Non-Mucinous Lung Adenocarcinoma Research Articles

LVI-PathNet: Segmentation-classification pipeline for detection of lymphovascular invasion in whole slide images of lung adenocarcinoma

Lymphovascular invasion (LVI) in lung cancer is a significant prognostic factor that influences treatment and outcomes, yet its reliable detection is challenging due to interobserver variability. This study aims to develop a deep learning model for LVI detection using whole slide images (WSIs) and evaluate its effectiveness within a pathologist's information system. Experienced pathologists annotated blood vessels and invading tumor cells in 162 WSIs of non-mucinous lung adenocarcinoma sourced from two external and one internal datasets. Two models were trained to segment vessels and identify images with LVI features. DeepLabV3+ model achieved an Intersection-over-Union of 0.8840 and an area under the receiver operating characteristic curve (AUC-ROC) of 0.9869 in vessel segmentation. For LVI classification, the ensemble model achieved a F1-score of 0.9683 and an AUC-ROC of 0.9987. The model demonstrated robustness and was unaffected by variations in staining and image quality. The pilot study showed that pathologists' evaluation time for LVI detecting decreased by an average of 16.95%, and by 21.5% in "hard cases". The model facilitated consistent diagnostic assessments, suggesting potential for broader applications in detecting pathological changes in blood vessels and other lung pathologies.

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

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

Reproducibility of Assessment of Lepidic (Noninvasive) Patterns in Lung Adenocarcinoma With Cytokeratin Immunostain Compared With Hematoxylin and Eosin and the Proposed New International Association for the Study of Lung Cancer (IASLC) Algorithm

Lepidic growth is considered noninvasive in lung nonmucinous adenocarcinoma, whereas other patterns are invasive. Considerable interobserver variability in assessing "invasion" has been reported. We assessed the utility of cytokeratin 7 (CK7) stain and recently proposed International Association for the Study of Lung Cancer criteria to improve assessment of noninvasion in lung adenocarcinoma. Four pathologists (two staff, two trainees) assessed 158 hematoxylin and eosin (HE)- and CK7-stained slides of 108 pT1N0-2 nonmucinous lung adenocarcinoma cases. Scoring took place in four rounds. First, sections were independently scored for percentage of noninvasive or probable noninvasive and invasive or probable invasive patterns. Second, after a consensus scoring algorithm for CK7 was formulated, the slides were rescored. Subsequent third-round scoring was conducted only on HE slides using the 2023 International Association for the Study of Lung Cancer proposed criteria, and fourth-round scoring on both HE and CK7 slides simultaneously. Intraclass correlation coefficient (ICC) was calculated for each round. Recurrence-free survival was assessed using Cox proportional hazards regression methods. In the first two rounds, interobserver concordance was consistently higher with CK7 (ICC range= 0.44-0.6) than HE (range= 0.24-0.49) scores. The IASLC proposed algorithm improved ICC of HE scores to 0.60 (95% confidence interval: 0.52-0.67), and round 4 HE and CK7 combined improved ICC to 0.75 (95% confidence interval: 0.70-0.80). Continuous measures of averaged noninvasive and probable noninvasive scores on HE were associated with improved recurrence-free survival (hazard ratio: 0.83-0.86). CK7 staining consistently increased interobserver concordance in assessment of invasive versus noninvasive patterns than HE. Combining CK7 with the 2023 IASLC criteria for morphologic features of invasion may further improve the interobservers' concordance for the recognition of lepidic growth in nonmucinous lung adenocarcinoma.

Prognostic impact of the IASLC grading system of lung adenocarcinoma: a systematic review and meta-analysis.

