Pawlotsky JM, Mulé S, Luciani A, Wainrib G, Clozel T, Courtiol P, Calderaro J. Predicting survival after hepatocellular carcinoma resection using deep learning on histological slides. Hepatology 2020; 72(6): 2000–2013
CrossRef
Google scholar
|
[123] |
Schmauch B, Romagnoni A, Pronier E, Saillard C, Maillé P, Calderaro J, Kamoun A, Sefta M, Toldo S, Zaslavskiy M, Clozel T, Moarii M, Courtiol P, Wainrib G. A deep learning model to predict RNA-Seq expression of tumours from whole slide images. Nat Commun 2020; 11(1): 3877
CrossRef
Google scholar
|
[124] |
Sun R, Limkin EJ, Vakalopoulou M, Dercle L, Champiat S, Han SR, Verlingue L, Brandao D, Lancia A, Ammari S, Hollebecque A, Scoazec JY, Marabelle A, Massard C, Soria JC, Robert C, Paragios N, Deutsch E, Ferté C. A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study. Lancet Oncol 2018; 19(9): 1180–1191
CrossRef
Google scholar
|
[125] |
Turkki R, Byckhov D, Lundin M, Isola J, Nordling S, Kovanen PE, Verrill C, von Smitten K, Joensuu H, Lundin J, Linder N. Breast cancer outcome prediction with tumour tissue images and machine learning. Breast Cancer Res Treat 2019; 177(1): 41–52
CrossRef
Google scholar
|
[126] |
Vanguri RS, Luo J, Aukerman AT, Egger JV, Fong CJ, Horvat N, Pagano A, Araujo-Filho JAB, Geneslaw L, Rizvi H, Sosa R, Boehm KM, Yang SR, Bodd FM, Ventura K, Hollmann TJ, Ginsberg MS, Gao J; MSK MIND Consortium; Hellmann MD, Sauter JL, Shah SP. Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L)1 blockade in patients with non-small cell lung cancer. Nat Can 2022; 3(10): 1151–1164
CrossRef
Google scholar
|
[127] |
Vamathevan J, Clark D, Czodrowski P, Dunham I, Ferran E, Lee G, Li B, Madabhushi A, Shah P, Spitzer M, Zhao S. Applications of machine learning in drug discovery and development. Nat Rev Drug Discov 2019; 18(6): 463–477
CrossRef
Google scholar
|
[128] |
Janowczyk A, Madabhushi A. Deep learning for digital pathology image analysis: a comprehensive tutorial with selected use cases. J Pathol Inform 2016; 7(1): 29
CrossRef
Google scholar
|
[129] |
Araújo T, Aresta G, Castro E, Rouco J, Aguiar P, Eloy C, Polónia A, Campilho A. Classification of breast cancer histology images using Convolutional Neural Networks. PLoS One 2017; 12(6): e0177544
CrossRef
Google scholar
|
[130] |
Ehteshami Bejnordi B, Mullooly M, Pfeiffer RM, Fan S, Vacek PM, Weaver DL, Herschorn S, Brinton LA, van Ginneken B, Karssemeijer N, Beck AH, Gierach GL, van der Laak JAWM, Sherman ME. Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies. Mod Pathol 2018; 31(10): 1502–1512
CrossRef
Google scholar
|
[131] |
Pavillon N, Hobro AJ, Akira S, Smith NI. Noninvasive detection of macrophage activation with single-cell resolution through machine learning. Proc Natl Acad Sci USA 2018; 115(12): E2676–E2685
CrossRef
Google scholar
|
[132] |
Liu H, Xu WD, Shang ZH, Wang XD, Zhou HY, Ma KW, Zhou H, Qi JL, Jiang JR, Tan LL, Zeng HM, Cai HJ, Wang KS, Qian YL. Breast cancer molecular subtype prediction on pathological images with discriminative patch selection and multi-instance learning. Front Oncol 2022; 12: 858453
CrossRef
Google scholar
|
[133] |
Tizhoosh HR, Pantanowitz L. Artificial intelligence and digital pathology: challenges and opportunities. J Pathol Inform 2018; 9(1): 38
CrossRef
Google scholar
|
[134] |
Tan WCC, Nerurkar SN, Cai HY, Ng HHM, Wu D, Wee YTF, Lim JCT, Yeong J, Lim TKH. Overview of multiplex immunohistochemistry/immunofluorescence techniques in the era of cancer immunotherapy. Cancer Commun (Lond) 2020; 40(4): 135–153
CrossRef
Google scholar
|
[135] |
Van Herck Y, Antoranz A, Andhari MD, Milli G, Bechter O, De Smet F, Bosisio FM. Multiplexed immunohistochemistry and digital pathology as the foundation for next-generation pathology in melanoma: methodological comparison and future clinical applications. Front Oncol 2021; 11: 636681
CrossRef
Google scholar
|
[136] |
Serag A, Ion-Margineanu A, Qureshi H, McMillan R, Saint Martin MJ, Diamond J, O’Reilly P, Hamilton P. Translational AI and deep learning in diagnostic pathology. Front Med (Lausanne) 2019; 6: 185
CrossRef
Google scholar
|
[137] |
Farmer H, McCabe N, Lord CJ, Tutt AN, Johnson DA, Richardson TB, Santarosa M, Dillon KJ, Hickson I, Knights C, Martin NM, Jackson SP, Smith GC, Ashworth A. Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy. Nature 2005; 434(7035): 917–921
CrossRef
Google scholar
|
[138] |
Bryant HE, Schultz N, Thomas HD, Parker KM, Flower D, Lopez E, Kyle S, Meuth M, Curtin NJ, Helleday T. Specific killing of BRCA2-deficient tumours with inhibitors of poly(ADP-ribose) polymerase. Nature 2005; 434(7035): 913–917
CrossRef
Google scholar
|
[139] |
Dias MP, Moser SC, Ganesan S, Jonkers J. Understanding and overcoming resistance to PARP inhibitors in cancer therapy. Nat Rev Clin Oncol 2021; 18(12): 773–791
CrossRef
Google scholar
|
[140] |
Ding L, Kim HJ, Wang Q, Kearns M, Jiang T, Ohlson CE, Li BB, Xie S, Liu JF, Stover EH, Howitt BE, Bronson RT, Lazo S, Roberts TM, Freeman GJ, Konstantinopoulos PA, Matulonis UA, Zhao JJ. PARP inhibition elicits STING-dependent antitumor immunity in Brca1-deficient ovarian cancer. Cell Rep 2018; 25(11): 2972–2980.e5
CrossRef
Google scholar
|
[141] |
Meng J, Peng J, Feng J, Maurer J, Li X, Li Y, Yao S, Chu R, Pan X, Li J, Zhang T, Liu L, Zhang Q, Yuan Z, Bu H, Song K, Kong B. Niraparib exhibits a synergistic anti-tumor effect with PD-L1 blockade by inducing an immune response in ovarian cancer. J Transl Med 2021; 19(1): 415
CrossRef
Google scholar
|
[142] |
Wang L, Wang D, Sonzogni O, Ke S, Wang Q, Thavamani A, Batalini F, Stopka SA, Regan MS, Vandal S, Tian S, Pinto J, Cyr AM, Bret-Mounet VC, Baquer G, Eikesdal HP, Yuan M, Asara JM, Heng YJ, Bai P, Agar NYR, Wulf GM. PARP-inhibition reprograms macrophages toward an anti-tumor phenotype. Cell Rep 2022; 41(2): 111462
CrossRef
Google scholar
|
[143] |
Kaufman B, Shapira-Frommer R, Schmutzler RK, Audeh MW, Friedlander M, Balmaña J, Mitchell G, Fried G, Stemmer SM, Hubert A, Rosengarten O, Steiner M, Loman N, Bowen K, Fielding A, Domchek SM. Olaparib monotherapy in patients with advanced cancer and a germline BRCA1/2 mutation. J Clin Oncol 2015; 33(3): 244–250
CrossRef
Google scholar
|
[144] |
Robson M, Im SA, Senkus E, Xu B, Domchek SM, Masuda N, Delaloge S, Li W, Tung N, Armstrong A, Wu W, Goessl C, Runswick S, Conte P. Olaparib for metastatic breast cancer in patients with a germline BRCA mutation. N Engl J Med 2017; 377(6): 523–533
