Table Info

Table 5.

Clinical trials investigating neoantigen-based immunotherapies

Therapy type	Cancer type(s)	Trial identifier(s)	Therapy combinations	Key outcomes/endpoints
Neoantigen-directed cancer vaccines
Dendritic cell (DC) vaccine	Melanoma	NCT00683670		Induction of neoantigen-specific T cells
Synthetic long peptide (SLP) vaccine	Melanoma	NCT01970358, NCT02035956		No evidence of disease (NED) in some patients, recurrence in others; response to PD-1 therapy
SLP vaccine (GAPVAC)	Glioblastoma	NCT02149225, NCT02287428		Increased neoantigen-specific T cell response
Ribonucleic acid (RNA) vaccine (IVAC MUTANOME)	Melanoma	NCT02035956		Induction of neoantigen-specific T cells
SLP vaccine (NEO-PV-01)	NSCLC	NCT03380871	Anti-PD-1 & Chemotherapy	Induction of neoantigen-specific T cells
Adenoviral & self-amplifying messenger RNA (samRNA) vectors	Microsatellite-Stable colorectal cancer (MSS-CRC), gastroesophageal adenocarcinoma (GEAC), NSCLC	NCT03639714	Anti-PD-1	One complete response (CR) (GEAC); neoantigen-specific T cell induction
Neoantigen-directed adoptive cell transfer (ACT)
Tumor-infiltrating lymphocyte adoptive cell transfer (TIL-ACT)	Cholangiocarcinoma	NCT01174121	Anti-PD-1	Durable response (~9 years) after retreatment with TIL-ACT
	MSS-CRC	NCT01174121		Regression of all metastases
	Breast cancer	NCT01174121		One CR (>5 years), partial response (PR) in others
T cell receptor-engineered adoptive cell transfer (TCR-ACT)	Pancreatic cancer	NCT04146298		PR, metastasis regression at 6 months
T cell receptor-engineered T cell therapy (TCR-T)
TCR-T	Multiple solid tumors	NCT05194735, NCT05105815, NCT04625205, NCT03171220, NCT05020119		Safety, overall response rate (ORR), disease-free survival (DFS) endpoints
	Various cancers	NCT04102436, NCT04596033, NCT02280811, NCT02858310	Chemotherapy	Response rate, adverse events (AEs), dose-limiting toxicities (DLTs)
	Solid tumors	NCT05349890, NCT04520711, NCT03970382	Immune checkpoint blockade (ICB)	Safety, tolerability, DLTs
	Multiple tumors	NCT03412877, NCT04536922	ICB & Chemotherapy	Response rate, treatment effect
	Hepatocellular carcinoma	NCT03199807	Radiotherapy	AEs
Tumor-infiltrating lymphocytes (TILs)
TIL therapy	Solid tumors	NCT05141474		AEs, serious adverse events (SAEs), treatment-limiting toxicity (TLT)
TILs	Gastrointestinal (GI) & pancreatic cancers	NCT04426669, NCT03658785, NCT02959905	Chemotherapy	Maximum tolerated dose (MTD), ORR, AEs
TILs	Melanoma, NSCLC	NCT03997474, NCT04032847	ICB	AEs
TILs	NSCLC, squamous cell carcinoma (SCC), adenosquamous carcinoma	NCT03215810	ICB & chemotherapy	DLTs
Chimeric antigen receptor t cell therapy (CAR-T)
CAR-T	Glioblastoma multiforme	NCT02844062	Chemotherapy	Safety
Immune checkpoint blockade (ICB) therapy
ICB monotherapy	Various cancers	NCT03600155, NCT02553642, NCT03827044, NCT03718767, NCT03925246, NCT03082534, NCT03357757, NCT03813394, NCT02437279, NCT04825990, NCT03130764, NCT03653052, NCT02113657, NCT03040791, NCT04019964, NCT04293419, NCT04262089		Clinical response, safety, DFS, ORR, progression-free survival (PFS)
ICB	Various cancers	NCT04214249, NCT03978624, NCT02990845, NCT02453620, NCT03409198, NCT05456165, NCT05201612, NCT03832621, NCT03186326, NCT04659382, NCT04262687, NCT05141721, NCT04014530, NCT03918499, NCT03655002, NCT03126812, NCT03554317, NCT04336943, NCT04068194, NCT05317000, NCT02883062	Chemotherapy	Clinical response, MTD, AEs, PFS, ORR
ICB	Cutaneous T-cell lymphoma	NCT03385226	Radiotherapy	ORR
ICB	Colorectal cancer, meningioma, rectal cancer	NCT03854799, NCT03604978, NCT04340401	Chemotherapy & radiotherapy	Pathologic response, MTD, ORR, AEs

Declarations

Author contributions

MMN: Conceptualization, Writing—original draft, Writing—review & editing. OAA: Writing—original draft, Writing—review & editing. SG: Writing—original draft. VB: Writing—review & editing. All authors read and approved the submitted version.

Conflicts of interest

The authors declare there are no conflicts of interest.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent to publication

Not applicable.

Availability of data and materials

Not applicable.

Funding

Not applicable.

Copyright

Publisher’s note

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References

Denis MM, Tolley ND, Bunting M, Schwertz H, Jiang H, Lindemann S, et al. Escaping the nuclear confines: signal-dependent pre-mRNA splicing in anucleate platelets. Cell. 2005;122:379–91. [DOI] [PubMed] [PMC]

Wang Y, Liu J, Huang BO, Xu Y, Li J, Huang L, et al. Mechanism of alternative splicing and its regulation. Biomed Rep. 2015;3:152–8. [DOI] [PubMed] [PMC]

Peng Q, Zhou Y, Oyang L, Wu N, Tang Y, Su M, et al. Impacts and mechanisms of alternative mRNA splicing in cancer metabolism, immune response, and therapeutics. Mol Ther. 2022;30:1018–35. [DOI] [PubMed] [PMC]

Baralle FE, Giudice J. Alternative splicing as a regulator of development and tissue identity. Nat Rev Mol Cell Biol. 2017;18:437–51. [DOI] [PubMed] [PMC]

Jiang W, Chen L. Alternative splicing: Human disease and quantitative analysis from high-throughput sequencing. Comput Struct Biotechnol J. 2020;19:183–95. [DOI] [PubMed] [PMC]

Choi S, Cho N, Kim E, Kim KK. The role of alternative pre-mRNA splicing in cancer progression. Cancer Cell Int. 2023;23:249. [DOI] [PubMed] [PMC]

Choi S, Cho N, Kim KK. The implications of alternative pre-mRNA splicing in cell signal transduction. Exp Mol Med. 2023;55:755–66. [DOI] [PubMed] [PMC]

Cui L, Zheng Y, Xu R, Lin Y, Zheng J, Lin P, et al. Alternative pre-mRNA splicing in stem cell function and therapeutic potential: A critical review of current evidence. Int J Biol Macromol. 2024;268:131781. [DOI] [PubMed]

Xie N, Shen G, Gao W, Huang Z, Huang C, Fu L. Neoantigens: promising targets for cancer therapy. Signal Transduct Target Ther. 2023;8:9. [DOI] [PubMed] [PMC]

10.

Guan H, Wu Y, Li LU, Yang Y, Qiu S, Zhao Z, et al. Tumor neoantigens: Novel strategies for application of cancer immunotherapy. Oncol Res. 2023;31:437–48. [DOI] [PubMed] [PMC]

11.

Yarchoan M, 3rd BAJ, Lutz ER, Laheru DA, Jaffee EM. Targeting neoantigens to augment antitumour immunity. Nat Rev Cancer. 2017;17:209–22. [DOI] [PubMed] [PMC]

12.

Peng M, Mo Y, Wang Y, Wu P, Zhang Y, Xiong F, et al. Neoantigen vaccine: an emerging tumor immunotherapy. Mol Cancer. 2019;18:128. [DOI] [PubMed] [PMC]

13.

Lang F, Schrörs B, Löwer M, Türeci Ö, Sahin U. Identification of neoantigens for individualized therapeutic cancer vaccines. Nat Rev Drug Discov. 2022;21:261–82. [DOI] [PubMed] [PMC]

14.

Zhu Y, Qian Y, Li Z, Li Y, Li B. Neoantigen-reactive T cell: An emerging role in adoptive cellular immunotherapy. MedComm (2020). 2021;2:207–20. [DOI] [PubMed] [PMC]

15.

Mardis ER. The Impact of Next-Generation Sequencing on Cancer Genomics: From Discovery to Clinic. Cold Spring Harb Perspect Med. 2019;9:a036269. [DOI] [PubMed] [PMC]

16.

Román ÁC, Benítez DA, Díaz-Pizarro A, Del Valle-Del Pino N, Olivera-Gómez M, Cumplido-Laso G, et al. Next generation sequencing technologies to address aberrant mRNA translation in cancer. NAR Cancer. 2024;6:zcae024. [DOI] [PubMed] [PMC]

17.

Nielsen M, Andreatta M, Peters B, Buus S. Immunoinformatics: Predicting Peptide-MHC Binding. Annu Rev Biomed Data Sci. 2020;3:191–215. [DOI] [PubMed] [PMC]

18.

Attermann AS, Barra C, Reynisson B, Schultz HS, Leurs U, Lamberth K, et al. Improved prediction of HLA antigen presentation hotspots: Applications for immunogenicity risk assessment of therapeutic proteins. Immunology. 2021;162:208–19. [DOI] [PubMed] [PMC]

19.

Rominiyi O, Vanderlinden A, Clenton SJ, Bridgewater C, Al-Tamimi Y, Collis SJ. Tumour treating fields therapy for glioblastoma: current advances and future directions. Br J Cancer. 2021;124:697–709. [DOI] [PubMed] [PMC]

20.

Angom RS, Nakka NMR, Bhattacharya S. Advances in Glioblastoma Therapy: An Update on Current Approaches. Brain Sci. 2023;13:1536. [DOI] [PubMed] [PMC]

21.

Yu MW, Quail DF. Immunotherapy for Glioblastoma: Current Progress and Challenges. Front Immunol. 2021;12:676301. [DOI] [PubMed] [PMC]

22.

Nelson TA, Dietrich J. Investigational treatment strategies in glioblastoma: progress made and barriers to success. Expert Opin Investig Drugs. 2023;32:921–30. [DOI] [PubMed] [PMC]

23.

Latzer P, Zelba H, Battke F, Reinhardt A, Shao B, Bartsch O, et al. A real-world observation of patients with glioblastoma treated with a personalized peptide vaccine. Nat Commun. 2024;15:6870. [DOI] [PubMed] [PMC]

24.

