Identificación y caracterización de linfocitos T neoantígeno específicos de donantes sanos con fines de inmunoterapia en cáncer

dc.contributor.advisorParra López, Carlos Alberto
dc.contributor.authorMartínez Enríquez, Laura Camila
dc.contributor.cvlacMartínez Enríquez, Laura Camila [0001705413]spa
dc.contributor.orcidMartinez Enriquez, Laura Camila [0000-0003-0799-942X]spa
dc.contributor.researchgroupInmunología y Medicina Traslacionalspa
dc.date.accessioned2023-01-16T12:57:53Z
dc.date.available2023-01-16T12:57:53Z
dc.date.issued2022-11-15
dc.descriptionilustraciones, diagramas, gráficas. tablasspa
dc.description.abstractLa inmunoterapia basada en neoantígenos permite estimular el sistema inmune del paciente con cáncer al inducir una respuesta antitumoral dirigida mediada por Linfocitos T (LT). Los neoantígenos son generados por mutaciones somáticas en el ADN que producen cambios en la secuencia de aminoácidos y que son exclusivas de las células tumorales. La selección de neoantígenos inmunogénicos se realiza por medio de herramientas in-silico que predicen la afinidad y tiempo de unión del neoantígeno a la molécula de HLA, luego estos son evaluados en sistemas de cultivo in-vitro con las células de los pacientes, sin embargo, la frecuencia reportada de respuestas a neoantígenos es aún baja. Por lo tanto, este estudio planteó dos acercamientos diferentes para identificar y caracterizar neoantígenos inmunogénicos. Por un lado, se propuso la implementación de sistemas de cultivo con células de donantes sanos para evaluar la inmunogenicidad de los neoantígenos de manera in-vitro. Por otra parte, se propuso el uso del docking y la dinámica molecular para identificar características moleculares asociadas a la inmunogenicidad de los neoantígenos. Para el primer enfoque se utilizaron células mononucleares de sangre periférica (PBMCs) de donantes sanos HLA-A*02:01. Se evaluaron cuatro tipos de cultivos diferentes, manteniendo el uso de las citoquinas IL-21, IL-15 e IL-7 pero modificando las células de partida: i) PBMCs totales, ii) cocultivo acelerado con células dendríticas a partir de PBMCs, iii) cocultivo de células dendríticas in-situ (DCs in-situ) con LT CD8+ vírgenes enriquecidos y iv) cocultivo de células dendríticas por adherencia de monocitos (moDCs) con LT CD8+ vírgenes enriquecidos. Los neoantígenos restringidos a HLA-A*02:01 fueron seleccionados a partir de una búsqueda en la literatura y se evaluaron en forma de pool. El reconocimiento de los LT CD8+ a neoantígenos se evaluó mediante la producción de las citoquinas IFN-γ y TNF-a y por la marcación de tetrámeros. Como resultados se pudo observar que es necesaria la presencia de células presentadoras profesionales, como lo son las DC, y un enriquecimiento de los LT CD8 vírgenes, pues fue en este cultivo que se logró detectar, aunque en baja proporción, LT específicos contra los neoantígenos. No obstante, estos resultados solo se observaron en 2 de 4 donantes evaluados, lo cual indica que es necesario realizar ensayos adicionales para poder determinar que este sistema de cultivo es el indicado. Para el segundo enfoque se realizó una prueba de concepto con dos neoantígenos (uno inmunogénico y otro no inmunogénico) para evaluar el uso del docking y la dinámica molecular como herramientas de tamizaje para la identificación de neoantígenos inmunogénicos, permitiendo determinar que un neoantígeno inmunogénico debe formar un complejo péptido-MHC estable en el tiempo. Este estudio demuestra la alta complejidad que representa el uso de células de donantes sanos y de las herramientas computacionales de docking y dinámica molecular, sin embargo, estos dos enfoques son prometedores ya que no solo permitirían mejorar la selección de neoantígenos inmunogénicos sino también tienen el potencial de identificar TCR específicos contra estos antígenos con fines de terapia adoptiva celular basada en modificación del TCR. (Texto tomado de la fuente)spa
dc.description.abstractImmunotherapy based on neoantigens allows to stimulate the immune system of cancer patients by inducing a directed antitumor response mediated by T cells. Neoantigens are generated by somatic mutations in DNA that produce changes in the amino acid sequence and are exclusive to tumor cells. The selection of immunogenic neoantigens to predict the affinity and binding of the neoantigen to the HLA is performed in silico and then evaluated with in vitro culture assays with patient cells, however, the reported frequency of responses to neoantigens is low. Therefore, this study proposed two different approaches to identify and characterize immunogenic neoantigens. On the one hand, the implementation of culture systems with cells from healthy donors to evaluate the immunogenicity of neoantigens in vitro. On the other hand, the use of docking and molecular dynamics to identify in silico molecular characteristics associated with the immunogenicity of neoantigens. To evaluate the first approach, peripheral blood mononuclear cells (PBMCs) from healthy HLA-A*02:01 donors were used as a model. HLA-A*02:01-restricted neoantigens were selected from a literature search and evaluated as a pool. Four different types of cultures were evaluated, maintaining the use of the cytokines IL-21, IL-15 and IL-7 but modifying the starting cells: i) total PBMCs, ii) accelerated co-culture with dendritic cells (acDCs) from PBMCs and iii ) co-culture of dendritic cells in situ with Naïve CD8+ T cells and iv) co-culture of monocyte derived dendritic cells with Naïve CD8+ T cells. Recognition of CD8+ T cells to neoantigens was assessed by cytokine production and by tetramer labeling. It was possible to observe that the presence of professional antigen presenting cells, such as DCs, and an enrichment of Naïve CD8+ T cells is necessary to detect, although in low proportion, specific