Association between soluble immune mediators and outcomes in patients with unresectable stage III non-small cell lung cancer treated with concurrent chemoradiotherapy followed by durvalumab

Introduction

Non-small cell lung cancer (NSCLC) accounts for 80% of all lung cancers, and approximately 30% of NSCLC patients present with stage III disease (1,2). Concurrent chemoradiotherapy (CCRT) followed by durvalumab, an anti-programmed death-ligand 1 (PD-L1) antibody, is the standard of care for these patients (3,4). However, only approximately 30% of these patients can be cured (3,4). Therefore, a biomarker to predict the prognosis of NSCLC patients receiving CCRT followed by durvalumab is urgently needed.

Immunohistochemical expression of PD-L1 in tumor tissues remains the most relevant biomarker of PD-(L)1 therapy for metastatic NSCLC (5). Similarly, PD-L1 expression before CCRT was associated with a better prognosis in a subgroup analysis of the PACIFIC trial (3). However, radiotherapy induces PD-L1 expression in tumors even if PD-L1 expression was absent before treatment (6,7). Therefore, PD-L1 expression before CCRT has not been regarded as a definitive biomarker of the response to durvalumab maintenance therapy.

Liquid biopsy has the advantage of collecting repeated samples via minimally invasive blood sampling. A recent study investigated plasma collected before CCRT for locally advanced NSCLC (8). Associations between blood-based biomarkers and immune-related adverse events have been reported in several studies, including the PACIFIC-KR study (9). However, antitumor immune activity is controlled through checkpoint pathways in immune cells [T cells, B cells, natural killer (NK) cells, macrophages] and by networks of cytokines, chemokines, and soluble receptors that shape the tumor microenvironment (10). We previously showed that soluble immune mediators could serve as indicators for monitoring clinical outcomes in metastatic NSCLC treated with programmed cell death protein 1 (PD-1) inhibitors (11).

Here, we aimed to analyze the relationships between soluble immune mediators and treatment response and to identify biomarkers predicting the treatment response in patients with unresectable stage III NSCLC. We present this article in accordance with the REMARK reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-563/rc).

Methods

Patients

We prospectively enrolled patients diagnosed with stage III NSCLC at Kurume University Hospital between October 2018 and January 2021. Patients pathologically diagnosed with locally advanced NSCLC who had received thoracic radiotherapy were eligible for inclusion. All patients had pathologically confirmed NSCLC. The PD-L1 IHC 22C3 pharmDx assay (Agilent, Santa Clara, CA, USA) was used to assess PD-L1 expression in tumor biopsy specimens. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of Kurume University Hospital (IRB No. 18168) and informed consent was taken from all the patients.

Multiplex assay

Peripheral blood samples were collected from patients at baseline and 6 weeks after durvalumab treatment (D6w). The blood samples were centrifuged at 3,000 rpm for 10 minutes, after which the plasma was collected, immediately transferred to cryovials, and frozen at −20 ℃ or below until assayed.

Plasma concentrations of soluble immune mediators—including cytokines, chemokines, and growth factors—were assessed before and after treatment using a bead-based multiplex platform. In this assay, soluble immune mediators were measured in 100-µL aliquots of twofold-diluted plasma using the Bio-Plex 200 system (Bio-Rad Laboratories, Hercules, CA, USA) in accordance with the manufacturer’s instructions. Analyte kits from Bio-Rad Laboratories were used to measure the following 83 soluble immune mediators: IL-1Rα, IL-1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-11, IL-12 (p40), IL-12 (p70), IL-13, IL-15, IL-16, IL-17A, IL-19, IL-20, IL-22, IL-26, IL-27, IL-28A, IL-29, IL-32, IL-34, IL-35, IFN-α2, IFN-β, IFN-γ, TNF-α, GM-CSF, 6Ckine, BCA1, CTACK, ENA-78, eotaxin, eotaxin-2, eotaxin-3, fractalkine, GCP-2, Gro-α, CXCL2 (Gro-β), IP-10, I-TAC, MIP-1α, MIP1δ, MIP-3α, MIP-3β, MPIF-1, SCYB16, SDF-1 α + β, TARC, TECK, I-309, MCP-1, MCP-2, MCP-3, MCP-4, MDC, MIF, MIG, VEGF, APRIL, BAFF, sCD30, sCD163, chitinase 3-like1, gp130, IL-6Rα, LIGHT, matrix metalloproteinase (MMP)-1, MMP-2, MMP-3, osteocalcin, osteopontin, pentraxin-3, sTNF-R1, sTNF-R2, TSLP, TWEAK, and VEGF.

