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

Integrating IASLC grading and radiomics for predicting postoperative outcomes in stage IA invasive lung adenocarcinoma

BACKGROUND

The International Association for the Study of Lung Cancer (IASLC) Pathology Committee introduced a histologic grading system for invasive lung adenocarcinoma (LUAD) in 2020. The IASLC grading system, hinging on the evaluation of predominant and high-grade histologic patterns, has proven to be practical and prognostic for invasive LUAD. However, there are still limitations in evaluating the prognosis of stage IA LUAD. Radiomics may serve as a valuable complement.

PURPOSE

To establish a model that integrates IASLC grading and radiomics, aimed at predicting the prognosis of stage IA LUAD.

METHODS

We conducted a retrospective analysis of 628 patients diagnosed with stage IA LUAD who underwent surgical resection between January 2015 and December 2018 at our institution. The patients were randomly divided into the training set (n = 439) and testing set (n = 189) at a ratio of 7:3. Overall survival (OS) and disease-free survival (DFS) were taken as the end points. Radiomics features were obtained by PyRadiomics. Feature selection was performed using the least absolute shrinkage and selection operator (LASSO). The prediction models for OS and DFS were developed using multivariate Cox regression analysis, and the models were visualized through nomogram plots. The model's performance was evaluated using area under the curves (AUC), concordance index (C-index), calibration curves, and survival decision curve analysis (DCA).

RESULTS

In total, nine radiomics features were selected for the OS prediction model, and 15 radiomics features were selected for the DFS prediction model. Patients with high radiomics scores were associated with a worse prognosis (p < 0.001). We built separate prediction models using radiomics or IASLC alone, as well as a combined prediction model. In the prediction of OS, we observed that the combined model (C-index: 0.812 ± 0.024, 3 years AUC: 0.692, 5 years AUC: 0.792) achieved superior predictive performance than the radiomics (C-index: 0.743 ± 0.038, 3 years AUC: 0.633, 5 years AUC: 0.768) and IASLC grading (C-index: 0.765 ± 0.042, 3 years AUC: 0.658, 5 years AUC: 0.743) models alone. Similar results were obtained in the models for DFS.

CONCLUSION

The combination of radiomics and IASLC pathological grading proves to be an effective approach for predicting the prognosis of stage IA LUAD. This has substantial clinical relevance in guiding treatment decisions for early-stage LUAD.

Advancing NSCLC pathological subtype prediction with interpretable machine learning: a comprehensive radiomics-based approach

Objective

This research aims to develop and assess the performance of interpretable machine learning models for diagnosing three histological subtypes of non-small cell lung cancer (NSCLC) utilizing CT imaging data.

Methods

A retrospective cohort of 317 patients diagnosed with NSCLC was included in the study. These individuals were randomly segregated into two groups: a training set comprising 222 patients and a validation set with 95 patients, adhering to a 7:3 ratio. A comprehensive extraction yielded 1,834 radiomic features. For feature selection, statistical methodologies such as the Mann-Whitney U test, Spearman's rank correlation, and one-way logistic regression were employed. To address data imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was utilized. The study designed three distinct models to predict adenocarcinoma (ADC), squamous cell carcinoma (SCC), and large cell carcinoma (LCC). Six different classifiers, namely Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, eXtreme Gradient Boosting (XGB), and LightGBM, were deployed for model training. Model performance was gauged through accuracy metrics and the area under the receiver operating characteristic (ROC) curves (AUC). To interpret the diagnostic process, the Shapley Additive Explanations (SHAP) approach was applied.

Results

For the ADC, SCC, and LCC groups, 9, 12, and 8 key radiomic features were selected, respectively. In terms of model performance, the XGB model demonstrated superior performance in predicting SCC and LCC, with AUC values of 0.789 and 0.848, respectively. For ADC prediction, the Random Forest model excelled, showcasing an AUC of 0.748.

Conclusion

The constructed machine learning models, leveraging CT imaging, exhibited robust predictive capabilities for SCC, LCC, and ADC subtypes of NSCLC. These interpretable models serve as substantial support for clinical decision-making processes.

Experience Sharing in Pathological Diagnosis of Early Adenocarcinoma of the Lung

Background: In daily work, there are still many pathologists who have difficulty handling the diagnosis of atypical adenomatous hyperplasia, adenocarcinoma in situ, minimally invasive adenocarcinoma, and lepidic adenocarcinoma, and the boundaries are not clear enough. Sometimes, the diagnosis is difficult, and there is sometimes poor reproducibility between different pathologists. Accurate diagnosis and differential diagnosis require a certain amount of experience. Methods: During the COVID-19 pandemic, we collected a large number (n = 381) of specimens of early lung adenocarcinoma, most of which (n = 356) were solitary lesions and 25 were multifocal lesions. There were 78 nodules in multifocal lesions, total 434 nodules. We summarized very careful microscopic observation and comparative analysis on all frozen and paraffin sections collected from many early lung adenocarcinoma specimens, continuously summarizing our experience. Results: Based on the World Health Organization's 2021 classification and diagnostic criteria for lung adenocarcinoma, new perspectives have been proposed on how to distinguish between atypical adenomatous hyperplasia, adenocarcinoma in situ, minimally invasive adenocarcinoma, and lepidic adenocarcinoma. In particular, new perspectives have been proposed on how to identify invasive aspects, and there are also some new perspectives on early lung mucinous lesions. Conclusion: Atypical adenomatous hyperplasia, adenocarcinoma in situ, minimally invasive adenocarcinoma, and lepidic adenocarcinoma all have corresponding morphological diagnostic criteria, but the morphological boundaries are sometimes not easy to determine and require some experience accumulation. The intraoperative frozen pathological diagnosis of early adenocarcinoma of the lung needs to be closely combined with imaging examination, and has very rich morphological experience.

Predictive value of radiomic features extracted from primary lung adenocarcinoma in forecasting thoracic lymph node metastasis: a systematic review and meta-analysis

BACKGROUND

The application of radiomics in thoracic lymph node metastasis (LNM) of lung adenocarcinoma is increasing, but diagnostic performance of radiomics from primary tumor to predict LNM has not been systematically reviewed. Therefore, this study sought to provide a general overview regarding the methodological quality and diagnostic performance of using radiomic approaches to predict the likelihood of LNM in lung adenocarcinoma.

METHODS

Studies were gathered from literature databases such as PubMed, Embase, the Web of Science Core Collection, and the Cochrane library. The Radiomic Quality Score (RQS) and the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) were both used to assess the quality of each study. The pooled sensitivity, specificity, and area under the curve (AUC) of the best radiomics models in the training and validation cohorts were calculated. Subgroup and meta-regression analyses were also conducted.

RESULTS

Seventeen studies with 159 to 1202 patients each were enrolled between the years of 2018 to 2022, of which ten studies had sufficient data for the quantitative evaluation. The percentage of RQS was between 11.1% and 44.4% and most of the studies were considered to have a low risk of bias and few applicability concerns in QUADAS-2. Pyradiomics and logistic regression analysis were the most commonly used software and methods for radiomics feature extraction and selection, respectively. In addition, the best prediction models in seventeen studies were mainly based on radiomics features combined with non-radiomics features (semantic features and/or clinical features). The pooled sensitivity, specificity, and AUC of the training cohorts were 0.84 (95% confidence interval (CI) [0.73-0.91]), 0.88 (95% CI [0.81-0.93]), and 0.93(95% CI [0.90-0.95]), respectively. For the validation cohorts, the pooled sensitivity, specificity, and AUC were 0.89 (95% CI [0.82-0.94]), 0.86 (95% CI [0.74-0.93]) and 0.94 (95% CI [0.91-0.96]), respectively.

CONCLUSIONS

Radiomic features based on the primary tumor have the potential to predict preoperative LNM of lung adenocarcinoma. However, radiomics workflow needs to be standardized to better promote the applicability of radiomics.

TRIAL REGISTRATION

CRD42022375712.

Morphological basis of the lung adenocarcinoma subtypes

Lung adenocarcinoma (LUAD), which accounts for a large proportion of lung cancers, is divided into five major subtypes based on histologic characteristics. The clinical characteristics, prognosis, and responses to treatments vary among subtypes. Here, we demonstrate that the variations of cell-cell contact energy result in the LUAD subtype-specific morphogenesis. We reproduced the morphologies of the papillary LUAD subtypes with the cellular Potts Model (CPM). Simulations and experimental validations revealed modifications of cell-cell contact energy changed the morphology from a papillary-like structure to micropapillary or solid subtype-like structures. Remarkably, differential gene expression analysis revealed subtype-specific expressions of genes relating to cell adhesion. Knockdown experiments of the micropapillary upregulated ITGA11 gene resulted in the morphological changes of the spheroids produced from an LUAD cell line PC9. This work shows the consequences of gene mutations and gene expressions on patient prognosis through differences in tissue composing physical forces among LUAD subtypes.

