cancer vaccines
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Cells ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 222
Author(s):  
Chunmei Fu ◽  
Li Zhou ◽  
Qing-Sheng Mi ◽  
Aimin Jiang

Despite largely disappointing clinical trials of dendritic cell (DC)-based vaccines, recent studies have shown that DC-mediated cross-priming plays a critical role in generating anti-tumor CD8 T cell immunity and regulating anti-tumor efficacy of immunotherapies. These new findings thus support further development and refinement of DC-based vaccines as mono-immunotherapy or combinational immunotherapies. One exciting development is recent clinical studies with naturally circulating DCs including plasmacytoid DCs (pDCs). pDC vaccines were particularly intriguing, as pDCs are generally presumed to play a negative role in regulating T cell responses in tumors. Similarly, DC-derived exosomes (DCexos) have been heralded as cell-free therapeutic cancer vaccines that are potentially superior to DC vaccines in overcoming tumor-mediated immunosuppression, although DCexo clinical trials have not led to expected clinical outcomes. Using a pDC-targeted vaccine model, we have recently reported that pDCs required type 1 conventional DCs (cDC1s) for optimal cross-priming by transferring antigens through pDC-derived exosomes (pDCexos), which also cross-prime CD8 T cells in a bystander cDC-dependent manner. Thus, pDCexos could combine the advantages of both cDC1s and pDCs as cancer vaccines to achieve better anti-tumor efficacy. In this review, we will focus on the pDC-based cancer vaccines and discuss potential clinical application of pDCexos in cancer immunotherapy.


2022 ◽  
Author(s):  
Sthiti Porna Dutta ◽  
Anis Alam

Abstract DBN possess the ability to induce bladder tumor as well as in the liver, and oesophagus when it is administered in the body.Exposure to DBN can happen by different modes such as by ingestion,inhalation as well through dermal contact.In the present investigation an attempt has been done to identify ,isolate as well to purify he TAA from the liver mitochondria of the mice which was exposed to DBN. It was found that mitochondrial membrane surface protein of DBN-exposed animals exhibited differential expression when compared with the control animals. A low molecular weight (~14 kDa) protein was found to be over expressed on liver mitochondrial membrane upon DBN exposure in mice as compared with the normal control and identified as TAA, showing the sign that some of the proteins could be used as TAA for further study.These identification and molecular characterization of TAAs will provide the basis for the development of cancer vaccines targeting TAAs.


2022 ◽  
pp. 359-408
Author(s):  
Elizabeth G. Graham-Gurysh ◽  
Brandon W. Carpenter ◽  
Wolfgang A. Beck ◽  
Devika M. Varma ◽  
Benjamin G. Vincent ◽  
...  

2021 ◽  
Author(s):  
Xian Xian Liu ◽  
Gloria Li ◽  
Wei Lou ◽  
Juntao Gao ◽  
Simon Fong

