The impact of local tumor immune responses on prognosis in resected lung adenocarcinoma

Introduction

Non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer cases, represents the leading cause of cancer-related mortality, and is the second most commonly diagnosed cancer worldwide (1-3). Despite substantial advances in surgery, radiation therapy, chemotherapy, and immunotherapy, the prognosis for patients with NSCLC remains poor. Therefore, identifying reliable prognostic biomarkers is essential for guiding treatment selection and optimizing therapeutic strategies in NSCLC.

Tertiary lymphoid structures (TLS) are ectopic lymphoid organs that form at sites of chronic inflammation and have been reported in several cancer types, including lung cancer (4). Mature TLS are organized into distinct T cell and B cell zones, with the B cell zone containing germinal centers and being surrounded by a T cell zone (5). In addition, mature TLS are associated with high endothelial venules (HEVs) and mature dendritic cells. HEVs are structurally specialized blood vessels that develop in all secondary lymphoid organs except the spleen during fetal and neonatal development. They mediate the recruitment of naïve and memory lymphocytes from the bloodstream, independent of antigen receptor specificity, and facilitate their interaction with antigen-presenting cells in lymph nodes under homeostatic conditions. As such, HEVs play a critical role in the initiation and maintenance of immune responses. Beyond secondary lymphoid organs, HEVs can also develop in non-lymphoid tissues after birth in the setting of chronic inflammation caused by autoimmunity, infection, allogeneic transplantation, and cancer. These extranodal HEVs are typically surrounded by TLS. HEV neogenesis is therefore thought to promote the local generation of tissue-damaging lymphocytes within chronically inflamed tissues and tumor microenvironments.

L-selectin binding to peripheral node addressin represents an essential initial step in homeostatic lymphocyte trafficking, a defining function of HEVs, and mediates L-selectin-dependent homing of lymphocytes from the bloodstream to lymphoid tissues and tumors.

Unlike primary and secondary lymphoid organs, the formation of TLS depends on antigenic stimulation and contributes to ongoing adaptive immune responses. TLS are frequently located at the tumor margin and within the interstitium and are thought to function as lymphoid outposts and sites of immune activation, forming in the context of inflammatory signaling (6). Within these immune cell aggregates, dendritic cells present antigens derived from adjacent tumor tissue to T cells via TLS (7,8). This process subsequently induces memory helper T cells and effector memory cytotoxic T cells, which are believed to contribute to antitumor immunity (9,10). In addition, B cells are activated within TLS, leading to the differentiation, activation, and proliferation of memory B and plasma cells (11,12).

Tumor-associated TLS are generally associated with a favorable prognosis. The recurrence-preventive effects observed with perioperative immune checkpoint inhibitors (ICIs) further suggest that the immune status of patients undergoing lung cancer resection may have a substantial impact on prognosis (13).

In this study, we examined the associations between patient prognosis and the abundance of immune cells within TLS, including CD8⁺ T cells, CD4⁺ T cells, and B cells, as well as the areas of TLS and HEVs. These features are considered critical for TLS formation and immune cell infiltration in resected lung adenocarcinoma. We present this article in accordance with the REMARK reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-1-0050/rc).

Methods

Patients and samples

Between January 2018 and January 2019, this study included 100 patients who underwent complete resection by lobectomy with at least selective mediastinal lymph node dissection for lung adenocarcinoma at Saitama Medical University International Medical Center. Pathological stage (p-stage) was determined according to the current TNM classification (14). In addition, the neutrophil-to-lymphocyte ratio was calculated using preoperative blood test data. The associations between these clinicopathological factors and prognosis were retrospectively analyzed. The percentage of lepidic growth was assessed by pathologists through examination of hematoxylin and eosin-stained specimens.

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of Saitama Medical University International Medical Center (No. 2024-051). Informed consent was waived in this retrospective study.