Omics-based deep learning approaches for lung cancer decision-making and therapeutics development

Lung cancer has been the most common and the leading cause of cancer deaths globally. Besides clinicopathological observations and traditional molecular tests, the advent of robust and scalable techniques for nucleic acid analysis has revolutionized biological research and medicinal practice in lung cancer treatment. In response to the demands for minimally invasive procedures and technology development over the past decade, many types of multi-omics data at various genome levels have been generated. As omics data grow, artificial intelligence models, particularly deep learning, are prominent in developing more rapid and effective methods to potentially improve lung cancer patient diagnosis, prognosis and treatment strategy. This decade has seen genome-based deep learning models thriving in various lung cancer tasks, including cancer prediction, subtype classification, prognosis estimation, cancer molecular signatures identification, treatment response prediction and biomarker development. In this study, we summarized available data sources for deep-learning-based lung cancer mining and provided an update on recent deep learning models in lung cancer genomics. Subsequently, we reviewed the current issues and discussed future research directions of deep-learning-based lung cancer genomics research.

CCT6A facilitates lung adenocarcinoma progression and glycolysis via STAT1/HK2 axis

BACKGROUND

Chaperonin Containing TCP1 Subunit 6 A (CCT6A) is a prominent protein involved in the folding and stabilization of newly synthesized proteins. However, its roles and underlying mechanisms in lung adenocarcinoma (LUAD), one of the most aggressive cancers, remain elusive.

METHODS

Our study utilized in vitro cell phenotype experiments to assess CCT6A's impact on the proliferation and invasion capabilities of LUAD cell lines. To delve into CCT6A's intrinsic mechanisms affecting glycolysis and proliferation in lung adenocarcinoma, we employed transcriptomic sequencing and liquid chromatography-mass spectrometry analysis. Co-immunoprecipitation (Co-IP) and chromatin immunoprecipitation (CHIP) assays were also conducted to substantiate the mechanism.

RESULTS

CCT6A was found to be significantly overexpressed in LUAD and associated with a poorer prognosis. The silencing of CCT6A inhibited the proliferation and migration of LUAD cells and elevated apoptosis rates. Mechanistically, CCT6A interacted with STAT1 protein, forming a complex that enhances the stability of STAT1 by protecting it from ubiquitin-mediated degradation. This, in turn, facilitated the transcription of hexokinase 2 (HK2), a critical enzyme in aerobic glycolysis, thereby stimulating LUAD's aerobic glycolysis and progression.

CONCLUSION

Our findings reveal that the CCT6A/STAT1/HK2 axis orchestrated a reprogramming of glucose metabolism and thus promoted LUAD progression. These insights position CCT6A as a promising candidate for therapeutic intervention in LUAD treatment.

Pulmonary mucinous adenocarcinoma: An overview of pathophysiology and advancements in treatment

Pulmonary mucinous adenocarcinoma (PMA), a distinct subtype of non-small cell lung cancer (NSCLC), is characterized by an abundance of mucin-producing cells. Although this subtype comprises a relatively small fraction of lung adenocarcinomas, PMA stands apart due to its unique clinical, pathological, and molecular features. This review comprehensively discusses the pathophysiology and etiology, clinical features, diagnostic methods, treatment strategies, prognosis, and future directions for PMA, drawing from relevant literature and existing studies. Advances in PMA treatment includes surgical intervention, targeted therapy, immunotherapy, and adjuvant therapy. Particularly, we discussed factors influencing the prognosis of PMAs, such as molecular markers, pathological features, and the impact of the latest treatment advances on prognosis. Moreover, we intended this review to be a comprehensive reference for diagnosing, treating, and assessing the prognosis of PMA, providing valuable guidance for clinical practice.

Advances in combined neuroendocrine carcinoma of lung cancer

Lung cancer incidence and mortality rates are increasing worldwide, posing a significant public health challenge and an immense burden to affected families. Lung cancer encompasses distinct subtypes, namely, non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC). In clinical investigations, researchers have observed that neuroendocrine tumors can be classified into four types: typical carcinoid, atypical carcinoid, small-cell carcinoma, and large-cell neuroendocrine carcinoma based on their unique features. However, there exist combined forms of neuroendocrine cancer. This study focuses specifically on combined pulmonary carcinomas with a neuroendocrine component. In this comprehensive review article, the authors provide an overview of combined lung cancers and present two pathological images to visually depict these distinctive subtypes.

Real-world efficacy of adjuvant therapy for totally resected stage I lung adenocarcinoma patients with pathological high-risk factors: propensity score analysis

BACKGROUND

We investigated the real-world efficacy of adjuvant therapy for stage I lung adenocarcinoma patients with pathological high-risk factors.

METHODS

Study participants were enrolled from November 1, 2016 and December 31, 2020. Clinical bias was balanced by propensity score matching. Disease-free survival (DFS) outcomes were compared by Kaplan-Meier analysis. The Cox proportional hazards regression was used to identify survival-associated factors. p ≤ 0.05 was the threshold for statistical significance.

RESULTS

A total of 454 patients, among whom 134 (29.5%) underwent adjuvant therapy, were enrolled in this study. One hundred and eighteen of the patients who underwent adjuvant therapy were well matched with non-treatment patients. Prognostic outcomes of the treatment group were significantly better than those of the non-treatment group, as revealed by Kaplan-Meier analysis after PSM. Differences in prevention of recurrence or metastasis between the targeted therapy and chemotherapy groups were insignificant. Adjuvant therapy was found to be positive prognostic factors, tumor size and solid growth patterns were negative.

CONCLUSIONS

Adjuvant therapy significantly improved the DFS for stage I lung adenocarcinoma patients with high-risk factors. Larger prospective clinical trials should be performed to verify our findings.

Predictors of moderate to severe obstructive sleep apnea in patients with lung cancer

BACKGROUND AND OBJECTIVES

OSA is a known medical condition that is associated with several comorbidities and affect patients' quality of life. The association between OSA and lung cancer remains debated. Some studies reported increased prevalence of OSA in patients with lung cancer. We aimed to assess predictors of moderate-to-severe OSA in patients with lung cancer.

METHODS

We enrolled 153 adult patients who were newly diagnosed with lung cancer. Cardiorespiratory monitoring was performed using home sleep apnea device. We carried out Univariate and multivariate logistic regression analysis on multiple parameters including age, gender, smoking status, neck circumference, waist circumference, BMI, stage and histopathology of lung cancer, presence of superior vena cava obstruction, and performance status to find out the factors that are independently associated with a diagnosis of moderate-to-severe OSA.

RESULTS

Our results suggest that poor performance status is the most significant predictor of moderate to severe OSA in patients with lung cancer after controlling for important confounders.

CONCLUSION

Performance status is a predictor of moderate to severe OSA in patients with lung cancer in our population of middle eastern ethnicity.

Expression patterns of novel immunotherapy targets in intermediate- and high-grade lung neuroendocrine neoplasms

BACKGROUND

Advancements in immunotherapeutic approaches only had a modest impact on the therapy of lung neuroendocrine neoplasms (LNENs). Our multicenter study aimed to investigate the expression patterns of novel immunotherapy targets in intermediate- and high-grade LNENs.

METHODS

The expressions of V-domain Ig suppressor of T cell activation (VISTA), OX40L, Glucocorticoid-induced TNF receptor (GITR), and T cell immunoglobulin and mucin domain 3 (TIM3) proteins were measured by immunohistochemistry in surgically resected tumor samples of 26 atypical carcinoid (AC), 49 large cell neuroendocrine lung cancer (LCNEC), and 66 small cell lung cancer (SCLC) patients. Tumor and immune cells were separately scored.

RESULTS

Tumor cell TIM3 expression was the highest in ACs (p < 0.001), whereas elevated tumor cell GITR levels were characteristic for both ACs and SCLCs (p < 0.001 and p = 0.011, respectively). OX40L expression of tumor cells was considerably lower in ACs (vs. SCLCs; p < 0.001). Tumor cell VISTA expression was consistently low in LNENs, with no significant differences across histological subtypes. ACs were the least immunogenic tumors concerning immune cell abundance (p < 0.001). Immune cell VISTA and GITR expressions were also significantly lower in these intermediate-grade malignancies than in SCLCs or in LCNECs. Immune cell TIM3 and GITR expressions were associated with borderline prognostic significance in our multivariate model (p = 0.057 and p = 0.071, respectively).

CONCLUSIONS

LNEN subtypes have characteristic and widely divergent VISTA, OX40L, GITR, and TIM3 protein expressions. By shedding light on the different expression patterns of these immunotherapy targets, the current multicenter study provides support for the future implementation of novel immunotherapeutic approaches.