Statistical analyses

We conducted two types of analyses to investigate the associations of soluble immune mediator levels at baseline or the differences in levels between two time points (baseline and D6w) with clinical outcomes. We evaluated the immune mediators at baseline in patients treated with thoracic radiotherapy (cohort A, n=48). Among these patients, those treated with durvalumab after CCRT (cohort B, n=29) were evaluated both at baseline and D6w (Figure 1). Progression-free survival (PFS) was defined as the interval from initiation of first-line therapy until disease progression or death from any cause. Overall survival (OS) was measured from the date of treatment initiation or initial diagnosis to the date of death or the last follow-up. The cut-off date was March 31, 2023.

Figure 1 The treatment and peripheral blood sampling schedules. Dynamics of plasma levels in stage III non-small cell lung cancer patients during radiotherapy followed by treatment with or without durvalumab.

The C-index quantifies how well predicted survival matches observed outcomes, by calculating the proportion of subject pairs ordered correctly. A value of 0.5 indicates random prediction, while 1.0 reflects perfect prediction. We included the soluble immune mediators that were significantly predictive of both PFS and OS using Cox proportional hazards models, and calculated the C-index as statistically significant at ≥0.70 (12). To evaluate the optimal cutoff value, we employed the Cutoff Finder application. The optimal cutoff was defined as the point showing the most significant separation of groups according to the log-rank test (13). Kaplan-Meier estimates were applied for survival analysis, and comparisons between groups were made with the log-rank test. Significance was defined as a two-sided P<0.05. All analyses were carried out in R.

Results

Patient characteristics and clinical outcomes

The clinical characteristics of cohorts A and B are shown in Table 1. In cohort A, the median age at diagnosis was 72 years (range, 47–86 years); 39 (81%) patients were male, and 46 (96%) patients had a good PS of 0–1. Two patients with a PS of 3 received thoracic radiotherapy alone. Adenocarcinoma was the most common histological subtype (n=23), with squamous cell carcinoma being the second most frequent (n=21). PD-L1 expression in tumor cells was observed in 17 patients, of whom 7 had very high levels. Thirty-four patients received platinum-based doublet plus radiotherapy, of whom 25 patients received durvalumab after CCRT. In 11 patients, carboplatin plus radiation was administered, and 4 of these patients received durvalumab after CCRT.

Identification of soluble immune mediators associated with PFS and OS in patients treated with radiotherapy (cohort A)

To determine which soluble immune mediators were associated with PFS and OS in patients treated with radiotherapy (cohort A), we examined the levels of 83 different soluble immune mediators at baseline. Cox regression analysis revealed 19 factors significantly correlated with PFS and OS. Table 2 shows the C-indexes of these 19 factors, which had angiogenic, monocyte-related, proinflammatory, anti-inflammatory, IFN-related, or TNF-related roles. Among these factors, MMP-2, which is involved in angiogenesis, was the only statistically significant factor related to PFS and OS (C-index: 0.70 and 0.75, respectively, Table 2). When the prognosis was analyzed by dividing the patients into two groups using a cutoff finder, the group with a higher plasma MMP-2 level had a better prognosis in terms of PFS and OS (Figure 2A).

Figure 2 Relationships between immune mediators at baseline and prognosis. Kaplan-Meier curves for PFS and OS in patients stratified by the plasma MMP-2 level (A) in cohort A and by the IFN-γ level (B) in cohort B. IFN-γ, interferon-gamma; MMP, matrix metalloproteinase; OS, overall survival; PFS, progression-free survival.

