The impact of aspirin on PD-L1 expression and alteration of M2 polarization in non-small cell lung cancer

The impact of aspirin on PD-L1 expression and alteration of M2 polarization in non-small cell lung cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The impact of aspirin on PD-L1 expression and alteration of M2 polarization in non-small cell lung cancer Nese Unver, Sila Uluturk, Ece Tavukcuoglu, Elif Duymaz Yilmaz, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6954264/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Sep, 2025 Read the published version in Inflammation Research → Version 1 posted 7 You are reading this latest preprint version Abstract Although aspirin is one of the best characterized drugs for the therapeutic effects on coagulation and inflammation, there are clues that it may also have a significant impact on cancer immunity. In this study, IFNg, a pro-inflammatory cytokine, has been demonstrated to increase the protein expression of PD-L1 in non-small cell lung carcinoma cells. In the molecular modeling of stimulated and/or aspirin-treated cancer secretome and macrophage interaction, CD38 (M1 macrophage marker) and CD209 (M2 macrophage marker) expressions confirmed that peripheral blood mononuclear cells differentiated into M1 or M2 macrophages afterwards polarization. Transcriptomic profiling was performed after 48 hours of culture with differentiated M2-polarized macrophages in the presence of lung cancer cell secretomes. In contrast to the EGFR mutant aspirin-treated HCC827 cell line, the findings revealed that factors produced by the non-EGFR mutant aspirin-treated IFNg-induced H838 cancer cell secretome can alter M2 macrophage dynamics. Furthermore, significant patterns were obtained in gene expression profiles related to “Hematopoietic Cell Lineage” and “Antigen Processing and Presentation” between groups in M2-polarized macrophages established with these secretomes. However, aspirin treatment had different effects on cancer cell lines that expressed endogenous and induced PD-L1. As a result, flow cytometry analysis demonstrated that administering aspirin to HCC827 cancer cells boosted the expression of PD-L1 on their surface. Analysis of EGFR mutations, aspirin resistance, and PD-L1 levels, as well as M2 macrophage infiltration in the non-small cell lung cancer microenvironment and immune phenotyping of M2 macrophage subtypes, will assist in developing lung cancer therapy approaches that combine EGFR inhibitors and aspirin. PD-L1 aspirin non-small cell lung cancer macrophage secretome Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Mutational load, lymphocyte count, immune cell infiltration (intratumoral T cells), PD-L1 expression, the abundance of inhibitory mediators, tumor response to immune effector cells, MHC expression, and sensitivity to IFNgamma (IFNg) are essential components in immune evasion of cancer cells [ 1 – 3 ]. Despite widespread utilization and rapid FDA approval of immune checkpoint inhibitor (ICI) drugs, more studies on predictive biomarkers, resistance mechanisms, treatment duration, immune-related toxicities, and the PD-L1 expression threshold remains required for a complete understanding of their anti-cancer potential [ 4 ]. The use of soluble PD-1 (sPD-1) and soluble PD-L1 (sPD-L1) as prognostic indicators or biomarkers of immunotherapy response is being assessed in molecular lung cancer research [ 5 ]. Chemopreventive agents, including aspirin and other COX-2 inhibitors, aromatase inhibitors, and bisphosphonates, hamper the formation of premalignant lesions and may ameliorate immune escape mechanisms. Furthermore, aspirin may be used therapeutically to prevent the development of cancer [ 6 – 9 ]. Aspirin and its effects on lung cancer have prompted significant interest, particularly because of its anti-inflammatory features and possible significance in cancer prevention and treatment. The prostaglandin E2 (PGE2) pathway is important to this connection. PGE2 plays a significant role function in the tumor microenvironment and can influence the development and progression of lung cancer [ 10 ]. PTGS1 is expressed constitutively in many cell types and is considered a housekeeping gene, whereas PTGS2 is triggered by growth factors, cytokines, and inflammatory stimuli. Three types of PGE2 synthase (PTGES, PTGES2, and PTGES3) can convert PGH2 into PGE2 [ 11 ] [ 12 ]. In both mouse peritoneal macrophages and the mouse macrophage cell line RAW264.7 cells, aspirin has been demonstrated to decrease the production of TNF-α and iNOS [ 13 ], which are the mediators of tumor-promoting inflammation. Targeting and re-educating TAMs seems to be a beneficial method when used alone, but it may cause resistance when therapy is stopped, since the effect of aspirin on macrophages is still unclear [ 14 , 15 ], and tumor recurrence or even accelerated tumor growth. However, when TAM-targeted treatments are combined with other immune-centered therapies such as those targeting PD-1/PD-L1, their anti-tumoral potency is significantly enhanced [ 16 ]. Combining TAM-directed therapies with other pharmaceuticals, such as immune checkpoint inhibitors or chemotherapy, can maximize their potential [ 17 ]. To determine the role of aspirin in the formation of pro/anti-tumoral macrophages (M1/M2 macrophages), our study will model the relationship between lung cancer cells and macrophages at the secretome level and shed light on how aspirin-mediated lung cancer cells release factors that affect macrophage plasticity. In our study, we examined the alterations in macrophage phenotypes when exposed to NSCLC secretome under the influence of aspirin. In addition to revealing the effect of aspirin on PD-L1 levels, we examined how M2 macrophages, are affected by the secretomes obtained from lung cancer cells in the presence and absence of aspirin. Material and Methods Cell culture H838 and HCC827 cell cultures were maintained in complete RPMI medium containing 10% fetal bovine serum (FBS), 2mM L-glutamine, 1 penicillin (100units/ml), and 1% streptomycin (100 µg/ml) in a humidified atmosphere with 5% CO 2 at 37°C. H838 cells were stimulated with IFNgamma (final conc. 20 ng/ml) for 48 hours and washed 3 times, and fresh medium was used for cell culture maintenance. For the aspirin treatment of IFNg-induced H838 and HCC827 cell lines, cells were washed three times, and fresh medium was used until secretomes were collected after 48 hours for each condition. Detection of soluble and total forms of PD-L1 protein after stimulation with IFNg : Stimulated PD-L1 expression was demonstrated by both ELISA and Western blot. Protein lysates were obtained from lung cancer cells with/without IFNg stimulation using RIPA buffer (Pierce Cat: 89901), protease inhibitor (Roche Cat: 05 056 489 001), and phosphatase inhibitor (Roche Cat: 04 906 837 001). Then, they were incubated for 20 minutes at 4°C with moderate shaking and centrifuged at 14000 rpm for 10 minutes at 4°C and the supernatants were collected. Protein concentration was measured using the Pierce™ BCA Protein Assay Kit (Thermo Fisher Scientific), and 10–20 ug/well protein was loaded per well. Western blot (WB) analysis was performed according to standard procedures. Proteins were transferred to polyvinylidene difluoride membranes and an enhanced chemiluminescence substrate (BioRad) and anti-PD-L1 and b-actin antibodies were used to visualize protein bands. For detection of soluble PD-L1 expression in lung cancer cells with/without IFNg, the human B7H1/PD-L1 ELISA Kit was used according to the manufacturer's protocol (RayBioetch). Determination of IC50 value of aspirin in lung cancer cells The cytotoxic effect of aspirin (ASA) in lung cancer cells was analyzed by CellTiter 96 AQueous One Solution Cell Proliferation Assay (Promega) at 24, 48, and 72 hours. Absorbance was measured at 490 nm using a microplate reader. Flow cytometric analysis of PBMC-derived macrophage polarization : In order to obtain a myeloid cell population from healthy donor-derived peripheral blood mononuclear cells (PBMCs) (Non-invasive Ethics Committee Approval: GO 23/82), Ficoll 1077 density gradient separation was performed, and monocytes were obtained with the CD14 Macs protocol. M0 macrophage cells were differentiated from monocytes via M-CSF. Macrophage population, CD68 (human macrophage marker) and CD11c markers were confirmed in flow cytometry. In obtaining M1 macrophages, LPS (100 ng/ml) and IFNgamma (20 ng/ml) were used, and in obtaining M2 macrophages, IL4 (25 ng/ml) and IL13 (25 ng/ml) were used to ensure polarization of macrophages. CD38 + macrophages and CD209 + macrophage cells were assessed in order to determine M1 macrophages and M2 macrophages, respectively. [ 13 ] [ 14 ]. Data analysis was performed on the BD FACS Canto II flow cytometry device according to the Mean Fluorescence Intensity (MFI) values of the samples. In addition, both CD38 and CD209 MFI values were analyzed on M1 and M2 macrophage cells using flow cytometry. RNA-seq analysis of M2-polarized macrophages RNA was isolated from M2-polarized macrophages cultured for 48 hours in the presence of secretomes obtained from lung cancer cells treated with aspirin and/or IFNg. RNA was isolated on columns at the single-cell level according to the RNA Purification Kit (Norgen 51800), protocol and RNA quality was checked in the bioanalyzer. After using the QIAseq Stranded mRNA Lib Kit UDI library, RNA sequencing was performed in the Novaseq 6000 device. CCLE data analysis : Lung cancer cells in the Cancer Cell Line Encyclopedia (CCLE) database were sorted by EGFR mutation status. Correlation analyses were performed between EGFR mutant and wild-type cancer cell lines employing 147 non-small cell lung cancer (NSCLC) cell lines expressing PD-L1 evaluated based on PGE2 pathway-linked genes such as PTGS1, PTGS2, PTGES, PTGES2, and PTGES3 at