Bernstock JD, Hoffman SE, Kappel AD, Valdes PA, Essayed W, Klinger NV, et al. Immunotherapy approaches for the treatment of diffuse midline gliomas. Oncoimmunology. 2022;11:2124058. [DOI] [PubMed] [PMC]

25.

van den Bent M, Saratsis AM, Geurts M, Franceschi E. H3 K27M-altered glioma and diffuse intrinsic pontine glioma: Semi-systematic review of treatment landscape and future directions. Neuro Oncol. 2024;26:S110–24. [DOI] [PubMed] [PMC]

26.

Zolkind P, Dunn GP, Lin T, Griffith M, Griffith OL, Uppaluri R. Neoantigens in immunotherapy and personalized vaccines: Implications for head and neck squamous cell carcinoma. Oral Oncol. 2017;71:169–76. [DOI] [PubMed] [PMC]

27.

Ward JP, Gubin MM, Schreiber RD. The Role of Neoantigens in Naturally Occurring and Therapeutically Induced Immune Responses to Cancer. Adv Immunol. 2016;130:25–74. [DOI] [PubMed] [PMC]

28.

Castro A, Zanetti M, Carter H. Neoantigen Controversies. Annu Rev Biomed Data Sci. 2021;4:227–53. [DOI] [PubMed] [PMC]

29.

Roerden M, Castro AB, Cui Y, Harake N, Kim B, Dye J, et al. Neoantigen architectures define immunogenicity and drive immune evasion of tumors with heterogenous neoantigen expression. J Immunother Cancer. 2024;12:e010249. [DOI] [PubMed] [PMC]

30.

Kim SH, Lee BR, Kim SM, Kim S, Kim MS, Kim J, et al. The identification of effective tumor-suppressing neoantigens using a tumor-reactive TIL TCR-pMHC ternary complex. Exp Mol Med. 2024;56:1461–71. [DOI] [PubMed] [PMC]

31.

Yin Q, Tang J, Zhu X. Next-generation sequencing technologies accelerate advances in T-cell therapy for cancer. Brief Funct Genomics. 2019;18:119–28. [DOI] [PubMed] [PMC]

32.

Marcus A, Gowen BG, Thompson TW, Iannello A, Ardolino M, Deng W, et al. Recognition of tumors by the innate immune system and natural killer cells. Adv Immunol. 2014;122:91–128. [DOI] [PubMed] [PMC]

33.

Javier RT, Butel JS. The history of tumor virology. Cancer Res. 2008;68:7693–706. [DOI] [PubMed] [PMC]

34.

Sim MJW, Sun PD. T Cell Recognition of Tumor Neoantigens and Insights Into T Cell Immunotherapy. Front Immunol. 2022;13:833017. [DOI] [PubMed] [PMC]

35.

Ashi MO, Mami-Chouaib F, Corgnac S. Mutant and non-mutant neoantigen-based cancer vaccines: recent advances and future promises. Explor Target Antitumor Ther. 2022;3:746–62. [DOI] [PubMed] [PMC]

36.

Okada M, Shimizu K, Fujii SI. Identification of Neoantigens in Cancer Cells as Targets for Immunotherapy. Int J Mol Sci. 2022;23:2594. [DOI] [PubMed] [PMC]

37.

Veatch JR, Jesernig BL, Kargl J, Fitzgibbon M, Lee SM, Baik C, et al. Endogenous CD4⁺ T Cells Recognize Neoantigens in Lung Cancer Patients, Including Recurrent Oncogenic KRAS and ERBB2 (Her2) Driver Mutations. Cancer Immunol Res. 2019;7:910–22. [DOI] [PubMed] [PMC]

38.

Gros A, Parkhurst MR, Tran E, Pasetto A, Robbins PF, Ilyas S, et al. Prospective identification of neoantigen-specific lymphocytes in the peripheral blood of melanoma patients. Nat Med. 2016;22:433–8. [DOI] [PubMed] [PMC]

39.

Hu Z, Leet DE, Allesøe RL, Oliveira G, Li S, Luoma AM, et al. Personal neoantigen vaccines induce persistent memory T cell responses and epitope spreading in patients with melanoma. Nat Med. 2021;27:515–25. [DOI] [PubMed] [PMC]

40.

Biswas N, Chakrabarti S, Padul V, Jones LD, Ashili S. Designing neoantigen cancer vaccines, trials, and outcomes. Front Immunol. 2023;14:1105420. [DOI] [PubMed] [PMC]

41.

De Mattos-Arruda L, Vazquez M, Finotello F, Lepore R, Porta E, Hundal J, et al. Neoantigen prediction and computational perspectives towards clinical benefit: recommendations from the ESMO Precision Medicine Working Group. Ann Oncol. 2020;31:978–90. [DOI] [PubMed] [PMC]

42.

Ebrahimi N, Akbari M, Ghanaatian M, Roozbahani Moghaddam P, Adelian S, Borjian Boroujeni M, et al. Development of neoantigens: from identification in cancer cells to application in cancer vaccines. Expert Rev Vaccines. 2022;21:941–55. [DOI] [PubMed]

43.

Davis L, Tarduno A, Lu YC. Neoantigen-Reactive T Cells: The Driving Force behind Successful Melanoma Immunotherapy. Cancers (Basel). 2021;13:6061. [DOI] [PubMed] [PMC]

44.

Yossef R, Tran E, Deniger DC, Gros A, Pasetto A, Parkhurst MR, et al. Enhanced detection of neoantigen-reactive T cells targeting unique and shared oncogenes for personalized cancer immunotherapy. JCI Insight. 2018;3:e122467. [DOI] [PubMed] [PMC]

45.

Cafri G, Gartner JJ, Zaks T, Hopson K, Levin N, Paria BC, et al. mRNA vaccine-induced neoantigen-specific T cell immunity in patients with gastrointestinal cancer. J Clin Invest. 2020;130:5976–88. [DOI] [PubMed] [PMC]

46.

Eshkiki ZS, Agah S, Tabaeian SP, Sedaghat M, Dana F, Talebi A, et al. Neoantigens and their clinical applications in human gastrointestinal cancers. World J Surg Oncol. 2022;20:321. [DOI] [PubMed] [PMC]

47.

Mørk SK, Kadivar M, Bol KF, Draghi A, Westergaard MCW, Skadborg SK, et al. Personalized therapy with peptide-based neoantigen vaccine (EVX-01) including a novel adjuvant, CAF^®09b, in patients with metastatic melanoma. Oncoimmunology. 2022;11:2023255. [DOI] [PubMed] [PMC]

48.

Ott PA, Hu Z, Keskin DB, Shukla SA, Sun J, Bozym DJ, et al. An immunogenic personal neoantigen vaccine for patients with melanoma. Nature. 2017;547:217–21. [DOI] [PubMed] [PMC]

49.

Zhu G, Pei L, Xia H, Tang Q, Bi F. Role of oncogenic KRAS in the prognosis, diagnosis and treatment of colorectal cancer. Mol Cancer. 2021;20:143. [DOI] [PubMed] [PMC]

50.

Sahin IH, Saridogan T, Ayasun R, Syed MP, Gorantla V, Malhotra M, et al. Targeting KRAS Oncogene for Patients With Colorectal Cancer: A New Step Toward Precision Medicine. JCO Oncol Pract. 2024;20:1336–47. [DOI] [PubMed]

51.

Ott PA, Hu-Lieskovan S, Chmielowski B, Govindan R, Naing A, Bhardwaj N, et al. A Phase Ib Trial of Personalized Neoantigen Therapy Plus Anti-PD-1 in Patients with Advanced Melanoma, Non-small Cell Lung Cancer, or Bladder Cancer. Cell. 2020;183:347–62.e24. [DOI] [PubMed]

52.

Chen X, Yang J, Wang L, Liu B. Personalized neoantigen vaccination with synthetic long peptides: recent advances and future perspectives. Theranostics. 2020;10:6011–23. [DOI] [PubMed] [PMC]

53.

Boisguérin V, Castle JC, Loewer M, Diekmann J, Mueller F, Britten CM, et al. Translation of genomics-guided RNA-based personalised cancer vaccines: towards the bedside. Br J Cancer. 2014;111:1469–75. [DOI] [PubMed] [PMC]

54.

Roudko V, Greenbaum B, Bhardwaj N. Computational Prediction and Validation of Tumor-Associated Neoantigens. Front Immunol. 2020;11:27. [DOI] [PubMed] [PMC]

55.

Mardis ER. Neoantigens and genome instability: impact on immunogenomic phenotypes and immunotherapy response. Genome Med. 2019;11:71. [DOI] [PubMed] [PMC]

56.

Diederichs S, Bartsch L, Berkmann JC, Fröse K, Heitmann J, Hoppe C, et al. The dark matter of the cancer genome: aberrations in regulatory elements, untranslated regions, splice sites, non-coding RNA and synonymous mutations. EMBO Mol Med. 2016;8:442–57. [DOI] [PubMed] [PMC]

57.

Richters MM, Xia H, Campbell KM, Gillanders WE, Griffith OL, Griffith M. Best practices for bioinformatic characterization of neoantigens for clinical utility. Genome Med. 2019;11:56. [DOI] [PubMed] [PMC]

58.

Lee M Jr, Ahmad SF, Xu J. Regulation and function of transposable elements in cancer genomes. Cell Mol Life Sci. 2024;81:157. [DOI] [PubMed] [PMC]

59.

Kassiotis G. Endogenous retroviruses and the development of cancer. J Immunol. 2014;192:1343–9. [DOI] [PubMed] [PMC]

60.

Dadush A, Merdler-Rabinowicz R, Gorelik D, Feiglin A, Buchumenski I, Pal LR, et al. DNA and RNA base editors can correct the majority of pathogenic single nucleotide variants. NPJ Genom Med. 2024;9:16. [DOI] [PubMed] [PMC]

61.

Lehner K, Mudrak SV, Minesinger BK, Jinks-Robertson S. Frameshift mutagenesis: the roles of primer-template misalignment and the nonhomologous end-joining pathway in Saccharomyces cerevisiae. Genetics. 2012;190:501–10. [DOI] [PubMed] [PMC]

62.

Roudko V, Bozkus CC, Orfanelli T, McClain CB, Carr C, O'Donnell T, et al. Shared Immunogenic Poly-Epitope Frameshift Mutations in Microsatellite Unstable Tumors. Cell. 2020;183:1634–1649.e17. [DOI] [PubMed] [PMC]

63.

Mistretta B, Rankothgedera S, Castillo M, Rao M, Holloway K, Bhardwaj A, et al. Chimeric RNAs reveal putative neoantigen peptides for developing tumor vaccines for breast cancer. Front Immunol. 2023;14:1188831. [DOI] [PubMed] [PMC]

64.

