Spread Through Air Spaces (STAS) Is Prognostic in Atypical Carcinoid, Large Cell Neuroendocrine Carcinoma, and Small Cell Carcinoma of the Lung

Predicting histopathological features of aggressiveness in lung cancer using CT radiomics: a systematic review

PURPOSE

To examine the accuracy of CT radiomics to predict histopathological features of aggressiveness in lung cancer using a systematic review of test accuracy studies.

METHODS

Data sources searched included Medline, Embase, Web of Science, and Cochrane Library from up to 3 November 2023. Included studies reported test accuracy of CT radiomics models to detect the presence of: spread through air spaces (STAS), predominant adenocarcinoma pattern, adenocarcinoma grade, lymphovascular invasion (LVI), tumour infiltrating lymphocytes (TIL) and tumour necrosis, in patients with lung cancer. The primary outcome was test accuracy. Two reviewers independently assessed articles for inclusion and assessed methodological quality using the QUality Assessment of Diagnostic Accuracy Studies-2 tool. A single reviewer extracted data, which was checked by a second reviewer. Narrative data synthesis was performed.

RESULTS

Eleven studies were included in the final analysis. 10/11 studies were in East Asian populations. 4/11 studies investigated STAS, 6/11 investigated adenocarcinoma invasiveness or growth pattern, and 1/11 investigated LVI. No studies investigating TIL or tumour necrosis met inclusion criteria. Studies were of generally mixed to poor methodological quality. Reported accuracies for radiomic models ranged from 0.67 to 0.94.

CONCLUSION

Due to the high risk of bias and concerns regarding applicability, the evidence is inconclusive as to whether radiomic features can accurately predict prognostically important histopathological features of cancer aggressiveness. Many studies were excluded due to lack of external validation. Rigorously conducted prospective studies with sufficient external validity will be required for radiomic models to play a role in improving lung cancer outcomes.

Spread Through Air Spaces in Stage I Pulmonary Large Cell Neuroendocrine Carcinoma

BACKGROUND

Pulmonary large cell neuroendocrine carcinoma (LCNEC) represents an exceptionally aggressive and infrequent variant within the realm of non-small cell lung cancer, necessitating surgical intervention as the primary therapeutic approach. However, the postoperative management strategy for early-stage patients continues to be a subject of intense debate and uncertainty.

METHODS

A retrospective analysis was conducted on a cohort of patients diagnosed with LCNEC who underwent surgical resection at Shanghai Pulmonary Hospital between July 2018 and June 2022. Comprehensive assessments, encompassing univariate and multivariate analyses, were performed to evaluate the prognostic significance of these indicators in patient clinical profiles, overall survival (OS), and disease-free survival (DFS).

RESULTS

A comprehensive screening effort identified 171 patients with LCNEC, with 70 stage I patients meeting the criteria for inclusion in the final cohort. Of these, 11 patients (15.7%) presented with combined LCNEC, and 59 (84.3%) exhibited pure LCNEC. Univariate and multivariate analyses both unveiled that spread through air spaces (STAS) status emerged as an independent prognostic determinant for both DFS (P = .003) and OS (P = .013), whereas histologic subtype independently predicted OS (P = .011). Subgroup survival analyses further underscored that the advantageous effects of postoperative chemotherapy were significantly pronounced exclusively among STAS-positive patients, showcasing a statistically significant enhancement in DFS (P = .047) and OS (P = .018).

CONCLUSIONS

STAS may serve as an adverse prognostic factor in stage I LCNEC patients, potentially offering guidance for postoperative chemotherapy decisions.

The International Association for the Study of Lung Cancer (IASLC) Staging Project for Lung Cancer: Recommendation to Introduce Spread Through Air Spaces as a Histologic Descriptor in the Ninth Edition of the TNM Classification of Lung Cancer. Analysis of 4061 Pathologic Stage I NSCLC

INTRODUCTION

Spread through air spaces (STAS) consists of lung cancer tumor cells that are identified beyond the edge of the main tumor in the surrounding alveolar parenchyma. It has been reported by meta-analyses to be an independent prognostic factor in the major histologic types of lung cancer, but its role in lung cancer staging is not established.

METHODS

To assess the clinical importance of STAS in lung cancer staging, we evaluated 4061 surgically resected pathologic stage I R0 NSCLC collected from around the world in the International Association for the Study of Lung Cancer database. We focused on whether STAS could be a useful additional histologic descriptor to supplement the existing ones of visceral pleural invasion (VPI) and lymphovascular invasion (LVI).

RESULTS

STAS was found in 930 of 4061 of the pathologic stage I NSCLC (22.9%). Patients with tumors exhibiting STAS had a significantly worse recurrence-free and overall survival in both univariate and multivariable analyses involving cohorts consisting of all NSCLC, specific histologic types (adenocarcinoma and other NSCLC), and extent of resection (lobar and sublobar). Interestingly, STAS was independent of VPI in all of these analyses.

CONCLUSIONS

These data support our recommendation to include STAS as a histologic descriptor for the Ninth Edition of the TNM Classification of Lung Cancer. Hopefully, gathering these data in the coming years will facilitate a thorough analysis to better understand the relative impact of STAS, LVI, and VPI on lung cancer staging for the Tenth Edition TNM Stage Classification.

Clinical Importance of Grading Tumor Spread through Air Spaces in Early-Stage Small-Lung Adenocarcinoma

This study aimed to identify the clinical manifestation and implications according to the grading of tumor spread through air spaces in early-stage small (≤2 cm) pathological stage I non-mucinous lung adenocarcinomas. Medical records of patients with pathological stage I tumors sized ≤2 cm were retrospectively reviewed and analyzed. The furthest distance of the spread through air spaces from the tumor margin was measured on a standard-length scale (mm). Enrolled patients were categorized into spread through air spaces (STAS) (-) and STAS (+), and STAS (+) was subdivided according to its furthest distance as follows: STAS (+)-L (<2 mm) and STAS (+)-H (≥2 mm). Risk factors for STAS (+) included papillary predominant subtype (p = 0.027), presence of micropapillary patterns (p < 0.001), and EGFR (p = 0.039). The overall survival of the three groups did not differ significantly (p = 0.565). The recurrence-free survival of STAS (+)-H groups was significantly lower than those of STAS (-) and STAS (+)-L (p < 0.001 and p = 0.039, respectively). A number of alveolar spaces were definite risk factors for STAS (+)-H groups (p < 0.001), and male gender could be one (p = 0.054). In the patient group with small (≤2 cm) pathological stage I lung adenocarcinomas, the presence of STAS ≥ 2 mm was related to significantly lower recurrence-free survival. For identifying definite risk factors for the presence of farther STAS, more precise analysis from a larger study population should be undertaken.

Spread Through Air Spaces in Stage I to III Resected Lung Adenocarcinomas: Should the Presence of Spread Through Air Spaces Lead to an Upstaging?

In recent years, the concept of spread through air spaces (STAS) has been discussed as an adverse prognostic factor for lung cancer. The aim of our study is to clarify the prognostic role of STAS in relation to the main recognized prognostic factors in a retrospective cohort of 330 European patients who underwent stages I to III lung adenocarcinoma resection. On univariate analysis, the presence of STAS was related to progression-free survival (PFS; hazard ratio [HR]: 1.48; 95% CI: 1.02-2.19; P = 0.038) and overall survival (OS; HR: 1.61; 95% CI: 1.03-2.52; P = 0.50). On multivariate analysis, STAS was related to PFS (HR: 1.51; 95% CI: 1.00-2.17; P = 0.050) and to OS (HR: 1.67; 95% CI: 1.00-2.81; P = 0.050). We showed that the presence of STAS was associated with lower PFS, equivalent to the next pathologic T stage, especially the median PFS of T3 stages without STAS was at 62.8 months while the median PFS of T3 stages with STAS was at 15.7 months, closer to the median PFS of 17.4 months in T4 stages. To conclude, STAS is an independent prognostic factor of PFS in this European cohort and is close to significance for OS. We suggest that the presence of STAS might lead to an upstaging of lung adenocarcinoma.

Preoperative nomogram for predicting spread through air spaces in clinical-stage IA non-small cell lung cancer using 18F-fluorodeoxyglucose positron emission tomography/computed tomography

PURPOSE

This study aims to assess the predictive value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) radiological features and the maximum standardized uptake value (SUVmax) in determining the presence of spread through air spaces (STAS) in clinical-stage IA non-small cell lung cancer (NSCLC).

