The 2015 World Health Organization Classification of Lung Tumors: Impact of Genetic, Clinical and Radiologic Advances Since the 2004 Classification. J Thorac Oncol. 2015;10:1243-1260. [PMID: 26291008 DOI: 10.1097/jto.0000000000000630]

Pulmonary NUT carcinoma, an elusive and refractory entity, shows transient response to chemotherapeutics and PD-1 inhibitor: a case report and literature review

Nuclear protein of the testis (NUT) carcinoma (NC) is a rare but highly aggressive disease, characterized by drug resistance and poor prognosis. This report describes the case of a 32-year-old male patient diagnosed to have pulmonary NC; the tumor exhibited positive immunohistochemical staining of NUT and showed rearrangement of BRD4::NUT midline carcinoma family member 1 (NUTM1). After two treatment cycles of chemotherapy (etoposide plus carboplatin) combined with the PD-1 inhibitor sintilimab, the thoracic lesion of the patient disappeared, resulting in a partial response. When the patient's disease progressed even after the targeted therapy with a bromodomain and extra-terminal motif (BET) inhibitor, sintilimab was readministered in combination with platinum-based chemotherapy. However, the disease rapidly progressed after only one treatment cycle. Notably, the disease showed de novo drug resistance to the combination of chemotherapy with the histone deacetylase inhibitor. Although the patient's NC initially responded well to the combination of the PD-1 inhibitor and chemotherapy, the response was transient. These findings suggest that pulmonary NC is a highly malignant thoracic carcinoma, with no durable response and survival benefits from treatment with chemotherapeutics or immune checkpoint inhibitors.

Prediction of tumor spread through air spaces with an automatic segmentation deep learning model in peripheral stage I lung adenocarcinoma

BACKGROUND

To evaluate the clinical applicability of deep learning (DL) models based on automatic segmentation in preoperatively predicting tumor spread through air spaces (STAS) in peripheral stage I lung adenocarcinoma (LUAD).

METHODS

This retrospective study analyzed data from patients who underwent surgical treatment for lung tumors from January 2022 to December 2023. An external validation set was introduced to assess the model's generalizability. The study utilized conventional radiomic features and DL models for comparison. ROI segmentation was performed using the VNet architecture, and DL models were developed with transfer learning and optimization techniques. We assessed the diagnostic accuracy of our models via calibration curves, decision curve analysis, and ROC curves.

RESULTS

The DL model based on automatic segmentation achieved an AUC of 0.880 (95% CI 0.780-0.979), outperforming the conventional radiomics model with an AUC of 0.833 (95% CI 0.707-0.960). The DL model demonstrated superior performance in both internal validation and external testing cohorts. Calibration curves, decision curve analysis, and ROC curves confirmed the enhanced diagnostic accuracy and clinical utility of the DL approach.

CONCLUSION

The DL model based on automatic segmentation technology shows significant promise in preoperatively predicting STAS in peripheral stage I LUAD, surpassing traditional radiomics models in diagnostic accuracy and clinical applicability. Clinical trial number The clinical trial was registered on April 22, 2024, with the registration number researchregistry10213 ( www.researchregistry.com ).

PMILACG Model: A Predictive Model for Identifying Invasiveness of Lung Adenocarcinoma Based on High-Resolution CT-Determined Ground Glass Nodule Features

The morphology of ground-glass nodule (GGN) under high-resolution computed tomography (HRCT) has been suggested to indicate different histological subtypes of lung adenocarcinoma (LUAD); however, existing studies only include the limited number of GGN characteristics, which lacks a systematic model for predicting invasive LUAD. This study aimed to construct a predictive model based on GGN features under HRCT for LUAD. A total of 1,189 surgical LUAD patients were enrolled, and their GGN-related features were assessed by 2 individual radiologists. The pathological diagnosis of the invasive LUAD was established by pathologic examination following surgery (including 1,073 invasive and 526 non-invasive LUAD). After adjustment by multivariate logistic regression, GGN diameter (OR = 1.382, 95% CI: 1.300-1.469), mean CT attenuation (OR = 1.007, 95% CI: 1.006-1.009), heterogeneous uniformity of density (OR = 2.151, 95% CI: 1.587-2.915), not defined nodule-lung interface (OR = 1.915, 95% CI: 1.384-2.651), GGN with spiculation (OR = 2.097, 95% CI: 1.519-2.896), type I (OR = 1.678, 95% CI: 1.216-2.371), and type II (OR = 3.577, 95% CI: 1.153-11.097) vessel changes were independent risk factors for invasive LUAD. In addition, a predictive model integrating these six independent GGN features was established (named as invasion of lung adenocarcinoma by GGN features (ILAG)), and receiver-operating characteristic curve illustrated that the ILAG model presented good predictive value for invasive LUAD (AUC: 0.905, 95% CI: 0.890-0.919). In conclusion, The ILAG predictive model, which integrates imaging features of GGN via HRCT, including diameter, mean CT attenuation, heterogeneous uniformity of density, not defined nodule-lung interface, GGN with spiculation, type I, and type II vessel changes, shows great potential for early estimation of LUAD invasiveness.

Frontline pemetrexed and cisplatin based-chemotherapy combined with NRT promoted the antitumor in a mouse model of lung carcinoma

The efficacy of neoantigen-reactive T cells (NRT) therapy in solid tumors, encompassing aspects such as infiltration, recognition, cytotoxicity, and enduring persistence, is notably influenced by the immunological microenvironment. This study endeavors to investigate whether the co-administration of pemetrexed and cisplatin augments the therapeutic efficacy of NRT therapy in lung cancer. Neoantigens were predicted using a comprehensive analysis of mutation data from Lewis lung carcinoma cells and mouse tail tissues. The immunogenicity of NRT cells was assessed through flow cytometry and IFN-γ ELISpot assays. A mouse model of NSCLC was used to investigate the anti-tumor effects of NRT combined with chemotherapy. The combination of NRT cells and chemotherapy significantly inhibited tumor growth in a mouse model, increased CD3+/CD137+ T cells to promote IFN-γ secretion from NRT cells, and up-regulated the levels of inflammatory cytokine proteins including IFN-γ, TNF, IL-6 and IL-10. Immunofluorescence analysis confirmed increased T-cell infiltration in tumor tissues without adverse effects on vital organs. In addition, transcriptome analyses indicated that the tumor microenvironment was altered to favor M1-like macrophages with an increased M1/M2 ratio, creating a pro-inflammatory environment. The integration of NRT with frontline chemotherapy for lung cancer could yield profoundly ideal therapeutic outcomes.

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

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

Immunotherapy-extended survival in patients with recurrent pulmonary pleomorphic carcinoma following surgery

OBJECTIVE

Pulmonary pleomorphic carcinoma is a relatively rare and aggressive subtype of non-small cell lung cancer (NSCLC), with a poor prognosis and early recurrence, and is resistant to conventional therapies. This study investigated the efficacy of immune checkpoint inhibitors (ICIs) in improving the survival outcomes of patients with pulmonary pleomorphic carcinoma with postoperative recurrence.

METHODS

We conducted a retrospective analysis of 71 patients with pulmonary pleomorphic carcinoma who underwent pulmonary resection at Tokyo Medical University Hospital between 2008 and 2022. Clinicopathological data, programmed cell death ligand 1 (PD-L1) expression, and postoperative recurrence treatment outcomes were reviewed.

RESULTS

Among the 71 patients with pulmonary pleomorphic carcinoma, the 5-year overall survival (OS) rate was 48.6 %, and high PD-L1 expression (28-8 clone) was observed in 87 %. The median recurrence-free survival (RFS) was 19.4 months, and postoperative recurrence occurred in 38 patients (54 %). Treatment after recurrence was administered to 24 patients (63 %), and immunotherapy was administered to 10 patients (26 %). In patients treated with ICI, the overall response rate (ORR) was significantly higher (50 %) compared to those treated without ICI (7 %). The median survival time after relapse was notably longer in the ICI-treated group (83.9 months), compared to the non-ICI group (10.1 months).

CONCLUSION

ICIs significantly improve survival outcomes in patients with recurrent pulmonary pleomorphic carcinoma, particularly in those with high PD-L1 expression. Early postoperative recurrence and rapid progression have been observed, making therapeutic intervention challenging. Close follow-up is crucial, and ICIs become a pivotal treatment option for managing this highly aggressive cancer.

Tumour spread through air spaces is a determiner for treatment of clinical stage I non-small cell lung Cancer: Thoracoscopic segmentectomy vs lobectomy

BACKGROUND

The choice of surgical procedure for early-stage non-small cell lung cancer (NSCLC) with tumour spread through air spaces (STAS) remain debated. This study aimed to analyse the prognostic influence of STAS on thoracoscopic segmentectomy compared to lobectomy for clinical stage I NSCLC.

METHODS

This retrospective study included prospectively collected data of consecutive patients who underwent thoracoscopic segmentectomy or lobectomy for clinical stage I NSCLC from September 2020 to September 2023 at a high-volume hospital. We assessed overall survival (OS) and recurrence-free survival (RFS) using Kaplan-Meier estimator with log-rank test. LASSO-Cox and Cox regression analyses identified independent factors for survivals of STAS presence.

RESULTS

Among the 785 patients in the study, 151 (19.2 %) had STAS-positive NSCLC. No significant difference was observed in OS and RFS between patients with the presence and absence of STAS, nor between those undergoing thoracoscopic segmentectomy and lobectomy for NSCLC in the absence of STAS. Whereas worse survivals were found in segmentectomy for patients with STAS when compared to lobectomy (3-year OS: 58.4 % vs 89.0 %, P < 0.001; 3-year RFS: 69.8 % vs 82.7 %, P < 0.001). On multivariable analysis, segmentectomy (vs. lobectomy) and increased maximum standardized uptake value in positron emission tomography were independent prognostic factors of OS (hazard ratio [HR] 5.81, P = 0.010; HR 1.12, P = 0.022) and RFS (HR 5.78, P = 0.004; HR 1.10, P = 0.025) among patients with STAS.