Comprehensive genomic profiling of pulmonary spindle cell carcinoma using tissue and plasma samples: insights from a real-world cohort analysis

Pulmonary spindle cell carcinoma (PSCC) is a rare and aggressive non-small cell lung cancer (NSCLC) subtype with a dismal prognosis. The molecular characteristics of PSCC are largely unknown due to its rarity, which limits the diagnosis and treatment of this historically poorly characterized malignancy. We present comprehensive genomic profiling results of baseline tumor samples from 22 patients histologically diagnosed with PSCC, representing the largest cohort to date. Somatic genetic variant detection was compared between paired plasma samples and primary tumors from 13 patients within our cohort. The associations among genomic features, treatment, and prognosis were also analyzed in representative patient cases. TP53 (54.5%), TERT (36.4%), CDKN2A (27.3%), and MET (22.7%) were most frequently mutated. Notably, 81.8% of patients had actionable targets in their baseline tumors, including MET (22.7%), ERBB2 (13.6%), EGFR (9.1%), KRAS (9.1%), ALK (9.1%), and ROS1 (4.5%). The median tumor mutation burden (TMB) for PSCC tumors was 5.5 mutations per megabase (muts/Mb). TMB-high tumors (>10 muts/Mb) exhibited a significantly higher mutation frequency in genes such as KRAS, ARID2, FOXL2, and LRP1B, as well as within the DNA mismatch repair pathway. The detection rates for single nucleotide variants and structural variants were comparable between matched tumor and plasma samples, with 48.6% of genetic variants being mutually identified in both sample types. Additionally, a patient with a high mutation load and positive PD-L1 expression demonstrated a 7-month survival benefit from chemoimmunotherapy. Furthermore, a patient with an ALK-rearranged tumor achieved a remarkable 3-year progression-free survival following crizotinib treatment. Overall, our findings deepen the understanding of the complex genomic landscape of PSCC, revealing actionable targets amenable to tailored treatment of this poorly characterized malignancy.

Whole-lesion iodine map histogram analysis versus single-slice spectral CT parameters for determining novel International Association for the Study of Lung Cancer grade of invasive non-mucinous pulmonary adenocarcinomas

PURPOSE

The purpose of this study was to evaluate and compare the performances of whole-lesion iodine map histogram analysis to those of single-slice spectral computed tomography (CT) parameters in discriminating between low-to-moderate grade invasive non-mucinous pulmonary adenocarcinoma (INMA) and high-grade INMA according to the novel International Association for the Study of Lung Cancer grading system of INMA.

MATERIALS AND METHODS

Sixty-one patients with INMA (34 with low-to-moderate grade [i.e., grade I and grade II] and 27 with high grade [i.e., grade III]) were evaluated with spectral CT. There were 28 men and 33 women, with a mean age of 56.4 ± 10.5 (standard deviation) years (range: 29-78 years). The whole-lesion iodine map histogram parameters (mean, standard deviation, variance, skewness, kurtosis, entropy, and 1st, 10th, 25th, 50th, 75th, 90th, and 99th percentile) were measured for each INMA. In other sessions, by placing regions of interest at representative levels of the tumor and normalizing them, spectral CT parameters (iodine concentration and normalized iodine concentration) were obtained. Discriminating capabilities of spectral CT and histogram parameters were assessed and compared using area under the ROC curve (AUC) and logistic regression models.

RESULTS

The 1st, 10th, and 25th percentiles of the iodine map histogram analysis, and iodine concentration and normalized iodine concentration of single-slice spectral CT parameters were significantly different between high-grade and low-to-moderate grade INMAs (P < 0.001 to P = 0.002). The 1st percentile of histogram parameters (AUC, 0.84; 95% confidence interval [CI]: 0.73-0.92) and iodine concentration (AUC, 0.78; 95% CI: 0.66-0.88) from single-slice spectral CT parameters had the best performance for discriminating between high-grade and low-to-moderate grade INMAs. At ROC curve analysis no significant differences in AUC were found between histogram parameters (AUC = 0.86; 95% CI: 0.74-0.93) and spectral CT parameters (AUC = 0.81; 95% CI: 0.74-0.93) (P = 0.60).

CONCLUSION

Both whole-lesion iodine map histogram analysis and single-slice spectral CT parameters help discriminate between low-to-moderate grade and high-grade INMAs according to the novel International Association for the Study of Lung Cancer grading system, with no differences in diagnostic performances.

Favorable treatment response of bevacizumab-combined chemotherapy for advanced or recurrent invasive mucinous adenocarcinoma of the lung: A retrospective observational study

Invasive mucinous adenocarcinoma (IMA) of the lung is a rare variant of adenocarcinoma characterized by abundant intracytoplasmic mucin within the tumor. Although IMA has poor sensitivity to conventional chemotherapy regimens used for non-small cell lung cancer, we observed a better response to the bevacizumab (BEV) regimen. In this retrospective study, we aimed to investigate the response to BEV-combined regimens in patients with IMA. Among 16 consecutive patients diagnosed with IMA between January 2016 and December 2020 at our institution and treated with systemic chemotherapy, seven patients were treated with BEV-combined regimens. The overall response rate to BEV-combined regimens was 85.7%, with six patients showing a partial response. The median progression-free survival was 6.1 months. One patient experienced respiratory failure, which was improved after administration of BEV-combined regimen. BEV-combined systemic therapy may have a favorable effect on advanced or recurrent IMA of the lung.

Computed tomography-based 3D convolutional neural network deep learning model for predicting micropapillary or solid growth pattern of invasive lung adenocarcinoma

PURPOSE

To investigate the value of a computed tomography (CT)-based deep learning (DL) model to predict the presence of micropapillary or solid (M/S) growth pattern in invasive lung adenocarcinoma (ILADC).

MATERIALS AND METHODS

From June 2019 to October 2022, 617 patients with ILADC who underwent preoperative chest CT scans in our institution were randomly placed into training and internal validation sets in a 4:1 ratio, and 353 patients with ILADC from another institution were included as an external validation set. Then, a self-paced learning (SPL) 3D Net was used to establish two DL models: model 1 was used to predict the M/S growth pattern in ILADC, and model 2 was used to predict that pattern in ≤ 2-cm-diameter ILADC.

RESULTS

For model 1, the training cohort's area under the curve (AUC), accuracy, recall, precision, and F1-score were 0.924, 0.845, 0.851, 0.842, and 0.843; the internal validation cohort's were 0.807, 0.744, 0.756, 0.750, and 0.743; and the external validation cohort's were 0.857, 0.805, 0.804, 0.806, and 0.804, respectively. For model 2, the training cohort's AUC, accuracy, recall, precision, and F1-score were 0.946, 0.858, 0.881,0.844, and 0.851; the internal validation cohort's were 0.869, 0.809, 0.786, 0.794, and 0.790; and the external validation cohort's were 0.831, 0.792, 0.789, 0.790, and 0.790, respectively. The SPL 3D Net model performed better than the ResNet34, ResNet50, ResNeXt50, and DenseNet121 models.

CONCLUSION

The CT-based DL model performed well as a noninvasive screening tool capable of reliably detecting and distinguishing the subtypes of ILADC, even in small-sized tumors.

Ki-67 Proliferation Index Is Associated With Tumor Grade and Survival in Pleural Epithelioid Mesotheliomas

Pleural epithelioid mesothelioma (PEM) is divided into low and high grades based on nuclear atypia, mitoses, and necrosis in the tumor. Assessing mitoses and nuclear atypia tend to be labor-intensive with limited reproducibility. Ki-67 proliferation index was shown to be a prognostic factor in PEM, but its performance has not been directly correlated with tumor grade or mitotic score. This study evaluated the potential of Ki-67 index as a surrogate of tumor grade. We also compared the predictability of mitoses and Ki-67 index for overall survival (OS). Ninety-six PEM samples from 85 patients were identified from the surgical pathology file during 2000-2021 at our institution, and all glass slides were reviewed by 2 pulmonary pathologists to confirm the diagnosis and assign the tumor grade. Digital image analysis (DIA) was done for Ki-67 index. The agreement on tumor grading between 2 reviewers was moderate (kappa value = 0.47). The correlation between mitotic count (average count by 2 reviewers) and Ki-67 index was 0.65. The areas under the curve for predicting tumor grade by mitotic score and Ki-67 index were 0.84 and 0.74 (reviewer 1) and 0.85 and 0.81 (reviewer 2), respectively. High Ki-67 index and mitoses were significantly associated with poor OS ( P =0.03 and 0.0005, using 30% and 10/2 mm 2 as cutoffs, respectively). In conclusion, Ki-67 index by DIA was associated with tumor grade as well as mitotic count, and its predictability for OS was comparable to that of mitotic score, thus being a potential surrogate for tumor grade.

A new schedule of one week on/one week off temozolomide as second-line treatment of advanced neuroendocrine carcinomas (TENEC-TRIAL): a multicenter, open-label, single-arm, phase II trial

BACKGROUND

There is no consensus on the second-line treatment of patients with progressive high-grade neuroendocrine neoplasms (NENs G3) and large-cell lung neuroendocrine carcinoma. These patients generally have poor performance status and low tolerance to combination therapy. In this trial, we aim to evaluate the efficacy and safety of temozolomide given every other week in patients with advanced platinum-pretreated NENs G3.

PATIENTS AND METHODS

This trial is an open-label, non-randomized, phase II trial. Patients with platinum-pretreated metastatic neuroendocrine carcinoma were treated with 75 mg/m2/day of temozolomide for 7 days, followed by 7 days of no treatment (regimen one week on/one week off). The primary endpoint was the overall response rate. Secondary endpoints included progression-free survival (PFS), overall survival (OS), safety and tolerability. This study is registered with ClinicalTrials.gov, NCT04122911.

