The impact of spread through air spaces on intrapulmonary metastasis in lung cancer: a retrospective study of multiple primary lung adenocarcinomas with confirmed common origin based on histological classification alone and combined histological-molecular classification

Introduction

Lung cancer, particularly lung adenocarcinoma in non-small cell lung cancer (NSCLC), is a leading cause of cancer-related deaths worldwide (1), despite advances in treatment methods, the pathological diagnosis of multiple lung cancers, especially the differentiation between multiple primary lung adenocarcinomas (MPLAs) and intrapulmonary metastases (IPMs), remains a significant challenge. These two entities require distinctly different clinical management approaches. IPM is generally managed with systemic palliative chemotherapy, whereas MPLA are typically treated with curative surgical resection when feasible. As a result, accurate classification directly influences treatment decisions and long-term outcomes. Recent study has shown that overall survival and recurrence-free intervals are significantly longer in MPLA compared to IPM (2).

Spread through air spaces (STAS), a unique mode of metastasis, has recently gained attention among researchers. This metastatic pattern refers to tumor cells entering the alveolar spaces through alveoli and colonizing other regions of the lung (3,4), potentially having a close association with IPM. Although STAS differs from traditional IPM (such as hematogenous or lymphatic spread), whether it directly leads to IPM, particularly in multiple lung adenocarcinomas, remains unclear. The presence of STAS may indicate local extension of the primary tumor or more aggressive biological behavior, which directly affects tumor staging, surgical decision-making, and the need for systemic therapy. Misclassifying IPM as MPLA may lead to inappropriate curative surgery, while misdiagnosing MPLA as IPM could deny patients potentially curative treatment. Therefore, understanding the diagnostic relevance of STAS is critical for optimizing treatment planning and prognostication (5-7).

Accurately distinguishing between MPLAs and IPMs is crucial for clinical management. Traditional histological methods, such as the martini and melamed criteria (8), while helpful in judgment, have shown significant limitations in the context of rapid advances in molecular biology (9). They rely heavily on morphological similarities and lack molecular assessment, making them prone to misclassification when tumors share histologic features but differ at the genomic level. Most lung adenocarcinomas display mixed histological subtypes, and lymph node status—a key component of the martini and melamed criteria—has limited discriminatory value. Furthermore, study has shown that up to 44% of tumors classified as MPLA by histology alone may actually be clonally related based on next-generation sequencing (NGS) (10). This underscores the need to incorporate molecular data and complementary markers such as STAS to improve diagnostic precision. If STAS indeed promotes IPM, it may influence tumor biological behavior and alter clinical management strategies. Furthermore, the role of gene mutations and molecular pathways in lung cancer metastasis has gradually been recognized. Mutations in genes such as Kirsten rat sarcoma viral oncogene homolog (KRAS) and epidermal growth factor receptor (EGFR) may play important roles in IPM (11,12), but their role in STAS remains unclear (13,14). This is particularly problematic when tumors share common driver mutations—such as EGFR or KRAS—since these mutations may independently arise due to field cancerization or environmental exposure, especially in high-prevalence populations (15). Therefore, relying on shared mutations alone may lead to misclassification. Given these limitations, there is a growing need for additional markers to support the differentiation of IPM from MPLA. STAS, a histologic pattern associated with tumor aggressiveness and recurrence, has recently emerged as a potential supportive feature.

This study aimed to investigate the potential association between STAS and IPM in patients with multiple lung adenocarcinomas. By integrating histological and molecular features, we sought to explore whether STAS could serve as a complementary pathological marker to assist in distinguishing IPM from MPLA, thereby providing additional insight into the existing diagnostic framework. We present this article in accordance with the STROBE reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-304/rc).

Methods

Patient and tumor selection

A total of 170 patients who were preoperatively diagnosed with MPLA were retrospectively enrolled. Clinical data (including gender, smoking history, tumor timing, location, among others), pathological specimens, and molecular testing results [including at least EGFR, KRAS, tumor protein p53 (TP53), among others] were collected for analysis.

