TY - JOUR
T1 - Peripherally-driven myeloid NFkB and IFN/ISG responses predict malignancy risk, survival, and immunotherapy regime in ovarian cancer
AU - Sprooten, Jenny
AU - Vankerckhoven, Ann
AU - Vanmeerbeek, Isaure
AU - Borras, Daniel M.
AU - Berckmans, Yani
AU - Wouters, Roxanne
AU - Laureano, Raquel S.
AU - Baert, Thais
AU - Boon, Louis
AU - Landolfo, Chiara
AU - Testa, Antonia Carla
AU - Fischerova, Daniela
AU - Van Holsbeke, Caroline
AU - Bourne, Tom
AU - Chiappa, Valentina
AU - Froyman, Wouter
AU - Schols, Dominique
AU - Agostinis, Patrizia
AU - Timmerman, DIrk
AU - Tejpar, Sabine
AU - Vergote, Ignace
AU - Coosemans, An
AU - Garg, Abhishek D.
N1 - Funding Information:
Funding This study is supported by Research Foundation Flanders (FWO) (Fundamental Research Grant, G0B4620N to ADG; G0B4716N to DT; Excellence of Science/EOS grant, 30837538, for ‘DECODE’ consortium, for ADG, PA), KU Leuven (C1 grant, C14/19/098, C3 grant, C3/21/037, and POR award funds, POR/16/040 to ADG; C24/15/037 to DT), Kom op Tegen Kanker (Stand Up To Cancer, the Flemish Cancer Society) (KOTK/2018/11509/1 to ADG and PA; KOTK/2016/10728/2603 to AC, DT, and IV; KOTK/2019/11955/1 to AC, ADG, IV, and 11758 to AK), Amgen Chair for Therapeutic Advances in Ovarian Cancer (2017/LUF/00069 to IV), Vriendtjes Tegen Kanker (2016_LUF_00078 to IV) and VLIR-UOS (iBOF grant, iBOF/21/048, for ‘MIMICRY’ consortium to ADG and ST). IsVa is supported by FWO-SB PhD Fellowship (1S06821N). CL was supported by the Linbury Trust Grant LIN2600. DMB is supported by KU Leuven’s Postdoctoral mandate grant (PDMT1/21/032), and the Belgian Federation against Cancer grant numbers 2018-127 and 2016-133 and by a grant from Fondation Roi-Baudouin to ST. ST and DT are further supported by a Senior Clinical Investigator award of FWO.
Publisher Copyright:
©
PY - 2021/11/18
Y1 - 2021/11/18
N2 - Background Tumors can influence peripheral immune macroenvironment, thereby creating opportunities for non-invasive serum/plasma immunobiomarkers for immunostratification and immunotherapy designing. However, current approaches for immunobiomarkers' detection are largely quantitative, which is unreliable for assessing functional peripheral immunodynamics of patients with cancer. Hence, we aimed to design a functional biomarker modality for capturing peripheral immune signaling in patients with cancer for reliable immunostratification. Methods We used a data-driven in silico framework, integrating existing tumor/blood bulk-RNAseq or single-cell (sc)RNAseq datasets of patients with cancer, to inform the design of an innovative serum-screening modality, that is, serum-functional immunodynamic status (sFIS) assay. Next, we pursued proof-of-concept analyses via multiparametric serum profiling of patients with ovarian cancer (OV) with sFIS assay combined with Luminex (cytokines/soluble immune checkpoints), CA125-antigen detection, and whole-blood immune cell counts. Here, sFIS assay's ability to determine survival benefit or malignancy risk was validated in a discovery (n=32) and/or validation (n=699) patient cohorts. Lastly, we used an orthotopic murine metastatic OV model, with anti-OV therapy selection via in silico drug-target screening and murine serum screening via sFIS assay, to assess suitable in vivo immunotherapy options. Results In silico data-driven framework predicted that peripheral immunodynamics of patients with cancer might be best captured via analyzing myeloid nuclear factor kappa-light-chain enhancer of activated B cells (NFκB) signaling and interferon-stimulated genes' (ISG) responses. This helped in conceptualization of an 'in sitro' (in vitro+in situ) sFIS assay, where human myeloid cells were exposed to patients' serum in vitro, to assess serum-induced (si)-NFκB or interferon (IFN)/ISG responses (as active signaling reporter activity) within them, thereby 'mimicking' patients' in situ immunodynamic status. Multiparametric serum profiling of patients with OV established that sFIS assay can: decode peripheral immunology (by indicating higher enrichment of si-NFκB over si-IFN/ISG responses), estimate survival trends (si-NFκB or si-IFN/ISG responses associating with negative or positive prognosis, respectively), and coestimate malignancy risk (relative to benign/borderline ovarian lesions). Biologically, we documented dominance of pro-tumorigenic, myeloid si-NFκB response HIGH si-IFN/ISG response LOW inflammation in periphery of patients with OV. Finally, in an orthotopic murine metastatic OV model, sFIS assay predicted the higher capacity of chemo-immunotherapy (paclitaxel-carboplatin plus anti-TNF antibody combination) in achieving a pro-immunogenic peripheral milieu (si-IFN/ISG response HIGH si-NFκB response LOW), which aligned with high antitumor efficacy. Conclusions We established sFIS assay as a novel biomarker resource for serum screening in patients with OV to evaluate peripheral immunodynamics, patient survival trends and malignancy risk, and to design preclinical chemo-immunotherapy strategies.