Multiplex immunofluorescence

A representative lung cancer tissue section from each case was stained to multiplex immunofluorescence staining using antibodies against CD8 (C8/144B, DAKO), CD4 (4B12, Leica Biosystem), CD20 (L26, CST), peripheral node addressin (MECA-79, Novus), and pan-cytokeratin (AE1/AE3, Nichirei Bioscience). Anti-peripheral node addressin antibody (MECA-79)-positive vessels were classified to be HEV. The numbers of immune cells within TLS, including CD8⁺ T cells, CD4⁺ T cells, and B cells, as well as the areas of TLSs and HEVs, were quantified using the Mantra imaging platform (Akoya biosciences, MA) and Mantra snap software (Akoya biosciences, MA). Color separation was done on inForm^® Sofware v2.5.1 (Akoya bioscience, MA) to extract image data. Multiplex immunohistochemical staining and data analysis were performed according to previously described procedures (15). Multiple observers manually marked the TLS and HEV regions, and the software calculated the area. The software counted the number of CD4, CD8, and CD20-positive cells.

In multiplex staining, the tumor specimen was formalin fixed and paraffin embedded (FFPE), and three with the largest area of viable tumor cells were selected. Then, 5 µm thick sections of FFPE tissue were deparaffinized and rehydrated by xylene and ethanol for multiplex immunofluorescence. Sequentially, all slides were treated with 0.3% hydrogen peroxide in methanol for 30 min to block endogenous peroxidase activity. To expose antigens, sections were autoclaved in 10 mmol/L sodium citrate buffer (pH 6.0) for 20 min and done in the microwave at 98 ℃ for 15 minutes, and cooled for 30 min. After rinsing in 0.05 M tris-buffered saline containing 0.1% tween 20, primary antibodies were then applied, followed by incubation with their respective biotinylated anti-mouse/anti-rabbit secondary antibodies (Agilent, K5003), streptavidin-HRP (Agilent, K5003), and opal fluorescent dye (Akoya). After six immunostaining steps, the nuclei were counterstained with DAPI (PerkinElmer, FP1490).

In this analysis, TLS were identified and evaluated across a spectrum of maturation, ranging from poorly differentiated structures, such as lymphoid aggregates and lymphoid follicles without germinal centers, to more mature structures associated with HEVs and characterized by dense cellular aggregates resembling the germinal centers of secondary lymphoid organs.

Following multiplex immunofluorescence and multilabeling of representative tumor sections, quantitative digital pathology software was used to assess TLS, HEV area, and the numbers of CD4-, CD8-, and CD20-positive lymphocytes within TLS on scanned images.

Statistical analysis

The Kaplan-Meier method was used to estimate survival, the log-rank test was applied for univariate comparisons, and the Cox proportional hazards model was used for multivariate analysis. Receiver operating characteristic (ROC) curve analysis was performed to determine optimal cutoff values for clinicopathological variables. For continuous variables such as age, Brinkman index, lymphocyte-to-neutrophil ratio, lepidic growth percentage, TLS and HEV area, CD4, CD8, and CD20-positive cell count, the point where sensitivity and specificity are maximized was analyzed using ROC curves, and the cutoff value was determined. The Pearson product-moment correlation coefficient was used to assess correlations between TLS area and immune cell counts. All P values were two-sided, and values less than 0.05 were considered statistically significant.

All statistical analyses were conducted using EZR (Jichi Medical University Saitama Medical Center, Saitama, Japan), a graphical user interface for R (The R Foundation for Statistical Computing, Vienna, Austria). EZR is an enhanced version of R Commander that incorporates statistical functions commonly used in biostatistical analyses (16).

Results

Patient characteristics

Patient characteristics are summarized in Table 1. The cohort included 44 men (44%) and 56 women (56%), with a median age at surgery of 79 years (range, 38–92 years). Pathological stage I, II, and III disease was observed in 77, 11, and 12 cases, respectively. Twenty-seven of the 100 patients received adjuvant chemotherapy, including 20 treated with tegafur/uracil and seven treated with cisplatin plus vinorelbine. No patients received neoadjuvant chemotherapy. Common epidermal growth factor receptor (EGFR) mutations were identified in 48 cases (48%), and anaplastic lymphoma kinase (ALK) fusion genes were detected in two cases among those tested. The follow-up period ranged from 28 to 2,810 days (median, 1,908.5 days). The 5-year overall survival rate was 90.4% (Figure 1).

Figure 1 Kaplan-Meier curve for overall survival in all cases. The 5-year overall survival rate was 90.4%. OS, overall survival.

Evaluation of multiplex immunofluorescence staining

Figure 2 presents representative images of multiplex immunofluorescence staining. Clusters of B cells and CD4⁺ T cells were defined as TLS, regardless of the presence of HEVs or dendritic cells, and are indicated by yellow arrows. Cells expressing each marker were scanned and digitally analyzed to quantify the number of immune cells within TLS and to measure the areas of TLS and HEVs.