RESULTS

From 2017 to 2020, 38 patients were enrolled. Among the patients with determined Ki67, 12 out of 36 (33.3%) had a Ki67 index <55% and the remaining 24 out of 36 (66.6%) had an index ≥55%. Overall response rate was 18% (7/38), including one complete response and six partial responses. The median PFS was 5.86 months [95% confidence interval (CI) 4.8 months-not applicable) and the median OS was 12.1 months (95% CI 5.6-20.4 months). The 1-year PFS rate was 37%. No statistically significant difference in median PFS [hazard ratio 1.3 (95% CI 0.6-2.8); P = 0.44] and median OS [hazard ratio 1.1 (95% CI 0.5-2.4); P = 0.77] was observed among patients with Ki67 <55% versus ≥55%. Only G1-G2 adverse events were registered, the most common being G1 nausea, diarrhea and abdominal pain.

CONCLUSION

One week on/one week off temozolomide shows promising activity in patients with poorly differentiated NEN. The good safety profile confirmed the possibility of using this scheme in patients with poor performance status.

Molecular and Pathologic Characterization of YAP1-Expressing Small Cell Lung Cancer Cell Lines Leads to Reclassification as SMARCA4-Deficient Malignancies

PURPOSE

The classification of small cell lung cancer (SCLC) into distinct molecular subtypes defined by ASCL1, NEUROD1, POU2F3, or YAP1 (SCLC-A, -N, -P, or -Y) expression, paves the way for a personalized treatment approach. However, the existence of a distinct YAP1-expressing SCLC subtype remains controversial.

EXPERIMENTAL DESIGN

To better understand YAP1-expressing SCLC, the mutational landscape of human SCLC cell lines was interrogated to identify pathogenic alterations unique to SCLC-Y. Xenograft tumors, generated from cell lines representing the four SCLC molecular subtypes, were evaluated by a panel of pathologists who routinely diagnose thoracic malignancies. Diagnoses were complemented by transcriptomic analysis of primary tumors and human cell line datasets. Protein expression profiles were validated in patient tumor tissue.

RESULTS

Unexpectedly, pathogenic mutations in SMARCA4 were identified in six of eight SCLC-Y cell lines and correlated with reduced SMARCA4 mRNA and protein expression. Pathologist evaluations revealed that SMARCA4-deficient SCLC-Y tumors exhibited features consistent with thoracic SMARCA4-deficient undifferentiated tumors (SMARCA4-UT). Similarly, the transcriptional profile SMARCA4-mutant SCLC-Y lines more closely resembled primary SMARCA4-UT, or SMARCA4-deficient non-small cell carcinoma, than SCLC. Furthermore, SMARCA4-UT patient samples were associated with a YAP1 transcriptional signature and exhibited strong YAP1 protein expression. Together, we found little evidence to support a diagnosis of SCLC for any of the YAP1-expressing cell lines originally used to define the SCLC-Y subtype.

CONCLUSIONS

SMARCA4-mutant SCLC-Y cell lines exhibit characteristics consistent with SMARCA4-deficient malignancies rather than SCLC. Our findings suggest that, unlike ASCL1, NEUROD1, and POU2F3, YAP1 is not a subtype defining transcription factor in SCLC. See related commentary by Rekhtman, p. 1708.

Construction of a prognostic model based on memory CD4+ T cell-associated genes for lung adenocarcinoma and its applications in immunotherapy

The association between memory CD4+ T cells and cancer prognosis is increasingly recognized, but their impact on lung adenocarcinoma (LUAD) prognosis remains unclear. In this study, using the cell-type identification by estimating relative subsets of RNA transcripts algorithm, we analyzed immune cell composition and patient survival in LUAD. Weighted gene coexpression network analysis helped identify memory CD4+ T cell-associated gene modules. Combined with module genes, a five-gene LUAD prognostic risk model (HOXB7, MELTF, ABCC2, GNPNAT1, and LDHA) was constructed by regression analysis. The model was validated using the GSE31210 data set. The validation results demonstrated excellent predictive performance of the risk scoring model. Correlation analysis was conducted between the clinical information and risk scores of LUAD samples, revealing that LUAD patients with disease progression exhibited higher risk scores. Furthermore, univariate and multivariate regression analyses demonstrated the model independent prognostic capability. The constructed nomogram results demonstrated that the predictive performance of the nomogram was superior to the prognostic model and outperformed individual clinical factors. Immune landscape assessment was performed to compare different risk score groups. The results revealed a better prognosis in the low-risk group with higher immune infiltration. The low-risk group also showed potential benefits from immunotherapy. Our study proposes a memory CD4+ T cell-associated gene risk model as a reliable prognostic biomarker for personalized treatment in LUAD patients.

Targeting KRASG12C in Non-Small-Cell Lung Cancer: Current Standards and Developments

Among the most common molecular alterations detected in non-small-cell lung cancer (NSCLC) are mutations in Kristen Rat Sarcoma viral oncogene homolog (KRAS). KRAS mutant NSCLC is a heterogenous group of diseases, different from other oncogene-driven tumors in terms of biology and response to therapies. Despite efforts to develop drugs aimed at inhibiting KRAS or its signaling pathways, KRAS had remained undruggable for decades. The discovery of a small pocket in the binding switch II region of KRASG12C has revolutionized the treatment of KRASG12C-mutated NSCLC patients. Sotorasib and adagrasib, direct KRASG12C inhibitors, have been approved by the US Food and Drug Administration (FDA) and other regulatory agencies for patients with previously treated KRASG12C-mutated NSCLC, and these advances have become practice changing. However, first-line treatment in KRASG12C-mutated NSCLC does not differ from NSCLC without actionable driver genomic alterations. Treatment with KRASG12C inhibitors is not curative and patients develop progressive disease, so understanding associated mechanisms of drug resistance is key. New KRASG12C inhibitors and several combination therapy strategies, including with immune checkpoint inhibitors, are being studied in clinical trials. The aim of this review is to explore the clinical impact of KRAS, and outline different treatment approaches, focusing on the novel treatment of KRASG12C-mutated NSCLC.

Proteomics-Derived Biomarker Panel Facilitates Distinguishing Primary Lung Adenocarcinomas With Intestinal or Mucinous Differentiation From Lung Metastatic Colorectal Cancer

The diagnosis of primary lung adenocarcinomas with intestinal or mucinous differentiation (PAIM) remains challenging due to the overlapping histomorphological, immunohistochemical (IHC), and genetic characteristics with lung metastatic colorectal cancer (lmCRC). This study aimed to explore the protein biomarkers that could distinguish between PAIM and lmCRC. To uncover differences between the two diseases, we used tandem mass tagging-based shotgun proteomics to characterize proteomes of formalin-fixed, paraffin-embedded tumor samples of PAIM (n = 22) and lmCRC (n = 17).Then three machine learning algorithms, namely support vector machine (SVM), random forest, and the Least Absolute Shrinkage and Selection Operator, were utilized to select protein features with diagnostic significance. These candidate proteins were further validated in an independent cohort (PAIM, n = 11; lmCRC, n = 19) by IHC to confirm their diagnostic performance. In total, 105 proteins out of 7871 proteins were significantly dysregulated between PAIM and lmCRC samples and well-separated two groups by Uniform Manifold Approximation and Projection. The upregulated proteins in PAIM were involved in actin cytoskeleton organization, platelet degranulation, and regulation of leukocyte chemotaxis, while downregulated ones were involved in mitochondrial transmembrane transport, vasculature development, and stem cell proliferation. A set of ten candidate proteins (high-level expression in lmCRC: CDH17, ATP1B3, GLB1, OXNAD1, LYST, FABP1; high-level expression in PAIM: CK7 (an established marker), NARR, MLPH, S100A14) was ultimately selected to distinguish PAIM from lmCRC by machine learning algorithms. We further confirmed using IHC that the five protein biomarkers including CDH17, CK7, MLPH, FABP1 and NARR were effective biomarkers for distinguishing PAIM from lmCRC. Our study depicts PAIM-specific proteomic characteristics and demonstrates the potential utility of new protein biomarkers for the differential diagnosis of PAIM and lmCRC. These findings may contribute to improving the diagnostic accuracy and guide appropriate treatments for these patients.

m6A-induced TRIB3 regulates Hippo pathway through interacting with LATS1 to promote the progression of lung adenocarcinoma

Recent studies have indicated that dysregulation of the Hippo/Yes-associated protein (YAP) axis is associated with tumor progression and therapy resistance in various cancer types, including lung adenocarcinoma (LUAD). Understanding the regulation of Hippo signaling in LUAD is of great significance. Elevated levels of TRIB3, a pseudo kinase, have been observed in certain lung malignancies and are associated with an unfavorable prognosis. Our research aims to investigate whether increased TRIB3 levels enhance the malignant characteristics of LUAD cells and tumor progression through its interaction with the Hippo signaling pathway. In this study, we reported a positive correlation between elevated expression of TRIB3 and LUAD progression. Additionally, TRIB3 has the ability to enhance TEAD luciferase function and suppress Hippo pathway activity. Moreover, TRIB3 increases total YAP protein levels and promotes YAP nuclear localization. Mechanistic experiments revealed that TRIB3 directly interacts with large tumor suppressor kinase 1 (LATS1), thereby suppressing Hippo signaling. Moreover, the decrease in METTL3-mediated N6-methyladenosine modification of TRIB3 results in a substantial elevation of its expression levels in LUAD cells. Collectively, our research unveils a novel discovery that TRIB3 enhances the growth and invasion of LUAD cells by interacting with LATS1 and inhibiting the Hippo signaling pathway. TRIB3 may serve as a potential biomarker for an unfavorable prognosis and a target for novel treatments in YAP-driven lung cancer.