Tumour grading is an essential part of the pathologic assessment that promotes patient management. The International Association for the Study of Lung Cancer (IASLC) proposed a grading system for non-mucinous lung adenocarcinoma in 2020. We aimed to validate the prognostic impact of this novel grading system on overall survival (OS) and recurrence-free survival (RFS) based on literature data. The review protocol was registered in PROSPERO (CRD42023396059). We aimed to identify randomized or non-randomized controlled trials published after 2020 comparing different IASLC grade categories in Medline, Embase, and CENTRAL. Hazard ratios (HRs) with 95% confidence intervals (CIs) of OS and RFS were pooled and the Quality In Prognosis Studies (QUIPS) tool was used to assess the risk of bias in the included studies. Ten articles were eligible for this review. Regarding OS estimates, grade 1 lung adenocarcinomas were better than grade 3 both in univariate and multivariate analyses (HROSuni = 0.19, 95% CI: 0.05-0.66, p = 0.009; HROSmulti = 0.21, 95% CI: 0.12-0.38, p < 0.001). Regarding RFS estimates, grade 3 adenocarcinomas had a worse prognosis than grade 1 in multivariate analysis (HRRFSmulti: 0.22, 95% CI: 0.14-0.35, p < 0.001). The literature data and the result of our meta-analysis demonstrate the prognostic relevance of the IASLC grading system. This supports the inclusion of this prognostic parameter in daily routine worldwide.

Proposed novel grading system for stage I invasive lung adenocarcinoma and a comparison with the 2020 IASLC grading system.

Several studies have proposed grading systems for risk stratification of early-stage lung adenocarcinoma based on histological patterns. However, the reproducibility of these systems is poor in clinical practice, indicating the need to develop a new grading system which is easy to apply and has high accuracy in prognostic stratification of patients. Patients with stage I invasive nonmucinous lung adenocarcinoma were retrospectively collected from pathology archives between 2009 and 2016. The patients were divided into a training and validation set at a 6:4 ratio. Histological features associated with patient outcomes (overall survival [OS] and progression-free survival [PFS]) identified in the training set were used to construct a new grading system. The newly proposed system was validated using the validation set. Survival differences between subgroups were assessed using the log-rank test. The prognostic performance of the novel grading system was compared with two previously proposed systems using the concordance index. A total of 539 patients were included in this study. Using a multioutcome decision tree model, four pathological factors, including the presence of tumor spread through air space (STAS) and the percentage of lepidic, micropapillary and solid subtype components, were selected for the proposed grading system. Patients were accordingly classified into three groups: low, medium, and high risk. The high-risk group showed a 5-year OS of 52.4% compared to 89.9% and 97.5% in the medium and low-risk groups, respectively. The 5-year PFS of patients in the high-risk group was 38.1% compared to 61.7% and 90.9% in the medium and low-risk groups, respectively. Similar results were observed in the subgroup analysis. Additionally, our proposed grading system provided superior prognostic stratification compared to the other two systems with a higher concordance index. The newly proposed grading system based on four pathological factors (presence of STAS, and percentage of lepidic, micropapillary, and solid subtypes) exhibits high accuracy and good reproducibility in the prognostic stratification of stage I lung adenocarcinoma patients.

Combined CT-Based Radiomics and Clinic-Radiological Characteristics for Preoperative Differentiation of Solitary-Type Invasive Mucinous and Non-Mucinous Lung Adenocarcinoma.

The clinical, pathological, gene expression, and prognosis of invasive mucinous adenocarcinoma (IMA) differ from those of invasive non-mucinous adenocarcinoma (INMA), but it is not easy to distinguish these two. This study aims to explore the value of combining CT-based radiomics features with clinic-radiological characteristics for preoperative diagnosis of solitary-type IMA and to establish an optimal diagnostic model. In this retrospective study, a total of 220 patients were enrolled and randomly assigned to a training cohort (n = 154; 73 IMA and 81 INMA) and a testing cohort (n = 66; 31 IMA and 35 INMA). Radiomics features and clinic-radiological characteristics were extracted from plain CT images. The radiomics models for predicting solitary-type IMA were developed by three classifiers: linear discriminant analysis (LDA), logistic regression-least absolute shrinkage and selection operator (LR-LASSO), and support vector machine (SVM). The combined model was constructed by integrating radiomics and clinic-radiological features with the best performing classifier. Receiver operating characteristic (ROC) curves were used to evaluate models' performance, and the area under the curve (AUC) were compared by the DeLong test. Decision curve analysis (DCA) was conducted to assess the clinical utility. Regarding CT characteristics, tumor lung interface, and pleural retraction were the independent risk factors of solitary-type IMA. The radiomics model using the SVM classifier outperformed the other two classifiers in the testing cohort, with an AUC of 0.776 (95% CI: 0.664-0.888). The combined model incorporating radiomics features and clinic-radiological factors was the optimal model, with AUCs of 0.843 (95% CI: 0.781-0.906) and 0.836 (95% CI: 0.732-0.940) in the training and testing cohorts, respectively. The combined model showed good ability in predicting solitary-type IMA and can provide a non-invasive and efficient approach to clinical decision-making.

