Histological Assessment and Interobserver Agreement in Major Pathologic Response for Non-Small Cell Lung Cancer with Neoadjuvant Therapy.

Purpose: Major pathologic response (MPR), defined as ≤10% of residual viable tumor (VT), is a prognostic factor in non-small cell lung cancer (NSCLC) after neoadjuvant therapy. This study evaluated interobserver reproducibility in assessing MPR, compared area-weighted and unweighted VT (%) calculation, and determined optimal VT (%) cutoffs across histologic subtypes for survival prediction. Materials and Methods: This retrospective study included 108 patients with NSCLC who underwent surgical resection after neoadjuvant chemotherapy or chemoradiation at Seoul National University Bundang Hospital between 2009-2018. Three observers with varying expertise independently assessed tumor bed and VT (%) based on digital whole-slide images. Results: Reproducibility in tumor bed delineation was reduced in squamous cell carcinoma (SqCC) with smaller tumor bed, although overall concordance was high (Dice coefficient, 0.96; IoU score, 0.92). Excellent agreement was achieved for VT (%) (ICC=0.959) and MPR using 10% cutoff (Fleiss' kappa=0.911). Shifting between area-weighted and unweighted VT (%) showed only one case differing in MPR status out of 81 cases. The optimal cutoff was 10% for both adenocarcinoma (ADC) and SqCC. MPR+ was observed in 18 patients (17%), with SqCC showing higher MPR+ rates (p=0.044), lower VT (%) (p<0.001), and better event-free survival (p=0.015) than ADC. MPR+ significantly improved overall survival (p=0.023), event-free survival (p=0.001), and lung cancer-specific survival (p=0.012). Conclusion: While MPR assessment demonstrated robust reproducibility with minimal impact from the tumor bed, attention is warranted when evaluating smaller tumor beds in SqCC. A 10% cutoff reliably predicted survival across histologic subtypes with higher interobserver reproducibility.

Extracting lung cancer staging descriptors from pathology reports: A generative language model approach.

BACKGROUND: In oncology, electronic health records contain textual key information for the diagnosis, staging, and treatment planning of patients with cancer. However, text data processing requires a lot of time and effort, which limits the utilization of these data. Recent advances in natural language processing (NLP) technology, including large language models, can be applied to cancer research. Particularly, extracting the information required for the pathological stage from surgical pathology reports can be utilized to update cancer staging according to the latest cancer staging guidelines. OBJECTIVES: This study has two main objectives. The first objective is to evaluate the performance of extracting information from text-based surgical pathology reports and determining pathological stages based on the extracted information using fine-tuned generative language models (GLMs) for patients with lung cancer. The second objective is to determine the feasibility of utilizing relatively small GLMs for information extraction in a resource-constrained computing environment. METHODS: Lung cancer surgical pathology reports were collected from the Common Data Model database of Seoul National University Bundang Hospital (SNUBH), a tertiary hospital in Korea. We selected 42 descriptors necessary for tumor-node (TN) classification based on these reports and created a gold standard with validation by two clinical experts. The pathology reports and gold standard were used to generate prompt-response pairs for training and evaluating GLMs which then were used to extract information required for staging from pathology reports. RESULTS: We evaluated the information extraction performance of six trained models as well as their performance in TN classification using the extracted information. The Deductive Mistral-7B model, which was pre-trained with the deductive dataset, showed the best performance overall, with an exact match ratio of 92.24% in the information extraction problem and an accuracy of 0.9876 (predicting T and N classification concurrently) in classification. CONCLUSION: This study demonstrated that training GLMs with deductive datasets can improve information extraction performance, and GLMs with a relatively small number of parameters at approximately seven billion can achieve high performance in this problem. The proposed GLM-based information extraction method is expected to be useful in clinical decision-making support, lung cancer staging and research.

Assessment of TP53 and CDKN2A status as predictive markers of malignant transformation of sinonasal inverted papilloma.

