Evaluation of the novel International Association for the Study of Lung Cancer grading system in adenocarcinoma with spread through air space

Introduction

Lung cancer is a heterogeneous group of malignancies with constantly evolving histopathologic classifications, especially in lung adenocarcinoma (LADC). The World Health Organization (WHO) classified five histologic subtypes (lepidic, acinar, papillary, solid, and micropapillary) and four variants (mucinous, colloid, enteric, and fetal) for invasive LADC in 2015 (1). The architectural grading system, which categorizes LADC into low (lepidic predominant), intermediate (acinar or papillary predominant), or high grades (solid or micropapillary predominant) based on the dominant histologic pattern (2), has been extensively investigated and validated as a reliable prognostic marker for diagnosis, treatment, and outcome (3,4). However, this system does not adequately consider the high-grade component (solid and micropapillary LADC), which remains a critical factor even when it is not the predominant histologic pattern (5). Furthermore, some complex glandular patterns, such as cribriform and fused glands, have been shown to be linked to poor outcome (6). Considering these factors, the International Association for the Study of Lung Cancer (IASLC) Pathology Committee has suggested a new grading system that accounts for the high-grade components with a threshold of 20% (7). Several studies have confirmed its predictive value on the recurrence and survival of resected LADCs (8-10).

However, most of the studies do not control for clinicopathologic characteristics among the grading group, which could introduce bias in the result and confirmation of the prognostic value of the novel IASLC grading system. Therefore, we aim to establish the prognostic value of the IASLC grading system for LADCs with spread through air space (STAS) using propensity score matching (PSM). STAS is an additional invasive feature of LADC that was first named by Kadota and colleagues in 2015 (11). It has been reported that STAS is correlated with aggressive characteristics such as lymphovascular invasion, pleural invasion, and high-grade histologic component (12,13). The presence of STAS is associated with increased recurrence and worse overall survival (OS) in early-stage LADC (14) and indicates the need for lobectomy and systemic therapy (15). Evaluating the prognostic value of the IASLC grading system in LADCs with STAS is essential for accurate risk stratification and appropriate decision-making for extensive surgical intervention and systemic therapy. Furthermore, although some radiographic features and genetic mutations have been correlated with pathologic grading (9,10), LADCs with STAS have a distinct genetic mutation profile and radiographic presentation (16), and research on their association with tumor grades in this specific patient population is still limited.

Therefore, the objectives of this study are to apply the new IASLC grading system to LADCs with STAS and validate its prognostic significance using PSM. We also examine clinicopathologic characteristics, including radiologic features and common driver mutations related to grades. Additionally, we assess the effects of adjuvant chemotherapy (ACT) based on IASLC grades in this study. We present this article in accordance with the STROBE reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-265/rc).

Methods

Patients

Data from 4,068 patients with pathologic stages I–III LADC who underwent resection at our institution between January 2017 and December 2020 were retrospectively analyzed. The pathologic stage was determined based on the eighth edition of the American Joint Committee on Cancer Staging Manual. We excluded patients who had neoadjuvant therapy, multiple nodules, concurrent disease progression, LADC in situ, minimally invasive LADC, invasive mucinous LADC, and other variants of LADC, or who had unavailable tumor slides for analysis or insufficient clinicopathologic information. Figure 1A shows the patient selection scheme of this study. Data on clinical variables were obtained by reviewing patient medical records, including age at diagnosis, sex, smoking history, operative procedure, and ACT. This retrospective study received approval from the Institutional Review Board of Shanghai Chest Hospital, China (No. IS22024). Patient informed consent was waived due to the study’s retrospective nature. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Figure 1 Patient selection, histopathology, and survival outcomes in matched stage I–III cohort. (A) Patient selection scheme. (B,C) Representative histopathologic images of LADC tumors with STAS in IASLC grade 2 [(B); HE, 20×] and 3 [(C); HE, 4×]. Arrows indicate the appearance of spread through air spaces, and dotted lines demarcate the margins of primary tumor. (D,E) RFS and OS outcome according to tumor grade 2 and grade 3 in the matched stage I–III cohort. STAS, spread through air spaces; PSM, propensity score matching; LADC, lung adenocarcinoma; IASLC, International Association for the Study of Lung Cancer; HE, hematoxylin and eosin; RFS, recurrence-free survival; OS, overall survival.