Stable Therapeutic Transgenic FIX Levels for More Than 10 Years in Subjects with Severe Hemophilia B Who Received scAAV2/8-LP1-Hfixco Adeno-Associated Virus Gene Therapy

Background: Previously, we reported data from a first-in-human, dose-escalation, Phase 1 gene therapy trial demonstrating a dose-dependent increase in transgenic factor IX (FIX) expression in 10 adults with severe hemophilia B (FIX activity ≤1%). This was achieved following a single intravenous infusion of a self-complementary adeno-associated virus (scAAV) vector containing the wild-type FIX gene (codon-optimized), under the control of a synthetic liver-specific promoter and pseudotyped AAV8 capsid (scAAV2/8-LP1-hFIXco; ClinicalTrials.gov:NCT00979238). We now report durable efficacy and long-term safety over at least 10 years of follow-up in these participants. Methods: FIX activity, annualized bleeding rate (ABR), use of FIX concentrates, safety (specifically transaminitis and oncogenesis), and FIX expression kinetics were evaluated in the 10 participants following a bolus infusion of scAAV2/8-LP1-hFIXco at a dose of 2x10 11vg/kg (N=2), 6x10 11vg/kg (N=2), or 2x10 12vg/kg (N=6), between 2010 and 2012. Results: As of December 31, 2022, the median follow-up was 10.7 years (range 4-12 years). A total of 11 treatment-related adverse events occurred in 10 participants, including transient elevation of liver transaminases within 3 months of vector infusion in 4 of 6 patients treated with the high vector dose, without any recurrence. Two new serious adverse events were reported: (1) non-mucinous lung adenocarcinoma in situ, identified incidentally following a bullectomy for spontaneous pneumothorax 5 years after gene therapy in a 48-year-old participant considered not related to gene therapy following molecular studies, and (2) adenocarcinoma of the prostate in a 72-year-old participant 12 years after gene therapy. Tissue evaluation of the latter case is ongoing. No FIX inhibitors, thrombosis, persistent transaminitis or deaths were observed. Transgenic FIX expression has remained stable, with mean (±SD) FIX activity (one-stage) for the three dose cohorts of 1.7±0.9, 2.3±0.9 and 4.9±2.2 IU/dL, respectively (Figure 1). The mean and median ABR over the 10-year period following gene therapy of all 10 participants were 1.95 and 1.6 compared to 16.5 and 14, respectively, before gene therapy. This represents an 8.5-fold reduction in bleeding events (Wilcoxon signed rank test p=0.002). In the 6 high-dose participants, the ABR was 21-fold lower (mean=1.16, median 1, paired t-test, p&amp;lt;0.008). Mean and median FIX concentrate usage before gene therapy in the 10 participants were 2869 and 2526 IU/kg dropping to 945 and 274 IU/kg, respectively, over a 10-year period after gene therapy (p=0.0003). All participants developed a persistent, high-titer polyclonal anti-AAV8 capsid-specific antibody response after administration of scAAV2/8-LP1-hFIXco. Conclusion: Expression of transgenic FIX has remained stable over a period of 10 years following systemic administration of scAAV2/8-LP1-hFIXco resulting in sustained clinical benefit, with substantial reduction in ABR and FIX concentrate use.

Clinical Significance of the Proposed Pathologic Criteria for Invasion by the International Association for the Study of Lung Cancer in Resected Nonmucinous Lung Adenocarcinoma