Liu S, Heumüller SE, Hossinger A, Müller SA, Buravlova O, Lichtenthaler SF, et al. Reactivated endogenous retroviruses promote protein aggregate spreading. Nat Commun. 2023;14:5034. [DOI] [PubMed] [PMC]

65.

Russ E, Iordanskiy S. Endogenous Retroviruses as Modulators of Innate Immunity. Pathogens. 2023;12:162. [DOI] [PubMed] [PMC]

66.

Sciarrillo R, Wojtuszkiewicz A, Assaraf YG, Jansen G, Kaspers GJL, Giovannetti E, et al. The role of alternative splicing in cancer: From oncogenesis to drug resistance. Drug Resist Updat. 2020;53:100728. [DOI] [PubMed]

67.

Dvinge H, Bradley RK. Widespread intron retention diversifies most cancer transcriptomes. Genome Med. 2015;7:45. [DOI] [PubMed] [PMC]

68.

Lee Y, Gamazon ER, Rebman E, Lee Y, Lee S, Dolan ME, et al. Variants affecting exon skipping contribute to complex traits. PLoS Genet. 2012;8:e1002998. [DOI] [PubMed] [PMC]

69.

Blazquez L, Emmett W, Faraway R, Pineda JMB, Bajew S, Gohr A, et al. Exon Junction Complex Shapes the Transcriptome by Repressing Recursive Splicing. Mol Cell. 2018;72:496–509.e9. [DOI] [PubMed] [PMC]

70.

Iida N, Okada A, Kobayashi Y, Chiba K, Yatabe Y, Shiraishi Y. Systematically developing a registry of splice-site creating variants utilizing massive publicly available transcriptome sequence data. Nat Commun. 2025;16:426. [DOI] [PubMed] [PMC]

71.

Hujová P, Souček P, Radová L, Kramárek M, Kováčová T, Freiberger T. Nucleotides in both donor and acceptor splice sites are responsible for choice in NAGNAG tandem splice sites. Cell Mol Life Sci. 2021;78:6979–93. [DOI] [PubMed] [PMC]

72.

Zheng JT, Lin CX, Fang ZY, Li HD. Intron Retention as a Mode for RNA-Seq Data Analysis. Front Genet. 2020;11:586. [DOI] [PubMed] [PMC]

73.

Liu Z, Rabadan R. Computing the Role of Alternative Splicing in Cancer. Trends Cancer. 2021;7:347–58. [DOI] [PubMed] [PMC]

74.

Mathur M, Kim CM, Munro SA, Rudina SS, Sawyer EM, Smolke CD. Programmable mutually exclusive alternative splicing for generating RNA and protein diversity. Nat Commun. 2019;10:2673. [DOI] [PubMed] [PMC]

75.

Park E, Pan Z, Zhang Z, Lin L, Xing Y. The Expanding Landscape of Alternative Splicing Variation in Human Populations. Am J Hum Genet. 2018;102:11–26. [DOI] [PubMed] [PMC]

76.

Shamnas V M, Singh A, Kumar A, Mishra GP, Sinha SK. Exitrons: offering new roles to retained introns-the novel regulators of protein diversity and utility. AoB Plants. 2024;16:plae014. [DOI] [PubMed] [PMC]

77.

Srivastava R, Budak G, Dash S, Lachke SA, Janga SC. Transcriptome analysis of developing lens reveals abundance of novel transcripts and extensive splicing alterations. Sci Rep. 2017;7:11572. [DOI] [PubMed] [PMC]

78.

Gabay O, Shoshan Y, Kopel E, Ben-Zvi U, Mann TD, Bressler N, et al. Landscape of adenosine-to-inosine RNA recoding across human tissues. Nat Commun. 2022;13:1184. [DOI] [PubMed] [PMC]

79.

Cheng H, Yu J, Wong CC. Adenosine-to-Inosine RNA editing in cancer: molecular mechanisms and downstream targets. Protein Cell. 2024;pwae039. [DOI] [PubMed]

80.

Othoum G, Maher CA. CrypticProteinDB: an integrated database of proteome and immunopeptidome derived non-canonical cancer proteins. NAR Cancer. 2023;5:zcad024. [DOI] [PubMed] [PMC]

81.

Yang H, Li Q, Stroup EK, Wang S, Ji Z. Widespread stable noncanonical peptides identified by integrated analyses of ribosome profiling and ORF features. Nat Commun. 2024;15:1932. [DOI] [PubMed] [PMC]

82.

Barczak W, Carr SM, Liu G, Munro S, Nicastri A, Lee LN, et al. Long non-coding RNA-derived peptides are immunogenic and drive a potent anti-tumour response. Nat Commun. 2023;14:1078. [DOI] [PubMed] [PMC]

83.

Chen Y, Long W, Yang L, Zhao Y, Wu X, Li M, et al. Functional Peptides Encoded by Long Non-Coding RNAs in Gastrointestinal Cancer. Front Oncol. 2021;11:777374. [DOI] [PubMed] [PMC]

84.

Aparicio B, Theunissen P, Hervas-Stubbs S, Fortes P, Sarobe P. Relevance of mutation-derived neoantigens and non-classical antigens for anticancer therapies. Hum Vaccin Immunother. 2024;20:2303799. [DOI] [PubMed] [PMC]

85.

Li YR, Liu MJ. Prevalence of alternative AUG and non-AUG translation initiators and their regulatory effects across plants. Genome Res. 2020;30:1418–33. [DOI] [PubMed] [PMC]

86.

Wright BW, Yi Z, Weissman JS, Chen J. The dark proteome: translation from noncanonical open reading frames. Trends Cell Biol. 2022;32:243–58. [DOI] [PubMed] [PMC]

87.

Kumar A, Narayanan V, Sekhar A. Characterizing Post-Translational Modifications and Their Effects on Protein Conformation Using NMR Spectroscopy. Biochemistry. 2020;59:57–73. [DOI] [PubMed] [PMC]

88.

Dunphy K, Dowling P, Bazou D, O'Gorman P. Current Methods of Post-Translational Modification Analysis and Their Applications in Blood Cancers. Cancers (Basel). 2021;13:1930. [DOI] [PubMed] [PMC]

89.

Wang TY, Liu Q, Ren Y, Alam SK, Wang L, Zhu Z, et al. A pan-cancer transcriptome analysis of exitron splicing identifies novel cancer driver genes and neoepitopes. Mol Cell. 2021;81:2246–60.e12. [DOI] [PubMed] [PMC]

90.

Öther-Gee Pohl S, Myant KB. Alternative RNA splicing in tumour heterogeneity, plasticity and therapy. Dis Model Mech. 2022;15:dmm049233. [DOI] [PubMed] [PMC]

91.

Lang F, Sorn P, Suchan M, Henrich A, Albrecht C, Köhl N, et al. Prediction of tumor-specific splicing from somatic mutations as a source of neoantigen candidates. Bioinform Adv. 2024;4:vbae080. [DOI] [PubMed] [PMC]

92.

Park J, Chung YJ. Identification of neoantigens derived from alternative splicing and RNA modification. Genomics Inform. 2019;17:e23. [DOI] [PubMed] [PMC]

93.

Zhang Y, Li L, Mendoza JJ, Wang D, Yan Q, Shi L, et al. Advances in A-to-I RNA editing in cancer. Mol Cancer. 2024;23:280. [DOI] [PubMed] [PMC]

94.

Cai Y, Li D, Lv D, Yu J, Ma Y, Jiang T, et al. MHC-I-presented non-canonical antigens expand the cancer immunotherapy targets in acute myeloid leukemia. Sci Data. 2024;11:831. [DOI] [PubMed] [PMC]

95.

Ouspenskaia T, Law T, Clauser KR, Klaeger S, Sarkizova S, Aguet F, et al. Unannotated proteins expand the MHC-I-restricted immunopeptidome in cancer. Nat Biotechnol. 2022;40:209–17. [DOI] [PubMed] [PMC]

96.

Minati R, Perreault C, Thibault P. A Roadmap Toward the Definition of Actionable Tumor-Specific Antigens. Front Immunol. 2020;11:583287. [DOI] [PubMed] [PMC]

97.

Lee TA, Tsai EY, Liu SH, Hsu Hung SD, Chang SJ, Chao CH, et al. Post-translational Modification of PD-1: Potential Targets for Cancer Immunotherapy. Cancer Res. 2024;84:800–7. [DOI] [PubMed] [PMC]

98.

Srivastava AK, Guadagnin G, Cappello P, Novelli F. Post-Translational Modifications in Tumor-Associated Antigens as a Platform for Novel Immuno-Oncology Therapies. Cancers (Basel). 2022;15:138. [DOI] [PubMed] [PMC]

99.

Wirth TC, Kühnel F. Neoantigen Targeting-Dawn of a New Era in Cancer Immunotherapy? Front Immunol. 2017;8:1848. [DOI] [PubMed] [PMC]

100.

Fu D, Calvo JA, Samson LD. Balancing repair and tolerance of DNA damage caused by alkylating agents. Nat Rev Cancer. 2012;12:104–20. [DOI] [PubMed] [PMC]

101.

Peng Y, Pei H. DNA alkylation lesion repair: outcomes and implications in cancer chemotherapy. J Zhejiang Univ Sci B. 2021;22:47–62. [DOI] [PubMed] [PMC]

102.

Cheung-Ong K, Giaever G, Nislow C. DNA-damaging agents in cancer chemotherapy: serendipity and chemical biology. Chem Biol. 2013;20:648–59. [DOI] [PubMed]

103.

Fan T, Zhang M, Yang J, Zhu Z, Cao W, Dong C. Therapeutic cancer vaccines: advancements, challenges, and prospects. Signal Transduct Target Ther. 2023;8:450. [DOI] [PubMed] [PMC]

104.

O'Donnell T, Christie EL, Ahuja A, Buros J, Aksoy BA, Bowtell DDL, et al. Chemotherapy weakly contributes to predicted neoantigen expression in ovarian cancer. BMC Cancer. 2018;18:87. [DOI] [PubMed] [PMC]

105.

Czajkowski D, Szmyd R, Gee HE. Impact of DNA damage response defects in cancer cells on response to immunotherapy and radiotherapy. J Med Imaging Radiat Oncol. 2022;66:546–59. [DOI] [PubMed] [PMC]

106.

Donlon NE, Power R, Hayes C, Reynolds JV, Lysaght J. Radiotherapy, immunotherapy, and the tumour microenvironment: Turning an immunosuppressive milieu into a therapeutic opportunity. Cancer Lett. 2021;502:84–96. [DOI] [PubMed]

107.

Chan Wah Hak CML, Rullan A, Patin EC, Pedersen M, Melcher AA, Harrington KJ. Enhancing anti-tumour innate immunity by targeting the DNA damage response and pattern recognition receptors in combination with radiotherapy. Front Oncol. 2022;12:971959. [DOI] [PubMed] [PMC]

108.