Histologic and radiologic evaluation

All available hematoxylin-eosin-stained tumor and lymph node slides were subjected to microscopic review and assessment by two pathologists (Zhao JK and Han YC). STAS was defined as tumor cells within air spaces located beyond the periphery of the primary tumor (11). In accordance with the IASLC/American Thoracic Society (ATS)/European Respiratory Society (ERS) multidisciplinary classification of LADC, tumors were classified and each subtype recorded with the proportional representation in increments of 5% (1). Nontraditional patterns, such as cribriform and fused glands, were also evaluated. Tumors were divided into three categories as the new IASLC grading system proposed: grade 1, lepidic predominant tumors with <20% of high-grade patterns (solid, micropapillary, cribriform, complex glandular patterns); grade 2, acinar or papillary predominant with <20% of high-grade patterns; grade 3, any tumor with ≥20% high-grade patterns. Figure 1B,1C displays representative pathological images of grade 2 and grade 3 LADCs with STAS, respectively.

Before surgery, all patients underwent a computed tomography (CT) examination. We classified the nodules observed on the CT scans into three types: solid, part-solid, and ground-glass nodules. We identified CT features such as lesion size, maximum diameter of solid component, enlarged lymph node (diameter ≥10 mm), consolidation tumor ratios (CTRs; maximum diameter of solid component/maximum diameter of lesion), location (central nodule: inner 2/3 of lung; peripheral nodule: outer 1/3 of lung), margins (smooth, lobulated, spiculated, or irregular), shape (round to oval or irregular), pseudocavity, calcification, central low-attenuation, air bronchogram, satellite lesions, pleural retraction, and others. For patients who also underwent a fluorine-18-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET)/CT examination, we evaluated the maximum standardized uptake value (SUV_max) for further analysis.

Mutation analysis

Gene mutation data were obtained by next-generation sequencing (NGS). Formalin-fixed paraffin-embedded tumor tissue was obtained from patient and processed with the QIAamp DNA FFPE Tissue Kit (Qiagen, Hilden, Germany) to extract DNA, which was further quantified using the Qubit 3.0 dsDNA assay (Life Technologies, Carlsbad, CA, USA). Sequencing libraries were created per Illumina standard protocols and sequenced using a Nextseq500 sequencer (Illumina, Inc., San Diego, CA, USA). The genetic profiling of our tumor samples was evaluated using a 68 cancer-related gene panel from Burning Rock Biotech (Guangzhou, China). Targeted RNA NGS was performed to identify common fusions at the transcript level. Briefly, RNA samples of ≥50 ng were reverse-transcribed into complementary DNA (cDNA). The resulting cDNA was then used for library preparation, during which target-specific primers were employed for polymerase chain reaction (PCR) amplification. We recorded several commonly occurring oncogenic driver mutations such as anaplastic lymphoma kinase (ALK), tumor protein p53 (TP53), epidermal growth factor receptor (EGFR), ROS proto-oncogene 1, receptor tyrosine kinase (ROS1), Kirsten rat sarcoma viral oncogene homolog (KRAS), and B-raf proto-oncogene, serine/threonine kinase (BRAF) (16).

Postoperative follow-up

Patients were instructed to attend follow-up outpatient appointments at regular intervals: quarterly for the first year postoperatively, and biannually thereafter. These appointments involved assessments that comprised blood tumor markers and both chest CT and head magnetic resonance imaging (MRI) scans. Whole-body bone imaging and PET-CT were conducted for patients with abnormal imaging or tumor marker results but inconclusive diagnosis of recurrence. Clinical data and survival outcomes were collected via telephone interviews for patients examined at local health facilities. OS was calculated as the duration between surgery and death or the last follow-up. Recurrence-free survival (RFS) was estimated by measuring the interval from surgery to either the first recurrence or the last follow-up visit. Local recurrence was identified as tumor reappearance near the staple line or bronchial stump. Regional recurrence was characterized by tumor reappearance in the ipsilateral lung, hilar and mediastinal lymph node. Distant metastasis was determined by the spread of cancer to the contralateral lung, other lymph node groups, or any extrathoracic sites.

