Translational lung cancer research最新文献

{"title":"<i>LNCAROD</i> was stabilized through N⁶-methyladenosine methylation and exerted its anticancer effects in lung squamous cell carcinoma by inhibiting SIRT1 activity via CCAR2.","authors":"Qihang Yan, Wingshing Wong, Jinsong Lei, Dachuan Liang, Jie Yang, Li Gong, Rossana Berardi, Shuqin Dai, Junye Wang","doi":"10.21037/tlcr-2025-267","DOIUrl":"10.21037/tlcr-2025-267","url":null,"abstract":"<p><strong>Background: </strong>Lung squamous cell carcinoma (LUSC), a deadly malignant tumor, is highly prevalent worldwide. Accumulating evidence indicates that long-chain noncoding RNAs play crucial regulatory roles in the occurrence and progression of LUSC. <i>LNCAROD</i> regulates the proliferation, migration, and invasion of cells by upregulating SERPINE1 expression in lung adenocarcinoma (LUAD). However, the functional mechanism of <i>LNCAROD</i> action in LUSC remains unclear. The aim of this study was to investigate the regulatory function and mechanism of <i>LNCAROD</i> action in the development of LUSC.</p><p><strong>Methods: </strong>Using quantitative polymerase chain reaction (qPCR) detection, we determined the expression of <i>LNCAROD</i> in LUSC tissues and cell lines. Cell Counting Kit-8 (CCK-8), EdU (5-ethynyl-2'-deoxyuridine), JC-1 mitochondrial membrane potential, flow cytometry, colony formation, scratch healing, and Transwell assays were conducted, and cell proliferation, migration, and invasion, as well as physiological changes were assessed. The tumorigenicity of LUSC cells was analyzed by in vitro tumor formation in nude mice. Molecular interactions were verified via Western blotting, RNA-protein pull-down assay, RNA binding protein immunoprecipitation (RIP), N6-methyladenosine (m6A)-RIP, and coimmunoprecipitation (Co-IP) analyses.</p><p><strong>Results: </strong><i>LNCAROD</i> was specifically and highly expressed in LUSC cells and tissues. <i>LNCAROD</i> expression was mediated by IGF2BP2 m6A methylation, which, along with CCAR2, inhibited SIRTI1's acetylation activity. This further induced p53 protein acetylation and promoted the mitochondrial apoptosis of LUSC cells, thereby inhibiting cell proliferation, migration, and invasion.</p><p><strong>Conclusions: </strong><i>LNCAROD</i> is specifically highly expressed in LUSC cells and tissues and may be a tumor-suppressor gene. The findings contribute to a deeper understanding of the function of <i>LNCAROD</i> in LUSC, and it may serve as a potential prognostic marker for personalized medical diagnosis in clinical practice.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 4","pages":"1351-1370"},"PeriodicalIF":4.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082203/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144094987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification and validation of diagnostic alternative splicing events in tumor-educated platelets for non-small cell lung cancer in patients with ground-glass opacity: a multicenter study.","authors":"Mengqi Shao, Wanwen Li, Jieming Cao, Li Wang, Shenglong Xie, Yan Hu, Gang Feng, Feredun Azari, Luca Bertolaccini, Wenliang Liu, Bin He","doi":"10.21037/tlcr-2025-287","DOIUrl":"10.21037/tlcr-2025-287","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The diagnostic potential of tumor-educated platelets (TEPs) across various cancer types has gained increasing recognition; however, the relationship between alternative splicing (AS) events in TEPs and tumor development remains understudied. Early detection of non-small cell lung cancer (NSCLC) in ground-glass opacities (GGOs) is critical for improving patient outcomes, yet current methods lack sufficient accuracy. Our research identified diagnostic-related alternative splicing events (DASEs) in TEPs, revealing several promising biomarkers for NSCLC, specifically in patients presenting with GGOs.