https://portals.broadinstitute.org/ccle . Bioinformatic analysis : A comprehensive bioinformatic analysis was performed on both experimental RNA-sequencing samples and publicly available datasets using a custom Nextflow pipeline. Transcript-level quantification was achieved with Salmon [ 18 ], and gene-level expression values were calculated as transcripts per million (TPM) and subsequently merged. The merged expression matrix was subjected to a two-step filtering process: first, genes with at least one TPM value exceeding an absolute threshold of 1 were retained; second, from these, only genes exhibiting a uniquely dominant expression in a single sample (i.e., a value greater than all other sample values for that gene) were selected for downstream analysis. Hierarchical clustering was then performed on the filtered dataset, and dendrograms were generated to visualize sample relationships. Gene expression patterns were further assessed using Euclidean distance calculations following logarithmic transformation. Distances between M0, M2a, and M2c polarization groups were computed based on the filtered gene expression profiles. All analysis codes will be made available through GitHub upon publication. Cytokine analysis in secretomes Simultaneous quantification of 13 soluble targets essential for immune response, such as IL4, IL2, CXCL10 (IP10), IL1β, TNFα, CCL2 (MCP1), IL17A, IL6, IL10, IFNγ, IL12p70, CXCL8 (IL8), and Free Active TGFβ1, was performed using secretomes of polarized M2 macrophages with lung cancer cell lines using the LEGENDplex™ HU Essential Immune Response Panel (13-plex). Tumor IMmune Estimation Resource (TIMER Analysis) Assessment The CIBERSORT algorithm [ 19 ] was used to assess the relative proportions of M2 macrophage profiling in the TCGA NSCLC patient cohort (n = 515). Spearman correlation analysis was used to examine the association between EGFR mutation and M2 macrophage infiltration. The comparison was carried out between EGFR-mutated vs. wild-type NSCLC. A p-value of 0.05 was used as a threshold for determining significance. Statistical Analyses Statistical analyses were performed using the R statistical analysis software R version 4.4.1 and Python 3.12. Student’s pairwise t-test, ANOVA with Tukey, and Mann-Whitney U test were used for intergroup comparisons. P ≤ 0.05 was considered significant. Data obtained from at least three independent experiments were presented with mean ± standard deviation or standard error values. Results IFNg induces membrane and soluble PD-L1 expression in NSCLC cells. The PD-L1 gene's RNAseq expression data from patients with EGFR-mutated lung adenocarcinoma were obtained from The Cancer Genome Atlas (TCGA, PanCancer Atlas; n = 511). The connection between PD-L1 and EGFR mRNA expression was assessed using the cBioportal database at https://www.cbioportal.org . Based on log2-transformed Transcript per Million (TPM) values, elevated PD-L1 expression was found to be related to the existence of an EGFR mutation in advanced lung cancer (Fig. 1 A). The study includes non-small cell lung cancer cell lines H838 that do not have K-Ras and EGFR mutations as well as the EGFR mutant HCC827 cell line that has substantial PD-L1 expression. De novo PD-L1 expression was induced in H838 cell line upon IFNg. Endogenous total PD-L1 expression in the EGFR mutant HCC827 cell line was confirmed at the protein level (Fig. 1 B-C). In supernatant samples of lung cancer cells, soluble PD-L1 (sPD-L1) levels reached a detectable level with IFNg (Fig. 1 D). Additionally, we determined the 48-hour IC50 values of aspirin for the H838 and HCC827 cell lines to be 2.5 mM. All experiments analyzed both cells and secretomes using the IC50 value of aspirin (Suppl. Figure 1). Administration of aspirin to cancer cell lines expressing endogenous and stimulated PD-L1 had distinct patterns. Using flow cytometry, PD-L1 expression was evaluated under different secretome conditions, and aspirin administration was shown to boost PD-L1 expression in HCC827 cells (Fig. 2 A). PD-L1 protein expressions were examined in accordance with our experimental strategy (Fig. 4 ) of inducing and enhancing PD-L1 expression in cancer cells connected with the M2-polarized macrophages cultured with the lung cancer secretomes. Due to aspirin irreversibly inhibiting COX-1 and COX-2 enzymes, which are responsible for converting arachidonic acid to prostaglandins, including PGE2, as genes involved in the PD-L1 and PGE2 pathways in NSCLC cells were correlated, it was shown that there was a positive correlation between PD-L1 and PTGS2 and a negative correlation between PD-L1 and PTGES3 in cells without an EGFR mutation (Fig. 2 B). Secretome analyses of cancer cells activated with IFNgamma and/or aspirin revealed a different pattern of cytokine release. The immune response-related cytokine panel in these cancer cell secretomes was also examined, as was the extent to which cancer secretomes impact M2 macrophage transcriptomes. After 48 hours of incubation, it was shown that the secretomes of H838 cells displayed a distinct pattern in terms of CCL2, IL6, and IL8 cytokines in comparison to those of HCC827 cells. When the incubation period was extended to 96 hours, the secretion of IL6, IL8, and CXCL10 increased in the H838 cell line, but the secretion of CCL10 increased with aspirin treatment as the incubation period was extended to 96 hours in HCC827 cells (Fig. 3 ). On the other hand, IL4, IL2, IL1β, TNFα, IL17A, IL10, IFNγ, IL12p70, and free Active TGFβ1 were found at very low concentrations ( data not shown ). IFNg or IFNg and Aspirin-stimulated cancer cell secretomes alter macrophage polarization. To determine the impact of cancer secretomes on macrophage differentiation and polarization, macrophages cultured for 48 hours with secretomes derived from lung cancer cells treated with aspirin and/or IFNg were examined for macrophage markers associated with M1 or M2 phenotypes (Fig. 4 ). Conditional lung cancer cell secretomes did not alter any of the markers in M1 polarized macrophages; however, secretomes derived from IFNg treated and/or aspirin-treated H838 cells boosted the expression of CD38 in M2 macrophages compared to the control counterpart (Fig. 5 ). Next, in order to have a better insight into M2 polarization in NSCLC patients, M2-type macrophages were assessed in 515 lung adenocarcinoma patients using TCGA. We compared the immune cell distribution of patients with EGFR mutations to those with wild-type adenocarcinoma. The violin plot graphs from the "Mutation Module" showed the log2 of the fold change between patients with EGFR and wild-type lung adenocarcinoma and the difference in TIMER-estimated differential M2 macrophage infiltration levels between tumors with EGFR mutant vs wild-type. According to that EGFR mutant lung cancer displayed greater numbers of M2 macrophages than patients without mutations (P value = 0.027, Wilcoxon test). The EGFR mutant lung cancer patient group did not, however, exhibit M1 macrophage infiltration in contrast to the wild-type group (P value = 0.56, Wilcoxon test) (Fig. 6 ). M2 polarized macrophages cultured with cancer cell secretomes modulate M2 macrophage plasticity. In order to determine the cytokine profile of M2 polarized macrophages, both the secretomes of cancer cells stimulated with IFNg and/or in the presence of aspirin and the factors derived from M2 polarized macrophages after M2 macrophage cultured in the cancer cell secretome were analyzed. Considering the effect of aspirin on M2 macrophages, M2 macrophages cultured in the presence of aspirin-treated and IFNg-stimulated H838 cell-derived secretomes showed an opposite pattern of CXCL10 (Fig. 7 ) compared to those cultured in the presence of secretomes of HCC827 treated with aspirin. On the other hand, M2 macrophages maintained in the presence of aspirin-treated HCC827 cell-derived secretome had higher levels of IL8 and IL6 (Fig. 7 ), which are secreted by M2 macrophages and promote tumor formation and proliferation. The secretome-conditioned M2 macrophages (H838 + IFNg + Aspirin) were found to be more similar to the M2c subtype than the M2a subtype. RNA sequencing (RNA-seq) analysis was conducted for both experimental RNA samples and publicly available literature datasets using a Nextflow pipeline. Cluster analysis was carried out to better understand hierarchical linkages, and dendrograms were utilized to assist in determining which groups were most similar. According to the hierarchical clustering dendrograms, it indicated that the clusters of M2 macrophages maintained in cancer secretomes generated by H838 differ from those cultured in secretomes obtained from HCC827 (Fig. 8 ). Following z-score normalization, gene lists curated based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database were analyzed separately. Hematopoietic Cell Lineage (HCL) with 69 overlapping genes out of 100 (Fig. 9 A) and Antigen Processing and Presentation (APP) with 52 overlapping genes out of 81 were identified (Fig. 9 B). Euclidean distance-based visualizations of gene expression levels were created for these groups using logarithmic transformations. Furthermore, heatmap representations were generated by normalizing the genes corresponding to the M1 and M2 macrophage markers identified in the literature using z-scores (Fig. 9 C-D). We also examined how comparable the M2 macrophages in our study were to those in the GEO data set GSE227737 [ 20 ]. In that set, transcript studies were also performed on M2 macrophages differentiated from PBMC using RNA-Seq data. Distances between the M0, M2a, and M2c groups were calculated based on the filtered RNA-seq data (Fig. 10 ). The calculated distances were 0.125874 for M0, 0.1201646 for M2a, and 0.1100931 for M2c. M2-polarized macrophages cultured with the secretome condition of (H838 + IFNg + Aspirin) were shown to shift from the