Progress of immune checkpoint therapy in the clinic (Review)

Fan, Yiqun; Zhang, Chi; Jin, Sheng‐Jie; Gao, Zhihui; Cao, Jun; Wang, Aoqing; Li, Dawei; Wang, Qian; Sun, Xiaohuan; Bai, Dou‐Sheng

doi:10.3892/or.2018.6819

Cited by 22 publications

(22 citation statements)

References 88 publications

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“…As of 2019, there are multiple Food and Drug Administration (FDA)approved therapeutics targeting checkpoint inhibitor associated mechanisms and others in clinical trials. 4 Despite their relative novelty, checkpoint inhibitors have quickly gained clinical popularity because they are efficacious in multiple cancer types with a favorable safety profile.…”

Section: Introductionmentioning

confidence: 99%

Comparison of commonly used solid tumor targeted gene sequencing panels for estimating tumor mutation burden shows analytical and prognostic concordance within the cancer genome atlas cohort

Bevins

Sun

Gaieb

et al. 2020

J Immunother Cancer

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BackgroundTumor mutation burden (TMB) is a biomarker frequently reported by clinical laboratories, which is derived by quantifying of the number of single nucleotide or indel variants (mutations) identified by next-generation sequencing of tumors. TMB values can inform prognosis or predict the response of a patient’s tumor to immune checkpoint inhibitor therapy. Methods for the calculation of TMB are not standardized between laboratories, with significant variables being the gene content of the panels sequenced and the inclusion or exclusion of synonymous variants in the calculations. The impact of these methodological differences has not been investigated and the concordance of reported TMB values between laboratories is unknown.MethodsSequence variant lists from more than 9000 tumors of various types were downloaded from The Cancer Genome Atlas. Variant lists were filtered to include only appropriate variant types (ie, non-synonymous only or synonymous and non-synonymous variants) within the genes found in five commonly used targeted solid tumor gene panels as well as an in-house gene panel. Calculated TMB was paired with corresponding overall survival (OS) data of each patient.ResultsRegression analysis indicates high concordance of TMB as derived from the examined panels. TMB derived from panels was consistently and significantly lower than that derived from a whole exome. TMB, as derived from whole exome or the examined panels, showed a significant correlation with OS in the examined data.ConclusionsTMB derived from the examined gene panels was analytically equivalent between panels, but not between panels and whole-exome sequencing. Correlation between TMB and OS is significant if TMB method-specific cut-offs are used. These results suggest that TMB values, as derived from the gene panels examined, are analytically and prognostically equivalent.

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Section: Introductionmentioning

confidence: 99%

Comparison of commonly used solid tumor targeted gene sequencing panels for estimating tumor mutation burden shows analytical and prognostic concordance within the cancer genome atlas cohort

Bevins

Sun

Gaieb

et al. 2020

J Immunother Cancer

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“…For example, slicing by gene family allows systematic identification of synergistic and antagonistic effects involving immune modulators of interest. Figure 3d shows a 2D projection of the landscape that contains stimulatory and inhibitory checkpoints, key regulators of the immune system with increasing therapeutic applications 9,10 . In the considered datasets, immune checkpoints show a variable propensity towards synergistic and antagonistic regulation.…”

Section: Building a Combinatorial Landscape Of Human Immunitymentioning

confidence: 99%

Deciphering the combinatorial interaction landscape

Cappuccio

Jensen

Hartmann

et al. 2019

Preprint

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From cellular activation to drug combinations, the control of biological systems involves multiple stimuli that can elicit complex nonlinear interactions. To elucidate the functions and logic of stimulus interactions, we developed SAIL (Synergistic/Antagonistic Interaction Learner). SAIL uses a machine learning classifier trained to categorize interactions across a complete taxonomy of possible combinatorial effects. The strategy resolves the most informative interactions, and helps infer their functions and regulatory mechanisms. SAIL-predicted interaction mechanisms controlling key immune functions were experimentally validated. SAIL can integrate results from multiple datasets to derive general properties of how cells respond to multiple stimuli. Using public immunological datasets, we assembled a fine-grained landscape of~30000 interactions. Analysis of the landscape shows the context-dependent functions of individual modulators, and reveals a probabilistic algebra that links the separate and combined stimulus effects. SAIL is available through a user friendly interface to resolve the effect of stimulus and drug combinations .

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“…Drugs that block immune checkpoints such as PD-1, PD-L1, and CTLA-4 have been developed in recent years [1,2]. They have a signi cant effect on highly malignant cancers and are used effectively in cancer treatment.…”

Section: Introductionmentioning

confidence: 99%

Inducing multiple antibodies to treat squamous cell esophageal carcinoma

Hoshino

Nabeya

Takiguchi

et al. 2020

Preprint

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Background The positive response and the clinical usefulness of 14 serum antibodies in patients with esophageal squamous cell carcinoma (ESCC) were examined in this study. The Cancer Genome Atlas (TCGA) was used to investigate the frequency of gene expressions, mutations, and amplification of these 14 antigens and also the possible effects of antibody induction. Methods Blood serum derived from 85 patients with ESCC was collected and analyzed for the 14 antibodies using ELISA. The prognosis between positive and negative antibodies were then compared. The antibody panel included galectin1, HCA25a, HCC-22-5, and HSP70. Results Patient serum was positive for all antibodies, except VEGF, with the positive rates ranging from 1.18% to 10.59%. Positive rates for galectin1, HCA25a, HCC-22-5, and HSP70 were >10%. TCGA data revealed that all antigen-related genes had little or no mutation or amplification, and hence an increase in gene expression affected antibody induction. The positive results from the panel accounted for the positive rate comparable to the combination of CEA and SCC. No significant association was observed between the presence of antibodies and disease prognosis. Conclusions The detection rates of galectin1, HCA25a, HCC-22-5, and HSP70 were 10% higher in patients with ESCC. Gene overexpression may be involved in such antibody production. These four antibodies were applied as a panel in comparison with conventional tumor markers. Moreover, it was confirmed that the combination of this panel and the conventional tumor markers significantly improved the positive rate.

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Progress of immune checkpoint therapy in the clinic (Review)

Cited by 22 publications

References 88 publications

Comparison of commonly used solid tumor targeted gene sequencing panels for estimating tumor mutation burden shows analytical and prognostic concordance within the cancer genome atlas cohort

Comparison of commonly used solid tumor targeted gene sequencing panels for estimating tumor mutation burden shows analytical and prognostic concordance within the cancer genome atlas cohort

Deciphering the combinatorial interaction landscape

Inducing multiple antibodies to treat squamous cell esophageal carcinoma

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