CrossRef
Google scholar
|
[145] |
Ettl J, Quek RGW, Lee KH, Rugo HS, Hurvitz S, Gonçalves A, Fehrenbacher L, Yerushalmi R, Mina LA, Martin M, Roché H, Im YH, Markova D, Bhattacharyya H, Hannah AL, Eiermann W, Blum JL, Litton JK. Quality of life with talazoparib versus physician’s choice of chemotherapy in patients with advanced breast cancer and germline BRCA1/2 mutation: patient-reported outcomes from the EMBRACA phase III trial. Ann Oncol 2018; 29(9): 1939–1947
CrossRef
Google scholar
|
[146] |
Moore KN, Secord AA, Geller MA, Miller DS, Cloven N, Fleming GF, Wahner Hendrickson AE, Azodi M, DiSilvestro P, Oza AM, Cristea M, Berek JS, Chan JK, Rimel BJ, Matei DE, Li Y, Sun K, Luptakova K, Matulonis UA, Monk BJ. Niraparib monotherapy for late-line treatment of ovarian cancer (QUADRA): a multicentre, open-label, single-arm, phase 2 trial. Lancet Oncol 2019; 20(5): 636–648
CrossRef
Google scholar
|
[147] |
Coleman RL, Oza AM, Lorusso D, Aghajanian C, Oaknin A, Dean A, Colombo N, Weberpals JI, Clamp A, Scambia G, Leary A, Holloway RW, Gancedo MA, Fong PC, Goh JC, O'Malley DM, Armstrong DK, Garcia-Donas J, Swisher EM, Floquet A, Konecny GE, McNeish IA, Scott CL, Cameron T, Maloney L, Isaacson J, Goble S, Grace C, Harding TC, Raponi M, Sun J, Lin KK, Giordano H, Ledermann JA; ARIEL3 investigators. Rucaparib maintenance treatment for recurrent ovarian carcinoma after response to platinum therapy (ARIEL3): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet 2017; 390(10106): 1949–1961
CrossRef
Google scholar
|
[148] |
Zimmer AS, Nichols E, Cimino-Mathews A, Peer C, Cao L, Lee MJ, Kohn EC, Annunziata CM, Lipkowitz S, Trepel JB, Sharma R, Mikkilineni L, Gatti-Mays M, Figg WD, Houston ND, Lee JM. A phase I study of the PD-L1 inhibitor, durvalumab, in combination with a PARP inhibitor, olaparib, and a VEGFR1-3 inhibitor, cediranib, in recurrent women’s cancers with biomarker analyses. J Immunother Cancer 2019; 7(1): 197
CrossRef
Google scholar
|
[149] |
Gerard CL, Delyon J, Wicky A, Homicsko K, Cuendet MA, Michielin O. Turning tumors from cold to inflamed to improve immunotherapy response. Cancer Treat Rev 2021; 101: 102227
CrossRef
Google scholar
|
[150] |
Topper MJ, Vaz M, Chiappinelli KB, DeStefano Shields CE, Niknafs N, Yen RC, Wenzel A, Hicks J, Ballew M, Stone M, Tran PT, Zahnow CA, Hellmann MD, Anagnostou V, Strissel PL, Strick R, Velculescu VE, Baylin SB. Epigenetic therapy ties MYC depletion to reversing immune evasion and treating lung cancer. Cell 2017; 171(6): 1284–1300.e21
CrossRef
Google scholar
|
[151] |
Abbas AR, Baldwin D, Ma Y, Ouyang W, Gurney A, Martin F, Fong S, van Lookeren Campagne M, Godowski P, Williams PM, Chan AC, Clark HF. Immune response in silico (IRIS): immune-specific genes identified from a compendium of microarray expression data. Genes Immun 2005; 6(4): 319–331
CrossRef
Google scholar
|
[152] |
Pai SG, Carneiro BA, Mota JM, Costa R, Leite CA, Barroso-Sousa R, Kaplan JB, Chae YK, Giles FJ. Wnt/beta-catenin pathway: modulating anticancer immune response. J Hematol Oncol 2017; 10(1): 101
CrossRef
Google scholar
|
[153] |
Yang L, Pang Y, Moses HL. TGF-beta and immune cells: an important regulatory axis in the tumor microenvironment and progression. Trends Immunol 2010; 31(6): 220–227
CrossRef
Google scholar
|
[154] |
Paez JG, Jänne PA, Lee JC, Tracy S, Greulich H, Gabriel S, Herman P, Kaye FJ, Lindeman N, Boggon TJ, Naoki K, Sasaki H, Fujii Y, Eck MJ, Sellers WR, Johnson BE, Meyerson M. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 2004; 304(5676): 1497–1500
CrossRef
Google scholar
|
[155] |
Gross S, Rahal R, Stransky N, Lengauer C, Hoeflich KP. Targeting cancer with kinase inhibitors. J Clin Invest 2015; 125(5): 1780–1789
CrossRef
Google scholar
|
[156] |
Tan HY, Wang N, Lam W, Guo W, Feng Y, Cheng YC. Targeting tumour microenvironment by tyrosine kinase inhibitor. Mol Cancer 2018; 17(1): 43
CrossRef
Google scholar
|
[157] |
Shi Y, Au JS, Thongprasert S, Srinivasan S, Tsai CM, Khoa MT, Heeroma K, Itoh Y, Cornelio G, Yang PC. A prospective, molecular epidemiology study of EGFR mutations in Asian patients with advanced non-small-cell lung cancer of adenocarcinoma histology (PIONEER). J Thorac Oncol 2014; 9(2): 154–162
CrossRef
Google scholar
|
[158] |
Sordella R, Bell DW, Haber DA, Settleman J. Gefitinib-sensitizing EGFR mutations in lung cancer activate anti-apoptotic pathways. Science 2004; 305(5687): 1163–1167
CrossRef
Google scholar
|
[159] |
Lynch TJ, Bell DW, Sordella R, Gurubhagavatula S, Okimoto RA, Brannigan BW, Harris PL, Haserlat SM, Supko JG, Haluska FG, Louis DN, Christiani DC, Settleman J, Haber DA. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med 2004; 350(21): 2129–2139
CrossRef
Google scholar
|
[160] |
Dominguez C, Tsang KY, Palena C. Short-term EGFR blockade enhances immune-mediated cytotoxicity of EGFR mutant lung cancer cells: rationale for combination therapies. Cell Death Dis 2016; 7(9): e2380
CrossRef
Google scholar
|
[161] |
Selenz C, Compes A, Nill M, Borchmann S, Odenthal M, Florin A, Brägelmann J, Büttner R, Meder L, Ullrich RT. EGFR inhibition strongly modulates the tumour immune microenvironment in EGFR-driven non-small-cell lung cancer. Cancers (Basel) 2022; 14(16): 3943
CrossRef
Google scholar
|
[162] |
Hsu KH, Huang YH, Tseng JS, Chen KC, Ku WH, Su KY, Chen JJW, Chen HW, Yu SL, Yang TY, Chang GC. High PD-L1 expression correlates with primary resistance to EGFR-TKIs in treatment naïve advanced EGFR-mutant lung adenocarcinoma patients. Lung Cancer 2019; 127: 37–43
CrossRef
Google scholar
|
[163] |
Oshima Y, Tanimoto T, Yuji K, Tojo A. EGFR-TKI-associated interstitial pneumonitis in nivolumab-treated patients with non-small cell lung cancer. JAMA Oncol 2018; 4(8): 1112–1115
CrossRef
Google scholar
|
[164] |
Kato S, Goodman A, Walavalkar V, Barkauskas DA, Sharabi A, Kurzrock R. Hyperprogressors after immunotherapy: analysis of genomic alterations associated with accelerated growth rate. Clin Cancer Res 2017; 23(15): 4242–4250
CrossRef
Google scholar
|
[165] |
Tian T, Yu M, Li J, Jiang M, Ma D, Tang S, Lin Z, Chen L, Gong Y, Zhu J, Zhou Q, Huang M, Lu Y. Front-line ICI-based combination therapy post-TKI resistance may improve survival in NSCLC patients with EGFR mutation. Front Oncol 2021; 11: 739090
CrossRef
Google scholar
|
