Homology Modeling Epitopes of Kirsten Rat Sarcoma (KRAS) G12D, G12V and G12R as Pancreatic Ductal Adenocarcinoma Vaccine Candidates

Yıl 2023, Cilt: 7 Sayı: 1, 62 - 71, 15.01.2023

Yenı Yeni , Nining Nining

https://doi.org/10.33435/tcandtc.1140158

Öz

Pancreatic ductal adenocarcinoma (PDAC) is among the world's deadliest cancers. Multiple studies demonstrated that PDAC is frequently characterized by the presence of Kirsten Rat Sarcoma (KRAS) G12D, G12V, and G12R protein mutants. The mutants are potential immunotherapy targets due to their potential as cancer-specific neoantigens. KRAS G12D, G12V and G12R contain vaccine-immunogenic epitopes. KRAS G12D, G12V and G12R epitopes were presented at major histocompatibility complexes (MHC) class I. The rational design of peptide vaccines to enhance the efficacy of cancer immunotherapy is facilitated by developing a peptide structural data library and knowledge of the MHC and antigen presentation processes. Before predicting peptide activity against MHC, homology modeling must transform the peptide into a three-dimensional structure. In this study, I-TASSER was used to perform homology modeling with the assistance of other applications. In silico methods for predicting epitopes to produce rationally designed peptide vaccines can increase the efficacy of these vaccines. This study yielded four epitope models that are potential PDAC vaccination candidates, KSFEDIHHYR, GIPFIETSAK, VVVGARGVGK and VVVGADGVGK.

