The utility of the proposed IASLC/ATS/ERS lung adenocarcinoma subtypes for disease prognosis and correlation of driver gene alterations

Multi-omics analyses reveal distinct molecular characteristics and transformation mechanisms of stage I-III micropapillary lung adenocarcinoma

The micropapillary (MIP) pattern is a high-grade histological subtype of lung adenocarcinoma (LUAD) with poor prognosis. In this study, surgically resected tumor samples from 101 patients with stage I-III MIP-LUAD (MIP ≥30%) were microdissected to separate MIP components from non-MIP components, all of which underwent RNA and DNA whole-exome sequencing (WES). The genomic and transcriptomic landscapes of MIP and non-MIP components within MIP-enriched tumor tissues demonstrated remarkable similarities, notably marked by high epidermal growth factor receptor (EGFR) alteration frequencies. However, when compared to MIP-naïve LUAD tissues, MIP components showed higher chromosomal instability and revealed 18 enriched alterations, encompassing EGFR mutations, EGFR amplifications, and CDKN2A/CDKN2B deletions, which all linked to upregulation of cell proliferation pathways and downregulation of immune pathways. Shared mutations were observed in 97.8% (91/93) of patients with paired DNA WES data for MIP and non-MIP components within the same tissues, suggesting a common origin. The recurrence-free survival analysis identified MACF1, PCLO, ADGRV1, and Fanconi Anemia pathway mutations as negative indicators. In all, we conducted an in-depth analysis of the molecular characteristics and transformation mechanisms of MIP-LUAD, employing microdissection techniques to investigate the genomic and transcriptomic levels within a substantial cohort, providing insights for precision medicine of this aggressive cancer subtype. © 2025 The Pathological Society of Great Britain and Ireland.

Intratumoral and peritumoral radiomics model for the preoperative prediction of cribriform component in invasive lung adenocarcinoma: a multicenter study

PURPOSE

This study aimed to investigate the predictive value of intratumoral and peritumoral radiomics model for the cribriform component (CC) of invasive lung adenocarcinoma (LUAD).

MATERIALS AND METHODS

The 144 patients with invasive LUAD from our center were randomly divided into training set (n = 100) and internal validation set (n = 44) in a ratio of 7:3, and 75 patients from center 2 were regarded as the external validation set. Clinical risk factors were examined using univariate and multivariate logistic regression to construct the clinical model. We extracted radiomics features from gross tumor volume (GTV), gross and peritumoral volume (GPTV), and peritumoral volume (PTV), respectively. Radiomics models were constructed with selected features. A combined model based on the optimal Radscore and clinically independent predictors was constructed, and its predictive performance was assessed by receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).

RESULTS

The area under curves (AUCs) of the GTV model were 0.882 (95% CI 0.817-0.948), 0.794 (95% CI 0.656-0.932), and 0.766 (95% CI 0.657-0.875) in the training, internal validation, and external validation sets, and the PTV model had AUCs of 0.812 (95% CI 0.725-0.899), 0.749 (95% CI 0.597-0.902), and 0.670 (95% CI 0.543-0.798) in the training, internal validation, and external validation sets, respectively. However, the GPTV radiomics model showed better predictive performance compared with the GTV and PTV radiomics models, with the AUCs of 0.950 (95% CI 0.911-0.989), 0.844 (95% CI 0.728-0.959), and 0.815 (95% CI 0.713-0.917) in the training, internal validation and external validation sets, respectively. In the clinical model, tumor shape, lobulation sign and maximal diameter were the independent predictors of CC in invasive LUAD. The combined model including independent clinical predictors and GPTV-Radscore show the considerable instructive to clinical practice, with the AUCs of 0.954(95% CI 0.918-0.990), 0.861(95% CI 0.752-0.970), and 0.794(95% CI 0.690-0.898) in training, internal validation, and external validation sets, respectively. DCA showed that the combined model had good clinical value and correction effect.

CONCLUSION

Radiomics model is a very powerful tool for predicting CC growth pattern in invasive LUAD and can help clinicians make the strategies of treatment and surveillance in patients with invasive LUAD.

Correlation between imaging features of pure ground-glass opacities and pathological subtypes of lung minimally invasive adenocarcinoma and precursor lesions

This study aimed to investigate the relationship between imaging features of pure ground-glass opacities (pGGOs) and the pathological subtypes of minimally invasive adenocarcinoma (MIA) and precursor lesions. A retrospective analysis was conducted on data from 1521 patients diagnosed with GGOs as lung adenocarcinoma or precursor lesions between January 2015 and March 2021. The pGGOs were categorized into atypical adenomatous hyperplasia (AAH) / adenocarcinoma in situ (AIS) and MIA groups. Clinical information and CT imaging features were collected. Statistical analysis, logistic regression, and receiver operating characteristic (ROC) curve analysis were performed. A total of 127 patients with 139 pGGOs were included. Maximum radiodensity, minimum radiodensity, mean radiodensity, variance, and skewness showed significant differences between the two groups. Maximum radiodensity and maximum cross-sectional area were identified as risk factors for pathology. The logistic regression model yielded an area under the curve (AUC) of 0.747 (95% CI, 0.666-0.816) for predicting pathological subtypes. The intensity features of pGGOs were found to be significantly different between AAH/AIS and MIA groups. Maximum radiodensity and skewness were independent risk factors for pathology. However, these features did not exhibit satisfactory diagnostic efficiency.

Impact of histopathological subtypes on invasive lung adenocarcinoma: from epidemiology to tumour microenvironment to therapeutic strategies

Lung adenocarcinoma is the most prevalent type of lung cancer, with invasive lung adenocarcinoma being the most common subtype. Screening and early treatment of high-risk individuals have improved survival; however, significant differences in prognosis still exist among patients at the same stage, especially in the early stages. Invasive lung adenocarcinoma has different histological morphologies and biological characteristics that can distinguish its prognosis. Notably, several studies have found that the pathological subtypes of invasive lung adenocarcinoma are closely associated with clinical treatment. This review summarised the distribution of various pathological subtypes of invasive lung adenocarcinoma in the population and their relationship with sex, smoking, imaging features, and other histological characteristics. We comprehensively analysed the genetic characteristics and biomarkers of the different pathological subtypes of invasive lung adenocarcinoma. Understanding the interaction between the pathological subtypes of invasive lung adenocarcinoma and the tumour microenvironment helps to reveal new therapeutic targets for lung adenocarcinoma. We also extensively reviewed the prognosis of various pathological subtypes and their effects on selecting surgical methods and adjuvant therapy and explored future treatment strategies.

Application of 18 F-fluorodeoxyglucose PET/computed tomography in the diagnosis of infiltrative subsolid nodules in lung adenocarcinoma

PURPOSE

To investigate the diagnostic value of 18 F-fluorodeoxyglucose(FDG) PET/computed tomography (CT) for infiltrative subsolid nodules at different stages of lung adenocarcinoma and to explore predictive factors for invasive adenocarcinoma, providing compelling evidence for timely intervention.

METHODS

A retrospective analysis was conducted on PET/CT imaging data of 170 subsolid nodules lesions confirmed postoperatively as lung adenocarcinoma or precursor glandular lesions. Lesions were categorized into preinvasive lesions including atypical adenomatous hyperplasia and adenocarcinoma in situ, microinvasive adenocarcinoma, and invasive adenocarcinoma. Compared the differences in imaging features and metabolic parameters among different groups and used a multifactor logistic regression model and receiver operating characteristic curve analysis to identify predictive factors for invasive adenocarcinoma.

RESULTS

From preinvasive lesions through microinvasive adenocarcinoma to invasive adenocarcinoma, there was a gradual increase in nodule diameter, nodule area, and proportion of part-solid nodule. Statistical significance ( P  < 0.05) was observed in the rates of spiculation and pleural indentation between preinvasive lesions versus microinvasive adenocarcinoma and invasive adenocarcinoma groups. The maximum standardized uptake value and maximum standardized uptake ratio show statistically significant differences ( P  < 0.05) between the invasive adenocarcinoma group and the other groups. Logistic regression analysis indicated that nodule composition, nodule diameter, and maximum standardized uptake ratio were predictive factors for invasive adenocarcinoma ( P  < 0.05). For part-solid nodules, the longest diameter of the solid component has a high diagnostic value.

CONCLUSION

The imaging features of 18 F-FDG PET/CT contribute to the diagnosis of infiltrative subsolid nodules at different stages of lung adenocarcinoma, providing robust evidence for timely intervention.

Phase II trial of dual anti-CTLA-4 and anti-PD-1 blockade in rare tumors SWOG/NCI experience: invasive mucinous or non-mucinous lepidic adenocarcinoma of the lung (formerly bronchioloalveolar carcinoma)

Background

Anti-programmed death-1 (PD-1)/cytotoxic T lymphocyte antigen-4 antibodies are efficacious in various malignancies.

Objectives

This study presents the first results of ipilimumab-nivolumab in invasive mucinous or non-mucinous lepidic adenocarcinoma (invasive mucinous adenocarcinoma (IMA) or invasive non-mucinous lepidic adenocarcinomas (INLA), respectively) of the lung.

Design

Dual anti-CTLA-4 and anti-PD-1 blockade in rare tumors (DART) is a prospective, open-label, multicenter (1016 US sites), multi-cohort phase II trial of ipilimumab (1 mg/kg intravenously (IV) every 6 weeks) plus nivolumab (240 mg IV every 2 weeks).

Methods

Participants histologically diagnosed with advanced IMA or INLA, who had not responded to at least one line of therapy, were included in the bronchioloalveolar carcinoma cohort. The primary endpoint was the overall response rate (ORR) by Response Evaluation Criteria in Solid Tumors (confirmed complete and partial responses (CR and PR)). Secondary endpoints were progression-free survival (PFS), overall survival (OS), clinical benefit rate (CBR; stable disease (SD) ⩾ 6 months plus ORR), and toxicity.