[166] |
Gridelli C, Peters S, Sgambato A, Casaluce F, Adjei AA, Ciardiello F. ALK inhibitors in the treatment of advanced NSCLC. Cancer Treat Rev 2014; 40(2): 300–306
CrossRef
Google scholar
|
[167] |
Arbour KC, Riely GJ. Diagnosis and treatment of anaplastic lymphoma kinase-positive non-small cell lung cancer. Hematol Oncol Clin North Am 2017; 31(1): 101–111
CrossRef
Google scholar
|
[168] |
Fang Y, Wang Y, Zeng D, Zhi S, Shu T, Huang N, Zheng S, Wu J, Liu Y, Huang G, Xue Y, Bin J, Liao Y, Shi M, Liao W. Comprehensive analyses reveal TKI-induced remodeling of the tumor immune microenvironment in EGFR/ALK-positive non-small-cell lung cancer. OncoImmunology 2021; 10(1): 1951019
CrossRef
Google scholar
|
[169] |
Spigel DR, Reynolds C, Waterhouse D, Garon EB, Chandler J, Babu S, Thurmes P, Spira A, Jotte R, Zhu J, Lin WH, Blumenschein G Jr. Phase 1/2 study of the safety and tolerability of nivolumab plus crizotinib for the first-line treatment of anaplastic lymphoma kinase translocation—positive advanced non-small cell lung cancer (CheckMate 370). J Thorac Oncol 2018; 13(5): 682–688
CrossRef
Google scholar
|
[170] |
Dummer R, Queirolo P, Abajo Guijarro AM, Hu Y, Wang D, de Azevedo SJ, Robert C, Ascierto PA, Chiarion-Sileni V, Pronzato P, Spagnolo F, Mujika Eizmendi K, Liszkay G, de la Cruz Merino L, Tawbi H. Atezolizumab, vemurafenib, and cobimetinib in patients with melanoma with CNS metastases (TRICOTEL): a multicentre, open-label, single-arm, phase 2 study. Lancet Oncol 2022; 23(9): 1145–1155
CrossRef
Google scholar
|
[171] |
Sullivan RJ, Hamid O, Gonzalez R, Infante JR, Patel MR, Hodi FS, Lewis KD, Tawbi HA, Hernandez G, Wongchenko MJ, Chang Y, Roberts L, Ballinger M, Yan Y, Cha E, Hwu P. Atezolizumab plus cobimetinib and vemurafenib in BRAF-mutated melanoma patients. Nat Med 2019; 25(6): 929–935
CrossRef
Google scholar
|
[172] |
Ribas A, Lawrence D, Atkinson V, Agarwal S, Miller WH Jr, Carlino MS, Fisher R, Long GV, Hodi FS, Tsoi J, Grasso CS, Mookerjee B, Zhao Q, Ghori R, Moreno BH, Ibrahim N, Hamid O. Combined BRAF and MEK inhibition with PD-1 blockade immunotherapy in BRAF-mutant melanoma. Nat Med 2019; 25(6): 936–940
CrossRef
Google scholar
|
[173] |
Ascierto PA, Stroyakovskiy D, Gogas H, Robert C, Lewis K, Protsenko S, Pereira RP, Eigentler T, Rutkowski P, Demidov L, Zhukova N, Schachter J, Yan Y, Caro I, Hertig C, Xue C, Kusters L, McArthur GA, Gutzmer R. Overall survival with first-line atezolizumab in combination with vemurafenib and cobimetinib in BRAFV600 mutation-positive advanced melanoma (IMspire150): second interim analysis of a multicentre, randomised, phase 3 study. Lancet Oncol 2023; 24(1): 33–44
CrossRef
Google scholar
|
[174] |
Chen DS, Mellman I. Oncology meets immunology: the cancer-immunity cycle. Immunity 2013; 39(1): 1–10
CrossRef
Google scholar
|
[175] |
Liu X, Pu Y, Cron K, Deng L, Kline J, Frazier WA, Xu H, Peng H, Fu YX, Xu MM. CD47 blockade triggers T cell-mediated destruction of immunogenic tumors. Nat Med 2015; 21(10): 1209–1215
CrossRef
Google scholar
|
[176] |
Wang H, Hu S, Chen X, Shi H, Chen C, Sun L, Chen ZJ. cGAS is essential for the antitumor effect of immune checkpoint blockade. Proc Natl Acad Sci USA 2017; 114(7): 1637–1642
CrossRef
Google scholar
|
[177] |
Li T, Cheng H, Yuan H, Xu Q, Shu C, Zhang Y, Xu P, Tan J, Rui Y, Li P, Tan X. Antitumor activity of cGAMP via stimulation of cGAS-cGAMP-STING-IRF3 mediated innate immune response. Sci Rep 2016; 6(1): 19049
CrossRef
Google scholar
|
[178] |
Deng L, Liang H, Xu M, Yang X, Burnette B, Arina A, Li XD, Mauceri H, Beckett M, Darga T, Huang X, Gajewski TF, Chen ZJ, Fu YX, Weichselbaum RR. STING-dependent cytosolic DNA sensing promotes radiation-induced type I interferon-dependent antitumor immunity in immunogenic tumors. Immunity 2014; 41(5): 843–852
CrossRef
Google scholar
|
[179] |
Diamond MS, Kinder M, Matsushita H, Mashayekhi M, Dunn GP, Archambault JM, Lee H, Arthur CD, White JM, Kalinke U, Murphy KM, Schreiber RD. Type I interferon is selectively required by dendritic cells for immune rejection of tumors. J Exp Med 2011; 208(10): 1989–2003
CrossRef
Google scholar
|
[180] |
Sivick KE, Desbien AL, Glickman LH, Reiner GL, Corrales L, Surh NH, Hudson TE, Vu UT, Francica BJ, Banda T, Katibah GE, Kanne DB, Leong JJ, Metchette K, Bruml JR, Ndubaku CO, McKenna JM, Feng Y, Zheng L, Bender SL, Cho CY, Leong ML, van Elsas A, Dubensky TW Jr, McWhirter SM. Magnitude of therapeutic STING activation determines CD8+ T cell-mediated anti-tumor immunity. Cell Rep 2019; 29(3): 785–789
CrossRef
Google scholar
|
[181] |
Kawasaki T, Kawai T. Toll-like receptor signaling pathways. Front Immunol 2014; 5: 461
CrossRef
Google scholar
|
[182] |
Wang C, Zhuang Y, Zhang Y, Luo Z, Gao N, Li P, Pan H, Cai L, Ma Y. Toll-like receptor 3 agonist complexed with cationic liposome augments vaccine-elicited antitumor immunity by enhancing TLR3-IRF3 signaling and type I interferons in dendritic cells. Vaccine 2012; 30(32): 4790–4799
CrossRef
Google scholar
|
[183] |
Krieg AM. Therapeutic potential of Toll-like receptor 9 activation. Nat Rev Drug Discov 2006; 5(6): 471–484
CrossRef
Google scholar
|
[184] |
Koh J, Kim S, Lee SN, Kim SY, Kim JE, Lee KY, Kim MS, Heo JY, Park YM, Ku BM, Sun JM, Lee SH, Ahn JS, Park K, Yang S, Ha SJ, Lim YT, Ahn MJ. Therapeutic efficacy of cancer vaccine adjuvanted with nanoemulsion loaded with TLR7/8 agonist in lung cancer model. Nanomedicine 2021; 37: 102415
CrossRef
Google scholar
|
[185] |
Ribas A, Medina T, Kummar S, Amin A, Kalbasi A, Drabick JJ, Barve M, Daniels GA, Wong DJ, Schmidt EV, Candia AF, Coffman RL, Leung ACF, Janssen RS. SD-101 in combination with pembrolizumab in advanced melanoma: results of a phase Ib, multicenter Study. Cancer Discov 2018; 8(10): 1250–1257
CrossRef
Google scholar
|
[186] |
Vonderheide RH. CD40 agonist antibodies in cancer immunotherapy. Annu Rev Med 2020; 71(1): 47–58
CrossRef
Google scholar
|
[187] |
Mangsbo SM, Broos S, Fletcher E, Veitonmäki N, Furebring C, Dahlén E, Norlén P, Lindstedt M, Tötterman TH, Ellmark P. The human agonistic CD40 antibody ADC-1013 eradicates bladder tumors and generates T-cell-dependent tumor immunity. Clin Cancer Res 2015; 21(5): 1115–1126
CrossRef
Google scholar
|
[188] |