Anahtar Kelimeler

Homology Modeling, Epitope, KRAS, Vaccine, PDAC

Destekleyen Kurum

Research and Development Institute of Universitas Muhammadiyah Prof. DR. HAMKA

Proje Numarası

174 / F.02.09 / 2019

Teşekkür

Special thanks for the assistance

Kaynakça

• https://gco.iarc.fr/today/home, 2020, Accessed: 29.06.2022.
• J. Earl, S. Garcia-Nieto, J.C. Martinez-Avila, J. Montans, A. Sanjuanbenito, M. Rodríguez-Garrote, E. Lisa, E. Mendía, E. Lobo, N. Malats, A. Carrato, C. Guillen-Ponce, Circulating tumor cells (Ctc) and kras mutant circulating free Dna (cfdna) detection in peripheral blood as biomarkers in patients diagnosed with exocrine pancreatic cancer, BMC Cancer 15 (1) (2015) 1–10.
• https://www.cancervic.org.au/research/vcr/cancer-fact-sheets/pancreatic-cancer.html, May 2022, Accessed: 29.06.2022.
• A.G. Jain, M. Wazir, H. Zafar, J. Zhou, K. Khanal, A.K. Khan, S. Ahmad, Chapter 15 - Epidermal growth factor receptor role in pancreatic cancer, in: G.P. Nagaraju, S. Ahmad (Eds.), Theranostic Approach for Pancreatic Cancer, Academic Press, 2019, 295–324.
• A.E. Becker, Y.G. Hernandez, H. Frucht, A.L. Lucas, Pancreatic ductal adenocarcinoma: Risk factors, screening, and early detection, World J. Gastroenterol. 20 (32) (2014) 11182–11198.
• P. Storz, H.C. Crawford, Carcinogenesis of Pancreatic Ductal Adenocarcinoma, Gastroenterology 158 (8) (2020) 2072–2081.
• P.K. Simoes, S.H. Olson, A. Saldia, R.C. Kurtz, Epidemiology of Pancreatic Adenocarcinoma, Chinese Clin. Oncol. 6 (3) (2017) 24.
• M. Kapszewicz, E. Małecka-Wojciesko, Simple serum pancreatic ductal adenocarcinoma (Pdac) protein biomarkers—is there anything in sight?, J. Clin. Med. 10 (22) (2021) 5463.
• P. Michl, M. Löhr, J.P. Neoptolemos, G. Capurso, V. Rebours, N. Malats, M. Ollivier, L. Ricciardiello, UEG position paper on pancreatic cancer Bringing pancreatic cancer to the 21st century: Prevent, detect, and treat the disease earlier and better, United Eur. Gastroenterol. J. 9 (7) (2021) 860–871.
• C. Mottini, L. Cardone, Beyond the genomic mutation: Rethinking the molecular biomarkers of K-RAS dependency in pancreatic cancers, Int. J. Mol. Sci. 21 (14) (2020) 5023.
• S. Hafezi, M. Saber-Ayad, W.M. Abdel-Rahman, Highlights on the role of KRAS mutations in reshaping the microenvironment of pancreatic adenocarcinoma, Int. J. Mol. Sci. 22 (19) (2021) 10219.
• B. Bournet, C. Buscail, F. Muscari, P. Cordelier, L. Buscail, Targeting KRAS for diagnosis, prognosis, and treatment of pancreatic cancer: Hopes and realities, Eur. J. Cancer 54 (2016) 75–83.
• F.I. Nollmann, D.A. Ruess, Targeting mutant KRAS in pancreatic cancer: Futile or promising?, Biomedicines 8 (8) (2020) 281.
• S.F. Bannoura, M.H. Uddin, M. Nagasaka, F. Fazili, M.N. Al-Hallak, P.A. Philip, B. El-Rayes, A.S. Azmi, Targeting KRAS in pancreatic cancer: new drugs on the horizon, Cancer Metastasis Rev. 40 (3) (2021) 819–835.
• C. Johnson, D.L. Burkhart, K.M. Haigis, Classification of KRAS-Activating Mutations and the Implications for Therapeutic Intervention, Cancer Discov. 12 (4) (2022) 913–923.
• M. Saliani, A. Mirzaiebadizi, A. Javadmanesh, A. Siavoshi, M.R. Ahmadian, KRAS-related long noncoding RNAs in human cancers, Cancer Gene Ther. (2021) 418–427.