LTs against neoantigens. However, these results were only observed in 2 of 4 donors evaluated, which indicates that additional tests are necessary to determine if this culture system work. For the second approach, a proof of concept was carried out with two neoantigens (one immunogenic and one non-immunogenic) to evaluate the use of docking and molecular dynamics as screening tools for the identification of immunogenic neoantigens, allowing to determine that an immunogenic neoantigen should form a peptide-MHC complex stable over time. This study demonstrates the high complexity of using healthy donor cells and tools such as molecular dynamics and docking, however, these two approaches are promising since they would not only allow to improve the selection of immunogenic neoantigens but also the identification of TCRs specific to neoantigens for adoptive cell therapy with cell modification of the TCReng
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagíster en Inmunologíaspa
dc.description.researchareaVacunas contra el cáncerspa
dc.format.extent144 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/82934
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.facultyFacultad de Medicinaspa
dc.publisher.placeBogotá, Colombiaspa
dc.publisher.programBogotá - Medicina - Maestría en Inmunologíaspa
dc.relation.references1. Pfister, S. and A. Ashworth, Marked for Death: Targeting Epigenetic Changes in Cancer. Nature reviews. Drug discovery, 2017. 16(4).spa
dc.relation.references2. Schreiber, R., L. Old, and M. Smyth, Cancer immunoediting: integrating immunity's roles in cancer suppression and promotion. Science (New York, N.Y.), 2011. 331(6024).spa
dc.relation.references3. Sung, H., et al., Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: a cancer journal for clinicians, 2021. 71(3).spa
dc.relation.references4. Wang, Z. and Y. Cao, Adoptive Cell Therapy Targeting Neoantigens: A Frontier for Cancer Research. Frontiers in immunology, 2020. 11spa
dc.relation.references5. Peng, M., et al., Neoantigen vaccine: an emerging tumor immunotherapy. Molecular cancer, 2019. 18(1).spa
dc.relation.references6. Kim, S., et al., Adoptive Cellular Therapy with Autologous Tumor-Infiltrating Lymphocytes and T-cell Receptor-Engineered T Cells Targeting Common p53 Neoantigens in Human Solid Tumors. Cancer immunology research, 2022. 10(8).spa
dc.relation.references7. Tran, E., et al., T-Cell Transfer Therapy Targeting Mutant KRAS in Cancer. The New England journal of medicine, 2016. 375(23).spa
dc.relation.references8. Sahin, U., et al., Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer. Nature, 2017. 547(7662).spa
dc.relation.references9. Keskin, D., et al., Neoantigen vaccine generates intratumoral T cell responses in phase Ib glioblastoma trial. Nature, 2019. 565(7738).spa
dc.relation.references10. Li, F., et al., Neoantigen vaccination induces clinical and immunologic responses in non-small cell lung cancer patients harboring EGFR mutations. Journal for immunotherapy of cancer, 2021. 9(7).spa
dc.relation.references11. Ott, P., et al., An immunogenic personal neoantigen vaccine for patients with melanoma. Nature, 2017. 547(7662).spa
dc.relation.references12. Carreno, B., et al., Cancer immunotherapy. A dendritic cell vaccine increases the breadth and diversity of melanoma neoantigen-specific T cells. Science (New York, N.Y.), 2015. 348(6236).spa
dc.relation.references13. Jiang, T., et al., Tumor Neoantigens: From Basic Research to Clinical Applications. Journal of hematology & oncology, 2019. 12(1).spa
dc.relation.references14. Coulie, P., et al., Tumour Antigens Recognized by T Lymphocytes: At the Core of Cancer Immunotherapy. Nature reviews. Cancer, 2014. 14(2).spa
dc.relation.references15. Garcia-Garijo, A., C.A. Fajardo, and A. Gros, Determinants for Neoantigen Identification. Front Immunol, 2019. 10: p. 1392.spa
dc.relation.references16. Schumacher, T.N., W. Scheper, and P. Kvistborg, Cancer Neoantigens. Annu Rev Immunol, 2019. 37: p. 173-200.spa
dc.relation.references17. Karpanen, T. and J. Olweus, The Potential of Donor T-Cell Repertoires in Neoantigen-Targeted Cancer Immunotherapy. Front Immunol, 2017. 8: p. 1718spa
dc.relation.references18. Wells, D., et al., Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction. Cell, 2020. 183(3).spa
dc.relation.references19. Bradley, P. and P. Thomas, Using T Cell Receptor Repertoires to Understand the Principles of Adaptive Immune Recognition. Annual review of immunology, 2019. 37.spa
dc.relation.references20. Baitsch, L., et al., The three main stumbling blocks for anticancer T cells. Trends Immunol, 2012. 33(7): p. 364-72.spa
dc.relation.references21. Salo-Ahen, O., et al., Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development. Processes, 2020. 9(1): p. 71spa
dc.relation.references22. Stronen, E., et al., Targeting of cancer neoantigens with donor-derived T cell receptor repertoires. Science, 2016. 352(6291): p. 1337-41.spa
dc.relation.references23. Rosenberg, S., et al., Adoptive Cell Transfer: A Clinical Path to Effective Cancer Immunotherapy. Nature reviews. Cancer, 2008. 8(4).spa
dc.relation.references24. Ott, P., et al., An Update on Adoptive T-Cell Therapy and Neoantigen Vaccines. American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting, 2019. 39.spa
dc.relation.references25. Vigneron, N., Human Tumor Antigens and Cancer Immunotherapy. BioMed Research International, 2015. 2015.spa
dc.relation.references26. Pan, R., et al., Recent Development and Clinical Application of Cancer Vaccine: Targeting Neoantigens. Journal of immunology research, 2018. 2018spa
dc.relation.references27. Hutchison, S. and A. Pritchard, Identifying Neoantigens for Use in Immunotherapy. Mammalian genome : official journal of the International Mammalian Genome Society, 2018. 29(11-12).spa