Johnson P, Challis R, Chowdhury F, Gao Y, Harvey M, Geldart T, Kerr P, Chan C, Smith A, Steven N, Edwards C, Ashton-Key M, Hodges E, Tutt A, Ottensmeier C, Glennie M, Williams A. Clinical and biological effects of an agonist anti-CD40 antibody: a Cancer Research UK phase I study. Clin Cancer Res 2015; 21(6): 1321–1328
CrossRef
Google scholar
|
[189] |
Rüter J, Antonia SJ, Burris HA, Huhn RD, Vonderheide RH. Immune modulation with weekly dosing of an agonist CD40 antibody in a phase I study of patients with advanced solid tumors. Cancer Biol Ther 2010; 10(10): 983–993
CrossRef
Google scholar
|
[190] |
Vonderheide RH, Flaherty KT, Khalil M, Stumacher MS, Bajor DL, Hutnick NA, Sullivan P, Mahany JJ, Gallagher M, Kramer A, Green SJ, O’Dwyer PJ, Running KL, Huhn RD, Antonia SJ. Clinical activity and immune modulation in cancer patients treated with CP-870,893, a novel CD40 agonist monoclonal antibody. J Clin Oncol 2007; 25(7): 876–883
CrossRef
Google scholar
|
[191] |
Bajor DL, Xu X, Torigian DA, Mick R, Garcia LR, Richman LP, Desmarais C, Nathanson KL, Schuchter LM, Kalos M, Vonderheide RH. Immune activation and a 9-year ongoing complete remission following CD40 antibody therapy and metastasectomy in a patient with metastatic melanoma. Cancer Immunol Res 2014; 2(11): 1051–1058
CrossRef
Google scholar
|
[192] |
Bajor DL, Mick R, Riese MJ, Huang AC, Sullivan B, Richman LP, Torigian DA, George SM, Stelekati E, Chen F, Melenhorst JJ, Lacey SF, Xu X, Wherry EJ, Gangadhar TC, Amaravadi RK, Schuchter LM, Vonderheide RH. Long-term outcomes of a phase I study of agonist CD40 antibody and CTLA-4 blockade in patients with metastatic melanoma. OncoImmunology 2018; 7(10): e1468956
CrossRef
Google scholar
|
[193] |
Russell L, Peng KW, Russell SJ, Diaz RM. Oncolytic viruses: priming time for cancer immunotherapy. BioDrugs 2019; 33(5): 485–501
CrossRef
Google scholar
|
[194] |
Gujar S, Pol JG, Kim Y, Lee PW, Kroemer G. Antitumor benefits of antiviral immunity: an underappreciated aspect of oncolytic virotherapies. Trends Immunol 2018; 39(3): 209–221
CrossRef
Google scholar
|
[195] |
Lemos de Matos A, Franco LS, McFadden G. Oncolytic viruses and the immune system: the dynamic duo. Mol Ther Methods Clin Dev 2020; 17: 349–358
CrossRef
Google scholar
|
[196] |
Andtbacka RH, Kaufman HL, Collichio F, Amatruda T, Senzer N, Chesney J, Delman KA, Spitler LE, Puzanov I, Agarwala SS, Milhem M, Cranmer L, Curti B, Lewis K, Ross M, Guthrie T, Linette GP, Daniels GA, Harrington K, Middleton MR, Miller WH Jr, Zager JS, Ye Y, Yao B, Li A, Doleman S, VanderWalde A, Gansert J, Coffin RS. Talimogene laherparepvec improves durable response rate in patients with advanced melanoma. J Clin Oncol 2015; 33(25): 2780–2788
CrossRef
Google scholar
|
[197] |
Ribas A, Dummer R, Puzanov I, VanderWalde A, Andtbacka RHI, Michielin O, Olszanski AJ, Malvehy J, Cebon J, Fernandez E, Kirkwood JM, Gajewski TF, Chen L, Gorski KS, Anderson AA, Diede SJ, Lassman ME, Gansert J, Hodi FS, Long GV. Oncolytic virotherapy promotes intratumoral T cell infiltration and improves anti-PD-1 immunotherapy. Cell 2017; 170(6): 1109–1119.e10
CrossRef
Google scholar
|
[198] |
Zhang Y, Zhang Z. The history and advances in cancer immunotherapy: understanding the characteristics of tumor-infiltrating immune cells and their therapeutic implications. Cell Mol Immunol 2020; 17(8): 807–821
CrossRef
Google scholar
|
[199] |
Ogi C, Aruga A. Immunological monitoring of anticancer vaccines in clinical trials. OncoImmunology 2013; 2(8): e26012
CrossRef
Google scholar
|
[200] |
Lorentzen CL, Haanen JB, Met Ö, Svane IM. Clinical advances and ongoing trials on mRNA vaccines for cancer treatment. Lancet Oncol 2022; 23(10): e450–e458
CrossRef
Google scholar
|
[201] |
Lin MJ, Svensson-Arvelund J, Lubitz GS, Marabelle A, Melero I, Brown BD, Brody JD. Cancer vaccines: the next immunotherapy frontier. Nat Can 2022; 3(8): 911–926
CrossRef
Google scholar
|
[202] |
Song Q, Zhang CD, Wu XH. Therapeutic cancer vaccines: from initial findings to prospects. Immunol Lett 2018; 196: 11–21
CrossRef
Google scholar
|
[203] |
Coventry BJ. Therapeutic vaccination immunomodulation: forming the basis of all cancer immunotherapy. Ther Adv Vaccines Immunother 2019; 7: 2515135519862234
CrossRef
Google scholar
|
[204] |
Zhang J, Shi Z, Xu X, Yu Z, Mi J. The influence of microenvironment on tumor immunotherapy. FEBS J 2019; 286(21): 4160–4175
CrossRef
Google scholar
|
[205] |
Shemesh CS, Hsu JC, Hosseini I, Shen BQ, Rotte A, Twomey P, Girish S, Wu B. Personalized cancer vaccines: clinical landscape, challenges, and opportunities. Mol Ther 2021; 29(2): 555–570
CrossRef
Google scholar
|
[206] |
Tsao SW, Tramoutanis G, Dawson CW, Lo AK, Huang DP. The significance of LMP1 expression in nasopharyngeal carcinoma. Semin Cancer Biol 2002; 12(6): 473–487
CrossRef
Google scholar
|
[207] |
Lin MC, Lin YC, Chen ST, Young TH, Lou PJ. Therapeutic vaccine targeting Epstein-Barr virus latent protein, LMP1, suppresses LMP1-expressing tumor growth and metastasis in vivo. BMC Cancer 2017; 17(1): 18
CrossRef
Google scholar
|
[208] |
Taylor GS, Jia H, Harrington K, Lee LW, Turner J, Ladell K, Price DA, Tanday M, Matthews J, Roberts C, Edwards C, McGuigan L, Hartley A, Wilson S, Hui EP, Chan AT, Rickinson AB, Steven NM. A recombinant modified vaccinia ankara vaccine encoding Epstein–Barr virus (EBV) target antigens: a phase I trial in UK patients with EBV-positive cancer. Clin Cancer Res 2014; 20(19): 5009–5022
CrossRef
Google scholar
|
[209] |
Kenter GG, Welters MJ, Valentijn AR, Lowik MJ, Berends-van der Meer DM, Vloon AP, Essahsah F, Fathers LM, Offringa R, Drijfhout JW, Wafelman AR, Oostendorp J, Fleuren GJ, van der Burg SH, Melief CJ. Vaccination against HPV-16 oncoproteins for vulvar intraepithelial neoplasia. N Engl J Med 2009; 361(19): 1838–1847
CrossRef
Google scholar
|
[210] |
Oka Y, Tsuboi A, Oji Y, Kawase I, Sugiyama H. WT1 peptide vaccine for the treatment of cancer. Curr Opin Immunol 2008; 20(2): 211–220
CrossRef
Google scholar
|
[211] |
Zhang W, Lu X, Cui P, Piao C, Xiao M, Liu X, Wang Y, Wu X, Liu J, Yang L. Phase I/II clinical trial of a Wilms’ tumor 1-targeted dendritic cell vaccination-based immunotherapy in patients with advanced cancer. Cancer Immunol Immunother 2019; 68(1): 121–130
CrossRef
Google scholar
|
[212] |
Moeller I, Spagnoli GC, Finke J, Veelken H, Houet L. Uptake routes of tumor-antigen MAGE-A3 by dendritic cells determine priming of naïve T-cell subtypes. Cancer Immunol Immunother 2012; 61(11): 2079–2090