Results

Eight evaluable patients (median age: 77 years; the number of prior therapies ranged from 0 to 4; one patient with prior exposure to a PD-1 inhibitor; comprising six IMA and two INLA) were treated. One IMA had a 40% regression (PFS 45.2+ months, PD-L1 0%, KRAS G12C mutated, tumor mutational burden [TMB] 13 mut/Mb). One INLA had 66% regression (PFS 23.8 months, PD-L1 unknown, no actionable mutations, TMB 3 mut/Mb). Overall ORR was 25.0% (2/8) and CBR, 62.5% (5/8); PFS for the patients with SD > 6 months was 43.4+, 11.7+, and 8.3 months. The median PFS was 16 months (5.3-not reached) and the median OS was 32.2 months (14.6-not reached). The toxicity profile was similar to previous reports.

Conclusion

Ipilimumab plus nivolumab in the bronchioloalveolar carcinoma cohort (IMA, INLA) resulted in a durable ORR of 25.0% and CBR of 62.5% (PFS, 8.3 11.7+. 23.8 (PR), 43.4+ and 45.2+ (PR) months). Correlative studies to determine response and resistance markers are ongoing. Expanded prospective studies are warranted.

Trial registration

ClinicalTrials.gov registry: NCT02834013.

Case of lung fine needle aspiration showing mucinous cells and extracellular mucin

Mucinous neoplasm with extracellular mucin can be challenging to interpret on fine needle aspiration and core biopsies. Determining the biologic origin of the mucin/mucinous cells, that is, benign/incidental versus neoplasm, invasive versus in situ, and primary versus metastatic tumors, requires a thorough multidisciplinary evaluation. The work up of these lesions includes morphologic analysis with ancillary immunohistochemical and/or molecular studies and correlation with clinical and imaging studies. This review outlines a practical approach to the diagnosis of mucinous lesions in the lung with comprehensive review of literature.

Immunoexpression of E-cadherin, β-catenin and Ezrin in non-small cell lung carcinomas

Lung cancer continues to have the highest mortality rate in the world, non-small cell lung carcinoma (NSCLC) representing the most common tumor form. The therapeutic interference of the tumor intercellular adhesion disruption mechanisms can provide therapeutic targets to improve the patients' prognosis. The study included 52 cases diagnosed with NSCLC, for which the immunohistochemical expressions of E-cadherin, β-catenin and Ezrin were analyzed in relation to the epidemiological and histological prognostic parameters. The histopathological analysis indicated the predominance of high-grade acinar adenocarcinoma (ADK) and non-keratinizing squamous cell carcinoma (SCC), with frequent vascular invasion and in stages II-IV. Final staining scores (FSS) of E-cadherin were superior in the case of acinar, lepidic and papillary ADK, with a high degree of differentiation, without vascular invasion and in initial tumor stages. The same aspect was also observed in the case of β-catenin reactions, which were present only at the membrane level, increased FSS being also present in the case of mucinous carcinomas. The membrane/cytoplasmic immunoexpression of Ezrin was superior in the case of cribriform, solid, micropapillary, lepidic and non-keratinized squamous carcinomas, with vascular invasion and in advanced tumor stages. Membrane reactions of Ezrin prevailed only in the case of acinar, lepidic and papillary ADK. The negative linear correlation of E-cadherin and β-catenin with Ezrin and the relationships of the markers with the histological parameters of NSCLC indicate their utility potential for the identification of aggressive malignant lung tumors.

Establishment of artificial intelligence model for precise histological subtyping of lung adenocarcinoma and its application to quantitative and spatial analysis

BACKGROUND

The histological subtype of lung adenocarcinoma is a major prognostic factor. We developed a new artificial intelligence model to classify lung adenocarcinoma images into seven histological subtypes and adopted the model for whole-slide images to investigate the relationship between the distribution of histological subtypes and clinicopathological factors.

METHODS

Using histological subtype images, which are typical for pathologists, we trained and validated an artificial intelligence model. Then, the model was applied to whole-slide images of resected lung adenocarcinoma specimens from 147 cases.

RESULT

The model achieved an accuracy of 99.7% in training sets and 90.4% in validation sets consisting of typical tiles of histological subtyping for pathologists. When the model was applied to whole-slide images, the predominant subtype according to the artificial intelligence model classification matched that determined by pathologists in 75.5% of cases. The predominant subtype and tumor grade (using the WHO fourth and fifth classifications) determined by the artificial intelligence model resulted in similar recurrence-free survival curves to those determined by pathologists. Furthermore, we stratified the recurrence-free survival curves for patients with different proportions of high-grade components (solid, micropapillary and cribriform) according to the physical distribution of the high-grade component. The results suggested that tumors with centrally located high-grade components had a higher malignant potential (P < 0.001 for 5-20% high-grade component).

CONCLUSION

The new artificial intelligence model for histological subtyping of lung adenocarcinoma achieved high accuracy, and subtype quantification and subtype distribution analyses could be achieved. Artificial intelligence model therefore has potential for clinical application for both quantification and spatial analysis.

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.

The presence of a cribriform pattern is related to poor prognosis in lung adenocarcinoma after surgical resection: A meta-analysis

OBJECTIVE

Previous studies reported that the cribriform pattern (CP) was associated with poor prognosis in lung adenocarcinoma (ADC) patients; therefore, a meta-analysis was performed to thoroughly evaluate the prognostic impact of cribriform pattern in postoperative ADC patients.

METHODS

Eligible studies were retrieved from PubMed, Embase databases, and Web of Science until April 2023. Studies evaluating the effect of the cribriform pattern on the prognosis of postoperative ADC patients were included. Subsequently, subgroup analysis was conducted according to the proportion of the cribriform pattern, with disease-free survival (DFS) and/or overall survival (OS) as outcomes. Hazard ratios (HRs) and 95% confidence intervals (CIs) were used as effect estimates in the meta-analyses, which were performed with a random-effects model despite the heterogeneity.

RESULTS

Nine studies published between 2015 and 2022 were included, with 4,289 ADC patients in total. The pooled results revealed a significantly poorer DFS (HR1.56, 95%CI 1.18-2.06, P = 0.11, I2 = 45%) and OS (HR2.11, 95%CI 1.63-2.72, P = 0.01, I2 = 56%) in patients with the cribriform pattern. Furthermore, the subgroup analysis showed that patients with a cribriform pattern (DFS: HR1.32, 95% CI 1.04-1.68 OS:HR2.30, 95% CI 1.55-3.39) and patients with a predominantly cribriform pattern (DFS:HR2.04, 95% CI 1.32--3.15 OS: HR1.92, 95% CI 1.41-2.61) were associated with poor prognosis.

CONCLUSIONS

The presence of a cribriform pattern is related to poor prognosis in postoperative ADC patients, despite not being a main tumor component. However, the results should be confirmed by large-scale and prospective studies owing to the small sample and potential heterogeneity.

[18F]FDG PET/CT is useful in discriminating invasive adenocarcinomas among pure ground-glass nodules: comparison with CT findings-a bicenter retrospective study

PURPOSE

Predicting the malignancy of pure ground-glass nodules (GGNs) using CT is challenging. The optimal role of [18F]FDG PET/CT in this context has not been clarified. We compared the performance of [18F]FDG PET/CT in evaluating GGNs for predicting invasive adenocarcinomas (IACs) with CT.

METHODS

From June 2012 to December 2020, we retrospectively enrolled patients with pure GGNs on CT who underwent [18F]FDG PET/CT within 90 days. Overall, 38 patients with 40 ≥ 1-cm GGNs were pathologically confirmed. CT images were analyzed for size, attenuation, uniformity, shape, margin, tumor-lung interface, and internal/surrounding characteristics. Visual [18F]FDG positivity, maximum standardized uptake value (SUVmax), and tissue fraction-corrected SUVmax (SUVmaxTF) were evaluated on PET/CT.

RESULTS

The histopathology of the 40 GGNs were: 25 IACs (62.5%), 9 minimally invasive adenocarcinomas (MIA, 22.5%), and 6 adenocarcinomas in situ (AIS, 15.0%). No significant differences were found in CT findings according to histopathology, whereas visual [18F]FDG positivity, SUVmax, and SUVmaxTF were significantly different (P=0.001, 0.033, and 0.018, respectively). The size, visual [18F]FDG positivity, SUVmax, and SUVmaxTF showed significant diagnostic performance to predict IACs (area under the curve=0.693, 0.773, 0.717, and 0.723, respectively; P=0.029, 0.001, 0.018, and 0.013, respectively). In the multivariate logistic regression analysis, visual [18F]FDG positivity discriminated IACs among GGNs among various CT and PET findings (P=0.008).

CONCLUSIONS

[18F]FDG PET/CT demonstrated superior diagnostic performance compared to CT in differentiating IAC from AIS/MIA among pure GGNs, thus it has the potential to guide the proper management of patients with pure GGNs.

Histology of Bronchiolar Tumor Spread Through Air Spaces

The clinical significance of lung tumor spread through air spaces (STAS) has been extensively studied, and is recognized as a unique pattern of invasion. Previous studies of STAS have focused primarily on STAS in alveolar spaces, whereas STAS in the bronchiolar spaces (bronchiolar STAS) has been described in only a few case reports only. Here, we examined 306 cases of primary lung adenocarcinoma and found that bronchiolar STAS was present in 18%. Bronchiolar STAS was associated with an inferior prognosis, more advanced stage, and higher histologic grade. No significant difference in clinicopathological factors or prognosis was observed between cases with bronchiolar STAS and those with alveolar STAS alone. Notably, bronchiolar STAS often occurred simultaneously with alveolar STAS and endobronchial spread of adenocarcinoma, particularly when bronchiolar STAS was present outside the main tumor. We also identified cases where bronchiolar STAS and endobronchial spread of adenocarcinoma occurred simultaneously in the same bronchi or bronchioles located outside the main tumor, as well as cases with bronchiolar STAS adjacent to intrapulmonary metastatic nodules. Our results highlight the significant role of bronchiolar STAS in the aerogenous spread of adenocarcinoma cells. Bronchiolar STAS can be regarded as a histologic variant of alveolar STAS. This study also supports the idea that STAS is not a tissue processing artifact, but a true biological process with clinical implications, offering histologic evidence of aerogenous spread in lung adenocarcinoma.