CONCLUSIONS

In this study, segmentectomy for clinical stage I NSCLC with STAS had inferior RFS and OS when compared to lobectomy.

Characteristics of genomic alterations and heavy metals in hypertensive patients with non‑small cell lung cancer

Both lung cancer and cardiovascular disease (CVD) are prevalent diseases that contribute to global mortality rates. Although individuals with CVD may face an elevated risk of cancer based on the presence of shared risk factors (such as tobacco smoking and excessive body weight), the roles of somatic mutations and heavy metal distributions remain unknown. The present study aimed to explore the differences in somatic mutations and heavy metal distributions between hypertensive patients and non-hypertensive patients in a cohort of patients with non-small cell lung cancer (NSCLC). Tumor tissue samples from 64 patients were analyzed using a next-generation sequencing panel consisting of 82 tumor-related genes through hybrid capture. Serum samples were also analyzed to determine the levels of 18 heavy metals using inductively-coupled plasma mass spectrometry. Among the 16 hypertensive patients, all patients (16/16; 100.00%) harbored 47 somatic mutations in 14 mutant genes, whereas 45 patients without hypertension (45/48; 93.75%) harbored 113 somatic mutations across 26 mutant genes (no mutations were detected in the remaining 3 patients). Among the 32 identified mutant genes in these two groups, FBXW7, CBR3, CDKN2A, HRAS, SMO and UGT1A1 were exclusively observed in patients with hypertension, while 18 mutant genes were only observed in patients without hypertension. No significant mutually exclusive interactions were found in hypertensive patients, but mutually exclusive interactions were observed between EGFR and STK11 (P=0.0240) and between STK11 and KRAS (P=0.0169) in non-hypertensive patients. 'Non-small cell lung cancer' was the top Kyoto Encyclopedia of Genes and Genomes pathway in hypertensive patients, whereas 'central carbon metabolism in cancer' was the top pathway in patients without hypertension. Moreover, the proportions of altered key signaling pathways and biological function categories shared between these two groups were 54.37% (56/103) and 21.62% (8/37), respectively. Furthermore, the levels of chromium (Cr) in the serum of hypertensive patients were notably elevated compared with those in patients without hypertension. In addition, significant negative correlations were observed between Cr and CEA, between CYFRA21-1 and Zn, and between NSE and As in hypertensive patients but not in non-hypertensive patients, indicating differing interactive profiles among the traditional serum biomarkers and heavy metals between these two patient groups. In summary, there were differences in genomic alterations, somatic interactions and the serum levels of Cr between patients with NSCLC with hypertension and patients with NSCLC without hypertension. Furthermore, patients with hypertension exhibited significant negative correlations between Cr and CEA, between CYFRA21-1 and Zn, and between NSE and As, suggesting that heavy metals may contribute to the occurrence of NSCLC with different hypertensive status.

Deceptive Pseudotuberculous Presentation of a Pulmonary Lepidic Adenocarcinoma

Misleading presentations of lepidic adenocarcinomas (ADC) often lead to diagnostic delays, potentially reducing the chances of curative treatment. We report a case of mucinous lepidic ADC that mimicked pulmonary tuberculosis and was diagnosed at a late stage. The tumor showed no epidermal growth factor receptor (EGFR) expression or anaplastic lymphoma kinase (ALK) rearrangement and was characterized by bilateral pulmonary involvement without distant metastases. Through this case, the authors emphasize the need to consider lepidic ADC in cases of chronic pulmonary consolidation, despite atypical radio-clinical presentations that may be encountered in routine practice.

Comparison of 2D and 3D radiomics features with conventional features based on contrast-enhanced CT images for preoperative prediction the risk of thymic epithelial tumors

BACKGROUND

This study aimed to develop and validate 2-Dimensional (2D) and 3-Dimensional (3D) radiomics signatures based on contrast-enhanced computed tomography (CECT) images for preoperative prediction of the thymic epithelial tumors (TETs) risk and compare the predictive performance with conventional CT features.

PATIENTS AND METHODS

149 TET patients were retrospectively enrolled from January 2016 to December 2018, and divided into high-risk group (B2/B3/TCs, n = 103) and low-risk group (A/AB/B1, n = 46). All patients were randomly assigned into the training (n = 104) and testing (n = 45) set. 14 conventional CT features were collected, and 396 radiomic features were extracted from 2D and 3D CECT images, respectively. Three models including conventional, 2D radiomics and 3D radiomics model were established using multivariate logistic regression analysis. The discriminative performances of the models were demonstrated by receiver operating characteristic (ROC) curves.

RESULTS

In the conventional model, area under the curves (AUCs) in the training and validation sets were 0.863 and 0.853, sensitivity was 78% and 55%, and specificity was 88% and 100%, respectively. The 2D model yielded AUCs of 0.854 and 0.834, sensitivity of 86% and 77%, and specificity of 72% and 86% in the training and validation sets. The 3D model revealed AUC of 0.902 and 0.906, sensitivity of 75% and 68%, and specificity of 94% and 100% in the training and validation sets.

CONCLUSIONS

Radiomics signatures based on 3D images could distinguish high-risk from low-risk TETs and provide complementary diagnostic information.

Proposal of real-world solutions for the implementation of predictive biomarker testing in patients with operable non-small cell lung cancer

The implementation of biomarker testing for targeted therapies and immune checkpoint inhibitors is a cornerstone in the management of metastatic and locally advanced non-small cell lung cancer (NSCLC), playing a pivotal role in guiding treatment decisions and patient care. The emergence of precision medicine in the realm of operable NSCLC has been marked by the recent approvals of osimertinib, atezolizumab, nivolumab, pembrolizumab and alectinib for early-stage disease, signifying a shift towards more tailored therapeutic strategies. Concurrently, the landscape of this disease is rapidly evolving, with several further pending approvals and numerous clinical trials in progress. To harness the benefits of these innovative neo-adjuvant and adjuvant therapies, the integration of predictive biomarker testing into standard clinical protocols is imperative for patients with operable NSCLC. A multidisciplinary international consortium has identified three primary obstacles impeding the effective testing of patients with operable NSCLC. These challenges encompass the limited number of test requests by physicians, the inadequacy of tissue samples for comprehensive testing, and the prevalence of cost-reduction measures leading to suboptimal testing practices. This review delineates the aforementioned challenges and proposed solutions, and strategic recommendations aimed at enhancing the testing process. By addressing these issues, we strive to optimize patient outcomes in operable NSCLC, ensuring that individuals receive the most appropriate and effective care based on their unique disease profile.

ABO-Blood Group Associates With Survival Outcomes in Patients With Metastatic Non-Small Cell Lung Cancer Treated With Pembrolizumab Monotherapy

PURPOSE

In patients with metastatic non-small cell lung cancer (NSCLC) with high programmed death-ligand 1 (PD-L1) expression, there is still a lack of biomarkers to identify patients with maximum benefit from first-line treatment with checkpoint inhibitor therapy (CIT) alone. This work examines the impact of different ABO blood groups (BG) on the response to CIT monotherapy.

METHODS

Retrospective analysis of patients with stage IV NSCLC and high PD-L1 expression (tumor proportional score/TPS ≥ 50%), receiving first-line therapy with pembrolizumab alone or in combination with chemotherapy at the West German Cancer Center from 2017 to 2022. Study endpoints were overall survival (OS) and progression-free survival (PFS).

RESULTS

Eighty-two patients were included in the analysis. Twenty-two patients (27%) received first-line therapy with pembrolizumab alone (monoimmunotherapy cohort/MIC), of which seven patients (32%) had BGO. Sixty patients (73%) were treated with pembrolizumab combined with platinum-based chemotherapy (chemoimmunotherapy cohort/CIC), of which 38 (63%) had BGO. In MIC, younger age and BGO were independent predictors of favorable OS (BGO vs. other ABO-BG: HR 0.22, 95% CI: 0.1-0.9; p = 0.037; median OS 62 versus 19 months) and PFS (BGO vs. other ABO-BG: HR 0.21, 95% CI: 0.1-0.8; p = 0.024; median PFS 39 vs. 4 months). There was no significant impact of ABO-BG in patients treated with CIC. In support, a historical control group treated with chemotherapy alone also showed no prognostic impact of the ABO-BG.

CONCLUSION

BGO associates with favorable survival in patients with NSCLC receiving pembrolizumab monotherapy, but not in patients with chemo-immunotherapy or chemotherapy. Further validation of this promising strategy for personalized decision-making is warranted.

Anticancer drug response prediction integrating multi-omics pathway-based difference features and multiple deep learning techniques

Individualized prediction of cancer drug sensitivity is of vital importance in precision medicine. While numerous predictive methodologies for cancer drug response have been proposed, the precise prediction of an individual patient's response to drug and a thorough understanding of differences in drug responses among individuals continue to pose significant challenges. This study introduced a deep learning model PASO, which integrated transformer encoder, multi-scale convolutional networks and attention mechanisms to predict the sensitivity of cell lines to anticancer drugs, based on the omics data of cell lines and the SMILES representations of drug molecules. First, we use statistical methods to compute the differences in gene expression, gene mutation, and gene copy number variations between within and outside biological pathways, and utilized these pathway difference values as cell line features, combined with the drugs' SMILES chemical structure information as inputs to the model. Then the model integrates various deep learning technologies multi-scale convolutional networks and transformer encoder to extract the properties of drug molecules from different perspectives, while an attention network is devoted to learning complex interactions between the omics features of cell lines and the aforementioned properties of drug molecules. Finally, a multilayer perceptron (MLP) outputs the final predictions of drug response. Our model exhibits higher accuracy in predicting the sensitivity to anticancer drugs comparing with other methods proposed recently. It is found that PARP inhibitors, and Topoisomerase I inhibitors were particularly sensitive to SCLC when analyzing the drug response predictions for lung cancer cell lines. Additionally, the model is capable of highlighting biological pathways related to cancer and accurately capturing critical parts of the drug's chemical structure. We also validated the model's clinical utility using clinical data from The Cancer Genome Atlas. In summary, the PASO model suggests potential as a robust support in individualized cancer treatment. Our methods are implemented in Python and are freely available from GitHub (https://github.com/queryang/PASO).