The golden key to open mystery boxes of SMARCA4-deficient undifferentiated thoracic tumor: focusing immunotherapy, tumor microenvironment and epigenetic regulation

SMARCA4-deficient undifferentiated thoracic tumor is extremely invasive. This tumor with poor prognosis is easily confused with SMARCA4-deficent non-small cell lung cancer or sarcoma. Standard and efficient treatment has not been established. In this review, we summarized the etiology, pathogenesis and diagnosis, reviewed current and proposed innovative strategies for treatment and improving prognosis. Immunotherapy, targeting tumor microenvironment and epigenetic regulator have improved the prognosis of cancer patients. We summarized clinicopathological features and immunotherapy strategies and analyzed the progression-free survival (PFS) and overall survival (OS) of patients with SMARCA4-UT who received immune checkpoint inhibitors (ICIs). In addition, we proposed the feasibility of epigenetic regulation in the treatment of SMARCA4-UT. To our knowledge, this is the first review that aims to explore innovative strategies for targeting tumor microenvironment and epigenetic regulation and identify potential benefit population for immunotherapy to improve the prognosis.

Sublobar Resection of Non-Small-Cell Lung Cancer: Wedge Resection vs. Segmentectomy

Lung cancer is the most common cause of cancer death. The mainstay treatment for non-small-cell lung cancer (NSCLC), particularly in the early stages, is surgical resection. Traditionally, lobectomy has been considered the gold-standard technique. Sublobar resection includes segmentectomy and wedge resection. Compared to lobectomy, these procedures have been viewed as a compromise procedure, reserved for those with poor cardiopulmonary function or who are poor surgical candidates for other reasons. However, with the advances in imaging and surgical techniques, the subject of sublobar resection as a curative treatment is being revisited. Many studies have now shown segmentectomy to be equivalent to lobectomy in patients with small (<2.0 cm), peripheral NSCLC. However, there is a mix of evidence when it comes to wedge resection and its suitability as a curative procedure. At this time, until more data can be found, segmentectomy should be considered before wedge resection for patients with early-stage NSCLC.

High core 1β1,3-galactosyltransferase 1 expression is associated with poor prognosis and promotes cellular radioresistance in lung adenocarcinoma

PURPOSE

Core 1β1,3-galactosyltransferase 1 (C1GALT1) exhibits elevated expression in multiple cancers. The present study aimed to elucidate the clinical significance of C1GALT1 aberrant expression and its impact on radiosensitivity in lung adenocarcinoma (LUAD).

METHODS

The C1GALT1 expression and its clinical relevance were investigated through public databases and LUAD tissue microarray analyses. A549 and H1299 cells with either C1GALT1 knockdown or overexpression were further assessed through colony formation, gamma-H2A histone family member X immunofluorescence, 5-ethynyl-2'-deoxyuridine incorporation, and flow cytometry assays. Bioinformatics analysis was used to explore single cell sequencing data, revealing the influence of C1GALT1 on cancer-associated cellular states. Vimentin, N-cadherin, and E-cadherin protein levels were measured through western blotting.

RESULTS

The expression of C1GALT1 was significantly higher in LUAD tissues than in adjacent non-tumor tissues both at mRNA and protein level. High expression of C1GALT1 was correlated with lymph node metastasis, advanced T stage, and poor survival, and was an independent risk factor for overall survival. Radiation notably upregulated C1GALT1 expression in A549 and H1299 cells, while radiosensitivity was increased following C1GALT1 knockdown and decreased following overexpression. Experiment results showed that overexpression of C1GALT1 conferred radioresistance, promoting DNA repair, cell proliferation, and G2/M phase arrest, while inhibiting apoptosis and decreasing E-cadherin expression, alongside upregulating vimentin and N-cadherin in A549 and H1299 cells. Conversely, C1GALT1 knockdown had opposing effects.

CONCLUSION

Elevated C1GALT1 expression in LUAD is associated with an unfavorable prognosis and contributes to increased radioresistance potentially by affecting DNA repair, cell proliferation, cell cycle regulation, and epithelial-mesenchymal transition (EMT).

Mean computed tomography value to predict spread through air spaces in clinical N0 lung adenocarcinoma

BACKGROUND

The aim of this study was to assess the ability of radiologic factors such as mean computed tomography (mCT) value, consolidation/tumor ratio (C/T ratio), solid tumor size, and the maximum standardized uptake (SUVmax) value by F-18 fluorodeoxyglucose positron emission tomography to predict the presence of spread through air spaces (STAS) of lung adenocarcinoma.

METHODS

A retrospective study was conducted on 118 patients those diagnosed with clinically without lymph node metastasis and having a pathological diagnosis of adenocarcinoma after undergoing surgery. Receiver operating characteristics (ROC) analysis was used to assess the ability to use mCT value, C/T ratio, tumor size, and SUVmax value to predict STAS. Univariate and multiple logistic regression analyses were performed to determine the independent variables for the prediction of STAS.

RESULTS

Forty-one lesions (34.7%) were positive for STAS and 77 lesions were negative for STAS. The STAS positive group was strongly associated with a high mCT value, high C/T ratio, large solid tumor size, large tumor size and high SUVmax value. The mCT values were - 324.9 ± 19.3 HU for STAS negative group and - 173.0 ± 26.3 HU for STAS positive group (p < 0.0001). The ROC area under the curve of the mCT value was the highest (0.738), followed by SUVmax value (0.720), C/T ratio (0.665), solid tumor size (0.649). Multiple logistic regression analyses using the preoperatively determined variables revealed that mCT value (p = 0.015) was independent predictive factors of predicting STAS. The maximum sensitivity and specificity were obtained at a cutoff value of - 251.8 HU.

CONCLUSIONS

The evaluation of mCT value has a possibility to predict STAS and may potentially contribute to the selection of suitable treatment strategies.

Human Papillomavirus Is Rare and Does Not Correlate with p16INK4A Expression in Non-Small-Cell Lung Cancer in a Jordanian Subpopulation

Background and Objectives: Human papillomavirus (HPV) was previously investigated in lung cancer with wide inter-geographic discrepancies. p16INK4a has been used as a surrogate for detecting high-risk HPV (HR-HPV) in some cancer types. This study assessed the evidence of HPV in non-small-cell lung cancer (NSCLC) among Jordanian patients, investigated the expression of p16INK4a, and evaluated its prognostic value and association with HPV status. Materials and Methods: The archived samples of 100 patients were used. HPV DNA detection was performed by real-time polymerase chain reaction (RT-PCR). p16INK4a expression was assessed by immunohistochemistry (IHC). The Eighth American Joint Committee on Cancer protocol (AJCC) of head and neck cancer criteria were applied to evaluate p16INK4a positivity considering a moderate/strong nuclear/cytoplasmic expression intensity with a distribution in ≥75% of cells as positive. Results: HPV DNA was detected in 5% of NSCLC cases. Three positive cases showed HR-HPV subtypes (16, 18, 52), and two cases showed the probable HR-HPV 26 subtype. p16INK4a expression was positive in 20 (20%) NSCLC cases. None of the HPV-positive tumors were positive for p16INK4a expression. A statistically significant association was identified between p16INK4a expression and the pathological stage (p = 0.029) but not with other variables. No survival impact of p16INK4a expression was detected in NSCLC cases as a group; however, it showed a statistically significant association with overall survival (OS) in squamous cell carcinoma (SqCC) cases (p = 0.033). Conclusions: This is the first study to assess HPV and p16INK4a expression in a Jordanian population. HPV positivity is rare in NSCLC among a Jordanian subpopulation. P16 INK4a reliability as a surrogate marker for HPV infection in lung cancer must be revisited.

