nach oben

Medical Oncology

Erschienen in:

01.05.2024 | Original Paper

Design and evaluation of a multiepitope vaccine for pancreatic cancer using immune-dominant epitopes derived from the signature proteome in expression datasets

verfasst von: Sooram Banesh, Nupoor Patil, Vihadhar Reddy Chethireddy, Arnav Bhukmaria, Prakash Saudagar

Erschienen in: Medical Oncology | Ausgabe 5/2024

Einloggen, um Zugang zu erhalten

Abstract

Pancreatic cancer is a highly aggressive and often lethal malignancy with limited treatment options. Its late-stage diagnosis and resistance to conventional therapies make it a significant challenge in oncology. Immunotherapy, particularly cancer vaccines, has emerged as a promising avenue for treating pancreatic cancer. Multi-epitope vaccines, designed to target multiple epitopes derived from various antigens associated with pancreatic cancer, have gained attention as potential candidates for improving therapeutic outcomes. In this study, we have explored transcriptomics and protein expression databases to identify potential upregulated proteins in pancreatic cancer cells. After examining a total of 21,054 proteins from various databases, it was discovered that 143 proteins expressed differently in malignant and healthy cells. The CTL, HTL and BCE epitopes were predicted for the shortlisted proteins. 51,840 vaccine constructs were created by concatenating CTL, HTL, and B-cell epitopes in the respective sequences. The best 86 structures were selected from a set of 51,840 designs after they were analyzed for vaxijenicity, allergenicity, toxicity, and antigenicity scores. In further simulation of the immune response using constructs, it was found that 41417, 37961, and 40841 constructs could produce a strong immune response when injected. Further, it was found that construct 37961 showed stronger interaction and stability with TLR-9 as determined from the large-scale molecular dynamics simulations. Moreover, the 37961 construct has shown interactions with TLR-9 suggests its potential in inducing immune response. In addition, construct 37961 has shown 100% predicted solubility in the E. coli expression system. Overall, the study indicates the designed construct 37961 has the potential to induce an anti-tumor immune response and long-standing protection pending further studies.

Graphical abstract

Nur mit Berechtigung zugänglich

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49.PubMedCrossRef

Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73(1):17–48.PubMedCrossRef

Jones S, Zhang X, Parsons DW, Lin JC-H, Leary RJ, Angenendt P, et al. Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science. 2008;321(5897):1801–6.PubMedPubMedCentralCrossRef

Hayashi A, Hong J, Iacobuzio-Donahue CA. The pancreatic cancer genome revisited. Nat Rev Gastroenterol Hepatol. 2021;18(7):469–81.PubMedCrossRef

Gheorghe G, Diaconu CC, Ionescu V, Constantinescu G, Bacalbasa N, Bungau S, et al. Risk factors for pancreatic cancer: emerging role of viral hepatitis. J Personal Med. 2022;12(1):83.CrossRef

Wang DS, Chen DL, Ren C, Wang ZQ, Qiu MZ, Luo HY, et al. ABO blood group, hepatitis B viral infection and risk of pancreatic cancer. Int J Cancer. 2012;131(2):461–8.PubMedCrossRef

Saung MT, Zheng L. Current standards of chemotherapy for pancreatic cancer. Clin Ther. 2017;39(11):2125–34.PubMedPubMedCentralCrossRef

Conroy T, Desseigne F, Ychou M, Bouché O, Guimbaud R, Bécouarn Y, et al. FOLFIRINOX versus gemcitabine for metastatic pancreatic cancer. N Engl J Med. 2011;364(19):1817–25.PubMedCrossRef

Von Hoff DD, Ervin T, Arena FP, Chiorean EG, Infante J, Moore M, et al. Increased survival in pancreatic cancer with nab-paclitaxel plus gemcitabine. N Engl J Med. 2013;369(18):1691–703.CrossRef

10.

Pontén F, Jirström K, Uhlen M. The human protein atlas—a tool for pathology. J Pathol: J Pathol Soc Great Br Irel. 2008;216(4):387–93.CrossRef

11.

