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|a 616.994061
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|a Garg, Abhishek.
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| 245 |
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|a Cell-Based Cancer Immunotherapy.
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| 250 |
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|a 1st ed.
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| 264 |
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1 |
|a San Diego :
|b Elsevier Science & Technology,
|c 2024.
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| 264 |
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4 |
|c ©2024.
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| 300 |
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|a 1 online resource (420 pages)
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|a Methods in cell biology ;
|v v. 183
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|a Description based on publisher supplied metadata and other sources.
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|a Intro -- Cell-Based Cancer Immunotherapy -- Copyright -- Contents -- Contributors -- Chapter 1: Generation and quality control of mature monocyte-derived dendritic cells for immunotherapy -- Abstract -- 1. Introduction -- 2. Materials -- 2.1. Common disposables -- 2.2. Reagents -- 2.3. Equipment -- 2.4. Software -- 3. Methods -- 3.1. Isolation of CD14+ monocytes -- 3.1.1. Clinical large-scale immunomagnetic enrichment -- 3.1.2. Small-scale immunomagnetic enrichment -- 3.2. Generation of mature monocyte-derived dendritic cells -- 3.2.1. Clinical large-scale generation of mature monocyte-derived dendritic cells -- 3.2.2. Small-scale generation of mature monocyte-derived dendritic cells -- 3.3. Assessment of key characteristics of monocyte-derived dendritic cells -- 3.3.1. Immunophenotype -- 3.3.2. Antigen-uptake activity of immature dendritic cells -- 3.3.3. T-cell stimulatory activity of mature dendritic cells -- 3.3.4. Migratory response of mature dendritic cells -- 3.3.5. Indoleamine-2,3-dioxygenase expression and activity in mature dendritic cells -- 3.3.5.1. IDO activity -- 3.3.5.2. IDO expression -- 4. Notes -- 5. Concluding remarks -- Acknowledgments -- Competing interests -- References -- Chapter 2: Fully closed and automated enrichment of primary blood dendritic cells for cancer immunotherapy -- Abstract -- 1. Introduction -- 2. Materials -- 2.1. Disposables -- 2.1.1. Disposables for DC enrichment -- 2.1.2. Disposables for flow cytometry -- 2.2. Reagents -- 2.2.1. Reagents for DC enrichment -- 2.2.2. Reagents for flow cytometry -- 2.3. Donors/patients -- 2.4. Equipment -- 2.5. Software -- 3. Methods -- 3.1. CliniMACS Prodigy DC isolation -- 3.1.1. Preparation -- 3.1.2. Predepletion -- 3.1.3. Enrichment -- 3.2. Purity assessment by flow cytometry -- 3.2.1. Cell staining -- 3.2.2. Flow cytometry acquisition -- 3.2.3. Gating and data analysis.
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| 505 |
8 |
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|a 4. Notes -- 5. Concluding remarks -- Acknowledgment -- Conflict of interest -- References -- Chapter 3: Methods behind oncolytic virus-based DC vaccines in cancer: Toward a multiphase combined treatment strategy for G -- Abstract -- 1. Introduction -- 2. Methods -- 3. Glioblastoma -- 4. Anticancer immunotherapy -- 5. The immune-editing in GBM -- 6. Dendritic cell vaccines as active specific immunotherapy for GBM -- 7. The changing landscape of immunotherapy of GBM -- 8. Integration of DC vaccination within the first-line combined treatment for GBM -- 9. Challenges to design randomized clinical trials with dendritic cell vaccines as part of first-line treatment of GBM -- 10. Immunogenic cell death immunotherapy for GBM -- 10.1. Newcastle disease virus -- 10.2. Electromagnetic fields -- 10.3. ICD immunotherapy at the IOZK -- 11. Extracellular microvesicles and apoptotic bodies: A new source of tumor antigens for DC vaccines? -- 12. Individualized multimodal immunotherapy as part of first-line multiphase combined treatment for GBM -- 13. IMI integrated during and after standard of care improves OS in adults with IDH1 wild-type GBM -- 14. Individualized multimodal immunotherapy in the current health care systems -- 15. The evidence -- 16. Quality of life -- 17. Perspectives -- 17.1. Tumor-associated virus-specific T cells -- 17.2. Bone marrow-derived T cells -- 18. The model of multiphase combined treatment for patients with GBM -- Acknowledgments -- References -- Chapter 4: Identification of TCR repertoire patterns linked with anti-cancer immunotherapy -- Abstract -- 1. Introduction -- 2. Materials -- 2.1. TCR data files -- 2.2. Code repository and tutorials -- 2.2.1. ClusTCR (v1.0.2) -- 2.2.2. Scikit-Bio (v0.5.6) -- 3. Methods -- 3.1. Preprocessing of online available TCR-seq data -- 3.2. Exploration of TCR repertoire diversity.