AB - Background Tumors can influence peripheral immune macroenvironment, thereby creating opportunities for non-invasive serum/plasma immunobiomarkers for immunostratification and immunotherapy designing. However, current approaches for immunobiomarkers' detection are largely quantitative, which is unreliable for assessing functional peripheral immunodynamics of patients with cancer. Hence, we aimed to design a functional biomarker modality for capturing peripheral immune signaling in patients with cancer for reliable immunostratification. Methods We used a data-driven in silico framework, integrating existing tumor/blood bulk-RNAseq or single-cell (sc)RNAseq datasets of patients with cancer, to inform the design of an innovative serum-screening modality, that is, serum-functional immunodynamic status (sFIS) assay. Next, we pursued proof-of-concept analyses via multiparametric serum profiling of patients with ovarian cancer (OV) with sFIS assay combined with Luminex (cytokines/soluble immune checkpoints), CA125-antigen detection, and whole-blood immune cell counts. Here, sFIS assay's ability to determine survival benefit or malignancy risk was validated in a discovery (n=32) and/or validation (n=699) patient cohorts. Lastly, we used an orthotopic murine metastatic OV model, with anti-OV therapy selection via in silico drug-target screening and murine serum screening via sFIS assay, to assess suitable in vivo immunotherapy options. Results In silico data-driven framework predicted that peripheral immunodynamics of patients with cancer might be best captured via analyzing myeloid nuclear factor kappa-light-chain enhancer of activated B cells (NFκB) signaling and interferon-stimulated genes' (ISG) responses. This helped in conceptualization of an 'in sitro' (in vitro+in situ) sFIS assay, where human myeloid cells were exposed to patients' serum in vitro, to assess serum-induced (si)-NFκB or interferon (IFN)/ISG responses (as active signaling reporter activity) within them, thereby 'mimicking' patients' in situ immunodynamic status. Multiparametric serum profiling of patients with OV established that sFIS assay can: decode peripheral immunology (by indicating higher enrichment of si-NFκB over si-IFN/ISG responses), estimate survival trends (si-NFκB or si-IFN/ISG responses associating with negative or positive prognosis, respectively), and coestimate malignancy risk (relative to benign/borderline ovarian lesions). Biologically, we documented dominance of pro-tumorigenic, myeloid si-NFκB response HIGH si-IFN/ISG response LOW inflammation in periphery of patients with OV. Finally, in an orthotopic murine metastatic OV model, sFIS assay predicted the higher capacity of chemo-immunotherapy (paclitaxel-carboplatin plus anti-TNF antibody combination) in achieving a pro-immunogenic peripheral milieu (si-IFN/ISG response HIGH si-NFκB response LOW), which aligned with high antitumor efficacy. Conclusions We established sFIS assay as a novel biomarker resource for serum screening in patients with OV to evaluate peripheral immunodynamics, patient survival trends and malignancy risk, and to design preclinical chemo-immunotherapy strategies.
KW - computational biology
KW - immunological techniques
KW - immunotherapy
KW - tumor biomarkers
KW - tumor microenvironment
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U2 - 10.1136/jitc-2021-003609
DO - 10.1136/jitc-2021-003609
M3 - Article
AN - SCOPUS:85120356149
VL - 9
JO - Journal for ImmunoTherapy of Cancer
JF - Journal for ImmunoTherapy of Cancer
SN - 2051-1426
IS - 11
M1 - 003609
ER -