5 research outputs found

    Quantifying the impact of immunotherapy on RNA dynamics in cancer

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    BACKGROUND: Checkpoint inhibitor (CPI) immunotherapies have provided durable clinical responses across a range of solid tumor types for some patients with cancer. Nonetheless, response rates to CPI vary greatly between cancer types. Resolving intratumor transcriptomic changes induced by CPI may improve our understanding of the mechanisms of sensitivity and resistance. METHODS: We assembled a cohort of longitudinal pre-therapy and on-therapy samples from 174 patients treated with CPI across six cancer types by leveraging transcriptomic sequencing data from five studies. RESULTS: Meta-analyses of published RNA markers revealed an on-therapy pattern of immune reinvigoration in patients with breast cancer, which was not discernible pre-therapy, providing biological insight into the impact of CPI on the breast cancer immune microenvironment. We identified 98 breast cancer-specific correlates of CPI response, including 13 genes which are known IO targets, such as toll-like receptors TLR1, TLR4, and TLR8, that could hold potential as combination targets for patients with breast cancer receiving CPI treatment. Furthermore, we demonstrate that a subset of response genes identified in breast cancer are already highly expressed pre-therapy in melanoma, and additionally we establish divergent RNA dynamics between breast cancer and melanoma following CPI treatment, which may suggest distinct immune microenvironments between the two cancer types. CONCLUSIONS: Overall, delineating longitudinal RNA dynamics following CPI therapy sheds light on the mechanisms underlying diverging response trajectories, and identifies putative targets for combination therapy

    A local human VĪ“1 T cell population is associated with survival in nonsmall-cell lung cancer

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    Funding Information: D.B. has consulted for NanoString, reports honoraria from AstraZeneca and has a patent (PCT/GB2020/050221) issued on methods for cancer prognostication. J.R. and M.A.B. have consulted for Achilles Therapeutics. N.M. has stock options in and has consulted for Achilles Therapeutics. N.M. holds European patents relating to targeting neoantigens (PCT/EP2016/059401), identifying patient response to immune checkpoint blockade (PCT/EP2016/071471), determining HLA loss of heterozygosity (PCT/GB2018/052004) and predicting survival rates of patients with cancer (PCT/GB2020/050221). A.H. attended one advisory board for Abbvie, Roche and GRAIL, and reports personal fees from Abbvie, Boehringer Ingelheim, Takeda, AstraZeneca, Daiichi Sankyo, Merck Serono, Merck/MSD, UCB and Roche for delivering general education/training in clinical trials. A.H. owned shares in Illumina and Thermo Fisher Scientific (sold in 2020) and receives fees for membership of Independent Data Monitoring Committees for Roche-sponsored clinical trials. S.A.Q. is co-founder and Chief Scientific Officer of Achilles Therapeutics. A.C.H. is a board member and equity holder in ImmunoQure, AG and Gamma Delta Therapeutics, and is an equity holder in Adaptate Biotherapeutics and chair of the scientific advisory board. C.S. acknowledges grant support from Pfizer, AstraZeneca, Bristol Myers Squibb, Roche-Ventana, Boehringer Ingelheim, Archer Dx Inc (collaboration in minimal residual disease-sequencing technologies) and Ono Pharmaceuticals, is an AstraZeneca Advisory Board member and Chief Investigator for the MeRmaiD1 clinical trial. C.S has consulted for Amgen, AstraZeneca, Bicycle Therapeutics, Bristol Myers Squibb, Celgene, Genentech, GlaxoSmithKline, GRAIL, Illumina, Medixci, Metabomed, MSD, Novartis, Pfizer, Roche-Ventana and Sarah Cannon Research Institute. C.S. has stock options in Apogen Biotechnologies, Epic Biosciences and GRAIL, and has stock options and is co-founder of Achilles Therapeutics. C.S. holds patents relating: to assay technology to detect tumor recurrence (PCT/GB2017/053289); to targeting neoantigens (PCT/EP2016/059401), identifying patent response to immune checkpoint blockade (PCT/EP2016/071471), determining HLA loss of heterozygosity (PCT/GB2018/052004), predicting survival rates of patients with cancer (PCT/GB2020/050221); to treating cancer by targeting Insertion/deletion (indel) mutations (PCT/GB2018/051893); to identifying indel mutation targets (PCT/GB2018/051892); to methods for lung cancer detection (PCT/US2017/028013); and to identifying responders to cancer treatment (PCT/GB2018/051912). The remaining authors declare no competing interests. Funding Information: We thank the Oxford Genomics Centre at the Wellcome Centre for Human Genetics (funded by Wellcome Trust grant no. 203141/Z/16/Z) for the generation and initial processing of the RNA-seq data from sorted TILs. We thank S. Bola for technical support and S. Vanloo for administrative support. The GTEx project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by the NCI, NHGRI, NHLBI, NIDA, NIMH and NINDS. Y.W. was supported by a Wellcome Trust Clinical Research Career Development Fellowship (no. 220589/Z/20/Z), an Academy of Medical Sciences Starter Grant for Clinical Lecturers, a National Institute for Health Research (NIHR) Academic Clinical Lectureship and the NIHR University College London Hospitals Biomedical Research Centre. D.B. was supported by funding from the NIHR University College London Hospitals Biomedical Research Centre, the ideas 2 innovation translation scheme at the Francis Crick Institute, the Breast Cancer Research Foundation (BCRF) and a Cancer Research UK (CRUK) Early Detection and Diagnosis Project award. M.J.H. is a CRUK Fellow and has received funding from CRUK, NIHR, Rosetrees Trust, UKI NETs and the NIHR University College London Hospitals Biomedical Research Centre. C.S. is Royal Society Napier Research Professor. This work was supported by the Francis Crick Institute which receives its core funding from CRUK (no. FC001169), the UK Medical Research Council (no. FC001169) and the Wellcome Trust (no. FC001169). This research was funded in whole, or in part, by the Wellcome Trust (no. FC001169). For the purpose of Open Access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. C.S. is funded by CRUK (TRACERx, PEACE and CRUK Cancer Immunotherapy Catalyst Network), CRUK Lung Cancer Centre of Excellence (no. C11496/A30025), the Rosetrees Trust, Butterfield and Stoneygate Trusts, NovoNordisk Foundation (ID16584), Royal Society Professorship Enhancement Award (no. RP/EA/180007), the NIHR Biomedical Research Centre at University College London Hospitals, the CRUKā€“University College London Centre, Experimental Cancer Medicine Centre and the BCRF. This work was supported by a Stand Up To Cancerā€LUNGevity-American Lung Association Lung Cancer Interception Dream Team Translational Research Grant (grant no. SU2C-AACR-DT23-17 to S. M. Dubinett and A. E. Spira). Stand Up To Cancer is a division of the Entertainment Industry Foundation. Research grants are administered by the American Association for Cancer Research, the Scientific Partner of SU2C. C.S. receives funding from the European Research Council (ERC) under the European Unionā€™s Seventh Framework Programme (no. FP7/2007-2013) Consolidator Grant (no. FP7-THESEUS-617844), European Commission ITN (no. FP7-PloidyNet 607722), an ERC Advanced Grant (PROTEUS) from the ERC under the European Unionā€™s Horizon 2020 research and innovation program (grant no. 835297), and Chromavision from the European Unionā€™s Horizon 2020 research and innovation program (grant no. 665233). Publisher Copyright: Ā© 2022, The Author(s).Peer reviewedPublisher PD