Papatheodorou I, Fonseca NA, Keays M, Tang YA, Barrera E, Bazant W, et al. Expression atlas: gene and protein expression across multiple studies and organisms. Nucleic Acids Res. 2018;46(D1):D246–51.PubMedCrossRef

12.

Zeng J, Zhang Y, Shang Y, Mai J, Shi S, Lu M, et al. CancerSCEM: a database of single-cell expression map across various human cancers. Nucleic Acids Res. 2022;50(D1):D1147–55.PubMedCrossRef

13.

Tang G, Cho M, Wang X. OncoDB: an interactive online database for analysis of gene expression and viral infection in cancer. Nucleic Acids Res. 2022;50(D1):D1334–9.PubMedCrossRef

14.

Thumuluri V, Almagro Armenteros JJ, Johansen AR, Nielsen H, Winther O. DeepLoc 2.0: multi-label subcellular localization prediction using protein language models. Nucleic Acids Res. 2022;50(W1):W228–34.PubMedPubMedCentralCrossRef

15.

Hallgren J, Tsirigos KD, Pedersen MD, Almagro Armenteros JJ, Marcatili P, Nielsen H, et al. (2022) DeepTMHMM predicts alpha and beta transmembrane proteins using deep neural networks. BioRxiv. 2022:2022.04. 08.487609

16.

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(1):1–9.CrossRef

17.

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(W1):W449–54.PubMedPubMedCentralCrossRef

18.

Clifford JN, Høie MH, Deleuran S, Peters B, Nielsen M, Marcatili P. BepiPred-3.0: improved B-cell epitope prediction using protein language models. Protein Sci. 2022;31(12):e4497.PubMedPubMedCentralCrossRef

19.

Kolaskar AS, Tongaonkar PC. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett. 1990;276(1–2):172–4.PubMedCrossRef

20.

Dimitrov I, Flower DR, Doytchinova I. AllerTOP-a server for in silico prediction of allergens. BMC Bioinform. 2013. https://doi.org/10.1186/1471-2105-14-S6-S4.CrossRef

21.

Morozov V, Rodrigues CH, Ascher DB. CSM-toxin: a web-server for predicting protein toxicity. Pharmaceutics. 2023;15(2):431.PubMedPubMedCentralCrossRef

22.

Rapin N, Lund O, Bernaschi M, Castiglione F. Computational immunology meets bioinformatics: the use of prediction tools for molecular binding in the simulation of the immune system. PLoS ONE. 2010;5(4):e9862.PubMedPubMedCentralCrossRef

23.

Stolfi P, Castiglione F, Mastrostefano E, Di Biase I, Di Biase S, Palmieri G, et al. In-silico evaluation of adenoviral COVID-19 vaccination protocols: assessment of immunological memory up to 6 months after the third dose. Front Immunol. 2022;13: 998262.PubMedPubMedCentralCrossRef

24.

Ragone C, Manolio C, Cavalluzzo B, Mauriello A, Tornesello ML, Buonaguro FM, et al. Identification and validation of viral antigens sharing sequence and structural homology with tumor-associated antigens (TAAs). J Immunother Cancer. 2021. https://doi.org/10.1136/jitc-2021-002694.CrossRefPubMedPubMedCentral

25.

Mirdita M, Schütze K, Moriwaki Y, Heo L, Ovchinnikov S, Steinegger M. ColabFold: making protein folding accessible to all. Nat Methods. 2022;19(6):679–82.PubMedPubMedCentralCrossRef

26.

Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Highly accurate protein structure prediction with AlphaFold. Nature. 2021;596(7873):583–9.PubMedPubMedCentralCrossRef

27.

Vaz J, Andersson R. Intervention on toll-like receptors in pancreatic cancer. World J Gastroenterol: WJG. 2014;20(19):5808.PubMedPubMedCentralCrossRef

28.

Kozakov D, Hall DR, Xia B, Porter KA, Padhorny D, Yueh C, et al. The ClusPro web server for protein–protein docking. Nat Protoc. 2017;12(2):255–78.PubMedPubMedCentralCrossRef

29.