M2a subtype to the M2c. Based on these results, the M2c group was selected for further analysis using Weighted Gene Co-expression Network Analysis (WGCNA). This analysis included variance stabilization using varianceStabilizingTransformation (set to 0.95), determination of the soft threshold with pickSoftThreshold, visualization of dendrograms and module assignments using plotDendroAndColors, and calculation of the topological overlap matrix (TOM) with TOMsimilarityFromExpr. Two gene modules, Green and Red, were identified based on the WGCNA results (Suppl. Figure 2 & Suppl. Table 1). For M2 macrophages established under the secretome condition (H838 + IFNg + Aspirin), genes exhibiting a profile similar to M2c were listed to indicate genes (Suppl. Table 1) involved in shifting the subtype from M2a to M2c. Discussion Mutation-induced EGFR activation in tumor cells enhances PD-L1 expression and favors T cell apoptosis and immunological evasion. EGFR-TKIs increase the number of CD8 + T cells and dendritic cells, eliminate FOXP3 + Tregs, block the polarization phenotype of M2 macrophages, and improve the presentation of MHC class I and II antigens in response to IFNg [ 21 ] [ 22 ]. Compared to PD-L1-high tumors, aspirin use after diagnosis has been also associated with a significantly decreased mortality risk for colorectal cancer in PD-L1-low tumors. [ 23 ]. We used conditioned media secreted from both EGFR mutant and non-EGFR mutant cells to perform secretome-mediated regulation of M2 polarized macrophages. PD-L1 surface expression, either endogenous or induced by IFN-gamma, was followed, and the impact of aspirin treatment on PD-L1 expression has been assessed at the protein level. Aspirin irreversibly inhibits the enzymes COX-1 and COX-2, which are required for PGE2 production [ 24 ]. The significant positive correlation on the PD-L1 expression in non-EGFR mutants suggests that it may play a role in aspirin sensitivity. Therefore, modulation of exogenous rather than endogenous PD-L1 expression is thought to alter the tumor microenvironment and especially macrophage plasticity in cancer cell secretome. These results imply that aspirin therapy resistance may be caused by activation of the PD-L1 immune checkpoint pathway, which can be reversed by immune checkpoint inhibitors. According to our study, aspirin treatment significantly increased the expression of PD-L1 in EGFR mutant lung cancer cells. Nevertheless, non-mutant IFN-gamma-stimulated cells did not exhibit an increase in PD-L1 expression in response to aspirin treatment. One of the consequences of aspirin resistance in EGFR mutant non-small cell lung cancer, as indicated by these data, is an increase in PD-L1 expression. Nevertheless, studies have demonstrated that aspirin dramatically reduced PD-L1 expression at both the mRNA and protein levels in non-EGFR-mutant lung cancer cells (A549 and H1299). Aspirin's blockade of TAZ, the transcriptional coactivator of the PD-L1 promoter, was linked to this reduction in PD-L1 expression [ 25 ]. Consequently, it is mechanically important to investigate the PD-L1 transcriptional regulators in aspirin-resistant cancer cells. The H838 cell line that we employed in our studies is derived from NSCLC. However, NSCLC cells that belong to distinct subclasses may respond differently to aspirin due to histological subclassification, such as H1299, large cell carcinoma [ 25 ]. M2-polarized macrophages are classified into four subgroups: M2a, M2b, M2c, and M2d. IL4 or IL13 stimulates M2a macrophages, leading to increased production of IL10, TGFβ, CCL17, CCL18, and CCL22 [ 26 ]. These macrophages boost endocytotic activity, which promotes cell proliferation and tissue repair [ 27 ]. We polarized macrophages from M0 macrophages with IL4 and IL13 cytokines, and M1 marker CD38 [ 28 ] and M2 marker CD209 [ 29 ] expression in M2-polarized macrophages were analyzed; CD11c, a monocyte/macrophage marker, was substantially higher in differentiated polarized macrophages. Furthermore, CD38 expression was observed to be considerably higher in M2 + (H838 & IFNg) secretome macrophages compared to M2 macrophages cultured with H838 secretome but not stimulated with IFNg. Also, CXCL10 was significantly lower in M2 macrophages cultured in the presence of aspirin-treated IFNg-induced H838 secretome, based on our analysis of the cytokine profiles of M2 macrophages, specifically M2a, which we differentiated through cytokine stimulation using IL4 and IL13. This implies that secretomes originating from cancer cells may influence the factors released by M2a polarized macrophages. M2b and M2c subtypes, on the other hand, are referred to as "regulatory macrophages" because they help maintain or restore cellular homeostasis. IL12, IL23, and TNFα activate M2b macrophages, which then release IL1β, TNFα, IL6, and IL10. M2c macrophages are activated by IL10, TGFβ, or glucocorticoids, resulting in increased production of IL10, CCL16, and CCL18 [ 30 ] [ 31 ]. It is emphasized that increased STAT6 signaling results in PPARγ-mediated macrophage programming [ 32 ], which contributes to increased efferocytosis and inflammation resolution [ 33 ]. STAT6 and PPARγ are also referred to as M2a macrophage markers. In our study, the decrease in the expression of STAT6 and PPARG transcription factors at the gene level in M2 + (H838 + IFNg + Aspirin) secretome macrophages compared to M2 macrophages cultured with H838 secretome that was not stimulated with IFNg draws attention to the fact that this condition modulates macrophage plasticity. When the gene expression profile of M1 macrophage markers was examined, it revealed that they were expressed higher in M2 + (H838 + IFNg + Aspirin) secretome macrophages than in macrophages maintained with other H838-derived secretomes. In addition, based on our transcriptomic analyses, CD38 expression showed an increased pattern in M2 macrophages cultured in the presence of (H838 + IFNg) secretome and (H838 + IFNg + Aspirin) secretome . We noticed that M2-polarized macrophages cultured in the presence of IFNg-stimulated and aspirin-treated IFNg-induced secretome had higher levels of CD38 surface expression than their counterparts. As a result, our findings highlight the ability of both M2 plasticity and EGFR non-mutant conditional secretomes to influence the phenotype of the M2 macrophage subtype. Furthermore, inhibiting PPAR-γ with an antagonist leads to differentiation of M2c-like cells. When macrophages are differentiated with IL-4 (M2a conditions), PPAR gamma agonist changes the polarization between M2a (CD206 + CD209 + CD163 − MerTK − ) and M2c (CD206 high CD209 − CD163 + MerTK + ) [ 34 ]. In our study, we additionally investigated the effect of aspirin on modulation of PD-L1 protein expression in EGFR mutant and non-mutant cancer cells. The combined effects of osimertinib and aspirin treatment have been examined in vitro and in vivo in osimertinib-resistant non-small cell lung cancer cell lines. The results demonstrated the combination of osimertinib and aspirin had strong anti-proliferative and pro-apoptotic effects in osimertinib-resistant cancer cells by increasing Bim expression and inhibiting phosphorylation of the Akt/FoxO3a signaling component [ 21 ]. For these reasons, assessing aspirin resistance and PD-L1 levels, as well as M2 macrophage infiltration in the non-small cell lung cancer microenvironment, will provide the basis for understanding aspirin resistance mechanisms and developing personalized therapeutics to suppress the immunosuppressive immune response. It has been reported that CD8 expression is reduced while M2 macrophages (CD68 + and CD206 + macrophages) are increased in the tissues of patients resistant to tyrosine kinase inhibitors (TKIs), particularly individuals resistant to EGFR-TKIs; thus, an immunosuppressive niche forms in TKI-resistant non-small cell lung cancer tissues [ 35 ]. In experimental assays in which macrophages and cancer cells were co-cultured, it was established that M2 macrophages inhibited the anticancer effect of EGFR-TKIs, whereas M1 macrophages increased the antitumor activity. During M2a polarization, secretome-containing conditioned media produced from mesenchymal stem cells greatly increased the expression of M2a-, M2b-, and M2c-specific genes and proteins, and macrophages secreted a substantial amount of IL10. Similarly, M2b/M2c-specific marker expressions were also higher in M2a macrophages established with these secretomes (preMSC-CM), revealing that they help to repolarize M2a-like macrophages to M2b/M2c subtypes [ 35 , 36 ]. The distinctive expression patterns of M2-polarized macrophages have significance for macrophage-targeting treatment approaches. [ 37 ]. Strategies that combine aspirin and receptor tyrosine kinase inhibitors, aspirin resistance and PD-L1 levels [ 38 ], M2 macrophage infiltration in the microenvironment of non-small cell lung cancer, and molecular classification of M2 macrophage subtypes have predictive value for the prognosis of the disease [ 39 ]. According to our results, aspirin treatment of EGFR non-mutant cancer cell-derived secretomes alters the molecular characteristics of M2 macrophages, thus changing their plasticity. As a result, mutation type, PD-L1 expression level, and immune phenotyping of tumor-associated M2 macrophages will assist in developing non-small cell lung cancer therapy regimens consisting of EGFR inhibitors and aspirin. Declarations Ethical approval: This study was performed in line with the principles of the Declaration of Helsinki. Experiments derived from PBMC samples obtained from healthy donors were approved by the non-invasive Ethics Committee (Approval: GO 23/82, Hacettepe University, Ankara, Türkiye). Written informed consent was obtained from all individual participants included in the study. Funding: This work has been supported by the Scientific Research Projects Coordination Unit of Hacettepe University under grant number TSA-2021-19475. Author Contribution N.U. wrote the main manuscript and prepared figures. S.U., E.T., and E.D.Y. prepared figures. Y.K. and G.E. edited the manuscript. All authors reviewed the manuscript. Acknowledgement This work has been supported by the Scientific Research Projects Coordination Unit of Hacettepe University under grant number TSA-2021-19475. Data Availability The GEO data set GSE227737 was used for the bioinformatic analysis. References T. Ma, J. Jiao, R. Huo, X. Li, G. Fang, Q. Zhao, W. Liu, X. Han, C. Xi, Y. Wang and Y. 