RICTOR amplification is associated with Rictor membrane staining and does not correlate with PD-L1 expression in lung squamous cell carcinoma

RICTOR gene, which encodes the scaffold protein of mTORC2, can be amplified in various tumor types, including squamous cell carcinoma (SCC) of the lung. RICTOR amplification can lead to hyperactivation of mTORC2 and may serve as a targetable genetic alteration, including in lung SCC patients with no PD-L1 expression who are not expected to benefit from immune checkpoint inhibitor therapy. This study aimed to compare RICTOR amplification detected by fluorescence in situ hybridization (FISH) with Rictor and PD-L1 protein expression detected by immunohistochemistry (IHC) in SCC of the lung. The study was complemented by analysis of the publicly available Lung Squamous Cell Carcinoma (TCGA, Firehose legacy) dataset. RICTOR amplification was observed in 20% of our cases and 16% of the lung SCC cases of the TCGA dataset. Rictor and PD-L1 expression was seen in 74% and 44% of the cases, respectively. Rictor IHC showed two staining patterns: membrane staining (16% of the cases) and cytoplasmic staining (58% of the cases). Rictor membrane staining predicted RICTOR amplification as detected by FISH with high specificity (95%) and sensitivity (70%). We did not find any correlation between RICTOR amplification and PD-L1 expression; RICTOR amplification was detected in 18% and 26% of PD-L1 positive and negative cases, respectively. The TCGA dataset analysis showed similar results; RICTOR copy number correlated with Rictor mRNA and protein expression but showed no association with PD-L1 mRNA and protein expression. In conclusion, the correlation between RICTOR amplification and Rictor membrane staining suggests that the latter can potentially be used as a surrogate marker to identify lung SCC cases with RICTOR amplification. Since a significant proportion of PD-L1 negative SCC cases harbor RICTOR amplification, analyzing PD-L1 negative tumors by RICTOR FISH or Rictor IHC can help select patients who may benefit from mTORC2 inhibitor therapy.

HIF1A-dependent overexpression of MTFP1 promotes lung squamous cell carcinoma development by activating the glycolysis pathway

Introduction

Mitochondrial fission process 1 (MTFP1) is an inner mitochondrial membrane (IMM) protein implicated in the development and progression of various tumors, particularly lung squamous cell carcinoma (LUSC). This study aims to provide a more theoretical basis for the treatment of LUSC.

Methods

Through bioinformatics analysis, MTFP1 was identified as a novel target gene of HIF1A. MTFP1 expression in LUSC was examined using The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Proteomics Data Commons (PDC) databases. The Kaplan-Meier plotter (KM plotter) database was utilized to evaluate its correlation with patient survival. Western blot and chromatin immunoprecipitation (ChIP) assays were employed to confirm the regulatory relationship between MTFP1 and HIF1A. Additionally, cell proliferation, colony formation, and migration assays were conducted to investigate the mechanism by which MTFP1 enhances LUSC cell proliferation and metastasis.

Results

Our findings revealed that MTFP1 overexpression correlated with poor prognosis in LUSC patients(P < 0.05). Moreover, MTFP1 was closely associated with hypoxia and glycolysis in LUSC (R = 0.203; P < 0.001, R = 0.391; P < 0.001). HIF1A was identified as a positive regulator of MTFP1. Functional enrichment analysis demonstrated that MTFP1 played a role in controlling LUSC cell proliferation. Cell proliferation, colony formation, and migration assays indicated that MTFP1 promoted LUSC cell proliferation and metastasis by activating the glycolytic pathway (P < 0.05).

Conclusions

This study establishes MTFP1 as a novel HIF1A target gene that promotes LUSC growth by activating the glycolytic pathway. Investigating MTFP1 may contribute to the development of effective therapies for LUSC patients, particularly those lacking targeted oncogene therapies.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Mechanisms of resistance to targeted therapy and immunotherapy in non-small cell lung cancer: promising strategies to overcoming challenges

Resistance to targeted therapy and immunotherapy in non-small cell lung cancer (NSCLC) is a significant challenge in the treatment of this disease. The mechanisms of resistance are multifactorial and include molecular target alterations and activation of alternative pathways, tumor heterogeneity and tumor microenvironment change, immune evasion, and immunosuppression. Promising strategies for overcoming resistance include the development of combination therapies, understanding the resistance mechanisms to better use novel drug targets, the identification of biomarkers, the modulation of the tumor microenvironment and so on. Ongoing research into the mechanisms of resistance and the development of new therapeutic approaches hold great promise for improving outcomes for patients with NSCLC. Here, we summarize diverse mechanisms driving resistance to targeted therapy and immunotherapy in NSCLC and the latest potential and promising strategies to overcome the resistance to help patients who suffer from NSCLC.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Early-Stage Non-Small Cell Lung Cancer: Prevalence of Actionable Alterations in a Monocentric Consecutive Cohort

Early-stage (ES) non-small cell lung cancer (NSCLC) is diagnosed in about 30% of cases. The preferred treatment is surgery, but a significant proportion of patients experience recurrence. Neoadjuvant and adjuvant chemotherapy has a limited clinical benefit. EGFR tyrosine kinase inhibitors and immunotherapy have recently opened new therapeutic scenarios. However, only a few data are available about the ES-NSCLC molecular landscape and the impact of oncogene addiction on therapy definition. Here, we determined the prevalence of the main lung cancer driver alterations in a monocentric consecutive cohort. Molecular analysis was performed on 1122 cases, including 368 ES and 754 advanced NSCLC. The prevalence of actionable alterations was similar between early and advanced stages. ES-NSCLC was significantly enriched for MET exon-14 skipping alterations and presented a lower prevalence of BRAF p.(V600E) mutation. PD-L1 expression levels, evaluated according to actionable alterations, were higher in advanced than early tumors harboring EGFR, KRAS, MET alterations and gene fusions. Taken together, these results confirm the value of biomarker testing in ES-NSCLC. Although approved targeted therapies for ES-NSCLC are still limited, the identification of actionable alterations could improve patients' selection for immunotherapy, favoring the enrollment in clinical trials and allowing a faster treatment start at disease recurrence.

Current and future genomic applications for surgeons

Genomics is a crucial part of managing surgical disease. This review focuses on some of the genomic advances that are available now and looks to the future of their application in surgical practice. Whole-genome sequencing enables unbiased coverage across the entire human genome of approximately three billion base pairs. Newer technologies, such as those that permit long-read sequence analysis, provide additional information in longer phased fragment and base pair epigenomic (methylomic) data. Whole-genome sequencing is currently available in England for cancers in children, teenagers and young adults, central nervous system tumours, sarcoma and haematological malignancies. Circulating tumour DNA (ctDNA), immunotherapy and pharmacogenomics have emerged as groundbreaking approaches in the field of cancer treatment. These are now revolutionising the way oncologists and surgeons approach curative cancer surgery. Cancer vaccines offer an innovative approach to reducing recurrence after surgery by priming the immune system to trigger an immune response. The Cancer Vaccine Launch Pad project facilitates cancer vaccine studies in England. The BNT122-01 trial is recruiting patients with ctDNA-positive high-risk colorectal cancer after surgery to assess the impact of cancer vaccines. The evolving landscape of cancer treatment demands a dynamic and integrated approach from the surgical multidisciplinary team. Immunotherapy, ctDNA, pharmacogenomics, vaccines, mainstreaming and whole-genome sequencing are just some of the innovations that have the potential to redefine the standards of care. The continued exploration of these innovative diagnostics and therapies, the genomic pathway evolution and their application in diverse cancer types highlights the transformative impact of precision medicine in surgery.

Diagnostic Accuracy of a Computed Tomography-Guided Transthoracic Needle Biopsy for Ground-Glass Opacities and Subsolid Pulmonary Nodules

Purpose The increasing use of computed tomography (CT) imaging has led to the detection of more ground-glass nodules (GGNs) and subsolid nodules (SSNs), which may be malignant and require a biopsy for proper diagnosis. Approximately 75% of persistent GGNs can be attributed to adenocarcinoma in situ or minimally invasive adenocarcinoma. A CT-guided biopsy has been proven to be a reliable procedure with high diagnostic performance. However, the diagnostic accuracy and safety of a CT-guided biopsy for GGNs and SSNs with solid components ≤6 mm are still uncertain. The aim of this study is to assess the diagnostic accuracy of a CT-guided core needle biopsy (CNB) for GGN and SSNs with solid components ≤6 mm. Methods This is a retrospective study of patients who underwent CT-guided CNB for the evaluation of GGNs and SSNs with solid components ≤6 mm between February 2020 and January 2023. Biopsy findings were compared to the final diagnosis determined by definite histopathologic examination and clinical course. Results A total of 22 patients were enrolled, with a median age of 74 years (IQR: 68-81). A total of 22 nodules were assessed, comprising 15 (68.2%) SSNs with a solid component measuring ≤6 mm and seven (31.8%) pure GGNs. The histopathological examination revealed that 12 (54.5%) were diagnosed as malignant, nine (40.9%) as benign, and one (4.5%) as non-diagnostic. The overall diagnostic accuracy and sensitivity for malignancy were 86.36% and 85.7%, respectively. Conclusion A CT-guided CNB for GGNs and SSNs with solid components measuring ≤6 mm appears to have a high diagnostic accuracy.

Phase II study of pembrolizumab and lenvatinib in advanced well-differentiated neuroendocrine tumors

BACKGROUND

Immune checkpoint inhibitors (CPIs) have not been shown to be active in well-differentiated neuroendocrine tumors (NETs), with response rates <5%. Lenvatinib is a multitargeted tyrosine kinase inhibitor which binds to vascular endothelial growth factor and fibroblast growth factor receptors and has demonstrated efficacy in pancreatic and gastrointestinal NETs [44% and 16% objective radiographic response rate (ORR), respectively]. The combination of antiangiogenic and CPI therapies can be synergistic. We therefore evaluated the combination of lenvatinib and pembrolizumab in well-differentiated gastrointestinal (GI) and thoracic NETs.

