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| | + | <h3>CAPOEIRA</h3> |
| | + | <h3>Cancer Personalized Encapsulin Immunotherapy and Relapse Assay</h3> |
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| − | <h1> Welcome to the team EPFL wiki for our 2018 iGEM project </h1>
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| − | <h1> Despcription of our project </h1>
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| − | <h1>Introduction</h1>
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| − | <p>While cancer is still the disease of the 21st century, new insights and approaches are changing the landscape of cancer therapy. Cancer immunotherapy is becoming a key technique for the successful fight against cancer. The goal of cancer immunotherapy
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| − | is to harness the immune system in the fight against cancer. The project that the EPFL 2018 iGEM team is presenting is focused on the development of a new therapeutic approach to target specific types of cancer using immunotherapy methods, with a
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| − | focus on vaccines. Furthermore, the project aims to integrate the personalised medicine approaches, by using patient-specific neoantigens to trigger the immune system and produce the response against the cancer. The project is exhaustive and can be
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| − | divided into the following parts:</p>
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| − | <h3> 1. Detection of patient/cancer specific neoantigens </h3>
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| − | <p>Vaccines should expand the pool of available tumor-specific T cells, and they could thus provide important partners for combination immunotherapy. However, the expected potential of cancer vaccines has not been realized in the clinical setting. In part,
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| − | this could be related to the choice of antigens: Most molecularly defined tumor vaccines, to date, have used a single “self” antigen. The use of multiple tumor-restricted antigens, such as neoepitopes resulting from tumor mutations, represents a promising
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| − | approach to tumor vaccination.</p>
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| − | <p>Detecting mutations in tumor cells requires expensive and labor-intensive methods like Next Generation Sequencing (NGS) on both tumor samples and normal cells followed by necessary bioinformatic pipelines to be able to detect those mutations that might
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| − | results in neoepitopes with high MHC-I or II binding. On the other hand, our solution seeks to bypass those steps and detect mutations in a faster, easier, and cheaper way, whenever it is possible. For doing so, we first choose one specific type of
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| − | cancer and use the results of bioinformatic tools on huge pool of cancer sequencing data for that type of cancer. Then we extract regions of interest on genes for once, and after that by using SHERLOCK technique, we try to detect mutations at attomolar
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| − | sensitivity on any new patients’ samples with the same type of cancer. This way we can reduce the cost, the time, and the tools that are necessary for detecting mutations, in many cases..</p>
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| − | <h3> 2. Production of neoantigen delivery system </h3>
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| − | <p> Although detecting the different patient-specific neoantigens is key to develop a therapeutic vaccine, epitope recognition for differential targeting of cancer cells by the immune system is a major challenge. In order for an efficient immune response
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| − | to be triggered against cancer cells, killer CD8+ T cells should be activated to recognize certain epitopes as dangerous. This usually occurs through antigen presentation by dendritic cells. Thus, dendritic cells should be guided towards labeling
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| − | cancer related epitopes as foreign or harmful. This can be achieved through the presentation of the antigen of interest to dendritic cells on a vaccine-like platform, where the antigen is associated with an adjuvant that labels the antigen as foreign
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| − | or harmful. Current strategies, have developed different nanoscale delivery platforms to encapsulate and transport these neoantigens for efficient targeting of peripheral or central dendritic cells. The goal for this specific part of the project is
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| − | to further develop these techniques, by synthesising a protein cage nanoparticle termed “Encapsulin” capable of targeting dendritic cells for efficient delivery of an antigen and its recognition as a foreign antigens. Such protein cage nanoparticle
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| − | can be expressed in a cell free system together with the neoantigens and targeting sequences simultaneously. </p>
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| − | <h3>3. Expression of the antigens in dendritic cells, maturation and co culture with T-cells. </h3>
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| − | <p>To ensure that the vaccine works as expected it is necessary to assess the immune response that it can stimulate. The vaccine should first, reach the dendritic cells, trigger the recruitment of the dendritic cell population, and instigate its proper
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| − | uptake. Then the delivery system should ensure the correct maturation of the dendritic cells, for subsequent presentation of the antigen on the MHC I complex. Finally, the dendritic cells should be able to activate the T cells. In order to validate
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| − | the immune activation scheme, we aim to culture dendritic cells in-vitro and present them with the intended antigen using the encapsulin-based vaccine, for characterization of dendritic cell response. Furthermore, co-culture of dendritic cells and
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| − | T cells can explore the full potential of our approach to target the tumor, through exploring T-cell response. </p>
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| − | <h3> 4. Detection of Relapse </h3>
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| − | <p>Tumor cells release fragments of their DNA in the blood as circulating tumour DNA (ctDNA) when they undergo certain processes, for example during the death of tumour cells. These ctDNA fragments carry specific information of the tumour cell which makes
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| − | them a highly valuable biomarker that can enable us to track the response of the cancer to therapies, as well as aiding the prediction of cancer metastasis and recurrence. Another advantage that ctDNA as a biomarker holds is that it is minimally invasive
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| − | and will allow monitoring of the tumour after treatment (for example after surgery or vaccine therapy) without the need of invasive biopsies. </p>
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| − | <p> We aim to investigate the use of ctDNA as a biomarker for gene specific and personalized mutations as well as personalized chromosomal rearrangements that are detected by applying bioinformatic pipelines that we will test using digital PCR (dPCR) and
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| − | deep-sequencing based methods, such as droplet dPCR and Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq). We also will investigate the possibility of coupling the use of ctDNA as a biomarker with other potential biomarkers such as microRNA.</p>
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