PD-1 Antibody Monotherapy for Malignant Melanoma: A Systematic Review and Meta-Analysis

Lin, Zhijuan; Chen, Xing; Li, Zhifeng; Luo, Yiming; Fang, Zhihong; Xu, Bing; Han, Mingzhe

doi:10.1371/journal.pone.0160485

Cited by 34 publications

(28 citation statements)

References 38 publications

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“…Previous meta-analyses have evaluated the efficacy of ICIs. [30][31][32][33][34][35][36][37][38] Some concluded that combination immunotherapy could result in better antitumor efficacy, but were based on only one or two studies. 31,38 One network meta-analysis compared ICIs with targeted therapies for metastatic melanoma, suggesting that a combination of BRAF and MEK inhibitors was superior to anti-CTLA-4 agents and anti-PD-1 agents.…”

Section: Agreement/disagreement With Previous Meta-analysesmentioning

confidence: 99%

The clinical value of combination of immune checkpoint inhibitors in cancer patients: A meta‐analysis of efficacy and safety

Shi

Jiang

et al. 2017

Intl Journal of Cancer

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The use of immune checkpoint inhibitors (ICIs) in combination therapy is an emerging trend in tumor immunology. However, the value of combination immunotherapy remains controversial, because of the toxic effects induced by combination. The added benefit of each additional drug has not been assessed against the added toxicity. We searched for clinical trials that evaluated ICI monotherapies and combination therapies in lung cancer and melanoma patients. The overall response rate (ORR), grade 3/4 treatment-related adverse event rate, overall survival (OS), and progression-free survival (PFS) were extracted from the most recently published studies to determine the relative risk (RR), hazard ratios (HRs), and 95% confidence intervals (CIs). Seven randomized controlled trials and one open-label study were identified (n = 3,097). Treatments included combinations of several ICIs, a combination of an ICI and dacarbazine, two combinations of an ICI, paclitaxel and carboplatin, and a combination of an ICI and gp100 vaccine. Higher ORR (RR: 1.51, 95% CI: 1.03-2.20, p = 0.034), OS (HR: 0.86, 95% CI: 0.78-0.95, p = 0.000), and PFS (HR: 0.93, 95% CI: 0.72-1.14, p = 0.000) values were observed in combination therapy than in monotherapy. In addition, the toxicity of combination ICI immunotherapy was higher (RR: 1.50, 95% CI: 1.03-2.19, p = 0.036) than that of monotherapy. This meta-analysis showed that the addition of nivolumab to ipilimumab better benefits PFS and ORR. Adding sargramostim was associated with better OS and safety. The efficacy and safety of a nivolumab-ipilimumab-sargramostim combination should be investigated further.

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Section: Agreement/disagreement With Previous Meta-analysesmentioning

confidence: 99%

The clinical value of combination of immune checkpoint inhibitors in cancer patients: A meta‐analysis of efficacy and safety

Shi

Jiang

et al. 2017

Intl Journal of Cancer

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“…The development and therapeutic potential of immune checkpoint inhibitors (ICPIs) has fundamentally changed cancer treatment paradigms across multiple tumor types. However, only a subset of patients treated with ICPIs experience durable clinical responses . Ongoing optimization of ICPI treatment requires additional predictive biomarkers that further establish which patients are most likely to benefit from such therapies.…”

Section: Introductionmentioning

confidence: 99%

Tumor Mutational Burden as a Predictive Biomarker for Response to Immune Checkpoint Inhibitors: A Review of Current Evidence