Spatial whole exome sequencing reveals the genetic features of highly-aggressive components in lung adenocarcinoma

In invasive lung adenocarcinoma (LUAD), patients with micropapillary (MIP) or solid (SOL) components had a significantly poorer prognosis than those with only lepidic (LEP), acinar (ACI) or papillary (PAP) components. It is interesting to explore the genetic features of different histologic subtypes, especially the highly aggressive components. Based on a cohort of 5,933 patients, this study observed that in different tumor size groups, LUAD with MIP/SOL components showed a different prevalence, and patients with ALK alteration or TP53 mutations had a higher probability of developing MIP/SOL components. To control individual differences, this research used spatial whole-exome sequencing (WES) via laser-capture microdissection of five patients harboring these five coexistent components and identified genetic features among different histologic components of the same tumor. In tracing the evolution of components, we found that titin (TTN) mutation might serve as a crucial intratumor potential driver for MIP/SOL components, which was validated by a cohort of 146 LUAD patients undergoing bulk WES. Functional analysis revealed that TTN mutations enriched the complement and coagulation cascades, which correlated with the pathway of cell adhesion, migration, and proliferation. Collectively, the histologic subtypes of invasive LUAD were genetically different, and certain trunk genotypes might synergize with branching TTN mutation to develop highly aggressive components.

Feasibility of UTE-MRI-based radiomics model for prediction of histopathologic subtype of lung adenocarcinoma: in comparison with CT-based radiomics model

OBJECTIVES

To assess the feasibility of the UTE-MRI radiomic model in predicting the micropapillary and/or solid (MP/S) patterns of surgically resected lung adenocarcinoma.

MATERIALS AND METHODS

We prospectively enrolled 74 lesions from 71 patients who underwent UTE-MRI and CT before curative surgery for early lung adenocarcinoma. For conventional radiologic analysis, we analyzed the longest lesion diameter and lesion characteristics at both UTE-MRI and CT. Radiomic features were extracted from the volume of interest of the lesions and Rad-scores were generated using the least absolute shrinkage and selection operator with fivefold cross-validation. Six models were constructed by combining the conventional radiologic model, UTE-MRI Rad-score, and CT Rad-score. The areas under the curves (AUCs) of each model were compared using the DeLong method. Early recurrence after curative surgery was analyzed, and Kaplan-Meier survival analysis was performed.

RESULTS

Twenty-four lesions were MP/S-positive, and 50 were MP/S-negative. The longitudinal size showed a small systematic difference between UTE-MRI and CT, with fair intermodality agreement of lesion characteristic (kappa = 0.535). The Rad-scores of the UTE-MRI and CT demonstrated AUCs of 0.84 and 0.841, respectively (p = 0.98). Among the six models, mixed conventional, UTE-MRI, and CT Rad-score model showed the highest diagnostic performance (AUC = 0.879). In the survival analysis, the high- and low-risk groups were successfully divided by the Rad-score in UTE-MRI (p = 0.01) and CT (p < 0.01).

CONCLUSION

UTE-MRI radiomic model predicting MP/S positivity is feasible compared with the CT radiomic model. Also, it was associated with early recurrence in the survival analysis.

CLINICAL RELEVANCE STATEMENT

A radiomic model utilizing UTE-MRI, which does not present a radiation hazard, was able to successfully predict the histopathologic subtype of lung adenocarcinoma, and it was associated with the patient's recurrence-free survival.

KEY POINTS

• No studies have reported the ultrashort echo time (UTE)-MRI-based radiomic model for lung adenocarcinoma. • The UTE-MRI Rad-score showed comparable diagnostic performance with CT Rad-score for predicting micropapillary and/or solid histopathologic pattern. • UTE-MRI is feasible not only for conventional radiologic analysis, but also for radiomics analysis.

Comparative study of imaging and pathology of primary mucinous adenocarcinoma with different imaging manifestations

BACKGROUND

Pulmonary mucinous adenocarcinoma is a special type of lung cancer. Its imaging manifestations are diverse, which brings challenges to clinical diagnosis. However, its formation mechanism is unclear.

OBJECTIVE

The objective of this study is to analyse the relevant mechanisms of the formation of pulmonary mucinous adenocarcinoma by observing its different imaging and pathological manifestations.

DATA AND METHODS

Retrospective analysis was conducted on imaging manifestations and pathological data of 103 patients with pulmonary mucinous adenocarcinoma confirmed intraoperatively or pathologically.

RESULTS

Forty-three patients had pulmonary mucinous adenocarcinoma with a solitary nodule/mass, 41 patients with localized pneumonia and 19 patients with diffuse pneumonia. Their CT manifestations included 'falling snowflake sign', ground-glass opacity close to the heart, vacuous signs/honeycombing and withered tree branches. Under the microscope, all the three types of pulmonary mucinous adenocarcinoma had visibly formed mucus lakes but were made of tumour cells with totally different shapes, which included the goblet-like shape (tall column-like shape) and quasi-circular shape. Tall column-shaped tumour cells were negative or weakly positive for thyroid transcription factor-1 (TTF-1) and strongly positive for ALK mutation, whereas quasi-circular tumour cells were positive for TTF-1 and less positive for ALK mutation.

CONCLUSION

The different imaging manifestations of mucinous adenocarcinoma are possibly due to the different amounts or viscosity of mucus produced, and the mechanisms of its formation may include (1) tumour cells in different shapes have different abilities to produce mucus; (2) tumours in different stages produce different amounts or viscosity of mucus; and (3) the TTF-1 and ALK genes affect the production of mucus.

The value of T2-weighted MRI contrast ratio combined with DWI in evaluating the pathological grade of solid lung adenocarcinoma

AIM

To assess the predictive value of T2-weighted (T2W) magnetic resonance imaging (MRI) in combination with diffusion-weighted imaging (DWI) for determining the pathological grading of solid lung adenocarcinoma.

MATERIALS AND METHODS

The clinical and imaging data from 153 cases of solid lung adenocarcinoma (82 men, 71 women, mean age 63.2 years) confirmed at histopathology in The First Affiliated Hospital of Xi'an Jiaotong University from January 2017 to May 2022 were analysed retrospectively. Adenocarcinomas were classified into low-grade (G1 and G2) and high-grade (G3) groups following the 2020 pathological grading system proposed by the International Association for the Study of Lung Cancer. The T2-weighted contrast ratio (T2CR), calculated as the T2 signal intensity of the lung mass/nodule divided by the T2 signal intensity of the right rhomboid muscle was utilised. Two experienced radiologists reviewed the MRI images independently, measured the T2CR, and obtained apparent diffusion coefficient (ADC) values. The Mann-Whitney U-test was used to compare general characteristics (sex, age, maximum diameter), T2CR, and ADC values between the low-grade and high-grade groups. The non-parametric Kruskal-Wallis test determined differences in T2CR and ADC values among the five adenocarcinoma subtypes. Receiver characteristic curve (ROC) analysis, along with area under the curve (AUC) calculation, assessed the effectiveness of each parameter in distinguishing the pathological grade of lung adenocarcinoma. A Z-test was used to compare the AUC values.

RESULTS

Among the 153 patients with adenocarcinoma, 103 had low-grade adenocarcinoma, and 50 had high-grade adenocarcinoma. The agreement between T2CR and ADC observers was good (0.948 and 0.929, respectively). None of the parameters followed a normal distribution (p<0.05). The ADC value was lower in the high-grade adenocarcinoma group compared to the low-grade adenocarcinoma group (p=0.004), while the T2CR value was higher in the high-grade group (p=0.011). Statistically significant differences were observed in maximum diameter and gender between the two groups (p<0.001 and p=0.005, respectively), while no significant differences were noted in age (p=0.980). Among the five adenocarcinoma subtypes, only the lepidic and micropapillary subtypes displayed statistical differences in ADC values (p=0.047), with the remaining subtypes showing no statistical differences (p>0.05). The AUC values for distinguishing high-grade adenocarcinoma from low-grade adenocarcinoma were 0.645 for ADC and 0.627 for T2CR. Combining T2CR, ADC, sex, and maximum diameter resulted in an AUC of 0.778, sensitivity of 70%, and specificity of 75%. This combination significantly improved diagnostic efficiency compared to T2CR and ADC alone (p=0.008, z = 2.624; p=0.007, z = 2.679).

CONCLUSION

The MRI quantitative parameters are useful for distinguishing the pathological grades of solid lung adenocarcinoma, offering valuable insights for precise lung cancer treatment.

Pulmonary adenocarcinoma in situ with morule - like components: A surgical case report

Unusual lung adenocarcinoma with morule-like components is characterized by uniform, tightly packed spindle-shaped cells filling the lumens of neoplastic glandular structures. We present a case of a 78-year-old woman who presented with a part-solid ground-glass nodule in the upper lobe of the right lung. Following right upper lobectomy, histological examination revealed adenocarcinoma in-situ with multiple morule-like intra-alveolar proliferative nests of epithelial cells. Immunostaining was positive for thyroid-transcription factor 1 in the tumor cells and morule-like components. The tumor was also positive for an epidermal growth factor receptor mutation. This case provides valuable insights about lung adenocarcinoma in-situ with morule-like components.