Accurate diagnostic criteria for tumor invasion are essential for precise pathologic tumor (pT) staging. Recently, the International Association for the Study of Lung Cancer (IASLC) Pathology Committee suggested a new set of criteria for assessing tumor invasion, but the clinical usefulness of the proposed criteria has not been evaluated. The study included 1295 patients with resected part-solid lung adenocarcinoma from January 2017 to December 2019 at the Samsung Medical Center, Seoul, Korea. The revised pT stage was determined by the extent of the newly measured invasive component using the IASLC criteria. The primary outcome was to compare the performance of the revised pT stage with the original pT stage in predicting recurrence-free survival and proof of invasion status (i.e., recurrence or lymph node metastasis). The secondary outcome was the correlation with radiologic surrogates of tumor invasiveness (consolidation-to-tumor ratio and maximum standardized uptake value) and pathologic risk factors. The re-evaluation resulted in a 22% downstaging and 2.5% upstaging of pT, which improved the correlation with radiologic (consolidation-to-tumor ratio and maximum standardized uptake value) and pathologic risk factors. The revised pT staging allowed for more accurate discrimination of recurrence-free survival than the original pT staging (c-index= 0.794 versus 0.717). Moreover, the revised pT staging significantly improved the prediction of recurrence or lymph node metastasis (area under the curve= 0.818 versus 0.741, p < 0.001). To our knowledge, this is the first study evaluating the clinical significance of the IASLC-proposed criteria for invasion. The proposed IASLC criteria offered better alignment with clinicopathologic risk factors and improved prognostication. Further studies are warranted to assess the impact of the IASLC criteria on treatment decisions and patient outcomes.

OA20.04 Clinical Significance of IASLC Proposed Pathologic Criteria for Invasion in Resected Non-mucinous Lung Adenocarcinoma

OA20.04 Clinical Significance of IASLC Proposed Pathologic Criteria for Invasion in Resected Non-mucinous Lung Adenocarcinoma

A pretreatment prediction model of grade 3 tumors classed by the IASLC grading system in lung adenocarcinoma

PurposeThe new grading system for invasive nonmucinous lung adenocarcinoma (LUAD) in the 2021 World Health Organization Classification of Thoracic Tumors was based on a combination of histologically predominant subtypes and high-grade components. In this study, a model for the pretreatment prediction of grade 3 tumors was established according to new grading standards.MethodsWe retrospectively collected 399 cases of clinical stage I (cStage-I) LUAD surgically treated in Tianjin Chest Hospital from 2015 to 2018 as the training cohort. Besides, the validation cohort consists of 216 patients who were collected from 2019 to 2020. These patients were also diagnosed with clinical cStage-I LUAD and underwent surgical treatment at Tianjin Chest Hospital. Univariable and multivariable logistic regression analyses were used to select independent risk factors for grade 3 adenocarcinomas in the training cohort. The nomogram prediction model of grade 3 tumors was established by R software.ResultsIn the training cohort, there were 155 grade 3 tumors (38.85%), the recurrence-free survival of which in the lobectomy subgroup was better than that in the sublobectomy subgroup (P = 0.034). After univariable and multivariable analysis, four predictors including consolidation-to-tumor ratio, CEA level, lobulation, and smoking history were incorporated into the model. A nomogram was established and internally validated by bootstrapping. The Hosmer–Lemeshow test result was χ2 = 7.052 (P = 0.531). The C-index and area under the receiver operating characteristic curve were 0.708 (95% CI: 0.6563–0.7586) for the training cohort and 0.713 (95% CI: 0.6426–0.7839) for the external validation cohort.ConclusionsThe nomogram prediction model of grade 3 LUAD was well fitted and can be used to assist in surgical or adjuvant treatment decision-making.

Analysis of Clinicopathological Features on Spread Through Air Spaces of Lung Adenocarcinoma

The biological and molecular characteristics of spread through air spaces (STAS), a newly recognized invasive mode of lung cancer, remain controversial. The aim of this study was to investigate the clinicopathological features and molecular characteristics of STAS in patients with pulmonary adenocarcinoma. A total of 694 resected invasive non-mucinous lung adenocarcinomas diagnosed by clinicopathology from July 2019 to March 2021 in the First Affiliated Hospital of Guangzhou Medical University were collected, and the relationship between STAS and clinicopathological factors was analyzed. The state of protein expression of anaplastic lymphoma kinase (ALK) was detected by immunohistochemical method. Epidermal growth factor receptor (EGFR) was detected by amplification refractory mutation system-polymerase chain reaction (ARMS-PCR). ROS proto-oncogene 1-receptor (ROS1) was detected by reverse transcription-PCR (RT-PCR). A total of 344 STAS positive cases and 350 STAS negative cases were collected. By univariate analysis, STAS positivity was statistically associated with tumor maximum diameter (P<0.001), pleural invasion (P<0.001), lymphovascular invasion (P<0.001), nerve invasion (P=0.013), lymph node metastasis (P<0.001), clinical stage (P<0.001) and histological type (P<0.001). There was a statistical correlation between STAS and ALK protein expression (P=0.001). Multivariate analysis showed that STAS positive was correlated with pleural invasion (P=0.001), vascular invasion (P<0.001), lymph node metastasis (P=0.005)and ALK protein expression (P=0.032). STAS is associated with highly aggressive biological behavior of lung adenocarcinoma, suggesting a poor prognosis.