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Paunel-Gorgulu, Int J Mol Sci 23, (2022) doi: 10.3390/ijms23084104 Z. Duan and Y. Luo, Signal Transduct Target Ther 6, 127 (2021) doi: 10.1038/s41392-021-00506-6 M. Aiad, A. Tahir, K. Fresco, Z. Prenatt, K. Ramos-Feliciano, J. Walia, J. Stoltzfus and H.J. Albandar, Cureus 14, e25891 (2022) doi: 10.7759/cureus.25891 D. Feng, X. Shi, D. Li, R. Wu, J. Wang, W. Wei and P. Han, Genes Dis 11, 101086 (2024) doi: 10.1016/j.gendis.2023.101086 Additional Declarations No competing interests reported. Supplementary Files Suppl.Table1.pdf Supplementary Table 1. Genes with similar profiles to M2c were identified in M2 macrophages generated under secretome condition stated as H838+IFNg+Aspirin. SupplementaryFigure2.tiff SupplementaryFigure1.tiff Cite Share Download PDF Status: Published Journal Publication published 16 Sep, 2025 Read the published version in Inflammation Research → Version 1 posted Editorial decision: Revision requested 16 Aug, 2025 Reviews received at journal 14 Jul, 2025 Reviewers agreed at journal 14 Jul, 2025 Reviewers invited by journal 06 Jul, 2025 Editor assigned by journal 23 Jun, 2025 Submission checks completed at journal 23 Jun, 2025 First submitted to journal 23 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6954264","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482374100,"identity":"45c0b3b6-9d16-4709-a056-650b2d465665","order_by":0,"name":"Nese Unver","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIiWNgGAWjYHAD5mMoPGK0sKWBSAkeuBY2glp4zIjTYs7e/vABY9udxH7pM98e/KixqbNn7z34gKHCOrFBvvcBNi2WPWeMDRjbniXO7MvdbthzLE2Ch+dcsgHDmfTEBjZ2A2xaDG7ksEkwth02NjjDu02Ct+GwBI9EjhlIBKgFu8sM7j9//gOkxf4MzzPJvw3/JXjk35j/YPyHR8sNBjMGoBY5Ax4eNmnehgNAW4DhwNiAR8uZHGOJhHOH5STOsJlJyxxLluw5k5cskXAs3bgNEuqYWo4ff/jhQ9lhHv4e5meSb2rs+Nnbzx788KHGWrYfNW5RQQIqlwciQjgmUbSMglEwCkbBKEACAONBV84JoS12AAAAAElFTkSuQmCC","orcid":"","institution":"Hacettepe University","correspondingAuthor":true,"prefix":"","firstName":"Nese","middleName":"","lastName":"Unver","suffix":""},{"id":482374101,"identity":"6c960475-b9e7-4c19-9d67-bd590faba367","order_by":1,"name":"Sila Uluturk","email":"","orcid":"","institution":"Hacettepe University","correspondingAuthor":false,"prefix":"","firstName":"Sila","middleName":"","lastName":"Uluturk","suffix":""},{"id":482374102,"identity":"422699f5-7db6-4999-9629-1f860465eadc","order_by":2,"name":"Ece Tavukcuoglu","email":"","orcid":"","institution":"Hacettepe University","correspondingAuthor":false,"prefix":"","firstName":"Ece","middleName":"","lastName":"Tavukcuoglu","suffix":""},{"id":482374103,"identity":"3d9c6106-24ff-4fae-afa8-a55c640db949","order_by":3,"name":"Elif Duymaz Yilmaz","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Elif","middleName":"Duymaz","lastName":"Yilmaz","suffix":""},{"id":482374104,"identity":"9cd72c16-b313-4cfc-a0df-b43a909aa4fb","order_by":4,"name":"Yasin Kaymaz","email":"","orcid":"","institution":"Ege University","correspondingAuthor":false,"prefix":"","firstName":"Yasin","middleName":"","lastName":"Kaymaz","suffix":""},{"id":482374105,"identity":"006da8d7-6b55-4dc0-8f87-e4ba334a50f1","order_by":5,"name":"Gunes Esendagli","email":"","orcid":"","institution":"Hacettepe University","correspondingAuthor":false,"prefix":"","firstName":"Gunes","middleName":"","lastName":"Esendagli","suffix":""}],"badges":[],"createdAt":"2025-06-23 08:08:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6954264/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6954264/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00011-025-02091-8","type":"published","date":"2025-09-16T15:57:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86499345,"identity":"309a9aa6-e1ac-456b-9f28-460d2b1773bc","added_by":"auto","created_at":"2025-07-11 10:46:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":283204,"visible":true,"origin":"","legend":"\u003cp\u003eDetection and modulation of PD-L1 expression. A. Bioinformatic analysis of PD-L1 and EGFR expression based on TCGA NSCLC patient data. B-C. Demonstration of induced PD-L1 expression in PD-L1-negative lung cancer cell lines as a result of IFNg stimulation (20 ng/ml, 48 h) by the western blot and flow cytometry D. Analysis of soluble PD-L1 protein.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/b3b4ade3fb794ab072d4fb81.png"},{"id":86498036,"identity":"2921feec-f5cd-4c32-8061-86cffbd530db","added_by":"auto","created_at":"2025-07-11 10:30:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":458953,"visible":true,"origin":"","legend":"\u003cp\u003eA. PD-L1 expression in lung cancer cells in the presence of IFNg stimulation and/or aspirin. MFI values regarding PD-L1 expression ​​were analyzed by flow cytometry (**P=1.42912E-05, H838 cell line vs. IFNg-stimulated H838 cell line); ***P=0.0001, H838 cell line vs. ASA-treated IFN-g-stimulated H838 cell line; ***P= 5.30514E-06, HCC827 cell line vs. ASA-treated HCC827 cell line; **P= 0.00215). ASA: aspirin. B. Correlation analyses were performed between EGFR mutant and wild-type NSCLC cell lines according to PD-L1 and PGE2 pathway-linked genes such as PTGS1, PTGS2, PTGES, PTGES2, and PTGES3.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/c3592352b867960e73909a35.png"},{"id":86498038,"identity":"db9c6ecd-c7ef-4259-9ce6-27bfde84b310","added_by":"auto","created_at":"2025-07-11 10:30:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":162615,"visible":true,"origin":"","legend":"\u003cp\u003eCytokine analysis in secretomes obtained from cancer cell-derived secretomes under IFNg and/or aspirin-treated conditions ( P \u0026lt; 0.05*; P \u0026lt; 0.01** and P \u0026lt; 0.001***).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/10cba13b4f1e27078d4cda09.png"},{"id":86498825,"identity":"bc7ed6d4-e750-4d6f-9891-3e46c7004c8a","added_by":"auto","created_at":"2025-07-11 10:38:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":348046,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative histograms showing macrophage polarization using CD68, CD11c, CD38, and CD209 markers with a conceptual illustration of the time-based experimental approach.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/61ae0aa51aad1ec5f6c9ed5f.png"},{"id":86498043,"identity":"9051a4ae-ac47-4e00-9129-26bfd8af3155","added_by":"auto","created_at":"2025-07-11 10:30:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":200294,"visible":true,"origin":"","legend":"\u003cp\u003eFlow cytometric analysis of CD11c, CD38, and CD209 proteins in polarized M2 macrophages cultured in the presence of conditional lung cancer cell secretomes (M2+H838\u003csub\u003esecretome \u003c/sub\u003evs. M2+(H838+IFNg)\u003csub\u003esecretome\u003c/sub\u003e, P=0.017; M2+H838\u003csub\u003esecretome\u003c/sub\u003e vs. M2+(H838+IFNg+Aspirin)\u003csub\u003esecretome\u003c/sub\u003e; P=0.03).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/0f53a69eea0a5d84bbbca96f.png"},{"id":86498828,"identity":"19332096-7429-42c0-88b7-e71b7dd804cc","added_by":"auto","created_at":"2025-07-11 10:38:48","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":292300,"visible":true,"origin":"","legend":"\u003cp\u003eViolin plot graphs of M2 macrophage infiltration. A) TIMER-estimated M1 macrophage infiltration levels between tumors with mutant or wild-type EGFR in lung cancer adenocarcinoma. B) M2 macrophage infiltration levels between tumors with mutant or wild-type EGFR in lung cancer adenocarcinoma.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/0a517c18aa4378e802385024.png"},{"id":86498064,"identity":"28d5265c-6208-4a4c-b2b6-dd453d6227f2","added_by":"auto","created_at":"2025-07-11 10:30:48","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":137659,"visible":true,"origin":"","legend":"\u003cp\u003eCytokine analysis in secretomes obtained from the culture of M2 macrophages in the presence of conditional cancer cell-derived secretomes under IFNg and/or aspirin-treated conditions.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/55099f724df91c220a99bb78.png"},{"id":86499346,"identity":"69799d11-f57f-45dd-99fe-51663c746b0c","added_by":"auto","created_at":"2025-07-11 10:46:48","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":87835,"visible":true,"origin":"","legend":"\u003cp\u003eHierarchical clustering dendrograms of sequenced RNA samples.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/4c9a5f0ffff3892777e959fa.png"},{"id":86498833,"identity":"3dda9d42-f992-46cb-930e-7fab08b129ac","added_by":"auto","created_at":"2025-07-11 10:38:48","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":375053,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap visualizations of the analyses regarding the Z-score normalized data for the determined A. Hematopoietic Cell Lineage (HCL) and B. Antigen Processing and Presentation (APP) gene lists C. M1-polarized and D. M2-polarized macrophage markers.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/18255b7d7b6a4f7d55ff35a9.png"},{"id":86499351,"identity":"898133cd-aa4a-4c35-b016-d6b8813113be","added_by":"auto","created_at":"2025-07-11 10:46:48","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":156383,"visible":true,"origin":"","legend":"\u003cp\u003eEuclidean distance analysis using logarithmic adjustments of gene expression levels. The GEO data set GSE227737 was used for the comparison. Distances between the M2a and M2c groups were calculated based on the filtered RNA-seq data.