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Patients with GGOs from two hospitals were prospectively enrolled [Hospital 1-Platelet (H1-P) and Hospital 2-Tissue (H2-T) in the validation cohort; Hospital 2-Platelet (H2-P) in the test cohort]. Benign/malignant diagnosis of GGOs was confirmed by pathological examination according to the World Health Organization (WHO) classification. TEPs from the H1-P cohort were collected for transcriptome sequencing and AS analysis. Chi-square tests, least absolute shrinkage and selection operator (LASSO) regression analysis, and protein-protein interaction (PPI) network were used for the preliminary screening of DASEs. Pathological tissue from the H2-T cohort was collected to validate the diagnostic efficacy of hub DASEs in NSCLC against the pathological gold standard. Moreover, TEPs from the H2-P cohort were used to assess the predictive performance of hub DASEs for GGOs using receiver operating characteristic (ROC) curves. Decision curve analysis (DCA) was used to determine whether diagnosing NSCLC in the GGOs population via hub DASEs could benefit patients.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 285 patients with GGOs were enrolled, including 151 NSCLC and 128 inflammatory nodules confirmed by pathological examination. Thirteen DASEs were screened with the chi-square test and LASSO regression analysis to identify diagnostic TEP AS markers for GGOs NSCLC. The PPI network identified four hub diagnostic-related alternative splice genes (DASGs) (&lt;i&gt;TMEM219&lt;/i&gt;, &lt;i&gt;MPV17&lt;/i&gt;, &lt;i&gt;FIBP&lt;/i&gt;, and &lt;i&gt;VPS28&lt;/i&gt;). Pathological tissues and platelets were collected to validate the four hub DASEs of these four hub DASGs. MXE-32112-&lt;i&gt;TMEM219&lt;/i&gt; yielded an area under the curve (AUC) of 0.82 [95% confidence interval (CI): 0.729-0.902], with a sensitivity of 83.33% and a specificity of 80.00%; RI-3259-&lt;i&gt;VPS28&lt;/i&gt; yielded an AUC of 0.77 (95% CI: 0.677-0.870) with a sensitivity of 93.33% and a specificity of 78.33%; and RI-3641-&lt;i&gt;MPV17&lt;/i&gt; yielded an AUC of 0.82 (95% CI: 0.728-0.901) with a sensitivity of 90.00% and a specificity of 80.00%. The DCA results suggested that using hub DASEs in diagnosing NSCLC in individuals with GGOs could provide benefits.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The specific diagnostic AS events (MXE-32112-&lt;i&gt;TMEM219&lt;/i&gt;, RI-3259-&lt;i&gt;VPS28&lt;/i&gt;, and RI-3641-&lt;i&gt;MPV17&lt;/i&gt;) identified in ","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 4","pages":"1395-1407"},"PeriodicalIF":4.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082202/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144094863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and validation of machine learning models based on molecular features for estimating the probability of multiple primary lung carcinoma versus intrapulmonary metastasis in patients presenting multiple non-small cell lung cancers.","authors":"Ning Liu, Xue Li, Xu Luo, Bin Liu, Jie Tang, Fei Xiao, Weiya Wang, Yuan Tang, Pei Shu, Benxia Zhang, Yue Chen, Diyuan Qin, Qizhi Ma, Fuchun Guo, Xiaojun Tang, Daxing Zhu, Jiandong Mei, Weizhi Chen, Dan Li, Lili Jiang, Yongsheng Wang","doi":"10.21037/tlcr-24-875","DOIUrl":"10.21037/tlcr-24-875","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Discrimination of multiple non-small cell lung cancers (NSCLCs) as multiple primary lung cancers (MPLCs) or intrapulmonary metastases (IPMs) is critical but remains challenging. The aim of this study is to develop and validate the machine learning (ML) models based on the molecular features for estimating the probability of MPLC or IPM for patients presenting multiple NSCLCs.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A total of 72 multiple NSCLCs patients with 157 surgical resection tumor lesions from January 2012 to January 2018 at two institutions were included for developing and testing models. Specifically, 46 patients with 103 tumors which were defined as definitive MPLC or IPM according to International Association for the Study of Lung Cancer (IASLC) criteria were used to develop models. They were spilt into training and validation sets using stratified random sampling and five-fold cross-validation. The developed models were tested in other 26 patients whose tumors were undetermined by traditional methods. Whole-exome sequencing (WES) was performed on all included tumor samples. Four molecular features were calculated to characterize tumors relatedness and served as model inputs, including genetic divergence, shared mutation number, Pearson correlation coefficient and early mutation number. Decision trees (DT), random forests (RF), and gradient boosting decision trees (GBDT) were employed, with performance assessed by areas under the curve (AUCs), accuracy, precision, recall, and F1 score in validation set. Disease-free survival (DFS) were used to evaluate model performance in test cohort. Clinical and genetic characteristics were then compared between MPLC and IPM populations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;All of the four molecular features showed significant differences between MPLC and IPM patients in development cohort. That is, MPLC exhibited higher genetic divergence, lower shared mutation number, Pearson correlation and early mutation number than IPM (P&lt;0.001). DT model, RF model and GBDT model were developed with these factors and achieved a mean AUC of 0.94 [standard deviation (SD) 0.09], 1.00 (SD 0.00) and 1.00 (SD 0.00) in validation set, respectively. DT model, RF model and GBDT model discriminated the undetermined multiple NSCLCs as MPLC (n=15) and IPM (n=11) consistently. MPLC identified by ML models had significantly prolonged DFS [hazard ratio =0.21; 95% confidence interval (CI): 0.04-1.0; P=0.04] than that of IPM. MPLC patients had a relative higher prevalence of family history of first-degree relatives with cancer, and more than half of these patients reported a family history of lung cancer. EGFR remains the most common mutated driver both in MPLC and IPM populations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;ML models based on the molecular features effectively distcriminate primary tumors from metastases in multiple NSCLCs, which improve the accuracy of multiple NSCLCs diagnosis and assist in clinica","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 4","pages":"1118-1137"},"PeriodicalIF":4.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082235/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144093575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy and safety of anlotinib plus EGFR tyrosine kinase inhibitors in slow- or locally progressing non-small cell lung cancer after adjuvant therapy.","authors":"Jiayue Ye, Jiacong Liu, Yucheng Ma, Wang Lv, Wenzhen Xu, Masaya Aoki, Yuhong Yang, Pinghui Xia, Luming Wang, Linhai Zhu, Jian Hu","doi":"10.21037/tlcr-2025-177","DOIUrl":"10.21037/tlcr-2025-177","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Anlotinib, a small-molecule tyrosine kinase inhibitor (TKI), suppresses angiogenesis and tumor progression. As the mechanisms underlying the resistance to epidermal growth factor receptor (EGFR)-TKIs are complex and diverse, further exploration of new treatment strategies is necessary. Combination therapy with EGFR-TKIs and anlotinib targets multiple signaling pathways, enhancing efficacy in patients with EGFR-positive non-small cell lung cancer (NSCLC). This study evaluated the efficacy and safety of anlotinib with EGFR-TKIs in patients with NSCLC who developed resistance to postoperative adjuvant therapy.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;From January 2020 to December 2023, 48 patients at the Department of Thoracic Surgery, the First Affiliated Hospital of Zhejiang University, who developed resistance to adjuvant therapy were included in this retrospective study. All patients received anlotinib (10-12 mg, po, d1-14, q3w) alongside their original EGFR-TKI regimen. The primary endpoint was progression-free survival (PFS), while secondary endpoints included 6- and 12-month PFS rates, overall survival (OS), and safety. PFS was defined as the time from the initiation of anlotinib plus EGFR-TKI to disease progression or death, and OS was defined as the time from the start of anlotinib plus EGFR-TKI to death from any cause.