Inclusion criteria were: (I) preoperative diagnosis of MPLA and postoperative pathological confirmation of lung adenocarcinoma; (II) presence of two or more lesions; (III) complete clinical, radiological, and pathological data; and (IV) molecular testing covering at least key genes such as EGFR, KRAS, TP53, ERBB2, ALK, among others.

Exclusion criteria included: (I) non-adenocarcinoma pathological types; (II) patients who had received radiotherapy, chemotherapy, or targeted therapy before surgery; (III) incomplete clinical data; and (IV) absence of any detectable mutations.

This study was approved by the hospital ethics committee, and all data were anonymized (see Figure 1).

Figure 1 The flowchart of patient selection and analysis. IPM, intrapulmonary metastasis; MPLA, multiple primary lung adenocarcinoma.

This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Medical Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (No. TJ-IRB202502150). As this was a retrospective study, the requirement for informed consent was waived by the ethics committee.

Power and sample size calculation

A priori power analysis was conducted using G*Power 3.1 software to estimate the required sample size for detecting a difference in STAS positivity between the IPM and MPLA groups. Assuming a two-sided test with α =0.05, power =0.80, and the observed proportions (IPM: 47.9%, MPLA: 23.8%), the minimum required sample size was calculated as 153 (43 in IPM, and 110 in MPLA). Our actual sample size of 170 exceeded this threshold, confirming that the study had sufficient power (actual power =0.80).

Clinical and imaging data collection

Demographic information (gender, age, smoking history, etc.), tumor timing (patients had synchronous tumors or metachronous, defined by a second tumor occurring at least 2 years after the first one), tumor location (same lobe or different lobes in the same lung), and lymph node status were collected. All clinical data were obtained from the hospital’s electronic medical record system and independently verified by two researchers before being entered into the database.

Histological evaluation

All surgical specimens were reviewed by two experienced lung cancer pathologists (blinded). Pathological evaluation included tumor size, major histological subtypes (acinar, papillary, lepidic, etc.), pleural invasion, vascular invasion, and the presence of STAS. Major histological subtypes were determined based on the 2015 World Health Organization (WHO) classification criteria for adenocarcinoma. The proportion of each histological component was recorded in 5% increments, with the top three components documented. STAS was assessed by examining all tumor borders and selecting one to three STAS-rich regions. Semi-quantitative evaluation was performed under a microscope at 20× objective and 10× eyepiece magnification. Tumor cells detached into alveolar spaces, forming scattered or clustered distributions, were observed without artificial manipulation. The STAS was classified into three categories: high STAS (≥5 clusters of STAS), low STAS (1–4 clusters of the micropapillary or solid nest-predominant STAS), and no STAS (16). And the only clusters showing a continuous trajectory from the main tumor to the alveolar spaces were considered true STAS, while clusters that appeared randomly scattered, lacked directional orientation, or were distant without continuity were excluded (4,17). Additional histological features recorded included: (I) histological structural patterns; (II) cytological features (cell size, cuboidal or columnar cells, nuclear heterogeneity, intranuclear inclusions, nucleolar size, mitotic rate, cytoplasmic content, and mucin cell count); (III) tumor stroma (cellular components, immune cell count, and type); and (IV) thyroid transcription factor 1 (TTF-1) expression. Based on these assessments, patients were preliminarily classified into MPLA and IPM groups.

Molecular analysis

For each patient’s tumor specimen, paraffin-embedded tissue blocks with high tumor cell content (≥30%) were prioritized for DNA extraction using standardized protocols. Molecular testing was performed using a NGS platform, covering key driver genes such as EGFR, KRAS, TP53, among others, as well as hotspot mutations in other relevant genes. Although the testing panels and mutation sites varied among patients, all cases included at least EGFR, KRAS, TP53, among others. Mutations were defined as having a variant allele frequency ≥2% and coverage depth ≥300×. All variant results were validated through bioinformatics analysis and manual review to ensure data accuracy.