dc.relation.references28. Bräunlein, E. and A. Krackhardt, Identification and Characterization of Neoantigens As Well As Respective Immune Responses in Cancer Patients. Frontiers in immunology, 2017. 8.spa
dc.relation.references29. Smith, C.C., et al., Alternative tumour-specific antigens. Nat Rev Cancer, 2019. 19(8): p. 465-78.spa
dc.relation.references30. Turajlic, S., et al., Insertion-and-deletion-derived Tumour-Specific Neoantigens and the Immunogenic Phenotype: A Pan-Cancer Analysis. The Lancet. Oncology, 2017. 18(8).spa
dc.relation.references31. van der Lee, D., et al., Mutated Nucleophosmin 1 as Immunotherapy Target in Acute Myeloid Leukemia. The Journal of clinical investigation, 2019. 129(2).spa
dc.relation.references32. Inderberg, E., et al., T cell therapy targeting a public neoantigen in microsatellite instable colon cancer reduces in vivo tumor growth. Oncoimmunology, 2017. 6(4).spa
dc.relation.references33. Saeterdal, I., et al., A TGF betaRII frameshift-mutation-derived CTL epitope recognised by HLA-A2-restricted CD8+ T cells. Cancer immunology, immunotherapy : CII, 2001. 50(9).spa
dc.relation.references34. Koster, J. and R. Plasterk, A Library of Neo Open Reading Frame Peptides (NOPs) as a Sustainable Resource of Common Neoantigens in Up to 50% of Cancer Patients. Scientific reports, 2019. 9(1).spa
dc.relation.references35. PM, A., Cellular Therapy Against Public Neoantigens. The Journal of clinical investigation, 2019. 129(2).spa
dc.relation.references36. Verdon, D. and M. Jenkins, Identification and Targeting of Mutant Peptide Neoantigens in Cancer Immunotherapy. Cancers, 2021. 13(16).spa
dc.relation.references37. Yossef, R., et al., Enhanced Detection of Neoantigen-Reactive T Cells Targeting Unique and Shared Oncogenes for Personalized Cancer Immunotherapy. JCI insight, 2018. 3(19).spa
dc.relation.references38. Zhou, J., et al., Neoantigens Derived from Recurrently Mutated Genes as Potential Immunotherapy Targets for Gastric Cancer. BioMed Research International, 2019. 2019.spa
dc.relation.references39. Olivera, I., et al., Exploiting TCR Recognition of Shared Hotspot Oncogene-encoded Neoantigens. Clinical cancer research : an official journal of the American Association for Cancer Research, 2020. 26(6).spa
dc.relation.references40. Cafri, G., et al., Memory T Cells Targeting Oncogenic Mutations Detected in Peripheral Blood of Epithelial Cancer Patients. Nature communications, 2019. 10(1).spa
dc.relation.references41. Schultz, N., et al., Frequencies and Prognostic Role of KRAS and BRAF Mutations in Patients With Localized Pancreatic and Ampullary Adenocarcinomas. Pancreas, 2012. 41(5).spa
dc.relation.references42. Chen, F., et al., Neoantigen Identification Strategies Enable Personalized Immunotherapy in Refractory Solid Tumors. The Journal of clinical investigation, 2019.spa
dc.relation.references43. McGranahan, N., et al., Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science (New York, N.Y.), 2016. 351(6280).spa
dc.relation.references44. Wolf, Y., et al., UVB-Induced Tumor Heterogeneity Diminishes Immune Response in Melanoma. Cell, 2019. 179(1).spa
dc.relation.references45. Klebanoff, C. and J. Wolchok, Shared Cancer Neoantigens: Making Private Matters Public. The Journal of experimental medicine, 2018. 215(1).spa
dc.relation.references46. Lugli, E., P. Kvistborg, and G. Galletti, Cancer Neoantigens Targeted by Adoptive T Cell Transfer: Private No More. The Journal of clinical investigation, 2019. 129(3).spa
dc.relation.references47. Pearlman, A., et al., Targeting public neoantigens for cancer immunotherapy. Nature cancer, 2021. 2(5).spa
dc.relation.references48. Castle, J., et al., Mutation-Derived Neoantigens for Cancer Immunotherapy. Frontiers in immunology, 2019. 10.spa
dc.relation.references49. Bassani-Sternberg, M., Mass Spectrometry Based Immunopeptidomics for the Discovery of Cancer Neoantigens. Methods in molecular biology (Clifton, N.J.), 2018. 1719.spa
dc.relation.references50. Yavad, M., et al., Predicting Immunogenic Tumour Mutations by Combining Mass Spectrometry and Exome Sequencing. Nature, 2014. 515(7528).spa
dc.relation.references51. Trolle, T. and M. Nielsen, NetTepi: An Integrated Method for the Prediction of T Cell Epitopes. Immunogenetics, 2014. 66(7-8).spa
dc.relation.references52. Hundal, J., et al., pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens. Cancer immunology research, 2020. 8(3).spa
dc.relation.references53. Lee, C., et al., Update on Tumor Neoantigens and Their Utility: Why It Is Good to Be Different. Trends in immunology, 2018. 39(7).spa
dc.relation.references54. Nonomura, C., et al., Identification of a neoantigen epitope in a melanoma patient with good response to anti-PD-1 antibody therapy. Immunol Lett, 2019. 208: p. 52-59.spa
dc.relation.references55. Wells, D., et al., Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction. Cell, 2020. 183(3).spa
dc.relation.references57. Richters, M., et al., Best practices for bioinformatic characterization of neoantigens for clinical utility. Genome medicine, 2019. 11(1).spa
dc.relation.references58. Vitiello, A. and M. Zanetti, Neoantigen Prediction and the Need for Validation. Nature biotechnology, 2017. 35(9).spa
dc.relation.references59. Kim, Y., et al., Dataset size and composition impact the reliability of performance benchmarks for peptide-MHC binding predictions. BMC bioinformatics, 2014. 15(1).spa
dc.relation.references60. Capietto, A., S. Jhunjhunwala, and L. Delamarre, Characterizing neoantigens for personalized cancer immunotherapy. Current opinion in immunology, 2017. 46.spa
dc.relation.references61. Kishton, R., R. Lynn, and N. Restifo, Strength in Numbers: Identifying Neoantigen Targets for Cancer Immunotherapy. Cell, 2020. 183(3).spa