The mechanism and predictive biomarkers of sinonasal inverted papilloma (IP) transformation into squamous cell carcinoma (SCC) are still unclear. We investigated the genetic mutations involved and the predictive biomarkers. Fourteen patients with SCC arising from IP and six patients with IPs without malignant transformation (sIP) were included. DNA was extracted separately from areas of normal tissue, IP, dysplasia, and SCC. Whole exome sequencing and immunohistochemistry was performed. Major oncogenic mutations were observed in the progression from IP to SCC. The most frequently mutated genes were TP53 (39%) and CDKN2A (27%). Mutations in TP53 and/or CDKN2A were observed in three of six IPs with malignant transformation (cIP); none were observed in sIPs. Tumor mutational burden (TMB) increased from IP to SCC (0.64/Mb, 1.11/Mb, and 1.25 for IP, dysplasia, and SCC, respectively). TMB was higher in the cIPs than in the sIPs (0.64/Mb vs 0.3/Mb). Three cIPs showed a diffuse strong or null pattern in p53, and one showed a total loss of p16, a distinct pattern from sIPs. Our result suggests that TP53 and CDKN2A status can be predictive markers of malignant transformation of IP. Furthermore, immunohistochemistry of p53 and p16 expression can be surrogate markers for TP53 and CDKN2A status.

Clinical Validation of Artificial Intelligence-Powered PD-L1 Tumor Proportion Score Interpretation for Immune Checkpoint Inhibitor Response Prediction in Non-Small Cell Lung Cancer.

PURPOSE: Evaluation of PD-L1 tumor proportion score (TPS) by pathologists has been very impactful but is limited by factors such as intraobserver/interobserver bias and intratumor heterogeneity. We developed an artificial intelligence (AI)-powered analyzer to assess TPS for the prediction of immune checkpoint inhibitor (ICI) response in advanced non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: The AI analyzer was trained with 393,565 tumor cells annotated by board-certified pathologists for PD-L1 expression in 802 whole-slide images (WSIs) stained by 22C3 pharmDx immunohistochemistry. The clinical performance of the analyzer was validated in an external cohort of 430 WSIs from patients with NSCLC. Three pathologists performed annotations of this external cohort, and their consensus TPS was compared with AI-based TPS. RESULTS: In comparing PD-L1 TPS assessed by AI analyzer and by pathologists, a significant positive correlation was observed (Spearman coefficient = 0.925; P < .001). The concordance of TPS between AI analyzer and pathologists according to TPS ≥50%, 1%-49%, and <1% was 85.7%, 89.3%, and 52.4%, respectively. In median progression-free survival (PFS), AI-based TPS predicted prognosis in the TPS 1%-49% or TPS <1% group better than the pathologist's reading, with the TPS ≥50% group as a reference (hazard ratio [HR], 1.49 [95% CI, 1.19 to 1.86] v HR, 1.36 [95% CI, 1.08 to 1.71] for TPS 1%-49% group, and HR, 2.38 [95% CI, 1.69 to 3.35] v HR, 1.62 [95% CI, 1.23 to 2.13] for TPS <1% group). CONCLUSION: PD-L1 TPS assessed by AI analyzer correlates with that of pathologists, with clinical performance also being comparable when referenced to PFS. The AI model can accurately predict tumor response and PFS of ICI in advanced NSCLC via assessment of PD-L1 TPS.

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

INTRODUCTION: The purpose of this study is to investigate the prognostic impact of spread through air spaces (STAS) in invasive mucinous adenocarcinoma (IMA). MATERIALS AND METHODS: From 2015 to 2019, patients who underwent complete resection of IMA were extracted from the prospective database. Multivariable Cox-regression analysis and inverse probability of treatment weight (IPTW) - adjusted log-rank test for 5-year recurrence-free survival (RFS) were performed. RESULTS: STAS was observed in 39.1% (53 out of 133). The STAS (+) group shows larger tumor size (2.9 ± 2.4 cm vs 3.8 ± 2.4 cm, p = 0.031) and higher incidence of lympho-vascular invasion (6 [7.5%] vs 18 [34.0%], p < 00.001) compared to the STAS (-) group. The 5-year RFS was 66.1% in the STAS (+) group and 91.8% in the STAS (-) group (p < 00.001), and the incidence of locoregional recurrence was significantly higher in the STAS (+) group than the STAS (-) group (1 [1.2%] vs 12 [22.6%], p < 00.001). Multivariable analysis revealed that STAS was associated with poor prognosis for all-recurrence (hazard ratio 2.81, 95% confidence interval 1.01-7.81, p = 0.048). After IPTW adjustment, 5-year RFS was 66.3% in the STAS (+) group and 92.9% in the STAS (-) group (p = 0.007), and risk for locoregional recurrence was greater in the STAS (+) group than the STAS (-) group (1.1 [0.9%] vs 20.8 [16.6%], p < 00.001). CONCLUSIONS: STAS showed negative prognostic impact on all-recurrence, especially due to locoregional recurrence, after curative resection of IMA.