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| 505 |
8 |
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|a 3.2.1. TCR repertoire richness -- 3.2.2. Shannon diversity -- 3.2.3. Pielou's evenness -- 3.2.4. Simpson index and Gini-Simpson index -- 3.2.5. TCRs per percentile -- 3.2.6. Gini coefficient (inequality) -- 3.2.7. Visual representation of the diversity metrics -- 3.2.8. Results and interpretation of the diversity analysis -- 3.3. Exploration of overlap between repertoires -- 3.3.1. Jaccard and Morisita distance -- 3.3.2. Public TCR sequences -- 3.3.3. Results of repertoire overlap analysis -- 3.4. Differential TCR frequency analysis -- 3.5. Clustering repertoires with ClusTCR -- Acknowledgments -- References -- Chapter 5: Training of epitope-TCR prediction models with healthy donor-derived cancer-specific T& -- spi -- Abstract -- 1. Introduction -- 2. Materials -- 2.1. Common disposables -- 2.2. Cells and reagents -- 2.3. Equipment -- 2.4. Software -- 3. Methods -- 3.1. Expansion of WT137-45-reactive T-cell clones from healthy donor buffy coats -- 3.2. In-house production of WT137-45/HLA-A2 tetramers -- 3.3. Sorting of WT137-45-specific T cells -- 3.4. RNA library preparation for next-generation sequencing -- 3.5. Sequencing of epitope-specific TCRs -- 3.6. Model training -- 4. Notes -- 5. Concluding remarks -- Acknowledgments -- Conflicts of interest -- References -- Chapter 6: Methods behind neoantigen prediction for personalized anticancer vaccines -- Abstract -- 1. Introduction -- 2. Materials -- 2.1. Input data -- 2.1.1. Samples -- 2.1.2. Genome reference files -- 2.2. Hardware -- 2.3. Software -- 3. Methods -- 3.1. Pre-processing -- 3.1.1. Quality control using FASTQC -- 3.1.2. Trimming using Trim Galore! -- 3.2. DNA analysis -- 3.2.1. Read alignment using BWA -- 3.2.2. Sort the SAM file by coordinate using GATK SortSam -- 3.2.3. BQSR with elPrep -- 3.2.4. Call Somatic SNV and INDEL variants using GATK MuTect2 -- 3.3. RNA analysis.
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| 505 |
8 |
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|a 3.3.1. Read alignment with STAR -- 3.3.2. Identify duplicates with elPrep -- 3.3.3. Split reads into exon segments with SplitNCigarReads -- 3.3.4. BQSR with elPrep -- 3.3.5. Somatic SNV and INDEL calling using Strelka2 -- 3.4. Obtaining a final variant list -- 3.4.1. Identify overlaps between DNA and RNA variants using bcftools isec -- 3.5. HLA-typing -- 3.6. Neoantigen prioritization -- 3.6.1. Expression analysis with Kallisto -- 3.6.2. p-HLA binding affinity prediction and peptide extraction with MuPeXI -- 4. Concluding remarks -- 5. Addendum -- 5.1. Workflow management systems: Snakemake -- 5.2. Example Snakefile -- References -- Chapter 7: Methods for generating the CD137L-DC-EBV-VAX anti-cancer vaccine -- Abstract -- 1. Introduction -- 2. Materials -- 2.1. Common disposables -- 2.2. Cells and reagents -- 2.3. Common equipment -- 3. Methods -- 3.1. Immobilization of anti-CD137L antibody onto cell culture dish -- 3.2. Cell processing and seeding onto anti-CD137L antibody coated dish -- 3.2.1. Processing of leukapheresis product -- 3.2.2. Peripheral blood mononuclear cell (PBMC) isolation -- 3.2.3. Red blood cell lysis and platelet removal -- 3.2.4. Seeding of cells for culture -- 3.2.5. Cryopreservation of excess PBMC -- 3.3. Removal of non-adhered cells -- 3.4. Maturation and pulsing of CD137L-DC -- 3.5. Harvesting and cryopreservation of CD137L-DC-EBV-VAX -- 4. Validation of CD137L-DC -- 4.1. Characterization of matured CD137L-DC -- 4.2. Phenotypic and functional characterization of cryopreserved CD137L-DC -- 4.3. Comparison of mo-DC and CD137L-DC-induced anti-EBV responses -- 5. Notes -- 6. Concluding remarks -- Competing interests -- References -- Chapter 8: Gold standard assessment of immunogenic cell death induced by photodynamic therapy: From in vitro to tumor mou ... -- Abstract -- 1. Introduction.
