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      Classifying cGAS-STING Activity Links Chromosomal Instability with Immunotherapy Response in Metastatic Bladder Cancer

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          Abstract

          The cGAS-STING pathway serves a critical role in anticancer therapy. Particularly, response to immunotherapy is likely driven by both active cGAS-STING signaling that attracts immune cells, and by the presence of cancer neoantigens that presents as targets for cytotoxic T cells. Chromosomal instability (CIN) is a hallmark of cancer, but also leads to an accumulation of cytosolic DNA that in turn results in increased cGAS-STING signaling. To avoid triggering the cGAS-STING pathway, it is commonly disrupted by cancer cells, either through mutations in the pathway or through transcriptional silencing. Given its effect on the immune system, determining the cGAS-STING activation status prior to treatment initiation is likely of clinical relevance. Here, we used combined expression data from 2,307 tumors from five cancer types from The Cancer Genome Atlas to define a novel cGAS-STING activity score based on eight genes with a known role in the pathway. Using unsupervised clustering, four distinct categories of cGAS-STING activation were identified. In multivariate models, the cGAS-STING active tumors show improved prognosis. Importantly, in an independent bladder cancer immunotherapy-treated cohort, patients with low cGAS-STING expression showed limited response to treatment, while patients with high expression showed improved response and prognosis, particularly among patients with high CIN and more neoantigens. In a multivariate model, a significant interaction was observed between CIN, neoantigens, and cGAS-STING activation. Together, this suggests a potential role of cGAS-STING activity as a predictive biomarker for the application of immunotherapy.

          Significance:

          The cGAS-STING pathway is induced by CIN, triggers inflammation and is often deficient in cancer. We provide a tool to evaluate cGAS-STING activity and demonstrate clinical significance in immunotherapy response.

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          Most cited references48

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          STAR: ultrafast universal RNA-seq aligner.

          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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            Near-optimal probabilistic RNA-seq quantification.

            We present kallisto, an RNA-seq quantification program that is two orders of magnitude faster than previous approaches and achieves similar accuracy. Kallisto pseudoaligns reads to a reference, producing a list of transcripts that are compatible with each read while avoiding alignment of individual bases. We use kallisto to analyze 30 million unaligned paired-end RNA-seq reads in <10 min on a standard laptop computer. This removes a major computational bottleneck in RNA-seq analysis.
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              Cancer immunotherapy using checkpoint blockade

              The release of negative regulators of immune activation (immune checkpoints) that limit antitumor responses has resulted in unprecedented rates of long-lasting tumor responses in patients with a variety of cancers. This can be achieved by antibodies blocking the cytotoxic T lymphocyte antigen-4 (CTLA-4) or the programmed death-1 (PD-1) pathway, either alone or in combination. The main premise for inducing an immune response is the pre-existence of antitumor T cells that were limited by specific immune checkpoints. Most patients who have tumor responses maintain long lasting disease control, yet one third of patients relapse. Mechanisms of acquired resistance are currently poorly understood, but evidence points to alterations that converge on the antigen presentation and interferon gamma signaling pathways. New generation combinatorial therapies may overcome resistance mechanisms to immune checkpoint therapy.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: SoftwareRole: Formal analysisRole: ValidationRole: VisualizationRole: MethodologyRole: Writing - original draftRole: Writing - review and editing
                Role: ConceptualizationRole: ValidationRole: Writing - review and editing
                Role: ConceptualizationRole: ValidationRole: Writing - original draftRole: Writing - review and editing
                Role: ConceptualizationRole: ResourcesRole: Data curationRole: ValidationRole: MethodologyRole: Writing - original draft
                Role: ResourcesRole: Data curationRole: SoftwareRole: Formal analysisRole: ValidationRole: VisualizationRole: MethodologyRole: Writing - original draft
                Role: ConceptualizationRole: ValidationRole: InvestigationRole: Methodology
                Role: ConceptualizationRole: ResourcesRole: SupervisionRole: Funding acquisitionRole: InvestigationRole: VisualizationRole: MethodologyRole: Writing - original draftRole: Project administration
                Role: ConceptualizationRole: ResourcesRole: Data curationRole: SoftwareRole: SupervisionRole: Funding acquisitionRole: InvestigationRole: VisualizationRole: Writing - original draftRole: Project administration
                Journal
                Cancer Res Commun
                Cancer Res Commun
                Cancer Research Communications
                American Association for Cancer Research
                2767-9764
                August 2022
                04 August 2022
                : 2
                : 8
                : 762-771
                Affiliations
                [1 ]Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark.
                [2 ]Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
                [3 ]Bioinformatics Research Center, Aarhus University, Aarhus, Denmark.
                [4 ]Tumour Immunogenomics and Immunosurveillance Laboratory, University College London Cancer Institute, London, United Kingdom.
                [5 ]Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, United Kingdom.
                [6 ]Department of Biomedicine, Aarhus University, Aarhus, Denmark.
                Author notes
                Corresponding Author: Nicolai J. Birkbak, Department of Clinical Medicine (or just leave as is, not critical), Aarhus University Just “Aarhus University,” Aarhus 8000, Denmark. Phone: +45 7845 5347; E-mail: nbirkbak@ 123456clin.au.dk .
                Author information
                https://orcid.org/0000-0001-9896-1544
                https://orcid.org/0000-0001-9175-0373
                https://orcid.org/0000-0002-6294-2517
                https://orcid.org/0000-0001-7061-9851
                https://orcid.org/0000-0001-8847-9201
                https://orcid.org/0000-0003-1613-9587
                Article
                CRC-22-0047
                10.1158/2767-9764.CRC-22-0047
                10010288
                36923311
                cab2b7ac-d065-4074-aa20-3ad7880ddb12
                © 2022 The Authors; Published by the American Association for Cancer Research

                This open access article is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

                History
                : 26 January 2022
                : 20 April 2022
                : 11 July 2022
                Page count
                Pages: 10
                Funding
                Funded by: http://dx.doi.org/10.13039/501100003554, Lundbeckfonden (Lundbeck Foundation);
                Award ID: R272-2017-4040
                Award Recipient :
                Funded by: http://dx.doi.org/10.13039/501100002739, Aarhus Universitets Forskningsfond (Aarhus University Research Foundation);
                Award ID: AUFF-E-2018-7-14
                Award Recipient :
                Funded by: http://dx.doi.org/10.13039/100015459, Danish Cancer Society Research Center (DCRC);
                Award ID: (R230-A13715
                Award Recipient :
                Funded by: http://dx.doi.org/10.13039/501100003554, Lundbeckfonden (Lundbeck Foundation);
                Award ID: R238-2016-2708
                Categories
                Research Article
                Biomarkers
                Prognostic Biomarkers
                Genitourinary Cancers
                Bladder Cancer
                Immunology
                Immune Responses to Cancer
                Computational Methods
                Gene Expression Profiling
                Immunotherapy
                Dna Damage And Repair
                Genomic Instability
                Custom metadata
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