Inflamed immune phenotype predicts favorable clinical outcomes of immune checkpoint inhibitor therapy across multiple cancer types.

BACKGROUND: The inflamed immune phenotype (IIP), defined by enrichment of tumor-infiltrating lymphocytes (TILs) within intratumoral areas, is a promising tumor-agnostic biomarker of response to immune checkpoint inhibitor (ICI) therapy. However, it is challenging to define the IIP in an objective and reproducible manner during manual histopathologic examination. Here, we investigate artificial intelligence (AI)-based immune phenotypes capable of predicting ICI clinical outcomes in multiple solid tumor types. METHODS: Lunit SCOPE IO is a deep learning model which determines the immune phenotype of the tumor microenvironment based on TIL analysis. We evaluated the correlation between the IIP and ICI treatment outcomes in terms of objective response rates (ORR), progression-free survival (PFS), and overall survival (OS) in a cohort of 1,806 ICI-treated patients representing over 27 solid tumor types retrospectively collected from multiple institutions. RESULTS: We observed an overall IIP prevalence of 35.2% and significantly more favorable ORRs (26.3% vs 15.8%), PFS (median 5.3 vs 3.1 months, HR 0.68, 95% CI 0.61 to 0.76), and OS (median 25.3 vs 13.6 months, HR 0.66, 95% CI 0.57 to 0.75) after ICI therapy in IIP compared with non-IIP patients, respectively (p<0.001 for all comparisons). On subgroup analysis, the IIP was generally prognostic of favorable PFS across major patient subgroups, with the exception of the microsatellite unstable/mismatch repair deficient subgroup. CONCLUSION: The AI-based IIP may represent a practical, affordable, clinically actionable, and tumor-agnostic biomarker prognostic of ICI therapy response across diverse tumor types.

Diagnostic performance and prognostic value of CT-defined visceral pleural invasion in early-stage lung adenocarcinomas.

OBJECTIVES: To analyze the diagnostic performance and prognostic value of CT-defined visceral pleural invasion (CT-VPI) in early-stage lung adenocarcinomas. METHODS: Among patients with clinical stage I lung adenocarcinomas, half of patients were randomly selected for a diagnostic study, in which five thoracic radiologists determined the presence of CT-VPI. Probabilities for CT-VPI were obtained using deep learning (DL). Areas under the receiver operating characteristic curve (AUCs) and binary diagnostic measures were calculated and compared. Inter-rater agreement was assessed. For all patients, the prognostic value of CT-VPI by two radiologists and DL (using high-sensitivity and high-specificity cutoffs) was investigated using Cox regression. RESULTS: In 681 patients (median age, 65 years [interquartile range, 58-71]; 382 women), pathologic VPI was positive in 130 patients. For the diagnostic study (n = 339), the pooled AUC of five radiologists was similar to that of DL (0.78 vs. 0.79; p = 0.76). The binary diagnostic performance of radiologists was variable (sensitivity, 45.3-71.9%; specificity, 71.6-88.7%). Inter-rater agreement was moderate (weighted Fleiss κ, 0.51; 95%CI: 0.43-0.55). For overall survival (n = 680), CT-VPI by radiologists (adjusted hazard ratio [HR], 1.27 and 0.99; 95%CI: 0.84-1.92 and 0.63-1.56; p = 0.26 and 0.97) or DL (HR, 1.44 and 1.06; 95%CI: 0.86-2.42 and 0.67-1.68; p = 0.17 and 0.80) was not prognostic. CT-VPI by an attending radiologist was prognostic only in radiologically solid tumors (HR, 1.82; 95%CI: 1.07-3.07; p = 0.03). CONCLUSION: The diagnostic performance and prognostic value of CT-VPI are limited in clinical stage I lung adenocarcinomas. This feature may be applied for radiologically solid tumors, but substantial reader variability should be overcome. CLINICAL RELEVANCE STATEMENT: Although the diagnostic performance and prognostic value of CT-VPI are limited in clinical stage I lung adenocarcinomas, this parameter may be applied for radiologically solid tumors with appropriate caution regarding inter-reader variability. KEY POINTS: • Use of CT-defined visceral pleural invasion in clinical staging should be cautious, because prognostic value of CT-defined visceral pleural invasion remains unexplored. • Diagnostic performance and prognostic value of CT-defined visceral pleural invasion varied among radiologists and deep learning. • Role of CT-defined visceral pleural invasion in clinical staging may be limited to radiologically solid tumors.

