Tumor-distant pulmonary immune landscapes are associated with postoperative outcomes in non-small cell lung cancer

Introduction

Antitumor immunity in lung cancer is regulated not only within the primary tumor microenvironment but also by immune cells distributed in the surrounding lung parenchyma (1,2). Antigen-presenting myeloid cells, including dendritic cells (DCs) and macrophages, play important roles in coordinating innate and adaptive immunity in peripheral tissues, including the lung. However, although these antigen-presenting cells have been extensively studied within tumors and lymphoid organs (3-5), their clinical significance in non-tumorous lung tissue—particularly at sites distant from the primary lesion—remains incompletely understood.

Dendritic cell-specific intercellular adhesion molecule-3-grabbing nonintegrin (DC-SIGN; CD209) is expressed by subsets of DCs as well as certain macrophage and monocyte-derived myeloid populations and is involved in antigen capture and immune regulation (6,7). CD169 marks a specialized population of macrophages that capture lymph-borne antigens and has been associated with antitumor immune responses and prognosis in regional lymph nodes (8-15). However, the distribution and clinical relevance of these antigen-presenting cells within non-tumorous lung parenchyma remain poorly characterized.

The lung parenchyma constitutes an immunologically active compartment harboring diverse resident and interstitial immune cells. Recent studies have demonstrated substantial inter-individual heterogeneity in immune composition within normal lung tissue and highlighted the prognostic relevance of immune features beyond the tumor itself (16-19). Previous morphometrical studies, including our recent work, have identified focal immune cell aggregates within the pulmonary interstitium, particularly along peripheral bronchovascular structures, suggesting localized sites of antigen presentation in the lung parenchyma (17). However, the clinical relevance of antigen-presenting cells within these interstitial immune aggregates remains unclear. These observations suggest that immune cell profiles in tumor-distant lung parenchyma may reflect inter-individual differences in pulmonary immune status.

Previous anatomical and immunohistochemical studies of regional lymph nodes have demonstrated spatial differences in immune cell distribution between proximal and distal nodes along lymphatic pathways (20-22). These findings suggest that immune landscapes located further from the primary tumor may reflect host-related immune characteristics rather than direct tumor-driven effects. Based on this concept, we focused on tumor-distant lung parenchyma as a compartment potentially less influenced by immediate tumor-associated factors.

In the present study, we quantified hotspot-based counts of DC-SIGN-positive cells and CD169-positive macrophages in lung tissue obtained near and distant from primary lung cancer lesions. Tumor-near specimens were analyzed as an internal spatial comparator to evaluate immune cell accumulation potentially influenced by local tumor-associated or inflammatory factors, whereas tumor-distant specimens were examined as a compartment potentially reflecting broader pulmonary immune heterogeneity. We present this article in accordance with the STROBE reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0474/rc).

Methods

Study design and patient selection

This retrospective observational study included patients who underwent curative-intent lobectomy for non-small cell lung cancer (NSCLC) at Kagoshima University Hospital between January 2011 and December 2016. Patients were eligible if paired lung tissue specimens obtained from both tumor-near and tumor-distant sites within the resected lobe were available for immunohistochemical evaluation.

Patients with pathological evidence of pleural invasion or pulmonary metastasis were excluded because these conditions could influence the pulmonary immune microenvironment. In particular, pleural invasion may alter subpleural lymphatic pathways along the lung surface, whereas pulmonary metastasis may reflect broader intrapulmonary dissemination through lymphatic or vascular routes. Other exclusion criteria included death within 30 days after surgery, active pulmonary infection at the time of surgery, incomplete resection, receipt of neoadjuvant therapy, and insufficient tissue specimens or clinical follow-up data for immunohistochemical or outcome evaluation. Cases with missing clinicopathological, immunohistochemical, or follow-up data required for the analyses were excluded from the study cohort.