PATIENTS AND METHODS

A prospective, phase II trial evaluated patients with advanced GI/thoracic NETs (pancreatic NETs were excluded due to high response rate of lenvatinib monotherapy in this patient population), with evidence of progression within 8 months of study entry and at least two prior lines of systemic therapy. Patients received lenvatinib 20 mg daily and pembrolizumab 200 mg intravenously every 3 weeks until unacceptable toxicity or progression of disease. Primary endpoint was objective response rate, and an interim analysis was planned once 20 patients were enrolled. Four ORRs were required to continue enrollment.

RESULTS

Twenty patients were enrolled on protocol from April 2021 to January 2022 (nine small intestine, five lung, two thymic, two unknown primary, one cecal, one presacral primaries). Two patients (10%) achieved a partial response (atypical lung and small intestinal primaries). Median progression-free survival (PFS) was 8 months (95% confidence interval 5.8-10.2 months). Twelve (60%) patients experienced probably or definitely associated grade 3 adverse events (10 hypertension). Fourteen patients (70%) required dose reductions or discontinued one of the medications. Two patients discontinued treatment before radiographic assessment.

CONCLUSIONS

The combination of pembrolizumab and lenvatinib did not show sufficient response in patients with NETs to warrant continued enrollment on trial.

Exhaled breath condensate contains extracellular vesicles (EVs) that carry miRNA cargos of lung tissue origin that can be selectively purified and analyzed

Lung diseases, including lung cancer, are rising causes of global mortality. Despite novel imaging technologies and the development of biomarker assays, the detection of lung cancer remains a significant challenge. However, the lung communicates directly with the external environment and releases aerosolized droplets during normal tidal respiration, which can be collected, stored and analzsed as exhaled breath condensate (EBC). A few studies have suggested that EBC contains extracellular vesicles (EVs) whose microRNA (miRNA) cargos may be useful for evaluating different lung conditions, but the cellular origin of these EVs remains unknown. In this study, we used nanoparticle tracking, transmission electron microscopy, Western blot analyses and super resolution nanoimaging (ONi) to detect and validate the identity of exhaled EVs (exh-EVs). Using our customizable antibody-purification assay, EV-CATCHER, we initially determined that exh-EVs can be selectively enriched from EBC using antibodies against three tetraspanins (CD9, CD63 and CD81). Using ONi we also revealed that some exh-EVs harbour lung-specific proteins expressed in bronchiolar Clara cells (Clara Cell Secretory Protein [CCSP]) and Alveolar Type II cells (Surfactant protein C [SFTPC]). When conducting miRNA next generation sequencing (NGS) of airway samples collected at five different anatomic levels (i.e., mouth rinse, mouth wash, bronchial brush, bronchoalveolar lavage [BAL] and EBC) from 18 subjects, we determined that miRNA profiles of exh-EVs clustered closely to those of BAL EVs but not to those of other airway samples. When comparing the miRNA profiles of EVs purified from matched BAL and EBC samples with our three tetraspanins EV-CATCHER assay, we captured significant miRNA expression differences associated with smoking, asthma and lung tumor status of our subjects, which were also reproducibly detected in EVs selectively purified with our anti-CCSP/SFTPC EV-CATCHER assay from the same samples, but that confirmed their lung tissue origin. Our findings underscore that enriching exh-EV subpopulations from EBC allows non-invasive sampling of EVs produced by lung tissues.

Advances in the role of circulating tumor cell heterogeneity in metastatic small cell lung cancer

Small cell lung cancer (SCLC), a highly aggressive malignancy, is rapidly at an extensive stage once diagnosed and is one of the leading causes of death from malignancy. In the past decade, the treatment of SCLC has largely remained unchanged, and chemotherapy remains the cornerstone of SCLC treatment. The therapeutic value of adding immune checkpoint inhibitors to chemotherapy for SCLC is low, and only a few SCLC patients have shown a response to immune checkpoint inhibitors. Circulating tumor cells (CTCs) are tumor cells shed from solid tumor masses into the peripheral circulation and are key to tumor metastasis. Single-cell sequencing has revealed that the genetic profiles of individual CTCs are highly heterogeneous and contribute to the poor outcome and prognosis of SCLC patients. Theoretically, phenotypic analysis of CTCs may be able to predict the diagnostic significance of new potential targets for metastatic tumors. In this paper, we will discuss in depth the heterogeneity of CTCs in SCLC and the value of CTCs for the diagnosis and prognosis of SCLC and as relevant tumor markers in metastatic SCLC.

The radiological characteristics, tertiary lymphoid structures, and survival status associated with EGFR mutation in patients with subsolid nodules like stage I-II LUAD

BACKGROUND

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) recommended for the patients with subsolid nodule in early lung cancer stage is not routinely. The clinical value and impact in patients with EGFR mutation on survival outcomes is further needed to be elucidated to decide whether the application of EGFR-TKIs was appropriate in early lung adenocarcinoma (LUAD) stage appearing as subsolid nodules.

MATERIALS AND METHODS

The inclusion of patients exhibiting clinical staging of IA-IIB subsolid nodules. Clinical information, computed tomography (CT) features before surgical resection and pathological characteristics including tertiary lymphoid structures of the tumors were recorded for further exploration of correlation with EGFR mutation and prognosis.

RESULTS

Finally, 325 patients were enrolled into this study, with an average age of 56.8 ± 9.8 years. There are 173 patients (53.2%) harboring EGFR mutation. Logistic regression model analysis showed that female (OR = 1.944, p = 0.015), mix ground glass nodule (OR = 2.071, p = 0.003, bubble-like lucency (OR = 1.991, p = 0.003) were significant risk factors of EGFR mutations. Additionally, EGFR mutations were negatively correlated with TLS presence and density. Prognosis analysis showed that the presence of TLS was associated with better recurrence-free survival (RFS)(p = 0.03) while EGFR mutations were associated with worse RFS(p = 0.01). The RFS in patients with TLS was considerably excel those without TLS within EGFR wild type group(p = 0.018). Multivariate analyses confirmed that EGFR mutation was an independent prognostic predictor for RFS (HR = 3.205, p = 0.037).

CONCLUSIONS

In early-phase LUADs, subsolid nodules with EGFR mutation had specific clinical and radiological signatures. EGFR mutation was associated with worse survival outcomes and negatively correlated with TLS, which might weaken the positive impact of TLS on prognosis. Highly attention should be paid to the use of EGFR-TKI for further treatment as agents in early LUAD patients who carrying EGFR mutation.

Case report: Molecular profiling facilitates the diagnosis of a challenging case of lung cancer with choriocarcinoma features

Accurate diagnoses are crucial in determining the most effective treatment across different cancers. In challenging cases, morphology-based traditional pathology methods have important limitations, while molecular profiling can provide valuable information to guide clinical decisions. We present a 35-year female with lung cancer with choriocarcinoma features. Her disease involved the right lower lung, brain, and thoracic lymph nodes. The pathology from brain metastasis was reported as "metastatic choriocarcinoma" (a germ cell tumor) by local pathologists. She initiated carboplatin and etoposide, a regimen for choriocarcinoma. Subsequently, her case was assessed by pathologists from an academic cancer center, who gave the diagnosis of "adenocarcinoma with aberrant expression of β-hCG" and finally pathologists at our hospital, who gave the diagnosis of "poorly differentiated carcinoma with choriocarcinoma features". Genomic profiling detected a KRAS G13R mutation and transcriptomics profiling was suggestive of lung origin. The patient was treated with carboplatin/paclitaxel/ipilimumab/nivolumab followed by consolidation radiation therapy. She had no evidence of progression to date, 16 months after the initial presentation. The molecular profiling could facilitate diagnosing of challenging cancer cases. In addition, chemoimmunotherapy and local consolidation radiation therapy may provide promising therapeutic options for patients with lung cancer exhibiting choriocarcinoma features.

An immune cell map of human lung adenocarcinoma development reveals an anti-tumoral role of the Tfh-dependent tertiary lymphoid structure

The immune responses during the initiation and invasion stages of human lung adenocarcinoma (LUAD) development are largely unknown. Here, we generated a single-cell RNA sequencing map to decipher the immune dynamics during human LUAD development. We found that T follicular helper (Tfh)-like cells, germinal center B cells, and dysfunctional CD8+ T cells increase during tumor initiation/invasion and form a tertiary lymphoid structure (TLS) inside the tumor. This TLS starts with an aggregation of CD4+ T cells and the generation of CXCL13-expressing Tfh-like cells, followed by an accumulation of B cells, and then forms a CD4+ T and B cell aggregate. TLS and its associated cells are correlated with better patient survival. Inhibiting TLS formation by Tfh or B cell depletion promotes tumor growth in mouse models. The anti-tumoral effect of the Tfh-dependent TLS is mediated through interleukin-21 (IL-21)-IL-21 receptor signaling. Our study establishes an anti-tumoral role of the Tfh-dependent TLS in the development of LUAD.