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/849c220c0c461709ad3f72b6.png"},{"id":91889786,"identity":"e84fdc97-60ba-4bc0-b86f-d9380c0e7160","added_by":"auto","created_at":"2025-09-22 16:01:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3177952,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/a09a4d25-e364-4c99-b3b3-87666e9e1974.pdf"},{"id":86498823,"identity":"896cb749-3387-472c-9ae2-b843977f5052","added_by":"auto","created_at":"2025-07-11 10:38:47","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":116412,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 1.\u003c/strong\u003e Genes with similar profiles to M2c were identified in M2 macrophages generated under secretome condition stated as H838+IFNg+Aspirin.\u003c/p\u003e","description":"","filename":"Suppl.Table1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/ba2ffa5854ca937320c34d96.pdf"},{"id":86498826,"identity":"2508cb19-a2c1-4901-bd47-62aad5e15f3b","added_by":"auto","created_at":"2025-07-11 10:38:48","extension":"tiff","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":4323662,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure2.tiff","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/ab6aa5a5a51aa61fc3dbe77d.tiff"},{"id":86498053,"identity":"cd21195d-4c5f-4e88-b574-ca5fc7992270","added_by":"auto","created_at":"2025-07-11 10:30:48","extension":"tiff","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":4323662,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.tiff","url":"https://assets-eu.researchsquare.com/files/rs-6954264/v1/2ece1258ddffa59edf08cc52.tiff"}],"financialInterests":"No competing interests reported.","formattedTitle":"The impact of aspirin on PD-L1 expression and alteration of M2 polarization in non-small cell lung cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMutational load, lymphocyte count, immune cell infiltration (intratumoral T cells), PD-L1 expression, the abundance of inhibitory mediators, tumor response to immune effector cells, MHC expression, and sensitivity to IFNgamma (IFNg) are essential components in immune evasion of cancer cells [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Despite widespread utilization and rapid FDA approval of immune checkpoint inhibitor (ICI) drugs, more studies on predictive biomarkers, resistance mechanisms, treatment duration, immune-related toxicities, and the PD-L1 expression threshold remains required for a complete understanding of their anti-cancer potential [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The use of soluble PD-1 (sPD-1) and soluble PD-L1 (sPD-L1) as prognostic indicators or biomarkers of immunotherapy response is being assessed in molecular lung cancer research [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eChemopreventive agents, including aspirin and other COX-2 inhibitors, aromatase inhibitors, and bisphosphonates, hamper the formation of premalignant lesions and may ameliorate immune escape mechanisms. Furthermore, aspirin may be used therapeutically to prevent the development of cancer [\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Aspirin and its effects on lung cancer have prompted significant interest, particularly because of its anti-inflammatory features and possible significance in cancer prevention and treatment. The prostaglandin E2 (PGE2) pathway is important to this connection. PGE2 plays a significant role function in the tumor microenvironment and can influence the development and progression of lung cancer [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. PTGS1 is expressed constitutively in many cell types and is considered a housekeeping gene, whereas PTGS2 is triggered by growth factors, cytokines, and inflammatory stimuli. Three types of PGE2 synthase (PTGES, PTGES2, and PTGES3) can convert PGH2 into PGE2 [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn both mouse peritoneal macrophages and the mouse macrophage cell line RAW264.7 cells, aspirin has been demonstrated to decrease the production of TNF-α and iNOS [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], which are the mediators of tumor-promoting inflammation. Targeting and re-educating TAMs seems to be a beneficial method when used alone, but it may cause resistance when therapy is stopped, since the effect of aspirin on macrophages is still unclear [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], and tumor recurrence or even accelerated tumor growth. However, when TAM-targeted treatments are combined with other immune-centered therapies such as those targeting PD-1/PD-L1, their anti-tumoral potency is significantly enhanced [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Combining TAM-directed therapies with other pharmaceuticals, such as immune checkpoint inhibitors or chemotherapy, can maximize their potential [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. To determine the role of aspirin in the formation of pro/anti-tumoral macrophages (M1/M2 macrophages), our study will model the relationship between lung cancer cells and macrophages at the secretome level and shed light on how aspirin-mediated lung cancer cells release factors that affect macrophage plasticity.\u003c/p\u003e\u003cp\u003eIn our study, we examined the alterations in macrophage phenotypes when exposed to NSCLC secretome under the influence of aspirin. In addition to revealing the effect of aspirin on PD-L1 levels, we examined how M2 macrophages, are affected by the secretomes obtained from lung cancer cells in the presence and absence of aspirin.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e\u003cstrong\u003eCell culture\u003c/strong\u003e\u003cp\u003eH838 and HCC827 cell cultures were maintained in complete RPMI medium containing 10% fetal bovine serum (FBS), 2mM L-glutamine, 1 penicillin (100units/ml), and 1% streptomycin (100 \u0026micro;g/ml) in a humidified atmosphere with 5% CO\u003csub\u003e2\u003c/sub\u003e at 37\u0026deg;C. H838 cells were stimulated with IFNgamma (final conc. 20 ng/ml) for 48 hours and washed 3 times, and fresh medium was used for cell culture maintenance. For the aspirin treatment of IFNg-induced H838 and HCC827 cell lines, cells were washed three times, and fresh medium was used until secretomes were collected after 48 hours for each condition.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eDetection of soluble and total forms of PD-L1 protein after stimulation with IFNg\u003c/b\u003e: Stimulated PD-L1 expression was demonstrated by both ELISA and Western blot. Protein lysates were obtained from lung cancer cells with/without IFNg stimulation using RIPA buffer (Pierce Cat: 89901), protease inhibitor (Roche Cat: 05 056 489 001), and phosphatase inhibitor (Roche Cat: 04 906 837 001). Then, they were incubated for 20 minutes at 4\u0026deg;C with moderate shaking and centrifuged at 14000 rpm for 10 minutes at 4\u0026deg;C and the supernatants were collected. Protein concentration was measured using the Pierce\u0026trade; BCA Protein Assay Kit (Thermo Fisher Scientific), and 10\u0026ndash;20 ug/well protein was loaded per well. Western blot (WB) analysis was performed according to standard procedures. Proteins were transferred to polyvinylidene difluoride membranes and an enhanced chemiluminescence substrate (BioRad) and anti-PD-L1 and b-actin antibodies were used to visualize protein bands. For detection of soluble PD-L1 expression in lung cancer cells with/without IFNg, the human B7H1/PD-L1 ELISA Kit was used according to the manufacturer's protocol (RayBioetch).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDetermination of IC50 value of aspirin in lung cancer cells\u003c/strong\u003e\u003cp\u003eThe cytotoxic effect of aspirin (ASA) in lung cancer cells was analyzed by CellTiter 96 AQueous One Solution Cell Proliferation Assay (Promega) at 24, 48, and 72 hours. Absorbance was measured at 490 nm using a microplate reader.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFlow cytometric analysis of PBMC-derived macrophage polarization\u003c/b\u003e: In order to obtain a myeloid cell population from healthy donor-derived peripheral blood mononuclear cells (PBMCs) (Non-invasive Ethics Committee Approval: GO 23/82), Ficoll 1077 density gradient separation was performed, and monocytes were obtained with the CD14 Macs protocol. M0 macrophage cells were differentiated from monocytes via M-CSF. Macrophage population, CD68 (human macrophage marker) and CD11c markers were confirmed in flow cytometry. In obtaining M1 macrophages, LPS (100 ng/ml) and IFNgamma (20 ng/ml) were used, and in obtaining M2 macrophages, IL4 (25 ng/ml) and IL13 (25 ng/ml) were used to ensure polarization of macrophages. CD38\u003csup\u003e+\u003c/sup\u003e macrophages and CD209\u003csup\u003e+\u003c/sup\u003e macrophage cells were assessed in order to determine M1 macrophages and M2 macrophages, respectively. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Data analysis was performed on the BD FACS Canto II flow cytometry device according to the Mean Fluorescence Intensity (MFI) values of the samples. In addition, both CD38 and CD209 MFI values were analyzed on M1 and M2 macrophage cells using flow cytometry.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eRNA-seq analysis of M2-polarized macrophages\u003c/strong\u003e\u003cp\u003eRNA was isolated from M2-polarized macrophages cultured for 48 hours in the presence of secretomes obtained from lung cancer cells treated with aspirin and/or IFNg. RNA was isolated on columns at the single-cell level according to the RNA Purification Kit (Norgen 51800), protocol and RNA quality was checked in the bioanalyzer. After using the QIAseq Stranded mRNA Lib Kit UDI library, RNA sequencing was performed in the Novaseq 6000 device.