Efficacy of Touch Imprint Cytology in Intraoperative Diagnosis of Invasive Mucinous Adenocarcinoma of the Lung: A Case Report and Literature Review

A preoperative diagnosis of the peripheral small lung nodule is often difficult, and an intraoperative frozen section diagnosis (FSD) is performed to guide treatment strategy. However, invasive mucinous adenocarcinoma (IMA) is prone to be overlooked because of the low sample quality and weak atypia. We herein report a case of IMA, in which touch imprint cytology (TIC) revealed diagnostic efficacy. A 74-year-old male with a small, subsolid nodule in the right upper lobe underwent a thoracoscopic wedge resection. A grayish brown, 10 × 7 mm-sized nodule was observed on the cut surface. Intraoperative FSD revealed lung tissue with mild alveolar septal thickening and stromal fibrosis but without overt atypia. Meanwhile, TIC revealed mucus and a few epithelial cells with intranuclear inclusions, which pathologists evaluated as reactive. Finally, focal organizing pneumonia was tentatively diagnosed, and surgery was finished without any additional resection. However, permanent section diagnosis revealed a microinvasive mucinous adenocarcinoma. Nuclear inclusions were confirmed in tumor cells. In the intraoperative setting, TIC may be more advantageous than FSD in observing nuclear inclusions and mucus. Mucinous background and nuclear inclusion on TIC may suggest IMA even if FSD does not suggest malignancy in an intraoperative diagnosis of the peripheral small lung nodule.

Lung-PNet: An Automated Deep Learning Model for the Diagnosis of Invasive Adenocarcinoma in Pure Ground-Glass Nodules on Chest CT

BACKGROUND. Pure ground-glass nodules (pGGNs) on chest CT representing invasive adenocarcinoma (IAC) warrant lobectomy with lymph node resection. For pGGNs representing other entities, close follow-up or sublobar resection without node dissection may be appropriate. OBJECTIVE. The purpose of this study was to develop and validate an automated deep learning model for differentiation of pGGNs on chest CT representing IAC from those representing atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), and minimally invasive adenocarcinoma (MIA). METHODS. This retrospective study included 402 patients (283 women, 119 men; mean age, 53.2 years) with a total of 448 pGGNs on noncontrast chest CT that were resected from January 2019 to June 2022 and were histologically diagnosed as AAH (n = 29), AIS (n = 83), MIA (n = 235), or IAC (n = 101). Lung-PNet, a 3D deep learning model, was developed for automatic segmentation and classification (probability of IAC vs other entities) of pGGNs on CT. Nodules resected from January 2019 to December 2021 were randomly allocated to training (n = 327) and internal test (n = 82) sets. Nodules resected from January 2022 to June 2022 formed a holdout test set (n = 39). Segmentation performance was assessed with Dice coefficients with radiologists' manual segmentations as reference. Classification performance was assessed by ROC AUC and precision-recall AUC (PR AUC) and compared with that of four readers (three radiologists, one surgeon). The code used is publicly available (https://github.com/XiaodongZhang-PKUFH/Lung-PNet.git). RESULTS. In the holdout test set, Dice coefficients for segmentation of IACs and of other lesions were 0.860 and 0.838, and ROC AUC and PR AUC for classification as IAC were 0.911 and 0.842. At threshold probability of 50.0% or greater for prediction of IAC, Lung-PNet had sensitivity, specificity, accuracy, and F1 score of 50.0%, 92.0%, 76.9%, and 60.9% in the holdout test set. In the holdout test set, accuracy and F1 score (p values vs Lung-PNet) for individual readers were as follows: reader 1, 51.3% (p = .02) and 48.6% (p = .008); reader 2, 79.5% (p = .75) and 75.0% (p = .10); reader 3, 66.7% (p = .35) and 68.3% (p < .001); reader 4, 71.8% (p = .48) and 42.1% (p = .18). CONCLUSION. Lung-PNet had robust performance for segmenting and classifying (IAC vs other entities) pGGNs on chest CT. CLINICAL IMPACT. This automated deep learning tool may help guide selection of surgical strategies for pGGN management.

Radiomics Nomogram Based on Optimal Volume of Interest Derived from High-Resolution CT for Preoperative Prediction of IASLC Grading in Clinical IA Lung Adenocarcinomas: A Multi-Center, Large-Population Study

The novel grading system developed by the International Association for the Study of Lung Cancer (IASLC) for clinical stage IA lung adenocarcinomas has demonstrated remarkable prognostic capabilities. Notably, tumors classified as grade 3 have been associated with poor prognostic outcomes, thereby playing a crucial role in the formulation of personalized surgical strategies. The objective of this study is to develop a radiomics nomogram that utilizes the optimal volume of interest (VOI) derived from high-resolution CT (HRCT) scans to accurately predict the presence of grade 3 tumors in patients with clinical IA lung adenocarcinomas.In this multi-center, large-population study, clinical, pathological, and HRCT imaging data from 1418 patients who were pathologically diagnosed with lung adenocarcinomas were retrospectively collected. The data was obtained from four hospital databases between January 2018 and May 2022. From this patient cohort, 1206 individuals were screened from three databases and randomly divided into training and internal validation datasets in a 7:3 ratio. An additional dataset consisting of 212 individuals was used for external validation dataset. Radiomics features were extracted from HRCT images at various scales, including VOI-2mm, VOI entire, VOI +2mm, and VOI +4mm. To reduce dimensionality, select relevant features, and build radiomics signatures, the maximal redundancy minimal relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) algorithm were utilized. Univariate and multivariate logistic regression analyses were conducted to identify independent clinic-radiological (Clin-Rad) predictors. Receiver operating characteristic (ROC) curves and corresponding area under the curve (AUC) were used to evaluate the diagnostic efficiency. A nomogram predicting the risk of grade 3 in clinical stage IA lung adenocarcinoma was constructed based on multivariate logistic regression, combining independent predictors and the optimal radiomics signatures.Multivariate logistic regression revealed that males exhibited a higher prevalence of grade 3 tumors, and solid nodules were frequently observed through radiological assessments. The utilization of radiomics features extracted from the VOI entire resulted in significant improvements in predictive performance, as evidenced by AUC values of 0.900 (0.880-0.942), 0.885 (0.824-0.946), and 0.888 (0.782-0.993) for the training, internal validation, and external validation datasets, respectively. Furthermore, the nomogram that combined VOI entire -based radiomics signatures and Clin-Rad characteristics, exhibited remarkable predictive performance. This was indicated by AUC values of 0.910(0.873-0.942), 0.891 (0.845-0.937), and 0.905 (0.846-0.964) for the training, internal validation, and external validation datasets, respectively.The extraction of radiomics features from both the indented and peri-tumoral regions does not offer any additional benefits in predicting grade 3 tumors according to the IASLC system. However, when combining the VOI entire-based radiomics model with Clin-Rad characteristics, the resulting integrated nomogram exhibited remarkable predictive performance.

Micropapillary and Solid Histologic Patterns in N1 and N2 Lymph Node Metastases Are Independent Factors of Poor Prognosis in Patients With Stages II to III Lung Adenocarcinoma

INTRODUCTION

High-grade histologic patterns are associated with poor prognosis in patients with primary nonmucinous lung adenocarcinoma (ADC). We investigated whether the presence of micropapillary (MIP), solid (SOL), or both patterns in lymph node (LN) metastases has prognostic value.

METHODS

Patients who underwent lobectomy for pathologic stages II to III lung ADC with N1 or N2 LN metastases (N = 360; 2000-2012) were analyzed. We assessed overall survival (OS), lung cancer-specific cumulative incidence of death (LC-CID), and cumulative incidence of recurrence (CIR) between patients with and without MIP/SOL patterns in LN metastases. Multivariable Cox regression analysis was used to quantify the association between MIP/SOL patterns and outcomes.

RESULTS

MIP and SOL in LN metastases were associated with a higher incidence of smoking history (p = 0.004), tumor necrosis (p = 0.013), and spread of tumor through air spaces (p < 0.0001), a higher prevalence of MIP or SOL in the primary tumor (p < 0.0001), shorter OS (5-y OS, 40% [95% confidence interval or CI: 29%-56%] versus 63% [48%-83%] for no MIP/SOL in LNs, p = 0.03), higher LC-CID (5-y, 43% [29%-56%] versus 14% [4%-29%], p = 0.013), and higher CIR (5-y, 65% [50%-77%] versus 43% [25%-60%], p = 0.057). MIP and SOL in LN metastases were independently associated with poor outcomes: OS (hazard ratio [HR] = 1.81 [95% CI: 1.00-3.29], p = 0.05), LC-CID (HR = 3.10 [1.30-7.37], p = 0.01), and CIR (HR = 2.06 [1.09-3.90], p = 0.026).

CONCLUSIONS

MIP/SOL histologic patterns in N1 or N2 LN metastases are associated with worse outcomes in patients with stages II to III lung ADC. MIP/SOL histologic patterns in LN metastases can stratify patients with high-risk stages II to III lung ADC.

EB-OCT: a potential strategy on early diagnosis and treatment for lung cancer

Lung cancer is the leading cause of cancer-related death in China and the world, mainly attributed to delayed diagnosis, given that currently available early screening strategies exhibit limited value. Endobronchial optical coherence tomography (EB-OCT) has the characteristics of non-invasiveness, accuracy, and repeatability. Importantly, the combination of EB-OCT with existing technologies represents a potential approach for early screening and diagnosis. In this review, we introduce the structure and strengths of EB-OCT. Furthermore, we provide a comprehensive overview of the application of EB-OCT on early screening and diagnosis of lung cancer from in vivo experiments to clinical studies, including differential diagnosis of airway lesions, early screening for lung cancer, lung nodules, lymph node biopsy and localization and palliative treatment of lung cancer. Moreover, the bottlenecks and difficulties in developing and popularizing EB-OCT for diagnosis and treatment during clinical practice are analyzed. The characteristics of OCT images of normal and cancerous lung tissues were in good agreement with the results of pathology, which could be used to judge the nature of lung lesions in real time. In addition, EB-OCT can be used as an assistant to biopsy of pulmonary nodules and improve the success rate of biopsy. EB-OCT also plays an auxiliary role in the treatment of lung cancer. In conclusion, EB-OCT is non-invasive, safe and accurate in real-time. It is of great significance in the diagnosis of lung cancer and suitable for clinical application and is expected to become an important diagnostic method for lung cancer in the future.