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Among the 48 patients, 23 previously received first- or second-generation EGFR-TKIs, and 25 received third-generation EGFR-TKIs. As of March 25, 2024, the median follow-up duration was 33.3 months [95% confidence interval (CI): 23.2-43.3]. The median PFS was 9.5 months (95% CI: 4.8-14.3), and 6- and 12-month PFS rates were 70.8% and 47.9%, respectively. For patients previously treated with first-/second- and third-generation EGFR-TKIs, the median PFS was 10.3 months (95% CI: 6.1-14.4) and 7.7 months (95% CI: 4.8-10.6), with a 6-month PFS rate of 69.6% and 72.0%, respectively, and a 12-month PFS rate of 47.8% and 48.0%, respectively. The median OS was 31.0 months [95% CI: not reached (NR)-NR], with 6-month and 12-month rates of 91.7% and 85.4%, respectively. For patients previously treated with first-/second- and third-generation EGFR-TKIs, the median OS was NR and 20.3 months (95% CI: 10.7-30.0), respectively; meanwhile, the OS rates were 95.7% and 88.0% at 6 months, and 91.3% and 80.0% at 12 months, respectively. The incidence rates of any grade and grade ≥3 treatment-related adverse events (TRAEs) were 75.0% (36/48) and 10.4% (5/48), respectively. The most common TRAEs included hypertension (17/48, 35.4%), proteinuria (15/48, 31.3%), rash (11/48, 22.9%), fatigue (5/48, 10.4%), and diarrhea (4/48, 8.3%), and no new safety events were observed. Dose reduction and discontinuation of anlotinib were reported in four (8.3%) and five (10.4%) patients previously treated with first-/second- and third-generation EGFR-TKIs, respectively.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Patien","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 4","pages":"1371-1383"},"PeriodicalIF":4.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082220/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144094816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors predicting early recurrence in patients with unresectable stage III non-small cell lung cancer on durvalumab consolidation after chemoradiotherapy.","authors":"Ji Eun Park, Chanmi Kim, Sun Ha Choi, Jong Geol Jang, Kyung Soo Hong, Yong Shik Kwon, Keum-Ju Choi, Jung Seop Eom, Saerom Kim, Hee Yun Seol, Jehun Kim, Insu Kim, Jin Han Park, Tae Hoon Kim, June Hong Ahn","doi":"10.21037/tlcr-2024-1112","DOIUrl":"10.21037/tlcr-2024-1112","url":null,"abstract":"<p><strong>Background: </strong>Durvalumab consolidation after concurrent chemoradiotherapy (CCRT) is the present standard of care for patients with unresectable stage III non-small cell lung cancer (NSCLC). However, some patients experience early recurrence. This study sought risk factors for early recurrence during durvalumab consolidation.</p><p><strong>Methods: </strong>This retrospective multicenter study was conducted between September 2017 and September 2022. We categorized patients into early and non-early recurrence groups. Early recurrence was defined as recurrence within 6 months after the first dose of durvalumab.</p><p><strong>Results: </strong>Of the 222 patients, 40 (18.0%) experienced early recurrence and 182 (82.0%) experienced non-early recurrence. The former group was younger than the latter group (P=0.02). Patients exhibiting lower-level programmed cell death-ligand 1 (PD-L1) expression were more likely to experience early recurrence (P=0.02). Stage IIIC patients tended to experience more early recurrence than stage IIIA/IIIB patients (P=0.055). Multivariate analyses revealed that older age [odds ratio (OR), 0.945; 95% confidence interval (CI): 0.902-0.991; P=0.02] and PD-L1 level ≥50% (OR, 0.303; 95% CI: 0.125-0.736; P=0.008) protected against early recurrence in NSCLC patients on durvalumab consolidation. Median overall survival was significantly longer in the non-early recurrence group than in the early recurrence group (non-evaluable <i>vs.</i> 11.0 months, respectively; P<0.001).</p><p><strong>Conclusions: </strong>Younger age and lower PD-L1 expression predicted early recurrence during durvalumab consolidation after CCRT. Careful follow-up of such patients is essential.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 4","pages":"1149-1157"},"PeriodicalIF":4.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082245/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144094858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>SMARCA4</i> deficiency: implications for non-small cell lung cancer and management strategies, with relevance to and distinctions from thoracic undifferentiated tumor.","authors":"Xin Zou, Xiaoqing Zhou, Xian Guo, Lei Pan, Wangping Li","doi":"10.21037/tlcr-24-927","DOIUrl":"10.21037/tlcr-24-927","url":null,"abstract":"<p><p>In 2021, the fifth edition of the World Health Organization (WHO) classification of thoracic tumors introduced a new category, \"Thoracic <i>SMARCA4</i>-deficient undifferentiated tumor\", highlighting <i>SMARCA4</i> deficiency as a key molecular marker