Genomic Staging of Multifocal Lung Squamous Cell Carcinomas Is Independent of the Comprehensive Morphologic Assessment.

INTRODUCTION: Morphologic and molecular data for staging of multifocal lung squamous cell carcinomas (LSCCs) are limited. In this study, whole exome sequencing (WES) was used as the gold standard to determine whether multifocal LSCC represented separate primary lung cancers (SPLCs) or intrapulmonary metastases (IPMs). Genomic profiles were compared with the comprehensive morphologic assessment. METHODS: WES was performed on 20 tumor pairs of multifocal LSCC and matched normal lymph nodes using the Illumina NovaSeq6000 S4-Xp (Illumina, San Diego, CA). WES clonal and subclonal analysis data were compared with histologic assessment by 16 thoracic pathologists. In addition, the immune gene profiling of the study cases was characterized by the HTG EdgeSeq Precision Immuno-Oncology Panel. RESULTS: By WES data, 11 cases were classified as SPLC and seven cases as IPM. Two cases were technically suboptimal. Analysis revealed marked genomic and immunogenic heterogeneity, but immune gene expression profiles highly correlated with mutation profiles. Tumors classified as IPM have a large number of shared mutations (ranging from 33.5% to 80.7%). The agreement between individual morphologic assessments for each case and WES was 58.3%. One case was unanimously interpreted morphologically as IPM and was in agreement with WES. In a further 17 cases, the number of pathologists whose morphologic interpretation was in agreement with WES ranged from two (one case) to 15 pathologists (one case) per case. Pathologists showed a fair interobserver agreement in the morphologic staging of multiple LSCCs, with an overall kappa of 0.232. CONCLUSIONS: Staging of multifocal LSCC based on morphologic assessment is unreliable. Comprehensive genomic analyses should be adopted for the staging of multifocal LSCC.

Genomic Landscape of Pulmonary Sarcomatoid Carcinoma.

PURPOSE: Pulmonary sarcomatoid carcinoma (PSC) is a rare aggressive subtype of non-small cell lung cancer (NSCLC) with limited therapeutic strategies. We attempted to elucidate the evolutionary trajectories of PSC using multiregional and longitudinal tumor samples. MATERIALS AND METHODS: A total of 31 patients were enrolled in this study and 11 longitudinal samples were available from them. Using whole exome sequencing data, we analyzed the mutational signatures in both carcinomatous and sarcomatous areas in primary tumors of the 31 patients and longitudinal samples obtained from 11 patients. Furthermore, digital droplet polymerase chain reaction (ddPCR), and programmed death-ligand 1 (PD-L1) immunohistochemistry using the Ventana SP263 assay were performed. RESULTS: TP53 was identified as the most frequently altered gene in the primary (74%) and metastatic (73%) samples. MET exon 14 skipping mutations, confirmed by ddPCR, and TP53 mutations were mutually exclusive; whereas, MET exon 14 skipping mutations frequently co-occurred with MDM2 amplification. Metastatic tumors showed dissimilar genetic profiles from either primary component. During metastasis, the signatures of APOBEC decreased in metastatic lesions compared with that in primary lesions. PSC showed higher MET and KEAP1 mutations and stronger PD-L1 protein expression compared with that recorded in other NSCLCs. CONCLUSION: Decreased APOBEC signatures and subclonal diversity were detected during malignant progression in PSC. Frequent MET mutations and strong PD-L1 expression distinguished PSC from other NSCLCs. The aggressiveness and therapeutic difficulties of PSC were possibly attributable to profound intratumoral and intertumoral genetic diversity. Next-generation sequencing could suggest the appropriate treatment strategy for PSC.