A new model using deep learning to predict recurrence after surgical resection of lung adenocarcinoma

This study aimed to develop a deep learning (DL) model for predicting the recurrence risk of lung adenocarcinoma (LUAD) based on its histopathological features. Clinicopathological data and whole slide images from 164 LUAD cases were collected and used to train DL models with an ImageNet pre-trained efficientnet-b2 architecture, densenet201, and resnet152. The models were trained to classify each image patch into high-risk or low-risk groups, and the case-level result was determined by multiple instance learning with final FC layer's features from a model from all patches. Analysis of the clinicopathological and genetic characteristics of the model-based risk group was performed. For predicting recurrence, the model had an area under the curve score of 0.763 with 0.750, 0.633 and 0.680 of sensitivity, specificity, and accuracy in the test set, respectively. High-risk cases for recurrence predicted by the model (HR group) were significantly associated with shorter recurrence-free survival and a higher stage (both, p < 0.001). The HR group was associated with specific histopathological features such as poorly differentiated components, complex glandular pattern components, tumor spread through air spaces, and a higher grade. In the HR group, pleural invasion, necrosis, and lymphatic invasion were more frequent, and the size of the invasion was larger (all, p < 0.001). Several genetic mutations, including TP53 (p = 0.007) mutations, were more frequently found in the HR group. The results of stages I-II were similar to those of the general cohort. DL-based model can predict the recurrence risk of LUAD and identify the presence of the TP53 gene mutation by analyzing histopathologic features.

DIEANet: an attention model for histopathological image grading of lung adenocarcinoma based on dimensional information embedding

Efficient and rapid auxiliary diagnosis of different grades of lung adenocarcinoma is conducive to helping doctors accelerate individualized diagnosis and treatment processes, thus improving patient prognosis. Currently, there is often a problem of large intra-class differences and small inter-class differences between pathological images of lung adenocarcinoma tissues under different grades. If attention mechanisms such as Coordinate Attention (CA) are directly used for lung adenocarcinoma grading tasks, it is prone to excessive compression of feature information and overlooking the issue of information dependency within the same dimension. Therefore, we propose a Dimension Information Embedding Attention Network (DIEANet) for the task of lung adenocarcinoma grading. Specifically, we combine different pooling methods to automatically select local regions of key growth patterns such as lung adenocarcinoma cells, enhancing the model's focus on local information. Additionally, we employ an interactive fusion approach to concentrate feature information within the same dimension and across dimensions, thereby improving model performance. Extensive experiments have shown that under the condition of maintaining equal computational expenses, the accuracy of DIEANet with ResNet34 as the backbone reaches 88.19%, with an AUC of 96.61%, MCC of 81.71%, and Kappa of 81.16%. Compared to seven other attention mechanisms, it achieves state-of-the-art objective metrics. Additionally, it aligns more closely with the visual attention of pathology experts under subjective visual assessment.

Thoracic SMARCA4-deficient undifferentiated tumor: current knowledge and future perspectives

Thoracic SMARCA4-deficient undifferentiated tumor is a newly recognized disease entity characterized as a high-grade malignant neoplasm with an undifferentiated or rhabdoid phenotype. The tumor was initially identified as a subtype of thoracic sarcoma with SMARCA4 loss, but further investigation resulted in its classification as a subtype of epithelial malignancies in the current World Health Organization classification. SMARCA4-deficient undifferentiated tumor is highly aggressive and has a poor prognosis. Because of its rarity, an optimal treatment strategy has not yet been identified. In this review, we summarize the literature on SMARCA4-deficient undifferentiated tumor in terms of its clinical characteristics, diagnosis, treatment strategy and future perspectives.

Lung adenocarcinoma: selection of surgical approaches in solid adenocarcinoma from the viewpoint of clinicopathologic features and tumor microenvironmental heterogeneity

Introduction

Solid adenocarcinoma represents a notably aggressive subtype of lung adenocarcinoma. Amidst the prevailing inclination towards conservative surgical interventions for diminutive lung cancer lesions, the critical evaluation of this subtype's malignancy and heterogeneity stands as imperative for the formulation of surgical approaches and the prognostication of long-term patient survival.

Methods

A retrospective dataset, encompassing 2406 instances of non-solid adenocarcinoma (comprising lepidic, acinar, and papillary adenocarcinoma) and 326 instances of solid adenocarcinoma, was analyzed to ascertain the risk factors concomitant with diverse histological variants of lung adenocarcinoma. Concurrently, RNA-sequencing data delineating explicit pathological subtypes were extracted from 261 cases in the TCGA database and 188 cases in the OncoSG database. This data served to illuminate the heterogeneity across lung adenocarcinoma (LUAD) specimens characterized by differential histological features.

Results

Solid adenocarcinoma is associated with an elevated incidence of pleural invasion, microscopic vessel invasion, and lymph node metastasis, relative to other subtypes of lung adenocarcinoma. Furthermore, the tumor microenvironment (TME) in solid pattern adenocarcinoma displayed suboptimal oxygenation and acidic conditions, concomitant with augmented tumor cell proliferation and invasion capacities. Energy and metabolic activities were significantly upregulated in tumor cells of the solid pattern subtype. This subtype manifested robust immune tolerance and capabilities for immune evasion.

Conclusion

This present investigation identifies multiple potential metrics for evaluating the invasive propensity, metastatic likelihood, and immune resistance of solid pattern adenocarcinoma. These insights may prove instrumental in devising surgical interventions that are tailored to patients diagnosed with disparate histological subtypes of LUAD, thereby offering valuable directional guidance.

Lung Cancer in Women-Sociodemographic, Clinical and Psychological Characteristics with Comparison to Men

(1) Background: There is a difference in the course of lung cancer between women and men. Therefore, there is a need to evaluate various factors in the patient population treated in daily practice. The purpose of this study was to analyze the clinical, sociodemographic and psychological aspects of female lung cancer. To better express the results, we compared women and men. (2) Methods: Consecutive patients with a history of lung cancer treatment admitted to the outpatient oncology clinic (Department of Lung Cancer and Chest Tumours, Maria Skłodowska-Curie National Research Institute of Oncology in Warsaw) and the Department of Internal Medicine, Pulmonary Diseases and Allergy, were enrolled. We conducted analyses of the clinical, psychological and socioeconomic factors of women with lung cancer treated in everyday practice, including a comparison with a group of men. Demographic data were collected from a self-administered questionnaire. We used the Perceived Stress Scale (PSS-10) and Acceptance of Illness Scale (AIS) questionnaires for psychological evaluation. (3) Results: A total of 100 patients with confirmed primary lung cancer with a history of treatment were enrolled in the study (50 women and 50 men). We found a significantly shorter history of smoking in the group of women; at the same time, there were no differences in the reported incidence of COPD. Despite comparable results to men on the psychological questionnaire (PSS-10, AIS), women more often reported a willingness to be supported by a psychologist or psychiatrist due to lung cancer. However, they did not decide to consult them more often than men. Immunotherapy was a significantly less frequently used method in women. (4) Conclusions: We should be more active in finding out the willingness to consult a psychologist or psychiatrist among women with lung cancer. The diagnosis of COPD should be considered more often among women due to the lack of differences in the reported incidence of COPD between men and women, despite a clear contrast in the number of pack-years.

Prognostic implications of CT-defined ground glass opacity in clinical stage I-IIA grade 3 invasive non-mucinous pulmonary adenocarcinoma

AIM

To investigate the prognostic impact of computed tomography (CT)-defined ground glass opacity (GGO) in patients with clinical stage I-IIA grade 3 invasive non-mucinous pulmonary adenocarcinoma (INPA).

MATERIALS AND METHODS

The present study retrospectively enrolled 187 patients diagnosed with stage I-IIA grade 3 INPA. Their clinicopathological, radiological, and genetic information was evaluated systematically, and a 5-year follow-up was conducted to monitor disease recurrence and mortality. Patients were stratified based on the presence of a GGO component, and the Cox proportional hazard model was employed to assess the influence of clinicopathological factors and genetic variables on tumour outcomes. Recurrence-free survival (RFS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared using the log-rank test.

RESULTS

Significant differences were observed in both OS and RFS based on the presence of a GGO component. The group with GGO exhibited superior OS (p=0.002) and RFS (p=0.029). Multivariate analysis revealed that the presence of a GGO component (hazard ratio [HR] = 0.412, 95% confidence interval [CI]: 0.177-0.959, p=0.040), clinical T2 stage (HR=2.473, 95% CI: 1.498-4.083, p<0.001), pathological N2 stage (HR=3.049, 95% CI: 1.800-5.167, p<0.001), and mixed high-grade patterns (HR=2.392, 95% CI: 1.418-4.036, p=0.001) were predictors of RFS.

CONCLUSION

The presence of a GGO component is strongly associated with a favourable prognosis in grade 3 INPA.