Empirical and Rational Design of T Cell Receptor-Based Immunotherapies

Jones, Heather F.; Molvi, Zaki; Klatt, Martin G.; Dao, Tao; Scheinberg, David A.

doi:10.3389/fimmu.2020.585385

Cited by 25 publications

(23 citation statements)

References 260 publications

(376 reference statements)

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“…Investigating the TCR-specific performance of the model revealed a likewise high predictive power, with~75% of predicted peptide targets (from the pool of three) being correct. Taken with some reservations, given the small peptide space covered, this high performance suggests that the model has the potential to resolve not only which TCRs are specific to a given peptide, but also which peptide is specific for a given TCR, pointing to important biomedical applications within T-cell therapy 26,27 .…”

Section: Discussionmentioning

confidence: 99%

NetTCR-2.0 enables accurate prediction of TCR-peptide binding by using paired TCRα and β sequence data

et al. 2021

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Prediction of T-cell receptor (TCR) interactions with MHC-peptide complexes remains highly challenging. This challenge is primarily due to three dominant factors: data accuracy, data scarceness, and problem complexity. Here, we showcase that “shallow” convolutional neural network (CNN) architectures are adequate to deal with the problem complexity imposed by the length variations of TCRs. We demonstrate that current public bulk CDR3β-pMHC binding data overall is of low quality and that the development of accurate prediction models is contingent on paired α/β TCR sequence data corresponding to at least 150 distinct pairs for each investigated pMHC. In comparison, models trained on CDR3α or CDR3β data alone demonstrated a variable and pMHC specific relative performance drop. Together these findings support that T-cell specificity is predictable given the availability of accurate and sufficient paired TCR sequence data. NetTCR-2.0 is publicly available at https://services.healthtech.dtu.dk/service.php?NetTCR-2.0.

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Section: Discussionmentioning

confidence: 99%

NetTCR-2.0 enables accurate prediction of TCR-peptide binding by using paired TCRα and β sequence data

et al. 2021

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“…This includes a range of both cellular (TCR-T) and soluble (e.g. ImmTACs and other TCR fusions) TCR therapies undergoing clinical trials (51)(52)(53). The ability of TCR research to effect change in basic immunology and in the clinic has never been greater.…”

Section: Discussionmentioning

confidence: 99%

“…to convert TCRs to soluble forms by adding appropriate constant region sequences (76). As screens for cancer or infection-recognizing clonotypes increase (77), and more engineered TCR assays and immunotherapies are developed (51,52), we believe that a tool like Stitchr stands to benefit the field by reducing the time and effort currently spent manually assembling full-length TCR expression construct sequences. Moreover, by effectively converting TCR design into a programmatic process it becomes exquisitely repeatable and reproducible, consistently producing the same output given the same input.…”

Section: Discussionmentioning

confidence: 99%

Stitchr: stitching coding TCR nucleotide sequences from V/J/CDR3 information

Heather

Spindler

Alonso

et al. 2021

Preprint

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The study and manipulation of T cell receptors (TCRs) is central to multiple fields across basic and translational immunology research. Produced by V(D)J recombination, TCRs are often only recorded in the literature and data repositories as a combination of their V and J gene symbols, plus their hypervariable CDR3 amino acid sequence. However, numerous applications require full-length coding nucleotide sequences. Here we present Stitchr, a software tool developed to specifically address this limitation. Given minimal V/J/CDR3 information, Stitchr produces complete coding sequences representing a fully spliced TCR cDNA. Due to its modular design, Stitchr can be used for TCR engineering using either published germline or novel/modified variable and constant region sequences. Sequences produced by Stitchr were validated by synthesizing and transducing TCR sequences into Jurkat cells, recapitulating the expected antigen specificity of the parental TCR. Using a companion script, Thimble, we demonstrate that Stitchr can process a million TCRs in under ten minutes using a standard desktop personal computer. By systemizing the production and modification of TCR sequences, we propose that Stitchr will increase the speed, repeatability, and reproducibility of TCR research. Stitchr is available on GitHub.

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“… 11 Other approaches are also explored with some success. 7 , 12 , 13 Third, solid tumors : although some satisfactory efficacy results were observed in some leukemic patients, especially with CD19 CAR‐T therapy for B‐cell lymphoma and BCMA CAR‐T for myeloid myeloma, comparable efficacy in solid tumors has not yet been achieved. These disappointing results can be attributed to several factors, including 6 , 7 , 8 , 9 the inability of the CAR T cell to infiltrate into solid tumors, immunosuppressive molecules, and cells in the tumor microenvironment (TME), heterogenous expression of target antigens in tumor cells, and intrinsic T cell dysfunction and exhaustion.…”

Section: Car‐t Therapy: Promise and Challengesmentioning

confidence: 99%

CAR-NK Cells from Engineered Pluripotent Stem Cells: Off-the-shelf Therapeutics for all Patients

Lu¹,

Feng²

2021

Stem Cells Translational Medicine

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Clinical success of adoptive cell therapy with chimeric antigen receptor (CAR) T cells for treating hematological malignancies has revolutionized the field of cellular immunotherapy. However, due to the nature of utilizing autologous T cells, affordability and availability are major hurdles, in addition to scientific challenges relating to CAR-T therapy optimization. Natural killer (NK) cell is a specialized immune effector cell type that recognizes and kills targets without human leukocyte antigen (HLA) restriction and prior sensitization. CAR-NK cells do not cause graft vs host disease and can be obtained from unrelated donors as well as pluripotent stem cells (PSC), representing an ideal off-the-shelf therapeutics readily available for patients. Furthermore, unlike cytotoxic T cells, NK cells specifically target and eliminate cancer stem cells, which are the cells causing relapse and metastasis. PSCs can be genetically manipulated and engineered with CARs at the pluripotent stage, which allows the establishment of permanent, stable, and clonal PSC-CAR lines for the manufacture of unlimited homogenous CAR-NK cells. Multiple master PSC-CAR cell banks targeting a variety of antigens for cancer, viral infection, and autoimmune diseases provide inexhaustible cell sources for all patients. Development of a next-generation 3D bioreactor platform for PSC expansion and NK cell production overcomes major barriers related to cost and scalability for CAR-NK product.

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Empirical and Rational Design of T Cell Receptor-Based Immunotherapies

Cited by 25 publications

References 260 publications

NetTCR-2.0 enables accurate prediction of TCR-peptide binding by using paired TCRα and β sequence data

NetTCR-2.0 enables accurate prediction of TCR-peptide binding by using paired TCRα and β sequence data

Stitchr: stitching coding TCR nucleotide sequences from V/J/CDR3 information

CAR-NK Cells from Engineered Pluripotent Stem Cells: Off-the-shelf Therapeutics for all Patients

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