Translational lung cancer research最新文献

{"title":"Neutrophil estimation and prognosis analysis based on existing lung squamous cell carcinoma datasets: the development and validation of a prognosis prediction model.","authors":"Youyu Wang, Dongfang Li, Qiang Li, Alina Basnet, Jimmy T Efird, Nobuhiko Seki","doi":"10.21037/tlcr-24-411","DOIUrl":"https://doi.org/10.21037/tlcr-24-411","url":null,"abstract":"<p><strong>Background: </strong>Notwithstanding the rapid developments in precision medicine in recent years, lung cancer still has a low survival rate, especially lung squamous cell cancer (LUSC). The tumor microenvironment (TME) plays an important role in the progression of lung cancer, in which high neutrophil levels are correlated with poor prognosis, potentially due to their interactions with tumor cells via pro-inflammatory cytokines and chemokines. However, the precise mechanisms of how neutrophils influence lung cancer remain unclear. This study aims to explore these mechanisms and develop a prognosis predictive model in LUSC, addressing the knowledge gap in neutrophil-related cancer pathogenesis.</p><p><strong>Methods: </strong>LUSC datasets from the Xena Hub and Gene Expression Omnibus (GEO) databases were used, comprising 473 tumor samples and 195 tumor samples, respectively. Neutrophil contents in these samples were estimated using CIBERSORT, xCell, and microenvironment cell populations (MCP) counter tools. Differentially expressed genes (DEGs) were identified using DEseq2, and a weighted gene co-expression network analysis (WGCNA) was performed to identify neutrophil-related genes. A least absolute shrinkage and selection operator (LASSO) Cox regression model was constructed for prognosis prediction, and the model's accuracy was validated using Kaplan-Meier survival curves and time-dependent receiver operating characteristic (ROC) curves. Additionally, genomic changes, immune correlations, drug sensitivity, and immunotherapy response were analyzed to further validate the model's predictive power.</p><p><strong>Results: </strong>Neutrophil content was significantly higher in adjacent normal tissue compared to LUSC tissue (P<0.001). High neutrophil content was associated with worse overall survival (OS) (P=0.02), disease-free survival (DFS) (P=0.02), and progression-free survival (PFS) (P=0.03) using different software estimates. Nine gene modules were identified, with blue and yellow modules showing strong correlations with neutrophil prognosis (P<0.001). Eight genes were selected for the prognostic model, which accurately predicted 1-, 3-, and 5-year survival in both the training set [area under the curve (AUC) value =0.60, 0.63, 0.66, respectively] and validation set (AUC value =0.58, 0.58, 0.59, respectively), with significant prognosis differences between high- and low-risk groups (P<0.001). The model's independent prognostic factors included risk group, pathologic M stage, and tumor stage (P<0.05). A further molecular mechanism analysis revealed differences between risk groups were revealed in immune checkpoint and human leukocyte antigen (HLA) gene expression, hallmark pathways, drug sensitivity, and immunotherapy responses.</p><p><strong>Conclusions: </strong>This study established a risk-score model that effectively predicts the prognosis of LUSC patients and sheds light on the molecular mechanisms involved. The findings enhan","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11384491/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142296337","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 features and prognostic biomarkers in patients with <i>SMARCA4</i>-mutated non-small cell lung cancer.","authors":"Jinyu Long, Ying Chen, Xingguang Luo, Ruiying Rao, Chenxi Wang, Yuxin Guo, Jinhe Xu, Ping Lin, Yingfang Song, Lijuan Qu, Qinghong Liu, Jun Lu, Chengzhi Zhou, Zhengbo Song, Xiandong Lin, Hiroyuki Adachi, Jacek Jassem, Masatsugu Hamaji, Zongyang Yu","doi":"10.21037/tlcr-24-381","DOIUrl":"https://doi.org/10.21037/tlcr-24-381","url":null,"abstract":"<p><strong>Background: </strong>Patients with non-small cell lung cancer (NSCLC) carrying <i>SMARCA4</i> mutations (<i>SMARCA4</i>-Mut) tend to have more advanced disease and a poor prognosis. However, due to the rarity of this mutation and the lack of related studies, the characteristics of <i>SMARCA4</i>-Mut NSCLC patients remains poorly determined. To clarify the clinical characteristics and prognostic factors of <i>SMARCA4</i>-Mut NSCLC, we initiated the present study to provide a clinical reference.