Guex N, Peitsch MC. SWISS-MODEL and the Swiss-Pdb viewer: an environment for comparative protein modeling. Electrophoresis. 1997;18(15):2714–23.PubMedCrossRef

30.

Krüger DM, Ahmed A, Gohlke H. NMSim web server: integrated approach for normal mode-based geometric simulations of biologically relevant conformational transitions in proteins. Nucleic Acids Res. 2012;40(W1):W310–6.PubMedPubMedCentralCrossRef

31.

Agostini F, Cirillo D, Livi CM, Delli Ponti R, Tartaglia GG. cc SOL omics: a webserver for solubility prediction of endogenous and heterologous expression in Escherichia coli. Bioinformatics. 2014;30(20):2975–7.PubMedPubMedCentralCrossRef

32.

Grossberg AJ, Chu LC, Deig CR, Fishman EK, Hwang WL, Maitra A, et al. Multidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma. CA Cancer J Clin. 2020;70(5):375–403.PubMedPubMedCentralCrossRef

33.

Sigalov AB. New therapeutic strategies targeting transmembrane signal transduction in the immune system. Cell Adh Migr. 2010;4(2):255–67.PubMedPubMedCentralCrossRef

34.

Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 2007;35:W407–10.PubMedPubMedCentralCrossRef

35.

Tyka MD, Keedy DA, André I, DiMaio F, Song Y, Richardson DC, et al. Alternate states of proteins revealed by detailed energy landscape mapping. J Mol Biol. 2011;405(2):607–18.PubMedCrossRef

36.

Gasteiger E, Hoogland C, Gattiker A, Se D, Wilkins MR, Appel RD, et al. Protein identification and analysis tools on the ExPASy server. Totowa: Springer; 2005.CrossRef

37.

Kara EE, Comerford I, Fenix KA, Bastow CR, Gregor CE, McKenzie DR, et al. Tailored immune responses: novel effector helper T cell subsets in protective immunity. PLoS Pathog. 2014;10(2): e1003905.PubMedPubMedCentralCrossRef

38.

Finn OJ. Cancer vaccines: between the idea and the reality. Nat Rev Immunol. 2003;3(8):630–41.PubMedCrossRef

39.

Luo W, Yin Q. B cell response to vaccination. Immunol Invest. 2021;50(7):780–801.PubMedCrossRef

40.

Zahavi D, Weiner L. Monoclonal antibodies in cancer therapy. Antibodies. 2020;9(3):34.PubMedPubMedCentralCrossRef

41.

Nardin A, Abastado J-P. Macrophages and cancer. Front Biosci. 2008;13(3):494–505.

42.

Burke JD, Young HA. IFN-γ: a cytokine at the right time, is in the right place. Semin Immunol. 2019. https://doi.org/10.1016/j.smim.2019.05.002.CrossRefPubMedPubMedCentral

43.

Helminen O, Huhta H, Kauppila JH, Lehenkari PP, Saarnio J, Karttunen TJ. Localization of nucleic acid-sensing toll-like receptors in human and mouse pancreas. APMIS. 2017;125(2):85–92.PubMedCrossRef

44.

Pahlavanneshan S, Sayadmanesh A, Ebrahimiyan H, Basiri M. Toll-like receptor-based strategies for cancer immunotherapy. J Immunol Res. 2021;2021:1–14.CrossRef

45.

Ruan M, Thorn K, Liu S, Li S, Yang W, Zhang C, et al. The secretion of IL-6 by CpG-ODN-treated cancer cells promotes T-cell immune responses partly through the TLR-9/AP-1 pathway in oral squamous cell carcinoma. Int J Oncol. 2014;44(6):2103–10.PubMedCrossRef

46.

Connor AA, Gallinger S. Pancreatic cancer evolution and heterogeneity: integrating omics and clinical data. Nat Rev Cancer. 2022;22(3):131–42.PubMedCrossRef

47.

Pilla L, Rivoltini L, Patuzzo R, Marrari A, Valdagni R, Parmiani G. Multipeptide vaccination in cancer patients. Expert Opin Biol Ther. 2009;9(8):1043–55.PubMedCrossRef

48.