Identification of soluble immune mediators associated with PFS and OS in patients treated with CCRT followed by durvalumab (cohort B)

We also identified baseline factors associated with PFS and OS after treatment with CCRT followed by durvalumab (cohort B). Cox regression analysis revealed that 13 factors were significantly associated with PFS and OS. Table 3 shows the C-indexes of these 13 factors, which had monocyte-related, proinflammatory, anti-inflammatory, IFN-related, or TNF-related roles. Among these factors, 9 (CCL23, CCL3, IL-1b, IL-6, CXCL8, CXCL9, TNFSF13B, IL-1ra, and IL-10) were common in both cohorts A and B. When the prognosis was analyzed by dividing the patients into two groups according to the cutoff levels of each of these nine factors, the group with higher plasma levels of CCL23, CCL3, IL-1b, IL-6, CXCL8, CXCL9, TNFSF13B, IL-1ra, and IL-10 had a worse prognosis in terms of PFS and OS in both cohorts A and B (Figures S1,S2). On the other hand, MMP-2 was not significantly correlated with PFS or OS in cohort B (Table 3), whereas it was the only significant factor correlated with PFS and OS in cohort A (Table 2). Furthermore, IFN-γ was significantly correlated with both PFS and OS in cohort B (Table 3 and Figure 2B), but not in cohort A (Table 2).

We further evaluated the change in expression of the 83 different soluble immune mediators from baseline to D6w in patients treated with durvalumab maintenance therapy to clarify which soluble immune mediators were associated with PFS and OS. Cox regression analysis revealed that nine factors were significantly correlated with PFS and OS. Table 4 shows the C-indexes of these nine factors, which have monocyte-related, proinflammatory, anti-inflammatory, IFN-related, or TNF-related roles. Among these factors, CXCL9 and CXCL10, the expression of which is induced by IFN-γ, as well as CCL23 were found to be significantly correlated with both PFS (C-index: 0.79, 0.73, and 0.70, respectively; Table 4) and OS (C-index: 0.75, 0.74, and 0.73, respectively; Table 4). In addition, TNFRSF8 was significantly correlated with PFS (C-index: 0.72; Table 4), and IL-2Ra was significantly correlated with OS (C-index: 0.74; Table 4). The group with higher increases in the plasma levels of CXCL9, CXCL10, CCL23, IL-2Ra, and TNFRSF8 from baseline to D6w had a worse prognosis in terms of both PFS and OS (Figure 3).

Figure 3 Relationships of changes in immune mediators from baseline to 6 weeks after durvalumab treatment with prognosis in cohort B. Kaplan-Meier curves for PFS (A) and OS (B) in patients stratified by changes in plasma CXCL9, CXCL10, CCL23, IL-2Ra, and TNFRSF8 levels. OS, overall survival; PFS, progression-free survival.

Discussion

This study examined soluble immune mediators in relation to radiotherapy outcomes among patients with unresectable stage III NSCLC. A higher baseline plasma level of MMP-2 was significantly associated with better PFS and OS in patients treated with radiotherapy (cohort A), whereas a higher baseline plasma level of IFN-γ was significantly associated with worse PFS and OS in patients treated with radiotherapy followed by durvalumab (cohort B). On the other hand, higher baseline plasma levels of many factors, including CCL23, CCL3, IL-1b, IL-6, IL-1ra, IL-10, CXCL8, CXCL9, and TNFSF13B, were commonly associated with PFS and OS in both cohorts A and B. Furthermore, we showed that PFS and OS were significantly shorter when CXCL9, CXCL10, CCL23, IL-2Ra, and TNFRSF8 levels were elevated after CCRT followed by durvalumab. Thus, these soluble mediators may be useful tools for the clinical management of locally advanced NSCLC treated with radiotherapy with or without anti-PD-L1 therapy.