Müsinöz Olmayan Akciğer Adenokarsinomlarında Caspase-3 ve GRIM-19 Ekspresyonu ile Bu Proteinlerin Klinikopatolojik Önemi

Aim: The current study aimed to investigate apoptotic proteins such as caspase-3 and GRIM-19 protein expression in non-mucinous lung adenocarcinomas and their clinicopathologic significance. Material and Methods: This study was performed on 81 patients diagnosed with non-mucinous lung adenocarcinoma between January 1, 2010, and June 1, 2020. Immunohistochemical analysis was performed to examine the expressions of caspase-3 and GRIM-19, and the association between these proteins and clinicopathological parameters was investigated. Results: Caspase-3 nuclear positivity was more common in high-grade non-mucinous lung adenocarcinomas (p&amp;lt;0.001). Caspase-3 cytoplasmic expression was stronger in tumors with advanced-stage (p=0.021) and lymph node metastases (p=0.020). GRIM-19 expression was low in tumors with high-grade non-mucinous lung adenocarcinomas (p=0.002), and tumors with lymphovascular invasion (p=0.021). The median follow-up time was 31.7 (range, 1-145 months. The overall 5-year survival rate of patients with low and high GRIM-19 expression tumors was 48% and 92%, respectively. GRIM-19 expression significantly affected the 5-year overall survival rate (p=0.008), but not the 5-year disease-free survival rate (p=0.368). Conclusion: We revealed a significant association between caspase-3 and GRIM-19 expressions and poor clinicopathologic features and prognosis. For the first time in the literature, we revealed an association between low GRIM-19 expression and worse clinical outcomes in patients with non-mucinous lung adenocarcinoma. Caspase-3 and GRIM-19 may become potential therapeutic targets and novel potential predictive biomarkers for non-mucinous lung adenocarcinoma patients.

Deep learning-based diagnosis of histopathological patterns for invasive non-mucinous lung adenocarcinoma using semantic segmentation

ObjectivesThe application of artificial intelligence (AI) to the field of pathology has facilitated the development of digital pathology, hence, making AI-assisted diagnosis possible. Due to the variety of lung cancers...

Defining morphologic features of invasion in pulmonary non-mucinous adenocarcinoma with lepidic growth - A proposal by the IASLC Pathology Committee.

Since the 8th edition of UICC/AJCC TNM classification system the primary tumor pT stage is determined based on presence and size of the invasive components. The aim of this study was to identify histological features in tumors with lepidic growth pattern that may be used to establish criteria for distinguishing invasive from non-invasive areas. A Delphi approach was used with two rounds of blinded anonymized analysis of resected non-mucinous lung adenocarcinoma cases with presumed invasive and non-invasive 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. 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 IASLC 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. EEP is characterized by multilayered luminal epithelial cell growth, usually with high grade cytological features in several alveolar spaces. 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.

Heterogeneous expression of predictive biomarkers PD-L1 and TIGIT in non-mucinous lung adenocarcinoma and corresponding lymph node metastasis: A challenge for clinical biomarker testing

The use of immune checkpoint inhibitors (ICI) targeting the PD-L1:PD1 interaction revolutionized tumor treatment by re-activating the anti-tumoral capacity of the immune system. Assessment of tumor mutational burden, microsatellite instability, or expression of the surface marker PD-L1 have been used to predict individual response to ICI therapy. However, the predicted response does not always correspond to the actual therapy outcome. We hypothesize that tumor heterogeneity might be a major cause of this inconsistency. In this respect we recently demonstrated that PD-L1 shows heterogenous expression in the different growth patterns of non-small cell lung cancer (NSCLC) - lepidic, acinar, papillary, micropapillary and solid. Furthermore, additional inhibitory receptors, like T cell immunoglobulin and ITIM domain (TIGIT), appear to be heterogeneously expressed and affect the outcome of anti-PD-L1 treatment. Given this heterogeneity in the primary tumor, we set out to analyze the situation in corresponding lymph node metastases, since these are often used to obtain biopsy material for tumor diagnosis, staging and molecular analysis. Again, we observed heterogeneous expression of PD-1, PD-L1, TIGIT, Nectin-2 and PVR in relation to different regions and growth pattern distribution that varied between the primary tumor and their metastases. Together, our study underscores the complex situation regarding the heterogeneity of NSCLC samples and suggest that the analysis of a small biopsy from lymph node metastases may not be sufficient to ensure a reliable prediction of ICI therapy success.