Patient grouping and classification criteria

Two grouping methods were employed in this study:

Histological classification: the distinction between IPM and MPLA was based on histological criteria from previous studies (18,19), including: (I) histological structural patterns; (II) cytological features (cell size, cuboidal or columnar cells, nuclear heterogeneity, intranuclear inclusions, nucleolar size, mitotic rate, cytoplasmic content, and mucin cell count); (III) tumor stroma (cellular components, immune cell count, and type); and (IV) TTF-1 expression (SP24 clone, Novocastra, Newcastle, UK). Based on these criteria, patients were initially classified into MPLA and IPM groups (detailed in Figure 2A).

Figure 2 Histological and histomolecular classification strategies for differentiating MPLA and IPM. (A) A histology-based classification approach, aligned with the WHO guidelines, is used to distinguish multiple lung adenocarcinomas as either MPLA or IPM. This method involves a detailed assessment of the tumor’s architectural patterns, cytological and stromal characteristics, as well as expression of TTF-1. (B) A combined histological and molecular classification model has been proposed to improve diagnostic accuracy. In this approach, rare mutations are defined as those excluding classical EGFR mutations (such as exon 19 deletions and p.L858R) and KRAS p.G12X mutations. AIS, adenocarcinoma in situ; BRAF, B-Raf proto-oncogene; EGFR, epidermal growth factor receptor; ERBB2, erb-b2 receptor tyrosine kinase 2; IPM, intrapulmonary metastasis; KRAS, Kirsten rat sarcoma viral oncogene homolog; MET, MNNG HOS transforming gene; MIA, minimally invasive adenocarcinoma; MPLA, multiple primary lung adenocarcinoma; NRAS, neuroblastoma RAS viral oncogene homolog; TP53, tumor protein p53; TTF-1, thyroid transcription factor-1; WHO, World Health Organization.

Combined histological-molecular classification: a classification algorithm integrating clinical, histological, and molecular features from previous study was used (20). First, if one lesion was adenocarcinoma in situ (AIS) or minimally invasive adenocarcinoma (MIA), the tumor pair was classified as MPLAs. Second, for metachronous lesions, if the interval was ≥5 years, they were classified as MPLAs. Subsequently, molecular analysis results were used for further classification, except for cases where tumors shared a single common hotspot mutation—specifically EGFR exon 19 deletion, EGFR L858R, or KRAS G12X—and no additional shared alterations were detected, classification was based on histologic criteria. The final classification results were compared with the Martini and Melamed classification. Cases with shared hotspot mutations were classified as IPM based on molecular information, while others were classified as MPLA (detailed in Figure 2B).

Statistical analysis

All statistical analyses were performed using R software and RStudio on Windows. Continuous variables were expressed as mean ± standard deviation (SD) for normally distributed data, and as median with interquartile range (IQR) for non-normally distributed data. Normality was assessed using the Shapiro-Wilk test. Comparisons between groups were performed using independent t-tests for normally distributed variables or Mann-Whitney U tests for non-normally distributed variables. Categorical variables were expressed as percentages, and comparisons between groups were performed using chi-square tests or Fisher’s exact tests. Univariate and multivariate logistic regression analyses were used to assess the impact of STAS, pleural invasion, vascular invasion, and lymph node status on IPM, with results expressed as odds ratios (ORs) and 95% confidence intervals (95% CIs). A two-sided P<0.05 was considered statistically significant.