In this study, we demonstrated that several immune mediators, including angiogenic, monocyte-related, proinflammatory, anti-inflammatory, IFN-related, and TNF-related factors, were associated with the prognosis of NSCLC patients treated with radiotherapy. Under irradiation, tumor or immune cells can release several different CC chemokines (14). CCL3, also known as macrophage inflammatory protein 1-alpha, which is secreted by neutrophils, facilitates the recruitment of dendritic cells for the presentation of tumor antigens and promotes T cell activation (15). A previous study showed that neutrophils phagocytose irradiated tumor cell-derived microparticles and secrete CCL3, which induces chemotaxis and macrophage maturation of monocytes (16). In a hepatocellular carcinoma model, mice treated with CCL3 and irradiation showed enhanced antitumor effects (17). In a phase I trial, in which breast cancer patients were treated with hydrogen peroxide and radiotherapy, blood marker analysis of CCL3 showed a significant association with tumor response (18). CCL23 is involved in anti-angiogenic activities by stimulating chemotaxis of human THP-1 monocytes and enhancing the release of MMP-2 (19). Previous reports have identified various prognostic factors related to angiogenesis, the MMP family, and inflammatory cytokines in NSCLC (20-22). Among these factors, we found that a high level of MMP-2 at baseline was significantly correlated with longer PFS and OS in cohort A but not in cohort B. Overexpression of MMP-2 in resected NSCLC has been identified as a negative prognostic factor (22). Other angiogenic factors, such as VEGF and ICAM-1 were also reported to be correlated with poor prognosis (10,23). Improved tumor responses are thought to arise from intricate crosstalk between tumor cells and their surrounding microenvironment. Although many angiogenic factors and many other complex interactions can be influenced by radiosensitivity, these molecules and interactions ultimately affect tumor size, which is the primary factor influencing the tumor response to radiation (24). Although there is no clear mechanism for an improved prognosis in the presence of higher levels of angiogenic factors, it is possible that other complex interactions, such as monocyte-related, proinflammatory, anti-inflammatory, IFN-related, and TNF-related interactions, affect the prognosis of NSCLC patients receiving radiotherapy. May influence the prognosis of radiotherapy-treated NSCLC and should be studied in more cases in the future.

We found that high levels of IFN-related cytokines at baseline were significantly associated with worse PFS and OS in both cohorts A and B. Similarly, a high baseline IFN-γ level was significantly associated with worse OS and PFS in advanced urothelial carcinoma patients treated with a PD-1 antibody (25). IFN-γ plays an important role in coordinating both innate and adaptive immune responses (26). Under inflammatory conditions, IFN-γ activates immune pathways and promotes pathogen clearance (27). The regulation of this balance involves complicated mechanisms that remain incompletely understood. Intercellular communication is driven by a complex and dynamic network of cytokines, chemokines, growth factors, and inflammatory and matrix-remodeling enzymes under major perturbations in the physical and chemical properties of the tissue (28). Additionally, stage III NSCLC is a clinically, biologically, histologically, and molecularly heterogeneous disease (29). The underlying cause of this heterogeneity is unknown and may reflect alterations in cells with varying differentiation potential or may represent different molecular alterations in the same target lung epithelial cells. This heterogeneity and molecular complexity contribute to the difficulty in elucidating lung cancer pathogenesis. Additional research is necessary to elucidate the complex association between immune mediators and prognosis in stage III NSCLC.

High levels of IL-1b, IL-6, IL-1ra, IL-10, and TNFSF13B at baseline were also associated with shorter PFS and OS in both cohorts A and B. The association of higher inflammatory cytokine levels and worse outcome under PD-1 inhibitor has also been noted in metastatic NSCLC (30,31). A high IL-1b level was associated with shorter PFS and OS in NSCLC patients treated with platinum-based chemotherapy (32). IL-6 is notable for being expressed in premalignant epithelial cells and for its association with unfavorable outcomes in lung cancer (33). In contrast to IL-1, which drives tumor growth and dissemination, IL-1ra blocks IL-1α and IL-6 release, thereby limiting tumor progression (34). Previous reports suggest that IL-1ra restrains metastasis and proliferation by downregulating angiogenic factors including VEGF and IL-8 (35), and its level has been significantly associated with NSCLC prognosis and survival (36). The baseline serum IL-10 level has independent prognostic value in patients with NSCLC (37). High expression of TNFSF13 in tumor cells and fibroblasts is associated with poor prognosis in NSCLC (38). These findings suggest that IL-1b, IL-6, IL-1ra, IL-10, and TNFSF13B are prognostic factors for stage III NSCLC treated with chemoradiotherapy, independent of treatment with durvalumab.