Association of frequent hypermethylation with high grade histological subtype in lung adenocarcinoma

Lung adenocarcinoma is classified morphologically into five histological subtypes according to the WHO classification. While each histological subtype correlates with a distinct prognosis, the molecular basis has not been fully elucidated. Here we conducted DNA methylation analysis of 30 lung adenocarcinoma cases annotated with the predominant histological subtypes and three normal lung cases using the Infinium BeadChip. Unsupervised hierarchical clustering analysis revealed three subgroups with different methylation levels: high-, intermediate-, and low-methylation epigenotypes (HME, IME, and LME). Micropapillary pattern (MPP)-predominant cases and those with MPP components were significantly enriched in HME (p = 0.02 and p = 0.03, respectively). HME cases showed a significantly poor prognosis for recurrence-free survival (p < 0.001) and overall survival (p = 0.006). We identified 365 HME marker genes specifically hypermethylated in HME cases with enrichment of "cell morphogenesis" related genes; 305 IME marker genes hypermethylated in HME and IME, but not in LME, with enrichment "embryonic organ morphogenesis"-related genes; 257 Common marker genes hypermethylated commonly in all cancer cases, with enrichment of "regionalization"-related genes. We extracted surrogate markers for each epigenotype and designed pyrosequencing primers for five HME markers (TCERG1L, CXCL12, FAM181B, HOXA11, GAD2), three IME markers (TBX18, ZNF154, NWD2) and three Common markers (SCT, GJD2, BARHL2). DNA methylation profiling using Infinium data was validated by pyrosequencing, and HME cases defined by pyrosequencing results also showed the worse recurrence-free survival. In conclusion, lung adenocarcinomas are stratified into subtypes with distinct DNA methylation levels, and the high-methylation subtype correlated with MPP-predominant cases and those with MPP components and showed a poor prognosis.

Treatment Strategies for KRAS-Mutated Non-Small-Cell Lung Cancer

Activating mutations in KRAS are highly prevalent in solid tumours and are frequently found in 35% of lung, 45% of colorectal, and up to 90% of pancreatic cancers. Mutated KRAS is a prognostic factor for disease-free survival (DFS) and overall survival (OS) in NSCLC and is associated with a more aggressive clinical phenotype, highlighting the need for KRAS-targeted therapy. Once considered undruggable due to its smooth shallow surface, a breakthrough showed that the activated G12C-mutated KRAS isozyme can be directly inhibited via a newly identified switch II pocket. This discovery led to the development of a new class of selective small-molecule inhibitors against the KRAS G12C isoform. Sotorasib and adagrasib are approved in locally advanced or metastatic NSCLC patients who have received at least one prior systemic therapy. Currently, there are at least twelve KRAS G12C inhibitors being tested in clinical trials, either as a single agent or in combination. In this study, KRAS mutation prevalence, subtypes, rates of occurrence in treatment-resistant invasive mucinous adenocarcinomas (IMAs), and novel drug delivery options are reviewed. Additionally, the current status of KRAS inhibitors, multiple resistance mechanisms that limit efficacy, and their use in combination treatment strategies and novel multitargeted approaches in NSCLC are discussed.

The prognostic value of histopathology in invasive lung adenocarcinoma: a comparative review of the main proposed grading systems

INTRODUCTION

An accurate histological evaluation of invasive lung adenocarcinoma is essential for a correct clinical and pathological definition of the tumour. Different grading systems have been proposed to predict the prognosis of invasive lung adenocarcinoma.

AREAS COVERED

Invasive non mucinous lung adenocarcinoma is often morphologically heterogeneous, consisting of complex combinations of architectural patterns with different proportions. Several grading systems for non-mucinous lung adenocarcinoma have been proposed, being the main based on architectural differentiation and the predominant growth pattern. Herein we perform a thorough review of the literature using PubMed, Scopus and Web of Science and we highlight the peculiarities and the differences between the main grading systems and compare the data about their prognostic value. In addition, we carried out an evaluation of the proposed grading systems for less common histological variants of lung adenocarcinoma, such as fetal adenocarcinoma and invasive mucinous adenocarcinoma.

EXPERT OPINION

The current IASLC grading system, based on the combined score of predominant growth pattern plus high-grade histological pattern, shows the stronger prognostic significance than the previous grading systems in invasive non mucinous lung adenocarcinoma.

Comparison of small biopsy and cytology specimens: Subtyping of pulmonary adenocarcinoma

Objectives

The aims of this study was to investigate the use of cytologic samples for subclassification of lung adenocarcinoma and the cytologic-histologic correlation in lung adenocarcinoma subtypes using small samples.

Methods and Methods

Cytological characteristics of lung adenocarcinoma subtypes were summarized by a literature review. Cytology samples from 115 patients with lung adenocarcinoma confirmed by small biopsies were classified by subtype. The diagnostic concordance of subtypes between biopsy and cytology samples was assessed.

Results

Among the 115 cases, 62 (53.9%) had acinar predominant pattern, 16 (13.9%) were papillary predominant pattern, 29 (25.2%) had solid predominant pattern, 3 (2.6%) had lepidic predominant pattern, and 5 (4.3%) had micropapillary predominant pattern. All corresponding cytologic samples were classified into five subtypes based on cytomorphology features, with concordance rates of 74.2% (46 patients) in c-acinar subtype, 56.3% (nine patients) in c-papillary subtype, 24.1% (seven patients) in c-solid subtype, 66.7% (two patients) in c-lepidic subtype, and 40% (two patients) in c-micropapillary subtype. Collectively, the cytology and small biopsy concordance rate was approximately 57.4%.

Conclusion

Subtyping of lung adenocarcinoma using cytologic specimens is challenging and the consistency rate varies with the subtype. Acinar predominant tumors have an excellent cytologic-histologic correlation compared to tumors with predominant solid or micropapillary pattern. Evaluating cytomorphologic features of different lung adenocarcinoma subtypes can reduce the false-negative rate of lung adenocarcinoma, particularly for the mild, atypical micropapillary subtype, and improve diagnostic accuracy.

Glucose metabolic heterogeneity correlates with pathological features and improves survival stratification of resectable lung adenocarcinoma

OBJECTIVE

We investigated whether glycolytic heterogeneity correlated with histopathology, and further stratified the survival outcomes pertaining to resectable lung adenocarcinoma.

METHODS

We retrospectively analyzed the ¹⁸F-fluorodeoxyglucose positron emission tomography-derived entropy and histopathology from 128 patients who had undergone curative surgery for lung adenocarcinoma. Disease-free survival (DFS) and overall survival (OS) were analyzed using univariate and multivariate Cox regression models. Independent predictors were used to construct survival prediction models.

RESULTS

Entropy significantly correlated with histopathology, including tumor grades, lympho-vascular invasion, and visceral pleural invasion. Furthermore, entropy was an independent predictor of unfavorable DFS (p = 0.031) and OS (p = 0.004), while pathological nodal metastasis independently predicted DFS (p = 0.009). Our entropy-based models outperformed the traditional staging system (c-index = 0.694 versus 0.636, p = 0.010 for DFS; c-index = 0.704 versus 0.630, p = 0.233 for OS). The models provided further survival stratification in subgroups comprising different tumor grades (DFS: HR = 2.065, 1.315, and 1.408 for grade 1-3, p = 0.004, 0.001, and 0.039, respectively; OS: HR = 25.557, 6.484, and 2.570, for grade 1-3, p = 0.006, < 0.001, and = 0.224, respectively).

CONCLUSION

The glycolytic heterogeneity portrayed by entropy is associated with aggressive histopathological characteristics. The proposed entropy-based models may provide more sophisticated survival stratification in addition to histopathology and may enable personalized treatment strategies for resectable lung cancer.

The IASLC grading system for invasive pulmonary adenocarcinoma: a potential prognosticator for patients receiving neoadjuvant therapy

Background

Grading system for resected invasive pulmonary adenocarcinoma proposed by the International Association for the Study of Lung Cancer (IASLC) was validated as a strong prognostic indicator. Nonetheless, the efficacy of utilizing such grading system in prognostic assessment of patients receiving neoadjuvant therapy still needs elucidating.

Methods

A retrospective study was conducted including patients with resected adenocarcinoma following neoadjuvant chemotherapy or targeted therapy from August 2012 to December 2020 in Shanghai Pulmonary Hospital. All the surgical specimens were re-evaluated and graded. The prognostic value of the grading system was further validated.

Results

Ultimately, a total of 198 patients were enrolled in this study, and subdivided into three cohorts according to the grading system. There were 13 (6.6%), 37 (18.7%), and 148 (74.7%) patients belonging to Grades 1, 2, and 3, respectively. IASLC grading system demonstrated significant power in prognosis differentiation of the entire cohort [recurrence-free survival (RFS), p < 0.001; overall survival (OS), p < 0.001] and the neoadjuvant chemotherapy and targeted therapy cohorts separately, and was further verified as a significant prognostic indicator for RFS and OS in multivariable Cox analysis. Since the majority of the patients (84.8%) did not achieve major pathologic response (MPR), representing a wide spectrum of survival, the prognostic value of grading system in non-MPR cohort was further evaluated. Similar results were also obtained that IASLC grading system was assessed significant in univariable analysis of RFS (p < 0.001) and univariable analysis of OS (p = 0.001).

Conclusions

The prognostic efficacy of pathological evaluation of the residual proportion of pulmonary adenocarcinoma post-neoadjuvant therapy using IASLC grading system was preliminarily verified. Such grading system might assist prognostic evaluation of neoadjuvant cohort other than traditional pathological parameters.

