Peripherally-driven myeloid NFkB and IFN/ISG responses predict malignancy risk, survival, and immunotherapy regime in ovarian cancer

Abstract

BackgroundTumors 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.MethodsWe 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.ResultsIn 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 responseHIGHsi-IFN/ISG responseLOW 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 responseHIGHsi-NFκB responseLOW), which aligned with high antitumor efficacy.ConclusionsWe 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.

Developing an Immune-Related Signature for Predicting Survival Rate and the Response to Immune Checkpoint Inhibitors in Patients With Glioma

“…Due to the high level of malignancy and poor prognosis of glioma (Xun et al, 2021), the development of accurate methods is required to predict the associated prognosis and to create effective therapy for patients with glioma. At present, immunotherapy demonstrates high levels of effectiveness in the treatment of malignant tumors (Chen et al, 2021b;Sprooten et al, 2021). Results of previous studies have demonstrated that TIME exhibits a high association with the occurrence and development of several tumor types, and this may act as an important prognostic indicator (Berraondo et al, 2016;Elola et al, 2018).…”

Identification of Potential Prognostic and Predictive Immunological Biomarkers in Patients with Stage I and Stage III Non-Small Cell Lung Cancer (NSCLC): A Prospective Exploratory Study

“…Both type I and type II IFNs can elicit the transcription of ISGs, which include the IFN-inducible CXCL9/CXCL10/CXCL11 chemokines. In the current study, we investigated whether the “sum total” of circulating proteins can result in the activation of IFN/ISG response within myeloid cells via newly established sFIS assay [ 36 ]. In patients with stage I NSCLC treated with SBRT, increased IFN/ISG response activity was associated with a better PFS.…”

“…This sFIS assay [ 36 ] consisted of THP1-Dual™ myeloid reporter cells (InvivoGen, Toulouse, France) seeded in a 96-well plate at a density of 30,000 cells per well in 100 µL media (RPMI-1640 containing 2 mM L-glutamine, 25 mM HEPES, 100 units/mL penicillin, 100 µg/L streptomycin, 100 µg/mL Normocin and 10% heat inactivated fetal calf serum). After 24 h, THP1 cells were treated with 100 µL of patient plasma for 24 h. To determine activation of interferon-stimulated response elements (ISRE) coding for interferon (IFN)-stimulated genes (ISG), luciferase was checked in media by adding 50 µL of Quanti-Luc GOLD (InvivoGen) to 100 µL of (separately recovered) THP1 media.…”

Peripheral gene signatures reveal distinct cancer patient immunotypes with therapeutic implications for autologous DC-based vaccines

“…Although tumor sampling is widely implemented for biomarker identification and analysis, there are several challenges including limited accessibility, heterogeneity of the biopsy site, and the patient’s condition. 11 Therefore, identification of potential predictive biomarkers using more accessible peripheral blood is critical for the development and clinical utility of biomarkers. 12 , 13 Recent technological, analytical, and mechanistic advances in immunology have enabled the identification of several circulating cancer biomarkers including, but not limited to: circulating tumor cells in breast and prostate cancer, tumor genomic alterations such as discrete oncogenic variants (e.g.…”