International Association for the Study of Lung Cancer Study of Reproducibility in Assessment of Pathologic Response in Resected Lung Cancers After Neoadjuvant Therapy.

INTRODUCTION: Pathologic response has been proposed as an early clinical trial end point of survival after neoadjuvant treatment in clinical trials of NSCLC. The International Association for the Study of Lung Cancer (IASLC) published recommendations for pathologic evaluation of resected lung cancers after neoadjuvant therapy. The aim of this study was to assess pathologic response interobserver reproducibility using IASLC criteria. METHODS: An international panel of 11 pulmonary pathologists reviewed hematoxylin and eosin-stained slides from the lung tumors of resected NSCLC from 84 patients who received neoadjuvant immune checkpoint inhibitors in six clinical trials. Pathologic response was assessed for percent viable tumor, necrosis, and stroma. For each slide, tumor bed area was measured microscopically, and pre-embedded formulas calculated unweighted and weighted major pathologic response (MPR) averages to reflect variable tumor bed proportion. RESULTS: Unanimous agreement among pathologists for MPR was observed in 68 patients (81%), and inter-rater agreement (IRA) was 0.84 (95% confidence interval [CI]: 0.76-0.92) and 0.86 (95% CI: 0.79-0.93) for unweighted and weighted averages, respectively. Overall, unweighted and weighted methods did not reveal significant differences in the classification of MPR. The highest concordance by both methods was observed for cases with more than 95% viable tumor (IRA = 0.98, 95% CI: 0.96-1) and 0% viable tumor (IRA = 0.94, 95% CI: 0.89-0.98). The most common reasons for discrepancies included interpretations of tumor bed, presence of prominent stromal inflammation, distinction between reactive and neoplastic pneumocytes, and assessment of invasive mucinous adenocarcinoma. CONCLUSIONS: Our study revealed excellent reliability in cases with no residual viable tumor and good reliability for MPR with the IASLC recommended less than or equal to 10% cutoff for viable tumor after neoadjuvant therapy.

A single-cell atlas of in vitro multiculture systems uncovers the in vivo lineage trajectory and cell state in the human lung.

We present an in-depth single-cell atlas of in vitro multiculture systems on human primary airway epithelium derived from normal and diseased lungs of 27 individual donors. Our large-scale single-cell profiling identified new cell states and differentiation trajectories of rare airway epithelial cell types in human distal lungs. By integrating single-cell datasets of human lung tissues, we discovered immune-primed subsets enriched in lungs and organoids derived from patients with chronic respiratory disease. To demonstrate the full potential of our platform, we further illustrate transcriptomic responses to various respiratory virus infections in vitro airway models. Our work constitutes a single-cell roadmap for the cellular and molecular characteristics of human primary lung cells in vitro and their relevance to human tissues in vivo.

Differential Prognostic Value of Vascular Invasion in Resected Lung Adenocarcinomas According to Epidermal Growth Factor Receptor Mutational Status.

BACKGROUND: It is unclear whether all patients with stage IB to IIIA epidermal growth factor receptor (EGFR)-mutant adenocarcinoma should receive adjuvant osimertinib. We investigated the prognostic value of vascular invasion for risk stratification according to EGFR mutational status. MATERIALS AND METHODS: This retrospective study evaluated patients with stage IB to IIIA lung adenocarcinoma resected between 2011 and 2016 at a tertiary care center. The study outcome was overall survival (OS). The prognostic value of vascular invasion was analyzed using the adjusted log-rank test and multivariable Cox regression with clinico-pathological factors as covariates. A sensitivity analysis, which included the presence of ground-glass opacity on CT scans as an additional covariate, and subgroup analyses according to the pathological stage were performed. RESULTS: In total, 272 patients were included (146 women; median age, 66 years [interquartile range: 58, 72 years]; 128 EGFR-mutant adenocarcinomas). The 5-year OS rate was 90.8% (95% CI: 84.0%, 98.1%) in EGFR-mutant, vascular invasion-absent lung adenocarcinomas, which was higher than in other subgroups (P < .05). Vascular invasion was an independent, negative prognostic factor in EGFR-mutant lung adenocarcinomas (adjusted log-rank test, P = .02; adjusted hazard ratio, 3.01; 95% CI: 1.30, 7.02; P = .01). However, the prognosis of EGFR wild-type adenocarcinomas was not associated with the presence of vascular invasion (adjusted log-rank test, P = .95; adjusted hazard ratio, 1.32; 95% CI: 0.74, 2.34; P = .35). Similar results were observed in the sensitivity analysis and subgroup analyses. CONCLUSIONS: Vascular invasion-absent, EGFR-mutant, resected lung adenocarcinomas showed a very good prognosis, and vascular invasion had a differential prognostic value according to EGFR mutational status.