dc.relation.references62. Roerden, M., A. Nelde, and J. Walz, Neoantigens in Hematological Malignancies-Ultimate Targets for Immunotherapy? Frontiers in immunology, 2019. 10spa
dc.relation.references63. Wagner, S., C.S. Mullins, and M. Linnebacher, Colorectal cancer vaccines: Tumor-associated antigens vs neoantigens. World J Gastroenterol, 2018. 24(48): p. 5418-32.spa
dc.relation.references64. Biernacki, M. and M. Bleakley, Neoantigens in Hematologic Malignancies. Frontiers in immunology, 2020. 11.spa
dc.relation.references65. Peng, S., et al., Sensitive Detection and Analysis of Neoantigen-Specific T Cell Populations From Tumors and Blood. Cell reports, 2019. 28(10).spa
dc.relation.references66. Bentzen, A. and S. Hadrup, Evolution of MHC-based Technologies Used for Detection of Antigen-Responsive T Cells. Cancer immunology, immunotherapy : CII, 2017. 66(5).spa
dc.relation.references67. Arnaud, M., et al., Biotechnologies to Tackle the Challenge of Neoantigen Identification. Current opinion in biotechnology, 2020. 65.spa
dc.relation.references68. Kato, T., et al., Effective Screening of T Cells Recognizing Neoantigens and Construction of T-cell Receptor-Engineered T Cells. Oncotarget, 2018. 9(13).spa
dc.relation.references69. Reading, J., et al., The Function and Dysfunction of Memory CD8 + T Cells in Tumor Immunity. Immunological reviews, 2018. 283(1)spa
dc.relation.references70. Ali, M., et al., Induction of neoantigen-reactive T cells from healthy donors. Nat Protoc, 2019. 14(6): p. 1926-1943.spa
dc.relation.references71. Yadav, M. and L. Delamarre, IMMUNOTHERAPY. Outsourcing the Immune Response to Cancer. Science (New York, N.Y.), 2016. 352(6291).spa
dc.relation.references72. Yamamoto, T.N., R.J. Kishton, and N.P. Restifo, Developing neoantigen-targeted T cell-based treatments for solid tumors. Nat Med, 2019. 25(10): p. 1488-1499spa
dc.relation.references73. Chapuis, A., et al., Transferred WT1-reactive CD8+ T cells can mediate antileukemic activity and persist in post-transplant patients. Science translational medicine, 2013. 5(174).spa
dc.relation.references74. Ohminami, H., M. Yasukawa, and S. Fujita, HLA class I-restricted lysis of leukemia cells by a CD8(+) cytotoxic T-lymphocyte clone specific for WT1 peptide. Blood, 2000. 95(1).spa
dc.relation.references75. Barnes, E., et al., Ultra-sensitive Class I Tetramer Analysis Reveals Previously Undetectable Populations of Antiviral CD8+ T Cells. European journal of immunology, 2004. 34(6).spa
dc.relation.references76. Koning, D., et al., In Vitro Expansion of Antigen-Specific CD8(+) T Cells Distorts the T-cell Repertoire. Journal of immunological methods, 2014. 405.spa
dc.relation.references77. Montes, M., et al., Optimum in Vitro Expansion of Human Antigen-Specific CD8 T Cells for Adoptive Transfer Therapy. Clinical and experimental immunology, 2005. 142(2).spa
dc.relation.references78. Dwyer, C., et al., Fueling Cancer Immunotherapy With Common Gamma Chain Cytokines. Frontiers in immunology, 2019. 10.spa
dc.relation.references79. Wölfl, M. and P. Greenberg, Antigen-specific Activation and Cytokine-Facilitated Expansion of Naive, Human CD8+ T Cells. Nature protocols, 2014. 9(4).spa
dc.relation.references80. Shevach, E., Mechanisms of foxp3+ T Regulatory Cell-Mediated Suppression. Immunity, 2009. 30(5).spa
dc.relation.references81. Gao, J., et al., Mechanism of Action of IL-7 and Its Potential Applications and Limitations in Cancer Immunotherapy, in Int J Mol Sci. 2015. p. 10267-80.spa
dc.relation.references82. Steel, J., T. Waldmann, and J. Morris, Interleukin-15 Biology and Its Therapeutic Implications in Cancer. Trends in pharmacological sciences, 2012. 33(1).spa
dc.relation.references83. Li, Y. and C. Yee, IL-21 Mediated Foxp3 Suppression Leads to Enhanced Generation of Antigen-Specific CD8+ Cytotoxic T Lymphocytes. Blood, 2008. 111(1).spa
dc.relation.references84. Wherry, E.J. and M. Kurachi, Molecular and cellular insights into T cell exhaustion. Nat Rev Immunol, 2015. 15(8): p. 486-99.spa
dc.relation.references85. Legat, A., et al., Inhibitory Receptor Expression Depends More Dominantly on Differentiation and Activation Than "Exhaustion" of Human CD8 T Cells. Frontiers in immunology, 2013. 4.spa
dc.relation.references86. Thommen, D. and T. Schumacher, T Cell Dysfunction in Cancer. Cancer cell, 2018. 33(4).spa
dc.relation.references87. Gonzalez, M. and M. Kann, Chapter 4: Protein interactions and disease. PLoS computational biology, 2012. 8(12).spa
dc.relation.references88. London, N., B. Raveh, and O. Schueler-Furman, Peptide docking and structure-based characterization of peptide binding: from knowledge to know-how. Current opinion in structural biology, 2013. 23(6).spa
dc.relation.references89. Janes, M., et al., Targeting KRAS Mutant Cancers with a Covalent G12C-Specific Inhibitor. Cell, 2018. 172(3).spa
dc.relation.references90. Ferreira, L., et al., Molecular docking and structure-based drug design strategies. Molecules (Basel, Switzerland), 2015. 20(7).spa
dc.relation.references91. Graves, J., et al., A Review of Deep Learning Methods for Antibodies. Antibodies (Basel, Switzerland), 2020. 9(2).spa
dc.relation.references92. Lengauer, T. and M. Rarey, Computational methods for biomolecular docking. Current opinion in structural biology, 1996. 6(3).spa
dc.relation.references93. Pinzi, L. and G. Rastelli, Molecular Docking: Shifting Paradigms in Drug Discovery. International journal of molecular sciences, 2019. 20(18).spa
dc.relation.references94. Ciemny, M., et al., Protein-peptide docking: opportunities and challenges. Drug discovery today, 2018. 23(8).spa
dc.relation.references95. Mahapatra, S., et al., Immunoinformatics and molecular docking studies reveal a novel Multi-Epitope peptide vaccine against pneumonia infection. Vaccine, 2021. 39(42).spa
dc.relation.references96. Krüger, D., et al., Structure-Based Design of Non-natural Macrocyclic Peptides That Inhibit Protein-Protein Interactions. Journal of medicinal chemistry, 2017. 60(21).spa