In the durvalumab maintenance phase, we showed that increased levels of nine factors, especially CXCL9 and CXCL10, from baseline to D6w were significantly correlated with poor PFS and OS. The role of CXCL9/10 in tumor progression involves multiple mechanisms, including activation of IFN-γ-secreting CD4⁺ Th1 and cytotoxic CD8+ T cells, stimulation of growth factors by CXCR3⁺ epithelial cells, suppression of tumor growth, recruitment of CXCR3⁺ T cells and NK cells into tumors, and co-signaling with anti-PD-1 (39). In several cancer types, except lung cancer, high levels of CXCL9/10 have been reported to be associated with a better prognosis (40,41). Radiation induces neutrophil infiltration and activation (42), and tumor-associated neutrophils can actively eliminate disseminated tumor cells (43). After incubation with IFN-γ, neutrophils have been found to synergistically express and release CXCL9/10 (44). However, there are no studies on the relationship between dynamic changes in CXCL9/10 levels and prognosis. Furthermore, we demonstrated that several immune mediators with monocyte-related (CCL23), proinflammatory (IL-2Ra), and TNF-related (TNFRSF8) roles were associated with the prognosis of NSCLC patients receiving durvalumab after CCRT. TNFRSF8, a member of the TNFα receptor family, is a receptor that specifically binds to TNFα (45), which is a cytokine that plays an important role in the regulation of immune responses. IL-2 is an essential cytokine that supports T cell expansion, differentiation, and effector activity, signaling through receptor complexes composed of IL-2Rα, IL-2Rβ, and IL-2Rγ subunits. Recently, it has been reported that mice treated with PD1/IL2Ra/IL2 combination therapy achieved robust tumor growth control (46). CCL23 attracts monocytes and macrophages to regulate cancer antigen presentation (47). We recently reported that the change in the CCL23 level during immune checkpoint inhibitor monotherapy for advanced NSCLC was significantly associated with PFS (48). In addition, changes in biomarker levels were linked with PFS and remained evident throughout anti-PD-1 monotherapy in stage IV NSCLC, where patients demonstrated improved outcomes (11). The combined model of 19 cytokines, excluding MMP2, CXCL2, CXCL9 and CXCL10, was used to show associations of these cytokine levels during treatment with prognosis (49). Because the complex and dynamic network of cytokines is not fully understood, further studies are warranted to investigate this complex tumor microenvironment with regard to dynamic changes in these cytokines induced by immune checkpoint inhibitor treatment.

Our study had several limitations. First, the sample size was relatively small. We fully acknowledge that the relatively small sample size and the single-center design are limitations of our study. These factors may indeed affect the generalizability and external validity of the findings. We believe that further validation in larger, multi-center cohorts will be essential to confirm our results. Second, our study included patients with varying clinical characteristics and PD-L1 expression. With increasing attention to immune checkpoint therapies in NSCLC, larger investigations involving similar patient cohorts are required to validate the relevance of the markers identified in this study. Third, the correlational nature of our study limits the ability to establish causal relationships between specific immune mediators and survival outcomes. Finally, updated analyses of the PACIFIC trial reported that an estimated 42.9% and 33.1% of patients randomly assigned to the durvalumab treatment arm remained alive at 5 years and free of disease progression, respectively (50). However, we lack long-term follow-up data, so we cannot conclude on the relationship between the levels of soluble immune mediators and disease cure. In the future, we will continue follow-up to update PFS and OS.

Conclusions

We evaluated dynamic changes in soluble immune mediators in locally advanced NSCLC treated with CCRT followed by durvalumab. Notably, CXCL9 and CXCL10 were significantly correlated with PFS and OS during treatment. These data suggest that dynamic changes in these mediators may provide a useful tool for the clinical management of locally advanced NSCLC patients treated with CCRT followed by PD-L1 therapy.

Acknowledgments

We would like to thank the participating patients for their contributions to this study.

Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-563/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-563/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-563/prf

Funding: This work was supported by JSPS KAKENHI (grant number 19K17688).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-563/coif). K.A. reports receiving personal fees from AstraZeneca, MSD, Bristol Myers Squibb, Ono Pharmaceutical, Takeda Pharmaceutical, Taiho Pharmaceutical, AMGEN, and Chugai Pharmaceutical, and research funds from MSD, Janssen Pharmaceutical, Bristol Myers Squibb, AstraZeneca, Taiho Pharmaceutical, AMGEN, Daiichi Sankyo, IQVIA, EPS and Syneos. T.T. reports receiving personal fees from AstraZeneca, Ono Pharmaceutical, MSD, Chugai Pharmaceutical, Bristol Myers Squibb, Nippon Kayaku and Boehringer Ingelheim. T.S. reports receiving personal fees from Chugai Pharmaceutical and Bristol Myers Squibb, and research funds from Taiho and BrightPath Biotherapeutics. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of Kurume University Hospital (IRB No. 18168) and informed consent was taken from all the patients.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Blackstock AW, Govindan R. Definitive chemoradiation for the treatment of locally advanced non small-cell lung cancer. J Clin Oncol 2007;25:4146-52. [Crossref] [PubMed]
2. National Comprehensive Cancer Network. NCCN Clinical Practice Guidelines in Oncology: Non-Small Cell Lung Cancer. Fort Washington, PA: NCCN; 2014.
3. Antonia SJ, Villegas A, Daniel D, et al. Durvalumab after Chemoradiotherapy in Stage III Non-Small-Cell Lung Cancer. N Engl J Med 2017;377:1919-29. [Crossref] [PubMed]
4. Antonia SJ, Villegas A, Daniel D, et al. Overall Survival with Durvalumab after Chemoradiotherapy in Stage III NSCLC. N Engl J Med 2018;379:2342-50. [Crossref] [PubMed]
5. Reck Martin. Pembrolizumab versus Chemotherapy for PD-L1–Positive Non–Small-Cell Lung Cancer. N Engl J Med 2016;375:1823-33. [Crossref] [PubMed]
6. Deng L, Liang H, Burnette B, et al. Irradiation and anti-PD-L1 treatment synergistically promote antitumor immunity in mice. J Clin Invest 2014;124:687-95. [Crossref] [PubMed]
7. Yoneda K, Kuwata T, Kanayama M, et al. Alteration in tumoural PD-L1 expression and stromal CD8-positive tumour-infiltrating lymphocytes after concurrent chemo-radiotherapy for non-small cell lung cancer. Br J Cancer 2019;121:490-6. [Crossref] [PubMed]
8. Sui X, Jiang L, Teng H, et al. Prediction of Clinical Outcome in Locally Advanced Non-Small Cell Lung Cancer Patients Treated With Chemoradiotherapy by Plasma Markers. Front Oncol 2020;10:625911. [Crossref] [PubMed]
9. Park CK, Oh HJ, Kim YC, et al. Korean Real-World Data on Patients With Unresectable Stage III NSCLC Treated With Durvalumab After Chemoradiotherapy: PACIFIC-KR. J Thorac Oncol 2023;18:1042-54. [Crossref] [PubMed]
10. Balkwill FR, Capasso M, Hagemann T. The tumor microenvironment at a glance. J Cell Sci 2012;125:5591-6. [Crossref] [PubMed]
11. Matsuo N, Azuma K, Hattori S, et al. Association between soluble immune mediators and tumor responses in patients with nonsmall cell lung cancer treated with anti-PD-1 inhibitor. Int J Cancer 2019;144:1170-9. [Crossref] [PubMed]
12. Jin V, Wang J, Tang B. editors. Integration of Multisource Heterogeneous Omics Information in Cancer. Lausanne, Switzerland: Frontiers Media SA; 2020.
13. Budczies J, Klauschen F, Sinn BV, et al. Cutoff Finder: a comprehensive and straightforward Web application enabling rapid biomarker cutoff optimization. PLoS One 2012;7:e51862. [Crossref] [PubMed]
14. Wang L, Jiang J, Chen Y, et al. The roles of CC chemokines in response to radiation. Radiat Oncol 2022;17:63. [Crossref] [PubMed]