for classifying as \"other pulmonary epithelial tumors\". <i>SMARCA4</i> is a gene encoding a protein involved in chromatin remodeling, and approximately 8% of non-small cell lung cancer (NSCLC) patients exhibit <i>SMARCA4</i> deletions. These patients are more prone to drug resistance, early recurrence, and unfavorable clinical outcomes. Moreover, NSCLC patients with concomitant <i>SMARCA4</i> mutations may not benefit from currently available treatments, underscoring the distinctiveness of this subgroup. Thoracic <i>SMARCA4</i>-deficient undifferentiated tumors (<i>SMARCA4</i>-UT) represent distinct entities from <i>SMARCA4</i>-deficient non-small cell lung cancer (<i>SMARCA4</i>-dNSCLC). This distinction is supported by their divergent pathological characteristics, demographic profiles, and survival outcomes. NSCLC cases deficient in <i>SMARCA4</i> exhibit high malignancy, yet the precise biological mechanisms underlying this phenomenon remain under intensive investigation. Pathological examination and immunohistochemistry can effectively differentiate <i>SMARCA4</i>-UT from <i>SMARCA4</i>-dNSCLC. <i>SMARCA4</i>-UT typically manifests as adenocarcinoma or, more rarely, as squamous cell carcinoma with undifferentiated rhabdomyoblastic morphology. Therefore, elucidating the mechanisms underlying <i>SMARCA4</i> alterations in NSCLC and their regulatory roles in tumorigenesis and the microenvironment is crucial. This article aims to discuss the structure, biological functions, significance in NSCLC development, and emerging potential therapeutic strategies related to <i>SMARCA4</i> while providing clinical practice guidance for NSCLC patients with <i>SMARCA4</i> deletions.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 4","pages":"1456-1470"},"PeriodicalIF":4.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082232/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144094988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of the effectiveness of alectinib versus crizotinib followed by alectinib in patients with ALK-positive advanced non-small-cell lung cancer in real-world setting and in the ALEX study.","authors":"Xue Yang, Yutao Liu, Gen Lin, Jinliang Wang, Yudong Wang, Yan Zhang, Qinxiang Guo, Fei Liang, Jun Zhao, Bo Jin, Xiaorong Dong","doi":"10.21037/tlcr-24-898","DOIUrl":"10.21037/tlcr-24-898","url":null,"abstract":"<p><strong>Background: </strong>Alectinib has been established as a standard of care for patients with treatment-naive anaplastic lymphoma kinase-rearranged (ALK-positive) advanced non-small-cell lung cancer (NSCLC); however, it has rarely been compared with the sequential approach (crizotinib followed by alectinib) in China. This study aimed to compare real-world alectinib upfront data with either real-world sequential approach data or clinical trial first-line alectinib data.</p><p><strong>Methods: </strong>The patients who received alectinib in the real-world setting were monitored from August 2016 to November 2020. The patients' characteristics were well balanced using the inverse probability of treatment weighting (IPTW) method. Real-world progression-free survival (rwPFS), real-world overall survival (rwOS), and real-world intracranial progression-free survival (rwiPFS) were calculated. To compare the effectiveness of alectinib in real-world setting with that in the ALEX study, data from the ALEX study were analyzed.</p><p><strong>Results: </strong>This study included 311 patients who were divided into three groups: alectinib group (n=102), sequential group (n=63), and alectinib group in ALEX (n=146). The rwPFS and rwOS were similar between the alectinib and sequential groups. However, alectinib group was associated with a lower risk of central nervous system progression than sequential group. Compared with alectinib group in ALEX, the alectinib group in the real world had a significantly longer PFS [hazard ratio (HR), 0.57; 95% confidence interval (CI): 0.37-0.89; P=0.01] and OS (HR, 0.42; 95% CI: 0.21-0.82; P=0.01) after IPTW.</p><p><strong>Conclusions: </strong>Our real world data suggested that sequential group was associated with a higher risk of progression in the brain than the alectinib upfront treatment. However, both treatments had similar survival in advanced ALK-positive NSCLC. Patients with advanced ALK-positive NSCLC in the real-world setting had significantly improved outcomes than those in the ALEX study.