Challenges of the eighth edition of the American Joint Committee on Cancer staging system for pathologists focusing on early stage lung adenocarcinoma

BACKGROUND

The eighth edition of the American Joint Committee on Cancer (AJCC) staging system for lung cancer adopts new criteria for tumor size, and for determining pTis, pT1a(mi), and pT1a. The latter is based on the size of stromal invasion. It is quite challenging for lung pathologists.

METHODS

All patients who had undergone surgical resection for pulmonary adenocarcinoma (ADC) at Chung Shan Medical University Hospital between January 2014 and April 2018 were reviewed, and restaged according to the eighth AJCC staging system. The clinical characteristics and survival of patients with tumor stage 0 (pTis), I or II were analyzed.

RESULTS

In total, 376 patients were analyzed. None of the pTis, pT1a(mi), or pT1a tumors recurred during the follow-up period up to 5 years, but pT1b, pT1c, pT2a, and pT2b tumors all had a few tumor recurrences (p < 0.0001). In addition, 95.2%, 100%, and 77.5% of pTis, pT1a(mi), and pT1a tumors, respectively, had tumor sizes ≤1.0 cm by gross examination. All pTis, pT1a(mi), and pT1a tumors exhibited only lepidic, acinar, or papillary patterns histologically.

CONCLUSIONS

This study demonstrated excellent survival for lung ADC patients with pTis, pT1a(mi), and pT1a tumors when completely excised. To reduce the inconsistencies between pathologists, staging lung ADC with tumors of ≤1 cm in size grossly as pTis, pT1a(mi), or pT1a may not be necessary when the tumors exhibit only lepidic, acinar, or papillary histological patterns. A larger cohort study with sufficient follow-up data is necessary to support this proposal.

Preoperative levels of folate receptor-positive circulating tumor cells in different subtypes of early-stage lung adenocarcinoma: Predictive value for determining extent of surgical resection

Background

The objective was to measure the correlations of preoperative levels of folate receptor-positive circulating tumor cells (FR⁺CTCs) with clinical characteristics and histologic subtype in early-stage lung adenocarcinoma, and to determine the predictive value of FR⁺CTC level in preoperative determination of the extent of surgical resection.

Patients and methods

In this retrospective, single-institution, observational study, preoperative FR⁺CTC levels were measured via ligand-targeted enzyme-linked polymerization in patients with early-stage lung adenocarcinoma. Receiver operating characteristic (ROC) analysis was used to identify the optimal cutoff value of FR⁺CTC level for prediction of various clinical characteristics and histologic subtypes.

Results

No significant difference in FR⁺CTC level was observed among patients with adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) (P = 0.813). Within the non-mucinous adenocarcinoma group, no difference was observed among patients with tumors whose predominant growth patterns were lepidic, acinar, papillary, micropapillary, solid, and complex gland (P = 0.053). However, significant differences in FR⁺CTC level were observed between patients with and without the micropapillary subtype [11.21 (8.22-13.61) vs. 9.85 (7.43-12.63), P = 0.017], between those with and without the solid subtype [12.16 (8.27-14.90) vs. 9.87 (7.50-12.49), P = 0.022], and between those with any of the advanced subtypes (micropapillary, solid, or complex glands) vs. none of these [10.48 (7.83-13.67) vs. 9.76 (7.42-12.42), P = 0.032]. FR⁺CTC level was also correlated with degree of differentiation of lung adenocarcinoma (P = 0.033), presence of visceral pleural invasion (VPI) of lung carcinoma (P = 0.003), and lymph node metastasis of lung carcinoma (P = 0.035).

Conclusion

FR⁺CTC level is of potential predictive value in determining the presence of aggressive histologic patterns (micropapillary, solid, and advanced subtypes), degree of differentiation, and occurrence of VPI and lymph node metastasis in IAC. Measurement of FR⁺CTC level combined with intraoperative frozen sections may represent a more effective method of guiding resection strategy in cases of cT1N0M0 IAC with high-risk factors.

Cyclin-Dependent Kinase Subunit 2 (CKS2) as a Prognostic Marker for Stages I-III Invasive Non-Mucinous Lung Adenocarcinoma and Its Role in Affecting Drug Sensitivity

With the aim of improving the prognosis of patients with lung adenocarcinoma (LUAD), we identified the biomarker related to the sensitivity of patients to chemotherapy drugs and explored the potential mechanisms. As a cell cycle-related protein, CKS2 has an essential role to play in tumor progression and prognosis. CKS2 expression was measured using TCGA RNA-sequencing data and immunohistochemistry. The sensitivity data of tumor cells to chemotherapeutic drugs for lung cancer was acquired from the Cancer Therapeutics Response Portal (CTRP) database. A range of bioinformatics methods was used to explore the mechanisms of CKS2 upregulation. The biological functions of CKS2 were predicted using GO and KEGG enrichment analysis, as well as GSEA. CKS2 expression was up-regulated in stages I-III invasive non-mucinous lung adenocarcinoma and varied significantly between various histological subtypes. High CKS2 expression worsened the prognosis of patients. The CKS2 expression level was linked to the sensitivity of LUAD cells to carboplatin and paclitaxel. CKS2 upregulation was associated with the immune microenvironment, mRNA methylation, and competing endogenous RNAs (ceRNAs). CKS2 can serve as a diagnostic and prognostic biomarker for stages I-III invasive non-mucinous lung adenocarcinoma and modulate the effect of paclitaxel and carboplatin by regulating microtubule binding and influencing carboplatin binding to DNA.

Immunogenomic profiling of lung adenocarcinoma reveals poorly differentiated tumors are associated with an immunogenic tumor microenvironment

OBJECTIVES

Pathologists have routinely observed distinct histologic patterns of growth in early-stage lung adenocarcinoma (LUAD), which have been suggested to be associated with prognosis. Herein, we investigated the relationship between LUAD patterns of growth, as defined by the updated international association for the study of lung cancer (IASLC) grading criteria, and differences in the tumor immune microenvironment to identify predictors of response to immunotherapy.

METHODS

174 resected stage I-III LUAD tumors were classified by histologic pattern of growth (i.e. solid, micropapillary, acinar, papillary, and lepidic) and then grouped as well differentiated, moderately differentiated, and poorly differentiated. Comprehensive multiplatform analysis including whole exome sequencing, gene expression profiling, immunohistochemistry, CIBERSORT, and T-cell receptor sequencing was performed and groups were compared for differences in genomic drivers, immune cell infiltrate, clonality, and survival. Finally, multivariate analysis was performed adjusting for pathologic stage and smoking status.

RESULTS

Poorly differentiated tumors demonstrated a strong association with smoking relative to moderately differentiated or well differentiated tumors. However, unlike in prior reports, poorly differentiated tumors were not associated with a worse survival after curative-intent resection. Genomic analysis revealed that poorly differentiated tumors are associated with high tumor mutation burden but showed no association with oncogenic drivers. Immune analyses revealed that poorly differentiated tumors are associated with increased T-cell clonality, expression of PD-L1, and infiltration by cytotoxic CD8 T-cells, activated CD4 T-cells, and pro-inflammatory (M1) macrophages. Finally, multivariate analysis controlling for stage and smoking status confirmed independence of immune differences between IASLC grade groups.

CONCLUSIONS

Poorly differentiated tumors, as defined by the updated IASLC grading criteria, are associated with a distinct immunogenic tumor microenvironment that predicts for therapeutic response to immune agents, including checkpoint inhibitors, and should be included in the clinical trial design of immunotherapy studies in early-stage lung adenocarcinoma.

Lung cancer: Premalignant biology and medical prevention

Lung cancer (both adenocarcinoma and squamous cell) progress through a series of pre-malignant histologic changes before the development of invasive disease. Each of these carcinogenic cascades is defined by genetic and epigenetic alterations in pulmonary epithelial cells. Additionally, alterations in the immune response, progenitor cell function, mutational burden, and microenvironmental mediated survival of mutated clones contribute to the risk of pre-malignant lesions progressing to cancer. Medical preventions studies have been completed and current and future trials are informed by the improved understanding of pre-malignancy. This will lead to precision chemoprevention trials based on lesional biology and histologic characteristics.

Radiomics for differentiating minimally invasive adenocarcinoma from precursor lesions in pure ground-glass opacities on chest computed tomography

OBJECTIVE

To explore the correlation between radiomic features and the pathology of pure ground-glass opacities (pGGOs), we established a radiomics model for predicting the pathological subtypes of minimally invasive adenocarcinoma (MIA) and precursor lesions.

METHODS

CT images of 1521 patients with lung adenocarcinoma or precursor lesions appearing as pGGOs on CT in our hospital (The Third Affiliated Hospital of Sun Yat-sen University) from January 2015 to March 2021 were analyzed retrospectively and selected based on inclusion and exclusion criteria. pGGOs were divided into an atypical adenomatous hyperplasia (AAH)/adenocarcinoma in situ (AIS) group and an MIA group. Radiomic features were extracted from the original and preprocessed images of the region of interest. ANOVA and least absolute shrinkage and selection operator feature selection algorithm were used for feature selection. Logistic regression algorithm was used to construct radiomics prediction model. Receiver operating characteristic curves were used to evaluate the classification efficiency.

RESULTS

129 pGGOs were included. 2107 radiomic features were extracted from each region of interest. 18 radiomic features were eventually selected for model construction. The area under the curve of the radiomics model was 0.884 [95% confidence interval (CI), 0.818-0.949] in the training set and 0.872 (95% CI, 0.756-0.988) in the test set, with a sensitivity of 72.73%, specificity of 88.24% and accuracy of 79.47%. The decision curve indicated that the model had a high net benefit rate.

CONCLUSION

The prediction model for pathological subtypes of MIA and precursor lesions in pGGOs demonstrated a high diagnostic accuracy.