15. Castellino F, Huang AY, Altan-Bonnet G, et al. Chemokines enhance immunity by guiding naive CD8+ T cells to sites of CD4+ T cell-dendritic cell interaction. Nature 2006;440:890-5. [Crossref] [PubMed]
16. Zhai D, Huang J, Hu Y, et al. Ionizing Radiation-Induced Tumor Cell-Derived Microparticles Prevent Lung Metastasis by Remodeling the Pulmonary Immune Microenvironment. Int J Radiat Oncol Biol Phys 2022;114:502-15. [Crossref] [PubMed]
17. Nalla AK, Gogineni VR, Gupta R, et al. Suppression of uPA and uPAR blocks radiation-induced MCP-1 mediated recruitment of endothelial cells in meningioma. Cell Signal 2011;23:1299-310. [Crossref] [PubMed]
18. Nimalasena S, Gothard L, Anbalagan S, et al. Intratumoral Hydrogen Peroxide With Radiation Therapy in Locally Advanced Breast Cancer: Results From a Phase 1 Clinical Trial. Int J Radiat Oncol Biol Phys 2020;108:1019-29. [Crossref] [PubMed]
19. Son KN, Hwang J, Kwon BS, et al. Human CC chemokine CCL23 enhances expression of matrix metalloproteinase-2 and invasion of vascular endothelial cells. Biochem Biophys Res Commun 2006;340:498-504. [Crossref] [PubMed]
20. Singhal S, Vachani A, Antin-Ozerkis D, et al. Prognostic implications of cell cycle, apoptosis, and angiogenesis biomarkers in non-small cell lung cancer: a review. Clin Cancer Res 2005;11:3974-86. [Crossref] [PubMed]
21. Yuan A, Yang PC, Yu CJ, et al. Interleukin-8 messenger ribonucleic acid expression correlates with tumor progression, tumor angiogenesis, patient survival, and timing of relapse in non-small-cell lung cancer. Am J Respir Crit Care Med 2000;162:1957-63. [Crossref] [PubMed]
22. Passlick B, Sienel W, Seen-Hibler R, et al. Overexpression of matrix metalloproteinase 2 predicts unfavorable outcome in early-stage non-small cell lung cancer. Clin Cancer Res 2000;6:3944-8.
23. Fontanini G, Vignati S, Boldrini L, et al. Vascular endothelial growth factor is associated with neovascularization and influences progression of non-small cell lung carcinoma. Clin Cancer Res 1997;3:861-5.
24. Wachsberger P, Burd R, Dicker AP. Tumor response to ionizing radiation combined with antiangiogenesis or vascular targeting agents: exploring mechanisms of interaction. Clin Cancer Res 2003;9:1957-71.
25. Shibata Y, Kishida T, Kouro T, et al. Immune mediators as predictive biomarkers for anti-PD-1 antibody therapy in urothelial carcinoma. Front Pharmacol 2023;14:1269935. [Crossref] [PubMed]
26. Mendoza JL, Escalante NK, Jude KM, et al. Structure of the IFNγ receptor complex guides design of biased agonists. Nature 2019;567:56-60. [Crossref] [PubMed]
27. Ivashkiv LB. IFNγ: signalling, epigenetics and roles in immunity, metabolism, disease and cancer immunotherapy. Nat Rev Immunol 2018;18:545-58. [Crossref] [PubMed]
28. Hanahan D, Coussens LM. Accessories to the crime: functions of cells recruited to the tumor microenvironment. Cancer Cell 2012;21:309-22. [Crossref] [PubMed]
29. Pass HI, Carbone DP, Johnson DH. editors. Principles and Practice of Lung Cancer: The Official Reference Text of the International Association for the Study of Lung Cancer (IASLC). Lippincott Williams & Wilkins (LWW); 2010.
30. Schindler H, Lusky F, Daniello L, et al. Serum cytokines predict efficacy and toxicity, but are not useful for disease monitoring in lung cancer treated with PD-(L)1 inhibitors. Front Oncol 2022;12:1010660. [Crossref] [PubMed]
31. Kauffmann-Guerrero D, Kahnert K, Kiefl R, et al. Systemic inflammation and pro-inflammatory cytokine profile predict response to checkpoint inhibitor treatment in NSCLC: a prospective study. Sci Rep 2021;11:10919. [Crossref] [PubMed]