Clinical, pathological, and follow-up data were obtained from medical records and pathology reports. Tumor staging and pathological evaluation were performed according to the seventh edition of the Union for International Cancer Control tumor-node-metastasis (TNM) classification, as proposed by the International Association for the Study of Lung Cancer (23). Recurrence was defined based on radiological and/or histological evidence during postoperative follow-up.

Study cohort

Among the eligible patients, 40 patients were included in the final analysis. All analyzed specimens were derived from the same lobe as the primary tumor and were processed using identical histological and immunohistochemical protocols. Because of the exploratory nature of this retrospective study and the limited availability of paired tumor-near and tumor-distant tissue specimens suitable for immunohistochemical analysis, no formal sample size calculation was performed. This study was a retrospective analysis using existing surgically resected tissue specimens and de-identified clinical information. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Institutional Review Board (IRB) of Kagoshima University Graduate School of Medical and Dental Sciences (protocol code: 210198epi; approval date: 13 December 2021). In accordance with the IRB’s determination and institutional policy for retrospective studies using existing materials, the requirement for written informed consent was waived. Instead, we implemented an opt-out procedure by publicly disclosing the study information online and providing potential participants (or their families) with the opportunity to decline participation.

Tissue sampling and definition of tumor-near and tumor-distant specimens

From each patient, lung tissue specimens were obtained from two predefined sites within the resected lobe. Tumor-near specimens were sampled from alveolar lung tissue adjacent to the primary tumor, typically within 5–10 mm from the tumor margin, while avoiding direct tumor infiltration. Tumor-distant specimens were sampled from macroscopically normal lung parenchyma at sites over 50 mm distant from the tumor margin, and no histological evidence of tumor involvement was identified in these specimens. All specimens consisted predominantly of alveolar regions and did not include gross tumor tissue. Formalin-fixed, paraffin-embedded tissue blocks were prepared according to standard pathological procedures.

Immunohistochemistry

Formalin-fixed, paraffin-embedded lung tissue blocks were sectioned at 4 µm thickness. Immunohistochemical staining was performed using a standard horseradish peroxidase-based method. After deparaffinization and rehydration, antigen retrieval was carried out using a PT Link system (Dako, Glostrup, Denmark) under antibody-specific conditions. Sections were incubated with a mouse monoclonal antibody against DC-SIGN (CD209; 1:200 dilution; Abcam, Cambridge, UK; high-pH antigen retrieval) or a rabbit monoclonal antibody against CD169 (1:100 dilution; Abcam; low-pH antigen retrieval), followed by species-appropriate secondary antibodies. Immunoreactivity was visualized with 3,3'-diaminobenzidine, and sections were counterstained with hematoxylin. Negative controls were prepared by omitting the primary antibody.

In the present study, immunohistochemical evaluation was focused on DC-SIGN-positive cells and CD169-positive macrophages as representative antigen-presenting cell populations within the lung interstitium. DC-SIGN-positive cells were interpreted as histologically identifiable interstitial antigen-presenting cells rather than lineage-defined DC subsets, because DC-SIGN may also be expressed by subsets of macrophages and monocyte-derived myeloid cells. No multiplex immunostaining or co-staining with lineage-specific markers was performed in the present study. CD169 immunostaining was used to identify a distinct subset of specialized macrophages for comparative analysis. For specimens showing no DC-SIGN-positive cells in tumor-distant aggregates, additional staining was performed three times with positive and negative controls, including mediastinal lymph nodes from the same patients as internal positive controls, to rule out potential technical staining artifacts. These repeated analyses confirmed the absence of DC-SIGN-positive cells.