dc.relation.references97. Salmaso, V. and S. Moro, Bridging Molecular Docking to Molecular Dynamics in Exploring Ligand-Protein Recognition Process: An Overview. Frontiers in pharmacology, 2018. 9.spa
dc.relation.references98. Bitencourt-Ferreira, G. and W. de Azevedo, Molecular Dynamics Simulations with NAMD2. Methods in molecular biology (Clifton, N.J.), 2019. 2053spa
dc.relation.references99. Wang, J., et al., Improved Modeling of Peptide-Protein Binding Through Global Docking and Accelerated Molecular Dynamics Simulations. Frontiers in molecular biosciences, 2019. 6.spa
dc.relation.references100. Hollingsworth, S. and R. Dror, Molecular Dynamics Simulation for All. Neuron, 2018. 99(6).spa
dc.relation.references101. Kumar, N. and D. Mohanty, Structure-based identification of MHC binding peptides: Benchmarking of prediction accuracy. 2010.spa
dc.relation.references102. Mei, X., et al., The Use of Molecular Dynamics Simulation Method to Quantitatively Evaluate the Affinity between HBV Antigen T Cell Epitope Peptides and HLA-A Molecules. International journal of molecular sciences, 2022. 23(9).spa
dc.relation.references103. Mirza, M., et al., Towards peptide vaccines against Zika virus: Immunoinformatics combined with molecular dynamics simulations to predict antigenic epitopes of Zika viral proteins. Scientific reports, 2016. 6.spa
dc.relation.references104. Rantam, F., et al., Molecular docking and dynamic simulation of conserved B cell epitope of SARS-CoV-2 glycoprotein Indonesian isolates: an immunoinformatic approach. F1000Research, 2021. 10.spa
dc.relation.references105. Riley, T., et al., Structure Based Prediction of Neoantigen Immunogenicity. Frontiers in immunology, 2019. 10spa
dc.relation.references106. Pang, Y., et al., Peptide-Binding Groove Contraction Linked to the Lack of T Cell Response: Using Complex Structure and Energy To Identify Neoantigens. ImmunoHorizons, 2018. 2(7).spa
dc.relation.references107. Tram, C., O. Hrytsenko, and M. Stanford, Optimization of the T2 HLA-A2 shift assay for testing of the biological activity of immunotherapies.spa
dc.relation.references108. Kessler, J., et al., Competition-based Cellular Peptide Binding Assay for HLA Class I. Current protocols in immunology, 2004. Chapter 18.spa
dc.relation.references109. Alanio, C., et al., Enumeration of human antigen-specific naive CD8+ T cells reveals conserved precursor frequencies. Blood, 2010. 115(18).spa
dc.relation.references110. McLaughlin-Taylor, E., et al., Identification of the major late human cytomegalovirus matrix protein pp65 as a target antigen for CD8+ virus-specific cytotoxic T lymphocytes. Journal of medical virology, 1994. 43(1).spa
dc.relation.references111. Martinuzzi, E., et al., acDCs enhance human antigen-specific T-cell responses. Blood, 2011. 118(8).spa
dc.relation.references112. Kuranda, K., et al., In Vitro Expansion of Anti-viral T Cells from Cord Blood by Accelerated Co-cultured Dendritic Cells. Molecular therapy. Methods & clinical development, 2018. 13.spa
dc.relation.references113. Berman, H.M., et al., The Protein Data Bank. Nucleic Acids Research, 2000. 28(1): p. 235-242.spa
dc.relation.references114. Raveh, B., et al., Rosetta FlexPepDock ab-initio: simultaneous folding, docking and refinement of peptides onto their receptors. PloS one, 2011. 6(4).spa
dc.relation.references115. Leaver-Fay, A., et al., ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules. Methods in enzymology, 2011. 487.spa
dc.relation.references116. Humphrey, W., A. Dalke, and K. Schulten, VMD: visual molecular dynamics. Journal of molecular graphics, 1996. 14(1).spa
dc.relation.references117. Phillips, J., et al., Scalable molecular dynamics on CPU and GPU architectures with NAMD. The Journal of chemical physics, 2020. 153(4).spa
dc.relation.references118. Huang, J. and A. MacKerell, CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data. Journal of computational chemistry, 2013. 34(25).spa
dc.relation.references119. Bayarri, G., A. Hospital, and M. Orozco, 3dRS, a Web-Based Tool to Share Interactive Representations of 3D Biomolecular Structures and Molecular Dynamics Trajectories. Frontiers in molecular biosciences, 2021. 8.spa
dc.relation.references120. Scheurer, M., et al., PyContact: Rapid, Customizable, and Visual Analysis of Noncovalent Interactions in MD Simulations. Biophysical journal, 2018. 114(3).spa
dc.relation.references121. Choi, J., et al., Systematic discovery and validation of T cell targets directed against oncogenic KRAS mutations. Cell reports methods, 2021. 1(5).spa
dc.relation.references122. Lo, W., et al., Immunologic Recognition of a Shared p53 Mutated Neoantigen in a Patient with Metastatic Colorectal Cancer. Cancer immunology research, 2019. 7(4).spa
dc.relation.references123. Malekzadeh, P., et al., Neoantigen screening identifies broad TP53 mutant immunogenicity in patients with epithelial cancers. The Journal of clinical investigation, 2019. 129(3).spa
dc.relation.references124. Chamucero-Millares, J., D. Bernal-Estévez, and C. Parra-López, Usefulness of IL-21, IL-7, and IL-15 conditioned media for expansion of antigen-specific CD8+ T cells from healthy donor-PBMCs suitable for immunotherapy. Cellular immunology, 2021. 360spa
dc.relation.references125. Rico, A., et al., Epidemiology of cytomegalovirus Infection among mothers and infants in Colombia. Journal of medical virology, 2021. 93(11).spa
dc.relation.references126. Feng-Qin, F., et al., Incidence of Cytomegalovirus Infection in Shanghai, China. 2009.spa
dc.relation.references127. Mueller, D., M. Jenkins, and R. Schwartz, Clonal expansion versus functional clonal inactivation: a costimulatory signalling pathway determines the outcome of T cell antigen receptor occupancy. Annual review of immunology, 1989. 7.spa