Jungles KM, Holcomb EA, Pearson AN, Jungles KR, Bishop CR, Pierce LJ, et al. Updates in combined approaches of radiotherapy and immune checkpoint inhibitors for the treatment of breast cancer. Front Oncol. 2022;12:1022542. [DOI] [PubMed] [PMC]

109.

Nguyen AT, Shiao SL, McArthur HL. Advances in Combining Radiation and Immunotherapy in Breast Cancer. Clin Breast Cancer. 2021;21:143–52. [DOI] [PubMed] [PMC]

110.

Majeed H, Gupta V. Adverse Effects of Radiation Therapy. Treasure Island (FL): StatPearls Publishing; 2025. [PubMed]

111.

Dalmasso G, Cougnoux A, Delmas J, Darfeuille-Michaud A, Bonnet R. The bacterial genotoxin colibactin promotes colon tumor growth by modifying the tumor microenvironment. Gut Microbes. 2014;5:675–80. [DOI] [PubMed] [PMC]

112.

Dougherty MW, Valdés-Mas R, Wernke KM, Gharaibeh RZ, Yang Y, Brant JO, et al. The microbial genotoxin colibactin exacerbates mismatch repair mutations in colorectal tumors. Neoplasia. 2023;43:100918. [DOI] [PubMed] [PMC]

113.

Ou S, Wang H, Tao Y, Luo K, Ye J, Ran S, et al. Fusobacterium nucleatum and colorectal cancer: From phenomenon to mechanism. Front Cell Infect Microbiol. 2022;12:1020583. [DOI] [PubMed] [PMC]

114.

Ranjbar M, Salehi R, Haghjooy Javanmard S, Rafiee L, Faraji H, Jafarpor S, et al. The dysbiosis signature of Fusobacterium nucleatum in colorectal cancer-cause or consequences? A systematic review. Cancer Cell Int. 2021;21:194. [DOI] [PubMed] [PMC]

115.

Lozenov S, Krastev B, Nikolaev G, Peshevska-Sekulovska M, Peruhova M, Velikova T. Gut Microbiome Composition and Its Metabolites Are a Key Regulating Factor for Malignant Transformation, Metastasis and Antitumor Immunity. Int J Mol Sci. 2023;24:5978. [DOI] [PubMed] [PMC]

116.

Tan HY, Wang N, Lam W, Guo W, Feng Y, Cheng YC. Targeting tumour microenvironment by tyrosine kinase inhibitor. Mol Cancer. 2018;17:43. [DOI] [PubMed] [PMC]

117.

Shyam Sunder S, Sharma UC, Pokharel S. Adverse effects of tyrosine kinase inhibitors in cancer therapy: pathophysiology, mechanisms and clinical management. Signal Transduct Target Ther. 2023;8:262. [DOI] [PubMed] [PMC]

118.

O'Brien S, Berman E, Moore JO, Pinilla-Ibarz J, Radich JP, Shami PJ, et al. NCCN Task Force report: tyrosine kinase inhibitor therapy selection in the management of patients with chronic myelogenous leukemia. J Natl Compr Canc Netw. 2011;9 Suppl 2:S1–25. [DOI] [PubMed] [PMC]

119.

Zhou Y, Tao L, Qiu J, Xu J, Yang X, Zhang Y, et al. Tumor biomarkers for diagnosis, prognosis and targeted therapy. Signal Transduct Target Ther. 2024;9:132. [DOI] [PubMed] [PMC]

120.

Wojtukiewicz MZ, Rek MM, Karpowicz K, Górska M, Polityńska B, Wojtukiewicz AM, et al. Inhibitors of immune checkpoints-PD-1, PD-L1, CTLA-4-new opportunities for cancer patients and a new challenge for internists and general practitioners. Cancer Metastasis Rev. 2021;40:949–82. [DOI] [PubMed] [PMC]

121.

Wei SC, Duffy CR, Allison JP. Fundamental Mechanisms of Immune Checkpoint Blockade Therapy. Cancer Discov. 2018;8:1069–86. [DOI] [PubMed]

122.

Yin Q, Wu L, Han L, Zheng X, Tong R, Li L, et al. Immune-related adverse events of immune checkpoint inhibitors: a review. Front Immunol. 2023;14:1167975. [DOI] [PubMed] [PMC]

123.

Lin D, Shen Y, Liang T. Oncolytic virotherapy: basic principles, recent advances and future directions. Signal Transduct Target Ther. 2023;8:156. [DOI] [PubMed] [PMC]

124.

Chen L, Zuo M, Zhou Q, Wang Y. Oncolytic virotherapy in cancer treatment: challenges and optimization prospects. Front Immunol. 2023;14:1308890. [DOI] [PubMed] [PMC]

125.

Palanivelu L, Liu CH, Lin LT. Immunogenic cell death: The cornerstone of oncolytic viro-immunotherapy. Front Immunol. 2023;13:1038226. [DOI] [PubMed] [PMC]

126.

Tian Y, Xie D, Yang L. Engineering strategies to enhance oncolytic viruses in cancer immunotherapy. Signal Transduct Target Ther. 2022;7:117. [DOI] [PubMed] [PMC]

127.

Aspeslagh S, Morel D, Soria J, Postel-Vinay S. Epigenetic modifiers as new immunomodulatory therapies in solid tumours. Ann Oncol. 2018;29:812–24. [DOI] [PubMed]

128.

Llinàs-Arias P, Íñiguez-Muñoz S, McCann K, Voorwerk L, Orozco JIJ, Ensenyat-Mendez M, et al. Epigenetic Regulation of Immunotherapy Response in Triple-Negative Breast Cancer. Cancers (Basel). 2021;13:4139. [DOI] [PubMed] [PMC]

129.

Yang J, Xu J, Wang W, Zhang B, Yu X, Shi S. Epigenetic regulation in the tumor microenvironment: molecular mechanisms and therapeutic targets. Signal Transduct Target Ther. 2023;8:210. [DOI] [PubMed] [PMC]

130.

Liu Z, Ren Y, Weng S, Xu H, Li L, Han X. A New Trend in Cancer Treatment: The Combination of Epigenetics and Immunotherapy. Front Immunol. 2022;13:809761. [DOI] [PubMed] [PMC]

131.

Li X, You J, Hong L, Liu W, Guo P, Hao X. Neoantigen cancer vaccines: a new star on the horizon. Cancer Biol Med. 2023;21:274–311. [DOI] [PubMed] [PMC]

132.

Chehelgerdi M, Chehelgerdi M. The use of RNA-based treatments in the field of cancer immunotherapy. Mol Cancer. 2023;22:106. [DOI] [PubMed] [PMC]

133.

Gupta RG, Li F, Roszik J, Lizée G. Exploiting Tumor Neoantigens to Target Cancer Evolution: Current Challenges and Promising Therapeutic Approaches. Cancer Discov. 2021;11:1024–39. [DOI] [PubMed] [PMC]

134.

Blass E, Ott PA. Advances in the development of personalized neoantigen-based therapeutic cancer vaccines. Nat Rev Clin Oncol. 2021;18:215–29. [DOI] [PubMed] [PMC]

135.

Lin X, Tang S, Guo Y, Tang R, Li Z, Pan X, et al. Personalized neoantigen vaccine enhances the therapeutic efficacy of bevacizumab and anti-PD-1 antibody in advanced non-small cell lung cancer. Cancer Immunol Immunother. 2024;73:26. [DOI] [PubMed] [PMC]

136.

Wu DW, Jia SP, Xing SJ, Ma HL, Wang X, Tang QY, et al. Personalized neoantigen cancer vaccines: current progression, challenges and a bright future. Clin Exp Med. 2024;24:229. [DOI] [PubMed] [PMC]

137.

Aizaz M, Khan AS, Khan M, Musazade E, Yang G. Advancements in tumor-infiltrating lymphocytes: Historical insights, contemporary milestones, and future directions in oncology therapy. Crit Rev Oncol Hematol. 2024;202:104471. [DOI] [PubMed]

138.

Kazemi MH, Sadri M, Najafi A, Rahimi A, Baghernejadan Z, Khorramdelazad H, et al. Tumor-infiltrating lymphocytes for treatment of solid tumors: It takes two to tango? Front Immunol. 2022;13:1018962. [DOI] [PubMed] [PMC]

139.

Zaborowski AM, Winter DC, Lynch L. The therapeutic and prognostic implications of immunobiology in colorectal cancer: a review. Br J Cancer. 2021;125:1341–9. [DOI] [PubMed] [PMC]

140.

Zhao Y, Deng J, Rao S, Guo S, Shen J, Du F, et al. Tumor Infiltrating Lymphocyte (TIL) Therapy for Solid Tumor Treatment: Progressions and Challenges. Cancers (Basel). 2022;14:4160. [DOI] [PubMed] [PMC]

141.

Hu Z, Ott PA, Wu CJ. Towards personalized, tumour-specific, therapeutic vaccines for cancer. Nat Rev Immunol. 2018;18:168–82. [DOI] [PubMed] [PMC]

142.

Yu C, Liu X, Yang J, Zhang M, Jin H, Ma X, et al. Combination of Immunotherapy With Targeted Therapy: Theory and Practice in Metastatic Melanoma. Front Immunol. 2019;10:990. [DOI] [PubMed] [PMC]

143.

Wu Y, Yu G, Jin K, Qian J. Advancing non-small cell lung cancer treatment: the power of combination immunotherapies. Front Immunol. 2024;15:1349502. [DOI] [PubMed] [PMC]

144.

Whiteside TL, Demaria S, Rodriguez-Ruiz ME, Zarour HM, Melero I. Emerging Opportunities and Challenges in Cancer Immunotherapy. Clin Cancer Res. 2016;22:1845–55. [DOI] [PubMed] [PMC]

145.

Zhao X, Pan X, Wang Y, Zhang Y. Targeting neoantigens for cancer immunotherapy. Biomark Res. 2021;9:61. [DOI] [PubMed] [PMC]

146.

Zhang Z, Lu M, Qin Y, Gao W, Tao L, Su W, et al. Neoantigen: A New Breakthrough in Tumor Immunotherapy. Front Immunol. 2021;12:672356. [DOI] [PubMed] [PMC]

147.

Lybaert L, Lefever S, Fant B, Smits E, De Geest B, Breckpot K, et al. Challenges in neoantigen-directed therapeutics. Cancer Cell. 2023;41:15–40. [DOI] [PubMed]

148.

Lussier DM, Alspach E, Ward JP, Miceli AP, Runci D, White JM, et al. Radiation-induced neoantigens broaden the immunotherapeutic window of cancers with low mutational loads. Proc Natl Acad Sci U S A. 2021;118:e2102611118. [DOI] [PubMed] [PMC]

149.