CrossRef
Google scholar
|
[213] |
Schnurr M, Orban M, Robson NC, Shin A, Braley H, Airey D, Cebon J, Maraskovsky E, Endres S. ISCOMATRIX adjuvant induces efficient cross-presentation of tumor antigen by dendritic cells via rapid cytosolic antigen delivery and processing via tripeptidyl peptidase II. J Immunol 2009; 182(3): 1253–1259
CrossRef
Google scholar
|
[214] |
Dreno B, Thompson JF, Smithers BM, Santinami M, Jouary T, Gutzmer R, Levchenko E, Rutkowski P, Grob JJ, Korovin S, Drucis K, Grange F, Machet L, Hersey P, Krajsova I, Testori A, Conry R, Guillot B, Kruit WHJ, Demidov L, Thompson JA, Bondarenko I, Jaroszek J, Puig S, Cinat G, Hauschild A, Goeman JJ, van Houwelingen HC, Ulloa-Montoya F, Callegaro A, Dizier B, Spiessens B, Debois M, Brichard VG, Louahed J, Therasse P, Debruyne C, Kirkwood JM. MAGE-A3 immunotherapeutic as adjuvant therapy for patients with resected, MAGE-A3-positive, stage III melanoma (DERMA): a double-blind, randomised, placebo-controlled, phase 3 trial. Lancet Oncol 2018; 19(7): 916–929
CrossRef
Google scholar
|
[215] |
Vansteenkiste JF, Cho BC, Vanakesa T, De Pas T, Zielinski M, Kim MS, Jassem J, Yoshimura M, Dahabreh J, Nakayama H, Havel L, Kondo H, Mitsudomi T, Zarogoulidis K, Gladkov OA, Udud K, Tada H, Hoffman H, Bugge A, Taylor P, Gonzalez EE, Liao ML, He J, Pujol JL, Louahed J, Debois M, Brichard V, Debruyne C, Therasse P, Altorki N. Efficacy of the MAGE-A3 cancer immunotherapeutic as adjuvant therapy in patients with resected MAGE-A3-positive non-small-cell lung cancer (MAGRIT): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol 2016; 17(6): 822–835
CrossRef
Google scholar
|
[216] |
Mittendorf EA, Lu B, Melisko M, Price Hiller J, Bondarenko I, Brunt AM, Sergii G, Petrakova K, Peoples GE. Efficacy and safety analysis of Nelipepimut-S vaccine to prevent breast cancer recurrence: a randomized, multicenter, phase III clinical trial. Clin Cancer Res 2019; 25(14): 4248–4254
CrossRef
Google scholar
|
[217] |
Hodi FS, O’Day SJ, McDermott DF, Weber RW, Sosman JA, Haanen JB, Gonzalez R, Robert C, Schadendorf D, Hassel JC, Akerley W, van den Eertwegh AJ, Lutzky J, Lorigan P, Vaubel JM, Linette GP, Hogg D, Ottensmeier CH, Lebbé C, Peschel C, Quirt I, Clark JI, Wolchok JD, Weber JS, Tian J, Yellin MJ, Nichol GM, Hoos A, Urba WJ. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med 2010; 363(8): 711–723
CrossRef
Google scholar
|
[218] |
Slingluff CL, Lewis KD, Andtbacka R, Hyngstrom J, Milhem M, Markovic SN, Bowles T, Hamid O, Hernandez-Aya L, Claveau J, Jang S, Philips P, Holtan SG, Shaheen MF, Curti B, Schmidt W, Butler MO, Paramo J, Lutzky J, Padmanabhan A, Thomas S, Milton D, Pecora A, Sato T, Hsueh E, Badarinath S, Keech J, Kalmadi S, Kumar P, Weber R, Levine E, Berger A, Bar A, Beck JT, Travers JB, Mihalcioiu C, Gastman B, Beitsch P, Rapisuwon S, Glaspy J, McCarron EC, Gupta V, Behl D, Blumenstein B, Peterkin JJ. Multicenter, double-blind, placebo-controlled trial of seviprotimut-L polyvalent melanoma vaccine in patients with post-resection melanoma at high risk of recurrence. J Immunother Cancer 2021; 9(10): e003272
CrossRef
Google scholar
|
[219] |
Srivastava PK. Neoepitopes of cancers: looking back, looking ahead. Cancer Immunol Res 2015; 3(9): 969–977
CrossRef
Google scholar
|
[220] |
Hu Z, Leet DE, Allesøe RL, Oliveira G, Li S, Luoma AM, Liu J, Forman J, Huang T, Iorgulescu JB, Holden R, Sarkizova S, Gohil SH, Redd RA, Sun J, Elagina L, Giobbie-Hurder A, Zhang W, Peter L, Ciantra Z, Rodig S, Olive O, Shetty K, Pyrdol J, Uduman M, Lee PC, Bachireddy P, Buchbinder EI, Yoon CH, Neuberg D, Pentelute BL, Hacohen N, Livak KJ, Shukla SA, Olsen LR, Barouch DH, Wucherpfennig KW, Fritsch EF, Keskin DB, Wu CJ, Ott PA. Personal neoantigen vaccines induce persistent memory T cell responses and epitope spreading in patients with melanoma. Nat Med 2021; 27(3): 515–525
CrossRef
Google scholar
|
[221] |
Chen H, Li Z, Qiu L, Dong X, Chen G, Shi Y, Cai L, Liu W, Ye H, Zhou Y, Ouyang J, Cai Z, Liu X. Personalized neoantigen vaccine combined with PD-1 blockade increases CD8+ tissue-resident memory T-cell infiltration in preclinical hepatocellular carcinoma models. J Immunother Cancer 2022; 10(9): e004389
CrossRef
Google scholar
|
[222] |
Ott PA, Hu Z, Keskin DB, Shukla SA, Sun J, Bozym DJ, Zhang W, Luoma A, Giobbie-Hurder A, Peter L, Chen C, Olive O, Carter TA, Li S, Lieb DJ, Eisenhaure T, Gjini E, Stevens J, Lane WJ, Javeri I, Nellaiappan K, Salazar AM, Daley H, Seaman M, Buchbinder EI, Yoon CH, Harden M, Lennon N, Gabriel S, Rodig SJ, Barouch DH, Aster JC, Getz G, Wucherpfennig K, Neuberg D, Ritz J, Lander ES, Fritsch EF, Hacohen N, Wu CJ. An immunogenic personal neoantigen vaccine for patients with melanoma. Nature 2017; 547(7662): 217–221
CrossRef
Google scholar
|
[223] |
Slaney CY, Kershaw MH, Darcy PK. Trafficking of T cells into tumors. Cancer Res 2014; 74(24): 7168–7174
CrossRef
Google scholar
|
[224] |
Huang M, Lin Y, Wang C, Deng L, Chen M, Assaraf YG, Chen ZS, Ye W, Zhang D. New insights into antiangiogenic therapy resistance in cancer: mechanisms and therapeutic aspects. Drug Resist Updat 2022; 64: 100849
CrossRef
Google scholar
|
[225] |
Palazón A, Aragonés J, Morales-Kastresana A, de Landázuri MO, Melero I. Molecular pathways: hypoxia response in immune cells fighting or promoting cancer. Clin Cancer Res 2012; 18(5): 1207–1213
CrossRef
Google scholar
|
[226] |
Bellone M, Calcinotto A. Ways to enhance lymphocyte trafficking into tumors and fitness of tumor infiltrating lymphocytes. Front Oncol 2013; 3: 231
CrossRef
Google scholar
|
[227] |
Lee WS, Yang H, Chon HJ, Kim C. Combination of anti-angiogenic therapy and immune checkpoint blockade normalizes vascular-immune crosstalk to potentiate cancer immunity. Exp Mol Med 2020; 52(9): 1475–1485
CrossRef
Google scholar
|
[228] |
Shigeta K, Datta M, Hato T, Kitahara S, Chen IX, Matsui A, Kikuchi H, Mamessier E, Aoki S, Ramjiawan RR, Ochiai H, Bardeesy N, Huang P, Cobbold M, Zhu AX, Jain RK, Duda DG. Dual programmed death receptor-1 and vascular endothelial growth factor receptor-2 blockade promotes vascular normalization and enhances antitumor immune responses in hepatocellular carcinoma. Hepatology 2020; 71(4): 1247–1261
CrossRef
Google scholar
|
[229] |