Clinical validity of oncogenic driver genes detected from circulating tumor DNA in the blood of lung cancer patients.

Background: This study aimed to evaluate the concordance of oncogenic driver mutations between tumor tissues and circulating tumor DNA (ctDNA) in patients with lung cancer. In addition, this study attempted to reveal the clinical utility of ctDNA in lung cancer treatment. Methods: Recurrent or metastatic non-small cell lung cancer (NSCLC) patients were prospectively enrolled in this study. Tumor tissue and serial blood samples were obtained from newly diagnosed patients (Cohort A) or patients treated with targeted therapy (Cohort B) and targeted gene panel sequencing was conducted to identify tumor mutational profiles. Results: At the time of diagnosis, patients in Cohort A with a high cell-free DNA (cfDNA) concentration had poorer overall survival than those with a low cfDNA concentration. The sensitivity and precision of ctDNA analysis in pre-treatment patients compared with those of tissue sequencing were 58.4% and 61.5%, respectively. Known lung cancer-associated variants of oncogenic driver genes, including EGFR and KRAS, and tumor suppressor genes, including TP53 and APC, were frequently detected in the ctDNA of the patients (76.9%). An association between smoking and TP53 mutation status was observed in both tissues and ctDNA (P=0.005 and 0.037, respectively). In addition, the EGFR T790M resistance mutation was detected solely from the ctDNA of two patients after treatment with an EGFR tyrosine kinase inhibitor. Conclusions: ctDNA may be a reliable prognostic biomarker with an additional role in treating patients with lung cancer. Further analyses are necessary to understand the properties of ctDNA and widen its clinical use.

Radiologic Extranodal Extension of Metastatic Lymph Nodes in Patients With Non-Small Cell Lung Cancer: Prognostic Utility and Diagnostic Performance.

BACKGROUND. Pathologic extranodal extension (ENE) in metastatic lymph nodes (LNs) has been associated with unfavorable prognosis in patients with non-small cell lung cancer (NSCLC). OBJECTIVE. The purpose of this article was to evaluate the prognostic utility of radiologic ENE and its diagnostic performance in predicting pathologic ENE in patients with NSCLC. METHODS. This retrospective study included 382 patients (mean age, 67 ± 10 [SD] years; 297 men, 85 women) diagnosed with NSCLC and clinical N1 or N2 disease between January 2010 and December 2016. Two thoracic radiologists reviewed staging chest CT examinations to record subjective overall impression for radiologic ENE (no ENE, possible/probable ENE, or unambiguous ENE), reviewing 30 examinations in consensus and the remaining examinations independently. Kaplan-Meier survival analysis and multivariable Cox proportional hazards model were used to evaluate the utility of radiologic ENE in predicting overall survival (OS). Prognostic utility of radiologic ENE was also assessed in patients with clinical N2a disease. In patients who underwent surgery, sensitivity and specificity were determined of radiologic unambiguous ENE in predicting pathologic ENE. RESULTS. The 5-year OS rates for no ENE, possible/probable ENE, and unambiguous ENE were 44.4%, 39.1%, and 20.9% for reader 1 and 45.7%, 36.6%, and 25.6% for reader 2, respectively. Unambiguous ENE was an independent prognostic factor for worse OS (reader 1: adjusted HR, 1.72, p = .008; reader 2: adjusted HR, 1.56, p = .03), whereas possible/probable ENE was not (reader 1: adjusted HR, 1.18, p = .33; reader 2: adjusted HR, 1.21, p = .25). In patients with clinical N2a disease, 5-year OS rate in patients with versus without unambiguous ENE for reader 1 was 22.2% versus 40.6% (p = .59) and for reader 2 was 27.6% versus 41.0% (p = .49). In 203 patients who underwent surgery (66 with pathologic ENE), sensitivity and specificity of radiologic unambiguous ENE for predicting pathologic ENE were 11% and 93% for reader 1 and 23% and 87% for reader 2. CONCLUSION. Radiologic unambiguous ENE was an independent predictor of worse OS in patients with NSCLC. The finding had low sensitivity but high specificity for pathologic ENE. CLINICAL IMPACT. Radiologic ENE may have a role in NSCLC staging workup and treatment selection.