Statistical analysis

Comparative analyses to identify differences between groups were performed using a chi-squared or Fisher exact test on categorical variables, and student’s t-tests or Mann-Whitney U test on continuous variables. We matched the patients who were classified as grade 2 and grade 3 using 1:1 PSM without replacement. Variables controlled during matching included age, gender, smoking history, tumor location, pathologic nodal status and stage, lymphovascular invasion, and pleural invasion. The PSM was conducted in RStudio (version 4.2.1, The R Foundation, Vienna, Austria) using the R packages “MatchIt” (version 4.4.0) and “foreign” (version 0.8-82), employing the nearest neighbor method with a caliper set at 0.01. We estimated survival using the Kaplan-Meier method and compared groups using the log-rank test. GraphPad Prism for Windows (version 9.0.0; San Diego, CA, USA) was used to visualize the survival curves. We utilized the Cox proportional hazards regression model in multivariate analyses to evaluate how each significant factor from the univariate analysis influenced prognosis. Additionally, both univariable and multivariable logistic regression analyses were conducted to identify preoperative factors independently predicting IASLC grade 3. The concordance index (C-index) and the area under the curve (AUC) of the time-dependent receiver-operating characteristic curve at 3 years were calculated to compare prognostic discrimination ability between the novel grading system and architectural grading system by identifying values for recurrence and death (17). In this study, all P values were two-sided and considered to be statistically significant at <0.05. Analyses were performed with SPSS 26.0 software (IBM Corporation, Armonk, NY, USA) and R Statistical Language (version 4.2.1).

Results

Patient characteristics

In this retrospective study, we identified 3,461 patients with invasive LADC. Among them, 2,551 were STAS-negative and 910 were STAS-positive. According to the novel IASLC grading system, the majority of cases in the STAS-negative cohort were classified as grade 2 (n=1,459, 57.2%), followed by grade 3 (n=777, 30.5%), with 315 patients (12.3%) classified as grade 1. Conversely, in the STAS-positive cohort, most cases were classified as grade 3 (n=604, 66.4%), followed by grade 2 (n=303, 33.3%), and only a few were classified as grade 1 (n=3, 0.3%). Due to the scarcity of grade 1 tumors in STAS-positive cohort, all analyses in this study were conducted exclusively on cases classified as grade 2 and grade 3 (Figure 1A).

Table 1 shows the patient clinicopathologic characteristics in IASLC grade 2 and grade 3 before and after matching. Before matching, grade 3 tumors were significantly associated with radiological invasive patterns such as solid nodule (P<0.001), as well as pathologic aggressive features, including advanced tumor stage (P<0.001), lymph node metastasis (P<0.001), pleural invasion (P<0.001), and lymphovascular invasion (P<0.001). Additionally, high-grade LADCs received lobectomy and ACT more frequently (P=0.002, P<0.001, respectively) due to their higher stage. After matching, almost all variables were well balanced between groups except solid nodule and surgical procedures. Notably, 180 (37.3%) patients with architectural intermediate-grade tumors in the matched cohort were upgraded to grade 3 based on the novel IASLC grading system.

Survival analyses and comparison between grading systems

The median follow-up period for the matched 606 patients was 40 months. During this period, 129 patients experienced recurrence and metastasis, of which 53 (41.1%) had local recurrence and 76 (58.9%) developed distant metastasis. Moreover, 26 patients in the cohort succumbed to lung cancer. Among patients with grade 2 tumors, there were 5 (9.4%) local recurrences, 13 (24.5%) regional recurrences, and 35 (66.0%) distant recurrences. In patients with grade 3 tumors, there were 7 (9.2%) local recurrences, 28 (36.8%) regional recurrences, and 41 (53.9%) distant recurrences (P=0.32). Compared with grade 2 tumors, grade 3 tumors had significantly lower 3-year RFS (77.4% vs. 83.8%, P=0.02) and OS (96.2% vs. 98.2%, P=0.02) rates, as illustrated in Figure 1D,1E, respectively. Moreover, IASLC grade 3 was an independent predictor of unfavorable RFS [hazard ratio (HR), 1.533; 95% confidence interval (CI): 1.077–2.183; P=0.02] and OS (HR, 2.765; 95% CI: 1.146–6.672; P=0.02), according to the multivariate Cox proportional hazards model, which is detailed in Table 2. Subsequently, we evaluated the prognostic utility of the novel grading system across different pathologic stages. The results showed that in stage I, the grading system did not effectively stratify the RFS curves (P=0.38), but it did demonstrate significant differences in OS (P=0.048) (Figure 2A,2B). For stage II tumors, RFS varied significantly between groups, while OS did not reach statistical significance (P=0.01 and P=0.12, respectively) (Figure 2C,2D). Additionally, we found that lymph node metastasis was more prevalent in grade 3 patients (74.4%) compared to grade 2 patients (47.1%) in the stage II cohort (P=0.01). In stage III tumors, grade 3 tumors demonstrated a trend towards poorer outcomes compared to grade 2 tumors, although the RFS and OS curves did not reach statistical significance (P=0.25 and P=0.37, respectively) (Figure 2E,2F).