Fabrizio²,

et al. 2019

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Treatment with immune checkpoint inhibitors (ICPIs) extends survival in a proportion of patients across multiple cancers. Tumor mutational burden (TMB)—the number of somatic mutations per DNA megabase (Mb)—has emerged as a proxy for neoantigen burden that is an independent biomarker associated with ICPI outcomes. Based on findings from recent studies, TMB can be reliably estimated using validated algorithms from next‐generation sequencing assays that interrogate a sufficiently large subset of the exome as an alternative to whole‐exome sequencing. Biological processes contributing to elevated TMB can result from exposure to cigarette smoke and ultraviolet radiation, from deleterious mutations in mismatch repair leading to microsatellite instability, or from mutations in the DNA repair machinery. A variety of clinical studies have shown that patients with higher TMB experience longer survival and greater response rates following treatment with ICPIs compared with those who have lower TMB levels; this includes a prospective randomized clinical trial that found a TMB threshold of ≥10 mutations per Mb to be predictive of longer progression‐free survival in patients with non‐small cell lung cancer. Multiple trials are underway to validate the predictive values of TMB across cancer types and in patients treated with other immunotherapies. Here we review the rationale, algorithm development methodology, and existing clinical data supporting the use of TMB as a predictive biomarker for treatment with ICPIs. We discuss emerging roles for TMB and its potential future value for stratifying patients according to their likelihood of ICPI treatment response. Implications for Practice Tumor mutational burden (TMB) is a newly established independent predictor of immune checkpoint inhibitor (ICPI) treatment outcome across multiple tumor types. Certain next‐generation sequencing‐based techniques allow TMB to be reliably estimated from a subset of the exome without the use of whole‐exome sequencing, thus facilitating the adoption of TMB assessment in community oncology settings. Analyses of multiple clinical trials across several cancer types have demonstrated that TMB stratifies patients who are receiving ICPIs by response rate and survival. TMB, alongside other genomic biomarkers, may provide complementary information in selecting patients for ICPI‐based therapies.

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“…It was revealed that the normal functions of T lymphocytes were suppressed in numerous types of solid tumors, resulting in reduced antitumor immunity and evasion of host immune surveillance (16,17). As an inflammatory factor, PD-1 exhibited marked immunosuppressive effects in a number of different types of tumors (18,19). In order to determine the change in the number of PD-1 + T cells during the progression of lung cancer, the levels of PD-1 expression in infiltrating CD4…”

Section: Expression Of Pd-1 In Infiltrating Cd8mentioning

confidence: 99%

Activation of PGE2/EP2 and PGE2/EP4 signaling pathways positively regulate the level of PD‑1 in infiltrating CD8+ T cells in patients with lung cancer

et al. 2017

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Abstract. The present study aimed to identify the level of programmed death-1 (PD-1) expression in infiltrating cluster of differentiation (CD)4 + and CD8 + T cells isolated from lung cancer tissues, and investigated whether the level of PD-1 expression may be directly regulated by lung cancer cells via prostaglandin E2 (PGE2)-associated signaling pathways in patients with lung cancer. A total of 75 patients with lung cancer were enrolled in the present study. The percentage of infiltrating CD4 + and CD8 + T cells was determined by flow cytometry. ELISA was performed to evaluate the concentration of PGE2 in lung cancer tissue homogenate. The correlation between PGE2 and PD-1 expression levels in CD8 + T cells was assessed by Spearman's rank correlation test. The expression levels of PD-1 and PGE2 receptors were determined by reverse transcription-quantitative polymerase chain reaction and western blotting, respectively. The level of PD-1 expression in infiltrating CD8 + T cells was gradually increased as the stage of lung cancer increased. The level of PD-1 expression was also positively associated with the concentration of PGE2 in lung cancer tissues. Furthermore, the level of PD-1 expression was closely associated with the PGE2/EP2 and PGE2/EP4 signaling pathways. The activation of PGE2-associated EP2-and EP4-pathways may positively regulate the level of PD-1 in infiltrating CD8 + T cells, which results in immune tolerance in the lung cancer microenvironment.

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PD-1 Antibody Monotherapy for Malignant Melanoma: A Systematic Review and Meta-Analysis

Cited by 34 publications

References 38 publications

The clinical value of combination of immune checkpoint inhibitors in cancer patients: A meta‐analysis of efficacy and safety

The clinical value of combination of immune checkpoint inhibitors in cancer patients: A meta‐analysis of efficacy and safety

Tumor Mutational Burden as a Predictive Biomarker for Response to Immune Checkpoint Inhibitors: A Review of Current Evidence

Activation of PGE2/EP2 and PGE2/EP4 signaling pathways positively regulate the level of PD‑1 in infiltrating CD8+ T cells in patients with lung cancer

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