Figure 2 Multiplex immunofluorescence staining. Following immunohistochemistry and multilabeling, quantitative digital pathology software was used to evaluate the numbers of CD4⁺, CD8⁺, and CD20⁺ lymphocytes, as well as HEV areas within TLS on scanned images. Yellow arrows indicate TLS. Areas positive for anti-peripheral node addressin antibody were determined to be HEV. HEV, high endothelial venule; TLS, tertiary lymphoid structure.

ROC curve analysis

ROC curve analysis for TLS area identified an optimal cutoff value of 1,065,465.4 µm², corresponding to the maximum sensitivity and specificity (Figure 3). The area under the ROC curve was 0.665, with a 95% confidence interval of 0.491–0.840.

Figure 3 ROC curve analysis of TLS area. The cutoff value was defined at the point of maximum sensitivity and specificity. ROC, receiver operating characteristic; TLS, tertiary lymphoid structure.

Kaplan-Meier survival analysis

Kaplan-Meier curves were used to assess associations between clinicopathological factors and overall survival. Larger TLS area, larger HEV area, higher CD4⁺ T cell counts within TLS, greater pathological lepidic growth percentage, and earlier p-stage were all associated with significantly improved prognosis (Figure 4).

Figure 4 Kaplan-Meier curve of overall survival by clinicopathological factors. Kaplan-Meier curves were used to assess associations between clinicopathological factors and overall survival. Larger TLS area, larger HEV area, higher CD4⁺ T cell counts within TLS, greater pathological lepidic growth percentage, and earlier pathological stage were associated with significantly improved prognosis. HEV, high endothelial venule; OS, overall survival; TLS, tertiary lymphoid structure.

Prognostic analysis

In univariate analysis, TLS area, HEV area, CD4⁺ T cell count within TLS, pathological lepidic growth percentage, and p-stage were identified as significant prognostic factors. In multivariate analysis, TLS area and p-stage remained independent prognostic factors (Table 2).

Correlation analysis of clinicopathological factors

Analysis of the relationship between TLS area and HEV area demonstrated a strong and significant positive correlation, indicating that larger TLS areas were associated with larger HEV areas (Figure 5). In contrast, no significant correlations were observed between TLS area and the numbers of lymphocyte subsets within TLS, including CD4⁺, CD20⁺, and CD8⁺ cells (Figure 6). Similarly, no significant correlation was detected between HEV area and the number of these immune cells. The correlation between TLS area and the pathological lepidic growth percentage was also evaluated; however, because TLS were also present within lepidic growth areas, no significant correlation was detected (Figure 7). Correlations between driver genes (EGFR mutations, ALK fusion genes) and immune-related factors (TLS, HEV, and immune cell count) were also analyzed, but no significant factors were detected (Table 3).

Figure 5 Correlation between TLS area and HEV area. The relationship between TLS area and HEV area is shown. Larger TLS areas were associated with larger HEV areas. HEV, high endothelial venule; TLS, tertiary lymphoid structure.

Figure 6 Correlations between TLS area and lymphocyte counts (CD4⁺, CD20⁺, CD8⁺ cells) within TLS were analyzed, but no significant associations were detected. TLS, tertiary lymphoid structure.

Figure 7 Correlation between TLS area and pathological lepidic growth percentage. The relationship between TLS area and pathological lepidic growth percentage was analyzed; however, no significant correlation was observed, as TLS was also present within lepidic growth areas. TLS, tertiary lymphoid structure.

Neoadjuvant therapy

In recent years, neoadjuvant therapy for lung cancer has shown excellent efficacy. We added similar multiplex immunofluorescence staining on a case in which we observed a pathological complete response to neoadjuvant therapy. While no viable cancer cells were observed, numerous TLS were found (Figure 8).

Figure 8 Multiplex immunofluorescence staining. Similar multiplex immunofluorescence staining on a case, in which we observed a pathological complete response to neoadjuvant therapy, was shown. While no viable cancer cells were observed, numerous TLS were found. Yellow arrows indicate TLS. TLS, tertiary lymphoid structure.