Kim CG, Jang M, Kim Y, Leem G, Kim KH, Lee H, Kim TS, Choi SJ, Kim HD, Han JW, Kwon M, Kim JH, Lee AJ, Nam SK, Bae SJ, Lee SB, Shin SJ, Park SH, Ahn JB, Jung I, Lee KY, Park SH, Kim H, Min BS, Shin EC. VEGF-A drives TOX-dependent T cell exhaustion in anti-PD-1-resistant microsatellite stable colorectal cancers. Sci Immunol 2019; 4(41): eaay0555
CrossRef
Google scholar
|
[230] |
Rini BI, Plimack ER, Stus V, Gafanov R, Hawkins R, Nosov D, Pouliot F, Alekseev B, Soulières D, Melichar B, Vynnychenko I, Kryzhanivska A, Bondarenko I, Azevedo SJ, Borchiellini D, Szczylik C, Markus M, McDermott RS, Bedke J, Tartas S, Chang YH, Tamada S, Shou Q, Perini RF, Chen M, Atkins MB, Powles T; KEYNOTE-426 Investigators. Pembrolizumab plus axitinib versus sunitinib for advanced renal-cell carcinoma. N Engl J Med 2019; 380(12): 1116–1127
CrossRef
Google scholar
|
[231] |
Rini BI, Powles T, Atkins MB, Escudier B, McDermott DF, Suarez C, Bracarda S, Stadler WM, Donskov F, Lee JL, Hawkins R, Ravaud A, Alekseev B, Staehler M, Uemura M, De Giorgi U, Mellado B, Porta C, Melichar B, Gurney H, Bedke J, Choueiri TK, Parnis F, Khaznadar T, Thobhani A, Li S, Piault-Louis E, Frantz G, Huseni M, Schiff C, Green MC, Motzer RJ; IMmotion151 Study Group. Atezolizumab plus bevacizumab versus sunitinib in patients with previously untreated metastatic renal cell carcinoma (IMmotion151): a multicentre, open-label, phase 3, randomised controlled trial. Lancet 2019; 393(10189): 2404–2415
CrossRef
Google scholar
|
[232] |
Motzer RJ, Powles T, Atkins MB, Escudier B, McDermott DF, Alekseev BY, Lee JL, Suarez C, Stroyakovskiy D, De Giorgi U, Donskov F, Mellado B, Banchereau R, Hamidi H, Khan O, Craine V, Huseni M, Flinn N, Dubey S, Rini BI. Final overall survival and molecular analysis in IMmotion151, a phase 3 trial comparing atezolizumab plus bevacizumab vs sunitinib in patients with previously untreated metastatic renal cell carcinoma. JAMA Oncol 2022; 8(2): 275–280
CrossRef
Google scholar
|
[233] |
Rafiq S, Hackett CS, Brentjens RJ. Engineering strategies to overcome the current roadblocks in CAR T cell therapy. Nat Rev Clin Oncol 2020; 17(3): 147–167
CrossRef
Google scholar
|
[234] |
Miao L, Zhang Z, Ren Z, Tang F, Li Y. Obstacles and coping strategies of CAR-T cell immunotherapy in solid tumors. Front Immunol 2021; 12: 687822
CrossRef
Google scholar
|
[235] |
Porter DL, Levine BL, Kalos M, Bagg A, June CH. Chimeric antigen receptor-modified T cells in chronic lymphoid leukemia. N Engl J Med 2011; 365(8): 725–733
CrossRef
Google scholar
|
[236] |
Maude SL, Frey N, Shaw PA, Aplenc R, Barrett DM, Bunin NJ, Chew A, Gonzalez VE, Zheng Z, Lacey SF, Mahnke YD, Melenhorst JJ, Rheingold SR, Shen A, Teachey DT, Levine BL, June CH, Porter DL, Grupp SA. Chimeric antigen receptor T cells for sustained remissions in leukemia. N Engl J Med 2014; 371(16): 1507–1517
CrossRef
Google scholar
|
[237] |
Brentjens RJ, Rivière I, Park JH, Davila ML, Wang X, Stefanski J, Taylor C, Yeh R, Bartido S, Borquez-Ojeda O, Olszewska M, Bernal Y, Pegram H, Przybylowski M, Hollyman D, Usachenko Y, Pirraglia D, Hosey J, Santos E, Halton E, Maslak P, Scheinberg D, Jurcic J, Heaney M, Heller G, Frattini M, Sadelain M. Safety and persistence of adoptively transferred autologous CD19-targeted T cells in patients with relapsed or chemotherapy refractory B-cell leukemias. Blood 2011; 118(18): 4817–4828
CrossRef
Google scholar
|
[238] |
Marofi F, Motavalli R, Safonov VA, Thangavelu L, Yumashev AV, Alexander M, Shomali N, Chartrand MS, Pathak Y, Jarahian M, Izadi S, Hassanzadeh A, Shirafkan N, Tahmasebi S, Khiavi FM. CAR T cells in solid tumors: challenges and opportunities. Stem Cell Res Ther 2021; 12(1): 81
CrossRef
Google scholar
|
[239] |
Bagley SJ, O’Rourke DM. Clinical investigation of CAR T cells for solid tumors: lessons learned and future directions. Pharmacol Ther 2020; 205: 107419
CrossRef
Google scholar
|
[240] |
Hegde M, Mukherjee M, Grada Z, Pignata A, Landi D, Navai SA, Wakefield A, Fousek K, Bielamowicz K, Chow KK, Brawley VS, Byrd TT, Krebs S, Gottschalk S, Wels WS, Baker ML, Dotti G, Mamonkin M, Brenner MK, Orange JS, Ahmed N. Tandem CAR T cells targeting HER2 and IL13Rα2 mitigate tumor antigen escape. J Clin Invest 2016; 126(8): 3036–3052
CrossRef
Google scholar
|
[241] |
Choi BD, Yu X, Castano AP, Bouffard AA, Schmidts A, Larson RC, Bailey SR, Boroughs AC, Frigault MJ, Leick MB, Scarfò I, Cetrulo CL, Demehri S, Nahed BV, Cahill DP, Wakimoto H, Curry WT, Carter BS, Maus MV. CAR-T cells secreting BiTEs circumvent antigen escape without detectable toxicity. Nat Biotechnol 2019; 37(9): 1049–1058
CrossRef
Google scholar
|
[242] |
Xu R, Du S, Zhu J, Meng F, Liu B. Neoantigen-targeted TCR-T cell therapy for solid tumors: how far from clinical application. Cancer Lett 2022; 546: 215840
CrossRef
Google scholar
|
[243] |
Morgan RA, Dudley ME, Wunderlich JR, Hughes MS, Yang JC, Sherry RM, Royal RE, Topalian SL, Kammula US, Restifo NP, Zheng Z, Nahvi A, de Vries CR, Rogers-Freezer LJ, Mavroukakis SA, Rosenberg SA. Cancer regression in patients after transfer of genetically engineered lymphocytes. Science 2006; 314(5796): 126–129
CrossRef
Google scholar
|
[244] |
Lee SWL, Adriani G, Ceccarello E, Pavesi A, Tan AT, Bertoletti A, Kamm RD, Wong SC. Characterizing the role of monocytes in T cell cancer immunotherapy using a 3D microfluidic model. Front Immunol 2018; 9: 416
CrossRef
Google scholar
|
[245] |
Pavesi A, Tan AT, Koh S, Chia A, Colombo M, Antonecchia E, Miccolis C, Ceccarello E, Adriani G, Raimondi MT, Kamm RD, Bertoletti A. A 3D microfluidic model for preclinical evaluation of TCR-engineered T cells against solid tumors. JCI Insight 2017; 2(12): e89762
CrossRef
Google scholar
|
[246] |
Rosenberg SA, Packard BS, Aebersold PM, Solomon D, Topalian SL, Toy ST, Simon P, Lotze MT, Yang JC, Seipp CA, Simpson C, Carter C, Bock S, Schwartzentruber D, Wei JP, White DE. Use of tumor-infiltrating lymphocytes and interleukin-2 in the immunotherapy of patients with metastatic melanoma. A preliminary report. N Engl J Med 1988; 319(25): 1676–1680
CrossRef
Google scholar
|
[247] |
Dudley ME, Yang JC, Sherry R, Hughes MS, Royal R, Kammula U, Robbins PF, Huang J, Citrin DE, Leitman SF, Wunderlich J, Restifo NP, Thomasian A, Downey SG, Smith FO, Klapper J, Morton K, Laurencot C, White DE, Rosenberg SA. Adoptive cell therapy for patients with metastatic melanoma: evaluation of intensive myeloablative chemoradiation preparative regimens. J Clin Oncol 2008; 26(32): 5233–5239