dc.relation.references128. Chen, L. and D. Flies, Molecular mechanisms of T cell co-stimulation and co-inhibition. Nature reviews. Immunology, 2013. 13(4).spa
dc.relation.references129. Cui, W. and S. Kaech, Generation of effector CD8+ T cells and their conversion to memory T cells. Immunological reviews, 2010. 236.spa
dc.relation.references130. Kalia, V. and S. Sarkar, Regulation of Effector and Memory CD8 T Cell Differentiation by IL-2-A Balancing Act. Frontiers in immunology, 2018. 9.spa
dc.relation.references131. Drijfhout, J., et al., Detailed motifs for peptide binding to HLA-A*0201 derived from large random sets of peptides using a cellular binding assay. Human immunology, 1995. 43(1).spa
dc.relation.references132. Jou, J., et al., The Changing Landscape of Therapeutic Cancer Vaccines-Novel Platforms and Neoantigen Identification. Clinical cancer research : an official journal of the American Association for Cancer Research, 2021. 27(3).spa
dc.relation.references133. Blass, E. and P. Ott, Advances in the development of personalized neoantigen-based therapeutic cancer vaccines. Nature reviews. Clinical oncology, 2021. 18(4).spa
dc.relation.references134. Jurtz, V., et al., NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data. Journal of immunology (Baltimore, Md. : 1950), 2017. 199(9).spa
dc.relation.references135. O'Donnell, T., et al., MHCflurry: Open-Source Class I MHC Binding Affinity Prediction. Cell systems, 2018. 7(1).spa
dc.relation.references136. Zhang, H., O. Lund, and M. Nielsen, The PickPocket method for predicting binding specificities for receptors based on receptor pocket similarities: application to MHC-peptide binding. Bioinformatics (Oxford, England), 2009. 25(10).spa
dc.relation.references137. Jørgensen, K., et al., NetMHCstab - predicting stability of peptide-MHC-I complexes; impacts for cytotoxic T lymphocyte epitope discovery. Immunology, 2014. 141(1).spa
dc.relation.references138. Chandran, S., et al., Immunogenicity and therapeutic targeting of a public neoantigen derived from mutated PIK3CA. Nature medicine, 2022. 28(5).spa
dc.relation.references139. Páez-Gutiérrez, I., et al., HLA-A, -B, -C, -DRB1 and -DQB1 allele and haplotype frequencies of 1463 umbilical cord blood units typed in high resolution from Bogotá, Colombia. Human immunology, 2019. 80(7).spa
dc.relation.references140. Gonzalez-Galarza, F., et al., Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data and new query tools. Nucleic acids research, 2020. 48(D1).spa
dc.relation.references141. Akazawa, Y., et al., Efficacy of immunotherapy targeting the neoantigen derived from epidermal growth factor receptor T790M/C797S mutation in non-small cell lung cancer. Cancer science, 2020. 111(8).spa
dc.relation.references142. Yamada, T., et al., EGFR T790M mutation as a possible target for immunotherapy; identification of HLA-A*0201-restricted T cell epitopes derived from the EGFR T790M mutation. PloS one, 2013. 8(11).spa
dc.relation.references143. Holmström, M. and M. Andersen, Healthy Donors Harbor Memory T Cell Responses to RAS Neo-Antigens. Cancers, 2020. 12(10).spa
dc.relation.references144. Holmström, M., et al., High frequencies of circulating memory T cells specific for calreticulin exon 9 mutations in healthy individuals. Blood cancer journal, 2019. 9(2).spa
dc.relation.references145. Wu, Y., et al., HLA-A2-Restricted Epitopes Identified from MTA1 Could Elicit Antigen-Specific Cytotoxic T Lymphocyte Response. Journal of immunology research, 2018. 2018.spa
dc.relation.references146. Hu, Z., et al., A cloning and expression system to probe T-cell receptor specificity and assess functional avidity to neoantigens. Blood, 2018. 132(18).spa
dc.relation.references147. Chheda, Z., et al., Novel and shared neoantigen derived from histone 3 variant H3.3K27M mutation for glioma T cell therapy. The Journal of experimental medicine, 2018. 215(1).spa
dc.relation.references148. Han, K., et al., Streamlined selection of cancer antigens for vaccine development through integrative multi-omics and high-content cell imaging. Scientific reports, 2020. 10(1).spa
dc.relation.references149. Flatmark, K., et al., Peptide vaccine targeting mutated GNAS: a potential novel treatment for pseudomyxoma peritonei. Journal for immunotherapy of cancer, 2021. 9(10).spa
dc.relation.references150. Wang, Z., et al., Identification of HLA-A2-Restricted Mutant Epitopes from Neoantigens of Esophageal Squamous Cell Carcinoma. Vaccines, 2021. 9(10).spa
dc.relation.references151. Iiizumi, S., et al., Identification of Novel HLA Class II-Restricted Neoantigens Derived from Driver Mutations. Cancers, 2019. 11(2).spa
dc.relation.references152. Nielsen, J., et al., Mapping the human T cell repertoire to recurrent driver mutations in MYD88 and EZH2 in lymphoma. Oncoimmunology, 2017. 6(7).spa
dc.relation.references153. Rivero-Hinojosa, S., et al., Proteogenomic discovery of neoantigens facilitates personalized multi-antigen targeted T cell immunotherapy for brain tumors. Nature communications, 2021. 12(1).spa
dc.relation.references154. Shi, R., et al., Screening and identification of HLA-A2-restricted neoepitopes for immunotherapy of non-microsatellite instability-high colorectal cancer. Science China. Life sciences, 2022. 65(3).spa
dc.relation.references155. Tang, Y., et al., The co-stimulation of anti-CD28 and IL-2 enhances the sensitivity of ELISPOT assays for detection of neoantigen-specific T cells in PBMC. Journal of immunological methods, 2020. 484-485.spa
dc.relation.references156. Galloway, S., et al., Peptide Super-Agonist Enhances T-Cell Responses to Melanoma. Frontiers in immunology, 2019. 10.spa
dc.relation.references157. Greiner, J., et al., Mutated regions of nucleophosmin 1 elicit both CD4(+) and CD8(+) T-cell responses in patients with acute myeloid leukemia. Blood, 2012. 120(6).spa
