TY - JOUR
T1 - Quantifying the impact of immunotherapy on RNA dynamics in cancer
AU - Usaite, Ieva
AU - Biswas, Dhruva
AU - Dijkstra, Krijn
AU - Watkins, Thomas Bk
AU - Pich, Oriol
AU - Puttick, Clare
AU - Angelova, Mihaela
AU - Thakkar, Krupa
AU - Hiley, Crispin
AU - Birkbak, Nicolai
AU - Kok, Marleen
AU - Zaccaria, Simone
AU - Wu, Yin
AU - Litchfield, Kevin
AU - Swanton, Charles
AU - Kanu, Nnennaya
N1 - Funding Information:
This work was supported by Breast Cancer Research Foundation (BCRF-22-157). CS is a Royal Society Napier Research Professor (RSRP\R\210001). This work was supported by the Francis Crick Institute that receives its core funding from Cancer Research UK (CC2041), the UK Medical Research Council (CC2041), and the Wellcome Trust (CC2041). 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. CS is funded by Cancer Research UK (TRACERx (C11496/A17786), PEACE (C416/A21999), and CRUK Cancer Immunotherapy Catalyst Network); Cancer Research UK Lung Cancer Centre of Excellence (C11496/A30025); the Rosetrees Trust, Butterfield and Stoneygate Trusts; NovoNordisk Foundation (ID16584); Royal Society Professorship Enhancement Award (RP/EA/180007); National Institute for Health Research (NIHR) University College London Hospitals Biomedical Research Centre; the Cancer Research UK-University College London Centre; Experimental Cancer Medicine Centre; the Breast Cancer Research Foundation (US); and The Mark Foundation for Cancer Research Aspire Award (Grant 21-029-ASP). This work was supported by a Stand Up To Cancer‐LUNGevity-American Lung Association Lung Cancer Interception Dream Team Translational Research Grant (Grant Number: 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. CS is in receipt of an ERC Advanced Grant (PROTEUS) from the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 835297). DB was supported by funding from a Cancer Research UK (CRUK) Early Detection and Diagnosis Project award, the Idea to Innovation (i2i) Crick translation scheme supported by the Medical Research Council, the National Institute for Health Research Biomedical Research Centre, and the Breast Cancer Research Foundation (BCRF-22-157). KD was supported by funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 101024529. YW is supported by a Wellcome Trust Clinical Research Career Development Fellowship (no. 220589/Z/20/Z). NK is supported by CRUK and the Breast Cancer Research Foundation (BCRF-22-157) and receives research support from AstraZeneca.
Publisher Copyright:
© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
PY - 2023/11/1
Y1 - 2023/11/1
N2 - 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.
AB - 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.
KW - gene expression profiling
KW - immune checkpoint inhibitors
KW - immunotherapy
KW - translational medical research
UR - http://www.scopus.com/inward/record.url?scp=85175770157&partnerID=8YFLogxK
U2 - 10.1136/jitc-2023-007870
DO - 10.1136/jitc-2023-007870
M3 - Article
C2 - 37914385
AN - SCOPUS:85175770157
SN - 2051-1426
VL - 11
JO - Journal for ImmunoTherapy of Cancer
JF - Journal for ImmunoTherapy of Cancer
IS - 11
M1 - e007870
ER -