Pang Z, Lu MM, Zhang Y, Gao Y, Bai JJ, Gu JY, et al. Neoantigen-targeted TCR-engineered T cell immunotherapy: current advances and challenges. Biomark Res. 2023;11:104. [DOI] [PubMed] [PMC]

150.

Shafer P, Kelly LM, Hoyos V. Cancer Therapy With TCR-Engineered T Cells: Current Strategies, Challenges, and Prospects. Front Immunol. 2022;13:835762. [DOI] [PubMed] [PMC]

151.

Korell F, Berger TR, Maus MV. Understanding CAR T cell-tumor interactions: Paving the way for successful clinical outcomes. Med. 2022;3:538–64. [DOI] [PubMed]

152.

Huang Q, Cai WQ, Han ZW, Wang MY, Zhou Y, Cheng JT, et al. Bispecific T cell engagers and their synergistic tumor immunotherapy with oncolytic viruses. Am J Cancer Res. 2021;11:2430–55. [PubMed] [PMC]

153.

Huehls AM, Coupet TA, Sentman CL. Bispecific T-cell engagers for cancer immunotherapy. Immunol Cell Biol. 2015;93:290–6. [DOI] [PubMed] [PMC]

154.

Kamigaki T, Takimoto R, Okada S, Ibe H, Oguma E, Goto S. Personalized Dendritic-cell-based Vaccines Targeting Cancer Neoantigens. Anticancer Res. 2024;44:3713–24. [DOI] [PubMed]

155.

Wang S, Sun J, Chen K, Ma P, Lei Q, Xing S, et al. Perspectives of tumor-infiltrating lymphocyte treatment in solid tumors. BMC Med. 2021;19:140. [DOI] [PubMed] [PMC]

156.

Betof Warner A, Corrie PG, Hamid O. Tumor-Infiltrating Lymphocyte Therapy in Melanoma: Facts to the Future. Clin Cancer Res. 2023;29:1835–54. [DOI] [PubMed] [PMC]

157.

Santos PM, Butterfield LH. Dendritic Cell-Based Cancer Vaccines. J Immunol. 2018;200:443–9. [DOI] [PubMed] [PMC]

158.

Lee KW, Yam JWP, Mao X. Dendritic Cell Vaccines: A Shift from Conventional Approach to New Generations. Cells. 2023;12:2147. [DOI] [PubMed] [PMC]

159.

Ingels J, De Cock L, Stevens D, Mayer RL, Théry F, Sanchez GS, et al. Neoantigen-targeted dendritic cell vaccination in lung cancer patients induces long-lived T cells exhibiting the full differentiation spectrum. Cell Rep Med. 2024;5:101516. [DOI] [PubMed] [PMC]

160.

Ramirez CA, Becker-Hapak M, Singhal K, Russler-Germain DA, Frenkel F, Barnell EK, et al. Neoantigen landscape supports feasibility of personalized cancer vaccine for follicular lymphoma. Blood Adv. 2024;8:4035–49. [DOI] [PubMed] [PMC]

161.

Fritsch EF, Burkhardt UE, Hacohen N, Wu CJ. Personal Neoantigen Cancer Vaccines: A Road Not Fully Paved. Cancer Immunol Res. 2020;8:1465–9. [DOI] [PubMed] [PMC]

162.

Li J, Zhang Y, Fu T, Xing G, Cai H, Li K, et al. Clinical advances and challenges associated with TCR-T cell therapy for cancer treatment. Front Immunol. 2024;15:1487782. [DOI] [PubMed] [PMC]

163.

Bui TA, Mei H, Sang R, Ortega DG, Deng W. Advancements and challenges in developing in vivo CAR T cell therapies for cancer treatment. EBioMedicine. 2024;106:105266. [DOI] [PubMed] [PMC]

164.

Lan HR, Chen M, Yao SY, Chen JX, Jin KT. Bispecific antibodies revolutionizing breast cancer treatment: a comprehensive overview. Front Immunol. 2023;14:1266450. [DOI] [PubMed] [PMC]

165.

Kaufman HL, Kohlhapp FJ, Zloza A. Oncolytic viruses: a new class of immunotherapy drugs. Nat Rev Drug Discov. 2015;14:642–2. [DOI] [PubMed] [PMC]

166.

Marelli G, Howells A, Lemoine NR, Wang Y. Oncolytic Viral Therapy and the Immune System: A Double-Edged Sword Against Cancer. Front Immunol. 2018;9:866. [DOI] [PubMed] [PMC]

167.

Liu D, Liu L, Li X, Wang S, Wu G, Che X. Advancements and Challenges in Peptide-Based Cancer Vaccination: A Multidisciplinary Perspective. Vaccines (Basel). 2024;12:950. [DOI] [PubMed] [PMC]

168.

Chen P, Liu X, Sun Y, Zhou P, Wang Y, Zhang Y. Dendritic cell targeted vaccines: Recent progresses and challenges. Hum Vaccin Immunother. 2016;12:612–22. [DOI] [PubMed] [PMC]

169.

Richard G, Princiotta MF, Bridon D, Martin WD, Steinberg GD, De Groot AS. Neoantigen-based personalized cancer vaccines: the emergence of precision cancer immunotherapy. Expert Rev Vaccines. 2022;21:173–84. [DOI] [PubMed]

170.

Garg P, Singhal G, Pareek S, Kulkarni P, Horne D, Nath A, et al. Unveiling the potential of gene editing techniques in revolutionizing Cancer treatment: A comprehensive overview. Biochim Biophys Acta Rev Cancer. 2025;1880:189233. [DOI] [PubMed]

171.

Fang X, Guo Z, Liang J, Wen J, Liu Y, Guan X, et al. Neoantigens and their potential applications in tumor immunotherapy. Oncol Lett. 2022;23:88. [DOI] [PubMed] [PMC]

172.

Cai Y, Chen R, Gao S, Li W, Liu Y, Su G, et al. Artificial intelligence applied in neoantigen identification facilitates personalized cancer immunotherapy. Front Oncol. 2023;12:1054231. [DOI] [PubMed] [PMC]

173.

Kumar A, Dixit S, Srinivasan K, M D, Vincent PMDR. Personalized cancer vaccine design using AI-powered technologies. Front Immunol. 2024;15:1357217. [DOI] [PubMed] [PMC]

174.

Liao J, Li X, Gan Y, Han S, Rong P, Wang W, et al. Artificial intelligence assists precision medicine in cancer treatment. Front Oncol. 2023;12:998222. [DOI] [PubMed] [PMC]

175.

Feng X, Li Z, Liu Y, Chen D, Zhou Z. CRISPR/Cas9 technology for advancements in cancer immunotherapy: from uncovering regulatory mechanisms to therapeutic applications. Exp Hematol Oncol. 2024;13:102. [DOI] [PubMed] [PMC]

176.

Augustin RC, Cai WL, Luke JJ, Bao R. Facts and Hopes in Using Omics to Advance Combined Immunotherapy Strategies. Clin Cancer Res. 2024;30:1724–32. [DOI] [PubMed] [PMC]

177.

Karimi MR, Karimi AH, Abolmaali S, Sadeghi M, Schmitz U. Prospects and challenges of cancer systems medicine: from genes to disease networks. Brief Bioinform. 2022;23:bbab343. [DOI] [PubMed] [PMC]

178.

Huber F, Arnaud M, Stevenson BJ, Michaux J, Benedetti F, Thevenet J, et al. A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy. Nat Biotechnol. 2024. [DOI] [PubMed]

179.

Terai YL, Huang C, Wang B, Kang X, Han J, Douglass J, et al. Valid-NEO: A Multi-Omics Platform for Neoantigen Detection and Quantification from Limited Clinical Samples. Cancers (Basel). 2022;14:1243. [DOI] [PubMed] [PMC]

180.

McGrail DJ, Federico L, Li Y, Dai H, Lu Y, Mills GB, et al. Multi-omics analysis reveals neoantigen-independent immune cell infiltration in copy-number driven cancers. Nat Commun. 2018;9:1317. [DOI] [PubMed] [PMC]

181.

Teplensky MH, Evangelopoulos M, Dittmar JW, Forsyth CM, Sinegra AJ, Wang S, et al. Multi-antigen spherical nucleic acid cancer vaccines. Nat Biomed Eng. 2023;7:911–27. [DOI] [PubMed] [PMC]

182.

Motamedi H, Ari MM, Shahlaei M, Moradi S, Farhadikia P, Alvandi A, et al. Designing multi-epitope vaccine against important colorectal cancer (CRC) associated pathogens based on immunoinformatics approach. BMC Bioinformatics. 2023;24:65. [DOI] [PubMed] [PMC]

183.

Bader JE, Voss K, Rathmell JC. Targeting Metabolism to Improve the Tumor Microenvironment for Cancer Immunotherapy. Mol Cell. 2020;78:1019–33. [DOI] [PubMed] [PMC]

184.

Marshall HT, Djamgoz MBA. Immuno-Oncology: Emerging Targets and Combination Therapies. Front Oncol. 2018;8:315. [DOI] [PubMed] [PMC]

185.

Rotte A. Combination of CTLA-4 and PD-1 blockers for treatment of cancer. J Exp Clin Cancer Res. 2019;38:255. [DOI] [PubMed] [PMC]

186.

Cheng W, Kang K, Zhao A, Wu Y. Dual blockade immunotherapy targeting PD-1/PD-L1 and CTLA-4 in lung cancer. J Hematol Oncol. 2024;17:54. [DOI] [PubMed] [PMC]

187.

Liu Z, Lv J, Dang Q, Liu L, Weng S, Wang L, et al. Engineering neoantigen vaccines to improve cancer personalized immunotherapy. Int J Biol Sci. 2022;18:5607–23. [DOI] [PubMed] [PMC]

188.

Nath K, Mailankody S, Usmani SZ. The Role of Chimeric Antigen Receptor T-Cell Therapy in the Era of Bispecific Antibodies. Hematol Oncol Clin North Am. 2023;37:1201–14. [DOI] [PubMed] [PMC]

189.

Al Hadidi S, Heslop HE, Brenner MK, Suzuki M. Bispecific antibodies and autologous chimeric antigen receptor T cell therapies for treatment of hematological malignancies. Mol Ther. 2024;32:2444–60. [DOI] [PubMed]

190.

Ali A, DiPersio JF. ReCARving the future: bridging CAR T-cell therapy gaps with synthetic biology, engineering, and economic insights. Front Immunol. 2024;15:1432799. [DOI] [PubMed] [PMC]

191.

Rashid MM, Selvarajoo K. Advancing drug-response prediction using multi-modal and -omics machine learning integration (MOMLIN): a case study on breast cancer clinical data. Brief Bioinform. 2024;25:bbae300. [DOI] [PubMed] [PMC]

192.