Results

Patient and histological characteristics

A total of 170 patients were included in this study, of whom 63 (37.1%) were male and 30 (17.6%) were smokers. Among the patients, 18 (10.6%) had metachronous tumors with an interval of more than 5 years, 65 (38.2%) had metachronous tumors with an interval of less than 5 years, and 87 (51.2%) had synchronous tumors. Lymph node-positive disease was observed in 13 patients (7.6%). In 59 patients (34.7%), both tumors were located in the same lobe, while in 97 patients (57.1%), the tumors were located in different lobes of the same lung. The three most common major histological subtypes were acinar (125 cases, 73.5%), papillary (80 cases, 47.1%), and lepidic (47 cases, 27.6%) (see Table 1). STAS was observed in 52 patients (30.6%), pleural invasion was detected in 23 patients (13.5%), and vascular invasion was present in 6 patients (3.5%) (see Table 1).

Molecular characteristics of tumors

Among the 340 tumors analyzed for gene mutations, 72 tumors (42.3%) harbored at least two mutations. Commonly mutated genes included TP53 (n=123), KRAS (n=93, of which 68 were KRAS p.G12C), EGFR (n=171, including 62 with exon 19 deletions, 79 with EGFR p.L858R, 13 with exon 20 insertions, and 17 with other mutations), STK11 (n=5), and BRAF (n=5) (see Figure 3).

Figure 3 Global distribution of gene mutations in the 170 studied lung adenocarcinomas. A total of 340 lung lesions (2 per patient) were analyzed, corresponding to 170 patients. EGFR, epidermal growth factor receptor; ERBB2, erb-b2 receptor tyrosine kinase 2; KRAS, Kirsten rat sarcoma viral oncogene homolog; TP53, tumor protein p53.

Classification of IPM and MPLA patients

A total of 170 patients were included in the study, classified into two groups based on histological classification: MPLA (n=94) and IPM (n=76). When integrating histological and molecular classifications, 122 patients were categorized as MPLA and 48 as IPM. No significant differences were observed in sex distribution, median age at first resection, smoking history, tumor laterality, or type of resection between the groups (all P>0.05).

There was no significant difference in the proportion of synchronous and metachronous tumors between the MPLA and IPM groups under histological classification (P=0.56). However, under the combined classification, synchronous tumors were more common in the IPM group (66.7%) compared to the MPLA group (45.1%) (P=0.005). The distribution of tumors (same lobe, ipsilateral different lobe, or contralateral) did not differ significantly between the groups (all P>0.05).

The median tumor size was significantly larger in the IPM group compared to the MPLA group in both classification systems (histological: 1.35±0.56 vs. 0.99±0.44 cm, P<0.001; combined: 1.36±0.55 vs. 1.06±0.49 cm, P=0.001). Nodal involvement (N-positive) was significantly more frequent in the IPM group than in the MPLA group under histological classification (13.2% vs. 3.2%, P=0.03), but this difference was not statistically significant in the combined classification (12.5% vs. 5.7%, P=0.24).

The presence of tumor STAS in at least one tumor was significantly higher in the IPM group than in the MPLA group under both classification systems (histological: 42.1% vs. 21.3%, P=0.006; combined: 47.9% vs. 23.8%, P=0.004). Additionally, STAS quantity was significantly higher in the IPM group, with a greater proportion of cases exhibiting low and high STAS (all P<0.05). No significant differences were observed in pleural invasion or vascular involvement between groups (all P>0.05).

EGFR mutations were more frequently detected in at least one tumor in the MPLA group than in the IPM group under the combined classification (63.1% vs. 41.7%, P=0.02), while no significant difference was observed under histological classification (P=0.23). KRAS mutation rates did not significantly differ between the groups in either classification system (all P>0.05).

Significant differences in histological subtypes were observed between groups. The MPLA group had a higher proportion of AIS and MIA compared to the IPM group (both P<0.001). The IPM group under histological classification exhibited a higher frequency of acinar subtype (P), while the MPLA group had a higher prevalence of lepidic growth patterns (all P<0.05). No significant differences were found in the distribution of papillary, tubular, solid, cribriform, micro papillary or mucinous subtypes (all P>0.05) (see Table 1).