CrossRef
Google scholar
|
[248] |
Kvistborg P, Shu CJ, Heemskerk B, Fankhauser M, Thrue CA, Toebes M, van Rooij N, Linnemann C, van Buuren MM, Urbanus JH, Beltman JB, Thor Straten P, Li YF, Robbins PF, Besser MJ, Schachter J, Kenter GG, Dudley ME, Rosenberg SA, Haanen JB, Hadrup SR, Schumacher TN. TIL therapy broadens the tumor-reactive CD8+ T cell compartment in melanoma patients. OncoImmunology 2012; 1(4): 409–418
CrossRef
Google scholar
|
[249] |
Schumacher TN, Schreiber RD. Neoantigens in cancer immunotherapy. Science 2015; 348(6230): 69–74
CrossRef
Google scholar
|
[250] |
Zhao Y, Deng J, Rao S, Guo S, Shen J, Du F, Wu X, Chen Y, Li M, Chen M, Li X, Li W, Gu L, Sun Y, Zhang Z, Wen Q, Xiao Z, Li J. Tumor infiltrating lymphocyte (TIL) therapy for solid tumor treatment: progressions and challenges. Cancers (Basel) 2022; 14(17): 4160
CrossRef
Google scholar
|
[251] |
Tran E, Robbins PF, Lu YC, Prickett TD, Gartner JJ, Jia L, Pasetto A, Zheng Z, Ray S, Groh EM, Kriley IR, Rosenberg SA. T-cell transfer therapy targeting mutant kras in cancer. N Engl J Med 2016; 375(23): 2255–2262
CrossRef
Google scholar
|
[252] |
Creelan BC, Wang C, Teer JK, Toloza EM, Yao J, Kim S, Landin AM, Mullinax JE, Saller JJ, Saltos AN, Noyes DR, Montoya LB, Curry W, Pilon-Thomas SA, Chiappori AA, Tanvetyanon T, Kaye FJ, Thompson ZJ, Yoder SJ, Fang B, Koomen JM, Sarnaik AA, Chen DT, Conejo-Garcia JR, Haura EB, Antonia SJ. Tumor-infiltrating lymphocyte treatment for anti-PD-1-resistant metastatic lung cancer: a phase 1 trial. Nat Med 2021; 27(8): 1410–1418
CrossRef
Google scholar
|
[253] |
Augustin RC, Leone RD, Naing A, Fong L, Bao R, Luke JJ. Next steps for clinical translation of adenosine pathway inhibition in cancer immunotherapy. J Immunother Cancer 2022; 10(2): e004089
CrossRef
Google scholar
|
[254] |
Leone RD, Emens LA. Targeting adenosine for cancer immunotherapy. J Immunother Cancer 2018; 6(1): 57
CrossRef
Google scholar
|
[255] |
Apasov S, Koshiba M, Redegeld F, Sitkovsky MV. Role of extracellular ATP and P1 and P2 classes of purinergic receptors in T-cell development and cytotoxic T lymphocyte effector functions. Immunol Rev 1995; 146(1): 5–19
CrossRef
Google scholar
|
[256] |
Apasov SG, Koshiba M, Chused TM, Sitkovsky MV. Effects of extracellular ATP and adenosine on different thymocyte subsets: possible role of ATP-gated channels and G protein-coupled purinergic receptor. J Immunol 1997; 158(11): 5095–5105
CrossRef
Google scholar
|
[257] |
Filippini A, Taffs RE, Agui T, Sitkovsky MV. Ecto-ATPase activity in cytolytic T-lymphocytes. Protection from the cytolytic effects of extracellular ATP. J Biol Chem 1990; 265(1): 334–340
CrossRef
Google scholar
|
[258] |
Ohta A, Gorelik E, Prasad SJ, Ronchese F, Lukashev D, Wong MK, Huang X, Caldwell S, Liu K, Smith P, Chen JF, Jackson EK, Apasov S, Abrams S, Sitkovsky M. A2A adenosine receptor protects tumors from antitumor T cells. Proc Natl Acad Sci USA 2006; 103(35): 13132–13137
CrossRef
Google scholar
|
[259] |
Iannone R, Miele L, Maiolino P, Pinto A, Morello S. Adenosine limits the therapeutic effectiveness of anti-CTLA4 mAb in a mouse melanoma model. Am J Cancer Res 2014; 4(2): 172–181
|
[260] |
Mittal D, Young A, Stannard K, Yong M, Teng MW, Allard B, Stagg J, Smyth MJ. Antimetastatic effects of blocking PD-1 and the adenosine A2A receptor. Cancer Res 2014; 74(14): 3652–3658
CrossRef
Google scholar
|
[261] |
Beavis PA, Henderson MA, Giuffrida L, Mills JK, Sek K, Cross RS, Davenport AJ, John LB, Mardiana S, Slaney CY, Johnstone RW, Trapani JA, Stagg J, Loi S, Kats L, Gyorki D, Kershaw MH, Darcy PK. Targeting the adenosine 2A receptor enhances chimeric antigen receptor T cell efficacy. J Clin Invest 2017; 127(3): 929–941
CrossRef
Google scholar
|
[262] |
Sitkovsky MV. Lessons from the A2A adenosine receptor antagonist-enabled tumor regression and survival in patients with treatment-refractory renal cell cancer. Cancer Discov 2020; 10(1): 16–19
CrossRef
Google scholar
|
[263] |
Stagg J, Divisekera U, McLaughlin N, Sharkey J, Pommey S, Denoyer D, Dwyer KM, Smyth MJ. Anti-CD73 antibody therapy inhibits breast tumor growth and metastasis. Proc Natl Acad Sci USA 2010; 107(4): 1547–1552
CrossRef
Google scholar
|
[264] |
Stagg J, Beavis PA, Divisekera U, Liu MC, Möller A, Darcy PK, Smyth MJ. CD73-deficient mice are resistant to carcinogenesis. Cancer Res 2012; 72(9): 2190–2196
CrossRef
Google scholar
|
[265] |
Terp MG, Olesen KA, Arnspang EC, Lund RR, Lagerholm BC, Ditzel HJ, Leth-Larsen R. Anti-human CD73 monoclonal antibody inhibits metastasis formation in human breast cancer by inducing clustering and internalization of CD73 expressed on the surface of cancer cells. J Immunol 2013; 191(8): 4165–4173
CrossRef
Google scholar
|
[266] |
Leclerc BG, Charlebois R, Chouinard G, Allard B, Pommey S, Saad F, Stagg J. CD73 expression is an independent prognostic factor in prostate cancer. Clin Cancer Res 2016; 22(1): 158–166
CrossRef
Google scholar
|
[267] |
Loi S, Pommey S, Haibe-Kains B, Beavis PA, Darcy PK, Smyth MJ, Stagg J. CD73 promotes anthracycline resistance and poor prognosis in triple negative breast cancer. Proc Natl Acad Sci USA 2013; 110(27): 11091–11096
CrossRef
Google scholar
|
[268] |
Gaudreau PO, Allard B, Turcotte M, Stagg J. CD73-adenosine reduces immune responses and survival in ovarian cancer patients. OncoImmunology 2016; 5(5): e1127496
CrossRef
Google scholar
|
[269] |
Wu XR, He XS, Chen YF, Yuan RX, Zeng Y, Lian L, Zou YF, Lan N, Wu XJ, Lan P. High expression of CD73 as a poor prognostic biomarker in human colorectal cancer. J Surg Oncol 2012; 106(2): 130–137
CrossRef
Google scholar
|
[270] |
Morello S, Capone M, Sorrentino C, Giannarelli D, Madonna G, Mallardo D, Grimaldi AM, Pinto A, Ascierto PA. Soluble CD73 as biomarker in patients with metastatic melanoma patients treated with nivolumab. J Transl Med 2017; 15(1): 244
CrossRef
Google scholar
|
[271] |
Herbst RS, Majem M, Barlesi F, Carcereny E, Chu Q, Monnet I, Sanchez-Hernandez A, Dakhil S, Camidge DR, Winzer L, Soo-Hoo Y, Cooper ZA, Kumar R, Bothos J, Aggarwal C, Martinez-Marti A. COAST: an open-label, phase II, multidrug platform study of durvalumab alone or in combination with oleclumab or monalizumab in patients with unresectable, stage III non-small-cell lung cancer. J Clin Oncol 2022; 40(29): 3383–3393
CrossRef
Google scholar
|
[272] |