Preoperative Maximum Standardized Uptake Value Emphasized in Explainable Machine Learning Model for Predicting the Risk of Recurrence in Resected Non-Small Cell Lung Cancer

PURPOSE

To comprehensively analyze the association between preoperative maximum standardized uptake value (SUVmax) on 18F-fluorodeoxyglucose positron emission tomography-computed tomography and postoperative recurrence in resected non-small cell lung cancer (NSCLC) using machine learning (ML) and statistical approaches.

PATIENTS AND METHODS

This retrospective study included 643 patients who had undergone NSCLC resection. ML models (random forest, gradient boosting, extreme gradient boosting, and AdaBoost) and a random survival forest model were developed to predict postoperative recurrence. Model performance was evaluated using the receiver operating characteristic (ROC) AUC and concordance index (C-index). Shapley additive explanations (SHAP) and partial dependence plots (PDPs) were used to interpret model predictions and quantify feature importance. The relationship between SUVmax and recurrence risk was evaluated by using a multivariable Cox proportional hazards model.

RESULTS

The random forest model showed the highest predictive performance (ROC AUC, 0.90; 95% CI, 0.86 to 0.97). The SHAP analysis identified SUVmax as an important predictor. The PDP analysis showed a nonlinear relationship between SUVmax and recurrence risk, with a sharp increase at SUVmax 2-5. The random survival forest model achieved a C-index of 0.82. A permutation importance analysis identified SUVmax as the most important feature. In the Cox model, increased SUVmax was associated with a higher risk of recurrence (adjusted hazard ratio, 1.03 [95% CI, 1.00 to 1.06]).

CONCLUSION

Preoperative SUVmax showed significant predictive value for postoperative recurrence after NSCLC resection. The nonlinear relationship between SUVmax and recurrence risk, with a sharp increase at relatively low SUVmax values, suggests its potential as a sensitive biomarker for early identification of high-risk patients. This may contribute to more precise assessments of the risk of recurrence and personalized treatment strategies for NSCLC.

Loss of TNFRSF21 induces cisplatin sensitivity in lung adenocarcinoma

Background

Despite the identification of numerous therapeutic targets in lung cancer, achieving significant efficacy has been challenging. TNFRSF21 plays an important role in various cancers. We investigated the function of TNFRSF21 in lung adenocarcinoma (LUAD).

Methods

The prognostic value of TNFRSF21 expression in lung cancer was evaluated by the GEPIA and Kaplan-Meier Plotter databases. Lung cancer cell viability was assessed by the CCK8 assay. TNFRSF21 expression patterns in lung cancer tissues and cells were examined using RT-PCR assay. Tumor sphere growth was evaluated through tumor sphere formation assays. MtROS contents in lung cancer cells were observed through MitoSOX fluorescent assays.

Result

TNFRSF21 was up-regulated in LUAD patients. TNFRSF21 induction was particularly notable in LUAD, especially in cancerous cells (A549, H1299, H460, and SPC-A1), compared to BEAS-2B cells. Additionally, TNFRSF21 was increased in cisplatin (DDP)-resistant LUAD cells. Loss of TNFRSF21 significantly inhibited LUAD cell growth. It was observed that forced expression of TNFRSF21 contributed to tumor cell proliferation and DDP resistance. The production of ROS was found to participate in the inhibitory effects on lung cancer stem cells (CSCs), with decreased TNFRSF21 restraining ROS contents. Collectively, these findings reveal that the downregulation of TNFRSF21 promotes ROS contents to restrain the lung CSC-like characteristics via modulation of CD44 and CD133.

Conclusions

In conclusion, TNFRSF21 may act as a novel target for lung cancer chemotherapy, particularly for eradicating lung CSCs.

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

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

Spread through air spaces may predict early progression after salvage surgery for EGFR-mutant advanced lung adenocarcinoma treated with targeted therapy

OBJECTIVE

Salvage resection for residual lung cancer harboring epidermal growth factor receptor (EGFR) mutations following EGFR-tyrosine kinase inhibitor (TKI) treatment is gaining traction for its survival benefits. However, the impact of pathological factors on survival remains unclear.

METHODS

Between 2013 and 2023, we retrospectively reviewed 34 patients with advanced lung adenocarcinoma who received EGFR-TKI therapy. After a median TKI treatment duration of 9.1 months, all patients demonstrated either partial response (n = 27) or stable disease (n = 7) before salvage surgery. Demographic, pathological outcomes, progression-free survival (PFS), and overall survival (OS) were analyzed.

RESULTS

Among the 34 patients, six (17.6%) achieved a pathological complete response (pCR) and nine (26.5%) had a major pathological response (MPR). Additionally, 11 patients (32.4%) exhibited spread through air spaces (STAS), and lymphovascular invasion (LVI) was observed in nine patients (26.5%). The 3-year PFS and OS rates were 55.8% and 60.5%, respectively. No significant differences in PFS or OS were observed regarding mutation type, TKI generation, pCR, MPR, or LVI. However, Kaplan-Meier analysis revealed that STAS was associated with shorter PFS compared to non-STAS cases (p = 0.01). In multivariate analysis, STAS was identified as an independent prognostic factor for PFS (hazard ratio: 2.83, 95% CI: 1.35-28.54, p = 0.02). No significant prognosticators were found for OS in univariate or multivariate analyses.

CONCLUSION

While salvage surgery following TKI treatment is feasible and prolongs survival by removing residual primary tumor with potential TKI resistance, STAS may contribute to a higher risk of early progression. This finding warrants further investigation and tailored treatment strategies.

A PET/CT-based 3D deep learning model for predicting spread through air spaces in stage I lung adenocarcinoma

PURPOSE

This study evaluates a three-dimensional (3D) deep learning (DL) model based on fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for predicting the preoperative status of spread through air spaces (STAS) in patients with clinical stage I lung adenocarcinoma (LUAD).

METHODS

A retrospective analysis of 162 patients with stage I LUAD was conducted, splitting data into training and test sets (4:1). Six 3D DL models were developed, and the top-performing PET and CT models (ResNet50) were fused for optimal prediction. The model's clinical utility was assessed through a two-stage reader study.

RESULTS

The fused PET/CT model achieved an area under the curve (AUC) of 0.956 (95% CI 0.9230-0.9881) in the training set and 0.889 (95% CI 0.7624-1.0000) in the test set. Compared to three physicians, the model demonstrated superior sensitivity and specificity. After the artificial intelligence (AI) assistance's participation, the diagnostic accuracy of the physicians improved during their subsequent reading session.

CONCLUSION

Our DL model demonstrates potential as a resource to aid physicians in predicting STAS status and preoperative treatment planning for stage I LUAD, though prospective validation is required.

Distinguishing MPLCs from IPMs using NGS-based molecular algorithms and histological assessment: A systematic review and validation study

Distinguishing between multiple primary lung cancers and intrapulmonary metastases is crucial for staging, therapeutic planning, and prognosis. Traditional histological assessment provides a foundation for diagnosis, which can be limited when tumors showed identical or similar histological types. This systematic review and independent validation study aimed to evaluate the performance of next-generation sequencing (NGS)-based molecular algorithms alongside histological methods for the classification of multiple lung adenocarcinomas (MLAs). We conducted a literature search to identify relevant studies and selected algorithms for validation using a cohort of patients with MLAs. Our analysis included 27 patients with MLAs and compared histological assessment using Martini and Melamed criteria and comprehensive histologic assessment combined with a low-grade lepidic component (CHA & lepidic) with NGS data. We found a high consistency between CHA & lepidic and NGS-based diagnoses, although some discrepancies remained, particularly in cases with no somatic mutations or distant metastases. NGS-based molecular algorithms offer a high degree of accuracy in determining the origin of MLAs, supporting or challenging histological diagnoses. However, histological methods remain valuable, especially when NGS data are inconclusive. This study underscores the complementary nature of histology and molecular diagnostics in the precise classification of MLAs.

Oncologic Outcomes of Thoracoscopic Segmentectomy in Patients with High-Grade Adenocarcinoma Pattern

BACKGROUND

Lung adenocarcinoma exhibits heterogeneity among different histological subtypes, with solid and micropapillary subgroups (classified as high-grade) associated with worse prognosis. The aim of this retrospective study was to investigate the impact of high-grade adenocarcinoma on survival in patients undergoing intentional thoracoscopic segmentectomy.

METHODS

Patients who underwent segmentectomy for clinical-stage IA non-small-cell lung cancer between 2016 and 2023 were reviewed. The adenocarcinoma population was divided and compared based on the presence of high-grade adenocarcinoma >20%, based on the 2021 WHO classification. Survival probabilities were estimated using the Kaplan-Meier method and log-rank test. The Cox proportional hazard regression model was used to test the association between survival and covariates.

RESULTS

The adenocarcinoma population included 216 patients, with high-grade adenocarcinoma >20% in 47 (21.7%). A consolidation-to-tumor ratio >0.8 was more frequent in the high-grade adenocarcinoma population. Survival analyses showed that overall (5-year OS rate 57% vs. 90%, p < 0.01), cancer-specific (5-year CSS rate 66% vs. 91%, p < 0.01) and disease-free survival (5-year DFS rate 53% vs. 75%, p < 0.01) were significantly worse in patients with high-grade adenocarcinoma. No significant differences in overall and disease-free survival were observed when compared to a contemporary cohort of lobectomy patients. Recurrence and high-grade pattern (HR 3.26, 95%CI 1.4-7.6, p < 0.01) were significant risk factors for reduced overall survival, whereas high-grade adenocarcinoma >20% (HR 2.43, 95%CI 1.25-4.71, p < 0.01) and a consolidation-to-tumor ratio >0.8 were risk factors for reduced disease-free survival.