Logistic regression analysis of STAS and IPM

We first classified patients based on histological methods and performed logistic regression analysis to evaluate the impact of STAS, pleural invasion, vascular involvement, and nodal status on IPM. In univariate analysis, STAS (OR =2.691; 95% CI: 1.385–5.335; P=0.004) and nodal status (OR =4.596; 95% CI: 1.346–21.089; P=0.02) were significantly associated with IPM. In contrast, pleural invasion (OR =1.733; 95% CI: 0.717–4.305; P=0.22) and vascular involvement (OR =2.556; 95% CI: 0.485–18.805; P=0.29) did not show statistical significance. In multivariate analysis, STAS remained an independent predictor of IPM (OR =2.267; 95% CI: 1.107–4.714; P=0.03), while the association of nodal status lost statistical significance after adjusting for other factors (OR =3.073; 95% CI: 0.750–16.730; P=0.14).

After further grouping patients using combined histological and molecular methods, we repeated the logistic regression analysis. The results showed that, in univariate analysis, STAS (OR =2.950; 95% CI: 1.462–5.998; P=0.003) remained significantly associated with IPM, while the OR for vascular involvement increased (OR =5.455; 95% CI: 1.028–40.347; P=0.055) but did not reach statistical significance. In multivariate analysis, STAS remained an independent predictor (OR =2.576; 95% CI: 1.200–5.526; P=0.01), while pleural invasion (OR =1.498; 95% CI: 0.551–3.864; P=0.41), vascular involvement (OR =2.753; 95% CI: 0.422–23.963; P=0.30), and nodal status (OR =0.952; 95% CI: 0.218–3.662; P=0.94) did not show statistical significance (see Table 2 and Figure 4).

Figure 4 Forest plot of multivariate logistic regression analysis stratified by classification methods. (A) Histology-based classification. (B) Integrated histology and molecular classification. Odds ratios and 95% confidence intervals are displayed for each variable. STAS, spread through air spaces.

In summary, STAS was identified as an independent predictor of IPM in both histological and combined histological-molecular classification systems. However, STAS was also observed in a subset of patients classified as having MPLA, indicating that it is not exclusive to IPM. These findings suggest that while STAS can serve as a supportive indicator of intrapulmonary spread, it should be interpreted alongside histological and molecular features to improve diagnostic accuracy. In contrast, pleural invasion, vascular involvement, and nodal status did not demonstrate significant associations with IPM in multivariate analysis.

Discussion

This study systematically analyzed the clinicopathological features, molecular profiles, and STAS expression patterns in patients with multiple lung adenocarcinomas, aiming to explore the potential diagnostic value of STAS in distinguishing MPLA from IPM. While we observed that histological classification alone may result in ambiguity, especially in cases with overlapping morphology, the integration of molecular data helped clarify clonal relationships in several discordant cases. Specifically, 28 patients exhibited inconsistency between histological and combined classifications, mainly due to divergent driver gene mutations such as KRAS and EGFR, reinforcing prior evidence that histological similarity does not guarantee clonal identity.

Our findings demonstrated that STAS was significantly more prevalent in IPM and independently associated with intrapulmonary spread, suggesting that STAS may serve as a supportive marker for differentiating IPM from MPLA. Given the potential for histologic misclassification and the limitations of molecular testing in some settings (10), STAS could provide additional diagnostic value.