Quantitative evaluation of immune cells (hotspot analysis)

Quantitative evaluation of DC-SIGN-positive cells and CD169-positive macrophages was performed using a hotspot counting method. The analyzed hotspots were considered to correspond to previously described pulmonary interstitial immune cell aggregates along peripheral bronchovascular structures, as identified in our prior morphometrical study (17). Entire tissue sections were first scanned at low magnification to identify areas with the highest number of immunopositive cells. A single hotspot, defined as the area containing the greatest number of immunopositive cells, was selected for each section. The hotspot was usually found along peripheral parts of the bronchopulmonary tree but was sometimes seen in the interalveolar septum (Figure 1). When the hotspot was found in the subpleural area, the next-greatest spot was chosen because subpleural lymphatic cell aggregation likely receives interlobar lymph from the cancer lesion. Cell counts were performed under a ×20 objective lens within a predefined rectangular field measuring approximately 0.6 mm × 0.4 mm. The same procedure was applied independently to tumor-near and tumor-distant specimens. Cell counts were expressed as the number of immunopositive cells per hotspot field. All evaluations were independently performed by two observers who were blinded to clinicopathological data and clinical outcomes. Discordant or borderline cases were reviewed jointly, and final values were determined by consensus. Formal inter-observer reproducibility metrics, such as the intraclass correlation coefficient, were not calculated.

Figure 1 Representative immunohistochemical staining of DC-SIGN and CD169 in tumor-near and tumor-distant non-tumorous lung tissue. (A,C,E,G) Low-power views and (B,D,F,H) high-power views of DC-SIGN and CD169 staining in tumor-near and tumor-distant lung tissue. DC-SIGN-positive cells and CD169-positive macrophages were observed within alveolar interstitial and perivascular regions. Arrows indicate representative immunoreactive cells. Scale bars, 0.1 mm. Ar, arteriole; Av, alveolus; Br, bronchiole; DC-SIGN, dendritic cell-specific intercellular adhesion molecule-3-grabbing nonintegrin or CD209.

Definition of clinicopathological groups and cutoff values

For categorical analyses, clinicopathological variables were dichotomized using clinically relevant cutoff values. Patient age was categorized using a cutoff of 70 years, and tumor size was categorized using a cutoff of 30 mm, corresponding to a clinically relevant threshold in tumor staging. Smoking exposure was evaluated using the Brinkman Index and analyzed as a continuous variable.

For immune cell analyses, DC-SIGN-positive cells and CD169-positive macrophages were stratified into high and low groups separately for tumor-near and tumor-distant specimens based on the median cell count of each parameter. Because immune cell distributions differed substantially between tumor-near and tumor-distant compartments, compartment-specific median values were used as cutoff values. These groupings were used for survival analyses and comparisons with clinicopathological variables, as detailed in the Tables S1,S2.

Statistical analysis

Continuous variables are presented as medians with interquartile ranges (IQRs), and categorical variables as counts and percentages. Comparisons between tumor-near and tumor-distant specimens were performed using the Wilcoxon signed-rank test. Between-group comparisons were conducted using the Mann-Whitney U test, as appropriate. Fisher’s exact test was used for comparisons of categorical variables between groups when appropriate. Correlations between smoking exposure, expressed as the Brinkman index, and immune cell counts were evaluated using Spearman’s rank correlation coefficient. Recurrence-free survival (RFS) was defined as the interval from surgical resection to the first documented recurrence or last follow-up without recurrence. RFS was estimated using the Kaplan-Meier method, and survival curves were compared using the log-rank test. The median follow-up period was calculated using the reverse Kaplan-Meier method. Multivariate analyses for RFS were performed using Cox proportional hazards models to account for the limited number of recurrence events. To further reduce the risk of overfitting and confounding due to the limited number of events, a propensity score (PS) was calculated using clinicopathological variables identified as prognostically relevant. Covariates were selected based on univariate analyses. When a variable was evaluated as the primary factor of interest, other variables that showed statistical significance in univariate analyses (P<0.05) were included as covariates, excluding the variable under evaluation. For variables that were not significant in univariate analyses, PS-adjusted Cox proportional hazards models were constructed, in which the PS was included as an adjusting covariate. These models were adjusted for distant DC-SIGN expression, tumor differentiation, and lymph node metastasis, which were identified as major prognostic factors. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated. A two-sided P value <0.05 was considered statistically significant. All statistical analyses were performed using IBM SPSS Statistics software (IBM Corp., Armonk, NY, USA).