CONCLUSIONS

The prognosis of high-grade adenocarcinoma is sub-optimal even in radically treated early-stage patients, and close monitoring and a complete bio-molecular assessment should be advisable in light of a multimodal adjuvant approach. However, the different subtypes of adenocarcinoma could be inserted as a staging parameter in future international staging systems.

Endogenous IL-33 inhibits apoptosis in non-small cell lung cancer cells by regulating BCL2/BAX via the ERK1/2 pathway

Lung cancer remains a leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for 85% of cases. Although targeted therapies have improved treatment outcomes, drug resistance poses a significant challenge, underscoring the need for novel therapeutic strategies. Interleukin-33 (IL-33), a member of the IL-1 superfamily, functions both as a nuclear protein and a cytokine, binding to its receptor, ST2. While IL-33 is known to promote tumour cell migration and metastasis, its role in regulating apoptosis remains incompletely understood. In this study, we focused on endogenous IL-33, employing lentiviral transfection to overexpress both the full-length and mature forms of IL-33 in lung cancer cells. We examined its effects on apoptosis in vitro and investigated the underlying molecular mechanisms. Our findings reveal that endogenous IL-33 inhibits apoptosis in lung cancer cells by modulating the expression of BCL2 and BAX via the ERK1/2 pathway in an autocrine manner. These results uncover a novel mechanism of IL-33-mediated tumour survival and provide a foundation for the development of IL-33/ST2-targeted therapies in NSCLC.

Perioperative inflammatory index differences between pulmonary squamous cell carcinoma and adenocarcinoma and their prognostic implications

Background

Perioperative inflammatory indices reflect systemic inflammatory responses and have been linked to cancer progression and prognosis. This study aims to explore the differences in perioperative inflammatory indices between lung squamous cell carcinoma (LSCC) and adenocarcinoma (LUAD) and their association with long-term outcomes.

Methods

This study included 287 lung cancer patients who underwent curative resection between June 2016 and December 2017, comprising 61 cases of LSCC and 226 cases of LUAD. Perioperative baseline information and inflammatory cell counts were collected. Patients were followed up for a median duration of 76 months, during which disease-free survival (DFS) and overall survival (OS) were recorded. Cox regression analysis was used to evaluate the prognostic significance of inflammatory factor levels.

Results

Significant differences were observed in white blood cell count and systemic inflammation response index (SIRI) between LSCC and LUAD (P < 0.05). Regression analysis identified age (OR=2.096, P=0.004), postoperative day 1 D-dimer level (OR=1.550, P<0.001), and Platelet-to-lymphocyte ratio (PLR) (OR=1.901, P=0.031) as independent risk factors for perioperative venous thromboembolism (VTE). Furthermore, open surgical approach (HR=2.437, P=0.016), tumor type (LSCC; HR=2.437, P=0.016), and PLR (HR=1.534, P=0.019) were independent risk factors for DFS.

Conclusion

Inflammatory index is key predictors of perioperative VTE and DFS in lung cancer, emphasizing their critical role in prognosis.

The potential of lazertinib and amivantamab combination therapy as a treatment strategy for uncommon EGFR-mutated NSCLC

Uncommon epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC) pose therapeutic challenge due to limited response to EGFR tyrosine kinase inhibitors (TKIs). This study presents preclinical evidence and mechanistic insights into the combination of lazertinib, a third-generation EGFR-TKI; and amivantamab, an EGFR-MET bispecific antibody, for treating NSCLC with uncommon EGFR mutations. The lazertinib-amivantamab combination demonstrates significant antitumor activity in patient-derived models with uncommon EGFR mutations either before treatment or after progressing on EGFR-TKIs. Lazertinib enhances the inhibitory capacity of amivantamab by increasing its on-target expression. Notably, the combination surpasses afatinib, a first-line treatment for uncommon EGFR mutations in NSCLC, in terms of in vivo efficacy. Promising clinical activity is also observed in two case studies of patients treated with this combination (NCT04077463). Our findings highlight the potential of the lazertinib-amivantamab combination as a therapeutic strategy for uncommon EGFR mutations, an area of unmet medical need, and support further clinical investigation.

Hybrid Approach to Classifying Histological Subtypes of Non-small Cell Lung Cancer (NSCLC): Combining Radiomics and Deep Learning Features from CT Images

This study aimed to develop a hybrid model combining radiomics and deep learning features derived from computed tomography (CT) images to classify histological subtypes of non-small cell lung cancer (NSCLC). We analyzed CT images and radiomics features from 235 patients with NSCLC, including 110 with adenocarcinoma (ADC) and 112 with squamous cell carcinoma (SCC). The dataset was split into a training set (75%) and a test set (25%). External validation was conducted using the NSCLC-Radiomics database, comprising 24 patients each with ADC and SCC. A total of 1409 radiomics and 8192 deep features underwent principal component analysis (PCA) and ℓ2,1-norm minimization for feature reduction and selection. The optimal feature sets for classification included 27 radiomics features, 20 deep features, and 55 combined features (30 deep and 25 radiomics). The average area under the receiver operating characteristic curve (AUC) for radiomics, deep, and combined features were 0.6568, 0.6689, and 0.7209, respectively, across the internal and external test sets. Corresponding average accuracies were 0.6013, 0.6376, and 0.6564. The combined model demonstrated superior performance in classifying NSCLC subtypes, achieving higher AUC and accuracy in both test datasets. These results suggest that the proposed hybrid approach could enhance the accuracy and reliability of NSCLC subtype classification.

Is CK7 a Prognostic Marker in Pulmonary LCNEC? Evidence from a Limited Cohort Study

Objectives: While the treatment of non-small-cell lung carcinoma has improved rapidly, the treatment of pulmonary large-cell neuroendocrine carcinoma (LCNEC) remains underdeveloped. The use of immunohistochemistry allows for accurate risk stratification. With our study, we investigated the outcome of patients with pulmonary LCNEC and analyzed whether CK7 correlates with long-term survival. Methods: We retrospectively collected the monocentric data of patients which underwent anatomical resection for lung cancer between January 2012 and December 2020. Patients that did not show pulmonary LCNEC or adenocarcinoma, had a positive resection margin, or underwent neoadjuvant therapy were excluded. The long-term survival rate of the LCNEC and adenocarcinoma groups were compared before and after propensity score matching. Furthermore, we performed survival analyses for a subgroup of LCNEC distinguished by CK7 expression, followed by Cox regression analyses. Results: A total of 466 patients were integrated for further analysis. The mean age was 65.3 ± 9.6 years. There were no significant differences between both groups regarding age, gender, or comorbidities. In terms of the UICC stage, the groups were equally distributed. Mean survival in the LCNEC group was significantly worse than in the adenocarcinoma group (LCENC: 36.4 ± 7.5 months; adenocarcinoma: 80.7 ± 8.1 months; p-value = 0.001). The mean survival rate was 19.23 ± 4.8 months in the CK7 expression group and 57.01 ± 8.5 months in the group without expression, which reached statistical significance (p-value = 0.019). Conclusions: Our study suggests that pulmonary LCNEC has a significantly worse prognosis than pulmonary adenocarcinoma. CK7 expression seems to be correlated with a worse outcome for the long-term survival rate of patients suffering from highly malignant pulmonary LCNEC.

Deciphering the intratumoral histologic heterogeneity of lung adenocarcinoma using radiomics

OBJECTIVE

To discern highly aggressive intratumoral areas among lung adenocarcinoma (LUAD) and its impact on occult nodal metastases and the recurrence rate with radiomic analysis.

METHODS

This prospective dual-institution study analyzed clinical information and high-resolution preoperative CT of 528 patients from institution A and 249 patients from institution B. We extracted radiomic features and performed pathologic evaluations for resected tumors, based on the 2020 International Association for the Study of Lung Cancer (IASLC) classification. Prediction models were developed to discern micropapillary and solid patterns within LUAD using clinical and radiomic features from institution A through logistic analysis.

RESULTS

Six selected CT radiomic features, sex, CTR (consolidation-to-tumor ratio), and solid diameter were selected to develop the prediction models. A composite model of radiomic and clinical characteristics outperformed radiomics-only and clinical-only models (AUC, 95% CI; the composite model: 0.84 [0.81-0.87]; the radiomics model: 0.82 [0.78-0.87]; the clinical model: 0.80 [0.76-0.83]) in institution A. External validation was performed with institution B cohort, showing even better results (AUC, 95% CI; the composite model: 0.91 [0.87-0.94]; the radiomics model: 0.89 [0.84-0.94]; the clinical model: 0.88 [0.84-0.92]).

CONCLUSIONS

Our study underscores the potential of radiomics to preoperatively predict aggressive histologic patterns in LUAD, enabling precise treatment planning and prognosis estimation.

KEY POINTS

Question Can any adjuvant methods address the limitations of core needle biopsies, which are invasive and may not capture the full heterogeneity of lung adenocarcinoma? Findings In a prospective study of 528 patients with cT1N0M0 lung adenocarcinoma, a composite model of clinical characteristics, conventional CT findings, and radiomics features predicted high-grade cancers. Clinical relevance Preoperative non-invasive diagnosis of histologically high-grade tumors using radiomics analysis offers crucial information for the treatment of lung adenocarcinoma with respect to occult lymph node metastasis and recurrence rate.