Ohta A. A Metabolic immune checkpoint: adenosine in tumor microenvironment. Front Immunol 2016; 7: 109
CrossRef
Google scholar
|
[273] |
Bonnefoy N, Bastid J, Alberici G, Bensussan A, Eliaou JF. CD39: a complementary target to immune checkpoints to counteract tumor-mediated immunosuppression. OncoImmunology 2015; 4(5): e1003015
CrossRef
Google scholar
|
[274] |
Deaglio S, Dwyer KM, Gao W, Friedman D, Usheva A, Erat A, Chen JF, Enjyoji K, Linden J, Oukka M, Kuchroo VK, Strom TB, Robson SC. Adenosine generation catalyzed by CD39 and CD73 expressed on regulatory T cells mediates immune suppression. J Exp Med 2007; 204(6): 1257–1265
CrossRef
Google scholar
|
[275] |
Sun X, Wu Y, Gao W, Enjyoji K, Csizmadia E, Müller CE, Murakami T, Robson SC. CD39/ENTPD1 expression by CD4+Foxp3+ regulatory T cells promotes hepatic metastatic tumor growth in mice. Gastroenterology 2010; 139(3): 1030–1040
CrossRef
Google scholar
|
[276] |
Michaud M, Martins I, Sukkurwala AQ, Adjemian S, Ma Y, Pellegatti P, Shen S, Kepp O, Scoazec M, Mignot G, Rello-Varona S, Tailler M, Menger L, Vacchelli E, Galluzzi L, Ghiringhelli F, di Virgilio F, Zitvogel L, Kroemer G. Autophagy-dependent anticancer immune responses induced by chemotherapeutic agents in mice. Science 2011; 334(6062): 1573–1577
CrossRef
Google scholar
|
[277] |
Cai XY, Ni XC, Yi Y, He HW, Wang JX, Fu YP, Sun J, Zhou J, Cheng YF, Jin JJ, Fan J, Qiu SJ. Overexpression of CD39 in hepatocellular carcinoma is an independent indicator of poor outcome after radical resection. Medicine (Baltimore) 2016; 95(40): e4989
CrossRef
Google scholar
|
[278] |
Cai XY, Wang XF, Li J, Dong JN, Liu JQ, Li NP, Yun B, Xia RL, Qin J, Sun YH. High expression of CD39 in gastric cancer reduces patient outcome following radical resection. Oncol Lett 2016; 12(5): 4080–4086
CrossRef
Google scholar
|
[279] |
Perry C, Hazan-Halevy I, Kay S, Cipok M, Grisaru D, Deutsch V, Polliack A, Naparstek E, Herishanu Y. Increased CD39 expression on CD4+ T lymphocytes has clinical and prognostic significance in chronic lymphocytic leukemia. Ann Hematol 2012; 91(8): 1271–1279
CrossRef
Google scholar
|
[280] |
Colak S, Ten Dijke P. Targeting TGF-β signaling in cancer. Trends Cancer 2017; 3(1): 56–71
CrossRef
Google scholar
|
[281] |
Tauriello DVF, Palomo-Ponce S, Stork D, Berenguer-Llergo A, Badia-Ramentol J, Iglesias M, Sevillano M, Ibiza S, Cañellas A, Hernando-Momblona X, Byrom D, Matarin JA, Calon A, Rivas EI, Nebreda AR, Riera A, Attolini CS, Batlle E. TGFβ drives immune evasion in genetically reconstituted colon cancer metastasis. Nature 2018; 554(7693): 538–543
CrossRef
Google scholar
|
[282] |
Huang CY, Chung CL, Hu TH, Chen JJ, Liu PF, Chen CL. Recent progress in TGF-β inhibitors for cancer therapy. Biomed Pharmacother 2021; 134: 111046
CrossRef
Google scholar
|
[283] |
Fang C, Lin J, Zhang T, Luo J, Nie D, Li M, Hu X, Zheng Y, Huang X, Xiao Z. Metastatic colorectal cancer patient with microsatellite stability and BRAFV600E mutation showed a complete metabolic response to PD-1 blockade and bevacizumab: a case report. Front Oncol 2021; 11: 652394
CrossRef
Google scholar
|
[284] |
Knudson KM, Hicks KC, Luo X, Chen JQ, Schlom J, Gameiro SR. M7824, a novel bifunctional anti-PD-L1/TGFβ Trap fusion protein, promotes anti-tumor efficacy as monotherapy and in combination with vaccine. OncoImmunology 2018; 7(5): e1426519
CrossRef
Google scholar
|
[285] |
Tan B, Khattak A, Felip E, Kelly K, Rich P, Wang D, Helwig C, Dussault I, Ojalvo LS, Isambert N. Bintrafusp Alfa, a bifunctional fusion protein targeting TGF-β and PD-L1, in patients with esophageal adenocarcinoma: results from a phase 1 cohort. Target Oncol 2021; 16(4): 435–446
CrossRef
Google scholar
|
[286] |
Zamanakou M, Germenis AE, Karanikas V. Tumor immune escape mediated by indoleamine 2,3-dioxygenase. Immunol Lett 2007; 111(2): 69–75
CrossRef
Google scholar
|
[287] |
Zhu MMT, Dancsok AR, Nielsen TO. Indoleamine dioxygenase inhibitors: clinical rationale and current development. Curr Oncol Rep 2019; 21(1): 2
CrossRef
Google scholar
|
[288] |
Tang S, Ning Q, Yang L, Mo Z, Tang S. Mechanisms of immune escape in the cancer immune cycle. Int Immunopharmacol 2020; 86: 106700
CrossRef
Google scholar
|
[289] |
Holmgaard RB, Zamarin D, Li Y, Gasmi B, Munn DH, Allison JP, Merghoub T, Wolchok JD. Tumor-expressed IDO recruits and activates MDSCs in a Treg-dependent manner. Cell Rep 2015; 13(2): 412–424
CrossRef
Google scholar
|
[290] |
Blair AB, Kleponis J, Thomas DL 2nd, Muth ST, Murphy AG, Kim V, Zheng L. IDO1 inhibition potentiates vaccine-induced immunity against pancreatic adenocarcinoma. J Clin Invest 2019; 129(4): 1742–1755
CrossRef
Google scholar
|
[291] |
Holmgaard RB, Zamarin D, Munn DH, Wolchok JD, Allison JP. Indoleamine 2,3-dioxygenase is a critical resistance mechanism in antitumor T cell immunotherapy targeting CTLA-4. J Exp Med 2013; 210(7): 1389–1402
CrossRef
Google scholar
|
[292] |
Muller AJ, DuHadaway JB, Donover PS, Sutanto-Ward E, Prendergast GC. Inhibition of indoleamine 2,3-dioxygenase, an immunoregulatory target of the cancer suppression gene Bin1, potentiates cancer chemotherapy. Nat Med 2005; 11(3): 312–319
CrossRef
Google scholar
|
[293] |
Spranger S, Koblish HK, Horton B, Scherle PA, Newton R, Gajewski TF. Mechanism of tumor rejection with doublets of CTLA-4, PD-1/PD-L1, or IDO blockade involves restored IL-2 production and proliferation of CD8+ T cells directly within the tumor microenvironment. J Immunother Cancer 2014; 2(1): 3
CrossRef
Google scholar
|
[294] |
Uyttenhove C, Pilotte L, Théate I, Stroobant V, Colau D, Parmentier N, Boon T, Van den Eynde BJ. Evidence for a tumoral immune resistance mechanism based on tryptophan degradation by indoleamine 2,3-dioxygenase. Nat Med 2003; 9(10): 1269–1274
CrossRef
Google scholar
|
[295] |
Long GV, Dummer R, Hamid O, Gajewski TF, Caglevic C, Dalle S, Arance A, Carlino MS, Grob JJ, Kim TM, Demidov L, Robert C, Larkin J, Anderson JR, Maleski J, Jones M, Diede SJ, Mitchell TC. Epacadostat plus pembrolizumab versus placebo plus pembrolizumab in patients with unresectable or metastatic melanoma (ECHO-301/KEYNOTE-252): a phase 3, randomised, double-blind study. Lancet Oncol 2019; 20(8): 1083–1097
CrossRef
Google scholar
|
[296] |
Stanta G, Bonin S. Overview on clinical relevance of intra-tumor heterogeneity. Front Med (Lausanne) 2018; 5: 85
CrossRef
Google scholar
|
/
〈 | 〉 |