Results

Patient characteristics

A total of 40 patients with paired tumor-near and tumor-distant lung tissue specimens were included (Table 1). The median age was 66.0 years (IQR, 61.0–72.3 years), and 60.0% were male. A history of smoking was present in 57.5% of patients. Adenocarcinoma was the predominant histological subtype (87.5%). Most patients had early-stage disease (stage I, 70.0%), although pathological lymph node metastasis was observed in 27.5%. During a median follow-up of 117.2 months, 13 patients (32.5%) experienced recurrence.

Overview of antigen-presenting cell counts in non-tumorous lung parenchyma

Representative immunohistochemical images of DC-SIGN and CD169 expression in non-tumorous lung parenchyma are shown in Figure 1. In both tumor-near and tumor-distant lung tissue, DC-SIGN-positive cells and CD169-positive macrophages were observed within alveolar interstitial and perivascular regions. Representative low-power and high-power views show hotspot areas containing immunoreactive cells in both spatial compartments. No organized lymphoid architecture was identified. Quantitative comparison of immune cell counts between tumor-near and tumor-distant regions was therefore performed using hotspot-based cell counting, as described below.

Hotspot-based differences in immune cell counts between tumor-near and tumor-distant lung tissue

Before comparing spatial differences, hotspot fields were defined as areas with the highest number of immunoreactive cells within each section identified by systematic scanning. In these fields, the number of DC-SIGN-positive cells ranged from 0 to 132 cells per field in tumor-distant lung tissue and from 0 to 189 cells per field in tumor-near lung tissue. Similarly, the number of CD169-positive macrophages ranged from 1 to 133 cells per field in tumor-distant regions and from 2 to 281 cells per field in tumor-near regions. Thus, absolute cell counts varied widely at the level of individual hotspots in both tumor-distant and tumor-near lung tissue, including fields in which no DC-SIGN-positive cells were detected.

Differences in antigen-presenting cell hotspot counts between tumor-near and tumor-distant lung tissue were examined. Quantitative hotspot analysis demonstrated that both DC-SIGN-positive cells and CD169-positive macrophages were significantly more abundant in tumor-near specimens than in tumor-distant specimens [DC-SIGN: median (IQR), 29.5 (4.8–71.3) vs. 7.5 (2.0–26.3), P<0.001; CD169: 45.5 (19.5–86.0) vs. 19.5 (7.8–39.3), P=0.004; Wilcoxon signed-rank test; Figure 2A,2B]. These findings indicate a clear difference in antigen-presenting cell abundance between tumor-near and tumor-distant lung tissue. Correlation analyses demonstrated moderate to strong associations between DC-SIGN-positive cells and CD169-positive macrophages, supporting coordinated immune cell distribution in the lung parenchyma (Figure S1). These correlations suggest that inter-individual differences in antigen-presenting cell counts are consistently observed across both spatial regions and cell types.

Figure 2 Differences in DC-SIGN-positive cell and CD169-positive macrophage counts between tumor-near and tumor-distant specimens. (A) Comparison of DC-SIGN-positive cell counts between tumor-near and tumor-distant lung specimens. (B) Comparison of CD169-positive macrophage counts between tumor-near and tumor-distant lung specimens. Cell counts were quantified by hotspot counting in paired tumor-near and tumor-distant specimens obtained from the same patients (n=40). Data are presented as median values with IQR. Comparisons between paired groups were performed using the Wilcoxon signed-rank test. DC-SIGN-positive cells and CD169-positive macrophages were both significantly more abundant in tumor-near specimens than in tumor-distant specimens (DC-SIGN, P<0.001; CD169, P=0.004). **, P<0.01; ***, P<0.001. DC-SIGN, dendritic cell-specific intercellular adhesion molecule-3-grabbing nonintegrin or CD209; IQR, interquartile range.