Correlation of monocyte counts with clinical outcomes in idiopathic nonspecific interstitial pneumonia.

Higher blood monocyte counts are related to worse survival in idiopathic pulmonary fibrosis. However, studies evaluating the association between blood monocyte counts and clinical outcomes of idiopathic nonspecific interstitial pneumonia (iNSIP) are lacking. We evaluated the impact of monocyte counts on iNSIP prognosis. iNSIP patients (n = 126; median age, 60 years; female, n = 64 [50.8%]) diagnosed by surgical lung biopsy were enrolled and categorized into low (monocyte < 600/µL) and high (monocyte ≥ 600/µL) monocyte groups. The median follow-up duration was 53.0 months. After adjusting for age, sex, and smoking history, the annual decline in forced vital capacity (FVC) showed differences between the monocyte groups (Pinteraction = 0.006) (low vs. high; - 28.49 mL/year vs. - 65.76 mL/year). The high-monocyte group showed a worse survival rate (P = 0.01) compared to low monocyte group. The 5-year survival rates were 83% and 72% in the low- and high-monocyte groups, respectively. In the Cox-proportional hazard analysis, older age, male sex, low baseline FVC, and diffusing capacity of the lung for carbon monoxide were independent risk factors for mortality. However, monocyte count (Hazard ratio 1.61, P = 0.126) was not an independent prognostic factor. Although high monocyte count might be associated with faster lung function decline, it could not independently predict survival in iNSIP.

Defining Morphologic Features of Invasion in Pulmonary Nonmucinous Adenocarcinoma With Lepidic Growth: A Proposal by the International Association for the Study of Lung Cancer Pathology Committee.

INTRODUCTION: Since the eight edition of the Union for International Cancer Control and American Joint Committee on Cancer TNM classification system, the primary tumor pT stage is determined on the basis of presence and size of the invasive components. The aim of this study was to identify histologic features in tumors with lepidic growth pattern which may be used to establish criteria for distinguishing invasive from noninvasive areas. METHODS: A Delphi approach was used with two rounds of blinded anonymized analysis of resected nonmucinous lung adenocarcinoma cases with presumed invasive and noninvasive components, followed by one round of reviewer de-anonymized and unblinded review of cases with known outcomes. A digital pathology platform was used for measuring total tumor size and invasive tumor size. RESULTS: The mean coefficient of variation for measuring total tumor size and tumor invasive size was 6.9% (range: 1.7%-22.3%) and 54% (range: 14.7%-155%), respectively, with substantial variations in interpretation of the size and location of invasion among pathologists. Following the presentation of the results and further discussion among members at large of the International Association for the Study of Lung Cancer Pathology Committee, extensive epithelial proliferation (EEP) in areas of collapsed lepidic growth pattern is recognized as a feature likely to be associated with invasive growth. The EEP is characterized by multilayered luminal epithelial cell growth, usually with high-grade cytologic features in several alveolar spaces. CONCLUSIONS: Collapsed alveoli and transition zones with EEP were identified by the Delphi process as morphologic features that were a source of interobserver variability. Definition criteria for collapse and EEP are proposed to improve reproducibility of invasion measurement.

Gallbladder adenocarcinomas undergo subclonal diversification and selection from precancerous lesions to metastatic tumors.