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 4","pages":"1158-1167"},"PeriodicalIF":4.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082225/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144095008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning model for predicting spread through air spaces of lung adenocarcinoma based on transfer learning mechanism.","authors":"Jia-Ning Zhang, Zhuo-Fu Li, Sun-Yi Zheng, Jiao-Jiao Li, Lei-Na Sun, Zhao-Xiang Ye","doi":"10.21037/tlcr-24-985","DOIUrl":"10.21037/tlcr-24-985","url":null,"abstract":"<p><strong>Background: </strong>Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma (LUAD) associated with poor prognosis. Preoperative predicting of STAS helps choose an appropriate surgical and therapeutic strategy. This study aimed to develop and validate an STAS prediction model in LUAD based on deep learning algorithms.</p><p><strong>Methods: </strong>A dataset of 290 patients with preoperative chest computed tomography (CT) images and confirmed STAS status was retrospectively selected. Optimal semantic features were selected by logistic regression. Image features were learned from cubic patches containing lung tumors and the area around the tumor within 5/10/15 mm extracted from CT scans. ResNet50 architecture was used to train deep learning models based on the transfer learning mechanism. The optimal semantic features are combined with the deep learning model to construct a hybrid model. Receiver operating characteristic (ROC) curves were used to evaluate the performance.</p><p><strong>Results: </strong>Patients were randomly partitioned into a training set (70%, n=203) and a test set (30%, n=87). The International Association for the Study of Lung Cancer (IASLC) grade, maximum tumor diameter, tumor density, spiculated sign, vacuole sign, and peritumor obstructive inflammation were incorporated into the hybrid model as independent predictors. The STAS-HYBRID_t10 proved to be the optimal STAS prediction model with an area under the curve (AUC) value of 0.874 in the training set and 0.801 in the test set. The sensitivity, specificity, and accuracy of STAS-HYBRID_t10 were 0.659/0.526, 0.904/0.837, and 0.798/0.701 in the training set and test set, respectively.</p><p><strong>Conclusions: </strong>The STAS-HYBRID_t10 has great potential for the preoperative prediction of STAS and may support decision-making for surgical and therapeutic planning in LUAD.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 4","pages":"1061-1075"},"PeriodicalIF":4.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082249/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144095010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prevalence of <i>EGFR</i> gene mutations in patients with early-stage resectable non-small cell lung cancer in Spain: the ORIGEN study.","authors":"Mar Varela, Cristina Teixidó, Carlos Álvarez-Fernández, Hugo Arasanz, Sergio Peralta, Martín Lázaro, Virginia Calvo, Rosa Álvarez, Javier Baena, Javier Valdivia, Edurne Arriola, Reyes Bernabé, Dolores Isla, Carmen Camacho, Bartomeu Massutí, Ana Blasco, Teresa García, Manuel Cobo, Marc Campayo, Sara Hijazo-Pechero, Ángel Callejo, Marta Domínguez, Ernest Nadal","doi":"10.21037/tlcr-2024-1146","DOIUrl":"10.21037/tlcr-2024-1146","url":null,"abstract":"<p><strong>Background: </strong>Geographic variability in epidermal growth factor receptor (<i>EGFR</i>) mutation rates in early-stage non-small cell lung cancer (NSCLC) has been reported. However, the frequency of <i>EGFR</i> mutations in patients with early-stage resected NSCLC in Spain has not been previously investigated. We aimed to determine the prevalence of <i>EGFR</i> mutations in patients with early-stage resected NSCLC in Spain.</p><p><strong>Methods: </strong>This was an observational, multicenter, cross-sectional study. Sensitizing <i>EGFR</i> mutations were assessed via real-time polymerase chain reaction (PCR)-based molecular analysis with the Idylla^TM EGFR Mutation Test, and next-generation sequencing (NGS) analysis with the Oncomine^TM Precision Assay.