STAS, as an independent poor prognostic factor, was significantly more prevalent in the IPM group compared to the MPLA group (47.9% vs. 23.8%). The higher frequency of STAS in IPM suggests a potential role in intrapulmonary dissemination and distal seeding. Previous studies have shown that STAS-positive lung cancer patients are more likely to experience postoperative recurrence (21-24), supporting its association with aggressive tumor behavior. Our findings reinforce this observation and indicate that STAS may serve as a supportive pathological marker in differentiating IPM from MPLA. However, the presence of STAS in approximately one-quarter of patients classified as MPLA highlights that STAS is not specific to IPM. Therefore, while STAS can aid in diagnostic evaluation, it should be interpreted in the context of molecular alterations, histological features, and clinical presentation, rather than used as a standalone criterion. Additionally, the correlation between STAS and multifocal lesions may reflect underlying mechanisms of local invasion and spread, warranting further investigation into its molecular basis in lung adenocarcinoma progression. Furthermore, in clinical practice—particularly in developing countries—access to comprehensive molecular testing may be limited due to cost constraints and resource availability. In such settings, STAS assessment via routine pathological examination offers a practical, cost-effective adjunct to support the diagnostic differentiation between MPLA and IPM. Although it cannot replace molecular analysis, STAS may help to indicate a propensity for intrapulmonary spread when molecular data are unavailable, thus informing treatment decisions in resource-limited environments.

We observed significant differences in EGFR mutation patterns between MPLA and IPM. EGFR mutations were more frequent in the MPLA group (63.1% vs. 41.7%, P=0.02), which is consistent with previous studies reporting that EGFR-mutant lung cancers are more likely to present as multiple primary lesions (25,26). In contrast, KRAS mutations did not differ significantly between the two groups. Notably, prior research has suggested that KRAS mutations may confer greater invasiveness and metastatic potential (27,28), indicating that their role in distinguishing MPLA from IPM remains complex and may extend beyond simple prevalence differences. Although BRAF and STK11 mutations were rare in the overall cohort, they warrant further investigation to explore their roles in multifocal lung lesions.

However, this study has several limitations. First, due to its retrospective design, some patients lacked complete molecular testing data. Although current diagnostic practice primarily treats STAS as a binary variable (present or absent), previous study has suggested that the extent or density of STAS—including the number of detached tumor cell clusters or their distance from the main tumor—may be associated with recurrence risk and clinical outcomes (16). Therefore, future studies with larger sample sizes and objective grading systems are needed to further determine whether the “degree” of STAS can enhance its diagnostic or prognostic value. Additionally, the single-center nature and limited sample size may affect the generalizability of the results. Furthermore, our study did not incorporate emerging technologies such as spatial transcriptomics or single-cell sequencing, which could provide higher-resolution insights into clonal evolution and further elucidate the molecular mechanisms underlying MPLA and IPM.

In conclusion, our study demonstrates that STAS is significantly more prevalent in IPM than in MPLA and serves as an independent predictor of IPM across both histologic and molecular classification systems. While not specific to IPM, the presence of STAS may reflect aggressive tumor behavior and can support diagnostic interpretation when integrated with other clinicopathologic and genomic data. In clinical settings where access to broad molecular testing is limited—such as in many developing countries—STAS may serve as a practical and cost-effective histologic adjunct. However, given that our analysis was based on surgically resected specimens, the utility of STAS in preoperative biopsy samples remains limited and warrants further investigation.

Conclusions

STAS was significantly associated with IPM and identified as an independent predictor of IPM under both histologic and combined histologic–molecular classification systems. Although STAS is not exclusive to IPM, its presence may provide valuable supportive information for differentiating IPM from MPLA. Given the limitations of histologic and molecular criteria and the diagnostic challenges in resource-limited settings, STAS may serve as a practical and cost-effective histopathologic adjunct to guide postoperative clinical decision-making. Future studies are warranted to further validate the diagnostic value of STAS and explore its integration into multidisciplinary evaluation frameworks.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-304/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-304/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-304/prf

Funding: This study was supported by the Chen Xiaoping Science and Technology Development Foundation (No. CXPJJH1180008 to W.S.).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-304/coif). W.S. reports that the study was supported by the Chen Xiaoping Science and Technology Development Foundation (No. CXPJJH1180008). 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. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Medical Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (No. TJ-IRB202502150). As this was a retrospective study, informed consent was waived by the ethics committee.

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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