Prognostic impact of immune cell counts

We next investigated the association between immune cell counts and postoperative recurrence. Patients were stratified into high and low groups based on the median immune cell counts in tumor-near and tumor-distant compartments, respectively. Kaplan-Meier analysis showed that patients with a high number of DC-SIGN-positive cells in tumor-distant specimens experienced significantly better RFS than those with low counts (log-rank P=0.02; Figure 3A, Table 2). In contrast, DC-SIGN-positive cell counts in tumor-near specimens were not significantly associated with RFS (Table 2).

Figure 3 Prognostic impact of DC-SIGN-positive cell counts in tumor-distant specimens and its association with clinicopathological factors. (A) Kaplan-Meier analysis of recurrence-free survival according to DC-SIGN-positive cell counts in tumor-distant specimens. Patients were stratified into high and low DC-SIGN groups based on the median value (n=20 per group). (B) Box-and-whisker plot showing the distribution of DC-SIGN-positive cell counts in tumor-distant specimens according to pathological stage (stage I vs. stage II–III). (C) Box-and-whisker plot showing the distribution of DC-SIGN-positive cell counts in tumor-distant specimens according to lymph node metastasis status (with vs. without LN metastasis). Survival curves were compared using the log-rank test, and group comparisons were performed using the Mann-Whitney U test. Tumor-distant DC-SIGN-positive cell counts were significantly associated with recurrence-free survival (P=0.02). In addition, DC-SIGN-positive cell counts in tumor-distant specimens showed associations with pathological stage (P=0.042) and a trend with lymph node metastasis (P=0.07). *, P<0.05. DC-SIGN, dendritic cell-specific intercellular adhesion molecule-3-grabbing nonintegrin or CD209; LN meta, lymph node metastasis.

When tumor-distant DC-SIGN-positive cell counts were compared according to pathological stage, patients with stage II–III disease showed significantly lower counts than those with stage I disease (P=0.042; Figure 3B, Table S1). In addition, tumor-distant DC-SIGN-positive cell counts tended to be lower in patients with lymph node metastasis than in those without nodal involvement, although this difference did not reach statistical significance (P=0.07; Figure 3C, Table S1). In addition, postoperative adjuvant therapy was administered in 19 patients (47.5%), and no significant difference in its frequency was observed between the high and low tumor-distant DC-SIGN groups (50.0% vs. 45.0%, P>0.99).

In contrast, CD169-positive macrophage counts in either tumor-near or tumor-distant specimens were not significantly associated with RFS (Table 2).

Univariate and PS-adjusted analyses for RFS

Table 2 summarizes the results of univariate log-rank analyses and subsequent PS-adjusted Cox proportional hazards analyses for RFS. In univariate analyses using the log-rank test, histological differentiation (G1 vs. G2–3; P=0.01), lymph node metastasis (P<0.001), and fewer DC-SIGN-positive cells in tumor-distant specimens (P=0.02) were significantly associated with RFS.

Subsequent PS-adjusted Cox proportional hazards analyses demonstrated that histological differentiation (adjusted HR, 0.278; 95% CI: 0.084–0.919; P=0.04) and lymph node metastasis (adjusted HR, 4.191; 95% CI: 1.319–13.313; P=0.02) remained independently associated with RFS. In contrast, tumor-distant DC-SIGN-positive cell counts were no longer significantly associated with RFS after PS adjustment (adjusted HR, 0.967; 95% CI: 0.924–1.013; P=0.16).

Association between immune cell counts and clinicopathological variables, including smoking exposure

Associations between immune cell counts and clinicopathological variables were examined for DC-SIGN-positive cells and CD169-positive macrophages. The results are summarized in Tables S1,S2, respectively.