ADVANCES IN KNOWLEDGE

We focused on lesions appearing as pGGOs on CT and revealed the differences in radiomic features between MIA and precursor lesions. We constructed a radiomics prediction model and improved the diagnostic accuracy for the pathology of MIA and precursor lesions.

Differential Diagnostic Value of Histology in MPLC and IPM: A Systematic Review and Meta-Analysis

Background

The paramount issue regarding multiple lung cancer (MLC) is whether it represents multiple primary lung cancer (MPLC) or intrapulmonary metastasis (IPM), as this directly affects both accurate staging and subsequent clinical management. As a classic method, histology has been widely utilized in clinical practice. However, studies examining the clinical value of histology in MLC have yielded inconsistent results; thus, this remains to be evaluated. Here, we performed a meta-analysis to assess the differential diagnostic value of histology in MPLC and IPM and to provide evidence-based medicine for clinical work.

Methods

PubMed, Embase, and Web of Science databases were searched to collect relevant literature according to PRISMA, and inclusion and exclusion criteria were set up to screen and assess the literature. The data required for reconstructing a 2 × 2 contingency table were extracted directly or calculated indirectly from the included studies, and statistical analysis was carried out by using Stata 15, Meta-DiSc 1.4, and Review Manager 5.4 software.

Results

A total of 34 studies including 1,075 pairs of tumors were included in this meta-analysis. Among these studies, 11 were about the M-M standard and the pooled sensitivity and specificity were 0.78 (95% CI: 0.71–0.84) and 0.47 (95% CI: 0.38–0.55), respectively; 20 studies were about CHA and the pooled sensitivity and specificity were 0.76 (95% CI: 0.72–0.80) and 0.74 (95% CI: 0.68–0.79), respectively; and 3 studies were about the “CHA & Lepidic” criteria and the pooled sensitivity and specificity were 0.96 (95% CI: 0.85–0.99) and 0.47 (95% CI: 0.21–0.73), respectively. The combined pooled sensitivity, specificity, PLR, NLR, DOR, and the area under the SROC curve of the 34 studies were 0.80 (95% CI: 0.73–0.86), 0.64 (95% CI: 0.51–0.76), 2.25 (95% CI: 1.59–3.17), 0.31 (95% CI: 0.23–0.43), 7.22 (95% CI: 4.06–12.81), and 0.81 (95% CI: 0.77–0.84), respectively.

Conclusion

The current evidence indicated that histology had a moderate differential diagnostic value between MPLC and IPM. Among the three subgroups, the “CHA & Lepidic” criteria showed the highest sensitivity and CHA showed the highest specificity. Further research is necessary to validate these findings and to improve clinical credibility.

Systematic Review Registration

PROSPERO, identifier CRD42022298180.

Preference of grade and lymphovascular invasion over invasive size measurement in stage I lung adenocarcinoma

AIMS

Although it is necessary to measure the invasive size of lung adenocarcinoma with a lepidic component, it is not uncommon to have trouble in measuring the invasive size of lung adenocarcinoma. This study examined whether there were other stronger prognostic factors than invasive size.

METHODS

We characterised the clinicopathological features associated with recurrence-free survival (RFS) of 686 patients with the pathological stage (p-Stage) I lung adenocarcinoma. Moreover, we compared the area under the curve (AUC) values for recurrence between various combinations of pathological-baseline (age & sex & p-Stage based on invasive size) (B(i)) and several prognostic factors, and various combinations of p-baseline based on total tumour size (B(t)) and several prognostic factors.

RESULTS

AUC showed no significant differences between B(i) & new International Association for the Study of Lung Cancer grade (G) or vascular invasion (V), and B(t) & G or V. AUC was the highest in B & G & lymphatic invasion (L) & V. RFS was significantly shorter in patients with G3 OR L(+) OR V(+) than in those with G≤2 AND L(-) AND V(-) in each p-Stage based on invasive size (p-Stage(i)) and p-Stage based on total tumour size (p-Stage(t)) (p<0.05), and there were no significant differences in RFS between each p-Stage(i) and p-Stage(t).

CONCLUSIONS

In any invasive size or total tumour size of p-Stage I lung adenocarcinoma, G, L and V are more powerful prognostic factors than the size criteria of p-Stage. Therefore, pathologists should focus on these pathological findings.

High-grade tumor classified by new system is a prognostic predictor in resected lung adenocarcinoma

OBJECTIVES

A grading system for pulmonary adenocarcinoma has not been established; hence, the International Association for the Study of Lung Cancer (IASLC) pathology panel developed a new grading system for invasive adenocarcinoma. We aimed to evaluate the prognostic significance of the IASLC grading system for invasive pulmonary adenocarcinoma.

METHODS

We conducted a retrospective analysis of 471 Japanese patients with resected lung adenocarcinoma. Tumors were classified in accordance with the IASLC grading system and 2015 World Health Organization classification. We analyzed recurrence-free probability (RFP) and overall survival (OS) using the log-rank test and compared the two grading systems using the Cox proportional hazards model.

RESULTS

Grade 3 tumors of the IASLC system and high-grade tumors of the 2015 World Health Organization classification were present in 38% and 17% of patients, respectively. The 5-year RFP was lower in patients with IASLC Grade 3 tumors (45%) than in patients with IASLC Grade 1 and 2 tumors (91% and 83%, respectively). The 5-year RFP of patients with IASLC Grade 2 tumors (83%) was higher than of those with 2015 World Health Organization intermediate tumors (69%). On multivariate analysis for recurrence, IASLC Grade 3 was an independent prognostic factor of worse RFP. We showed similar results on analysis for the OS.

CONCLUSIONS

The prognostic significance of IASLC Grade 3 tumors on recurrence-free probability was confirmed through both univariate and multivariate analyses. Thus, the IASLC Grade 3 tumor is an independent factor of poor prognosis in patients with resected lung adenocarcinoma.

Primary lung invasive adenocarcinoma misdiagnosed as infectious pneumonia in 18F-FDG PET/CT:A case report

A 64-year-old woman presented to our hospital with cough and a large amount of white foam sputum, F-fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT) showed diffuse ground-glass opacities in both lungs, which was considered as infectious pneumonia. However, after ineffective anti-infection, the primary invasive mucinous adenocarcinoma was finally diagnosed. Pulmonary invasive mucinous adenocarcinoma is rare and special subtype of lung adenocarcinoma, it has a variety of imaging manifestations. When intense tracer uptake, air bronchial sign, honeycomb sign present in diffuse ground-glass opacities in F-FDG PET/CT, lung invasive mucinous adenocarcinoma should be highly suspected.

A lepidic gene signature predicts patient prognosis and sensitivity to immunotherapy in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma, the most common type of lung cancer, has a high level of morphologic heterogeneity and is composed of tumor cells of multiple histological subtypes. It has been reported that immune cell infiltration significantly impacts clinical outcomes of patients with lung adenocarcinoma. However, it is unclear whether histologic subtyping can reflect the tumor immune microenvironment, and whether histologic subtyping can be applied for therapeutic stratification of the current standard of care.

METHODS

We inferred immune cell infiltration levels using a histological subtype-specific gene expression dataset. From differential gene expression analysis between different histological subtypes, we developed two gene signatures to computationally determine the relative abundance of lepidic and solid components (denoted as the L-score and S-score, respectively) in lung adenocarcinoma samples. These signatures enabled us to investigate the relationship between histological composition and clinical outcomes in lung adenocarcinoma using previously published datasets.

RESULTS

We found dramatic immunological differences among histological subtypes. Differential gene expression analysis showed that the lepidic and solid subtypes could be differentiated based on their gene expression patterns while the other subtypes shared similar gene expression patterns. Our results indicated that higher L-scores were associated with prolonged survival, and higher S-scores were associated with shortened survival. L-scores and S-scores were also correlated with global genomic features such as tumor mutation burdens and driver genomic events. Interestingly, we observed significantly decreased L-scores and increased S-scores in lung adenocarcinoma samples with EGFR gene amplification but not in samples with EGFR gene mutations. In lung cancer cell lines, we observed significant correlations between L-scores and cell sensitivity to a number of targeted drugs including EGFR inhibitors. Moreover, lung cancer patients with higher L-scores were more likely to benefit from immune checkpoint blockade therapy.

CONCLUSIONS

Our findings provided further insights into evaluating histology composition in lung adenocarcinoma. The established signatures reflected that lepidic and solid subtypes in lung adenocarcinoma would be associated with prognosis, genomic features, and responses to targeted therapy and immunotherapy. The signatures therefore suggested potential clinical translation in predicting patient survival and treatment responses. In addition, our framework can be applied to other types of cancer with heterogeneous histological subtypes.

Correlation of Epidermal Growth Factor Receptor Mutation With Major Histologic Subtype of Lung Adenocarcinoma According to IASLC/ATS/ERS Classification

OBJECTIVE

Our prospective study aims to define the correlation of EGFR(epidermal growth factor receptor) mutations with major histological subtypes of lung adenocarcinoma from resected and non-resected specimens, according to the WHO 2015 classification, in Moroccan North East Population.

METHODS

Epidermal growth factor receptor mutations of 150 primary lung adenocarcinoma were performed using Real-Time PCR or SANGER sequencing. SPSS 21 was used to assess the relationship between histological subtypes of lung adenocarcinoma and EGFR mutation status.

RESULTS

25 mutations were detected in the series of 150 lung adenocarcinomas, most of which were found in cases with papillary, acinar, patterns than without these patterns and more frequently occurred in the cases without solid pattern than with this pattern. A significant correlation was observed between EGFR mutation and acinar (P = 0,024), papillary pattern (P = 0,003) and, negative association with a solid pattern (P < 0,001). In females, EGFR mutations were significantly correlated with the acinar pattern (P = 0,02), whereas in males with the papillary pattern (P = 0,01). Association between the histologic component and exon 19 deletions and exon 21 mutations were also evaluated and, we found a significant correlation between the papillary major pattern with exon 19 mutations (P = 0,004) and, ex21 with the acinar component (P = 0,03).