METHODS

A retrospective analysis was conducted on 180 cases of NSCLC with postoperative pathological assessment of STAS status, spanning from September 2019 to September 2023. Of these, 116 cases from hospital one comprised the training set, while 64 cases from hospital two formed the testing set. The clinical information, tumor SUVmax, and 13 related CT features were analyzed. Subgroup analysis was carried out based on tumor density type. In the training set, univariable and multivariable logistic regression analyses were employed to identify the most significant variables. A multivariable logistic regression model was constructed and the corresponding nomogram was developed to predict STAS in NSCLC, and its diagnostic efficacy was evaluated in the testing set.

RESULTS

SUVmax, consolidation-to-tumor ratio (CTR), and lobulation sign emerged as the best combination of variables for predicting STAS in NSCLC. Among these, SUVmax and CTR were identified as independent predictors for STAS prediction. The constructed prediction model demonstrated area under the curve (AUC) values of 0.796 and 0.821 in the training and testing sets, respectively. Subgroup analysis revealed a 2.69 times higher STAS-positive rate in solid nodules compared to part-solid nodules. SUVmax was an independent predictor for predicting STAS in solid nodular NSCLC, while CTR and an emphysema background were independent predictors for STAS in part-solid nodular NSCLC.

CONCLUSION

Our nomogram based on preoperative 18F-FDG PET/CT radiological features and SUVmax effectively predicts STAS status in clinical-stage IA NSCLC. Furthermore, our study highlights that metabolic parameters and CT variables associated with STAS differ between solid and part-solid nodular NSCLC.

Predictive value of CT and 18F-FDG PET/CT features on spread through air space in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma, a leading cause of cancer-related mortality, demands precise prognostic indicators for effective management. The presence of spread through air space (STAS) indicates adverse tumor behavior. However, comparative differences between 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography(PET)/computed tomography(CT) and CT in predicting STAS in lung adenocarcinoma remain inadequately explored. This retrospective study analyzes preoperative CT and 18F-FDG PET/CT features to predict STAS, aiming to identify key predictive factors and enhance clinical decision-making.

METHODS

Between February 2022 and April 2023, 100 patients (108 lesions) who underwent surgery for clinical lung adenocarcinoma were enrolled. All these patients underwent 18F-FDG PET/CT, thin-section chest CT scan, and pathological biopsy. Univariate and multivariate logistic regression was used to analyze CT and 18F-FDG PET/CT image characteristics. Receiver operating characteristic curve analysis was performed to identify a cut-off value.

RESULTS

Sixty lesions were positive for STAS, and 48 lesions were negative for STAS. The STAS-positive was frequently observed in acinar predominant. However, STAS-negative was frequently observed in minimally invasive adenocarcinoma. Univariable analysis results revealed that CT features (including nodule type, maximum tumor diameter, maximum solid component diameter, consolidation tumor ratio, pleural indentation, lobulation, spiculation) and all 18F-FDG PET/CT characteristics were statistically significant difference in STAS-positive and STAS-negative lesions. And multivariate logistic regression results showed that the maximum tumor diameter and SUVmax were the independent influencing factors of CT and 18F-FDG PET/CT in STAS, respectively. The area under the curve of maximum tumor diameter and SUVmax was 0.68 vs. 0.82. The cut-off value for maximum tumor diameter and SUVmax was 2.35 vs. 5.05 with a sensitivity of 50.0% vs. 68.3% and specificity of 81.2% vs. 87.5%, which showed that SUVmax was superior to the maximum tumor diameter.

CONCLUSION

The radiological features of SUVmax is the best model for predicting STAS in lung adenocarcinoma. These radiological features could predict STAS with excellent specificity but inferior sensitivity.

Prognosis of spread through air spaces in invasive mucinous lung adenocarcinoma after curative surgery

INTRODUCTION

The purpose of this study is to investigate the prognostic impact of spread through air spaces (STAS) in invasive mucinous adenocarcinoma (IMA).

MATERIALS AND METHODS

From 2015 to 2019, patients who underwent complete resection of IMA were extracted from the prospective database. Multivariable Cox-regression analysis and inverse probability of treatment weight (IPTW) - adjusted log-rank test for 5-year recurrence-free survival (RFS) were performed.

RESULTS

STAS was observed in 39.1% (53 out of 133). The STAS (+) group shows larger tumor size (2.9 ± 2.4 cm vs 3.8 ± 2.4 cm, p = 0.031) and higher incidence of lympho-vascular invasion (6 [7.5%] vs 18 [34.0%], p < 00.001) compared to the STAS (-) group. The 5-year RFS was 66.1% in the STAS (+) group and 91.8% in the STAS (-) group (p < 00.001), and the incidence of locoregional recurrence was significantly higher in the STAS (+) group than the STAS (-) group (1 [1.2%] vs 12 [22.6%], p < 00.001). Multivariable analysis revealed that STAS was associated with poor prognosis for all-recurrence (hazard ratio 2.81, 95% confidence interval 1.01-7.81, p = 0.048). After IPTW adjustment, 5-year RFS was 66.3% in the STAS (+) group and 92.9% in the STAS (-) group (p = 0.007), and risk for locoregional recurrence was greater in the STAS (+) group than the STAS (-) group (1.1 [0.9%] vs 20.8 [16.6%], p < 00.001).

CONCLUSIONS

STAS showed negative prognostic impact on all-recurrence, especially due to locoregional recurrence, after curative resection of IMA.

CT-Based Intratumoral and Peritumoral Radiomics Nomograms for the Preoperative Prediction of Spread Through Air Spaces in Clinical Stage IA Non-small Cell Lung Cancer

The study aims to investigate the value of intratumoral and peritumoral radiomics and clinical-radiological features for predicting spread through air spaces (STAS) in patients with clinical stage IA non-small cell lung cancer (NSCLC). A total of 336 NSCLC patients from our hospital were randomly divided into the training cohort (n = 236) and the internal validation cohort (n = 100) at a ratio of 7:3, and 69 patients from the other two external hospitals were collected as the external validation cohort. Univariate and multivariate analyses were used to select clinical-radiological features and construct a clinical model. The GTV, PTV5, PTV10, PTV15, PTV20, GPTV5, GPTV10, GPTV15, and GPTV20 models were constructed based on intratumoral and peritumoral (5 mm, 10 mm, 15 mm, 20 mm) radiomics features. Additionally, the radscore of the optimal radiomics model and clinical-radiological predictors were used to construct a combined model and plot a nomogram. Lastly, the ROC curve and AUC value were used to evaluate the diagnostic performance of the model. Tumor density type (OR = 6.738) and distal ribbon sign (OR = 5.141) were independent risk factors for the occurrence of STAS. The GPTV10 model outperformed the other radiomics models, and its AUC values were 0.887, 0.876, and 0.868 in the three cohorts. The AUC values of the combined model constructed based on GPTV10 radscore and clinical-radiological predictors were 0.901, 0.875, and 0.878. DeLong test results revealed that the combined model was superior to the clinical model in the three cohorts. The nomogram based on GPTV10 radscore and clinical-radiological features exhibited high predictive efficiency for STAS status in NSCLC.

Development and validation of a clinic-radiological model to predict tumor spread through air spaces in stage I lung adenocarcinoma

OBJECTIVES

Tumor spread through air spaces (STAS) is associated with poor prognosis and impacts surgical options. We aimed to develop a user-friendly model based on 2-[18F] FDG PET/CT to predict STAS in stage I lung adenocarcinoma (LAC).

MATERIALS AND METHODS

A total of 466 stage I LAC patients who underwent 2-[18F] FDG PET/CT examination and resection surgery were retrospectively enrolled. They were split into a training cohort (n = 232, 20.3% STAS-positive), a validation cohort (n = 122, 27.0% STAS-positive), and a test cohort (n = 112, 29.5% STAS-positive) according to chronological order. Some commonly used clinical data, visualized CT features, and SUVmax were analyzed to identify independent predictors of STAS. A prediction model was built using the independent predictors and validated using the three chronologically separated cohorts. Model performance was assessed using ROC curves and calculations of AUC.

RESULTS

The differences in age (P = 0.009), lesion density subtype (P < 0.001), spiculation sign (P < 0.001), bronchus truncation sign (P = 0.001), and SUVmax (P < 0.001) between the positive and negative groups were statistically significant. Age ≥ 56 years [OR(95%CI):3.310(1.150-9.530), P = 0.027], lesion density subtype (P = 0.004) and SUVmax ≥ 2.5 g/ml [OR(95%CI):3.268(1.021-1.356), P = 0.005] were the independent factors predicting STAS. Logistic regression was used to build the A-D-S (Age-Density-SUVmax) prediction model, and the AUCs were 0.808, 0.786 and 0.806 in the training, validation, and test cohorts, respectively.

