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Mutational and putative neoantigen load predict clinical benefit of adoptive T cell therapy in melanoma.

Martin Lauss | Marco Donia | Katja Harbst | Rikke Andersen | Shamik Mitra | Frida Rosengren | Maryem Salim | Johan Vallon-Christersson | Therese Törngren | Anders Kvist | Markus Ringnér | Inge Marie Svane | Göran Jönsson
Nature communications | 2017

Adoptive T-cell therapy (ACT) is a highly intensive immunotherapy regime that has yielded remarkable response rates and many durable responses in clinical trials in melanoma; however, 50-60% of the patients have no clinical benefit. Here, we searched for predictive biomarkers to ACT in melanoma. Whole exome- and transcriptome sequencing and neoantigen prediction were applied to pre-treatment samples from 27 patients recruited to a clinical phase I/II trial of ACT in stage IV melanoma. All patients had previously progressed on other immunotherapies. We report that clinical benefit is associated with significantly higher predicted neoantigen load. High mutation and predicted neoantigen load are significantly associated with improved progression-free and overall survival. Further, clinical benefit is associated with the expression of immune activation signatures including a high MHC-I antigen processing and presentation score. These results improve our understanding of mechanisms behind clinical benefit of ACT in melanoma.

Pubmed ID: 29170503

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GATK (tool)

RRID:SCR_001876

A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)

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Gene Set Enrichment Analysis (tool)

RRID:SCR_003199

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

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Picard (tool)

RRID:SCR_006525

Java toolset for working with next generation sequencing data in the BAM format.

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VARSCAN (tool)

RRID:SCR_006849

A platform-independent, technology-independent software tool for identifying SNPs and indels in massively parallel sequencing of individual and pooled samples. Given data for a single sample, VarScan identifies and filters germline variants based on read counts, base quality, and allele frequency. Given data for a tumor-normal pair, VarScan also determines the somatic status of each variant (Germline, Somatic, or LOH) by comparing read counts between samples. (entry from Genetic Analysis Software)

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Agilent Technologies (tool)

RRID:SCR_013575

Company provides laboratories worldwide with analytical instruments and supplies, clinical and diagnostic testing services, consumables, applications and expertise in life sciences and applied chemical markets.

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