dc.relation.references158. Matsuda, T., et al., Induction of Neoantigen-Specific Cytotoxic T Cells and Construction of T-cell Receptor-Engineered T Cells for Ovarian Cancer. Clinical cancer research : an official journal of the American Association for Cancer Research, 2018. 24(21).spa
dc.relation.references159. Paret, C., et al., Identification of an Immunogenic Medulloblastoma-Specific Fusion Involving EPC2 and GULP1. Cancers, 2021. 13(22).spa
dc.relation.references160. Biernacki, M., et al., CBFB-MYH11 fusion neoantigen enables T cell recognition and killing of acute myeloid leukemia. The Journal of clinical investigation, 2020. 130(10).spa
dc.relation.references161. Bear, A.S., et al., Biochemical and functional characterization of mutant KRAS epitopes validates this oncoprotein for immunological targeting. Nature Communications, 2021. 12(1): p. 1-16.spa
dc.relation.references162. Shinkawa, T., et al., Characterization of CD8 + T-cell responses to non-anchor-type HLA class I neoantigens with single amino-acid substitutions. Oncoimmunology, 2021. 10(1).spa
dc.relation.references163. Çınar, Ö., et al., High-affinity T-cell receptor specific for MyD88 L265P mutation for adoptive T-cell therapy of B-cell malignancies. Journal for immunotherapy of cancer, 2021. 9(7).spa
dc.relation.references164. Lazdun, Y., et al., A New Pipeline to Predict and Confirm Tumor Neoantigens Predict Better Response to Immune Checkpoint Blockade. Molecular cancer research : MCR, 2021. 19(3).spa
dc.relation.references165. Colugnati, F., et al., Incidence of cytomegalovirus infection among the general population and pregnant women in the United States. BMC infectious diseases, 2007. 7.spa
dc.relation.references166. Tokars, J.I., et al., Seasonal Incidence of Symptomatic Influenza in the United States. Clinical Infectious Diseases, 2018. 66(10): p. 1511-1518.spa
dc.relation.references167. Wills, M., et al., The human cytotoxic T-lymphocyte (CTL) response to cytomegalovirus is dominated by structural protein pp65: frequency, specificity, and T-cell receptor usage of pp65-specific CTL. Journal of virology, 1996. 70(11).spa
dc.relation.references168. Gamadia, L., et al., Differentiation of cytomegalovirus-specific CD8(+) T cells in healthy and immunosuppressed virus carriers. Blood, 2001. 98(3).spa
dc.relation.references169. He, X., et al., High frequencies cytomegalovirus pp65(495-503)-specific CD8+ T cells in healthy young and elderly Chinese donors: characterization of their phenotypes and TCR Vbeta usage. Journal of clinical immunology, 2006. 26(5).spa
dc.relation.references170. Choo, J., et al., The immunodominant influenza A virus M158-66 cytotoxic T lymphocyte epitope exhibits degenerate class I major histocompatibility complex restriction in humans. Journal of virology, 2014. 88(18).spa
dc.relation.references171. Soema, P., et al., Whole-Inactivated Influenza Virus Is a Potent Adjuvant for Influenza Peptides Containing CD8 + T Cell Epitopes. Frontiers in immunology, 2018. 9.spa
dc.relation.references172. Sridhar, S., et al., Cellular immune correlates of protection against symptomatic pandemic influenza. Nature medicine, 2013. 19(10).spa
dc.relation.references173. Jin, X., et al., High frequency of cytomegalovirus-specific cytotoxic T-effector cells in HLA-A*0201-positive subjects during multiple viral coinfections. The Journal of infectious diseases, 2000. 181(1).spa
dc.relation.references174. Cimen Bozkus, C., et al., Immune Checkpoint Blockade Enhances Shared Neoantigen-Induced T-cell Immunity Directed against Mutated Calreticulin in Myeloproliferative Neoplasms. Cancer discovery, 2019. 9(9).spa
dc.relation.references175. Ott, P., 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(2).spa
dc.relation.references176. Pittet, M., et al., High frequencies of naive Melan-A/MART-1-specific CD8(+) T cells in a large proportion of human histocompatibility leukocyte antigen (HLA)-A2 individuals. The Journal of experimental medicine, 1999. 190(5).spa
dc.relation.references177. Hinrichs, C., et al., IL-2 and IL-21 confer opposing differentiation programs to CD8+ T cells for adoptive immunotherapy. Blood, 2008. 111(11).spa
dc.relation.references178. Hondowicz, B., et al., Discovery of T cell antigens by high-throughput screening of synthetic minigene libraries. PloS one, 2012. 7(1).spa
dc.relation.references179. Grunert, C., et al., Isolation of Neoantigen-Specific Human T Cell Receptors from Different Human and Murine Repertoires. Cancers, 2022. 14(7).spa
dc.relation.references180. Roudko, V., et al., Shared Immunogenic Poly-Epitope Frameshift Mutations in Microsatellite Unstable Tumors. Cell, 2020. 183(6).spa
dc.relation.references181. Arstila, T., et al., A direct estimate of the human alphabeta T cell receptor diversity. Science (New York, N.Y.), 1999. 286(5441).spa
dc.relation.references182. Cieri, N., et al., IL-7 and IL-15 instruct the generation of human memory stem T cells from naive precursors. Blood, 2013. 121(4).spa
dc.relation.references183. Gattinoni, L., et al., T memory stem cells in health and disease. Nature medicine, 2017. 23(1).spa
dc.relation.references184. Blackburn, S.D., et al., Coregulation of CD8+ T cell exhaustion by multiple inhibitory receptors during chronic viral infection. Nature Immunology, 2008. 10(1): p. 29-37.spa
dc.relation.references185. Zhao, Y., Q. Shao, and G. Peng, Exhaustion and senescence: two crucial dysfunctional states of T cells in the tumor microenvironment. Cellular & molecular immunology, 2020. 17(1).spa
dc.relation.references186. Fuertes Marraco, S., et al., Inhibitory Receptors Beyond T Cell Exhaustion. Frontiers in immunology, 2015. 6.spa
dc.relation.references187. Bruniquel, D., et al., Regulation of expression of the human lymphocyte activation gene-3 (LAG-3) molecule, a ligand for MHC class II. Immunogenetics, 1998. 48(2).spa