CONCLUSION

An analysis of resected and non-resected lung ADC specimens in 150 Moroccan Northeast patients, revealed that acinar and papillary patterns may predict the presence of a mutation in the EGFR gene. While the solid major pattern may indicate a low mutation rate of the EGFR gene.

Prognostic Nomograms Based on Ground Glass Opacity and Subtype of Lung Adenocarcinoma for Patients with Pathological Stage IA Lung Adenocarcinoma

The value of lung adenocarcinoma (LUAD) subtypes and ground glass opacity (GGO) in pathological stage IA invasive adenocarcinoma (IAC) has been poorly understood, and reports of their association with each other have been limited. In the current study, we retrospectively reviewed 484 patients with pathological stage IA invasive adenocarcinoma (IAC) at Sun Yat-sen University Cancer Center from March 2011 to August 2018. Patients with at least 5% solid or micropapillary presence were categorized as high-risk subtypes. Independent indicators for disease-free survival (DFS) and overall survival (OS) were identified by multivariate Cox regression analysis. Based on these indicators, we developed prognostic nomograms of OS and DFS. The predictive performance of the two nomograms were assessed by calibration plots. A total of 412 patients were recognized as having the low-risk subtype, and 359 patients had a GGO. Patients with the low-risk subtype had a high rate of GGO nodules (p < 0.001). Multivariate Cox regression analysis showed that the high-risk subtype and GGO components were independent prognostic factors for OS (LUAD subtype: p = 0.002; HR 3.624; 95% CI 1.263–10.397; GGO component: p = 0.001; HR 3.186; 95% CI 1.155–8.792) and DFS (LUAD subtype: p = 0.001; HR 2.284; 95% CI 1.448–5.509; GGO component: p = 0.003; HR 1.877; 95% CI 1.013–3.476). The C-indices of the nomogram based on the LUAD subtype and GGO components to predict OS and DFS were 0.866 (95% CI 0.841–0.891) and 0.667 (95% CI 0.586–0.748), respectively. Therefore, the high-risk subtype and GGO components were potential prognostic biomarkers for patients with stage IA IAC, and prognostic models based on these indicators showed good predictive performance and satisfactory agreement between observational and predicted survival.

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.

Mucinous Adenocarcinoma With Intrapulmonary Metastasis Harboring KRAS and GNAS Mutations Arising in Congenital Pulmonary Airway Malformation

OBJECTIVES

Mucinous adenocarcinoma arising in unresected congenital pulmonary airway malformation (CPAM) is rare. Underlying driver mutations in addition to KRAS gain-of-function mutations in this setting and the long-term outcomes of these patients are unknown.

METHODS

We report a case of metastatic mucinous adenocarcinoma harboring both KRAS and GNAS mutations arising in a type 1 CPAM of a 14-year-old male. A literature review was performed.

RESULTS

Next-generation sequencing revealed identical KRAS (G12V) mutations in both the CPAM and metastatic adenocarcinoma and a missense mutation in the GNAS (R201C) gene in the metastatic adenocarcinoma only. Median survival was 23 and 4 years for patients with localized (no or limited spread within the same lobe of CPAM) and distant involvement (spread to any different lobe of CPAM) of mucinous cells, respectively (95% confidence interval, 23-23 and 1.5-22 years, respectively; P = .017).

CONCLUSIONS

Mucinous cell proliferation associated with type 1 CPAM has exceptionally good long-term outcomes if confined within the same lobe of CPAM. A second oncogenic mutation in the GNAS gene may be necessary for progression to malignancy and distant spread.

Clinicopathological, Radiological, and Molecular Features of Primary Lung Adenocarcinoma with Morule-Like Components

BACKGROUND

Morule-like component (MLC) was a rare structure in primary lung adenocarcinoma. We aimed to reveal the clinicopathological, radiological, immunohistochemical, and molecular features of lung adenocarcinoma with MLCs.

METHODS

Twenty lung adenocarcinomas with MLCs were collected, and computed tomographic and histological documents were reviewed. Immunohistochemistry, targeted next-generation sequencing, and Sanger sequencing for β-catenin gene were performed.

RESULTS

There were 9 lepidic adenocarcinomas, 8 acinar adenocarcinomas, 2 papillary adenocarcinomas, and 1 minimally invasive adenocarcinoma. Most patients (16/17) were shown a pure solid nodule, and 1 patient was shown a partly solid nodule on chest computed tomography (CT). Nine cases were accompanied with micropapillary components, and 3 were with cribriform components in which 2 suffered a worse prognosis. No significant association was found between the MCLs and the overall survival of lung adenocarcinoma (P = 0.109). The MLCs were often arranged in whorled or streaming patterns. The cells in MLCs showed syncytial and mild appearance. The MLCs were positive for E-cadherin, CK7, TTF-1, napsin-A, vimentin, and β-catenin (membrane), and negative for CK5/6, p40, p63, Synaptophysin, chromogranin A, and Cdx-2. EGFR mutation, ALK-EML4 fusion, HER2 amplification, and PIK3CA mutation were detected in 16 cases, 2 cases, 1 case, and 1 case, respectively. EGFR mutation was more frequent in adenocarcinomas with MLCs than those without MLCs (P = 0.040). β-catenin gene mutation was not detected in any patients.

CONCLUSIONS

MLC is often observed in the background of acinar, lepidic, and papillary adenocarcinomas. Lung adenocarcinomas with MLCs tend to appear as a solid mass on CT and harbor EGFR gene mutations. The micropapillary components and cribriform components may cause poor prognosis of lung adenocarcinomas with MLCs. Vimentin is always positive in MLCs, and it is a useful marker for the identification of MLCs.

The Prognostic Value of Non-Predominant Micropapillary Pattern in a Large Cohort of Resected Invasive Lung Adenocarcinoma Measuring ≤3 cm

The aim of this study was to analyze the influence of non-predominant micropapillary pattern in small sized invasive lung adenocarcinoma. A total of 986 lung adenocarcinoma patients with tumor size ≤3 cm were identified and classified according to the IALSC/ATS/ERS classification. Emphasis was placed on the impact of non-predominant micropapillary pattern on disease-free survival (DFS) and overall survival (OS). The relationship between lung adenocarcinoma subtype and lymph node involvement, EGFR mutation and KRAS mutation was also evaluated. A nomogram was developed to predict the probability of 3- and 5-year OS for these patients. The concordance index and calibration plot were used to validate this model. Among all 986 patients, the percentages of lymph node involvement were: 58.1, 50.0, 33.5, 21.4, 21.1, 10.9, 0, and 0% for micropapillary predominant, solid predominant, acinar predominant, papillary predominant, invasive mucinous adenocarcinoma (IMA), lepidic predominant, minimally invasive adenocarcinoma (MIA), adenocarcinoma in situ (AIS), respectively. The frequency of EGFR mutation in the cases of lepidic predominant, acinar predominant, MIA, micropapillary predominant, papillary predominant, solid predominant, IMA, and AIS were 51.1, 45.2, 44.4, 36.8, 29.3, 26.8, 8.3, and 0%, respectively. A non-predominant micropapillary pattern was observed in 344 (38.4%) invasive adenocarcinoma (IAC), and its presence predicted a poorer DFS (median: 56.0 months vs. 66.0 months, P <0.001) and OS (median: 61.0 months vs. 70.0 months, P <0.001). After propensity score matching, non-predominant micropapillary pattern retained its unfavorable effect on DFS (P = 0.007) and OS (P = 0.001). Multivariate analysis showed that non-predominant micropapillary pattern was identified as an independent prognostic factor for DFS (P = 0.003) and OS (P <0.001) in IAC. The nomogram showed good calibration and reliable discrimination ability (C-index = 0.775) to evaluated the 3- and 5-year OS. This retrospective analysis of patients with small sized IAC suggests the value of non-predominant micropapillary pattern to predict poor prognosis. A reliable nomogram model was constructed to provide personalized survival predictions.

CT Texture Analysis for Differentiating Bronchiolar Adenoma, Adenocarcinoma In Situ, and Minimally Invasive Adenocarcinoma of the Lung

Purpose: This study aimed to investigate the potential of computed tomography (CT) imaging features and texture analysis to distinguish bronchiolar adenoma (BA) from adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA).

Materials and Methods: Fifteen patients with BA, 38 patients with AIS, and 36 patients with MIA were included in this study. Clinical data and CT imaging features of the three lesions were evaluated. Texture features were extracted from the thin-section unenhanced CT images using Artificial Intelligence Kit software. Then, multivariate logistic regression analysis based on selected texture features was employed to distinguish BA from AIS/MIA. Receiver operating characteristics curves were performed to determine the diagnostic performance of the features.

Results: By comparison with AIS/MIA, significantly different CT imaging features of BA included nodule type, tumor size, and pseudo-cavitation sign. Among them, pseudo-cavitation sign had a moderate diagnostic value for distinguishing BA and AIS/MIA (AUC: 0.741 and 0.708, respectively). Further, a total of 396 quantitative texture features were extracted. After comparation, the top six texture features showing the most significant difference between BA and AIS or MIA were chosen. The ROC results showed that these key texture features had a high diagnostic value for differentiating BA from AIS or MIA, among which the value of a comprehensive model with six selected texture features was the highest (AUC: 0.977 or 0.976, respectively) for BA and AIS or MIA. These results indicated that texture analyses can effectively improve the efficacy of thin-section unenhanced CT for discriminating BA from AIS/MIA.

Conclusion: CT texture analysis can effectively improve the efficacy of thin-section unenhanced CT for discriminating BA from AIS/MIA, which has a potential clinical value and helps pathologist and clinicians to make diagnostic and therapeutic strategies.