Figure 2 Kaplan-Meier survival curves of patients stratified by tumor grade in the pathological (A,B) stage I cohort, (C,D) stage II cohort, (E,F) stage III cohort.

We also performed a comparative analysis of patient prognosis based on the architectural grading system and observed a significant difference in RFS among the all-stages cohort (P<0.001), as well as stage I and stage II tumors (P=0.007 and P=0.008, respectively) (Figure S1A-S1C), but not stage III tumors (P=0.80) (Figure S1D). However, the architectural grade group only showed a statistically significant difference in OS in the all-stage patients (P=0.002) (Figure S1E), and not in any substage patients (Figure S1F-S1H). Moreover, architectural high-grade tumor emerged as an independent factor associated with RFS (HR, 1.537; 95% CI:1.061–2.227; P=0.02) and OS (HR, 2.345; 95% CI: 1.066–5.161; P=0.03) by a multivariate Cox proportional hazards model excluding IASLC grades (Table S1). We also compared the prognosis of architectural intermediate grade tumors that remained grade 2 with the IASLC grading and those upgraded to the novel grade 3 tumors, and found no significant difference in terms of RFS and OS (Figure S2). Additionally, a subgroup analysis based on pathological nodal status revealed that grade 3 tumors with negative nodal status have significantly worse OS, while grade 3 tumors with positive nodal status have significantly worse RFS (Figure S3).

We evaluated the prognostic validity of four models to stratify recurrence and death: (I) a baseline model with age, sex, and tumor-node-metastasis (TNM) staging; (II) an architectural grading model that added the architectural grading system to the baseline model; (III) a Sica’s grading model (18) that added the architectural grading system to the baseline model; and (IV) an IASLC grading model that used the new IASLC grading system. Table 3 shows that, for recurrence and death in stage I–III tumors, the IASLC grading model had an AUC of 0.754 (95% CI: 0.698–0.810) and 0.891 (95% CI: 0.836–0.945), respectively, comparable to those of the other grading model. Similar results were obtained in the C-index calculation. In the stage I cohort, the C-index and AUC of the IASLC system were 0.813 (95% CI: 0.668–0.959) and 0.812 (95% CI: 0.781–0.844) for death, respectively, higher than those of the architectural grading group (0.735, 0.766, respectively). For recurrence, the C-index and AUC of the IASLC system were 0.570 (95% CI: 0.487–0.654) and 0.565 (95% CI: 0.468–0.662), respectively, slightly lower than those of the architectural grading group (0.575, 0.575, respectively).

Clinicopathologic and molecular correlation with IASLC grade

Through both univariate and multivariate logistic regression analyses, we identified specific CT features associated with IASLC grade 3. Notable associations included the presence of solid nodules (HR, 1.884; 95% CI: 1.267–2.800; P=0.002), pseudocavity (HR, 0.640; 95% CI: 0.414–0.991; P=0.045) and positive clinical lymph nodes (HR, 2.136; 95% CI: 1.314–3.470; P=0.002), as outlined in Table S2. Despite a higher median SUV_max value observed in grade 3 tumors, it did not prove to be a reliable predictive factor for poorly differentiated LADC with STAS (P=0.82).

A NGS panel targeting 68 cancer-related genes was employed to analyze 429 out of the 606 surgically resected STAS-positive LADC tissue samples. Figure 3 illustrates the identified driver mutations and clinical parameters such as tumor grade and survival. Grade 3 tumors exhibited a higher frequency of ALK and TP53 mutations (P<0.001 and P=0.02, respectively) than grade 2 tumors; whereas EGFR mutation was considerably more prevalent in grade 2 tumors (P<0.001). In contrast, there were no statistically significant intergroup differences in the ROS1 fusion, KRAS mutation, or BRAF mutation (P=0.07, P>0.99, and P=0.93, respectively). EGFR mutation alone did not correlate significantly with the patients’ survival (data not shown).