Li Y, Wu X, Fang D, Luo Y. Informing immunotherapy with multi-omics driven machine learning. NPJ Digit Med. 2024;7:67. [DOI] [PubMed] [PMC]

193.

Chen F, Zou Z, Du J, Su S, Shao J, Meng F, et al. Neoantigen identification strategies enable personalized immunotherapy in refractory solid tumors. J Clin Invest. 2019;129:2056–70. [DOI] [PubMed] [PMC]

194.

Park Y, Heider D, Hauschild AC. Integrative Analysis of Next-Generation Sequencing for Next-Generation Cancer Research toward Artificial Intelligence. Cancers (Basel). 2021;13:3148. [DOI] [PubMed] [PMC]

195.

Clark AJ, Lillard JW Jr. A Comprehensive Review of Bioinformatics Tools for Genomic Biomarker Discovery Driving Precision Oncology. Genes (Basel). 2024;15:1036. [DOI] [PubMed] [PMC]

196.

Huang J, Mao L, Lei Q, Guo AY. Bioinformatics tools and resources for cancer and application. Chin Med J (Engl). 2024;137:2052–64. [DOI] [PubMed] [PMC]

197.

Chen I, Chen MY, Goedegebuure SP, Gillanders WE. Challenges targeting cancer neoantigens in 2021: a systematic literature review. Expert Rev Vaccines. 2021;20:827–37. [PubMed] [PMC]

198.

Macy AM, Herrmann LM, Adams AC, Hastings KT. Major histocompatibility complex class II in the tumor microenvironment: functions of nonprofessional antigen-presenting cells. Curr Opin Immunol. 2023;83:102330. [DOI] [PubMed] [PMC]

199.

Story CM, Wang T, Bhatt VR, Battiwalla M, Badawy SM, Kamoun M, et al.; Center for International Blood and Marrow Transplant Research Immunobiology Working Committee. Genetics of HLA Peptide Presentation and Impact on Outcomes in HLA-Matched Allogeneic Hematopoietic Cell Transplantation. Transplant Cell Ther. 2021;27:591–9. [DOI] [PubMed] [PMC]

200.

Karnaukhov V, Paes W, Woodhouse IB, Partridge T, Nicastri A, Brackenridge S, et al. HLA variants have different preferences to present proteins with specific molecular functions which are complemented in frequent haplotypes. Front Immunol. 2022;13:1067463. [DOI] [PubMed] [PMC]

201.

Wang S, Wang M, Chen L, Pan G, Wang Y, Li SC. SpecHLA enables full-resolution HLA typing from sequencing data. Cell Rep Methods. 2023;3:100589. [DOI] [PubMed] [PMC]

202.

Matey-Hernandez ML, Danish Pan Genome C, Brunak S, Izarzugaza JMG. Benchmarking the HLA typing performance of Polysolver and Optitype in 50 Danish parental trios. BMC Bioinformatics. 2018;19:239. [DOI] [PubMed] [PMC]

203.

Chen J, Madireddi S, Nagarkar D, Migdal M, Heiden JV, Chang D, et al. In silico tools for accurate HLA and KIR inference from clinical sequencing data empower immunogenetics on individual-patient and population scales. Brief Bioinform. 2021;22:bbaa223. [DOI] [PubMed] [PMC]

204.

Racle J, Guillaume P, Schmidt J, Michaux J, Larabi A, Lau K, et al. Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes. Immunity. 2023;56:1359–75.e13. [DOI] [PubMed]

205.

Mikhaylov V, Brambley CA, Keller GLJ, Arbuiso AG, Weiss LI, Baker BM, et al. Accurate modeling of peptide-MHC structures with AlphaFold. Structure. 2024;32:228–41.e4. [DOI] [PubMed] [PMC]

206.

Mei S, Li F, Leier A, Marquez-Lago TT, Giam K, Croft NP, et al. A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction. Brief Bioinform. 2020;21:1119–35. [DOI] [PubMed] [PMC]

207.

Koşaloğlu-Yalçın Z, Lee J, Greenbaum J, Schoenberger SP, Miller A, Kim YJ, et al. Combined assessment of MHC binding and antigen abundance improves T cell epitope predictions. iScience. 2022;25:103850. [DOI] [PubMed] [PMC]

208.

Fotakis G, Trajanoski Z, Rieder D. Computational cancer neoantigen prediction: current status and recent advances. Immunooncol Technol. 2021;12:100052. [DOI] [PubMed] [PMC]

209.

Hao Q, Wei P, Shu Y, Zhang YG, Xu H, Zhao J. Improvement of Neoantigen Identification Through Convolution Neural Network. Front Immunol. 2021;12:682103. [DOI] [PubMed] [PMC]

210.

Bradley P. Structure-based prediction of T cell receptor:peptide-MHC interactions. Elife. 2023;12:e82813. [DOI] [PubMed] [PMC]

211.

Szeto C, Lobos CA, Nguyen AT, Gras S. TCR Recognition of Peptide-MHC-I: Rule Makers and Breakers. Int J Mol Sci. 2020;22:68. [DOI] [PubMed] [PMC]

212.

BBjerregaard AM, Nielsen M, Hadrup SR, Szallasi Z, Eklund AC. MuPeXI: prediction of neo-epitopes from tumor sequencing data. Cancer Immunol Immunother. 2017;66:1123–30. [DOI] [PubMed] [PMC]

213.

Zhou C, Wei Z, Zhang Z, Zhang B, Zhu C, Chen K, et al. pTuneos: prioritizing tumor neoantigens from next-generation sequencing data. Genome Med. 2019;11:67. [DOI] [PubMed] [PMC]

214.

Smith CC, Chai S, Washington AR, Lee SJ, Landoni E, Field K, et al. Machine-Learning Prediction of Tumor Antigen Immunogenicity in the Selection of Therapeutic Epitopes. Cancer Immunol Res. 2019;7:1591–604. [DOI] [PubMed] [PMC]

215.

Schmidt J, Smith AR, Magnin M, Racle J, Devlin JR, Bobisse S, et al. Prediction of neo-epitope immunogenicity reveals TCR recognition determinants and provides insight into immunoediting. Cell Rep Med. 2021;2:100194. [DOI] [PubMed] [PMC]

216.

Shah RK, Cygan E, Kozlik T, Colina A, Zamora AE. Utilizing immunogenomic approaches to prioritize targetable neoantigens for personalized cancer immunotherapy. Front Immunol. 2023;14:1301100. [DOI] [PubMed] [PMC]

217.

Müller M, Huber F, Arnaud M, Kraemer AI, Altimiras ER, Michaux J, et al. Machine learning methods and harmonized datasets improve immunogenic neoantigen prediction. Immunity. 2023;56:2650–63.e6. [DOI] [PubMed]

218.

Karasaki T, Nagayama K, Kuwano H, Nitadori JI, Sato M, Anraku M, et al. Prediction and prioritization of neoantigens: integration of RNA sequencing data with whole-exome sequencing. Cancer Sci. 2017;108:170–77. [DOI] [PubMed] [PMC]

219.

Zhang J, Mardis ER, Maher CA. INTEGRATE-neo: a pipeline for personalized gene fusion neoantigen discovery. Bioinformatics. 2017;33:555–7. [DOI] [PubMed] [PMC]

220.

Anzar I, Sverchkova A, Stratford R, Clancy T. NeoMutate: an ensemble machine learning framework for the prediction of somatic mutations in cancer. BMC Med Genomics. 2019;12:63. [DOI] [PubMed] [PMC]

221.

Jurtz V, Paul S, Andreatta M, Marcatili P, Peters B, Nielsen M. NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data. J Immunol. 2017;199:3360–8. [DOI] [PubMed] [PMC]

222.

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. [DOI] [PubMed] [PMC]

223.

Zeng H, Gifford DK. Quantification of Uncertainty in Peptide-MHC Binding Prediction Improves High-Affinity Peptide Selection for Therapeutic Design. Cell Syst. 2019;9:159–66.e3. [DOI] [PubMed] [PMC]

224.

Nielsen M, Andreatta M. NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets. Genome Med. 2016;8:33. [DOI] [PubMed] [PMC]

225.

Reynisson B, Alvarez B, Paul S, Peters B, Nielsen M. NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data. Nucleic Acids Res. 2020;48:W449–54. [DOI] [PubMed] [PMC]

226.

Nielsen M, Justesen S, Lund O, Lundegaard C, Buus S. NetMHCIIpan-2.0 - Improved pan-specific HLA-DR predictions using a novel concurrent alignment and weight optimization training procedure. Immunome Res. 2010;6:9. [DOI] [PubMed] [PMC]

227.

Stranzl T, Larsen MV, Lundegaard C, Nielsen M. NetCTLpan: pan-specific MHC class I pathway epitope predictions. Immunogenetics. 2010;62:357–68. [DOI] [PubMed] [PMC]

228.

O’Donnell TJ, Rubinsteyn A, Laserson U. MHCflurry 2.0: Improved Pan-Allele Prediction of MHC Class I-Presented Peptides by Incorporating Antigen Processing. Cell Syst. 2020;11:42–8.e7. [DOI] [PubMed]

229.

O'Donnell TJ, Rubinsteyn A, Bonsack M, Riemer AB, Laserson U, Hammerbacher J. MHCflurry: Open-Source Class I MHC Binding Affinity Prediction. Cell Syst. 2018;7:129–32.e4. [DOI] [PubMed]

230.

Ong E, Cooke MF, Huffman A, Xiang Z, Wong MU, Wang H, et al. Vaxign2: the second generation of the first Web-based vaccine design program using reverse vaccinology and machine learning. Nucleic Acids Res. 2021;49:W671–8. [DOI] [PubMed] [PMC]

231.

Ong E, Wang H, Wong MU, Seetharaman M, Valdez N, He Y. Vaxign-ML: supervised machine learning reverse vaccinology model for improved prediction of bacterial protective antigens. Bioinformatics. 2020;36:3185–91. [DOI] [PubMed] [PMC]

232.

He Y, Xiang Z, Mobley HL. Vaxign: the first web-based vaccine design program for reverse vaccinology and applications for vaccine development. J Biomed Biotechnol. 2010;2010:297505. [DOI] [PubMed] [PMC]

233.

Salimi N, Fleri W, Peters B, Sette A. The immune epitope database: a historical retrospective of the first decade. Immunology. 2012;137:117–23. [DOI] [PubMed] [PMC]

234.

Martini S, Nielsen M, Peters B, Sette A. The Immune Epitope Database and Analysis Resource Program 2003-2018: reflections and outlook. Immunogenetics. 2020;72:57–76. [DOI] [PubMed] [PMC]

235.