Exploring RNA cargo in extracellular vesicles for pleural mesothelioma detection

BACKGROUND

Pleural Mesothelioma (PM) is a highly aggressive cancer, for which effective early detection remains a challenge due to limited screening options and low sensitivity of biomarkers discovered so far. While extracellular vesicles (EVs) have emerged as promising candidates for blood-based biomarkers, their role in PM has not been studied yet. In this study, we characterized the transcriptomic profile of EVs secreted by PM primary cells and explored their potential as a biomarker source for PM detection.

METHODS

We collected cell culture supernatant from early-passage PM cell cultures derived from the pleural effusion of 4 PM patients. EVs were isolated from the supernatant using Qiagen exoEasy Maxi kit. RNA isolation from EVs was done using the mirVana PARIS kit. Finally, single-end RNA sequencing was done with Illumina Novaseq 6000.

RESULTS

We identified a range of RNA species expressed in EVs secreted by PM cells, including protein-coding RNA (80%), long non-coding RNA (13%), pseudogenes (4.5%), and short non-coding RNA (1.6%). We detected a subset of genes associated with the previously identified epithelioid (32 genes) and sarcomatoid molecular components (36 genes) in PM-EVs. To investigate whether these markers could serve as biomarkers for PM detection in blood, we compared the RNA content of PM-EVs with the cargo of EVs isolated from the plasma of healthy donors (publicly available data). Majority of upregulated genes in PM-EVs were protein-coding and long non-coding RNAs. Interestingly, 25 of them were the sarcomatoid and epithelioid marker genes. Finally, functional analysis revealed that the PM-EV RNA cargo was associated with Epithelial-Mesenchymal transition, glycolysis, and hypoxia.

CONCLUSIONS

This is the first study to characterize the transcriptomic profile of EVs secreted by PM primary cell cultures, demonstrating their potential as biomarker source for early detection. Further investigation of the functional role of PM-EVs will provide new insights into disease biology and therapeutic avenues.

Nanoparticle-aptamer based cytosensing for the detection of human non-small cell lung cancer cells

This study reports a simple and rapid aptamer-based sensor platform designed for the sensitive and selective detection of human non-small cell lung cancer (NSCLC) cells. Under standard conditions, gold nanoparticles (AuNPs) remain dispersed and exhibit a characteristic peak at 520 nm. However, the addition of sodium chloride (NaCl) destabilizes the charge of the solution, leading to the aggregation of AuNPs. The AS1411 aptamer can adsorb onto the surface of AuNPs, effectively preventing their aggregation. In the presence of A549 cells, the AS1411 aptamer is induced to form stable G-tetrads, which allows for specific binding to the cells and results in the aggregation of AuNPs in the NaCl solution. This proposed aptasensor platform demonstrates high specificity for A549 cells when compared to other control human normal cells. The method exhibits a dynamic range of 101 to 106 cells per mL, with a detection limit of 7 cells per mL.

Segmentectomy versus lobectomy in younger patients with early-stage non-small cell lung cancer

OBJECTIVES

Despite clinical trials supporting the efficacy of segmentectomy for early-stage non-small cell lung cancer (NSCLC), a previous report indicated its limited efficacy in younger patients, raising concerns about its indication.

METHODS

Patients aged <70 years with radiologically solid-dominant clinical stage IA NSCLC ≤2 cm who underwent lobectomy or segmentectomy at three institutions between 2010 and 2017 were enrolled. Propensity scores were estimated to adjust for confounding variables (age, sex, smoking history, tumour location, size, ground-glass opacity, maximum standardized uptake value and histological type). To elucidate the prognostic impact of surgical indications in the late postoperative phase, restricted mean survival time (RMST) from 0 to 5 and 8 years was also determined.

RESULTS

Overall, 388 patients with a median age of 63 years were enrolled. Overall survival (OS) (hazard ratio [HR], 0.447; 95% confidence interval [CI], 0.152-1.316) and recurrence-free survival (RFS) (HR, 0.638; 95% CI, 0.335-1.216) did not differ significantly between the segmentectomy (n = 114) and lobectomy groups (n = 274). In the propensity score matching of 100 pairs, OS (HR, 0.577; 95% CI, 0.162-2.056) and RFS (HR, 0.945; 95% CI, 0.408-2.191) were comparable between the segmentectomy and lobectomy groups. Regarding OS in the segmentectomy and lobectomy groups, the 5- and 8-year RMST were 4.95 years versus 4.92 years (difference: 0.02 years; 95% CI, -0.09-0.13; P = 0.699) and 7.82 years versus 7.69 years (difference: 0.12 years; 95% CI, -0.17-0.42; P = 0.420), respectively.

CONCLUSIONS

Segmentectomy is a viable option for younger patients with early-stage NSCLC, suggesting that indications for segmentectomy need not vary by age.

Comparison of segmentectomy and wedge resection for cT1cN0M0 non-small cell lung cancer

OBJECTIVE

Sublobar resection is considered a standard surgical procedure for early non-small cell lung cancer, although the survival of patients undergoing sublobar resection for clinical T1cN0M0 non-small cell lung cancer remains unclear. This study aimed to compare survival between segmentectomy and wedge resection for clinical T1cN0M0 non-small cell lung cancer.

METHODS

This retrospective study included patients who had undergone curative surgery for cT1cN0M0 stage IA3 non-small cell lung cancer. The overall and recurrence-free survival rates of 91 patients who underwent segmentectomy or wedge resection were compared.

RESULTS

Thirty-nine (42.9%) and 52 patients (57.1%) were included in the segmentectomy and wedge resection groups, respectively. The median length of follow-up was 6.0 years (95% confidence interval 4.2 - - years) (Kaplan-Meier estimate). The 5 year overall survival rates were not significantly different between the segmentectomy and wedge resection groups (67.7% vs 52.0%, P = 0.132). The 5 year recurrence-free survival rate was worse in the wedge resection group than in the segmentectomy group (66.6% vs 46.9%, P = 0.047). In univariable analysis, spread through air spaces (hazard ratio, 5.889; 95% confidence interval, 2.357-14.715; P < 0.001) was an important prognostic factor for recurrence-free survival in the wedge resection group.

CONCLUSIONS

The overall survival of patients who underwent segmentectomy for clinical T1cN0M0 non-small cell lung cancer was not significantly different from that of patients who underwent wedge resection. However, patients with cT1cN0M0 non-small cell lung cancer who underwent wedge resection tended to have a worse recurrence-free survival prognosis than those who underwent segmentectomy.

Prognostic Impact of Non-Predominant Lepidic Components in Pathologic Stage I Invasive Nonmucinous Adenocarcinoma

INTRODUCTION

This study investigated the prognostic impact of non-predominant lepidic components in invasive nonmucinous adenocarcinoma.

METHODS

Patients who underwent lobectomy and were diagnosed with stage I nonmucinous, non-lepidic-predominant invasive adenocarcinoma based on pathologic findings were included. Tumors were staged according to the eighth edition of TNM classification and categorized on the basis of the presence of lepidic components in the final pathologic findings. Overall survival (OS) and recurrence-free survival (RFS) were analyzed before and after applying inverse probability of treatment weighting. Competing risk analyses for recurrence were also compared in the two groups.

RESULTS

Of the 1270 patients, 858 (67.6%) had lepidic components (+). The pathologic stage and histologic grade were higher in the lepidic (-) group (p < 0.001, respectively). The 5-year OS and RFS were significantly worse in the lepidic (-) group than in the lepidic (+) group (OS: 88.2% versus 94.9%, p < 0.001; RFS: 79.4% versus 91.9%, p < 0.001). These trends were consistent after weighted analysis (OS: 92.4% versus 96.4%, p = 0.029; RFS: 85.6% versus 92.3%, p = 0.007). The 5-year cumulative incidence of any recurrence was 14.0% in the lepidic (-) group and 4.1% in the lepidic (+) group (p < 0.001). Multivariable Fine-Gray regression analysis found that the lepidic (+) group exhibited a lower risk of recurrence than did the lepidic (-) group (hazard ratio = 0.52, 95% confidence interval: 0.29-0.93, p = 0.031).

CONCLUSIONS

In pathologic stage I invasive nonmucinous adenocarcinoma, the presence of histologically diagnosed non-predominant lepidic components might be associated with a better prognosis after curative surgery.

Patients outcomes in lung adenocarcinoma transforming to small-cell lung cancer after tyrosine kinase inhibitor therapy

BACKGROUND

Non-small cell lung cancer (NSCLC) transforming to small cell lung cancer (SCLC) is one of the mechanisms of resistance to tyrosine kinase inhibitors (TKIs). Cases of NSCLC transforming into SCLC have been discovered. However, we lack concentrated data on the characteristics of this population and the transformed SCLC to aid our insight of the biology and clinical value of NSCLC transforming with positive.

METHODS

We systematically reviewed the published literatures and summarized the pathological and clinical characteristics, and the prognosis, of published cases.

RESULTS

140 patients with lung adenocarcinoma (LUAD) were included in this study, with a median age of 56.8 years. The median time from the first diagnosis of LUAD transforming to SCLC (ttSCLC) was 20.0 months. The median overall survival (mOS) after the diagnosis of SCLC was 11.0 months (95% CI, 7.41 to 14.59 months). In the univariate analysis, ever smoking (either former or current) was a promising predictor of a shorter ttSCLC (HR, 1.73; 95% CI, 1.14 to 2.62; P = 0.010). TKIs therapy administered as a second line and beyond treatment was related to a significant delay in SCLC onset compared to first-line therapy (HR, 0.62; 95% CI, 0.40 to 0.96; P = 0.031). The median progression-free survival (mPFS) on first-line platinum plus etoposide after the conversion to SCLC was 3.0 months. Female appeared to be related to worse outcomes after transformation of SCLC.

CONCLUSION

Transformed SCLC exhibited poor response to primary SCLC classic chemotherapy and immunotherapy. It carries a worse prognosis. Exploring novel therapeutic strategies for transformed SCLC is imperative.