Figure 3 Mutation profile of the 429 adenocarcinoma patients with STAS stratified by IASLC grades. Grade 3 and grade 2 patients are shown on the left and right, respectively. The oncoprint displays the mutation profile of each patient, with individual mutations represented by vertical bars. The histogram on the right shows the mutation frequency of different genes in the two IASLC grades. The top of the oncoprint annotates patient characteristics including architectural grade, pathologic stage (TNM), age, sex, and survival status. IASLC, International Association for the Study of Lung Cancer; pTNM, pathologic tumor-node-metastasis; TP53, tumor protein p53; EGFR, epidermal growth factor receptor; ALK, anaplastic lymphoma kinase; ROS1, ROS proto-oncogene 1, receptor tyrosine kinase; KRAS, Kirsten rat sarcoma viral oncogene homolog; BRAF, B-raf proto-oncogene, serine/threonine kinase; STAS, spread through air space; TNM, tumor-node-metastasis.

Potential benefits of ACT in patients stratified by IASLC grade

We further evaluated the effectiveness of ACT in patients categorized according to the IASLC grading system across different stages. The Kaplan-Meier curves showed no improvement in RFS or OS for stage IB or II–III LADCs who received ACT post-surgery compared to those who did not, regardless of their tumor grade (Figure 4A-4D). Among the ACT recipients (n=347), the most common regimen was cisplatin plus pemetrexed (n=201, 57.9%), followed by cisplatin plus vinorelbine (n=103, 29.7%).

Figure 4 Curves of RFS and OS for patients with or without ACT, stratified by IASLC grade 2 or 3, in (A,B) stage IB cohort and (C,D) stage II–III cohort. ACT, adjuvant chemotherapy; RFS, recurrence-free survival; OS, overall survival; IASLC, International Association for the Study of Lung Cancer.

Discussion

Accurate and practical tumor grading systems are essential for guiding the treatment of lung cancer patients. By emphasizing the presence of high-grade components and complex glandular patterns which are linked to lymph node metastasis and unfavorable prognoses even as minor components of LADC (5,7,19,20), IASLC grading system is expected to have enhanced prognostic stratification ability. This study sought to evaluate the effectiveness of the new IASLC grading system in estimating the risk of recurrence and death in STAS-positive LADCs. STAS is a prognostic factor for LADCs (12,14) and is strongly correlated with micropapillary and solid predominant subtypes (13). Our results confirmed these correlations, as shown by the low frequency of low-grade tumors and the high proportion of architectural intermediate-grade tumors that were upgraded to IASLC grade 3. We validated the prognostic stratification of the novel grading system in stage I–III LADC, in agreement with previous studies (8-10,21). Most previous studies focused on all-stage and stage I cohorts (8,21). Kagimoto et al. reported that the new grading system did not stratify the prognosis of patients with pathologic stage II or III well (22). However, our study demonstrated that the new grading system effectively stratified RFS in stage II tumors, which may be attributed to the higher rate of nodal positivity in grade 3 tumors among stage II patients. Furthermore, grade 3 tumors exhibited worse outcomes regardless of nodal status. Similarly, Weng et al. (23) found that poorly differentiated advanced-stage LADC (stage III & IV) had the worst RFS, suggesting that the IASLC grading system can accurately stratify LADCs regardless of tumor stage or nodal status. Moreover, while the IASLC system exhibited commendable performance levels in terms of C-index and AUC, comparable to findings reported in other validation studies (8,10), it did not exhibit a distinct advantage over other grading systems. We propose that the presence of STAS may influence the classification efficacy of the IASLC system. This proposition is supported by the lack of a significant survival difference between architectural intermediate-grade tumors that remained classified as grade 2 under the IASLC system and those reclassified as grade 3 in the novel grading system.

Our study showed that solid nodules on CT scans and preoperative positive nodules were independent factors associated with Grade 3 tumors in STAS-positive LADC. These findings are consistent with previous work, which identifies solid nodules as predictive factors for poor prognosis histological subtypes (24). However, we did not find a significant association between SUV_max and higher-grade tumors in our results. One report suggested that ¹⁸F-FDG PET/CT is highly sensitive for predicting high-grade components and a cutoff SUV_max value of 3.45 on ¹⁸F-FDG PET/CT scans could identify higher IASLC grade tumors preoperatively (9). Our study implies the possibility of STAS’ influence in altering the relationships of prognostic factors with higher-grade tumors. STAS is closely linked to high glycolytic hypermetabolism and invasive radiomic features, as evidenced by higher SUV_max values in our study cohort. Interestingly, STAS did not add value to the IASLC model proposed (7), indicating some ambiguity around its inherent aggression, or whether it merely correlates with high-grade components. However, we could not fully explore this association due to a lack of follow-up data for STAS-negative LADCs within our cohort. Further investigations are necessary to provide a definitive answer.