Fleri W, Paul S, Dhanda SK, Mahajan S, Xu X, Peters B, et al. The Immune Epitope Database and Analysis Resource in Epitope Discovery and Synthetic Vaccine Design. Front Immunol. 2017;8:278. [DOI] [PubMed] [PMC]

236.

Martins J, Magalhães C, Rocha M, Osório NS. Machine Learning-Enhanced T Cell Neoepitope Discovery for Immunotherapy Design. Cancer Inform. 2019;18:1176935119852081. [DOI] [PubMed] [PMC]

237.

Borch A, Carri I, Reynisson B, Alvarez HMG, Munk KK, Montemurro A, et al. IMPROVE: a feature model to predict neoepitope immunogenicity through broad-scale validation of T-cell recognition. Front Immunol. 2024;15:1360281. [DOI] [PubMed] [PMC]

238.

Wongklaew P, Sriswasdi S, Chuangsuwanich E. MHCSeqNet2-improved peptide-class I MHC binding prediction for alleles with low data. Bioinformatics. 2024;40:btad780. [DOI] [PubMed] [PMC]

239.

Lundegaard C, Lund O, Buus S, Nielsen M. Major histocompatibility complex class I binding predictions as a tool in epitope discovery. Immunology. 2010;130:309–18. [DOI] [PubMed] [PMC]

240.

Wang M, Lei C, Wang J, Li Y, Li M. TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning. Brief Bioinform. 2024;25:bbae154. [DOI] [PubMed] [PMC]

241.

Nilsson JB, Kaabinejadian S, Yari H, Kester MGD, van Balen P, Hildebrand WH, et al. Accurate prediction of HLA class II antigen presentation across all loci using tailored data acquisition and refined machine learning. Sci Adv. 2023;9:eadj6367. [DOI] [PubMed] [PMC]

242.

Reynisson B, Barra C, Kaabinejadian S, Hildebrand WH, Peters B, Nielsen M. Improved Prediction of MHC II Antigen Presentation through Integration and Motif Deconvolution of Mass Spectrometry MHC Eluted Ligand Data. J Proteome Res. 2020;19:2304–15. [DOI] [PubMed]

243.

Karosiene E, Rasmussen M, Blicher T, Lund O, Buus S, Nielsen M. NetMHCIIpan-3.0, a common pan-specific MHC class II prediction method including all three human MHC class II isotypes, HLA-DR, HLA-DP and HLA-DQ. Immunogenetics. 2013;65:711–24. [DOI] [PubMed] [PMC]

244.

Nielsen M, Lundegaard C, Blicher T, Lamberth K, Harndahl M, Justesen S, et al. NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and -B locus protein of known sequence. PLoS One. 2007;2:e796. [DOI] [PubMed] [PMC]

245.

Dhanda SK, Mahajan S, Manoharan M. Neoepitopes prediction strategies: an integration of cancer genomics and immunoinformatics approaches. Brief Funct Genomics. 2023;22:1–8. [DOI] [PubMed]

246.

Yalamarty SSK, Filipczak N, Li X, Subhan MA, Parveen F, Ataide JA, et al. Mechanisms of Resistance and Current Treatment Options for Glioblastoma Multiforme (GBM). Cancers (Basel). 2023;15:2116. [DOI] [PubMed] [PMC]

247.

Shergalis A, Bankhead A 3rd, Luesakul U, Muangsin N, Neamati N. Current Challenges and Opportunities in Treating Glioblastoma. Pharmacol Rev. 2018;70:412–45. [DOI] [PubMed] [PMC]

248.

Lin H, Liu C, Hu A, Zhang D, Yang H, Mao Y. Understanding the immunosuppressive microenvironment of glioma: mechanistic insights and clinical perspectives. J Hematol Oncol. 2024;17:31. [DOI] [PubMed] [PMC]

249.

Rong L, Li N, Zhang Z. Emerging therapies for glioblastoma: current state and future directions. J Exp Clin Cancer Res. 2022;41:142. [DOI] [PubMed] [PMC]

250.

Nabian N, Ghalehtaki R, Zeinalizadeh M, Balaña C, Jablonska PA. State of the neoadjuvant therapy for glioblastoma multiforme-Where do we stand? Neurooncol Adv. 2024;6:vdae028. [DOI] [PubMed] [PMC]

251.

Lovly CM, Salama AK, Salgia R. Tumor Heterogeneity and Therapeutic Resistance. Am Soc Clin Oncol Educ Book. 2016;35:e585–93. [DOI] [PubMed] [PMC]

252.

Cheng L, Chen L, Shi Y, Gu W, Ding W, Zheng X, et al. Efficacy and safety of bispecific antibodies vs. immune checkpoint blockade combination therapy in cancer: a real-world comparison. Mol Cancer. 2024;23:77. [DOI] [PubMed] [PMC]

253.

Wang M, Zhang C, Wang X, Yu H, Zhang H, Xu J, et al. Tumor-treating fields (TTFields)-based cocktail therapy: a novel blueprint for glioblastoma treatment. Am J Cancer Res. 2021;11:1069–86. [PubMed] [PMC]

254.

Rios SA, Oyervides S, Uribe D, Reyes AM, Fanniel V, Vazquez J, et al. Emerging Therapies for Glioblastoma. Cancers (Basel). 2024;16:1485. [DOI] [PubMed] [PMC]

255.

Fu M, Zhou Z, Huang X, Chen Z, Zhang L, Zhang J, et al. Use of Bevacizumab in recurrent glioblastoma: a scoping review and evidence map. BMC Cancer. 2023;23:544. [DOI] [PubMed] [PMC]

256.

Ghiaseddin A, Peters KB. Use of bevacizumab in recurrent glioblastoma. CNS Oncol. 2015;4:157–69. [DOI] [PubMed] [PMC]

257.

Moser JC, Salvador E, Deniz K, Swanson K, Tuszynski J, Carlson KW, et al. The Mechanisms of Action of Tumor Treating Fields. Cancer Res. 2022;82:3650–8. [DOI] [PubMed] [PMC]

258.

Morad G, Helmink BA, Sharma P, Wargo JA. Hallmarks of response, resistance, and toxicity to immune checkpoint blockade. Cell. 2021;184:5309–37. [DOI] [PubMed] [PMC]

259.

Catanzaro E, Beltrán-Visiedo M, Galluzzi L, Krysko DV. Immunogenicity of cell death and cancer immunotherapy with immune checkpoint inhibitors. Cell Mol Immunol. 2025;22:24–39. [DOI] [PubMed] [PMC]

260.

Wang C, Yu M, Zhang W. Neoantigen discovery and applications in glioblastoma: An immunotherapy perspective. Cancer Lett. 2022;550:215945. [DOI] [PubMed]

261.

Segura-Collar B, Hiller-Vallina S, de Dios O, Caamaño-Moreno M, Mondejar-Ruescas L, Sepulveda-Sanchez JM, et al. Advanced immunotherapies for glioblastoma: tumor neoantigen vaccines in combination with immunomodulators. Acta Neuropathol Commun. 2023;11:79. [DOI] [PubMed] [PMC]

262.

Tapescu I, Madsen PJ, Lowenstein PR, Castro MG, Bagley SJ, Fan Y, et al. The transformative potential of mRNA vaccines for glioblastoma and human cancer: technological advances and translation to clinical trials. Front Oncol. 2024;14:1454370. [DOI] [PubMed] [PMC]

263.

Strika Z, Petković K, Likić R. Effectiveness and Safety of mRNA Vaccines in the Therapy of Glioblastoma. J Pers Med. 2024;14:993. [DOI] [PubMed] [PMC]

264.

Restifo NP, Dudley ME, Rosenberg SA. Adoptive immunotherapy for cancer: harnessing the T cell response. Nat Rev Immunol. 2012;12:269–81. [DOI] [PubMed] [PMC]

265.

Dagar G, Gupta A, Masoodi T, Nisar S, Merhi M, Hashem S, et al. Harnessing the potential of CAR-T cell therapy: progress, challenges, and future directions in hematological and solid tumor treatments. J Transl Med. 2023;21:449. [DOI] [PubMed] [PMC]

266.

Deng Z, Zhan P, Yang K, Liu L, Liu J, Gao W. Identification of personalized neoantigen-based vaccines and immune subtype characteristic analysis of glioblastoma based on abnormal alternative splicing. Am J Cancer Res. 2022;12:3581–600. [PubMed] [PMC]

267.

Zhang X, Zhao L, Zhang H, Zhang Y, Ju H, Wang X, et al. The immunosuppressive microenvironment and immunotherapy in human glioblastoma. Front Immunol. 2022;13:1003651. [DOI] [PubMed] [PMC]

268.

Bell M, Gottschalk S. Engineered Cytokine Signaling to Improve CAR T Cell Effector Function. Front Immunol. 2021;12:684642. [DOI] [PubMed] [PMC]

269.

Muhammad S, Fan T, Hai Y, Gao Y, He J. Reigniting hope in cancer treatment: the promise and pitfalls of IL-2 and IL-2R targeting strategies. Mol Cancer. 2023;22:121. [DOI] [PubMed] [PMC]

270.

Wei F, Cheng XX, Xue JZ, Xue SA. Emerging Strategies in TCR-Engineered T Cells. Front Immunol. 2022;13:850358. [DOI] [PubMed] [PMC]

271.

Baulu E, Gardet C, Chuvin N, Depil S. TCR-engineered T cell therapy in solid tumors: State of the art and perspectives. Sci Adv. 2023;9:eadf3700. [DOI] [PubMed] [PMC]

272.

McGrath K, Dotti G. Combining Oncolytic Viruses with Chimeric Antigen Receptor T Cell Therapy. Hum Gene Ther. 2021;32:150–7. [DOI] [PubMed] [PMC]

273.

Luksik AS, Yazigi E, Shah P, Jackson CM. CAR T Cell Therapy in Glioblastoma: Overcoming Challenges Related to Antigen Expression. Cancers (Basel). 2023;15:1414. [DOI] [PubMed] [PMC]

274.

Kringel R, Lamszus K, Mohme M. Chimeric Antigen Receptor T Cells in Glioblastoma-Current Concepts and Promising Future. Cells. 2023;12:1770. [DOI] [PubMed] [PMC]

275.

Bartoszewska E, Tota M, Kisielewska M, Skowron I, Sebastianka K, Stefaniak O, et al. Overcoming Antigen Escape and T-Cell Exhaustion in CAR-T Therapy for Leukemia. Cells. 2024;13:1596. [DOI] [PubMed] [PMC]

276.

Lin H, Yang X, Ye S, Huang L, Mu W. Antigen escape in CAR-T cell therapy: Mechanisms and overcoming strategies. Biomed Pharmacother. 2024;178:117252. [DOI] [PubMed]

277.