For DC-SIGN-positive cells (Table S1), tumor-near cell counts showed significant associations with sex and smoking status, with higher counts observed in male patients than in female patients (P=0.02) and in ever smokers compared with never smokers (P=0.042). In contrast, tumor-distant DC-SIGN-positive cell counts were significantly associated with pathological stage (P=0.042) and showed a trend toward association with lymph node metastasis (P=0.07), consistent with the results shown in Figure 3.

To further characterize the impact of smoking exposure, correlations between immune cell counts and the Brinkman index were evaluated (Figure S2). DC-SIGN-positive cell counts showed a significant positive correlation with smoking exposure in tumor-near specimens (Spearman’s ρ=0.391, P=0.01; Figure S2A), whereas no significant correlation was observed in tumor-distant specimens (ρ=0.223, P=0.17; Figure S2B).

For CD169-positive macrophages (Table S2), tumor-near cell counts showed significant associations with sex and smoking status, with higher counts in male patients than in female patients (P=0.006) and in ever smokers compared with never smokers (P=0.01). Correlation analysis using the Brinkman index demonstrated significant positive correlations with smoking exposure in both tumor-near and tumor-distant specimens (tumor-near: ρ=0.419, P=0.007; tumor-distant: ρ=0.350, P=0.03; Figure S2C,S2D).

Discussion

The present study suggests that inter-individual variability in hotspot-based cell counts, particularly in tumor-distant lung tissue, may have distinct clinical implications. Although both DC-SIGN-positive cells and CD169-positive macrophages were more abundant in tumor-near lung tissue, only tumor-distant DC-SIGN-positive cell counts exhibited substantial inter-individual variability that was associated with postoperative recurrence and unfavorable pathological characteristics. Rather than the magnitude of the near-distant difference within each patient, the present findings indicate that inter-individual variability in tumor-distant immune cell counts itself was associated with clinical outcomes.

Importantly, a higher number of DC-SIGN-positive cells in tumor-distant, macroscopically and histologically tumor-free lung parenchyma was associated with favorable RFS, suggesting that immune features beyond the primary lesion may reflect inter-individual differences in pulmonary immune status. Notably, tumor-distant DC-SIGN-positive cell counts were lower in patients with advanced pathological stage and in those with lymph node metastasis. These findings raise the possibility that inter-individual variability in pulmonary immune microenvironments, as well as differential responsiveness to tumor-related stimuli, may influence the biological behavior of lung cancer, including its propensity for lymph node metastasis. Although tumor-distant DC-SIGN-positive cell counts were significantly associated with RFS in univariate analysis, this association did not remain independent after multivariate adjustment. This likely reflects the close interrelationship between tumor-distant immune features and established pathological factors such as tumor differentiation and nodal involvement. In this context, tumor-distant DC-SIGN-positive cell counts may capture aspects of host-related immune background that are partly embedded within conventional staging parameters. Consistent with recent evidence demonstrating substantial inter-individual heterogeneity in normal lung immune composition and the prognostic relevance of immune features different from the tumor itself (18,19), the present findings are compatible with the possibility that inter-individual differences in pulmonary immune landscapes may be linked to more aggressive tumor phenotypes. This wide inter-individual variability, including cases with absent DC-SIGN-positive cells, supports the notion that tumor-distant immune landscapes differ substantially among patients. From an anatomical perspective, direct lymphatic drainage from the primary lesion to the present distant specimens appears limited (16,17). Therefore, although indirect or systemic influences cannot be entirely excluded, the observed inter-individual variability in tumor-distant immune cell counts suggests contributions from host-related immune characteristics. Tumor-associated effects may also partly influence these findings.