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| 505 |
8 |
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|a 2. Materials and step-by-step procedures -- 2.1. Analysis of light absorption and fluorescence of PS -- 2.2. Assessment of cellular uptake of PS and its photodynamic activity against tumor cells -- 2.2.1. Semi-quantitative analysis of cellular uptake of PS -- 2.2.2. Analysis of subcellular localization of PS in tumor cells -- 2.2.3. Estimation of dark toxicity and photodynamic efficiency of PS against tumor cells -- 2.3. Assessment of dark toxicity effects of PS on non-cancerous cells -- 2.3.1. Preparation of primary cortical cell cultures -- 2.3.2. Determination of long-term dark toxicity effects of PS on normal brain cells -- 2.3.3. Determination of the safety concentration of PS for PDT in relation to normal brain cells -- 2.4. Determination of the type of PDT-induced cancer cell death by inhibitor analysis -- 2.5. Assessment of regulated cell death in PDT-induced tumor cells -- 2.6. Determination of the profile of DAMPs released from PDT-induced tumor cells -- 2.6.1. Assessment of surface exposure of CRT -- 2.6.2. ATP release analysis -- 2.6.3. HMGB1 release analysis -- 2.7. Analysis of efferocytosis (i.e., phagocytosis) of PDT-induced tumor cells by dendritic cells -- 2.7.1. Isolation of murine BMDCs -- 2.7.2. Analysis of efferocytosis -- 2.8. Analysis of phenotypic status of dendritic cells in the presence of PDT-induced tumor cells -- 2.9. Syngeneic heterotopic prophylactic vaccination mice tumor model -- 2.9.1. Preparation of anti-cancer vaccine based on the PDT-induced tumor cells -- 2.9.2. Procedure of mouse vaccination with dead/dying tumor cells -- 2.9.3. Preparation of viable tumor cells for challenge -- 2.9.4. Mouse challenge with viable tumor cells -- 2.9.5. Tumor growth measurements -- 2.10. DCs-based mice prophylactic vaccination orthotopic tumor model.
|
| 520 |
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|a Cell-based Cancer Immunotherapy, Volume 183 provides the latest progress concerning research on anticancer cellular immunotherapies and their immunological, translation, or clinical aspects.
|
| 650 |
|
0 |
|a Antigen.
|
| 650 |
|
0 |
|a Immunotherapy.
|
| 650 |
|
0 |
|a Cellular therapy.
|
| 650 |
|
0 |
|a Tumor antigens.
|
| 650 |
|
2 |
|a Immunotherapy
|
| 650 |
|
2 |
|a Neoplasms
|x therapy
|
| 650 |
|
2 |
|a Cell- and Tissue-Based Therapy
|
| 650 |
|
2 |
|a Antigens, Neoplasm
|
| 650 |
|
6 |
|a Immunothérapie.
|
| 650 |
|
6 |
|a Thérapie cellulaire.
|
| 650 |
|
6 |
|a Antigènes tumoraux.
|
| 655 |
|
7 |
|a Electronic books.
|2 local
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| 700 |
1 |
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|a Galluzzi, Lorenzo.
|
| 710 |
2 |
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|a ScienceDirect (Online service)
|
| 776 |
0 |
8 |
|i Print version:
|a Garg, Abhishek
|t Cell-Based Cancer Immunotherapy
|d San Diego : Elsevier Science & Technology,c2024
|z 9780443139956
|
| 830 |
|
0 |
|a Methods in cell biology ;
|v v. 183.
|
| 856 |
4 |
0 |
|u http://proxy.library.tamu.edu/login?url=https://www.sciencedirect.com/science/bookseries/0091679X/183
|z Connect to the full text of this electronic book
|t 0
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| 936 |
|
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|a BATCHLOAD
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| 955 |
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|a Elsevier Methods in Cell Biology ebooks
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| 994 |
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|a Texas A&M University
|b College Station
|c Electronic Resources
|s www_evans
|d Available Online
|t 0
|e QR82.S7 .G374 2024
|h Library of Congress classification
|
| 998 |
f |
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|a QR82.S7 .G374 2024
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|l Available Online
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