[Background]: An emerging type of cancer treatment, known as cell immunotherapy, is gaining popularity over chemotherapy or other radia-tion therapy that causes mass destruction to our body. One favourable ap-proach in cell immunotherapy is the use of neoantigens as targets that help our body immune system identify the cancer cells from healthy cells. Neoan-tigens, which are non-autologous proteins with individual specificity, are generated by non-synonymous mutations in the tumor cell genome. Owing to its strong immunogenicity and lack of expression in normal tissues, it is now an important target for tumor immunotherapy. Neoantigens are some form of special protein fragments excreted as a by-product on the surface of cancer cells during the DNA mutation at the tumour. In cancer immunotherapies, certain neoantigens which exist only on cancer cells elicit our white blood cells (body's defender, anti-cancer T-cell) responses that fight the cancer cells while leaving healthy cells alone. Personalized cancer vaccines there-fore can be designed de novo for each individual patient, when the specific neoantigens are found to be relevant to his/her tumour. The vaccine which is usually coded in synthetic long peptides, RNA or DNA representing the neo-antigens trigger an immune response in the body to destroy the cancer cells (tumour). The specific neoantigens can be found by a complex process of biopsy and genome sequencing. Alternatively, modern technologies nowa-days tap on AI to predict the right neoantigen candidates using algorithms. However, determining the binding and non-binding of neoantigens on T-cell receptors (TCR) is a challenging computational task due to its very large search space. [Objective]: To enhance the efficiency and accuracy of traditional deep learning tools, for serving the same purpose of finding potential responsive-ness to immunotherapy through correctly predicted neoantigens. It is known that deep learning is possible to explore which novel neoantigens bind to T-cell receptors and which ones don't. The exploration may be technically ex-pensive and time-consuming since deep learning is an inherently computa-tional method. one can use putative neoantigen peptide sequences to guide personalized cancer vaccines design. [Methods]: These models all proceed through complex feature engineering, including feature extraction, dimension reduction and so on. In this study, we derived 4 features to facilitate prediction and classification of 4 HLA-peptide binding namely AAC and DC from the global sequence, and the LAAC and LDC from the local sequence information. Based on the patterns of sequence formation, a nested structure of bidirectional long-short term memory neural network called local information module is used to extract context-based features around every residue. Another bilstm network layer called global information module is introduced above local information module layer to integrate context-based features of all residues in the same HLA-peptide binding chain, thereby involving inter-residue relationships in the training process. introduced. [Results]: Finally, a more effective model is obtained by fusing the above two modules and 4 features matric, the method performs significantly better than previous prediction schemes, whose overall r-square increased to 0.0125 and 0.1064 on train and increased to 0.0782 and 0.2926 on test da-tasets. The RMSE for our proposed models trained decreased to approxi-mately 0.0745 and 1.1034, respectively, and decreased to 0.6712 and 1.6506 on test dataset. [Conclusion]: Our work has been actively refining a machine-learning model to improve neoantigen identification and predictions with the determinants for Neoantigen identification. The final experimental results show that our method is more effective than existing methods for predicting peptide types, which can help laboratory researchers to identify the type of novel HLA-peptide binding. Keywords: machine learning; Cancer Cell Immunology; HLA-peptide binding Neoantigen Prediction; HLA; Data Visualization; Novel Neoanti-gen and TCR Pairing Discovery; Vector representation


2021 ◽  
Vol 10 (17) ◽  
pp. e132101723015
Author(s):  
Tatiane Batista dos Santos ◽  
Denilson dos Santos Gomes ◽  
Alícia Beatriz Fontes de Sousa ◽  
Ítalo Samuel Gonçalves Rodrigues ◽  
Francine Ferreira Padilha ◽  
...  
Keyword(s):  

Osteossarcoma (OS) é um tumor ósseo maligno, cujo sua terapêutica é realizada através da remoção cirúrgica associado a quimioterapia combinada, a qual incluem a utilização de medicamentos. Com intuito de verificar a importância da imunoterapia no cunho científico, foram realizadas pesquisas a fim de se confirmar a relevância que o estudo apresenta como inovação tecnológica. Para isso as bibliotecas de artigos do PubMed e Science Direct foram acessadas para a realização de uma prospecção científica, um quantitativo de 278 e 40 com as associações dos descritores “Bone Neoplasms AND cancer vaccines” e “Osteosarcoma AND cancer vaccines" foram obtidos, respectivamente. Em relação a prospecção tecnológica utilizou-se os mesmos descritores e as buscas foram realizadas no Google Patents selecionando os escritórios WO e BR quando necessário, com o uso dos descritores “bone neoplasms”, “osteosarcoma” e “cancer vaccines”, apresentando um total de 62.610, 20410 e 34337 patentes, respectivamente para o escritório WO. Já no escritório BR foram encontrados 687, 613 e 585 respectivamente. Dentre esses achados foi possível perceber que a busca por imunoterapias para OS é crescente, no entanto, o uso de vacinas para OS foi mais presente na prospecção científica do que na tecnológica, isso pode ser atribuído a tecnologia das vacinas terapêuticas serem recentes. A partir desses resultados pode-se concluir que o estudo forneceu dados de prospecção científico-tecnológico, que pode auxiliar no direcionamento de pesquisas, ressaltando a relevância da análise prospectiva tecnológica, como oportunidade de investir na propriedade intelectual como solução das necessidades sociais e econômicas.


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