An important question raised by our findings is whether DC-SIGN-positive cells in tumor-distant lung tissue are shaped by tumor-derived influences or reflect pre-existing host immune characteristics. One possible interpretation is that DC-SIGN-positive cell counts in tumor-distant lung parenchyma may partly reflect underlying pulmonary immune status rather than solely representing local tumor-related antigen exposure. In this context, reduced DC-SIGN-positive cell counts may reflect altered pulmonary immune microenvironments associated with more aggressive tumor behavior, consistent with our previous observation that DC-SIGN expression differs across distinct anatomical compartments with different immune microenvironments (24,25). In tumor-near regions, immune cell accumulation may occur through direct cell-to-cell contact, exposure to soluble mediators, or local lymphatic flow. In contrast, in tumor-distant lung tissue, antigen exposure may occur through systemic circulation or interlobular vascular pathways, whereas direct lymphatic spread is less likely. The present data do not demonstrate a uniform tumor-driven modulation of DC-SIGN-positive cells across individuals; instead, the marked inter-individual variability observed in tumor-distant immune cell counts aligns with accumulating evidence of substantial heterogeneity in normal lung immune composition and the clinical relevance of immune features beyond the tumor itself (18,19). Taken together, these findings suggest that tumor-distant immune landscapes may reflect a combination of host-related immune characteristics and differential responsiveness to tumor-associated influences, rather than being determined by either factor alone. These considerations indicate that antigen exposure pathways differ qualitatively between tumor-near and tumor-distant compartments, rather than representing a continuous gradient of the same mechanism. Because no pre-tumor baseline or truly tumor-free control lung tissue was available in the present study, these interpretations should be considered hypothesis-generating rather than definitive evidence of pre-existing baseline host immunity.

In contrast, both DC-SIGN-positive cells and CD169-positive macrophages were significantly more abundant in tumor-near lung tissue, yet showed no clear association with RFS. Immune cell counts in tumor-near specimens were strongly influenced by smoking exposure and sex, indicating that local inflammatory stimuli substantially shape immune cell recruitment in this compartment. Notably, the observed sex-related differences were largely attributable to differences in smoking exposure (P<0.001; data not shown). These findings suggest that increased numbers of antigen-presenting cells in tumor-near lung tissue may reflect inflammation-driven accumulation rather than coordinated antitumor immune responses. Although cigarette smoke exposure affects the entire lung, its biological impact is spatially heterogeneous; smoking-related injury, including emphysema and airway inflammatory responses, shows marked regional variation within the lung (26). Lung cancer has been reported to preferentially arise in regions subjected to more intense and sustained inflammatory injury (27). Moreover, smoking induces field-wide epithelial alterations even in histologically normal lung tissue (28). Consistent with this concept, smoking-related chronic lung diseases drive quantitative accumulation of DCs in small airways and alveolar parenchyma, while their maturation and functional polarization may be impaired (16,29,30). Such inflammation-driven remodeling of antigen-presenting cell networks may attenuate the prognostic relevance of immune cell density in tumor-near lung tissue, in contrast to the immune heterogeneity observed in tumor-distant parenchyma.

CD169-positive macrophages showed associations with smoking exposure in the present study, including in tumor-distant lung tissue; however, their counts were not associated with RFS. Adult alveolar macrophages are largely maintained through local self-renewal and generally show low or absent CD169 expression (31), whereas CD169-positive macrophages may represent recruited inflammatory or monocyte-derived populations emerging under pathological conditions (32). Given that CD169-positive macrophages can exert either immunostimulatory or immunosuppressive effects depending on tissue and inflammatory context (33,34), the smoking-associated increase observed here may reflect chronic inflammatory exposure and context-dependent immune remodeling rather than coordinated antitumor immune priming. This interpretation contrasts with the favorable prognostic impact consistently reported for CD169-positive sinus macrophages within regional lymph nodes (9-15), highlighting the compartment-dependent nature of CD169-positive macrophage function across anatomical environments (20-22).