Clinical and pathological characteristics of pulmonary meningioma: a case report and literature review

This case report aimed to examine the clinical pathological characteristics, immunohistochemical phenotype, and differential diagnosis of primary pulmonary meningioma (PM), which is a rare tumor. A retrospective analysis was conducted on the clinical data, imaging manifestations, histological features, immunohistochemical results, and in situ hybridization results of a 60-year-old male patient who underwent surgical resection and was diagnosed with PM by pathology. Additionally, the relevant literature was reviewed. Multiple nodules were detected in the right lung of the patient during a re-examination because of a novel coronavirus infection but there were no obvious clinical symptoms. Imaging revealed well-defined masses in the upper, middle, and lower lobes of the right lung, and the masses were surgically removed. Microscopy showed that the boundary between the tumor and surrounding lung tissue was clear, and consisted of spindle cells and epithelioid cells. The final diagnosis was multiple grade II meningiomas of the right lung. No postoperative radiotherapy or chemotherapy was performed. There was no recurrence or metastasis during a 6-month follow-up. Pulmonary metastatic meningioma is rare, while primary PM is even rarer. Surgical resection is the preferred treatment method for PM, with a generally good prognosis, but a few malignant manifestations may require close follow-up.

Revolutionizing lung cancer treatment: Introducing PROTAC therapy as a novel paradigm in targeted therapeutics

This comprehensive review explores the transformative potential of PROTAC (Proteolysis-Targeting Chimeras) therapy as a groundbreaking approach in the landscape of lung cancer treatment. The introduction provides a succinct overview of current challenges in lung cancer treatment, emphasizing the significance of targeted therapies. Focusing on PROTAC therapy, the article elucidates its mechanism of action, comparing it with traditional targeted therapies and highlighting the key components and design principles of PROTAC molecules. In the context of lung cancer, the review meticulously summarizes preclinical evidence, emphasizing efficacy and specificity gleaned from studies evaluating PROTAC therapy. It delves into the implications of this preclinical data, discussing potential advantages over existing targeted therapies. An update on ongoing clinical trials involving PROTAC therapy for lung cancer offers a snapshot of the current progress, with a summary of key outcomes and advancements in early-phase trials. The mechanistic insights into PROTAC therapy's impact on lung cancer cells are explored, alongside a discussion on potential biomarkers for patient stratification and response prediction. The influence of tumor heterogeneity on PROTAC therapy outcomes is also addressed. Safety and tolerability assessments, encompassing preclinical and clinical studies, are comprehensively evaluated, including a comparative analysis with traditional targeted therapies and strategies to mitigate side effects. Looking forward, the article discusses the future perspectives of PROTAC therapy in lung cancer treatment and addresses ongoing challenges, providing a nuanced exploration of potential combination therapies and synergistic approaches. In conclusion, the review summarizes key findings and insights, underscoring the tremendous potential of PROTAC therapy as a promising and innovative avenue in pursuing more effective lung cancer treatments.

Solid-type adenocarcinoma on thin-section CT: quantitative parameters from dual-energy CT associated with spread through air spaces

BackgroundSpread through air spaces (STAS) is a well-established factor associated with poor oncological outcomes in patients undergoing surgery for solid lung adenocarcinoma. There could potentially be a disparity in iodine uptake between patients with positive and negative airway spread of solid lung adenocarcinoma.PurposeTo explore the associations and find correlations of iodine uptake with STAS status in patients who underwent surgery for solid lung adenocarcinoma.Material and MethodsPatients who underwent solid lung adenocarcinoma resection between January and June 2022 were included in this retrospective study. Iodine concentration and CT features were assessed using contrast-enhanced dual-energy computed tomography (DECT) scans, and these were compared with the status of STAS.ResultsOf 52 patients included, 25 (48%) were STAS-positive and 27 (52%) were STAS-negative. There were no statistically significant differences in CT features between the two groups (P > 0.05). STAS-positive was significantly associated with low arterial phase iodine concentration (ICA), normalized arterial phase iodine concentration (NICA), and venous phase iodine concentration (ICV), with a cutoff established at 1.15 mg/mL, 0.11, and 1.35 mg/mL, respectively (P < 0.05). The AUCs for ICA, NICA, and ICV in predicting STAS in solid lung adenocarcinoma were 0.82, 0.83, and 0.73, respectively. ICA and NICA were identified as independent risk factors for STAS in solid lung adenocarcinoma, with a combined AUC of 0.89.ConclusionThis study suggests that solid lung adenocarcinoma patients with low ICA, NICA, and ICVA were associated with STAS-positive, as well as a worse survival outcomes.

Breathing new insights into the role of mutant p53 in lung cancer

The tumour suppressor gene p53 is one of the most frequently mutated genes in lung cancer and these defects are associated with poor prognosis, albeit some debate exists in the lung cancer field. Despite extensive research, the exact mechanisms by which mutant p53 proteins promote the development and sustained expansion of cancer remain unclear. This review will discuss the cellular responses controlled by p53 that contribute to tumour suppression, p53 mutant lung cancer mouse models and characterisation of p53 mutant lung cancer. Furthermore, we discuss potential approaches of targeting mutant p53 for the treatment of lung cancer.

LncRNA DGUOK-AS1 Promotes Cell Progression in Lung Squamous Cell Carcinoma by Regulation of miR-653-5p/SLC6A15 Axis

Long noncoding RNA (lncRNA) plays a key role in regulating cancer development. LncRNA deoxyguanosine kinase antisense RNA 1 (DGUOK-AS1) has been reported as a promoter in tumor. The work was designed to further investigate the mechanism of action of DGUOK-AS1 in lung squamous cell carcinoma (LUSC). DGUOK-AS1 level in LUSC cells was measured using RT-qPCR. Counting Kit-8 assays and colony forming assays were performed to evaluate LUSC cell viability and proliferation. Transwell assays were performed to detect cell migration and invasion. Luciferase reporter and RNA pulldown assays were used to verify the binding capacity of DGUOK-AS1 and miR-653-5p. RNA immunoprecipitation assays were performed to verify the relationship of DGUOK-AS1, miR-653-5p, and SLC6A15. DGUOK-AS1 was highly expressed in LUSC cells. DGUOK-AS1 knockdown suppressed LUSC cell proliferation, migration, and invasion. SLC6A15 was demonstrated to be targeted by miR-653-5p, and DGUOK-AS1 interacted with miR-653-5p to modulate SLC6A15 level in LUSC cells. Overexpression of SLC6A15 reversed the suppressive effects of DGUOK-AS1 knockdown on LUSC cell processes. In conclusion, DGUOK-AS1 promotes malignant behaviors of LUSC cells by upregulating SLC6A15 level through interaction with miR-653-5p.

Pediatric Neuroendocrine Tumors in Denmark: Incidence, Management, and Outcome From 1995 to 2020

BACKGROUND

Neuroendocrine tumors (NETs), although rare, are considered one of the most common gastrointestinal and bronchopulmonary pediatric neoplasms. We aimed to determine the incidence, tumor characteristics, management, and outcome of NETs and explore the role of genetic predisposition, focusing on low and intermediate grade tumors.

METHODS

Using the Danish National Pathology Registry, we conducted a nationwide retrospective study including all Danish children aged ≤18 years diagnosed with a pathology-proven NET between 1995 and 2020.

RESULTS

We identified 220 patients, with a 1.89:1 female to male ratio. The yearly incidence was 6.84 per 1 million children, with no significant change in incidence throughout the observation period. NETs were located in the appendix (93.2%), the pulmonary system (4.5%), and pancreas (2.3%). One recurrence was noted in the pancreas in a genetically predisposed patient with multiple neuroendocrine neoplasia type 1 (MEN1), resulting in an overall recurrence rate of 0.5% (0% in appendiceal NETs; 0% in bronchopulmonary NETs; 20.0% in pancreatic NETs). No NET-related mortality was registered. Four patients had a known predisposing genetic condition, one appendiceal NET associated with neurofibromatosis type 1, and three pancreatic NETs associated with MEN1. Postsurgical surveillance regimes, choice of tumor markers, and imaging modality varied throughout the study period.

CONCLUSIONS

We confirmed a stable incidence of pediatric NETs during the study period. The overall recurrence rate was 0.5% and no NET-related mortality was observed. Known genetic predisposition was present in 1.8% of patients. Future guidelines should consider the apparent indolent nature and excellent prognosis of these tumors.

Prognostic Impact of Low Muscle Mass and Inflammatory Markers in Stage III Nonsmall Cell Lung Cancer Turkish Oncology Group and Turkish Society of Radiation Oncology Thoracic Cancer Study Group (08-005)

OBJECTIVES

The aim of this retrospective multicenter study was to evaluate the prognostic significance of low muscle mass, and inflammatory markers in patients with stage III nonsmall cell lung cancer (NSCLC) who received definitive chemoradiotherapy (CRT). Furthermore, the study aimed to determine the threshold value of disease-specific low muscle mass.

METHODS

A total of 461 patients with stage III NSCLC were evaluated. Low muscle mass, prognostic nutritional index (PNI), and biochemical inflammatory markers were assessed. The Kaplan-Meier method and Cox regression analysis were used to analyze overall survival (OS) and progression-free survival (PFS).

RESULTS

This study found a disease-specific low muscle mass threshold of LSMI <38.7 cm²/m² for women and <45.1 cm²/m² for men, with 25.2% of patients having disease-specific low muscle mass. Multivariate cox regression analysis revealed that low PNI was found to be an independent unfavorable prognostic factor for both PFS (HR=0.67; 95% CI: 0.48-0.92, P = 0.015) and OS (HR=0.67; 95% CI: 0.50-0.91, P =0.008). Other factors including ECOG PS 3 (HR=7.76; 95% CI: 1.73-34.76, P =0.007), induction CT (HR=0.66; 95% CI: 0.49-0.88, P = 0.004), and disease-specific low muscle mass (HR=1.40; 95% CI: 1.02-1.92, P = 0.038) also had independent effects on prognosis.