32. Kim JW, Koh Y, Kim DW, et al. Clinical Implications of VEGF, TGF-β1, and IL-1β in Patients with Advanced Non-small Cell Lung Cancer. Cancer Res Treat 2013;45:325-33. [Crossref] [PubMed]
33. Seike M, Yanaihara N, Bowman ED, et al. Use of a cytokine gene expression signature in lung adenocarcinoma and the surrounding tissue as a prognostic classifier. J Natl Cancer Inst 2007;99:1257-69. [Crossref] [PubMed]
34. Lewis AM, Varghese S, Xu H, et al. Interleukin-1 and cancer progression: the emerging role of interleukin-1 receptor antagonist as a novel therapeutic agent in cancer treatment. J Transl Med 2006;4:48. [Crossref] [PubMed]
35. Konishi N, Miki C, Yoshida T, et al. Interleukin-1 receptor antagonist inhibits the expression of vascular endothelial growth factor in colorectal carcinoma. Oncology 2005;68:138-45. [Crossref] [PubMed]
36. Yigit M, Değirmencioğlu S, Ugurlu E, et al. Effect of serum interleukin-1 receptor antagonist level on survival of patients with non-small cell lung cancer. Mol Clin Oncol 2017;6:708-12. [Crossref] [PubMed]
37. De Vita F, Orditura M, Galizia G, et al. Serum interleukin-10 levels as a prognostic factor in advanced non-small cell lung cancer patients. Chest 2000;117:365-73. [Crossref] [PubMed]
38. Qian Z, Qingshan C, Chun J, et al. High expression of TNFSF13 in tumor cells and fibroblasts is associated with poor prognosis in non-small cell lung cancer. Am J Clin Pathol 2014;141:226-33. [Crossref] [PubMed]
39. Barash U, Zohar Y, Wildbaum G, et al. Heparanase enhances myeloma progression via CXCL10 downregulation. Leukemia 2014;28:2178-87. [Crossref] [PubMed]
40. Jiang Z, Xu Y, Cai S. CXCL10 expression and prognostic significance in stage II and III colorectal cancer. Mol Biol Rep 2010;37:3029-36. [Crossref] [PubMed]
41. Li Y, Liang M, Lin Y, et al. Transcriptional Expressions of CXCL9/10/12/13 as Prognosis Factors in Breast Cancer. J Oncol 2020;2020:4270957. [Crossref] [PubMed]
42. Nolan E, Bridgeman VL, Ombrato L, et al. Radiation exposure elicits a neutrophil-driven response in healthy lung tissue that enhances metastatic colonization. Nat Cancer 2022;3:173-87. [Crossref] [PubMed]
43. Granot Z, Henke E, Comen EA, et al. Tumor entrained neutrophils inhibit seeding in the premetastatic lung. Cancer Cell 2011;20:300-14. [Crossref] [PubMed]
44. Siwicki M, Gort-Freitas NA, Messemaker M, et al. Resident Kupffer cells and neutrophils drive liver toxicity in cancer immunotherapy. Sci Immunol 2021;6:eabi7083. [Crossref] [PubMed]
45. Krishnamurthy PM, Shukla S, Ray P, et al. Involvement of p38-βTrCP-Tristetraprolin-TNFα axis in radiation pneumonitis. Oncotarget 2017;8:47767-79. [Crossref] [PubMed]
46. Wu J, Bloch N, Chang AY, et al. A PD-1-targeted, receptor-masked IL-2 immunocytokine that engages IL-2Rα strengthens T cell-mediated anti-tumor therapies. Cell Rep Med 2024;5:101747. [Crossref] [PubMed]
47. Nagarsheth N, Wicha MS, Zou W. Chemokines in the cancer microenvironment and their relevance in cancer immunotherapy. Nat Rev Immunol 2017;17:559-72. [Crossref] [PubMed]
48. Murata D, Azuma K, Murotani K, et al. Characterization of pre- and on-treatment soluble immune mediators and the tumor microenvironment in NSCLC patients receiving PD-1/L1 inhibitor monotherapy. Cancer Immunol Immunother 2024;73:214. [Crossref] [PubMed]
49. Wei F, Azuma K, Nakahara Y, et al. Machine learning for prediction of immunotherapeutic outcome in non-small-cell lung cancer based on circulating cytokine signatures. J Immunother Cancer 2023;11:e006788. [Crossref] [PubMed]
50. Spigel DR, Faivre-Finn C, Gray JE, et al. Five-Year Survival Outcomes From the PACIFIC Trial: Durvalumab After Chemoradiotherapy in Stage III Non-Small-Cell Lung Cancer. J Clin Oncol 2022;40:1301-11. [Crossref] [PubMed]