• P. Liu, Y. Wang, X. Li, Targeting the untargetable KRAS in cancer therapy, Acta Pharm. Sin. B 9 (5) (2019) 871–879.
• G. Zhu, L. Pei, H. Xia, Q. Tang, F. Bi, Role of oncogenic KRAS in the prognosis, diagnosis and treatment of colorectal cancer, Mol. Cancer 20 (1) (2021) 1–17.
• C. Muñoz-Maldonado, Y. Zimmer, M. Medová, A Comparative Analysis of Individual RAS Mutations in Cancer Biology, Front. Oncol. 9 (2019) 1088.
• A.F. Hezel, A.C. Kimmelman, B.Z. Stanger, N. Bardeesy, R. a Depinho, Genetics and biology of pancreatic ductal adenocarcinoma, Cold Spring Harb. Lab. Press 20 (10) (2006) 1218–1249.
• E. Zorde Khvalevsky, R. Gabai, I.H. Rachmut, E. Horwitz, Z. Brunschwig, A. Orbach, A. Shemi, T. Golan, A.J. Domb, E. Yavin, H. Giladi, L. Rivkin, A. Simerzin, R. Eliakim, A. Khalaileh, A. Hubert, M. Lahav, Y. Kopelman, E. Goldin, A. Dancour, et al., Mutant KRAS is a druggable target for pancreatic cancer, Proc. Natl. Acad. Sci. 110 (51) (2013) 20723–20728.
• Q.J. Wang, Z. Yu, K. Griffith, K. -i. Hanada, N.P. Restifo, J.C. Yang, Identification of T-cell Receptors Targeting KRAS-Mutated Human Tumors, Cancer Immunol. Res. 4 (3) (2016) 204–214.
• B. Bournet, F. Muscari, C. Buscail, E. Assenat, M. Barthet, P. Hammel, J. Selves, R. Guimbaud, P. Cordelier, L. Buscail, KRAS G12D Mutation Subtype Is A Prognostic Factor for Advanced Pancreatic Adenocarcinoma, Clin. Transl. Gastroenterol. 7 (3) (2016) 157.
• E. Tran, M. Ahmadzadeh, Y.C. Lu, A. Gros, S. Turcotte, P.F. Robbins, J.J. Gartner, Z. Zheng, Y.F. Li, S. Ray, J.R. Wunderlich, R.P. Somerville, S.A. Rosenberg, Immunogenicity of somatic mutations in human gastrointestinal cancers, Science 350 (6266) (2015) 1387–1390.
• C.A. Carter, A. Rajan, C. Keen, E. Szabo, S. Khozin, A. Thomas, C. Brzezniak, U. Guha, L.A. Doyle, S.M. Steinberg, L. Xi, M. Raffeld, Y. Tomita, M.J. Lee, S. Lee, J.B. Trepel, K.L. Reckamp, S. Koehler, B. Gitlitz, R. Salgia, et al., Selumetinib with and without erlotinib in KRAS mutant and KRAS wild-type advanced nonsmall-cell lung cancer, Ann. Oncol. 27 (4) (2016) 693–699.
• F. Garrido, N. Aptsiauri, Cancer immune escape: MHC expression in primary tumours versus metastases, Immunology 158 (4) (2019) 255–266.
• M. Padariya, U. Kalathiya, S. Mikac, K. Dziubek, M.C. Tovar Fernandez, E. Sroka, R. Fahraeus, A. Sznarkowska, Viruses, cancer and non-self recognition, Open Biol. 11 (3) (2021) 200348.
• A.S. Bear, T. Blanchard, J. Cesare, M.J. Ford, L.P. Richman, C. Xu, M.L. Baroja, S. McCuaig, C. Costeas, K. Gabunia, J. Scholler, A.D. Posey, M.H. O’Hara, A. Smole, D.J. Powell, B.A. Garcia, R.H. Vonderheide, G.P. Linette, B.M. Carreno, Biochemical and functional characterization of mutant KRAS epitopes validates this oncoprotein for immunological targeting, Nat. Commun. 12 (1) (2021) 1–16.
• J. Choi, S.P. Goulding, B.P. Conn, C.D. McGann, J.L. Dietze, J. Kohler, D. Lenkala, A. Boudot, D.A. Rothenberg, P.J. Turcott, J.R. Srouji, K.C. Foley, M.S. Rooney, M.M. van Buuren, R.B. Gaynor, J.G. Abelin, T.A. Addona, V.R. Juneja, Systematic discovery and validation of T cell targets directed against oncogenic KRAS mutations, Cell Reports Methods 1 (5) (2021) 100084.
• S. Zdanov, M. Mandapathil, R. Abu Eid, S. Adamson-Fadeyi, W. Wilson, J. Qian, A. Carnie, N. Tarasova, M. Mkrtichyan, J.A. Berzofsky, T.L. Whiteside, S.N. Khleif, Mutant KRAS Conversion of Conventional T Cells into Regulatory T Cells, Cancer Immunol. Res. 4 (4) (2016) 354–365.