CONCLUSIONS

The present study provides evidence that the presence of low muscle mass and low PNI significantly impacts the prognosis of patients with stage III NSCLC who undergo definitive CRT. Furthermore, our study is notable for being the first multicenter investigation to identify a disease-specific low muscle mass threshold.

A Novel DNA Repair-Gene Model to Predict Responses to Immunotherapy and Prognosis in Patients With EGFR-Mutant Non-Small Cell Lung Cancer

BACKGROUND

The epidermal growth factor receptor mutant (EGFRm) non-small cell lung cancer (NSCLC) has a unique "cold" immune profile. DNA damage repair (DDR) genes are closely related to tumorigenesis and the effectiveness of immunotherapy in many tumors. However, the role and mechanism of DDR in the genesis and progression of EGFRm NSCLC remain unclear.

METHODS

This study included 101 EGFRm NSCLC samples from The Cancer Genome Atlas (TCGA) dataset and a GSE31210 dataset (external set) from the GEO database. Cluster analysis was used to identify different subtypes of EGFRm NSCLC based on the expression of DDR genes. Univariate and LASSO regression analysis was used to develop a DDR-based predictive model. The prognostic significance of this model was assessed using Cox regression, Kaplan-Meier, and receiver operating characteristic (ROC) curve analyses. Bioinformatics analysis was performed to investigate the clinicopathological characteristics and immune profiles associated with this model. In vitro experiment was performed to testify the role of DDR genes in EGFRm NSCLC.

RESULTS

We identified two subtypes of EGFRm NSCLC: DDR-activated and DDR-suppressed. The DDR-activated subtype showed more aggressive clinical behavior and poorer prognosis and was more responsive to immunotherapy. A prognostic model for EGFRm NSCLC was constructed using four DDR genes: CAPS, FAM83A, IGLV8-61, and SLC7A5. The derived risk score could serve as an independent prognostic indicator. High- and low-risk patients exhibited distinct clinicopathological characteristics, immune profiles, and responses to immunotherapy. The T-cell inflammation and Tumor Immune Dysfunction and Exclusion (TIDE) scores differed between the high- and low-risk subgroups, with both showing enhanced effectiveness of immunotherapy in the low-risk subgroup. Targeted therapy such as BI.2536, an inhibitor of polo-like kinase 1, could be effective for patients with high-risk EGFRm NSCLC. Meanwhile, in vitro detection approved the role of DDR genes in EGFRm NSCLC response.

CONCLUSION

This study demonstrated a diversity of DDR genes in EGFRm NSCLC and developed a predictive model using these genes. This model could assist in identifying potential candidates for immunotherapy and in assessing personalized treatment and prognosis of patients with EGFRm NSCLC.

Patient-Centered Physical Activity Intervention in Lung Cancer Patients: A Clinical Severity and Functional Capacity Systematic Review and Meta-analysis

BACKGROUND

Increasing physical activity levels is a significant unmet need in cancer survivors, and it can likely be enhanced through a better understanding of the interventions developed. Some studies on patient-centered physical activity interventions have shown promising results in increasing daily activity levels among lung cancer survivors. However, the programs present a high heterogeneity, and there is no consensus on the parameters and their effectiveness.

OBJECTIVE

To examine the effectiveness of patient-centered physical activity interventions on clinical severity and functional capacity in lung cancer patients.

METHODS

A systematic review was performed on randomized controlled trials. A literature search was conducted using MEDLINE, Web of Science, Science Direct, and Cochrane Library (last search November 2023). The Cochrane tool and the Grading of Recommendations Assessment, Development, and Evaluation system were used for quality assessment. Pooled data were meta-analyzed for physical activity levels, functional capacity, and cancer-related symptoms.

RESULTS

Fourteen studies, encompassing 1123 lung cancer patients, were included. The treatment status of patients varied. The components of the physical activity programs showed heterogeneity. Results revealed significant differences favoring patient-centered physical activity interventions over the control group for physical activity levels (P < .05), functional capacity (P < .001), and cancer-related symptoms (P < .05).

CONCLUSION

The results indicate that patient-centered physical activity programs positively enhance physical activity levels, improve functional capacity, and reduce cancer-related symptoms in patients with lung cancer.

IMPLICATIONS FOR PRACTICE

Patient-centered physical activity interventions show promise in improving the care and management of lung cancer patients. These interventions provide a basis for encouraging lung cancer patients to actively participate in their treatment.

Efficacy and safety of immunotherapy in locally advanced or metastatic pulmonary lymphoepithelioma-like carcinoma: a multicenter retrospective study

Background

Pulmonary lymphoepithelioma-like carcinoma (pLELC) is a rare subtype of non-small-cell lung cancer that predominantly affects younger, non-smoking individuals in southern and southeast Asia, where Epstein-Barr virus (EBV) prevalence is high. The efficacy and safety of immunotherapy in pLELC, especially in second-line settings, remain inadequately explored.

Objectives

This study aimed to evaluate the efficacy of immunotherapy, either alone or in combination with chemotherapy, in improving progression-free survival (PFS) and overall survival (OS) in patients with advanced pLELC.

Design

This was a multicenter retrospective study.

Methods

A retrospective analysis was conducted on 252 patients with stage IIIB-IV pLELC treated across six centers. Patients received chemotherapy, immunotherapy, or a combination of both (chemoimmunotherapy). The primary outcomes measured were PFS and OS across different treatment regimens.

Results

Chemoimmunotherapy significantly improved both PFS and OS compared to chemotherapy alone, in both first- and second-line settings. In first-line treatment, chemoimmunotherapy resulted in a median PFS of 17.6 months and OS of 26.1 months, compared to chemotherapy alone (PFS 8.7 months, OS 19.2 months). In the second-line setting, chemoimmunotherapy achieved a median PFS of 5.1 months and OS of 13.5 months, surpassing the outcomes with chemotherapy alone (PFS 3.3 months, OS 8.9 months). High baseline EBV-DNA levels (>2000 copies/mL) and low programmed death ligand 1 (PD-L1) expression (<50%) were associated with poorer outcomes. In addition, patients with high baseline serum tumor markers (STMs) and a dynamic reduction of ⩽20% in STMs exhibited significantly worse PFS and OS.

Conclusion

The study suggests that immunotherapy, particularly when combined with chemotherapy, offers significant survival benefits for patients with advanced pLELC. Baseline EBV-DNA levels, PD-L1 expression, and both baseline and dynamic STM changes serve as important predictors of treatment response, highlighting the need for personalized therapeutic approaches in this unique subtype of lung cancer.

Determining the status of tertiary lymphoid structures in invasive pulmonary adenocarcinoma based on chest CT radiomic features

OBJECTIVES

The aim of this study was to determine the status of tertiary lymphoid structures (TLSs) using radiomic features in patients with invasive pulmonary adenocarcinoma (IA).

METHODS

In this retrospective study, patients with IA from November 2015 to March 2024 were recruited from two independent centers (center 1, training and internal test data set; center 2, external test data set). TLS was divided into two groups according to hematoxylin-eosin staining. Radiomic features were extracted, and support vector machine (SVM) were implemented to predict the status of TLSs. Receiver operating characteristic (ROC) curves were used to analyze diagnostic performance. Furthermore, visual assessments of the test set were also conducted by two thoracic radiologists and compared with the radiomics results.

RESULTS

A total of 456 patients were included (training data set, n = 278; internal test data set, n = 115; external test data set, n = 63). The area under the curve (AUC) of the radiomics model on the validation set, the internal test set, and the external test set were 0.781 (95% confidence interval (CI): 0.659-0.905;), 0.804 (95% CI: 0.723-0.884;) and 0.747 (95% CI: 0.621-0.874;), respectively. In the visual assessments, the mean CT value and air bronchogram were important indicators of TLS, the AUC was 0.683. In the external test set, the AUC of the clinical model was 0.632.

CONCLUSIONS

The radiomics model has a higher AUC than the clinical model and effectively discriminates TLSs in patients with IA.

CRITICAL RELEVANCE STATEMENT

This study demonstrates that the radiomics-based model can differentiate TLSs in patients with IA. As a non-invasive biomarker, it enhances our understanding of tumor prognosis and management.

KEY POINTS

TLSs are closely related to favorable clinical outcomes in non-small cell lung cancer. Radiomics from Chest CT predicted TLSs in patients with IA. This study supports individualized clinical decision-making for patients with IA.

The Detection of Lung Cancer Cell Profiles in Mediastinal Lymph Nodes Using a Hematological Analyzer and Flow Cytometry Method

The presence of metastases in mediastinal lymph nodes (LNs) is essential for planning lung cancer treatment and assessing anticancer immune responses. The aim of the study was to assess LNs for the presence of neoplastic cells and evaluate lung cancer-selected antigen expression. LN aspirates were obtained during an EBUS/TBNA procedure. The cells were analyzed using a hematological analyzer and flow cytometry. It was possible to indicate the presence of cells characterized by high fluorescence connected with high metabolic activity using a hematological analyzer and to determine their non-hematopoietic origin using flow cytometry. Using these methods together, we detected very quickly a high proportion of cancer cells in LNs. We noticed that it was possible to determine a high expression of EpCAM, TTF-1, Ki67, cytokeratin, HER, and differences between non-small-cell (NSCLC) and small-cell lung cancer (SCLC) for the antigens MUC-1, CD56, HLA-DR, CD39, CD184, PD-L1, PD-L2 and CTLA-4 on tumor cells. We report, for the first time, that the detection of tumor cells in LNs with the expression of specific antigens is easy to evaluate using a hematological analyzer and flow cytometry in EBUS/TBNA samples. Such precise characteristics of non-hematopoietic cells in LNs may be of great diagnostic importance in the detection of micrometastases.