CONCLUSIONS

STAS was more likely to occur in older patients, in solid lesions and higher SUVmax in stage I LAC. The PET/CT-based A-D-S prediction model is easy to use and has a high level of reliability in diagnosing.

Secret learning for lung cancer diagnosis-a study with homomorphic encryption, texture analysis and deep learning

Advanced lung cancer diagnoses from radiographic images include automated detection of lung cancer from CT-Scan images of the lungs. Deep learning is a popular method for decision making which can be used to classify cancerous and non-cancerous lungs from CT-Scan images. There are many experiments which show the uses of deep learning for performing such classifications but very few of them have preserved the privacy of users. Among existing methods, federated learning limits data sharing to a central server and differential privacy although increases anonymity the original data is still shared. Homomorphic encryption can resolve the limitations of both of these. Homomorphic encryption is a cryptographic technique that allows computations to be performed on encrypted data. In our experiment, we have proposed a series of textural information extraction with the implementation of homomorphic encryption of the CT-Scan images of normal, adenocarcinoma, large cell carcinoma and squamous cell carcinoma. We have further processed the encrypted data to make it classifiable and later we have classified it with deep learning. The results from the experiments have obtained a classification accuracy of 0.9347.

Clinicopathological and computed tomography features associated with recurrence-free survival of patients with small-sized peripheral invasive lung adenocarcinoma after sublobectomy

Background

Sublobar resection is gradually becoming a standard treatment for small-sized (≤2 cm) peripheral non-small cell lung cancer (NSCLC), with lung adenocarcinoma (LADC) being the most frequent histologic subtype. However, the prognostic predictors for preoperatively determining whether sublobectomy is feasible for patients with early LADC have not yet been well identified. Therefore, this study aimed to investigate the clinicopathological and computed tomography (CT) features associated with the recurrence-free survival (RFS) of patients with small-sized invasive LADC (SILADC) after sublobar resection.

Methods

This retrospective cohort study analyzed 107 patients with SILADC who underwent preoperative chest CT scan and sublobar resection from December 2012 to March 2019. The Kaplan-Meier survival was used to analyze the relationship between clinicopathological characteristics, preoperative chest CT findings, and RFS. The Cox proportional hazards regression was used to identify independent prognostic factors of poor RFS.

Results

For clinicopathological characteristics, RFS was shorter in patients aged ≥70 years, smokers, and those with micropapillary/solid-predominant adenocarcinomas (all P values <0.05). For preoperative CT features, RFS was shorter in patients with tumor size ≥1.4 cm, solid component size ≥1.1 cm, proportion of solid component ≥72%, solid density, spiculation, vascular convergence sign, peripheral fibrosis, and type II pleural tag (all P values <0.05). Multivariate analysis showed proportion of solid component ≥72% [hazard ratio (HR): 5.920; P=0.006; 95% confidence interval (CI): 1.686-20.794], spiculation (HR: 5.026; P=0.001; 95% CI: 2.008-12.581), and type II pleural tag (HR: 4.638; P=0.002; 95% CI: 1.773-12.136) were independent risk factors for poor prognosis in patients with SILADC after sub-lobectomy.

Conclusions

Clinicopathological and CT characteristics are helpful for predicting the RFS of patients with SILADC after sublobar resection and can be used as an auxiliary tool for thoracic surgeons to choose the best surgical mode.

An individualized nomogram for predicting and validating spread through air space (STAS) in surgically resected lung adenocarcinoma: a single center retrospective analysis

OBJECTIVE

A single-center study was conducted to explore the association between STAS and other clinical features in surgically resected adenocarcinoma to enhance our current understanding of STAS.

METHODS

We retrospectively enrolled patients with lung adenocarcinoma (n = 241) who underwent curative surgeries. Patients undergoing surgery in 2019 were attributed to the training group (n = 188) and those undergoing surgery in January 2022 to June 2022 were attributed to the validation (n = 53) group. Univariate and multivariate logistic regression analyses were used to identify predictive factors for STAS, which were used to construct a simple nomogram. Furthermore, ROC and calibration curves were used to evaluate the performance of the nomogram. In addition, we conducted decision curve analysis (DCA) to assess the clinical utility of this nomogram.

RESULTS

In our cohort, 52 patients were identified as STAS-positive (21.6%). In univariate analysis, STAS was significantly associated with age, surgical approach, CEA, CTR (Consolidation Tumor Ratio), TNM stage, tumor grade, gross tumor size, resection margin, vessel cancer embolus, pleural invasion, lymph node metastasis, high ki67 and positive PD-L1 staining (P < 0.05). Lower age, CTR > 0.75, vessel cancer embolus, high Ki67 and PD-L1 stain positive were significant predictors for STAS during multivariate logistics analysis. A simple nomogram was successfully constructed based on these five predictors. The AUC values of our nomogram for the probability of tumor STAS were 0.860 in the training group and 0.919 in the validation group. In addition, the calibration curve and DCA validated the good performance of this model.

CONCLUSION

A nomogram was successfully constructed to identify the presence of STAS in surgically resected lung adenocarcinoma patients.

Prognostic significance of limited resection in pathologic stage I lung adenocarcinoma with spread through air spaces

Background

Tumor spread through air spaces (STAS) is now recognized as tumor invasion. However, the association between STAS and procedure-specific outcomes (limited resection and lobectomy) in patients with pathologic stage I lung adenocarcinoma (ADC) is still under investigation.

Methods

To investigate whether limited resection predicts poorer survival in such patients, we retrospectively analyzed the clinicopathologic features of a large cohort of 1,566 patients with stage I ADC from 2017 to 2020 and classified them according to STAS status and surgical method. Kaplan-Meier, Cox hazard proportional regression, and propensity score matching (PSM) were adopted for prognostic evaluation.

Results

STAS-positive patients had worse recurrence-free survival (RFS) (P<0.001). There was no significant difference in RFS and overall survival (OS) between limited resection and lobectomy, neither for the STAS-negative nor STAS-positive group before matching. After matching, limited resection was found to achieve comparable RFS to lobectomy in STAS-positive patients with pathologic I, IA, or IB stage tumor, (P=0.816, P=0.576, P=0.281, respectively), but worse OS in stage I and stage IB patients (P=0.029, P=0.010, respectively). Furthermore, in multivariable analysis, limited resection was not an independent prognostic factor of RFS or OS. Instead, the high-grade histological subtype was the only independent prognostic factor for RFS (P=0.001). In the subgroup analysis, adjuvant chemotherapy (ACT) did not improve the outcomes of stage IB STAS-positive patients.

Conclusions

Limited resection was associated with worse survival than lobectomy in stage I STAS-positive patients, but not in stage IA STAS-positive patients.

CT-based radiomics model to predict spread through air space in resectable lung cancer

BACKGROUND

Spread through air space (STAS) has been identified as a pathological pattern associated with lung cancer progression. Patients with STAS were related to a worse prognosis compared with patients without STAS. The objective of this study was to establish a radiomics model capable of forecasting STAS before surgery, which can assist surgeons in selecting the most appropriate operation type for patients with STAS.

METHOD

There were 537 eligible patients retrospectively included in this study. ROI segmentation was performed manually on all CT images to identify the region of interest. From each segmented lesion, a total of 1688 features were extracted. The tumor size, maximum tumor diameters, and tumor type were also recorded. Using Spearman's correlation coefficient to calculate the correlation and redundancy of elements, and redundant features less than 0.80 were removed. In order to reduce the level of overfitting and avoid statistical biases, a dimension reduction process of the dataset was conducted to decrease the number of features. Finally, a radiomics model included 44 features was established to predict STAS. To evaluate the performance of the model, the receiver operating characteristic (ROC) curve was used, and the area under the curve (AUC) was calculated, and the accuracy of the model was verified by 10-fold cross-validation.

RESULTS

The incidence of STAS was 38.2% (205/537). The tumor type, maximum tumor diameters, and consolidation tumor ratio were significantly different between STAS group and non-STAS group. The training group included 430 patients, while the test group was consisted with 107. The training group achieved an AUC of 0.825 (sensitivity, 0.875; specificity, 0.621; and accuracy, 0.749) and the test group had an AUC of 0.802 (sensitivity, 0.797; specificity,0.688; and accuracy, 0.748). The 10-fold cross-validation had an AUC of 0.834.

CONCLUSION

CT-based radiomic model can predict STAS effectively, which is of great importance to guide the selection of operation types before surgery.

Evolutionary characterization of lung adenocarcinoma morphology in TRACERx

Lung adenocarcinomas (LUADs) display a broad histological spectrum from low-grade lepidic tumors through to mid-grade acinar and papillary and high-grade solid, cribriform and micropapillary tumors. How morphology reflects tumor evolution and disease progression is poorly understood. Whole-exome sequencing data generated from 805 primary tumor regions and 121 paired metastatic samples across 248 LUADs from the TRACERx 421 cohort, together with RNA-sequencing data from 463 primary tumor regions, were integrated with detailed whole-tumor and regional histopathological analysis. Tumors with predominantly high-grade patterns showed increased chromosomal complexity, with higher burden of loss of heterozygosity and subclonal somatic copy number alterations. Individual regions in predominantly high-grade pattern tumors exhibited higher proliferation and lower clonal diversity, potentially reflecting large recent subclonal expansions. Co-occurrence of truncal loss of chromosomes 3p and 3q was enriched in predominantly low-/mid-grade tumors, while purely undifferentiated solid-pattern tumors had a higher frequency of truncal arm or focal 3q gains and SMARCA4 gene alterations compared with mixed-pattern tumors with a solid component, suggesting distinct evolutionary trajectories. Clonal evolution analysis revealed that tumors tend to evolve toward higher-grade patterns. The presence of micropapillary pattern and 'tumor spread through air spaces' were associated with intrathoracic recurrence, in contrast to the presence of solid/cribriform patterns, necrosis and preoperative circulating tumor DNA detection, which were associated with extra-thoracic recurrence. These data provide insights into the relationship between LUAD morphology, the underlying evolutionary genomic landscape, and clinical and anatomical relapse risk.

Comprehensive molecular characterizations of stage I-III lung adenocarcinoma with tumor spread through air spaces

Purpose: The aim of this study is to investigate integrative genomic spectra of stage I-III lung adenocarcinoma with tumor spread through air spaces (STAS). Methods: We retrospectively identified 442 surgically resected lung adenocarcinoma patients of pathological stage I-III in Shanghai Chest Hospital from January 2018 to February 2021. Surgically resected tissues were used for next-generation sequencing (NGS) with a panel of 68 lung cancer-related genes to profile comprehensive molecular characterizations. Results: A total of 442 cases were analyzed, including 221 (50%) STAS-positive (SP) and 221 (50%) STAS-negative (SN) lung adenocarcinoma patients. In total, 440 cases (99.6%) were positive for the overall mutational spectrum, and the higher mutational genes were EGFR, TP53, KRAS, ALK, SMAD4, and ERBB2 (62%, 42%, 14%, 10%, 7%, and 7%, respectively). Compared with the SN population, there was significantly lower EGFR alteration in the single-nucleotide variant (SNV) mutation spectrum (52.5% vs 69.7%, p < 0.001) and significantly higher TP53 alteration in the SP population (49.8% vs 34.8%, p = 0.002). EGFR L858R missense mutation (19.5% vs 37.6%, p < 0.001) and ERBB2 exon 20 indel mutation (1.8% vs 5.9%, p = 0.045) were more frequent in the SN population. The detection rate of ALK fusion rearrangements in the SP population was significantly higher than that in the SN population (13.1% vs 2.3%, p < 0.001). In the analysis of signaling pathways, no significant difference was discovered between SP and SN patients. No difference in 1-year disease-free survival was observed between SP and SN patients in this study. Conclusion: Significant differences exist in stage I-III lung adenocarcinoma patients with STAS in molecular characterizations.

Comprehensive analysis for clarifying transcriptomics landscapes of spread through air spaces in lung adenocarcinoma

Patients with spread through air spaces (STAS) have worse postoperative survival and a higher recurrence rate in lung adenocarcinoma, even in the earliest phases of the disease. At present, the molecular pathogenesis of STAS is not well understood. Therefore, to illustrate the underlying pathogenic mechanism of STAS, we accomplished a comprehensive analysis of a microarray dataset of STAS. Differential expression analysis revealed 841 differentially expressed genes (DEGs) between STAS_positive and STAS_negative groups. Additionally, we acquired two hub genes associated with survival. Gene set variation analysis (GSVA) confirmed that the main differential signaling pathways between the two groups were hypoxia VHL targets, PKC, and pyrimidine metabolism pathways. Analysis of immune activity showed that the increased expression of MHC-class-Ⅰ was observed in the STAS_positive group. These findings provided novel insights for a better knowledge of pathogenic mechanisms and potential therapeutic markers for STAS treatment.

Impact of preoperative biopsy on tumor spread through air spaces in stage I non-small cell lung cancer: a propensity score-matched study

Background

Percutaneous needle biopsy (PNB) and bronchoscopic biopsy (BB) are widely used in the preoperative diagnosis of pulmonary nodules, but whether PNB or BB may cause tumor spread through air spaces (STAS) has not been reported.

Methods

433 postoperative patients with pathological stage I non-small cell lung cancer (NSCLC) from January 2015 to December 2018 at our hospital were enrolled and divided into PNB group (n = 40), BB group (n = 48) and non-biopsy group (n = 345). The PNB and BB groups were matched using propensity score matched (PSM) separately from the non-biopsy group, after which the effects of PNB and BB on STAS, recurrence-free survival (RFS) and overall survival (OS) were assessed.

Results

After PSM for 9 confounding factors (gender, age, smoking history, tumor site, scope of surgery, pathology type, stage, maximum tumor diameter and postoperative treatment), 38 cases in the PNB group were successfully matched with 38 cases in the non-biopsy group and 28 cases in the BB group were successfully matched with 28 cases in the non-biopsy group. After PSM, there was no significant difference in the incidence of STAS between the PNB and non-biopsy groups (42.1% vs. 34.2%, P > 0.05) and between the BB and non-biopsy groups (42.9% vs. 46.4%, P > 0.05). The results after PSM showed no significant effect of both PNB and BB on RFS and OS after radical surgery (P > 0.05).

Conclusion

Preoperative biopsy in patients with stage I NSCLC has not been shown to increase the occurrence of STAS, nor postoperative recurrence and death.

Spread Through Air Spaces (STAS) Is an Independent Prognostic Factor in Resected Lung Squamous Cell Carcinoma

Objective: There is no histoprognostic grading for lung squamous cell carcinoma (LUSC). Different prognostic factors have been described in the recent literature and are not always studied in parallel. Our objective was to search for morphological histopathological prognostic factors in LUSC. Materials and Methods: In this single-center retrospective study of 241 patients, all patients with LUSC who underwent surgical excision over a 12-year period were included. The primary endpoint was 5-year overall survival. Results: STAS was present in 86 (35.7%) patients. The presence of Spread Through Air Spaces (STAS) was correlated with tumor location (p < 0.001), pathological stage (p = 0.039), tumor differentiation (p = 0.029), percentage of necrosis (p = 0.004), presence of vascular and/or lymphatic emboli, budding (p = 0.02), single cell invasion (p = 0.002) and tumor nest size (p = 0.005). The percentage of tumor necrosis was correlated with the overall survival at 5 years: 44.6% of patients were alive when the percentage of necrosis was ≥50%, whereas 68.5% were alive at 5 years when the necrosis was <30% (p < 0.001). When vasculolymphatic emboli were present, the percentage of survival at 5 years was 42.5% compared to 65.5% when they were absent (p = 0.002). The presence of isolated cell invasion was correlated with a lower 5-year survival rate: 51.1% in the case of presence, versus 66% in the case of absence (p = 0.02). In univariate analysis, performance status, pathological stage pT or pN, pleural invasion, histopathological subtype, percentage of tumor necrosis, vasculolymphatic invasion, single-cell invasion, budding and tumor nest size correlated with the percentage of survival at 5 years. On multivariate analysis, only STAS > 3 alveoli (HR, 2.74; 95% CI, 1.18−6.33) was related to overall survival. Conclusion: In conclusion, extensive STAS is an independent factor of poor prognosis in LUSC. STAS is correlated with the presence of other poor prognostic factors such as emboli and pleural invasion and would reflect greater tumor aggressiveness.

Clinicopathological Impact of the Spread through Air Space in Non-Small Cell Lung Cancer: A Meta-Analysis

This study aimed to elucidate the clinicopathological significance of spread through air space (STAS) in non-small cell lung cancer (NSCLC) through a meta-analysis. Using 47 eligible studies, we obtained the estimated rates of STAS in various histological subtypes of NSCLC and compared the clinicopathological characteristics and prognosis between NSCLC with and without STAS. The estimated STAS rate was 0.368 (95% confidence interval [CI], 0.336–0.0.401) in patients with NSCLC. Furthermore, the STAS rates for squamous cell carcinoma and adenocarcinoma were 0.338 (95% CI, 0.273–0.411) and 0.374 (95% CI, 0.340–0.409), respectively. Among the histological subtypes of adenocarcinoma, micropapillary-predominant tumors had the highest rate of STAS (0.719; 95% CI, 0.652–0.778). The STAS rates of solid- and papillary-predominant adenocarcinoma were 0.567 (95% CI, 0.478–0.652) and 0.446 (95% CI, 0.392–0.501), respectively. NSCLCs with STAS showed a higher visceral pleural, venous, and lymphatic invasion than those without STAS. In addition, anaplastic lymphoma kinase mutations and ROS1 rearrangements were significantly more frequent in NSCLCs with STAS than in those without STAS. The presence of STAS was significantly correlated with worse overall and recurrence-free survival (hazard ratio, 2.119; 95% CI, 1.811–2.480 and 2.372; 95% CI, 2.018–2.788, respectively). Taken together, the presence of STAS is useful in predicting the clinicopathological significance and prognosis of patients with NSCLC.

Poor Prognosis of Grade 2 Spread Through Air Spaces in Neuroendocrine Tumors

Background

Spread through air spaces (STAS) has recently emerged as a prognostic factor in lung adenocarcinoma, but little is known about the association of STAS and its grade with recurrence in neuroendocrine tumors (NETs). This study investigated the prognostic effect of STAS grade in NETs after curative resection.

Methods

Seventy-seven patients were retrospectively reviewed, including 9 with typical carcinoid (TC), 6 with atypical carcinoid (AC), 26 with large cell neuroendocrine carcinoma (LCNEC), and 36 with small cell carcinoma (SCC). STAS was defined as the presence of floating tumor cells within air spaces in the lung parenchyma beyond the edge of the main tumor. STAS was classified as grade 1 or 2 depending on whether it was found within or beyond one ×10 objective lens field away from the main tumor margin, respectively.

Results

Fifty-four patients (70%) had STAS, including 22% with TC, 50% with AC, 69% with LCNEC, and 86% with SCC. Patients with STAS had more nodal metastasis, lymphatic and vascular invasion, tumor necrosis, and tumor subtypes other than TC. Among STAS cases, grade 2 STAS was present in 33% of AC, 78% of LCNEC, and 87% of SCC. The 5-year recurrence-free survival (RFS) rate was 81%, 63%, and 35% in patients with no STAS, grade 1, and grade 2 STAS, respectively. Multivariate analysis found that grade 2 STAS was an independent negative prognostic factor for RFS.

Conclusion

Although STAS itself was not associated with a poor prognosis, grade 2 STAS was an independent negative prognostic factor for RFS.

[Research Progress on Spread Through Air Spaces of Lung Cancer]

The concept of spread through air spaces (STAS) was first proposed in the World Health Organization (WHO) Classification of Tumors of the Lung, Pleura, Thymus and Heart (version 2015). STAS is defined as the micropapillary clusters, solid nests or single cells of tumor that exist in the air spaces of the surrounding lung parenchyma beyond the edge of the main tumor. Meanwhile, apart from the traditional invasion modes of lung adenocarcinoma (interstitial, visceral pleura and lym-phovascular invasion), STAS has been identified as the fourth invasion mode of lung adenocarcinoma. In recent years, the research on STAS has been a hot spot in the field of lung adenocarcinoma. The existence of STAS is related to lung cancer histopathology, gene mutation and other factors, and many studies have also confirmed that it can be used as an independent factor for tumor recurrence and prognosis. However, according to some studies, human factors can cause morphological artifacts of STAS, which still needs to be distinguished in clinical work. This paper reviews the research progress of STAS classification, related pathological features, genetic status changes, and human factors that may cause STAS artifacts.
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A case of haemoptysis and bilateral areas of lung consolidation sparing the right lower lobe

Multiple primary lung cancers (MPLC) are often neglected. Obtaining pre-operative specimens through bronchoscopy could play a role. It is important to distinguish aerogenous metastasis from MPLC in the adenocarcinoma spectrum due to the different prognosis.https://bit.ly/3zbdVrw

Prognostic implication of tumor spread through air spaces in patients with pathologic N0 lung adenocarcinoma

OBJECTIVES

Tumor spread through air spaces (STAS) has been identified as an invasive pattern in lung adenocarcinoma (ADC), but the prognostic implication of STAS has not been well studied in patients with pathologic N0 lung ADC. The purpose of this study was to evaluate the prognostic implication of STAS in pathologic N0 lung ADC patients after radical surgery.

MATERIALS AND METHODS

Between January 2017 and December 2018, 796 patients with completely resected pathologic N0 lung ADC were reviewed. Pearson's chi-square test or Fisher exact test was used for comparing the relationship between STAS and clinicopathological features. The log-rank test and multivariate Cox regression models were used to explore prognostic factors.

RESULTS

Among the 796 patients, STAS was positive in 201 patients (25.3%). The presence of STAS was significantly associated with patients with solid nodules (P < 0.001), micropapillary pattern-predominant adenocarcinoma/solid pattern-predominant adenocarcinoma (P < 0.001), larger tumor size (P < 0.001), visceral pleural invasion (P < 0.001) and lymphovascular invasion (P < 0.001). Multivariable analysis showed that STAS was an independent prognostic factor for recurrence-free survival (RFS) in pathologic N0 lung ADC patients (P = 0.014). For patients with acinar pattern-predominant adenocarcinoma (APA) / papillary pattern-predominant adenocarcinoma (PPA) / invasive mucinous adenocarcinoma (IMA) and patients who underwent lobectomy, STAS was an independent prognostic factor for RFS (P = 0.015, P = 0.011; respectively) and overall survival (OS) (P = 0.038, P = 0.020; respectively).

CONCLUSION

In this study, STAS was an independent prognostic factor for RFS in pathologic N0 lung adenocarcinomas, and it was also an independent prognostic factor for RFS and OS in patients with APA/PPA/IMA and those who received lobectomy.

The 2021 WHO Classification of Lung Tumors: Impact of advances since 2015

The 2021 World Health Organisation (WHO) Classification of Thoracic Tumours was published earlier this year, with classification of lung tumors being one of the chapters. The principles remain those of using morphology first, supported by immunohistochemistry and then molecular techniques. In 2015, there was particular emphasis on using immunohistochemistry to make classification more accurate. In 2021, there is greater emphasis throughout the book on advances in molecular pathology across all tumor types. Major features within this edition are 1) broader emphasis on genetic testing than in the 2015 WHO Classification, 2) a chapter entirely dedicated to the classification of small diagnostic samples, 3) continued recommendation to document percentages of histological patterns in invasive non-mucinous adenocarcinomas, with utilization of these features to apply a formal grading system, as well as using only invasive size for T-factor size determination in part lepidic non-mucinous lung adenocarcinomas as recommended by the 8^th Edition TNM Classification, 4) recognition of spread through airspaces (STAS) as a histological feature with prognostic significance, 5) moving lymphoepithelial carcinoma to squamous cell carcinomas, 6) update on evolving concepts in lung neuroendocrine neoplasm classification, 7) recognition of bronchiolar adenoma/ciliated muconodular papillary tumor (BA/CMPT) as a new entity within the adenoma subgroup, 8) recognition of thoracic SMARCA4-deficient undifferentiated tumor, and 9) inclusion of essential and desirable diagnostic criteria for each tumor.

Spread Through Air Spaces (STAS) in Non-Small Cell Lung Carcinoma: Evidence Supportive of an In Vivo Phenomenon

Tumor spread through air spaces (STAS) is associated with locoregional recurrence in patients undergoing limited resection (LR) for non-small cell lung carcinoma (NSCLC). We hypothesized that the observation of STAS in both the initial LR specimen and the additional resection specimen from the same patient, processed using different knives, would provide evidence that STAS is an in vivo phenomenon contributing to locoregional recurrence. We retrospectively identified patients with NSCLC (9 adenocarcinoma, 1 squamous cell carcinoma) who underwent LR, had STAS in the LR specimen, and underwent additional resection (lobectomy or LR). The LR and additional resection specimens from each patient were processed at different times using different tissue-processing knives. All specimens were analyzed for STAS. All 10 patients underwent LR with negative margins (R0). All additional resection specimens had STAS: 8 patients had STAS clusters in their completion lobectomy specimens, and 2 had STAS in their additional LR specimens. In 2 patients, STAS was found in the completion lobectomy specimen only after extensive sampling (>10 sections) from the staple line adjacent to the initial LR. The presence of STAS in both the LR and the additional resection specimen processed using different knives supports the concept that STAS is an in vivo phenomenon, rather than an artifact from tissue processing. This observation indicates that occult STAS tumor cells can be present in the lung tissue of the remaining unresected lobe after LR and supports the concept that STAS is a contributing factor for locoregional recurrence following LR.

Aerogenous Metastasis and Spread Through the Air Spaces - Distinct Entities or Spectrum of the Same Process?

Clinicopathological and imaging studies indicate that metastatic spread of cancer cells through the airways may occur in primary lung cancer. The term aerogenous metastasis was been proposed years before the concept of spread through the airspaces (STAS) was introduced in the current World Health Organization classification. The pathogenesis of STAS has not been fully elucidated. The current definition of STAS is controversial and limited to early stage adenocarcinomas. In this article, existing knowledge on the pathogenesis, histology, imaging findings, and clinical and prognostic significance of these 2 entities is presented.

Automated Analysis of Proliferating Cells Spatial Organisation Predicts Prognosis in Lung Neuroendocrine Neoplasms

Simple Summary

Lung neuroendocrine neoplasms (lung NENs) are categorised by morphology, defining a classification sometimes unable to reflect ultimate clinical outcome, particularly for the intermediate domains of adenocarcinomas and large-cell neuroendocrine carcinomas. Moreover, subjectivity and poor reproducibility characterise diagnosis and prognosis assessment of all NENs. The aim of this study was to design and evaluate an objective and reproducible approach to the grading of lung NENs, potentially extendable to other NENs, by exploring a completely new perspective of interpreting the well-recognised proliferation marker Ki-67. We designed an automated pipeline to harvest quantitative information from the spatial distribution of Ki-67-positive cells, analysing its heterogeneity in the entire extent of tumour tissue—which currently represents the main weakness of Ki-67—and employed machine learning techniques to predict prognosis based on this information. Demonstrating the efficacy of the proposed framework would hint at a possible path for the future of grading and classification of NENs.

Abstract

Lung neuroendocrine neoplasms (lung NENs) are categorised by morphology, defining a classification sometimes unable to reflect ultimate clinical outcome. Subjectivity and poor reproducibility characterise diagnosis and prognosis assessment of all NENs. Here, we propose a machine learning framework for tumour prognosis assessment based on a quantitative, automated and repeatable evaluation of the spatial distribution of cells immunohistochemically positive for the proliferation marker Ki-67, performed on the entire extent of high-resolution whole slide images. Combining features from the fields of graph theory, fractality analysis, stochastic geometry and information theory, we describe the topology of replicating cells and predict prognosis in a histology-independent way. We demonstrate how our approach outperforms the well-recognised prognostic role of Ki-67 Labelling Index on a multi-centre dataset comprising the most controversial lung NENs. Moreover, we show that our system identifies arrangement patterns in the cells positive for Ki-67 that appear independently of tumour subtyping. Strikingly, the subset of these features whose presence is also independent of the value of the Labelling Index and the density of Ki-67-positive cells prove to be especially relevant in discerning prognostic classes. These findings disclose a possible path for the future of grading and classification of NENs.

Radiomics is feasible for prediction of spread through air spaces in patients with nonsmall cell lung cancer

Tumor spread through air spaces (STAS) in non-small-cell lung cancer (NSCLC) is known to influence a poor patient outcome, even in patients presenting with early-stage disease. However, the pre-operative diagnosis of STAS remains challenging. With the progress of radiomics-based analyses several attempts have been made to predict STAS based on radiological findings. In the present study, patients with NSCLC which is located peripherally and tumors ≤ 2 cm in size on computed tomography (CT) that were potential candidates for sublobar resection were enrolled in this study. The radiologic features of the targeted tumors on thin-section CT were extracted using the PyRadiomics v3.0 software package, and a predictive model for STAS was built using the t-test and XGBoost. Thirty-five out of 226 patients had a STAS histology. The predictive model of STAS indicated an area under the receiver-operator characteristic curve (AUC) of 0.77. There was no significant difference in the overall survival (OS) for lobectomy between the predicted-STAS (+) and (−) groups (p = 0.19), but an unfavorable OS for sublobar resection was indicated in the predicted-STAS (+) group (p < 0.01). These results suggest that radiomics with machine-learning helped to develop a favorable model of STAS (+) NSCLC, which might be useful for the proper selection of candidates who should undergo sublobar resection.

Clinical-Pathologic Challenges in the Classification of Pulmonary Neuroendocrine Neoplasms and Targets on the Horizon for Future Clinical Practice

Diagnosing a pulmonary neuroendocrine neoplasm (NEN) may be difficult, challenging clinical decision making. In this review, the following key clinical and pathologic issues and informative molecular markers are being discussed: (1) What is the preferred outcome parameter for curatively resected low-grade NENs (carcinoid), for example, overall survival or recurrence-free interval? (2) Does the WHO classification combined with a Ki-67 proliferation index and molecular markers, such as OTP and CD44, offer improved prognostication in low-grade NENs? (3) What is the value of a typical versus atypical carcinoid diagnosis on a biopsy specimen in local and metastatic disease? Diagnosis is difficult in biopsy specimens and recent observations of an increased mitotic rate in metastatic carcinoid from typical to atypical and high-grade NEN can further complicate diagnosis. (4) What is the (ir)relevance of morphologically separating large cell neuroendocrine carcinoma (LCNEC) SCLC and the value of molecular markers (RB1 gene and pRb protein or transcription factors NEUROD1, ASCL1, POU2F3, or YAP1 [NAPY]) to predict systemic treatment outcome? (5) Are additional diagnostic criteria required to accurately separate LCNEC from NSCLC in biopsy specimens? Neuroendocrine morphology can be absent owing to limited sample size leading to missed LCNEC diagnoses. Evaluation of genomic studies on LCNEC and marker studies have identified that a combination of napsin A and neuroendocrine markers could be helpful. Hence, to improve clinical practice, we should consider to adjust our NEN classification incorporating prognostic and predictive markers applicable on biopsy specimens to inform a treatment outcome-driven classification.

The Evolving Concept of Complete Resection in Lung Cancer Surgery

Simple Summary

In the surgical treatment of lung cancer, the complete removal of the portion of the lung where the cancer is and of the involved adjacent structures is of paramount importance to achieve long-term survival. The International Association for the Study of Lung Cancer (IASLC) proposed a definition of complete resection that included a well-defined type of removal of the regional lymph nodes as a fundamental step. The lymph nodes may contain cancer cells and, if left behind, cancer will soon progress. The IASLC also defined incomplete resection when there is any evidence of persistent cancer after the operation. It also defined an intermediate condition, uncertain resection, when no evidence of residual disease can be proved, but all the conditions of complete resection are not fulfilled. Four validations of the definitions have proved their prognostic value and, therefore, the definitions should be followed when a surgical resection of lung cancer is planned.

Abstract

Different definitions of complete resection were formulated to complement the residual tumor (R) descriptor proposed by the American Joint Committee on Cancer in 1977. The definitions went beyond resection margins to include the status of the visceral pleura, the most distant nodes and the nodal capsule and the performance of a complete mediastinal lymphadenectomy. In 2005, the International Association for the Study of Lung Cancer (IASLC) proposed definitions for complete, incomplete and uncertain resections for international implementation. Central to the IASLC definition of complete resection is an adequate nodal evaluation either by systematic nodal dissection or lobe-specific systematic nodal dissection, as well as the integrity of the highest mediastinal node, the nodal capsule and the resection margins. When there is evidence of cancer remaining after treatment, the resection is incomplete, and when all margins are free of tumor, but the conditions for complete resection are not fulfilled, the resection is defined as uncertain. The prognostic relevance of the definitions has been validated by four studies. The definitions can be improved in the future by considering the cells spread through air spaces, the residual tumor cells, DNA or RNA in the blood, and the determination of the adequate margins and lymphadenectomy in sublobar resections.

Current status and perspectives of spread through air spaces in lung cancer

According to the World Health Organization classification of 2015, spread through air spaces (STAS) is a newly recognized pattern of invasion in lung adenocarcinoma. Many researchers have reported that STAS is recognized in all histological subtypes, and there is a strong association between STAS and prognosis in lung cancer. However, there are several technical issues associated with STAS, such as distinction between the actual in vivo phenomenon and an artifact, difficulty in assessing STAS in frozen specimens, and establishing the relationship between morphological and molecular properties of STAS. This review focuses on the current state of knowledge and the outlook of the STAS phenomenon from the perspective of surgeons, pathologists, and radiologists.

Improvement of pathological staging system for neuroendocrine tumors of the lung

Background

Currently, the tumor, node, and metastasis (TNM) staging system has a limited value in prognostic stratification for neuroendocrine tumors of the lung (NETL). A specific pathological staging system was therefore explored.

Methods

Two cohorts were assessed: the training cohort was composed of surgically treated patients from the Surveillance, Epidemiologic, and End Results (SEER) database [2004-2015]; the Shanghai cohort included Shanghai resident patients treated at Shanghai Pulmonary Hospital [2009-2018]. Multivariable Cox regression analysis was performed to identify factors associated with overall survival. A new staging system was proposed based on survival tree, and was further compared with the 8^th edition of the TNM staging system.

Results

In the training set (n=3,204), multivariate Cox analysis showed that tumor histotype and nodal status were independently associated with survival, but not T stage. Therefore, by incorporating NETL histotype (G1, low-grade typical pulmonary carcinoids; G2, intermediate-grade atypical pulmonary carcinoids; G3, high-grade large-cell neuroendocrine carcinomas) and N stage, a new staging system was developed: IA, G1N0; IB, G1N1 or G2N0; II, G1N2, G2N1-2, or G3N0; III, G3N1-2. Five-year survival rates were 91.2%, 81.3%, 50.2% and 27.6% for the new stages IA to III in the validation set (n=3,204), respectively (P<0.001). Additionally, the new staging system had significantly better predictive ability than the TNM staging system, in both the SEER [C-index, 0.75 vs. 0.62; net reclassification improvement (NRI), 0.62; integrated discrimination improvement (IDI), 20%] and Shanghai (IDI, 8%) cohorts. Based on the new staging system, adjuvant chemotherapy conferred a significantly better survival in stage-III NETL cases (HR =0.34, 95% CI, 0.25-0.45).

Conclusions

The new pathological staging system can better predict NETL prognosis than the 8^th edition of the TNM staging system, with the potential to guide postoperative treatment.

Tumor spread through air spaces (STAS): prognostic significance of grading in non-small cell lung cancer

Tumor spread through air spaces (STAS) is an invasive pattern of lung cancer that was recently described. In this study, we investigated the association between the extent of STAS and clinicopathological characteristics and patient outcomes in resected non-small cell lung cancers (NSCLCs). STAS has been prospectively described from 2008 and graded its extent with a two-tiered system (STAS I: <2500 μm [one field of ×10 objective lens] from the edge of tumor and STAS II: ≥2500 μm from the edge of tumor) from 2011 in Seoul National University Bundang Hospital. We retrospectively analyzed the correlations between the extent of STAS and clinicopathologic characteristics and prognostic significance in 1869 resected NSCLCs. STAS was observed in 765 cases (40.9%) with 456 STAS I (24.4%) and 309 STAS II (16.5%). STAS was more frequently found in patients with adenocarcinoma (ADC) (than squamous cell carcinoma), pleural invasion, lymphovascular invasion, and/or higher pathologic stage. In ADC, there were significant differences in recurrence free survival (RFS), overall survival (OS), and lung cancer specific survival (LCSS) according to the extent of STAS. In stage IA non-mucinous ADC, multivariate analysis revealed that STAS II was significantly associated with shorter RFS and LCSS (p < 0.001 and p = 0.006, respectively). In addition, STAS II was an independent poor prognostic factor for recurrence in both limited and radical resection groups (p = 0.001 and p = 0.023, respectively). In conclusion, presence of STAS II was an independent poor prognostic factor in stage IA non-mucinous ADC regardless of the extent of resection.

Gross Specimen Handling Procedures Do Not Impact the Occurrence of Spread Through Air Spaces (STAS) in Lung Cancer

Spread Through Air Spaces (STAS) is a form of invasion characterized by neoplastic cell dissemination in the lung parenchyma surrounding the outer edge of the tumor. Its possible artifactual origin is widely debated in the literature. The aim of this study is to investigate the potential impact of gross sampling procedures in causing STAS. A prospective series of 51 surgical lung specimens was collected (35 adenocarcinomas, 68.6%; 13 squamous cell carcinomas, 25.5%; 2 large-cell neuroendocrine carcinomas, 3.9%; 1 atypical carcinoid, 2%). The fresh tissue was sectioned with a new and clean blade for each cut, to obtain a tissue slice comprising the upper lung parenchyma, the tumor, and the lower parenchyma. This slice was cut in half and separately processed. The same procedure was repeated in the residual (specular) specimen after formalin fixation. STAS was identified in 33/51 (64.7%) cases, the predominant pattern being cluster formation (29 cases, 87.9%), the remaining 4 cases having single-cell invasion. Comparing STAS detection in upper and lower lung parenchyma areas (ie, before and after the blade crossed the tumor), no significant preferential STAS distribution was observed, indeed being almost overlapping (60.6% and 63.6% for fresh and 61.3% and 65.6% for fixed tissues, respectively). There was no difference between STAS occurrence in freshly cut and fixed corresponding samples. These findings indicate that STAS is not a pathologist-related artifactual event because of knife transportation of tumor cells during gross specimen handling and support the notion that it is a phenomenon preexisting to surgical tissue processing.

Correlation between spread through air spaces (STAS) and other clinicopathological parameters in lung cancer

BACKGROUND

"Spread through airspace" (STAS) is defined as micropapillary clusters, solid nests or single cells of tumor extending beyond the edge of the tumor into the air spaces of the surrounding lung parenchyma. It is associated with reduced overall survival and disease-free survival. Assessment of STAS in lung cancer appears to be necessary to guide clinical interventions. However, data on the correlation between the status of STAS and other lung cancer clinicopathological parameters are scarce.

METHODS

We reviewed 240 resected lung cancers and investigated the clinical significance of STAS in relation to other relevant lung cancer clinicopathological variables. We performed univariate and multivariate logistic regression analyses with STAS as a dependent variable.

RESULTS

Of the total 240 patients, STAS was observed in 67 (27.9 %) of them. STAS is highly prevalent in adenocarcinoma with a micropapillary growth pattern (70.0 %) than in other lung cancer growth patterns. STAS was frequently reported in wedge resections (31.0%) than in lobectomy specimens (26.7 %). STAS was significantly associated with advanced pN stage (p < 0.001) and lymphovascular invasion (p = 0.005). In multivariate models, we found that lung cancers in the right lower lobe (RLL) (OR, 2.674; 95 % CI = 1.313-5.448, p = 0.007), micropapillary lung cancer growth pattern (OR = 5.199, 95 % CI = 1.220-22.162, p = 0.026), and pN2 stage (OR = 3.683, 95 % CI = 1.324-10.245, p = 0.013) serve as independent predictors for STAS.

CONCLUSION

Our findings suggest that the presence of STAS is associated with right lower lobe tumors, micropapillary adenocarcinoma, and pN2 tumor stage. Hence, it could serve as one of the prognostically significant histologic findings in lung cancer. It is thus valid to mandate reporting STAS status in CAP surgical pathology lung cancer case summaries.

Updates on spread through air spaces (STAS) in lung cancer

Air space invasion of tumours, particularly spread through air spaces (STAS), is a relatively recent concept that has been identified as a novel mechanism of invasion. It has predominantly been described in lung adenocarcinoma, although it may be seen in other primary lung malignancies as well. STAS in lung cancer has been reported to have numerous associations with poor survival. The objective of this article was to review the concept of air space invasion, update findings regarding its clinical impact, and discuss controversies in the field. With this aim, we performed a PubMed search of the English-language literature. STAS has been introduced as a novel mechanism of invasion that is important for pathologists to recognise. There is a compelling body of evidence associating the presence of STAS with lower survival and suggesting that STAS is an independent prognostic factor, regardless of the stage of tumour. The standard of care for lung adenocarcinomas with STAS irrespective of size of tumour and nodal metastasis may be lobectomy rather than sublobar resection, owing to the risk of locoregional recurrence. Emerging data suggest that more work should be performed to improve consensus on and identification of STAS, including at frozen section.

Significance of tumor spread through air spaces (STAS) in lung cancer from the pathologist perspective

Airspace invasion in lung cancer has been known over the last 30 years, but it was only recently that WHO 2015 formally recognized it as a mechanism of invasion with the terminology of tumor spread through air spaces (STAS). Multiple studies have shown the association of STAS with lower survival and suggest that STAS is an independent prognostic factor across lung adenocarcinoma of all stages and in other histologic subtypes of lung cancer as well. Consequently, STAS is designated as an exclusion criterion of adenocarcinoma in situ and minimally invasive adenocarcinoma; thus, the presence of STAS impacts the diagnosis and staging of lung adenocarcinoma. Further, wedge resection and segmentectomy have been increasingly applied for small node negative tumors and the presence of STAS in those specimens may indicate the requirement of completion lobectomy. Given these significant clinical implications, we, pathologists, need to recognize and appropriately report STAS (possibly including at the time of intraoperative consultation). However, emerging data suggests that more work should be done to improve consensus and identification of STAS, including at frozen section. In this review, the evolution of our understanding of airspace invasion over the past decade, the clinical significance of STAS, and controversies and practical issues associated with the diagnosis of STAS are discussed.