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

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. 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. 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). 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.

EP16.03-034 Differential Prognostic Effect of EGFR Mutation According to Smoking Status and Pathologic Stage in Non-mucinous Lung Adenocarcinoma

EP16.03-034 Differential Prognostic Effect of EGFR Mutation According to Smoking Status and Pathologic Stage in Non-mucinous Lung Adenocarcinoma

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.

CT Features of Stage IA Invasive Mucinous Adenocarcinoma of the Lung and Establishment of a Prediction Model

ObjectiveTo investigate computed tomography (CT) features of stage IA invasive mucinous adenocarcinoma (IMA) of the lung and establish a predictive model.MethodsFifty-three lesions from 53 cases of stage IA IMA between January 2017 and December 2019 were examined, while 141 lesions from 141 cases of invasive non-mucinous lung adenocarcinoma (INMA) served as control cases. Univariate analysis was performed to compare differences in demographics and CT features between the two groups, and multivariate logistic regression analysis was performed to determine primary influencing factors of solitary nodular IMA. A risk score prediction model was established based on the regression coefficients of these factors, and receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performance of the model.ResultsUnivariate analysis showed that age, nodule type, maximum nodule diameter, tumor lung interface, lobulation, spiculation, air bronchogram or vacuolar signs, and abnormal vascular changes differed significantly between the two groups (p < 0.05). Compared to INMA, spiculation of IMA was relatively longer and softer. Multivariate logistic regression analysis showed that nodule type, indistinct tumor lung interface, air bronchogram or vacuolar signs, and abnormal vascular changes were the primary influencing factors. A prediction model based on the regression coefficients of these factors was established. ROC curve analysis indicated that the area under the curve was 0.882 (p < 0.05).ConclusionCompared to INMA, solitary peripheral stage IA nodular IMA were more common in older patients; they more frequently had indistinct tumor lung interface and air bronchogram or vacuolar signs on CT; spiculation was relatively longer and softer; our risk score prediction model based on nodule type, tumor lung interface, air bronchogram or vacuolar signs, and abnormal vascular changes was established with good predictive efficacy for solitary nodular IMA.

Novel Genetic Prognostic Signature for Lung Adenocarcinoma Identified by Differences in Gene Expression Profiles of Low- and High-Grade Histological Subtypes.

The 2021 WHO classification proposed a pattern-based grading system for early-stage invasive non-mucinous lung adenocarcinoma. Lung adenocarcinomas with high-grade patterns have poorer outcomes than those with lepidic-predominant patterns. This study aimed to establish genetic prognostic signatures by comparing differences in gene expression profiles between low- and high-grade adenocarcinomas. Twenty-six (9 low- and 17 high-grade adenocarcinomas) patients with histologically “near-pure” patterns (predominant pattern comprising >70% of tumor areas) were selected retrospectively. Using RNA sequencing, gene expression profiles between the low- and high-grade groups were analyzed, and genes with significantly different expression levels between these two groups were selected for genetic prognostic signatures. In total, 196 significant candidate genes (164 upregulated and 32 upregulated in the high- and low-grade groups, respectively) were identified. After intersection with The Cancer Genome Atlas–Lung Adenocarcinoma prognostic genes, three genes, exonuclease 1 (EXO1), family with sequence similarity 83, member A (FAM83A), and disks large-associated protein 5 (DLGAP5), were identified as prognostic gene signatures. Two independent cohorts were used for validation, and the areas under the time-dependent receiver operating characteristic were 0.784 and 0.703 in the GSE31210 and GSE30219 cohorts, respectively. Our result showed the feasibility and accuracy of this novel three-gene prognostic signature for predicting the clinical outcomes of lung adenocarcinoma.