• G.T. Clifton, H.E. Kohrt, G.E. Peoples, Critical issues in cancer vaccine trial design, Vaccine 33 (51) (2015) 7386–7392.
• U. Wiedermann, E. Garner-Spitzer, Y. Chao, M. Maglakelidze, I. Bulat, A. Dechaphunkul, W. Arpornwirat, C. Charoentum, C.J. Yen, T.C. Yau, S. Tanasanvimon, J. Maneechavakajorn, A. Sookprasert, L.Y. Bai, W.C. Chou, T. Ungtrakul, M. Drinic, J. Tobias, C.C. Zielinski, L. Chong, et al., Clinical and immunologic responses to a B-Cell epitope vaccine in patients with HER2/neu-overexpressing advanced gastric cancer—results from phase Ib trial IMUACS001, Clin. Cancer Res. 27 (13) (2021) 3649–3660.
• T. Jebastin, S. Narayanan, In silico epitope identification of unique multidrug resistance proteins from Salmonella Typhi for vaccine development, Comput. Biol. Chem. 78 (2019) 74–80.
• P. Rettman, M.D. Blunt, R.J. Fulton, A.F. Vallejo, L.Y. Bastidas-Legarda, L. España-Serrano, M.E. Polak, A. Al-Shamkhani, C. Retiere, S.I. Khakoo, Peptide: MHC-based DNA vaccination strategy to activate natural killer cells by targeting killer cell immunoglobulin-like receptors, J. Immunother. Cancer 9 (5) (2021) e001912.
• P. Rettman, M.D. Blunt, B. Mbiribindi, R. Fulton, R.B. Schittenhelm, A.V. Pulido, L. Bastidas-Legarda, M.E. Polak, R. Ayala, A.W. Purcell, A. Al-Shamkhani, C. Retiere, S.I. Khakoo, Peptide:MHC dependent activation of natural killer cells through KIR2DS2 generates anti-tumor responses, BioRxiv (2020).
• G.A. Cherryholmes, S.E. Stanton, M.L. Disis, Current methods of epitope identification for cancer vaccine design, Vaccine 33 (51) (2015) 7408–7414.
• D. Yeni; Tjahjono, Homology modeling epitop isocitrate dehydrogenase tipe 1 (r132h) 2 menggunakan modeller, i-tasser dan (ps) untuk vaksin glioma, 4 (1) (2017) 21–32.
• M.R. Pitman, R.I. Menz, Methods for protein homology modelling, Appl. Mycol. Biotechnol. 6 (C) (2006) 37–59.
• A.H. Mohseni, V. Razavilar, H. Keyvani, M.R. Razavi, R.A. Khavari-Nejad, Oral immunization with recombinant Lactococcus lactis NZ9000 expressing human papillomavirus type 16 E7 antigen and evaluation of its immune effects in female C57BL/6 mice, J. Med. Virol. 91 (2) (2019) 296–307.
• V. Pandey, V. Krishnan, N. Basak, A. Marathe, V. Thimmegowda, A. Dahuja, M. Jolly, A. Sachdev, Molecular modeling and in silico characterization of GmABCC5: a phytate transporter and potential target for low-phytate crops, 3 Biotech 8 (1) (2018) 1–16.
• M. Andreatta, M. Nielsen, Gapped sequence alignment using artificial neural networks: Application to the MHC class i system, Bioinformatics 32 (4) (2015) 511–517.
• R. Vita, S. Mahajan, J.A. Overton, S.K. Dhanda, S. Martini, J.R. Cantrell, D.K. Wheeler, A. Sette, B. Peters, The Immune Epitope Database (IEDB): 2018 update, Nucleic Acids Res. 47 (October 2018) (2018) 339–343.
• E.W. Hewitt, The MHC class I antigen presentation pathway: Strategies for viral immune evasion, Immunology 110 (2) (2003) 163–169.
• C.L.P. Eng, T.W. Tan, J.C. Tong, Immunoinformatics databases, Encycl. Bioinforma. Comput. Biol., 2018, 931-939.
• S. Urbán, G. Paragi, K. Burián, G.R. McLean, D.P. Virok, Identification of similar epitopes between severe acute respiratory syndrome coronavirus-2 and Bacillus Calmette–Guérin: potential for cross-reactive adaptive immunity, Clin. Transl. Immunol. 9 (12) (2020) e1227.