From a biological perspective, the present findings suggest that immune cell counts in tumor-distant lung tissue may reflect aspects of host immune status different from those in the tumor microenvironment. In line with this concept, findings from the JCOG0802/WJOG4607L trial, which demonstrated improved overall survival after segmentectomy compared with standard lobectomy despite a higher incidence of local recurrence at 5- and 7-year follow-up (35,36), suggest that factors beyond local tumor control may contribute to long-term outcomes. One possible interpretation is that preservation of lung parenchyma could help maintain pulmonary immune cell networks, potentially influencing systemic antitumor immune responses. Although this hypothesis remains speculative, it is conceptually consistent with the view that cancer progression may be accompanied by alterations in DC-SIGN-positive immune microenvironments within the lung parenchyma. Preservation of such pulmonary immune landscapes may therefore have potential clinical implications in the era of lung cancer surgery and immunotherapy.

Limitations

Several limitations should be acknowledged, including the retrospective design, limited sample size, lack of functional immune assays, and the absence of multiplex immunostaining or co-staining with lineage-specific markers. Because DC-SIGN is not specific to conventional DCs, the precise lineage identity of DC-SIGN-positive cells could not be determined in the present study. The single-center nature of the cohort may also limit the generalizability of the findings. In addition, immune cell quantification was based on manual hotspot analysis using a single selected field per section, which may be susceptible to selection bias and may not fully capture the spatial heterogeneity of immune cell distribution within the lung parenchyma. Although all evaluations were performed by two blinded observers and finalized by consensus review, formal inter-observer reproducibility metrics, such as the intraclass correlation coefficient, were not available. Whole-slide digital image analysis combined with quantitative reproducibility assessment will be required in future studies to more comprehensively evaluate pulmonary immune landscapes. Molecular profiling data, including EGFR, ALK, KRAS mutation status and programmed death-ligand 1 (PD-L1) expression, were unavailable in most patients because the study cohort was collected between 2011 and 2016, before routine implementation of comprehensive molecular testing in clinical practice. Therefore, potential interactions between pulmonary immune landscapes and tumor molecular characteristics or subsequent systemic therapies could not be evaluated. Importantly, the present study design does not allow definitive determination of causal relationships between pulmonary immune landscapes and tumor progression, and tumor-related systemic influences on distant lung tissue cannot be entirely excluded. Moreover, because no longitudinal sampling or benign disease control cohort was included, the present study could not distinguish pre-existing host immune characteristics from tumor-associated systemic influences or field effects. Future studies incorporating longitudinal sampling before and after tumor resection, as well as comparisons with truly tumor-free lung tissue, will be necessary to clarify these mechanisms. Nevertheless, the present findings suggest that antitumor immunity in lung cancer may involve pulmonary immune landscapes beyond the tumor microenvironment.

Conclusions

In conclusion, the present findings suggest that immune landscapes in tumor-distant lung parenchyma may reflect inter-individual pulmonary immune heterogeneity associated with pathological progression and postoperative recurrence in NSCLC. Further studies are required to clarify the biological and clinical significance of these observations.

Acknowledgments

Special support for immunostaining experiments in this research was received from Ms. Mai Tokudome, a technician belonging to the Department of Pathology, Kagoshima University Graduate School of Medical and Dental Sciences. This study was previously presented in part at the 43rd Annual Meeting of the Japanese Association for Thoracic Surgery (May 14–15, 2026).

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0474/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0474/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0474/prf

Funding: This research was partially supported by Research Support Project for Life Science and Drug Discovery [Basis for Supporting Innovative Drug Discovery and Life Science Research (BINDS)] from AMED (No. JP25ama121054).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-0474/coif). All authors report research funding from the Japan Agency for Medical Research and Development (AMED) (No. JP25ama121054). The authors have no other 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. This study was approved by the Institutional Review Board (IRB) of Kagoshima University Graduate School of Medical and Dental Sciences (protocol code: 210198epi; approval date: 13 December 2021). In accordance with the IRB’s determination and institutional policy for retrospective studies using existing materials, the requirement for written informed consent was waived.

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/.

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