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eCCLE data analysis\u003c/b\u003e: Lung cancer cells in the Cancer Cell Line Encyclopedia (CCLE) database were sorted by EGFR mutation status. Correlation analyses were performed between EGFR mutant and wild-type cancer cell lines employing 147 non-small cell lung cancer (NSCLC) cell lines expressing PD-L1 evaluated based on PGE2 pathway-linked genes such as PTGS1, PTGS2, PTGES, PTGES2, and PTGES3 at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://portals.broadinstitute.org/ccle\u003c/span\u003e\u003cspan address=\"https://portals.broadinstitute.org/ccle\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eBioinformatic analysis\u003c/b\u003e: A comprehensive bioinformatic analysis was performed on both experimental RNA-sequencing samples and publicly available datasets using a custom Nextflow pipeline. Transcript-level quantification was achieved with Salmon [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and gene-level expression values were calculated as transcripts per million (TPM) and subsequently merged. The merged expression matrix was subjected to a two-step filtering process: first, genes with at least one TPM value exceeding an absolute threshold of 1 were retained; second, from these, only genes exhibiting a uniquely dominant expression in a single sample (i.e., a value greater than all other sample values for that gene) were selected for downstream analysis. Hierarchical clustering was then performed on the filtered dataset, and dendrograms were generated to visualize sample relationships. Gene expression patterns were further assessed using Euclidean distance calculations following logarithmic transformation. Distances between M0, M2a, and M2c polarization groups were computed based on the filtered gene expression profiles. All analysis codes will be made available through GitHub upon publication.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCytokine analysis in secretomes\u003c/strong\u003e\u003cp\u003eSimultaneous quantification of 13 soluble targets essential for immune response, such as IL4, IL2, CXCL10 (IP10), IL1β, TNFα, CCL2 (MCP1), IL17A, IL6, IL10, IFNγ, IL12p70, CXCL8 (IL8), and Free Active TGFβ1, was performed using secretomes of polarized M2 macrophages with lung cancer cell lines using the LEGENDplex\u0026trade; HU Essential Immune Response Panel (13-plex).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTumor IMmune Estimation Resource (TIMER Analysis) Assessment\u003c/strong\u003e\u003cp\u003eThe CIBERSORT algorithm [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] was used to assess the relative proportions of M2 macrophage profiling in the TCGA NSCLC patient cohort (n\u0026thinsp;=\u0026thinsp;515). Spearman correlation analysis was used to examine the association between EGFR mutation and M2 macrophage infiltration. The comparison was carried out between EGFR-mutated vs. wild-type NSCLC. A p-value of 0.05 was used as a threshold for determining significance.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eStatistical Analyses\u003c/strong\u003e\u003cp\u003eStatistical analyses were performed using the R statistical analysis software R version 4.4.1 and Python 3.12. Student\u0026rsquo;s pairwise t-test, ANOVA with Tukey, and Mann-Whitney U test were used for intergroup comparisons. P\u0026thinsp;\u0026le;\u0026thinsp;0.05 was considered significant. Data obtained from at least three independent experiments were presented with mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or standard error values.\u003c/p\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eIFNg induces membrane and soluble PD-L1 expression in NSCLC cells.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe PD-L1 gene's RNAseq expression data from patients with EGFR-mutated lung adenocarcinoma were obtained from The Cancer Genome Atlas (TCGA, PanCancer Atlas; n\u0026thinsp;=\u0026thinsp;511). The connection between PD-L1 and EGFR mRNA expression was assessed using the cBioportal database at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cbioportal.org\u003c/span\u003e\u003cspan address=\"https://www.cbioportal.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Based on log2-transformed Transcript per Million (TPM) values, elevated PD-L1 expression was found to be related to the existence of an EGFR mutation in advanced lung cancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The study includes non-small cell lung cancer cell lines H838 that do not have K-Ras and EGFR mutations as well as the EGFR mutant HCC827 cell line that has substantial PD-L1 expression.\u003c/p\u003e\u003cp\u003e\u003cem\u003eDe novo\u003c/em\u003e PD-L1 expression was induced in H838 cell line upon IFNg. Endogenous total PD-L1 expression in the EGFR mutant HCC827 cell line was confirmed at the protein level (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB-C). In supernatant samples of lung cancer cells, soluble PD-L1 (sPD-L1) levels reached a detectable level with IFNg (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Additionally, we determined the 48-hour IC50 values of aspirin for the H838 and HCC827 cell lines to be 2.5 mM. All experiments analyzed both cells and secretomes using the IC50 value of aspirin (Suppl. Figure\u0026nbsp;1).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eAdministration of aspirin to cancer cell lines expressing endogenous and stimulated PD-L1 had distinct patterns.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUsing flow cytometry, PD-L1 expression was evaluated under different secretome conditions, and aspirin administration was shown to boost PD-L1 expression in HCC827 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). PD-L1 protein expressions were examined in accordance with our experimental strategy (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) of inducing and enhancing PD-L1 expression in cancer cells connected with the M2-polarized macrophages cultured with the lung cancer secretomes. Due to aspirin irreversibly inhibiting COX-1 and COX-2 enzymes, which are responsible for converting arachidonic acid to prostaglandins, including PGE2, as genes involved in the PD-L1 and PGE2 pathways in NSCLC cells were correlated, it was shown that there was a positive correlation between PD-L1 and PTGS2 and a negative correlation between PD-L1 and PTGES3 in cells without an EGFR mutation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSecretome analyses of cancer cells activated with IFNgamma and/or aspirin revealed a different pattern of cytokine release.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe immune response-related cytokine panel in these cancer cell secretomes was also examined, as was the extent to which cancer secretomes impact M2 macrophage transcriptomes. After 48 hours of incubation, it was shown that the secretomes of H838 cells displayed a distinct pattern in terms of CCL2, IL6, and IL8 cytokines in comparison to those of HCC827 cells. When the incubation period was extended to 96 hours, the secretion of IL6, IL8, and CXCL10 increased in the H838 cell line, but the secretion of CCL10 increased with\u003c/p\u003e\u003cp\u003easpirin treatment as the incubation period was extended to 96 hours in HCC827 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). On the other hand, IL4, IL2, IL1β, TNFα, IL17A, IL10, IFNγ, IL12p70, and free Active TGFβ1 were found at very low concentrations (\u003cem\u003edata not shown\u003c/em\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eIFNg or IFNg and Aspirin-stimulated cancer cell secretomes alter macrophage polarization.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo determine the impact of cancer secretomes on macrophage differentiation and polarization, macrophages cultured for 48 hours with secretomes derived from lung cancer cells treated with aspirin and/or IFNg were examined for macrophage markers associated with M1 or M2 phenotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eConditional lung cancer cell secretomes did not alter any of the markers in M1 polarized macrophages; however, secretomes derived from IFNg treated and/or aspirin-treated H838 cells boosted the expression of CD38 in M2 macrophages compared to the control counterpart (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNext, in order to have a better insight into M2 polarization in NSCLC patients, M2-type macrophages were assessed in 515 lung adenocarcinoma patients using TCGA. We compared the immune cell distribution of patients with EGFR mutations to those with wild-type adenocarcinoma. The violin plot graphs from the \"Mutation Module\" showed the log2 of the fold change between patients with EGFR and wild-type lung adenocarcinoma and the difference in TIMER-estimated differential M2 macrophage infiltration levels between tumors with EGFR mutant vs wild-type. According to that EGFR mutant lung cancer displayed greater numbers of M2 macrophages than patients without mutations (P value\u0026thinsp;=\u0026thinsp;0.027, Wilcoxon test). The EGFR mutant lung cancer patient group did not, however, exhibit M1 macrophage infiltration in contrast to the wild-type group (P value\u0026thinsp;=\u0026thinsp;0.56, Wilcoxon test) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eM2 polarized macrophages cultured with cancer cell secretomes modulate M2 macrophage plasticity.