Discussion

The mechanisms underlying TLS formation remain incompletely understood but are thought to resemble those involved in lymph node formation. TLS are organized, secondary lymphoid organ-like aggregates that can develop locally (17) and regulate antitumor immune responses through mechanisms distinct from the conventional cancer immunity cycle. Within tumor sites, TLS facilitate local presentation of tumor antigens by dendritic cells, promote the generation of effector T cells and antibody-producing plasma cells, and have been associated with a favorable prognosis across multiple cancer types (18).

Within tumors, B cells rarely occur in isolation and instead tend to co-localize with CD4⁺ and CD8⁺ tumor-infiltrating lymphocytes (19). Patients whose tumors contain both B cells and CD8⁺ T cells generally have a more favorable prognosis than those with CD8⁺ T cells alone. TLS are ectopic lymphoid structures that develop in non-lymphoid tissues at sites of chronic inflammation, including tumors.

Within TLS, a T cell zone containing mature dendritic cells forms around B cell areas, which comprise plasma cells, follicular helper T cells, and follicular dendritic cells. In addition to antibody production, B cells within TLS can function as antigen-presenting cells for T cells, including CD8⁺ T cells. Co-localization of B cells with an aberrant memory phenotype (CD27⁻) and high expression of antigen-presenting molecules alongside CD8⁺ T cells has been observed in ovarian cancer metastases. In this setting, the presence of both B cells and CD8⁺ T cells has been associated with improved patient survival compared with CD8⁺ T cells alone (20,21).

Cross-presentation of antigens by B cells to CD8⁺ T cells has been reported for cancer-testis antigens such as NY-ESO-1 and mutant antigens such as p53 (22,23). Engagement of CD80 and CD40 on B cells can obviate the requirement for CD4⁺ T cell-mediated antigen delivery to cytotoxic T lymphocytes in viral and antitumor immune responses (24-26). In addition, the presence of plasma cells has been shown to correlate with CD8⁺ T cell infiltration, thereby enhancing the prognostic value of CD8⁺ T cells (27). Notably, a recent large-scale meta-analysis of human cancers demonstrated that the prognostic impact of T cells was generally stronger when tumor-infiltrating B cells or plasma cells were present, highlighting the importance of coordinated cellular and humoral adaptive immune responses in antitumor immunity (21).

Regarding the relationship between TLS and histopathological parameters, the presence of HEVs in primary tumors from 225 patients with malignant melanoma was reported to correlate with tumor regression and favorable clinical characteristics (28). Aoyama et al. further demonstrated that HEVs were an independent favorable prognostic factor in a multivariate analysis of 156 patients of hepatocellular carcinoma (29). In a cohort of 80 patients with oral squamous cell carcinoma, TLS were more abundant in T1 and T2 stages than in T3 and T4 stages (30). Across multiple cancer types, including lung cancer, colorectal cancer, pancreatic cancer, oral squamous cell carcinoma, and invasive breast cancer, the presence of TLS has consistently been associated with prolonged overall survival and recurrence-free survival (17).

In the present analysis, TLS area emerged as an independent prognostic factor in resected lung adenocarcinoma. HEVs are thought to play a key role in TLS maturation, and our findings further demonstrated a strong correlation between TLS area and HEV area. Wang et al. reported that vascular cell adhesion molecule 1 and intercellular adhesion molecule 1 expressed on HEVs recruit and activate CXCL13-positive T cells through the CXCL13-ACKR1 pathway and promote TLS formation via CXCL13-CXCR5-dependent crosstalk with B lymphocytes (31). While germinal center markers such as BCL6 and Ki67, and follicular dendritic cell markers such as CD21 and CD23 (32) should be used to evaluate the maturity of TLS, this analysis did not allow for such evaluation. This study does not focus on mature TLS itself, but rather on evaluating the quantity of TLS and HEV-related structures, these observations support the involvement of TLS in antitumor immune responses and their contribution to patient prognosis.

In this study, univariate analysis of immune cell populations within TLS showed that a higher number of CD4⁺ T cells in TLS was associated with significantly improved prognosis, although this factor was not independently prognostic in multivariate analysis. Whereas previous studies have primarily evaluated the presence, absence, or number of TLS, the present study employed digital quantification using multiplex immunofluorescence and multispectral imaging. This approach enabled more detailed assessment, including precise quantification of immune cell populations within TLS as well as measurement of TLS and HEV areas.