Ray SK, Mukherjee S. Altering landscape of cancer vaccines: unique platforms, research on therapeutic applications and recent patents. Recent Pat Anti-Cancer Drug Discovery. 2023;18(2):133–46.CrossRef

49.

Gan L-L, Hii L-W, Wong S-F, Leong C-O, Mai C-W. Molecular mechanisms and potential therapeutic reversal of pancreatic cancer-induced immune evasion. Cancers. 2020;12(7):1872.PubMedPubMedCentralCrossRef

50.

de Paula PL, da Luz FAC, dos Anjos PB, Brigido PC, de Araujo RA, Goulart LR, et al. Peptide vaccines in breast cancer: the immunological basis for clinical response. Biotechnol Adv. 2015;33(8):1868–77.CrossRef

51.

Tamiola K, Acar B, Mulder FA. Sequence-specific random coil chemical shifts of intrinsically disordered proteins. J Am Chem Soc. 2010;132(51):18000–3.PubMedCrossRef

52.

Saber MM, Monir N, Awad AS, Elsherbiny ME, Zaki HF. TLR9: a friend or a foe. Life Sci. 2022;307:120874.PubMedCrossRef

53.

Lin X, Ye L, Wang X, Liao Z, Dong J, Yang Y, et al. Follicular helper T cells remodel the immune microenvironment of pancreatic cancer via secreting CXCL13 and IL-21. Cancers. 2021;13(15):3678.PubMedPubMedCentralCrossRef

54.

den Haan JM, Arens R, van Zelm MC. The activation of the adaptive immune system: cross-talk between antigen-presenting cells, T cells and B cells. Immunol Lett. 2014;162(2):103–12.CrossRef

55.

Alshaker HA, Matalka KZ. IFN-γ, IL-17 and TGF-β involvement in shaping the tumor microenvironment: the significance of modulating such cytokines in treating malignant solid tumors. Cancer Cell Int. 2011;11(1):1–12.CrossRef

Titel: Design and evaluation of a multiepitope vaccine for pancreatic cancer using immune-dominant epitopes derived from the signature proteome in expression datasets
verfasst von: Sooram Banesh
Nupoor Patil
Vihadhar Reddy Chethireddy
Arnav Bhukmaria
Prakash Saudagar
Publikationsdatum: 01.05.2024
Verlag: Springer US
Erschienen in: Medical Oncology / Ausgabe 5/2024
Print ISSN: 1357-0560
Elektronische ISSN: 1559-131X
DOI: https://doi.org/10.1007/s12032-024-02334-4

Springer Medizin

Design and evaluation of a multiepitope vaccine for pancreatic cancer using immune-dominant epitopes derived from the signature proteome in expression datasets

Abstract

Graphical abstract

Neu im Fachgebiet Onkologie

Labor, CT-Anthropometrie zeigen Risiko für Pankreaskrebs

Viel pflanzliche Nahrung, seltener Prostata-Ca.-Progression

Alter verschlechtert Prognose bei Endometriumkarzinom

Darf man die Behandlung eines Neonazis ablehnen?

Update Onkologie

Springer Medizin

Abstract

Graphical abstract

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Ausgabe 5/2024

Dual function of activated PPARγ by ligands on tumor growth and immunotherapy

The efficacy and safety of PD-1 inhibitor combined with TACE in the first-line treatment of unresectable hepatocellular carcinoma

Liver cancer wars: plant-derived polyphenols strike back

Exploring the combined anti-cancer effects of sodium butyrate and celastrol in glioblastoma cell lines: a novel therapeutic approach

Study of the effect of sFRP1 protein on molecules involved in the regulation of DNA methylation in CML cell line

Ferroptosis is an effective strategy for cancer therapy

Neu im Fachgebiet Onkologie

Labor, CT-Anthropometrie zeigen Risiko für Pankreaskrebs

Viel pflanzliche Nahrung, seltener Prostata-Ca.-Progression

Alter verschlechtert Prognose bei Endometriumkarzinom

Darf man die Behandlung eines Neonazis ablehnen?

Update Onkologie