• M.W. Loffler, D.J. Kowalewski, L. Backert, J. Bernhardt, P. Adam, H. Schuster, F. Dengler, D. Backes, H.G. Kopp, S. Beckert, S. Wagner, I. Konigsrainer, O. Kohlbacher, L. Kanz, A. Konigsrainer, H.G. Rammensee, S. Stevanovic, S.P. Haen, Mapping the HLA ligandome of colorectal cancer reveals an imprint of malignant cell transformation, Cancer Res. 78 (16) (2018) 4627–4641.
• F. Heidary, M. Tourani, F. Hejazi-Amiri, S.H. Khatami, N. Jamali, M. Taheri-Anganeh, Design of a new multi-epitope peptide vaccine for non-small cell Lung cancer via vaccinology methods: an in silico study, Mol. Biol. Res. Commun. 11 (1) (2022) 55.
• I.A. Doytchinova, D.R. Flower, VaxiJen: A server for prediction of protective antigens, tumour antigens and subunit vaccines, BMC Bioinformatics 8 (1) (2007) 1–7.
• N. Zaharieva, I. Dimitrov, D.R. Flower, I. Doytchinova, VaxiJen Dataset of Bacterial Immunogens: An Update, Curr. Comput. Aided. Drug Des. 15 (5) (2019) 398–400.
• J. Yang, R. Yan, A. Roy, D. Xu, J. Poisson, Y. Zhang, The I-TASSER suite: Protein structure and function prediction, Nat. Methods 12 (1) (2015) 7–8.
• S. Kandasamy, S. Hassan, R. Gopalaswamy, S. Narayanan, Homology modelling, docking, pharmacophore and site directed mutagenesis analysis to identify the critical amino acid residue of PknI from Mycobacterium tuberculosis, J. Mol. Graph. Model. 52 (2014) 11–19.
• F. Sievers, D.G. Higgins, Clustal Omega for making accurate alignments of many protein sequences, Protein Sci. 27 (1) (2018) 135–145.
• F. Sievers, D.G. Higgins, The Clustal Omega Multiple Alignment Package, Methods Mol. Biol., 2021, 3–16.
• V.B. Chen, W.B. Arendall, J.J. Headd, D.A. Keedy, R.M. Immormino, G.J. Kapral, L.W. Murray, J.S. Richardson, D.C. Richardson, MolProbity: All-atom structure validation for macromolecular crystallography, Acta Crystallogr. Sect. D Biol. Crystallogr. 66 (1) (2010) 12–21.
• M. Wiederstein, M.J. Sippl, ProSA-web: Interactive web service for the recognition of errors in three-dimensional structures of proteins, Nucleic Acids Res. 35 (suppl_2) (2007) W407–W410.
• P. Benkert, M. Biasini, T. Schwede, Toward the estimation of the absolute quality of individual protein structure models, Bioinformatics 27 (3) (2011) 343–350.
• P. Benkert, M. Künzli, T. Schwede, QMEAN server for protein model quality estimation, Nucleic Acids Res. 37 (suppl_2) (2009) W510–W514.
• L. Heo, H. Park, C. Seok, GalaxyRefine: Protein structure refinement driven by side-chain repacking, Nucleic Acids Res. 41 (W1) (2013) W384–W388.
• J. Ko, H. Park, L. Heo, C. Seok, GalaxyWEB server for protein structure prediction and refinement, Nucleic Acids Res. 40 (W1) (2012) W294–W297.
• G.R. Lee, L. Heo, C. Seok, Effective protein model structure refinement by loop modeling and overall relaxation, Proteins 84 (2016) 293–301.
• C.J. Williams, J.J. Headd, N.W. Moriarty, M.G. Prisant, L.L. Videau, L.N. Deis, V. Verma, D.A. Keedy, B.J. Hintze, V.B. Chen, S. Jain, S.M. Lewis, W.B. Arendall, J. Snoeyink, P.D. Adams, S.C. Lovell, J.S. Richardson, D.C. Richardson, MolProbity: More and better reference data for improved all-atom structure validation, Protein Sci. 27 (1) (2018) 293–315.