Driver mutations in tumors hold potential prognostic value and therapeutic significance (10,25). We found that EGFR mutations were more common in grade 2 tumors, while TP53 mutations and ALK fusion were more frequent in grade 3 tumors. These results agree with previous studies that reported a high prevalence of EGFR mutations in acinar and papillary adenocarcinomas, and a higher occurrence of TP53 mutations and ALK fusion in solid tumors (3,26,27). However, the associations between genotype and phenotype may differ across populations. Deng et al. (10) observed a different pattern of EGFR mutations, which were linked to a high proportion of moderate grade in their cohort. Although EGFR mutations have been shown to improve prognosis (10), we did not detect a significant survival advantage for patients with EGFR mutations. Moreover, Hong et al. found that EGFR mutation was a risk factor for recurrence, especially in patients with grade 3 tumors, using the IASLC grading system (28). The effect of adjuvant targeted therapy by histologic grade is still unclear and needs further investigation.

The heterogeneity in growth patterns can affect the responses to antineoplastic therapy. Prior studies have indicated that the efficacy of ACT on RFS differs significantly between acinar/papillary and micropapillary/solid subtypes, with the latter demonstrating a benefit (29). Deng and colleagues (10) found an improved prognosis for patients with stages IB-III who were classified as grade 3 by the new IASLC grading system and received ACT. Similarly, Hou and colleagues (21) verified the same benefits for stage IB patients with IASLC grade 3 LADCs. ACT is generally considered for stage II–IIIA patients and stage IB patients who have a high risk of tumor recurrence (30). However, our predictive analyses indicate that differentiation grade may not serve as a reliable indicator for ACT in stage IB or II–III LADC with STAS. We cannot discern whether the presence of STAS, which has been proposed as a marker for ACT (31), influences the predictive value of the IASLC Grading System for ACT benefit. In our previous work, we demonstrated that giving ACT to stage IB patients with high-risk factors such as architectural high-grade tumor, lymphovascular invasion, visceral pleural invasion, and lymph node metastasis led to significantly better RFS outcomes than non-ACT-treated patients (32). Together, our findings imply that traditional invasive patterns may have more potential and practical value than differentiation grade in indicating the need for postoperative chemotherapy in stage IB patients.

This study has several limitations that should be considered. Firstly, the retrospective nature of this single-center study raises concerns about its susceptibility to selection bias, which may affect the validity of the results. Secondly, the limited number of participants with grade 1 tumors and a lack of related analyses limit the generalizability of the findings beyond the study cohort. A further limitation is the absence of specific information on the chemotherapy and targeted regimens administered to patients limiting the ability to analyze outcomes by treatment regimens. Future multi-center and prospective investigations are necessary to validate the grading system’s ability to predict the benefits of adjuvant therapy.

Conclusions

By employing PSM, this study has validated the utility of the novel IASLC grading system as a reliable prognostic indicator for survival in patients diagnosed with stage I–III LADC with STAS. Nevertheless, its applicability remains restricted within certain stage subgroups. Through preoperative imaging, we discerned solid nodules and positive lymph nodes as potential markers suggestive of high-grade malignancy. Furthermore, we detected genotypic variations within different grade subgroups and determined that the IASLC grading system exhibits limited predictive efficacy for ACT in STAS-positive LADC.

Acknowledgments

We thank Jikai Zhao for reviewing and diagnosing the pathological slides.

Funding: This work was supported by a grant from the Shanghai Clinical Key Specialty Construction Project-Thoracic Surgery Specialty (No. shslczdzk02102).

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-265/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-265/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-265/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-265/coif). The 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 (as revised in 2013). This retrospective study received approval from the Institutional Review Board of Shanghai Chest Hospital, China (No. IS22024). Patient informed consent was waived due to the study’s retrospective nature.