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn order to determine the cytokine profile of M2 polarized macrophages, both the secretomes of cancer cells stimulated with IFNg and/or in the presence of aspirin and the factors derived from M2 polarized macrophages after M2 macrophage cultured in the cancer cell secretome were analyzed. Considering the effect of aspirin on M2 macrophages, M2 macrophages cultured in the presence of aspirin-treated and IFNg-stimulated H838 cell-derived secretomes showed an opposite pattern of CXCL10 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) compared to those cultured in the presence of secretomes of HCC827 treated with aspirin. On the other hand, M2 macrophages maintained in the presence of aspirin-treated HCC827 cell-derived secretome had higher levels of IL8 and IL6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e), which are secreted by M2 macrophages and promote tumor formation and proliferation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe secretome-conditioned M2 macrophages (H838\u0026thinsp;+\u0026thinsp;IFNg\u0026thinsp;+\u0026thinsp;Aspirin) were found to be more similar to the M2c subtype than the M2a subtype.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eRNA sequencing (RNA-seq) analysis was conducted for both experimental RNA samples and publicly available literature datasets using a Nextflow pipeline. Cluster analysis was carried out to better understand hierarchical linkages, and dendrograms were utilized to assist in determining which groups were most similar. According to the hierarchical clustering dendrograms, it indicated that the clusters of M2 macrophages maintained in cancer secretomes generated by H838 differ from those cultured in secretomes obtained from HCC827 (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFollowing z-score normalization, gene lists curated based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database were analyzed separately. Hematopoietic Cell Lineage (HCL) with 69 overlapping genes out of 100 (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eA) and Antigen Processing and Presentation (APP) with 52 overlapping genes out of 81 were identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eB). Euclidean distance-based visualizations of gene expression levels were created for these groups using logarithmic transformations. Furthermore, heatmap representations were generated by normalizing the genes corresponding to the M1 and M2 macrophage markers identified in the literature using z-scores (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eC-D).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe also examined how comparable the M2 macrophages in our study were to those in the GEO data set GSE227737 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In that set, transcript studies were also performed on M2 macrophages differentiated from PBMC using RNA-Seq data. Distances between the M0, M2a, and M2c groups were calculated based on the filtered RNA-seq data (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). The calculated distances were 0.125874 for M0, 0.1201646 for M2a, and 0.1100931 for M2c. M2-polarized macrophages cultured with the secretome condition of (H838\u0026thinsp;+\u0026thinsp;IFNg\u0026thinsp;+\u0026thinsp;Aspirin) were shown to shift from the M2a subtype to the M2c.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBased on these results, the M2c group was selected for further analysis using Weighted Gene Co-expression Network Analysis (WGCNA). This analysis included variance stabilization using varianceStabilizingTransformation (set to 0.95), determination of the soft threshold with pickSoftThreshold, visualization of dendrograms and module assignments using plotDendroAndColors, and calculation of the topological overlap matrix (TOM) with TOMsimilarityFromExpr. Two gene modules, Green and Red, were identified based on the WGCNA results (Suppl. Figure\u0026nbsp;2 \u0026amp; Suppl. Table\u0026nbsp;1). For M2 macrophages established under the secretome condition (H838\u0026thinsp;+\u0026thinsp;IFNg\u0026thinsp;+\u0026thinsp;Aspirin), genes exhibiting a profile similar to M2c were listed to indicate genes (Suppl. Table\u0026nbsp;1) involved in shifting the subtype from M2a to M2c.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMutation-induced EGFR activation in tumor cells enhances PD-L1 expression and favors T cell apoptosis and immunological evasion. EGFR-TKIs increase the number of CD8\u003csup\u003e+\u003c/sup\u003e T cells and dendritic cells, eliminate FOXP3\u003csup\u003e+\u003c/sup\u003e Tregs, block the polarization phenotype of M2 macrophages, and improve the presentation of MHC class I and II antigens in response to IFNg [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Compared to PD-L1-high tumors, aspirin use after diagnosis has been also associated with a significantly decreased mortality risk for colorectal cancer in PD-L1-low tumors. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. We used conditioned media secreted from both EGFR mutant and non-EGFR mutant cells to perform secretome-mediated regulation of M2 polarized macrophages. PD-L1 surface expression, either endogenous or induced by IFN-gamma, was followed, and the impact of aspirin treatment on PD-L1 expression has been assessed at the protein level.\u003c/p\u003e\u003cp\u003eAspirin irreversibly inhibits the enzymes COX-1 and COX-2, which are required for PGE2 production [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The significant positive correlation on the PD-L1 expression in non-EGFR mutants suggests that it may play a role in aspirin sensitivity. Therefore, modulation of exogenous rather than endogenous PD-L1 expression is thought to alter the tumor microenvironment and especially macrophage plasticity in cancer cell secretome. These results imply that aspirin therapy resistance may be caused by activation of the PD-L1 immune checkpoint pathway, which can be reversed by immune checkpoint inhibitors. According to our study, aspirin treatment significantly increased the expression of PD-L1 in EGFR mutant lung cancer cells. Nevertheless, non-mutant IFN-gamma-stimulated cells did not exhibit an increase in PD-L1 expression in response to aspirin treatment. One of the consequences of aspirin resistance in EGFR mutant non-small cell lung cancer, as indicated by these data, is an increase in PD-L1 expression. Nevertheless, studies have demonstrated that aspirin dramatically reduced PD-L1 expression at both the mRNA and protein levels in non-EGFR-mutant lung cancer cells (A549 and H1299). Aspirin's blockade of TAZ, the transcriptional coactivator of the PD-L1 promoter, was linked to this reduction in PD-L1 expression [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Consequently, it is mechanically important to investigate the PD-L1 transcriptional regulators in aspirin-resistant cancer cells. The H838 cell line that we employed in our studies is derived from NSCLC. However, NSCLC cells that belong to distinct subclasses may respond differently to aspirin due to histological subclassification, such as H1299, large cell carcinoma [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eM2-polarized macrophages are classified into four subgroups: M2a, M2b, M2c, and M2d. IL4 or IL13 stimulates M2a macrophages, leading to increased production of IL10, TGFβ, CCL17, CCL18, and CCL22 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. These macrophages boost endocytotic activity, which promotes cell proliferation and tissue repair [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. We polarized macrophages from M0 macrophages with IL4 and IL13 cytokines, and M1 marker CD38 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] and M2 marker CD209 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] expression in M2-polarized macrophages were analyzed; CD11c, a monocyte/macrophage marker, was substantially higher in differentiated polarized macrophages. Furthermore, CD38 expression was observed to be considerably higher in M2 + (H838 \u0026amp; IFNg)\u003csub\u003esecretome\u003c/sub\u003e macrophages compared to M2 macrophages cultured with H838 secretome but not stimulated with IFNg. Also, CXCL10 was significantly lower in M2 macrophages cultured in the presence of aspirin-treated IFNg-induced H838 secretome, based on our analysis of the cytokine profiles of M2 macrophages, specifically M2a, which we differentiated through cytokine stimulation using IL4 and IL13. This implies that secretomes originating from cancer cells may influence the factors released by M2a polarized macrophages. M2b and M2c subtypes, on the other hand, are referred to as \"regulatory macrophages\" because they help maintain or restore cellular homeostasis. IL12, IL23, and TNFα activate M2b macrophages, which then release IL1β, TNFα, IL6, and IL10. M2c macrophages are activated by IL10, TGFβ, or glucocorticoids, resulting in increased production of IL10, CCL16, and CCL18 [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIt is emphasized that increased STAT6 signaling results in PPARγ-mediated macrophage programming [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], which contributes to increased efferocytosis and inflammation resolution [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. STAT6 and PPARγ are also referred to as M2a macrophage markers. In our study, the decrease in the expression of STAT6 and PPARG transcription factors at the gene level in M2 + (H838\u0026thinsp;+\u0026thinsp;IFNg\u0026thinsp;+\u0026thinsp;Aspirin)\u003csub\u003esecretome\u003c/sub\u003e macrophages compared to M2 macrophages cultured with H838\u003csub\u003esecretome\u003c/sub\u003e that was not stimulated with IFNg draws attention to the fact that this condition modulates macrophage plasticity. When the gene expression profile of M1 macrophage markers was examined, it revealed that they were expressed higher in M2 + (H838\u0026thinsp;+\u0026thinsp;IFNg\u0026thinsp;+\u0026thinsp;Aspirin)\u003csub\u003esecretome\u003c/sub\u003e macrophages than in macrophages maintained with other H838-derived secretomes. In addition, based on our transcriptomic analyses, CD38 expression showed an increased pattern in M2 macrophages cultured in the presence of (H838\u0026thinsp;+\u0026thinsp;IFNg)\u003csub\u003esecretome\u003c/sub\u003e and (H838\u0026thinsp;+\u0026thinsp;IFNg\u0026thinsp;+\u0026thinsp;Aspirin)\u003csub\u003esecretome\u003c/sub\u003e.