We aimed to elucidate the evolutionary trajectories of gallbladder adenocarcinoma (GBAC) using multi-regional and longitudinal tumor samples. Using whole-exome sequencing data, we constructed phylogenetic trees in each patient and analyzed mutational signatures. A total of 11 patients including 2 rapid autopsy cases were enrolled. The most frequently altered gene in primary tumors was ERBB2 and TP53 (54.5%), followed by FBXW7 (27.3%). Most mutations in frequently altered genes in primary tumors were detectable in concurrent precancerous lesions (biliary intraepithelial neoplasia [BilIN]), but a substantial proportion was subclonal. Subclonal diversity was common in BilIN (n=4). However, among subclones in BilIN, a certain subclone commonly shrank in concurrent primary tumors. In addition, selected subclones underwent linear and branching evolution, maintaining subclonal diversity. Combined analysis with metastatic tumors (n=11) identified branching evolution in nine patients (81.8%). Of these, eight patients (88.9%) had a total of 11 subclones expanded at least sevenfold during metastasis. These subclones harbored putative metastasis-driving mutations in cancer-related genes such as SMAD4, ROBO1, and DICER1. In mutational signature analysis, six mutational signatures were identified: 1, 3, 7, 13, 22, and 24 (cosine similarity >0.9). Signatures 1 (age) and 13 (APOBEC) decreased during metastasis while signatures 22 (aristolochic acid) and 24 (aflatoxin) were relatively highlighted. Subclonal diversity arose early in precancerous lesions and clonal selection was a common event during malignant transformation in GBAC. However, selected cancer clones continued to evolve and thus maintained subclonal diversity in metastatic tumors.

Pulmonary blastoma that was first diagnosed as dedifferentiated chondrosarcoma using medical thoracoscopy: A case report.

RATIONALE: Pulmonary blastoma is an extremely rare and highly aggressive tumor. Only a few hundred cases of pulmonary blastoma have been reported. In other cases, a definitive diagnosis is often made through surgical resection. The use of preoperative histopathological sampling in diagnosing was of limited value because of the variety of pulmonary blastoma histology. And there was no literature that the first biopsy was attempted with medical thoracoscopy for diagnosis. PATIENT CONCERNS: A 65-year-old man presented to our hospital with pleural effusion and lung mass. DIAGNOSES: The patient was initially diagnosed with dedifferentiated chondrosarcoma by medical thoracoscopic biopsy but the final diagnosis was pulmonary blastoma through bilobectomy. INTERVENTIONS: Medical thoracoscopy, and video-assisted thoracoscopic surgery (bilobectomy) followed by adjuvant chemotherapy. OUTCOMES: After surgical resection of the tumor, adjuvant chemotherapy has been performed 5 cycles at 3 weeks intervals, and there was no evidence of recurrence on follow-up computed tomography performed 4 months after surgery. LESSONS: Medical thoracoscopy is useful for the diagnosis of indeterminate pleural effusion; however, caution is needed when confirming rare malignancies, such as pulmonary blastoma. Although surgical resection is the treatment of choice, appropriate adjuvant chemotherapy to improve the prognosis may be necessary if there is pleural metastasis.

Biomarker testing of cytology specimens in personalized medicine for lung cancer patients.

Every patient with advanced non-small cell lung cancer (NSCLC) should be tested for targetable driver mutations and gene arrangements that may open avenues for targeted therapy. As most patients with NSCLC in the advanced stage of the disease are not candidates for surgery, these tests have to be performed on small biopsies or cytology samples. A growing number of other genetic changes with targetable mutations may be treatable in the near future. To identify patients who might benefit from novel targeted therapy, relevant markers should be tested in an appropriate context. In addition, immunotherapy of lung cancer is guided by the status of programmed death-ligand 1 expression in tumor cells. The variety and versatility of cytological specimen preparations offer significant advantages for molecular testing; however, they frequently remain underused. Therefore, evaluating the utility and adequacy of cytologic specimens is important, not only from a lung cancer diagnosis, but also for the large number of ancillary studies that are necessary to provide appropriate clinical management. A large proportion of lung cancers is diagnosed by aspiration or exfoliative cytology specimens; thus, optimizing strategies to triage and best use the tissue for diagnosis and biomarker studies forms a critical component of lung cancer management. In this review, we discuss the opportunities and challenges of using cytologic specimens for biomarker testing of lung cancer and the role of cytopathology in the molecular era.