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A Correlation Between Differentiation Phenotypes of Infused T Cells and Anti-Cancer Immunotherapy.

ABSTRACT: T-cell therapy, usually with ex-vivo expansion, is very promising to treat cancer. Differentiation status of infused T cells is a crucial parameter for their persistence and antitumor immunity. Key phenotypic molecules are effective and efficient to analyze differentiation status. Differentiation status is crucial for T cell exhaustion, in-vivo lifespan, antitumor immunity, and even antitumor pharmacological interventions. Strategies including cytokines, Akt, Wnt and Notch signaling, epigenetics, and metabolites have been developed to produce less differentiated T cells. Clinical trials have shown better clinical outcomes from infusion of T cells with less differentiated phenotypes. CD27+, CCR7+ and CD62L+ have been the most clinically relevant phenotypic molecules, while Tscm and Tcm the most clinically relevant subtypes. Currently, CD27+, CD62L+ and CCR7+ are recommended in the differentiation phenotype to evaluate strategies of enhancing stemness. Future studies may discover highly clinically relevant differentiation phenotypes for specific T-cell production methods or specific subtypes of cancer patients, with the advantages of precision medicine.

SUBMITTER: Ren H

PROVIDER: S-EPMC8479103 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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A Correlation Between Differentiation Phenotypes of Infused T Cells and Anti-Cancer Immunotherapy.

Ren Hao H Cao Kunkun K Wang Mingjun M

Frontiers in immunology 20210915

T-cell therapy, usually with ex-vivo expansion, is very promising to treat cancer. Differentiation status of infused T cells is a crucial parameter for their persistence and antitumor immunity. Key phenotypic molecules are effective and efficient to analyze differentiation status. Differentiation status is crucial for T cell exhaustion, in-vivo lifespan, antitumor immunity, and even antitumor pharmacological interventions. Strategies including cytokines, Akt, Wnt and Notch signaling, epigenetics ...[more]

PMID: 34603332

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Project description:Overexpression of the human epidermal growth factor receptor 2 (HER2) defines a subgroup of breast tumors with aggressive behavior. The addition of HER2-targeted antibodies (i.e., trastuzumab, pertuzumab) to chemotherapy significantly improves relapse-free and overall survival in patients with early-stage and advanced disease. Nonetheless, considerable proportions of patients develop resistance to treatment, highlighting the need for additional and co-adjuvant therapeutic strategies. HER2-specific antibodies can trigger natural killer (NK) cell-mediated antibody-dependent cellular cytotoxicity and indirectly enhance the development of tumor-specific T cell immunity; both mechanisms contributing to their antitumor efficacy in preclinical models. Antibody-dependent NK cell activation results in the release of cytotoxic granules as well as the secretion of pro-inflammatory cytokines (i.e., IFNγ and TNFα) and chemokines. Hence, NK cell tumor suppressive functions include direct cytolytic killing of tumor cells as well as the regulation of subsequent antitumor adaptive immunity. Albeit tumors with gene expression signatures associated to the presence of cytotoxic lymphocyte infiltrates benefit from trastuzumab-based treatment, NK cell-related biomarkers of response/resistance to HER2-specific therapeutic antibodies in breast cancer patients remain elusive. Several variables, including (i) the configuration of the patient NK cell repertoire; (ii) tumor molecular features (i.e., estrogen receptor expression); (iii) concomitant therapeutic regimens (i.e., chemotherapeutic agents, tyrosine kinase inhibitors); and (iv) evasion mechanisms developed by progressive breast tumors, have been shown to quantitatively and qualitatively influence antibody-triggered NK cell responses. In this review, we discuss possible interventions for restoring/enhancing the therapeutic activity of HER2 therapeutic antibodies by harnessing NK cell antitumor potential through combinatorial approaches, including immune checkpoint blocking/stimulatory antibodies, cytokines and toll-like receptor agonists.

Project description:ObjectivesWe sought to evaluate the correlation between MRI phenotypes of prostate cancer as defined by PI-RADS v2 and the Decipher Genomic Classifier (used to estimate the risk of early metastases).MethodsThis single-center, retrospective study included 72 nonconsecutive men with prostate cancer who underwent MRI before radical prostatectomy performed between April 2014 and August 2017 and whose MRI registered lesions were microdissected from radical prostatectomy specimens and then profiled using Decipher (89 lesions; 23 MRI invisible [PI-RADS v2 scores ≤ 2] and 66 MRI visible [PI-RADS v2 scores ≥ 3]). Linear regression analysis was used to assess clinicopathologic and MRI predictors of Decipher results; correlation coefficients (r) were used to quantify these associations. AUC was used to determine whether PI-RADS v2 could accurately distinguish between low-risk (Decipher score < 0.45) and intermediate-/high-risk (Decipher score ≥ 0.45) lesions.ResultsMRI-visible lesions had higher Decipher scores than MRI-invisible lesions (mean difference 0.22; 95% CI 0.13, 0.32; p < 0.0001); most MRI-invisible lesions (82.6%) were low risk. PI-RADS v2 had moderate correlation with Decipher (r = 0.54) and had higher accuracy (AUC 0.863) than prostate cancer grade groups (AUC 0.780) in peripheral zone lesions (95% CI for difference 0.01, 0.15; p = 0.018).ConclusionsMRI phenotypes of prostate cancer are positively correlated with Decipher risk groups. Although PI-RADS v2 can accurately distinguish between lesions classified by Decipher as low or intermediate/high risk, some lesions classified as intermediate/high risk by Decipher are invisible on MRI.Key points• MRI phenotypes of prostate cancer as defined by PI-RADS v2 positively correlated with a genomic classifier that estimates the risk of early metastases. • Most but not all MRI-invisible lesions had a low risk for early metastases according to the genomic classifier. • MRI could be used in conjunction with genomic assays to identify lesions that may carry biological potential for early metastases.

Dataset Information

A Correlation Between Differentiation Phenotypes of Infused T Cells and Anti-Cancer Immunotherapy.

Publications

A Correlation Between Differentiation Phenotypes of Infused T Cells and Anti-Cancer Immunotherapy.

Similar Datasets

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