Grosser R, Cherkassky L, Chintala N, Adusumilli PS. Combination Immunotherapy with CAR T Cells and Checkpoint Blockade for the Treatment of Solid Tumors. Cancer Cell. 2019;36:471–82. [DOI] [PubMed] [PMC]

278.

Sharma P, Goswami S, Raychaudhuri D, Siddiqui BA, Singh P, Nagarajan A, et al. Immune checkpoint therapy-current perspectives and future directions. Cell. 2023;186:1652–69. [DOI] [PubMed]

279.

Ou X, Ma Q, Yin W, Ma X, He Z. CRISPR/Cas9 Gene-Editing in Cancer Immunotherapy: Promoting the Present Revolution in Cancer Therapy and Exploring More. Front Cell Dev Biol. 2021;9:674467. [DOI] [PubMed] [PMC]

280.

Chen X, Zhong S, Zhan Y, Zhang X. CRISPR-Cas9 applications in T cells and adoptive T cell therapies. Cell Mol Biol Lett. 2024;29:52. [DOI] [PubMed] [PMC]

281.

Stephens AJ, Burgess-Brown NA, Jiang S. Beyond Just Peptide Antigens: The Complex World of Peptide-Based Cancer Vaccines. Front Immunol. 2021;12:696791. [DOI] [PubMed] [PMC]

282.

Kanaly CW, Ding D, Heimberger AB, Sampson JH. Clinical applications of a peptide-based vaccine for glioblastoma. Neurosurg Clin N Am. 2010;21:95–109. [DOI] [PubMed] [PMC]

283.

Noushmehr H, Herrgott G, Morosini NS, Castro AV. Noninvasive approaches to detect methylation-based markers to monitor gliomas. Neurooncol Adv. 2022;4:ii22–ii32. [DOI] [PubMed] [PMC]

284.

García-Montaño LA, Licón-Muñoz Y, Martinez FJ, Keddari YR, Ziemke MK, Chohan MO, et al. Dissecting Intra-tumor Heterogeneity in the Glioblastoma Microenvironment Using Fluorescence-Guided Multiple Sampling. Mol Cancer Res. 2023;21:755–67. [DOI] [PubMed] [PMC]

285.

Lv X, Wang B, Liu K, Li MJ, Yi X, Wu X. Decoding heterogeneous and coordinated tissue architecture in glioblastoma using spatial transcriptomics. iScience. 2024;27:110064. [DOI] [PubMed] [PMC]

286.

Jacquemin V, Antoine M, Dom G, Detours V, Maenhaut C, Dumont JE. Dynamic Cancer Cell Heterogeneity: Diagnostic and Therapeutic Implications. Cancers (Basel). 2022;14:280. [DOI] [PubMed] [PMC]

287.

Yabo YA, Niclou SP, Golebiewska A. Cancer cell heterogeneity and plasticity: A paradigm shift in glioblastoma. Neuro Oncol. 2022;24:669–82. [DOI] [PubMed] [PMC]

288.

Lindau D, Gielen P, Kroesen M, Wesseling P, Adema GJ. The immunosuppressive tumour network: myeloid-derived suppressor cells, regulatory T cells and natural killer T cells. Immunology. 2013;138:105–15. [DOI] [PubMed] [PMC]

289.

Haist M, Stege H, Grabbe S, Bros M. The Functional Crosstalk between Myeloid-Derived Suppressor Cells and Regulatory T Cells within the Immunosuppressive Tumor Microenvironment. Cancers (Basel). 2021;13:210. [DOI] [PubMed] [PMC]

290.

Gonzalez H, Hagerling C, Werb Z. Roles of the immune system in cancer: from tumor initiation to metastatic progression. Genes Dev. 2018;32:1267–84. [DOI] [PubMed] [PMC]

291.

Motz GT, Coukos G. Deciphering and reversing tumor immune suppression. Immunity. 2013;39:61–73. [DOI] [PubMed] [PMC]

292.

Kim SK, Cho SW. The Evasion Mechanisms of Cancer Immunity and Drug Intervention in the Tumor Microenvironment. Front Pharmacol. 2022;13:868695. [DOI] [PubMed] [PMC]

293.

Cui JW, Li Y, Yang Y, Yang HK, Dong JM, Xiao ZH, et al. Tumor immunotherapy resistance: Revealing the mechanism of PD-1 / PD-L1-mediated tumor immune escape. Biomed Pharmacother. 2024;171:116203. [DOI] [PubMed]

294.

Lin X, Kang K, Chen P, Zeng Z, Li G, Xiong W, et al. Regulatory mechanisms of PD-1/PD-L1 in cancers. Mol Cancer. 2024;23:108. [DOI] [PubMed] [PMC]

295.

Seidel JA, Otsuka A, Kabashima K. Anti-PD-1 and Anti-CTLA-4 Therapies in Cancer: Mechanisms of Action, Efficacy, and Limitations. Front Oncol. 2018;8:86. [DOI] [PubMed] [PMC]

296.

Shang S, Zhao Y, Qian K, Qin Y, Zhang X, Li T, et al. The role of neoantigens in tumor immunotherapy. Biomed Pharmacother. 2022;151:113118. [DOI] [PubMed]

297.

Qi Y, Zhang L, Liu Y, Li Y, Liu Y, Zhang Z. Targeted modulation of myeloid-derived suppressor cells in the tumor microenvironment: Implications for cancer therapy. Biomed Pharmacother. 2024;180:117590. [DOI] [PubMed]

298.

Rossetti R, Brand H, Lima SCG, Furtado IP, Silveira RM, Fantacini DMC, et al. Combination of genetically engineered T cells and immune checkpoint blockade for the treatment of cancer. Immunother Adv. 2022;2:ltac005. [DOI] [PubMed] [PMC]

299.

Khair DO, Bax HJ, Mele S, Crescioli S, Pellizzari G, Khiabany A, et al. Combining Immune Checkpoint Inhibitors: Established and Emerging Targets and Strategies to Improve Outcomes in Melanoma. Front Immunol. 2019;10:453. [DOI] [PubMed] [PMC]

300.

Vafaei S, Zekiy AO, Khanamir RA, Zaman BA, Ghayourvahdat A, Azimizonuzi H, et al. Combination therapy with immune checkpoint inhibitors (ICIs); a new frontier. Cancer Cell Int. 2022;22:2. [DOI] [PubMed] [PMC]

301.

Yu G, He X, Li X, Wu Y. Driving neoantigen-based cancer vaccines for personalized immunotherapy into clinic: A burdensome journey to promising land. Biomed Pharmacother. 2022;153:113464. [DOI] [PubMed]

302.

Ni L. Advances in mRNA-Based Cancer Vaccines. Vaccines (Basel). 2023;11:1599. [DOI] [PubMed] [PMC]

303.

Li C, Jiang P, Wei S, Xu X, Wang J. Regulatory T cells in tumor microenvironment: new mechanisms, potential therapeutic strategies and future prospects. Mol Cancer. 2020;19:116. [DOI] [PubMed] [PMC]

304.

Chen Y, Zhou Q, Jia Z, Cheng N, Zhang S, Chen W, et al. Enhancing cancer immunotherapy: Nanotechnology-mediated immunotherapy overcoming immunosuppression. Acta Pharm Sin B. 2024;14:3834–54. [DOI] [PubMed] [PMC]

305.

Supabphol S, Li L, Goedegebuure SP, Gillanders WE. Neoantigen vaccine platforms in clinical development: understanding the future of personalized immunotherapy. Expert Opin Investig Drugs. 2021;30:529–41. [DOI] [PubMed] [PMC]

306.

Kumari K, Singh A, Chaudhary A, Singh RK, Shanker A, Kumar V, et al. Neoantigen Identification and Dendritic Cell-Based Vaccines for Lung Cancer Immunotherapy. Vaccines (Basel). 2024;12:498. [DOI] [PubMed] [PMC]

307.

Jogalekar MP, Rajendran RL, Khan F, Dmello C, Gangadaran P, Ahn BC. CAR T-Cell-Based gene therapy for cancers: new perspectives, challenges, and clinical developments. Front Immunol. 2022;13:925985. [DOI] [PubMed] [PMC]

308.

Zappasodi R, Merghoub T, Wolchok JD. Emerging Concepts for Immune Checkpoint Blockade-Based Combination Therapies. Cancer Cell. 2018;33:581–98. [DOI] [PubMed] [PMC]

309.

Ren L, Leisegang M, Deng B, Matsuda T, Kiyotani K, Kato T, et al. Identification of neoantigen-specific T cells and their targets: implications for immunotherapy of head and neck squamous cell carcinoma. Oncoimmunology. 2019;8:e1568813. [DOI] [PubMed] [PMC]

310.

Kula T, Dezfulian MH, Wang CI, Abdelfattah NS, Hartman ZC, Wucherpfennig KW, et al. T-Scan: A Genome-wide Method for the Systematic Discovery of T Cell Epitopes. Cell. 2019;178:1016–28.e13. [DOI] [PubMed] [PMC]

311.

Dezfulian MH, Kula T, Pranzatelli T, Kamitaki N, Meng Q, Khatri B, et al. TScan-II: A genome-scale platform for the de novo identification of CD4⁺ T cell epitopes. Cell. 2023;186:5569–86.e21. [DOI] [PubMed] [PMC]

312.

Pearlman AH, Hwang MS, Konig MF, Hsiue EH, Douglass J, DiNapoli SR, et al. Targeting public neoantigens for cancer immunotherapy. Nat Cancer. 2021;2:487–97. [DOI] [PubMed] [PMC]

313.

Liu B, Zhou H, Tan L, Siu KTH, Guan XY. Exploring treatment options in cancer: Tumor treatment strategies. Signal Transduct Target Ther. 2024;9:175. [DOI] [PubMed] [PMC]

314.

Birnboim-Perach R, Benhar I. Using Combination therapy to overcome diverse challenges of Immune Checkpoint Inhibitors treatment. Int J Biol Sci. 2024;20:3911–22. [DOI] [PubMed] [PMC]

315.

Cheng AL, Hsu C, Chan SL, Choo SP, Kudo M. Challenges of combination therapy with immune checkpoint inhibitors for hepatocellular carcinoma. J Hepatol. 2020;72:307–19. [DOI] [PubMed]

316.

Ruan S, Greenberg Z, Pan X, Zhuang P, Erwin N, He M. Extracellular Vesicles as an Advanced Delivery Biomaterial for Precision Cancer Immunotherapy. Adv Healthc Mater. 2022;11:e2100650. [DOI] [PubMed] [PMC]

317.

Wang L, Yu X, Zhou J, Su C. Extracellular Vesicles for Drug Delivery in Cancer Treatment. Biol Proced Online. 2023;25:28. [DOI] [PubMed] [PMC]