\u003c/p\u003e\u003cp\u003eWe noticed that M2-polarized macrophages cultured in the presence of IFNg-stimulated and aspirin-treated IFNg-induced secretome had higher levels of CD38 surface expression than their counterparts. As a result, our findings highlight the ability of both M2 plasticity and EGFR non-mutant conditional secretomes to influence the phenotype of the M2 macrophage subtype. Furthermore, inhibiting PPAR-γ with an antagonist leads to differentiation of M2c-like cells. When macrophages are differentiated with IL-4 (M2a conditions), PPAR gamma agonist changes the polarization between M2a (CD206\u003csup\u003e+\u003c/sup\u003e CD209\u003csup\u003e+\u003c/sup\u003e CD163\u003csup\u003e\u0026minus;\u003c/sup\u003e MerTK\u003csup\u003e\u0026minus;\u003c/sup\u003e) and M2c (CD206\u003csup\u003ehigh\u003c/sup\u003e CD209\u003csup\u003e\u0026minus;\u003c/sup\u003e CD163\u003csup\u003e+\u003c/sup\u003e MerTK\u003csup\u003e+\u003c/sup\u003e) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn our study, we additionally investigated the effect of aspirin on modulation of PD-L1 protein expression in EGFR mutant and non-mutant cancer cells. The combined effects of osimertinib and aspirin treatment have been examined \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e in osimertinib-resistant non-small cell lung cancer cell lines. The results demonstrated the combination of osimertinib and aspirin had strong anti-proliferative and pro-apoptotic effects in osimertinib-resistant cancer cells by increasing Bim expression and inhibiting phosphorylation of the Akt/FoxO3a signaling component [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. For these reasons, assessing aspirin resistance and PD-L1 levels, as well as M2 macrophage infiltration in the non-small cell lung cancer microenvironment, will provide the basis for understanding aspirin resistance mechanisms and developing personalized therapeutics to suppress the immunosuppressive immune response.\u003c/p\u003e\u003cp\u003eIt has been reported that CD8 expression is reduced while M2 macrophages (CD68\u003csup\u003e+\u003c/sup\u003e and CD206\u003csup\u003e+\u003c/sup\u003e macrophages) are increased in the tissues of patients resistant to tyrosine kinase inhibitors (TKIs), particularly individuals resistant to EGFR-TKIs; thus, an immunosuppressive niche forms in TKI-resistant non-small cell lung cancer tissues [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In experimental assays in which macrophages and cancer cells were co-cultured, it was established that M2 macrophages inhibited the anticancer effect of EGFR-TKIs, whereas M1 macrophages increased the antitumor activity. During M2a polarization, secretome-containing conditioned media produced from mesenchymal stem cells greatly increased the expression of M2a-, M2b-, and M2c-specific genes and proteins, and macrophages secreted a substantial amount of IL10. Similarly, M2b/M2c-specific marker expressions were also higher in M2a macrophages established with these secretomes (preMSC-CM), revealing that they help to repolarize M2a-like macrophages to M2b/M2c subtypes [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe distinctive expression patterns of M2-polarized macrophages have significance for macrophage-targeting treatment approaches. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Strategies that combine aspirin and receptor tyrosine kinase inhibitors, aspirin resistance and PD-L1 levels [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], M2 macrophage infiltration in the microenvironment of non-small cell lung cancer, and molecular classification of M2 macrophage subtypes have predictive value for the prognosis of the disease [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. According to our results, aspirin treatment of EGFR non-mutant cancer cell-derived secretomes alters the molecular characteristics of M2 macrophages, thus changing their plasticity. As a result, mutation type, PD-L1 expression level, and immune phenotyping of tumor-associated M2 macrophages will assist in developing non-small cell lung cancer therapy regimens consisting of EGFR inhibitors and aspirin.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003eEthical approval:\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Experiments derived from PBMC samples obtained from healthy donors were approved by the non-invasive Ethics Committee (Approval: GO 23/82, Hacettepe University, Ankara, T\u0026uuml;rkiye). Written informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eThis work has been supported by the Scientific Research Projects Coordination Unit of Hacettepe University under grant number TSA-2021-19475.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eN.U. wrote the main manuscript and prepared figures. S.U., E.T., and E.D.Y. prepared figures. Y.K. and G.E. edited the manuscript. All authors reviewed the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eThis work has been supported by the Scientific Research Projects Coordination Unit of Hacettepe University under grant number TSA-2021-19475.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe GEO data set GSE227737 was used for the bioinformatic analysis.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eT. Ma, J. 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Han, Genes Dis 11, 101086 (2024) doi: 10.1016/j.gendis.2023.101086\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"inflammation-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"inre","sideBox":"Learn more about [Inflammation Research](http://link.springer.com/journal/11)","snPcode":"11","submissionUrl":"https://submission.nature.com/new-submission/11/3","title":"Inflammation Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"PD-L1, aspirin, non-small cell lung cancer, macrophage, secretome","lastPublishedDoi":"10.21203/rs.3.rs-6954264/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6954264/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAlthough aspirin is one of the best characterized drugs for the therapeutic effects on coagulation and inflammation, there are clues that it may also have a significant impact on cancer immunity. In this study, IFNg, a pro-inflammatory cytokine, has been demonstrated to increase the protein expression of PD-L1 in non-small cell lung carcinoma cells. In the molecular modeling of stimulated and/or aspirin-treated cancer secretome and macrophage interaction, CD38 (M1 macrophage marker) and CD209 (M2 macrophage marker) expressions confirmed that peripheral blood mononuclear cells differentiated into M1 or M2 macrophages afterwards polarization. Transcriptomic profiling was performed after 48 hours of culture with differentiated M2-polarized macrophages in the presence of lung cancer cell secretomes. In contrast to the EGFR mutant aspirin-treated HCC827 cell line, the findings revealed that factors produced by the non-EGFR mutant aspirin-treated IFNg-induced H838 cancer cell secretome can alter M2 macrophage dynamics. Furthermore, significant patterns were obtained in gene expression profiles related to \u0026ldquo;Hematopoietic Cell Lineage\u0026rdquo; and \u0026ldquo;Antigen Processing and Presentation\u0026rdquo; between groups in M2-polarized macrophages established with these secretomes. However, aspirin treatment had different effects on cancer cell lines that expressed endogenous and induced PD-L1. As a result, flow cytometry analysis demonstrated that administering aspirin to HCC827 cancer cells boosted the expression of PD-L1 on their surface. Analysis of EGFR mutations, aspirin resistance, and PD-L1 levels, as well as M2 macrophage infiltration in the non-small cell lung cancer microenvironment and immune phenotyping of M2 macrophage subtypes, will assist in developing lung cancer therapy approaches that combine EGFR inhibitors and aspirin.\u003c/p\u003e","manuscriptTitle":"The impact of aspirin on PD-L1 expression and alteration of M2 polarization in non-small cell lung cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-11 10:30:42","doi":"10.21203/rs.3.rs-6954264/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-16T13:55:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-14T21:46:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"290241624655704609384977540288906313480","date":"2025-07-14T13:37:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-06T11:51:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-23T09:27:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-23T09:25:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Inflammation Research","date":"2025-06-23T08:01:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"inflammation-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"inre","sideBox":"Learn more about [Inflammation Research](http://link.springer.com/journal/11)","snPcode":"11","submissionUrl":"https://submission.nature.com/new-submission/11/3","title":"Inflammation Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"bd026006-6bd4-4bea-a4cc-ceee7749c6ae","owner":[],"postedDate":"July 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-22T15:58:50+00:00","versionOfRecord":{"articleIdentity":"rs-6954264","link":"https://doi.org/10.1007/s00011-025-02091-8","journal":{"identity":"inflammation-research","isVorOnly":false,"title":"Inflammation Research"},"publishedOn":"2025-09-16 15:57:09","publishedOnDateReadable":"September 16th, 2025"},"versionCreatedAt":"2025-07-11 10:30:42","video":"","vorDoi":"10.1007/s00011-025-02091-8","vorDoiUrl":"https://doi.org/10.1007/s00011-025-02091-8","workflowStages":[]},"version":"v1","identity":"rs-6954264","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6954264","identity":"rs-6954264","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}