dc.relation.references188. Annunziato, F., et al., Expression and release of LAG-3-encoded protein by human CD4+ T cells are associated with IFN-gamma production. FASEB journal : official publication of the Federation of American Societies for Experimental Biology, 1996. 10(7).spa
dc.relation.references189. Kinter, A., et al., The common gamma-chain cytokines IL-2, IL-7, IL-15, and IL-21 induce the expression of programmed death-1 and its ligands. Journal of immunology (Baltimore, Md. : 1950), 2008. 181(10).spa
dc.relation.references190. Andreatta, M. and M. Nielsen, Gapped sequence alignment using artificial neural networks: application to the MHC class I system. Bioinformatics (Oxford, England), 2016. 32(4).spa
dc.relation.references191. Perez, M., et al., Structural Prediction of Peptide-MHC Binding Modes. Methods in molecular biology (Clifton, N.J.), 2022. 2405.spa
dc.relation.references192. Brennick, C., et al., An unbiased approach to defining bona fide cancer neoepitopes that elicit immune-mediated cancer rejection. The Journal of clinical investigation, 2021. 131(3).spa
dc.relation.references193. Hellman, L., et al., Improving T Cell Receptor On-Target Specificity via Structure-Guided Design. Molecular therapy : the journal of the American Society of Gene Therapy, 2019. 27(2).spa
dc.relation.references194. Wu, D., et al., Structural basis for oligoclonal T cell recognition of a shared p53 cancer neoantigen. Nature Communications, 2020. 11(1): p. 1-12.spa
dc.relation.references195. Bai, P., et al., Rational discovery of a cancer neoepitope harboring the KRAS G12D driver mutation. Science China. Life sciences, 2021. 64(12).spa
dc.relation.references196. Garboczi, D., et al., Structure of the complex between human T-cell receptor, viral peptide and HLA-A2. Nature, 1996. 384(6605).spa
dc.relation.references197. Malonis, R., J. Lai, and O. Vergnolle, Peptide-Based Vaccines: Current Progress and Future Challenges. Chemical reviews, 2020. 120(6).spa
dc.relation.references198. Duan, F., et al., Genomic and bioinformatic profiling of mutational neoepitopes reveals new rules to predict anticancer immunogenicity. The Journal of experimental medicine, 2014. 211(11).spa
dc.relation.references199. Sarkizova, S., et al., A large peptidome dataset improves HLA class I epitope prediction across most of the human population. Nature biotechnology, 2020. 38(2).spa
dc.relation.references200. Devlin, J., et al., Structural dissimilarity from self drives neoepitope escape from immune tolerance. Nature chemical biology, 2020. 16(11).spa
dc.relation.references201. Sharma, A., et al., Class I major histocompatibility complex anchor substitutions alter the conformation of T cell receptor contacts. The Journal of biological chemistry, 2001. 276(24).spa
dc.relation.references202. Borbulevych, O., et al., Structures of MART-126/27-35 Peptide/HLA-A2 complexes reveal a remarkable disconnect between antigen structural homology and T cell recognition. Journal of molecular biology, 2007. 372(5).spa
dc.relation.references203. Theodossis, A., et al., Constraints within major histocompatibility complex class I restricted peptides: presentation and consequences for T-cell recognition. Proceedings of the National Academy of Sciences of the United States of America, 2010. 107(12).spa
dc.relation.references204. Harndahl, M., et al., Peptide-MHC class I stability is a better predictor than peptide affinity of CTL immunogenicity. European journal of immunology, 2012. 42(6).spa
dc.relation.references205. van der Burg, S., et al., Immunogenicity of peptides bound to MHC class I molecules depends on the MHC-peptide complex stability. Journal of immunology (Baltimore, Md. : 1950), 1996. 156(9).spa
dc.relation.references206. Capietto, A., et al., Mutation position is an important determinant for predicting cancer neoantigens. The Journal of experimental medicine, 2020. 217(4).spa
dc.relation.references207. Feltkamp, M., et al., Efficient MHC class I-peptide binding is required but does not ensure MHC class I-restricted immunogenicity. Molecular immunology, 1994. 31(18).spa
dc.rightsDerechos reservados al autor, 2016spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseReconocimiento 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/spa
dc.subject.ddc610 - Medicina y salud::616 - Enfermedadesspa
dc.subject.decsPrevención del cáncerspa
dc.subject.decsCancer Preventioneng
dc.subject.decsSistema Inmunológicospa
dc.subject.decsImmune Systemeng
dc.subject.proposalNeoantígenosspa
dc.subject.proposalinmunogenicidadspa
dc.subject.proposaldonantes sanosspa
dc.subject.proposalLinfocitos T CD8spa
dc.subject.proposaltetrámerospa
dc.subject.proposalSistemas de cultivospa
dc.subject.proposalNeoantigenseng
dc.subject.proposalCD8 T celleng
dc.subject.proposalhealthy donoreng
dc.subject.proposalImmugenicityeng
dc.titleIdentificación y caracterización de linfocitos T neoantígeno específicos de donantes sanos con fines de inmunoterapia en cáncerspa
dc.title.translatedIdentification and characterization of antigen specific t cells from healthy donors for cancer immunotherapyeng
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TMspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audience.professionaldevelopmentEstudiantesspa
dcterms.audience.professionaldevelopmentInvestigadoresspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

Archivos

Bloque original

Mostrando 1 - 1 de 1
Cargando...
Miniatura
Nombre:
Tesis de Maestría Laura Camila Martinez Enríquez.pdf
Tamaño:
9.65 MB
Formato:
Adobe Portable Document Format
Descripción:
Tesis de Maestría en Inmunología

Bloque de licencias

Mostrando 1 - 1 de 1
No hay miniatura disponible
Nombre:
license.txt
Tamaño:
5.74 KB
Formato:
Item-specific license agreed upon to submission
Descripción: