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

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.

CT-Based Super-Resolution Deep Learning Models with Attention Mechanisms for Predicting Spread Through Air Spaces of Solid or Part-Solid Lung Adenocarcinoma

RATIONALE AND OBJECTIVES

Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma (LUAD), and preoperative knowledge of STAS status is helpful in choosing an appropriate surgical approach.

MATERIALS AND METHODS

This retrospective study collected and analyzed 602 patients diagnosed with LUAD from two medical centers: center 1 was randomly partitioned into training (n = 358) and validation cohorts (n = 154) at a 7:3 ratio; and center 2 was the external test cohort (n = 90). Super resolution was performed on all images to acquire high-resolution images, which were used to train the SE-ResNet50 model, before creating an equivalent parameter ResNet50 model. Disparities were compared between the two models using receiver operating characteristic curves, area under the curve, accuracy, precision, sensitivity, and specificity.

RESULTS

In this study, 512 and 90 patients with LUAD were enrolled from centers 1 and 2, respectively. The curve values of the SE-ResNet50 and ResNet50 models were compared for training, validation, and test cohorts, resulting in values of 0.933 vs 0.909, 0.783 vs 0.728, and 0.806 vs 0.695, respectively. In the external test cohort, the accuracy of the SE-ResNet50 model demonstrated a 10% improvement over the ResNet50 model (82.2% vs 72.2%).

CONCLUSION

The SE-ResNet50 model based on computed tomography super-resolution has great potential for predicting STAS status in patients with solid or partially solid LUAD, with superior predictive performance compared to traditional deep learning models.

Does dual-layer spectral detector CT provide added value in predicting spread through air spaces in lung adenocarcinoma? A preliminary study

OBJECTIVES

To examine the predictive value of dual-layer spectral detector CT (DLCT) for spread through air spaces (STAS) in clinical lung adenocarcinoma.

METHODS

A total of 225 lung adenocarcinoma cases were retrospectively reviewed for demographic, clinical, pathological, traditional CT, and spectral parameters. Multivariable logistic regression analysis was carried out based on three logistic models, including a model using traditional CT features (traditional model), a model using spectral parameters (spectral model), and an integrated model combining traditional CT and spectral parameters (integrated model). Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were performed to assess these models.

RESULTS

Univariable analysis showed significant differences between the STAS and non-STAS groups in traditional CT features, including nodule density (p < 0.001), pleural indentation types (p = 0.006), air-bronchogram sign (p = 0.031), the presence of spiculation (p < 0.001), long-axis diameter of the entire nodule (LD) (p < 0.001), and consolidation/tumor ratio (CTR) (p < 0.001). Multivariable analysis revealed that LD > 20 mm (odds ratio [OR] = 2.271, p = 0.025) and CTR (OR = 24.208, p < 0.001) were independent predictors in the traditional model, while electronic density (ED) in the venous phase was an independent predictor in the spectral (OR = 1.062, p < 0.001) and integrated (OR = 1.055, p < 0.001) models. The area under the curve (AUC) for the integrated model (0.84) was the highest (spectral model, 0.83; traditional model, 0.80), and the difference between the integrated and traditional models was statistically significant (p = 0.015). DCA showed that the integrated model had superior clinical value versus the traditional model.

CONCLUSIONS

DLCT has added value for STAS prediction in lung adenocarcinoma.

CLINICAL RELEVANCE STATEMENT

Spectral CT has added value for spread through air spaces prediction in lung adenocarcinoma so may impact treatment planning in the future.

KEY POINTS

• Electronic density may be a potential spectral index for predicting spread through air spaces in lung adenocarcinoma. • A combination of spectral and traditional CT features enhances the performance of traditional CT for predicting spread through air spaces.

Different types of tumor microvessels in stage I-IIIA squamous cell lung cancer and their clinical significance

BACKGROUND

Lung cancer (LC) is the leading cause of morbidity and mortality among malignant neoplasms. Improving the diagnosis and treatment of LC remains an urgent task of modern oncology. Previously, we established that in gastric, breast and cervical cancer, tumor microvessels (MVs) differ in morphology and have different prognostic significance. The connection between different types of tumor MVs and the progression of LC is not well understood.

AIM

To evaluate the morphological features and clinical significance of tumor MVs in lung squamous cell carcinoma (LUSC).

METHODS

A single-center retrospective cohort study examined medical records and archival paraffin blocks of 62 and 180 patients with stage I-IIIA LUSC in the training and main cohorts, respectively. All patients underwent radical surgery (R0) at the Orenburg Regional Cancer Clinic from May/20/2009 to December/14/2021. Tumor sections were routinely processed, and routine Mayer's hematoxylin and eosin staining and immunohistochemical staining for cluster of differentiation 34 (CD34), podoplanin, Snail and hypoxia-inducible factor-1 alpha were performed. The morphological features of different types of tumor MVs, tumor parenchyma and stroma were studied according to clinicopathological characteristics and LUSC prognosis. Statistical analysis was performed using Statistica 10.0 software. Univariate and multivariate logistic regression analyses were performed to identify potential risk factors for LUSC metastasis to regional lymph nodes (RLNs) and disease recurrence. Receiver operating characteristic curves were constructed to discriminate between patients with and without metastases in RLNs and those with and without disease recurrence. The effectiveness of the predictive models was assessed by the area under the curve. Survival was analyzed using the Kaplan-Meier method. The log-rank test was used to compare survival curves between patient subgroups. A value of P < 0.05 was considered to indicate statistical significance.

RESULTS

Depending on the morphology, we classified tumor vessels into the following types: normal MVs, dilated capillaries (DCs), atypical DCs, DCs with weak expression of CD34, "contact-type" DCs, structures with partial endothelial linings, capillaries in the tumor solid component and lymphatic vessels in lymphoid and polymorphocellular infiltrates. We also evaluated the presence of loose, fine fibrous connective tissue (LFFCT) and retraction clefts in the tumor stroma, tumor spread into the alveolar air spaces (AASs) and fragmentation of the tumor solid component. According to multivariate analysis, the independent predictors of LUSC metastasis in RLNs were central tumor location (P < 0.00001), the presence of retraction clefts (P = 0.003), capillaries in the tumor solid component (P = 0.023) and fragmentation in the tumor solid component (P = 0.009), whereas the independent predictors of LUSC recurrence were tumor grade 3 (G3) (P = 0.001), stage N2 (P = 0.016), the presence of LFFCT in the tumor stroma (P < 0.00001), fragmentation of the tumor solid component (P = 0.0001), and the absence of tumor spread through the AASs (P = 0.0083).

CONCLUSION

The results obtained confirm the correctness of our previously proposed classification of different types of tumor vessels and may contribute to improving the diagnosis and treatment of LUSC.

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 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 predictors of spread through air spaces in lung cancer

OBJECTIVE

Spread through air spaces (STAS) is a new histologic feature of invasion of non-small cell lung cancer that lacks sensitivity and specificity on frozen sections and is associated with higher recurrence and worse survival with sublobar resections. Our objective is to identify preoperative characteristics that are predictive of STAS to guide operative decisions.

METHODS

From January 2018 through December 2021, 439 cT1-3N0 M0 patients with non-small cell lung cancer and a median age of 68 years, 255 (58%) women, who underwent primary surgery at our institution were included. Patients who received neoadjuvant therapy and whose STAS status was not documented were excluded. Age, sex, smoking status, tumor size, ground-glass opacities, maximum standardized uptake values, and molecular markers on preoperative biopsy were evaluated as preoperative markers. Comparisons between groups were conducted using standardized mean differences and random forest classification was used for prediction modeling.

RESULTS

Of the 439 patients, 177 had at least 1 STAS-positive tumor, and 262 had no STAS-positive tumors. Overall, 179 STAS tumors and 293 non-STAS tumors were evaluated. Younger age (50 years or younger), solid tumor, size ≥2 cm, and maximum standardized uptake value ≥2.5 were independently predictive of STAS with prediction probabilities of 50%, 40%, 38%, and 40%, respectively. STAS tumors were more likely to harbor KRAS mutations and be PD-L1 negative.

CONCLUSIONS

Young age (50 years or younger), larger (≥2 cm) solid tumors, high maximum standardized uptake values, and presence of KRAS mutation, are risk factors for STAS and can be considered for lobectomy. Smoking status and gender are still controversial risk factors for STAS.

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.

Predicting micropapillary or solid pattern of lung adenocarcinoma with CT-based radiomics, conventional radiographic and clinical features

BACKGROUND

To build prediction models with radiomics features, clinical/conventional radiographic signs and combined scores for the discrimination of micropapillary or solid subtypes (high-risk subtypes) of lung adenocarcinoma.

METHODS

This retrospective study enrolled 351 patients with and without high-risk subtypes. Least Absolute Shrinkage and Selection Operator (LASSO) regression with cross-validation was performed to determine the optimal features of radiomics model. Missing clinical data were imputed by Multiple Imputation with Chain Equations (MICE). Clinical model with radiographic signs was built and scores of both models were integrated to establish combined model. Receiver operating characteristics (ROC) curves, area under ROC curves and decision curve analysis (DCA) were plotted to evaluate the model performance and clinical application.

RESULTS

Stratified splitting allocated 246 patients into training set. MICE for missing values obtained complete and unbiased data for the following analysis. Ninety radiomic features and four clinical/conventional radiographic signs were used to predict the high-risk subtypes. The radiomic model, clinical model and combined model achieved AUCs of 0.863 (95%CI: 0.817-0.909), 0.771 (95%CI: 0.713-0.713) and 0.872 (95%CI: 0.829-0.916) in the training set, and 0.849 (95%CI: 0.774-0.924), 0.778 (95%CI: 0.687-0.868) and 0.853 (95%CI: 0.782-0.925) in the test set. Decision curve showed that the radiomic and combined models were more clinically useful when the threshold reached 37.5%.

CONCLUSIONS

Radiomics features could facilitate the prediction of subtypes of lung adenocarcinoma. A simple combination of radiomics and clinical scores generated a robust model with high performance for the discrimination of micropapillary or solid subtype of lung adenocarcinoma.

Analysis of recurrence in lung adenocarcinoma with spread through air spaces

OBJECTIVES

Spread through air spaces is defined as tumor cells in air spaces away from the edge of tumor in lung carcinoma. It is associated with higher locoregional recurrence and lower survival in lung adenocarcinoma. The features of spread through air spaces portending worse outcomes are still under investigation. We reviewed our lung cancer experience to define potential factors related to spread through air spaces that influence recurrence and survival.

METHODS

Between January 2010 and December 2017, we identified 968 patients who underwent resection for T1-3N0M0 lung adenocarcinoma. Of these, histologic examination was possible in 787 patients. We examined the presence of spread through air spaces, spread through air spaces characteristics (micropapillary, solid nest, or single cell), average density (number per slide), and farthest distance from tumor at which spread through air spaces was detected, or maximal spread distance. Overall survival and recurrence-free survival were estimated using Kaplan-Meier curves, and differences between spread through air spaces positive versus spread through air spaces negative groups were assessed using the log-rank test.

RESULTS

Spread through air spaces was present in 389 of 787 of the reviewed cases (49.4%). Overall survival and recurrence-free survival were significantly lower in the spread through air spaces positive group over 10 years (P < .0001). The incidences of locoregional and distant recurrence were nearly doubled over 10 years in the spread through air spaces positive group compared with the spread through air spaces negative group (P = .002 and <.0001, respectively). In a multivariable Cox regression model adjusted for spread through air spaces characteristics, distance, and tumor size, lobar resection did not confer survival advantage in patients with spread through air spaces (hazard ratio of sublobar resection with respect to lobar resection, 1.44; 95% confidence interval, 0.98-2.11; P = .067). In the spread through air spaces positive group, spread through air spaces density was 2.7 ± 1.4 clusters per slide and the maximal spread distance was 2.2 ± 1.7 mm from the tumor edge. There was no observed correlation between spread through air spaces density or maximal spread distance and overall survival or recurrence.

CONCLUSIONS

We show increased distant recurrence in spread through air spaces positive lung adenocarcinoma. Quantifiable measures of spread through air spaces do not appear to correlate with recurrence or survival metrics.

Comparison of lobectomy and sublobar resection for stage I non-small cell lung cancer: a meta-analysis based on randomized controlled trials

Background

This meta-analysis aimed to compare the prognostic between lobectomy and sublobar resection in patients with stage I non-small cell lung cancer (NSCLC).

Methods

We conducted a detailed search in PubMed, Embase, Web of Science, and the Cochrane Library for randomized controlled trials (RCTs) comparing the prognosis of lobectomy and sublobar resection for stage I NSCLC, with the primary outcomes being overall survival (OS) and disease-free survival (DFS).

Results

A total of 2222 patients were included in the 5 RCTs. The results showed no statistical difference in OS (HR=0.87, p=0.445) and DFS (HR=0.99, p=0.918) between patients who underwent lobectomy and sublobar resection during the total follow-up period. In terms of dichotomous variables, there were no statistical differences in OS (relative ratio [RR]=1.05, p=0.848) and DFS (RR=1.21, p=0.075) between the two groups during the total follow-up period, as well as 5-year OS (RR=0.96, p=0.409) and 5-year DFS (RR=0.95, p=0.270). In addition, subgroup analysis showed a better prognosis for non-adenocarcinoma patients with sublobar resection than lobectomy (HR=0.53, p=0.037), but also an increased cause of cancer death (not limited to lung cancer) (RR=1.56, p=0.004).

Conclusion

Our results showed that for stage I NSCLC, lobectomy is usually not a justified operation.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023407301, identifier CRD42023407301.

High grade tumor budding is associated with poor survival in pathologic stage I lung adenocarcinoma

AIM

Tumor budding is a significant prognostic parameter that has been related to aggressive behavior in early-stage tumors of various origins. The aim of this study was to evaluate the clinicopathological significance of tumor budding in pathologic stage (pStage) I lung adenocarcinomas.

METHODS

This study comprised 107 patients who underwent curative resection for pStage I lung adenocarcinomas at our hospital between December 2010 and January 2016. We examined tumor budding on routine hematoxylin and eosin (H&E) slides from resected specimens. Tumors were categorized into two groups based on the degree of tumor budding: low grade (grade 0-1) and high grade (grade 2-3). We evaluated the relationship between tumor budding and overall survival (OS), disease-free survival (DFS) and clinicopathological parameters.

RESULTS

There is a significant difference (p = 0.002) between the 5-year DFS rates of the high-grade and the low-grade tumor budding group, which were 70 % and 90 %, respectively. High-grade tumor budding positive patients from the same pathological stage (p < 0.001; HR = 2.93 [1.51-5.68]) and clinical stage (p = 0.002) had poorer cumulative survival rates than low grade tumor budding positive patients. High grade tumor budding was positively associated with spread through air spaces (STAS) (p < 0 0.001), lymphovascular invasion (LVI) (p < 0.001), tumor necrosis (p < 0.001), high SUVmax value (SUVmax>3.0) (p < 0.001), and tumor size >20 mm (p = 0.024). High-grade tumor budding was significant prognostic factor of OS (p < 0.006) and DFS (p < 0.001) on univariate Cox regression hazard model analysis. However, it did not show significance in the multivariate analysis (p > 0.05).

CONCLUSIONS

High-grade tumor budding is an independent prognostic factor and associated with adverse clinicopathological features and poor survival rates. We proposed that high-grade tumor budding should be recognized as a new prognostic parameter and will be beneficial in predicting the clinical course in pStage I lung adenocarcinomas.

Germline mutations and developmental mosaicism underlying EGFR-mutant lung cancer

While the development of multiple primary tumors in smokers with lung cancer can be attributed to carcinogen-induced field cancerization, the occurrence of multiple primary tumors in individuals with EGFR-mutant lung cancer who lack known environmental exposures remains unexplained. We identified ten patients with early-stage, resectable non-small cell lung cancer who presented with multiple anatomically distinct EGFR-mutant tumors. We analyzed the phylogenetic relationships among multiple tumors from each patient using whole exome sequencing (WES) and hypermutable poly-guanine (poly-G) repeat genotyping, as orthogonal methods for lineage tracing. In two patients, we identified germline EGFR variants, which confer moderately enhanced signaling when modeled in vitro. In four other patients, developmental mosaicism is supported by the poly-G lineage tracing and WES, indicating a common non-germline cell-of-origin. Thus, developmental mosaicism and germline variants define two distinct mechanisms of genetic predisposition to multiple EGFR-mutant primary tumors, with implications for understanding their etiology and clinical management.

B-Cell Infiltrate in the Tumor Microenvironment Is Associated With Improved Survival in Resected Lung Adenocarcinoma

Introduction

Relapse is common after resection of lung adenocarcinoma (LUAD). Features of the tumor microenvironment (TME) which influence postsurgical survival outcomes are poorly characterized. Here, we analyzed the TME of more than 1500 LUAD specimens to identify the relationship between B-cell infiltration and prognosis.

Methods

Whole exome sequencing and bulk RNA sequencing were performed on LUADs and adjacent normal lung tissue. Relapse-free survival and overall survival (OS) were retrospectively correlated with characteristics of the tumor and TME in three data sets.

Results

High B-cell content (defined as >10% B cells) was associated with improved OS in both a The Cancer Genome Atlas-resected LUAD data set (p = 0.01) and a separate institutional stage II LUAD data set (p = 0.04, median not reached versus 89.5 mo). A validation cohort consisting of pooled microarray data representing more than 1400 resected stage I to III LUADs confirmed the association between greater B-cell abundance, specifically higher B-cell expression, and longer postsurgical survival (median OS 90 versus 71 mo, p < 0.01). Relapse-free survival was longer for patients with adenocarcinomas with high B-cell content across data sets, but it did not reach statistical significance. Subcategorization of B-cell subsets indicated that high naive B-cell content was most predictive of survival. There was no correlation between programmed death-ligand 1 expression, lymphoid aggregates, or overall immune infiltrate density and survival outcomes across the cohorts.

Conclusions

The growing adjuvant immunotherapy repertoire has increased the urgency for identifying prognostic and predictive biomarkers. Comprehensive profiling of more than 1500 LUADs suggests that high tumor-infiltrating B-cell content is a favorable prognostic marker.

Proposal of a revised International Association for the Study of Lung Cancer grading system in pulmonary non-mucinous adenocarcinoma: The importance of the lepidic proportion

OBJECTIVES

We aimed to measure the validity of the International Association for the Study of Lung Cancer (IASLC) grading system in Korean patients and propose a modification for an increase of its predictability, especially in grade 2 patients.

MATERIALS AND METHODS

From 2012 to 2017, histopathologic characteristics of 1358 patients with invasive pulmonary adenocarcinoma (stage I-III) from two institutions were retrospectively reviewed and re-classified according to the IASLC grading system. Considering the amount of the lepidic proportion, the validity of the revised model (Lepidic-10), derived from the training cohort (hospital A), was measured using the validation cohort (hospital B). Its predictability was compared to that of the IASLC system.

RESULTS

Of the 1358 patients, 259 had a recurrence, and 189 died during follow-up. The Harrell's concordance index and area under the curve of the IASLC system were 0.685 and 0.699 for recurrence-free survival (RFS) and 0.669 and 0.679 for death, respectively. From the training cohort, the IASLC grade 2 patients were divided into grades 2a and 2b (Lepidic-10 model) with a 10 % lepidic pattern. This new model further distinguished patients in both institutions that had better performance than the IASLC grading (Hospital A, p < 0.001 for RFS and death; Hospital B, p = 0.0215 for RFS, p = 0.0429 for death).

CONCLUSION

The IASLC grading system was easily applicable; its clinical use in predicting the prognosis of Korean patients with pulmonary adenocarcinoma was validated. Furthermore, the introduction of the lepidic proportion as an additional criterion to differentiate grade 2 patients improved its predictability.

B4GALT1 as a New Biomarker of Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a disease characterized by progressive scarring of the lung that involves the pulmonary interstitium. The disease may rapidly progress, leading to respiratory failure, and the long-term survival is poor. There are no accurate biomarkers available so far. Our aim was to evaluate the expression of the B4GALT1 in patients with IPF. Analysis of B4GALT1 gene expression was performed in silico on two gene sets, retrieved from the Gene Expression Omnibus database. Expression of B4GALT1 was then evaluated, both at the mRNA and protein levels, on lung specimens obtained from lung biopsies of 4 IPF patients, on one IPF-derived human primary cell and on 11 cases of IPF associated with cancer. In silico re-analysis demonstrated that the B4GALT1 gene was overexpressed in patients and human cell cultures with IPF (p = 0.03). Network analysis demonstrated that B4GALT1 upregulation was correlated with genes belonging to the EMT pathway (p = 0.01). The overexpression of B4GALT1 was observed, both at mRNA and protein levels, in lung biopsies of our four IPF patients and in the IPF-derived human primary cell, in other fibrotic non-lung tissues, and in IPF associated with cancer. In conclusion, our results indicate that B4GALT1 is overexpressed in IPF and could represent a novel marker of this disease.

Construction of Pulmonary Nodule CT Radiomics Random Forest Model Based on Artificial Intelligence Software for STAS Evaluation of Stage IA Lung Adenocarcinoma

Objective

Spread through air space (STAS) is an invasive characterization of lung adenocarcinoma and is regarded as a risk factor for poor prognosis. The aim of this study is to develop a random forest model for preoperative prediction of spread through air spaces (STAS) in stage IA lung adenocarcinoma.

Methods

92 patients with stage IA lung adenocarcinoma, who underwent computed tomography (CT) scan and surgical resection, were retrospectively reviewed. Each pulmonary nodule was automatically segmented by artificial intelligence (AI) software, and its CT-based radiomics were extracted. All patients were pathologically classified into STAS-negative and STAS-positive cohorts; then, clinical pathological and CT-based radiomics were compared between the two cohorts. Finally, a prediction model for evaluating STAS status in stage IA lung adenocarcinoma was established by a random forest model.

Results

Among 92 patients with stage IA lung adenocarcinoma, STAS positive was identified in 19 patients. The random forest classification model identified predictive features, including CT maximum value, consolidation to tumor ratio (CTR), 3D diameter, CT mean value, entropy, and CT minimum value. The misclassification rate of the random forest model is only 7.69%.

Conclusion

The risk factors of STAS in stage IA lung adenocarcinoma can be effectively identified based on the random forest model, and the hierarchical management of characteristic risk can be effectively realized. A random forest model for predicting STAS in IA lung adenocarcinoma is simple and practical.

Retrospective analysis of the prognostic implications of tumor spread through air spaces in lung adenocarcinoma patients treated with surgery

Background

Tumor spread through air spaces (STAS) in lung adenocarcinoma is a novel mechanism of invasion. STAS has been proposed as an independent predictor of poor prognosis. The aim of this study was to evaluate the correlations between STAS status and other clinicopathologic variables and to assess the prognostic implications of STAS and the distance from the edge of the tumor to the farthest STAS in patients with resected lung adenocarcinoma.

Material and methods

This is a single-institution retrospective observational study. We included all patients with resected lung adenocarcinoma from January 2017 to December 2018 at La Paz University Hospital. The cut-off for the distance from the edge of the tumor to the farthest STAS was 1.5 mm and was assessed by the area under the receiver operating characteristic curve.

Results

A total of 73 patients were included. STAS was found in 52 patients (71.2%). Histological grade 3 (P = 0.035) and absence of lepidic pattern (P = 0.022) were independently associated with the presence of STAS. The median recurrence-free survival (RFS) was 48.06 months [95% confidence interval (CI) 33.58 months to not reached]. STAS-positive patients had shorter median RFS [39.23 months (95% CI 29.34-49.12 months)] than STAS-negative patients (not reached) (P = 0.04). STAS-positive patients with a distance from the edge of the tumor to the farthest STAS ≥1.5 mm had an even shorter median RFS [37.63 months (95% CI 28.14-47.11 months)]. For every 1 mm increase in distance, the risk of mortality increased by 1.26 times (P = 0.04).

Conclusions

Histological grade 3 and absence of lepidic pattern were independently associated with the presence of STAS. STAS was associated with a higher risk of recurrence. The distance from the edge of the tumor to the farthest STAS also had an impact on overall survival.

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Lung adenocarcinoma patients with STAS had higher risk of recurrence.

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Patients with STAS and a distance from the edge of the tumor to the farthest STAS ≥1.5 mm had an even shorter RFS.

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The distance from the edge of the tumor to the farthest STAS also had an impact on overall survival.

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.

Pretreatment prediction of tumour spread through air spaces in clinical stage I non-small cell lung cancer

OBJECTIVES

To construct a nomogram prediction model for tumour spread through air spaces (STAS) in clinical stage I non-small cell lung cancer (NSCLC) and discuss its potential application value.

METHODS

380 patients with clinical stage I NSCLC in Tianjin Chest Hospital were collected as the training cohort and 285 patients in Fujian Provincial Hospital were collected as the validation cohort. Univariable and multivariable logistic regression analyses were performed to determine independent factors for STAS in the training cohort. Based on the results of the multivariable analysis, the nomogram prediction model of STAS was constructed by R software.

RESULTS

The incidence of STAS in the training cohort was 39.2%. STAS was associated with worse overall survival and recurrence-free survival (P<0.01). Univariable analysis showed that maximum tumour diameter (Tdmax), consolidation-to-tumour ratio (CTR), spiculation, vacuole and carcinoembryonic antigen were associated with STAS (P<0.05). Multivariable analysis showed that Tdmax, CTR, spiculation sign, and vacuole were independent risk factors for STAS (P<0.05). Based on this, the nomogram prediction model of STAS in clinical stage I NSCLC was constructed and internally validated by bootstrap. The Hosmer-Lemeshow test showed a χ2 value of 7.218 (P=0.513). The area under the ROC curve (AUC) and C-index were 0.724 (95% CI: 0.673-0.775). The external validation conducted on validation cohort produced an AUC of 0.759 (95% CI: 0.703-0.816).

CONCLUSIONS

The constructed nomogram prediction model of STAS in clinical stage I NSCLC has good calibration and can potentially be applied to guide treatment selection.

Assessment of the feasibility of frozen sections for the detection of spread through air spaces (STAS) in pulmonary adenocarcinoma

Spread through air spaces (STAS) is reportedly associated with worse prognosis in sublobar resections of lung adenocarcinoma. Recently, it was proposed that STAS detected on frozen sections can be an indication for lobectomy instead of sublobar resection. We undertook this study to evaluate the reliability of STAS assessment on frozen sections compared to permanent sections, as well as the associations among STAS, tumor grade, and recurrence-free survival (RFS) after sublobar resection. A total of 163 stage I lung adenocarcinoma resections with frozen sections were identified retrospectively. For each case, and for frozen and permanent sections separately, the presence or absence of STAS, as well as the tumor grade, were recorded. Compared to permanent sections, STAS detection on frozen sections had low sensitivity (55%), low positive predictive value (48%), and fair agreement (K = 0.34), whereas there was higher specificity (80%) and negative predictive value (85%). Accuracy was 74%. Tumor grade assessment on frozen sections showed higher sensitivity (77%), positive predictive value (90%), agreement (K = 0.72), specificity (94%), and accuracy (87%), and the same negative predictive value (85%). High-grade histology on frozen sections was associated with shorter RFS (p = 0.02), whereas STAS on frozen sections was not (p = 0.47). Our results suggest that the intraoperative detection of STAS has low sensitivity and positive predictive value. False-positive results may lead to overtreatment of patients with lung cancer. The determination of tumor grade on frozen sections offers better sensitivity and specificity, plus it is associated with RFS, whereas STAS on frozen sections is not. Further study is needed to explore the utility of assessing tumor grade on frozen sections.

A narrative review of prognosis prediction models for non-small cell lung cancer: what kind of predictors should be selected and how to improve models?

Objective

To discover potential predictors and explore how to build better models by summarizing the existing prognostic prediction models of non-small cell lung cancer (NSCLC).

Background

Research on clinical prediction models of NSCLC has experienced explosive growth in recent years. As more predictors of prognosis are discovered, the choice of predictors to build models is particularly important, and in the background of more applications of next-generation sequencing technology, gene-related predictors are widely used. As it is more convenient to obtain samples and follow-up data, the prognostic model is preferred by researchers.

Methods

PubMed and the Cochrane Library were searched using the items “NSCLC”, “prognostic model”, “prognosis prediction”, and “survival prediction” from 1 January 1980 to 5 May 2021. Reference lists from articles were reviewed and relevant articles were identified.

Conclusions

The performance of gene-related models has not obviously improved. Relative to the innovation and diversity of predictors, it is more important to establish a highly stable model that is convenient for clinical application. Most of the prevalent models are highly biased and referring to PROBAST at the beginning of the study may be able to significantly control the bias. Existing models should be validated in a large external dataset to make a meaningful comparison.