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

References

1. Travis WD, Brambilla E, Nicholson AG, et al. The 2015 World Health Organization Classification of Lung Tumors: Impact of Genetic, Clinical and Radiologic Advances Since the 2004 Classification. J Thorac Oncol 2015;10:1243-60. [Crossref] [PubMed]
2. Yoshizawa A, Motoi N, Riely GJ, et al. Impact of proposed IASLC/ATS/ERS classification of lung adenocarcinoma: prognostic subgroups and implications for further revision of staging based on analysis of 514 stage I cases. Mod Pathol 2011;24:653-64. [Crossref] [PubMed]
3. Yoshizawa A, Sumiyoshi S, Sonobe M, et al. Validation of the IASLC/ATS/ERS lung adenocarcinoma classification for prognosis and association with EGFR and KRAS gene mutations: analysis of 440 Japanese patients. J Thorac Oncol 2013;8:52-61. [Crossref] [PubMed]
4. Murakami S, Ito H, Tsubokawa N, et al. Prognostic value of the new IASLC/ATS/ERS classification of clinical stage IA lung adenocarcinoma. Lung Cancer 2015;90:199-204. [Crossref] [PubMed]
5. Tsubokawa N, Mimae T, Sasada S, et al. Negative prognostic influence of micropapillary pattern in stage IA lung adenocarcinoma. Eur J Cardiothorac Surg 2016;49:293-9. [Crossref] [PubMed]
6. Ding Q, Chen D, Wang X, et al. Characterization of lung adenocarcinoma with a cribriform component reveals its association with spread through air spaces and poor outcomes. Lung Cancer 2019;134:238-44. [Crossref] [PubMed]
7. Moreira AL, Ocampo PSS, Xia Y, et al. A Grading System for Invasive Pulmonary Adenocarcinoma: A Proposal From the International Association for the Study of Lung Cancer Pathology Committee. J Thorac Oncol 2020;15:1599-610. [Crossref] [PubMed]
8. Rokutan-Kurata M, Yoshizawa A, Ueno K, et al. Validation Study of the International Association for the Study of Lung Cancer Histologic Grading System of Invasive Lung Adenocarcinoma. J Thorac Oncol 2021;16:1753-8. [Crossref] [PubMed]
9. Fujikawa R, Muraoka Y, Kashima J, et al. Clinicopathologic and Genotypic Features of Lung Adenocarcinoma Characterized by the International Association for the Study of Lung Cancer Grading System. J Thorac Oncol 2022;17:700-7. [Crossref] [PubMed]
10. Deng C, Zheng Q, Zhang Y, et al. Validation of the Novel International Association for the Study of Lung Cancer Grading System for Invasive Pulmonary Adenocarcinoma and Association With Common Driver Mutations. J Thorac Oncol 2021;16:1684-93. [Crossref] [PubMed]
11. Kadota K, Nitadori JI, Sima CS, et al. Tumor Spread through Air Spaces is an Important Pattern of Invasion and Impacts the Frequency and Location of Recurrences after Limited Resection for Small Stage I Lung Adenocarcinomas. J Thorac Oncol 2015;10:806-14. [Crossref] [PubMed]
12. Toyokawa G, Yamada Y, Tagawa T, et al. Significance of Spread Through Air Spaces in Resected Pathological Stage I Lung Adenocarcinoma. Ann Thorac Surg 2018;105:1655-63. [Crossref] [PubMed]
13. Masai K, Sakurai H, Sukeda A, et al. Prognostic Impact of Margin Distance and Tumor Spread Through Air Spaces in Limited Resection for Primary Lung Cancer. J Thorac Oncol 2017;12:1788-97. [Crossref] [PubMed]
14. Khalil HA, Shi W, Mazzola E, et al. Analysis of recurrence in lung adenocarcinoma with spread through air spaces. J Thorac Cardiovasc Surg 2023;166:1317-1328.e4. [Crossref] [PubMed]
15. Shiono S, Endo M, Suzuki K, et al. Spread Through Air Spaces Is a Prognostic Factor in Sublobar Resection of Non-Small Cell Lung Cancer. Ann Thorac Surg 2018;106:354-60. [Crossref] [PubMed]
16. Tian Y, Feng J, Jiang L, et al. Integration of clinicopathological and mutational data offers insight into lung cancer with tumor spread through air spaces. Ann Transl Med 2021;9:985. [Crossref] [PubMed]
