T Cell Recognition of Tumor Neoantigens and Insights Into T Cell Immunotherapy

Sim, Malcolm J. W.; Sun, Peter D.

doi:10.3389/fimmu.2022.833017

Cited by 22 publications

(26 citation statements)

References 76 publications

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“…First, we explored the percent weight of binary response and immune phenotype in high- and low-risk scores. Tumor neoantigens are antigens that are not expressed in normal tissues but only in tumor tissues, which are not only highly specific but also strongly immunogenic ( 32 , 33 ). Combining risk scores and tumor neoantigens to predict prognosis of patients with GBM and plotting the survival curve.…”

Section: Methodsmentioning

confidence: 99%

Identification and validation of an anoikis-associated gene signature to predict clinical character, stemness, IDH mutation, and immune filtration in glioblastoma

et al. 2022

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BackgroundGlioblastoma (GBM) is the most prominent and aggressive primary brain tumor in adults. Anoikis is a specific form of programmed cell death that plays a key role in tumor invasion and metastasis. The presence of anti-anoikis factors is associated with tumor aggressiveness and drug resistance.MethodsThe non-negative matrix factorization algorithm was used for effective dimension reduction for integrated datasets. Differences in the tumor microenvironment (TME), stemness indices, and clinical characteristics between the two clusters were analyzed. Difference analysis, weighted gene coexpression network analysis (WGCNA), univariate Cox regression, and least absolute shrinkage and selection operator regression were leveraged to screen prognosis-related genes and construct a risk score model. Immunohistochemistry was performed to evaluate the expression of representative genes in clinical specimens. The relationship between the risk score and the TME, stemness, clinical traits, and immunotherapy response was assessed in GBM and pancancer.ResultsTwo definite clusters were identified on the basis of anoikis-related gene expression. Patients with GBM assigned to C1 were characterized by shortened overall survival, higher suppressive immune infiltration levels, and lower stemness indices. We further constructed a risk scoring model to quantify the regulatory patterns of anoikis-related genes. The higher risk score group was characterized by a poor prognosis, the infiltration of suppressive immune cells and a differentiated phenotype, whereas the lower risk score group exhibited the opposite effects. In addition, patients in the lower risk score group exhibited a higher frequency of isocitrate dehydrogenase (IDH) mutations and a more sensitive response to immunotherapy. Drug sensitivity analysis was performed, revealing that the higher risk group may benefit more from drugs targeting the PI3K/mTOR signaling pathway.ConclusionWe revealed potential relationships between anoikis-related genes and clinical features, TME, stemness, IDH mutation, and immunotherapy and elucidated their therapeutic value.

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Section: Methodsmentioning

confidence: 99%

Identification and validation of an anoikis-associated gene signature to predict clinical character, stemness, IDH mutation, and immune filtration in glioblastoma

et al. 2022

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“…3B, C). While G12V-TCR exhibits specificity to the KRAS neoantigen, the binding affinity is weaker than that observed with therapeutic KRAS-G12D specific TCRs defined previously [2,5,7].…”

Section: Specificity and Affinity Of G12v-tcrmentioning

confidence: 68%

Identification and Structural Characterization of a mutant KRAS-G12V specific TCR restricted by HLA-A3

Sim,

Hanada,

Stotz

et al. 2024

Preprint

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SummaryMutations in KRAS are some of the most common across multiple cancer types and are thus attractive targets for therapy. Recent studies demonstrated that mutant KRAS generates immunogenic neoantigens that can be targeted in adoptive T cell therapy in metastatic diseases. To expand mutant KRAS specific immunotherapies, it is critical to identify additional HLA-I allotypes that can present KRAS neoantigens and their cognate T cell receptors (TCR). Here, we identified a murine TCR specific to a KRAS-G12V neoantigen (7VVVGAVGVGK16) using a vaccination approach with transgenic mice expressing the common HLA-I allotype, HLA-A*03:01 (HLA-A3). This TCR demonstrated exquisite specificity for mutant G12V and not Wt KRAS peptides. To investigate the molecular basis for neoantigen recognition by This TCR, we determined its structure in complex with HLA-A3(G12V). G12V-TCR CDR3β and CDR1 β formed a hydrophobic pocket to interact with p6 Val of the G12V but not Wt KRAS peptide. To improve the tumor sensitivity of This TCR, we designed rational substitutions to improve TCR:HLA-A3 contacts. Two substitutions exhibited modest improvements in TCR binding to HLA-A3 (G12V), but did not sufficiently improve T cell sensitivity for further clinical development. Our study provides mechanistic insight into how TCRs detect neoantigens and reveals the challenges in targeting KRAS-G12V mutations. [203]

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“…More sophisticated computational tools that predict KIR ligands, analogous to major histocompatibility complex (MHC) peptide binding prediction algorithms, are needed ( 42 ). This approach could also be applicable to cancer where neoantigen peptides, derived from single amino acid substitutions ( 43 ), may affect KIR binding and, in some cases, trigger activating KIRs. Furthermore, understanding how NK cells integrate KIR signals with all the other signals they receive from target cells could help interpret disease associations with KIR-HLA combinations.…”

Section: Discussionmentioning

confidence: 99%

Innate receptors with high specificity for HLA class I–peptide complexes

Sim,

Brennan,

Wahl

et al. 2023

Sci. Immunol.

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Genetic studies associate killer cell immunoglobulin-like receptors (KIRs) and their HLA class I ligands with a variety of human diseases. The basis for these associations and the relative contribution of inhibitory and activating KIR to NK cell responses are unclear. Because KIR binding to HLA-I is peptide dependent, we performed systematic screens, which totaled more than 3500 specific interactions, to determine the specificity of five KIR for peptides presented by four HLA-C ligands. Inhibitory KIR2DL1 was largely peptide sequence agnostic and could bind ~60% of hundreds of HLA-peptide complexes tested. Inhibitory KIR2DL2, KIR2DL3, and activating KIR2DS1 and KIR2DS4 bound only 10% and down to 1% of HLA-peptide complexes tested, respectively. Activating KIR2DS1, previously described as weak, had high binding affinity for HLA-C, with high peptide sequence specificity. Our data revealed MHC-restricted peptide recognition by germline-encoded NK receptors and suggest that NK cell responses can be shaped by HLA-I–bound immunopeptidomes in the context of disease or infection.

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T Cell Recognition of Tumor Neoantigens and Insights Into T Cell Immunotherapy

Cited by 22 publications

References 76 publications

Identification and validation of an anoikis-associated gene signature to predict clinical character, stemness, IDH mutation, and immune filtration in glioblastoma

Identification and validation of an anoikis-associated gene signature to predict clinical character, stemness, IDH mutation, and immune filtration in glioblastoma

Identification and Structural Characterization of a mutant KRAS-G12V specific TCR restricted by HLA-A3

Innate receptors with high specificity for HLA class I–peptide complexes

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