</p><p><strong>Results: </strong>A total of 172 patients with surgically resected non-squamous NSCLC were analysed. Median age was 67.5 years and 57.6% were male, 96.5% had adenocarcinoma histology and 65% had stage IA/IB. <i>EGFR</i> mutations were found using Idylla^TM EGFR Mutation Test in 25 patients out of 172 patients (14.5%), which consisted of exon 19 deletion in 13 patients (7.6%), exon 21 L858R point mutation in 11 (6.4%), and exon 20 mutation (T790M) in 1 (0.6%) patient. The Oncomine^TM test was conducted in 128 patients, which detected exon 19 deletions in 10 patients (7.8%), exon 21 mutations in 10 patients (7.8%), and exon 20 insertions in 5 (3.9%) patients. The Oncomine^TM test was able to detect concurrent mutations in tumor suppressor genes (<i>TP53, PI3KCA, CDKN2A, PTEN</i>) and another actionable alteration beyond <i>EGFR</i>, such as mutations in <i>KRAS G12C</i> (22%), <i>ERBB2</i> (6%), <i>METex14</i> (2%), <i>BRAF V600E</i> (2%) and <i>ALK</i> and <i>ROS1</i> fusions (2%, each).</p><p><strong>Conclusions: </strong>The prevalence of <i>EGFR</i> mutations in early stage (IA-IIIB), resectable, non-squamous NSCLC observed in our study is consistent with that reported in advanced NSCLC in Spain. Molecular testing is crucial in early-stage NSCLC and can be performed either with single-gene testing or NGS.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 4","pages":"1254-1265"},"PeriodicalIF":4.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082214/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144095012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical application of minimal residual disease detection by ctDNA testing in non-small cell lung cancer: a narrative review.","authors":"Yishan Wang, Wenjun Shao, Hui Li, Peiyan Zhao, Lin Tian, Liang Zhang, Shaowei Lan, Rui Zhong, Shuang Zhang, Ying Cheng","doi":"10.21037/tlcr-24-942","DOIUrl":"https://doi.org/10.21037/tlcr-24-942","url":null,"abstract":"<p><strong>Background and objective: </strong>In recent years, significant advancements have been achieved in the treatment of non-small cell lung cancer (NSCLC), leading to prolonged patient survival; however, a subset of NSCLC patients may experience recurrence or distant metastasis following initial successful treatment. This phenomenon may be attributed to the presence of minimal residual disease (MRD) that remains undetectable by conventional imaging or laboratory techniques post-treatment. The potential sources of tumor recurrence (MRD), are significantly associated with adverse patient prognosis; therefore, the monitoring of these lesions is critically important in the management of NSCLC. This review seeks to examine the current evidence regarding the application of MRD in NSCLC clinical practice, as well as the challenges encountered in its role as a biomarker.</p><p><strong>Methods: </strong>We performed a narrative review by systematically searching the PubMed and Web of Science databases for pertinent literature published from 2005 to 2024, with the objective of identifying significant literature related to clinical research and detection techniques for MRD in NSCLC.</p><p><strong>Key content and findings: </strong>The detection of circulating tumor DNA (ctDNA) for MRD has emerged as a significant focus in high-sensitivity genetic testing for monitoring NSCLC. This method may facilitate the assessment of recurrence risk in NSCLC and inform clinical decision-making to identify high-risk patients who are likely to benefit from treatment, thereby providing a rationale for treatment escalation or de-escalation. Nevertheless, the clinical application of ctDNA MRD continues to encounter several challenges, among which improving detection sensitivity and selecting the best detection timing are urgent issues that need to be addressed.</p><p><strong>Conclusions: </strong>ctDNA MRD testing offers robust evidence to assist clinicians in the early identification of NSCLC recurrence and in guiding clinical treatment. We recommend integrating ctDNA MRD with traditional biomarkers and imaging modalities for a comprehensive evaluation aiming at optimizing treatment strategies.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":"14 3","pages":"1007-1020"},"PeriodicalIF":4.0,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12000943/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144020193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}