17. Uno H, Cai T, Pencina MJ, et al. On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data. Stat Med 2011;30:1105-17. [Crossref] [PubMed]
18. Sica G, Yoshizawa A, Sima CS, et al. A grading system of lung adenocarcinomas based on histologic pattern is predictive of disease recurrence in stage I tumors. Am J Surg Pathol 2010;34:1155-62. [Crossref] [PubMed]
19. Yanagawa N, Shiono S, Abiko M, et al. The Clinical Impact of Solid and Micropapillary Patterns in Resected Lung Adenocarcinoma. J Thorac Oncol 2016;11:1976-83. [Crossref] [PubMed]
20. Zhao Y, Wang R, Shen X, et al. Minor Components of Micropapillary and Solid Subtypes in Lung Adenocarcinoma are Predictors of Lymph Node Metastasis and Poor Prognosis. Ann Surg Oncol 2016;23:2099-105. [Crossref] [PubMed]
21. Hou L, Wang T, Chen D, et al. Prognostic and predictive value of the newly proposed grading system of invasive pulmonary adenocarcinoma in Chinese patients: a retrospective multicohort study. Mod Pathol 2022;35:749-56. [Crossref] [PubMed]
22. Kagimoto A, Tsutani Y, Kambara T, et al. Utility of Newly Proposed Grading System From International Association for the Study of Lung Cancer for Invasive Lung Adenocarcinoma. JTO Clin Res Rep 2021;2:100126. [Crossref] [PubMed]
23. Weng CF, Huang CJ, Huang SH, et al. New International Association for the Study of Lung Cancer (IASLC) Pathology Committee Grading System for the Prognostic Outcome of Advanced Lung Adenocarcinoma. Cancers (Basel) 2020;12:3426. [Crossref] [PubMed]
24. Miao Y, Zhang J, Zou J, et al. Correlation in histological subtypes with high resolution computed tomography signatures of early stage lung adenocarcinoma. Transl Lung Cancer Res 2017;6:14-22. [Crossref] [PubMed]
25. Kneuertz PJ, Carbone DP, D'Souza DM, et al. Prognostic value and therapeutic implications of expanded molecular testing for resected early stage lung adenocarcinoma. Lung Cancer 2020;143:60-6. [Crossref] [PubMed]
26. de Melo AC, Karen de Sá V, Sternberg C, et al. Mutational Profile and New IASLC/ATS/ERS Classification Provide Additional Prognostic Information about Lung Adenocarcinoma: A Study of 125 Patients from Brazil. Oncology 2015;89:175-86. [Crossref] [PubMed]
27. Dong YJ, Cai YR, Zhou LJ, et al. Association between the histological subtype of lung adenocarcinoma, EGFR/KRAS mutation status and the ALK rearrangement according to the novel IASLC/ATS/ERS classification. Oncol Lett 2016;11:2552-8. [Crossref] [PubMed]
28. Hong TH, Hwang S, Choi YL, et al. Different prognostic role of EGFR mutation according to the IASLC histological grade in patients with resected early-stage lung adenocarcinoma. Histopathology 2023;83:168-77. [Crossref] [PubMed]
29. Tsao MS, Marguet S, Le Teuff G, et al. Subtype Classification of Lung Adenocarcinoma Predicts Benefit From Adjuvant Chemotherapy in Patients Undergoing Complete Resection. J Clin Oncol 2015;33:3439-46. [Crossref] [PubMed]
30. Kris MG, Gaspar LE, Chaft JE, et al. Adjuvant Systemic Therapy and Adjuvant Radiation Therapy for Stage I to IIIA Completely Resected Non-Small-Cell Lung Cancers: American Society of Clinical Oncology/Cancer Care Ontario Clinical Practice Guideline Update. J Clin Oncol 2017;35:2960-74. [Crossref] [PubMed]
31. Chen D, Wang X, Zhang F, et al. Could tumor spread through air spaces benefit from adjuvant chemotherapy in stage I lung adenocarcinoma? A multi-institutional study. Ther Adv Med Oncol 2020;12:1758835920978147. [Crossref] [PubMed]
32. Lv Y, Li S, Liu Z, et al. Impact of surgery and adjuvant chemotherapy on the survival of stage I lung adenocarcinoma patients with tumor spread through air spaces. Lung Cancer 2023;177:51-8. [Crossref] [PubMed]