The association between body composition and overall survival in patients with advanced non-small cell lung cancer

Nutritional status is associated with prognosis in a variety of cancers. Studies analyzing the association between the measurements of skeletal muscle and adipose tissue obtained from Computerized Tomography (CT) images at the time of diagnosis of advanced non-small cell lung cancer (NSCLC) and overall survival (OS) are relatively few. Data from 425 patients diagnosed with advanced NSCLC between January 2016 and December 2017 were retrospectively analyzed, with an average follow-up of 15.3 months. To outline the patient's chest CT plain image at the time of diagnosis,skeletal muscle and subcutaneous fat at the level of both thoracic vertebrae were quantified in terms of mass and quantity by the pectoral muscle index (PMI), pectoral muscle density (PMD), subcutaneous fat index (SFI), subcutaneous fat density (SFD), paravertebral muscle index (PVMI), and paravertebral muscle density (PVMD). The SFI value in the female survival group is significantly lower than that in the death group (P = 0.049), and the PVMI value in the overall survival group is significantly lower than that in the death group (P < 0.001). After adjusting for clinical variables such as gender, smoking status, clinical staging, degree of differentiation, and radiotherapy history, the multivariable Cox regression analysis showed that an increase in SFI significantly improves the overall survival rate of patients (Hazard Ratio [HR] = 1.410, 95% Confidence Interval [CI]: 1.042-1.908, P = 0.026). Conversely, a decrease in PVMD is significantly associated with improved overall survival and prognosis (HR = 0.762, 95% CI: 0.579-0.982, P = 0.048). No association was found between body mass index (BMI) and chest muscle status indicators and overall survival (P > 0.05). CT-measured body composition parameters provide precise prognostic information and are superior to BMI; an increased OS rate in advanced NSCLC is associated with a greater SFI and a lower PVMD.

Pulmonary enteric adenocarcinoma with progression disease after second - line therapy: a case report

Pulmonary enteric adenocarcinoma (PEAC, also known as Enteric-type adenocarcinoma of the lung, lung - ETAC) is a rare subtype of non-small cell lung cancer (NSCLC) that has the same morphological and immunohistochemical characteristics as colorectal adenocarcinoma and requires gastroenteroscopy to rule out lesions of enteric origin. As a rare solid tumor in lung cancer, PEAC has unique clinical outcome, imaging, pathological and molecular characteristics, and poor prognosis. However, the molecular characteristics and therapeutic biomarkers of PEAC are unclear, and its treatment remains challenging. In this case, we describe a 61-year-old man diagnosed with advanced primary PEAC with KRAS mutation. In the case of unknown PD-L1 expression status, first-line treatment was given to lung adenocarcinoma regimen (immunotherapy combined with chemotherapy), progression occurred after 2 cycles, and progression-free survival (PFS) was 1.5 months. Then the second-line XELOX regimen (oxaliplatin combined with capecitabine) was adjusted. The lesions were significantly reduced after 2 and 4 cycles, and the disease progressed again after 6 cycles, with a PFS of 4.5 months. Anlotinib targeted drugs were selected for third-line treatment, but considering the overall poor condition of the patient, the patient himself refused further treatment. Finally, after discharge, the patient went to the local hospital for nutritional support and symptomatic treatment. The results suggest that standard first-line therapies (immunotherapy plus chemotherapy) and colorectal cancer regimens may have a relatively limited impact on survival in KRAS-driver positive advanced PEAC.

Intelligent classification of lung cancer pathology images through comparative morphological feature learning

BACKGROUND

The accurate classification of lung cancer pathology images is of paramount importance for both diagnostic and therapeutic purposes. However, the development of robust classification models is often hindered by the intricate cellular morphologies and the scarcity of labeled images, which is a critical bottleneck in the field.

OBJECTIVES

The study is designed to incorporate unlabeled data into the training process, thereby enhancing the classification of lung cancer pathology images through the use of comparative learning techniques.

METHODS

A methodology is introduced wherein confidently classified unlabeled images are integrated with labeled ones, enriching the training dataset. This approach draws on principles of farthest and nearest neighbor contrastive learning to cultivate a more challenging learning environment and to augment the variability of contrastive samples. To effectively extract key cellular morphological features, an encoder based on the ResNet50 architecture, fortified with deformable and dynamic convolutional techniques, is utilized.

RESULTS

Demonstrated by experimental results, the proposed classification strategy achieves a significant improvement in the accuracy of lung cancer image classification, even under conditions characterized by a limited availability of labeled data, thus underscoring the robustness of the method.

CONCLUSION

The integration of comparative learning with both labeled and unlabeled images, complemented by the application of advanced convolutional techniques, is shown to be a promising avenue for enhancing the classification of lung cancer pathology images. This research is presented as a practical solution to the urgent need for accurate and efficient diagnostic tools in the field of oncology.

Molecular characterization of EBV-associated primary pulmonary lymphoepithelial carcinoma by multiomics analysis

BACKGROUND

Primary pulmonary lymphoepithelial carcinoma (pLEC) is a subtype of non-small cell lung cancer (NSCLC) characterized by Epstein-Barr virus (EBV) infection. However, the molecular pathogenesis of pLEC remains poorly understood.

METHODS

In this study, we explored pLEC using whole-exome sequencing (WES) and RNA-whole-transcriptome sequencing (RNA-seq) technologies. Datasets of normal lung tissue, other types of NSCLC, and EBV-positive nasopharyngeal carcinoma (EBV+-NPC) were obtained from public databases. Furthermore, we described the gene signatures, viral integration, cell quantification, cell death and immune infiltration of pLEC.

RESULTS

Compared with other types of NSCLC and EBV+-NPC, pLEC patients exhibited a lower somatic mutation burden and extensive copy number deletions, including 1p36.23, 3p21.1, 7q11.23, and 11q23.3. Integration of EBV associated dysregulation of gene expression, with CNV-altered regions coinciding with EBV integration sites. Specifically, ZBTB16 and ERRFI1 were downregulated by CNV loss, and the FOXD family genes were overexpressed with CNV gain. Decreased expression of the FOXD family might be associated with a favorable prognosis in pLEC patients, and these patients exhibited enhanced cytotoxicity.

CONCLUSION

Compared with other types of NSCLC and NPC, pLEC has distinct molecular characteristics. EBV integration, the aberrant expression of genes, as well as the loss of CNVs, may play a crucial role in the pathogenesis of pLEC. However, further research is needed to assess the potential role of the FOXD gene family as a biomarker.

Advancing presurgical non-invasive spread through air spaces prediction in clinical stage IA lung adenocarcinoma using artificial intelligence and CT signatures

Background

To accurately identify spread through air spaces (STAS) in clinical stage IA lung adenocarcinoma, our study developed a non-invasive and interpretable biomarker combining clinical and radiomics features using preoperative CT.

Methods

The study included a cohort of 1,325 lung adenocarcinoma patients from three centers, which was divided into four groups: a training cohort (n = 930), a testing cohort (n = 238), an external validation 1 cohort (n = 93), and 2 cohort (n = 64). We collected clinical characteristics and semantic features, and extracted radiomics features. We utilized the LightGBM algorithm to construct prediction models using the selected features. Quantifying the contribution of radiomics features of CT to prediction model using Shapley additive explanations (SHAP) method. The models' performance was evaluated using metrics such as the area under the receiver operating characteristic curve (AUC), negative predictive value (NPV), positive predictive value (PPV), sensitivity, specificity, calibration curve, and decision curve analysis (DCA).

Results

In the training cohort, the clinical model achieved an AUC value of 0.775, the radiomics model achieved an AUC value of 0.836, and the combined model achieved an AUC value of 0.837. In the testing cohort, the AUC values of the models were 0.743, 0.755, and 0.768. In the external validation 1 cohort, the AUC values of the models were 0.717, 0.758, and 0.765, while in the external validation 2 cohort, 0.725, 0.726 and 0.746. The DeLong test results indicated that the combined model outperformed the clinical model (p < 0.05). DCA indicated that the models provided a net benefit in predicting STAS. The SHAP algorithm explains the contribution of each feature in the model, visually demonstrating the impact of each feature on the model's decisions.

Conclusion

The combined model has the potential to serve as a biomarker for predicting STAS using preoperative CT scans, determining the appropriate surgical strategy, and guiding the extent of resection.

Recent Advances in the Clinical Translation of Small-Cell Lung Cancer Therapeutics

Small-cell lung cancer (SCLC) is a recalcitrant form of cancer, representing 15% of lung cancer cases globally. SCLC is classified within the range of neuroendocrine pulmonary neoplasms, exhibiting shared morphologic, ultrastructural, immunohistochemical, and molecular genomic features. It is marked by rapid proliferation, a propensity for early metastasis, and an overall poor prognosis. The current conventional therapies involve platinum-etoposide-based chemotherapy in combination with immunotherapy. Nonetheless, the rapid emergence of therapeutic resistance continues to pose substantial difficulties. The genomic profiling of SCLC uncovers significant chromosomal rearrangements along with a considerable mutation burden, typically involving the functional inactivation of the tumor suppressor genes TP53 and RB1. Identifying biomarkers and evaluating new treatments is crucial for enhancing outcomes in patients with SCLC. Targeted therapies such as topoisomerase inhibitors, DLL3 inhibitors, HDAC inhibitors, PARP inhibitors, Chk1 inhibitors, etc., have introduced new therapeutic options for future applications. In this current review, we will attempt to outline the key molecular pathways that play a role in the development and progression of SCLC, together with a comprehensive overview of the most recent advancements in the development of novel targeted treatment strategies, as well as some ongoing clinical trials against SCLC, with the goal of improving patient outcomes.