A higher abundance of B cells and CD8⁺ T cells within TLS has been associated with improved prognosis (4,33). However, the specific CD4⁺ T cell subsets that contribute to antitumor immune responses remain unclear. CXCL13-producing CD4⁺ T cells have been implicated in TLS formation and shown to promote antitumor immunity in ovarian cancer (34). In the present study, we also examined the relationship between TLS area and the numbers of immune cells within TLS, but no significant correlations were identified for any immune cell subset.

In contrast, Mori et al. reported that CD103⁺ T cells, so-called tumor-resident T cells, are preferentially localized around TLS, and that patients with high CD103 expression were enriched for TLS (35). Patients with both high CD103 expression and enriched TLS had a more favorable prognosis than those with low CD103 expression and sparse TLS. We previously demonstrated that high levels of CD103⁺ T cells within tumors are associated with favorable prognosis in patients with squamous cell lung cancer (36). Furthermore, in patients treated with ICIs, the combination of high CD103 expression and enriched TLS was predictive of a favorable therapeutic response (35). We have also reported that CD103⁺ T cells may serve as a predictor of response to ICI therapy (37). Notably, CD103⁺ CD8⁺ T cells within germinal centers were shown to express higher levels of programmed cell death protein 1, granzyme B, and interferon-γ compared with CD103⁻ CD8⁻ T cells (35). These findings suggest that CD103⁺ CD8⁺ T cells within germinal centers are closely associated with TLS and may enhance antitumor immune responses at these sites.

In recent years, neoadjuvant therapy for lung cancer has become widely applied, and in cases where complete response was achieved, it has been suggested that pre-existing B cells matured due to the neoadjuvant therapy, leading to its effectiveness (38). In a case of complete response to neoadjuvant therapy for lung cancer experienced in our department, many TLS were also observed. Further analysis is needed, but TLS are expected to be not only a prognostic factor after surgery for lung adenocarcinoma, but also a predictor of the effectiveness of neoadjuvant therapy.

Tumor-infiltrating B cells within TLS have been reported to be associated with the therapeutic efficacy of ICIs (4,39-41). In the present study, because TLS were observed even in lesions with a pure lepidic growth pattern, we examined the association between the pathological lepidic growth percentage and TLS; however, no significant correlation was identified. To the best of our knowledge, no previous studies have evaluated the relationship between lepidic growth proportion and TLS in lung adenocarcinoma. Although no association was observed, this study represents the first report addressing this relationship.

Previous studies have also investigated associations between driver gene alterations, such as EGFR mutations, and TLS in lung adenocarcinoma, without identifying significant correlations (42,43). It was revealed that TLS formation was reduced in lung adenocarcinoma cases with EGFR mutations (43,44). Zou et al. reported that in lung adenocarcinoma cases with ALK fusion genes, TLS formation is reduced, which may be related to the reduced effectiveness of ICIs (45). Consistent with these findings, we analyzed the relationships between EGFR mutations, ALK fusion genes, and TLS in the present cohort and found no significant associations. Although subtypes of adenocarcinoma were included in the analysis, no significant differences were found (data not shown).

This study has several limitations, including its retrospective design, single-center setting, and relatively small sample size. This analysis evaluated immunofluorescence-positive cells within a representative lung cancer tissue slide, thus including cells within and near the tumor. Therefore, the positional relationship between the tumor and immune cells cannot be evaluated. OS was analyzed as the primary endpoint of postoperative prognosis, but similar results were observed for relapse-free survival/disease-free survival.

Conclusions

In patients with resected lung adenocarcinoma, TLS are an independent favorable prognostic factor, and their presence is associated with improved outcomes. A significant correlation was observed between TLS area and HEV area.

Acknowledgments

The authors are grateful to Ms. Watanabe K for her technical support.

Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-1-0050/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-1-0050/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-1-0050/prf

Funding: This work was supported by JSPS KAKENHI (No. 22K09013, to Y.I.).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-1-0050/coif). Y.I. reports support from JSPS KAKENHI. H.K. reports grants from Boehringer Ingelheim and lecture fees from Ono Pharm, Bristol Myers Squibb, AstraZeneca, Chugai Pharm, MSD, Amgen, and Janssen Pharm. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of Saitama Medical University International Medical Center (No. 2024-051). Informed consent was waived in this retrospective study.

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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