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Combined targeted therapy and immunotherapy in melanoma: a review of the impact on the tumor microenvironment and outcomes of early clinical trials.

ABSTRACT: The development of BRAF and MEK inhibitors (BRAFis and MEKis) and immune checkpoint inhibitors have changed the management of advanced stage melanoma and improved the outcomes of patients with this malignancy. However, both therapeutic approaches have limitations, including a limited duration of benefit in subsets of BRAF-mutant melanoma patients treated with targeted therapy and a lower overall response rate without a clear predictive biomarker in patients treated with checkpoint inhibitors. Preclinical and translational data have shown that BRAFis and MEKis alter the tumor microenvironment to make it more amenable to immunotherapy and have provided the scientific rationale for combing BRAFis and MEKis with immunotherapy. In this review, the initial studies demonstrating the impact of BRAFis and MEKis on the expression of melanoma differentiation antigens, T-cell infiltration, and the balance of immune stimulatory and immune suppressive cells and cytokines are addressed. Preclinical work on the combination of targeted therapy with BRAFis and MEKis with immunotherapy are reviewed, highlighting improved tumor responses in mouse models of BRAF-mutated melanoma treated with combinatorial strategies. Lastly, data from early clinical trials of combined targeted therapy and immunotherapy are discussed, focusing on response rates and toxicities.

SUBMITTER: Pelster MS

PROVIDER: S-EPMC6384439 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Combined targeted therapy and immunotherapy in melanoma: a review of the impact on the tumor microenvironment and outcomes of early clinical trials.

Pelster Meredith S MS Amaria Rodabe N RN

Therapeutic advances in medical oncology 20190219

The development of BRAF and MEK inhibitors (BRAFis and MEKis) and immune checkpoint inhibitors have changed the management of advanced stage melanoma and improved the outcomes of patients with this malignancy. However, both therapeutic approaches have limitations, including a limited duration of benefit in subsets of BRAF-mutant melanoma patients treated with targeted therapy and a lower overall response rate without a clear predictive biomarker in patients treated with checkpoint inhibitors. Pr ...[more]

PMID: 30815041

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Project description:BackgroundMelanoma is the deadliest form of skin tumor, and G protein-coupled receptors (GPCRs) play crucial roles in its carcinogenesis. Furthermore, the tumor microenvironment (TME) affects the overall survival (OS) and the response to immunotherapy. The combination of GPCRs and TME from a multi-omics perspective may help to predict the survival of the melanoma patients and their response to immunotherapy.MethodsBulk-seq, single-cell RNA sequencing (scRNA-seq), gene mutations, immunotherapy responses, and clinicopathologic feature data were downloaded from public databases, and prognostic GPCRs and immune cells were screened using multiple machine learning algorithms. The expression levels of GPCRs were detected using real-time quantitative polymerase chain reaction (qPCR) in A375 and HaCaT cell lines. The GPCR-TME classifier was constructed and verified using different cohorts and multi-omics. Gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), and tracking tumor immunophenotype (TIP) were used to identify the key biological pathways among the GPCR-TME subgroups. Then, tumor mutational burden (TMB), vital mutant genes, antigen presentation genes, and immune checkpoints were compared among the subgroups. Finally, the differences in immunotherapy response rates among the GPCR-TME subgroups were investigated.ResultsA total of 12 GPCRs and five immune cell types were screened to establish the GPCR-TME classifier. No significant differences in the expression levels of the 12 GPCRs were found in the two cell lines. Patients with high GPCR score or low TME score had a poor OS; thus, the GPCRlow/TMEhigh subgroup had the most favorable OS. The scRNA-seq result revealed that immune cells had a higher GPCR score than tumor and stromal cells. The GPCR-TME classifier acted as an independent prognostic factor for melanoma. GSEA, WGCNA, and TIP demonstrated that the GPCRlow/TMEhigh subgroup was related to the activation and recruitment of anti-tumor immune cells and the positive regulation of the immune response. From a genomic perspective, the GPCRlow/TMEhigh subgroup had higher TMB, and different mutant genes. Ultimately, higher expression levels of antigen presentation genes and immune checkpoints were observed in the GPCRlow/TMEhigh subgroup, and the melanoma immunotherapy cohorts confirmed that the response rate was highest in the GPCRlow/TMEhigh cohort.ConclusionsWe have developed a GPCR-TME classifier that could predict the OS and immunotherapy response of patients with melanoma highly effectively based on multi-omics analysis.

Dataset Information

Combined targeted therapy and immunotherapy in melanoma: a review of the impact on the tumor microenvironment and outcomes of early clinical trials.

Publications

Combined targeted therapy and immunotherapy in melanoma: a review of the impact on the tumor microenvironment and outcomes of early clinical trials.

Similar Datasets

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