    Quantifying the impact of immunotherapy on RNA dynamics in cancer

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    BACKGROUND: Checkpoint inhibitor (CPI) immunotherapies have provided durable clinical responses across a range of solid tumor types for some patients with cancer. Nonetheless, response rates to CPI vary greatly between cancer types. Resolving intratumor transcriptomic changes induced by CPI may improve our understanding of the mechanisms of sensitivity and resistance. METHODS: We assembled a cohort of longitudinal pre-therapy and on-therapy samples from 174 patients treated with CPI across six cancer types by leveraging transcriptomic sequencing data from five studies. RESULTS: Meta-analyses of published RNA markers revealed an on-therapy pattern of immune reinvigoration in patients with breast cancer, which was not discernible pre-therapy, providing biological insight into the impact of CPI on the breast cancer immune microenvironment. We identified 98 breast cancer-specific correlates of CPI response, including 13 genes which are known IO targets, such as toll-like receptors TLR1, TLR4, and TLR8, that could hold potential as combination targets for patients with breast cancer receiving CPI treatment. Furthermore, we demonstrate that a subset of response genes identified in breast cancer are already highly expressed pre-therapy in melanoma, and additionally we establish divergent RNA dynamics between breast cancer and melanoma following CPI treatment, which may suggest distinct immune microenvironments between the two cancer types. CONCLUSIONS: Overall, delineating longitudinal RNA dynamics following CPI therapy sheds light on the mechanisms underlying diverging response trajectories, and identifies putative targets for combination therapy.</p

    A local human VĪ“1 T cell population is associated with survival in nonsmall-cell lung cancer.

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    Murine tissues harbor signature Ī³Ī“ T cell compartments with profound yet differential impacts on carcinogenesis. Conversely, human tissue-resident Ī³Ī“ cells are less well defined. In the present study, we show that human lung tissues harbor a resident VĪ“1 Ī³Ī“ T cell population. Moreover, we demonstrate that VĪ“1 T cells with resident memory and effector memory phenotypes were enriched in lung tumors compared with nontumor lung tissues. Intratumoral VĪ“1 T cells possessed stem-like features and were skewed toward cytolysis and helper T cell type 1 function, akin to intratumoral natural killer and CD8+ T cells considered beneficial to the patient. Indeed, ongoing remission post-surgery was significantly associated with the numbers of CD45RA-CD27- effector memory VĪ“1 T cells in tumors and, most strikingly, with the numbers of CD103+ tissue-resident VĪ“1 T cells in nonmalignant lung tissues. Our findings offer basic insights into human body surface immunology that collectively support integrating VĪ“1 T cell biology into immunotherapeutic strategies for nonsmall cell lung cancer

    Metastasis and immune evasion from extracellular cGAMP hydrolysis

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    Cytosolic DNA is characteristic of chromosomally unstable metastatic cancer cells, resulting in constitutive activation of the cGAS-STING innate immune pathway. How tumors co-opt inflammatory signaling while evading immune surveillance remains unknown. Here we show that the ectonucleotidase ENPP1 promotes metastasis by selectively degrading extracellular cGAMP, an immune stimulatory metabolite whose breakdown products include the immune suppressor, adenosine. ENPP1 loss suppresses metastasis, restores tumor immune infiltration, and potentiates response to immune checkpoint blockade in a manner dependent on tumor cGAS and host STING. Conversely, overexpression of wildtype ENPP1, but not an enzymatically weakened mutant, promotes migration and metastasis, in part, through the generation of extracellular adenosine, and renders otherwise sensitive tumors completely resistant to immunotherapy. In human cancers, ENPP1 expression correlates with reduced immune cell infiltration, increased metastasis, and resistance to anti-PD1/PD-L1 treatment. Thus, cGAMP hydrolysis by ENPP1 enables chromosomally unstable tumors to transmute cGAS activation into an immune suppressive pathway
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