The role of spread through air spaces (STAS) in lung adenocarcinoma prognosis and therapeutic decision making

Spread through air spaces (STAS) was included as a novel pattern of invasion in lung adenocarcinoma by the World Health Organization in 2015. Since then, multiple studies have investigated the association of STAS with clinicopathological and molecular features and its implication in the prognosis of early stage lung cancer patients undergoing different surgery types. The aim of this comprehensive review is to present current data on the role of STAS and its perspective in lung adenocarcinoma management.

Spread Through Air Spaces (STAS) in Lung Cancer: A Multiple-Perspective and Update Review

BACKGROUND

Spread through air spaces (STAS) is a spreading phenomenon of lung cancers, which is defined as tumor cells within air spaces in the lung parenchyma beyond the edge of the main tumor. To date, several articles have reviewed the studies concerning the significance of STAS; however, most articles focused on the prognosis without summarizing the significance of STAS on other aspects. In this review, we comprehensively summarized the current literature related to STAS, so as to explore the clinical significance of STAS from multiple perspectives.

MAIN BODY

This section provided a comprehensive overview of the significance of STAS from multiple perspectives and summarized current controversies and challenges in the diagnosis and clinical application.

CONCLUSION

STAS is a conspicuous spreading phenomenon of lung cancers indicating worse prognosis; nevertheless, the treatment strategy for patients with STAS remains to be discussed. Further studies are needed to elaborate whether a STAS-positive patient who underwent limited resection needs a second operation or postoperative adjuvant treatment. Meanwhile, the internal mechanism of STAS formation is largely undiscovered. Whether the capability of detachment-migration-reattachment in STAS tumor cells is achieved at the time of primary tumorigenesis or in the progress of tumor development needs to be studied, and the related signal pathways or genetic alterations need to be explored. With this information, it may be possible to improve the prognosis of patients with STAS-positive lung cancers.

Three-Dimensional Histologic, Immunohistochemical, and Multiplex Immunofluorescence Analyses of Dynamic Vessel Co-Option of Spread Through Air Spaces in Lung Adenocarcinoma

INTRODUCTION

Spread through air spaces (STAS) is a method of invasion in lung adenocarcinoma and is associated with tumor recurrence and poor survival. The spatial orientation of STAS cells in the lung alveolar parenchyma is not known. The aim of this study was to use high-resolution and high-quality three-dimensional (3D) reconstruction of images from immunohistochemical (IHC) and multiplex immunofluorescence (IF) experiments to understand the spatial architecture of tumor cell clusters by STAS in the lung parenchyma.

METHODS

Four lung adenocarcinomas, three micropapillary-predominant and one solid predominant adenocarcinoma subtypes, were investigated. A 3D reconstruction image was created from formalin-fixed, paraffin-embedded blocks. A total of 350 serial sections were obtained and subjected to hematoxylin and eosin (100 slides), IHC (200 slides), and multiplex IF staining (50 slides) with the following antibodies: cluster of differentiation 31, collagen type IV, thyroid transcription factor-1, and E-cadherin. Whole slide images were reconstructed into 3D images for evaluation.

RESULTS

Serial 3D image analysis by hematoxylin and eosin, IHC, and IF staining revealed that the micropapillary clusters and solid nests of STAS are focally attached to the alveolar walls, away from the main tumor.

CONCLUSIONS

Our 3D reconstructions found that STAS tumor cells can attach to the alveolar walls rather than appearing free floating, as seen on the two-dimensional sections. This suggests that the tumor cells detach from the main tumor, migrate through air spaces, and reattach to the alveolar walls through vessel co-option, allowing them to survive and grow. This may explain the higher recurrence rate and worse survival of patients with STAS-positive tumors who undergo limited resection than those who undergo lobectomy.

New Approaches to SCLC Therapy: From the Laboratory to the Clinic

The outcomes of patients with SCLC have not yet been substantially impacted by the revolution in precision oncology, primarily owing to a paucity of genetic alterations in actionable driver oncogenes. Nevertheless, systemic therapies that include immunotherapy are beginning to show promise in the clinic. Although, these results are encouraging, many patients do not respond to, or rapidly recur after, current regimens, necessitating alternative or complementary therapeutic strategies. In this review, we discuss ongoing investigations into the pathobiology of this recalcitrant cancer and the therapeutic vulnerabilities that are exposed by the disease state. Included within this discussion, is a snapshot of the current biomarker and clinical trial landscapes for SCLC. Finally, we identify key knowledge gaps that should be addressed to advance the field in pursuit of reduced SCLC mortality. This review largely summarizes work presented at the Third Biennial International Association for the Study of Lung Cancer SCLC Meeting.

Relevance and prognostic ability of Twist, Slug and tumor spread through air spaces in lung adenocarcinoma

BACKGROUND

Tumor spread through air spaces (STAS) is a novel pathologic characteristic in lung adenocarcinomas that indicates invasive tumor behavior. We aimed to explore the relationship between Twist, Slug and STAS in lung adenocarcinoma and to investigate the potential relationship between epithelial-mesenchymal transition (EMT) and STAS.

MATERIALS AND METHODS

Our study retrospectively analyzed 115 patients with resected lung adenocarcinomas to evaluate the relationship between Twist, Slug and STAS. STAS was diagnosed using hematoxylin-eosin (H&E) staining. Immunohistochemistry was used to evaluate the expression levels of Slug and Twist.

RESULTS

In this study, 56 (48.7%) patients had STAS, 40 (34.8%) patients had Slug overexpression, and 28 (24.3%) patients had Twist overexpression. Patients with either STAS or Slug and Twist overexpression experienced poor recurrence-free survival (RFS) and overall survival (OS). There were significant associations between Twist overexpression, Slug overexpression and the presence of STAS. The logistic model further revealed that pathological stage, Twist overexpression and Slug overexpression were independent risk factors for STAS. A multivariate analysis that contained Twist, Slug, pathologic stage and STAS, showed that pathologic stage and STAS were independent prognostic factors for poor RFS and OS. Another multivariate model that contained Twist, Slug and pathologic stage, showed that pathologic stage, Twist overexpression and Slug overexpression were independent risk factors for poor RFS and OS. In the cohort with STAS, the multivariate analysis showed that pathologic stage and Twist overexpression were independent risk factors for poor survival. The subgroup analysis showed that patients with both Slug overexpression and Twist overexpression with STAS received a poor prognosis.

CONCLUSIONS

STAS, Slug and Twist were correlated with poor RFS and OS in resected lung adenocarcinomas. Additionally, STAS was correlated with the overexpression of Twist and Slug, which could potentially provide information on the mechanism of STAS.

Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis

BACKGROUND

Large-cell neuroendocrine carcinoma of the lung (LCNEC) and small-cell lung carcinoma (SCLC) are neuroendocrine neoplasms. However, the underlying mechanisms of common and distinct genetic characteristics between LCNEC and SCLC are currently unclear. Herein, protein expression profiles and possible interactions with miRNAs were provided by integrated bioinformatics analysis, in order to explore core genes associated with tumorigenesis and prognosis in SCLC and LCNEC.

METHODS

GSE1037 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in LCNEC and SCLC, as compared with normal lung tissues, were selected using the GEO2R online analyzer and Venn diagram software. Gene ontology (GO) analysis was performed using Database for Annotation, Visualization and Integrated Discovery. The biological pathway analysis was performed using the FunRich database. Subsequently, a protein-protein interaction (PPI) network of DEGs was generated using Search Tool for the Retrieval of Interacting Genes and displayed via Cytoscape software. The PPI network was analyzed by the Molecular Complex Detection app from Cytoscape, and 16 upregulated hub genes were selected. The Oncomine database was used to detect expression patterns of hub genes for validation. Furthermore, the biological pathways of these 16 hub genes were re-analyzed, and potential interactions between these genes and miRNAs were explored via FunRich.

RESULTS

A total of 384 DEGs were identified. A Venn diagram determined 88 common DEGs. The PPI network was constructed with 48 nodes and 221 protein pairs. Among them, 16 hub genes were extracted, 14 of which were upregulated in SCLC samples, as compared with normal lung specimens, and 10 were correlated with the cell cycle pathway. Furthermore, 57 target miRNAs for 8 hub genes were identified, among which 31 miRNAs were correlated with the progression of carcinoma, drug-resistance, radio-sensitivity, or autophagy in lung cancer.

CONCLUSION

This study provided effective biomarkers and novel therapeutic targets for diagnosis and prognosis of SCLC and LCNEC.