</p><p><strong>Methods: </strong>We used data from two cohorts of NSCLC-<i>SMARCA4</i>-mutated samples: The Cancer Genome Atlas (TCGA) database and our center's clinical data. The TCGA database was used to obtain 481 NSCLC-<i>SMARCA4</i>-Mut samples for clinical characterization. The center collected data on 224 consecutive NSCLC patients treated between December 2020 to July 2022. Among them, 26 harbored <i>SMARCA4</i> mutations, and 20 were eligible for inclusion in the study. Clinical, pathological, and molecular features, as well as prognostic role of <i>SMARCA4</i> mutations were analyzed. Additionally, we analyzed the prognostic impact of Napsin A expression in <i>SMARCA4</i>-Mut patients.</p><p><strong>Results: </strong>The TCGA database included 480 patients with <i>SMARCA4</i>-Mut NSCLC, 311 males (64.8%) and 169 females (35.2%), with a median age of 67 years. Among the 20 <i>SMARCA4</i>-Mut patients in our center series, 12 (60%) were males and 8 (40%) females, with a median age of 63. The intergroup prognostic correlation analysis showed that <i>SMARCA4</i>-Mut patients had significantly worse prognosis than those the wild-type <i>SMARCA4</i> (<i>SMARCA4</i>-WT) (P=0.04). Within the <i>SMARCA4</i>-Mut group, patients with Napsin A expression had longer overall survival (OS) (P=0.03) than those without expression. Median survival in the Napsin A-positive and negative groups was 32 and 15 months, respectively. According to time-dependent receiver operating curve analysis, patients with Napsin A expression had significantly longer first-line treatment progression-free survival (PFS1) [area under the curve (AUC) =0.748] and OS (AUC =0.586). No prognostic value of Napsin A was found in patients <i>SMARCA4</i>-WT patients.</p><p><strong>Conclusions: </strong><i>SMARCA4</i>-Mut is an adverse prognostic feature in NSCLC patients. Napsin A expression in <i>SMARCA4</i>-Mut patients is associated with prolonged OS.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11384479/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142296323","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":"Single-center clinical experience of extended sleeve lobectomy (ESL) versus standard sleeve lobectomy (SL).","authors":"Haoyou Wang, Wei Wang, Peng Zu, Gregor J Kocher, Mara B Antonoff, Alberto Lopez-Pastorini, Chenlei Zhang, Wei Chen, Hongxu Liu","doi":"10.21037/tlcr-24-546","DOIUrl":"https://doi.org/10.21037/tlcr-24-546","url":null,"abstract":"<p><strong>Background: </strong>Sleeve lobectomy (SL) and extended SL (ESL), which aim to preserve pulmonary function and enhance the quality of life of patients while ensuring oncological outcomes, are valuable surgical options for the treatment of centrally located non-small cell lung cancer (NSCLC). This study aimed to compare perioperative adverse events and long-term survival between SL and ESL in NSCLC patients, providing a comprehensive review of surgical outcomes, complications, and survival to assess the roles of SL and ESL in thoracic oncology.</p><p><strong>Methods: </strong>This single-center retrospective study assessed the outcomes of NSCLC patients who underwent SL or ESL from June 2014 to January 2022. The patients were selected based on specific inclusion criteria, and statistical analyses were conducted to examine the postoperative outcomes, overall survival (OS), and disease-free survival (DFS) of the patients.</p><p><strong>Results: </strong>A total of 218 patients met the inclusion criteria. Among 218 patients, 33 underwent ESL and 185 underwent SL. Compared to SL, ESL was associated with longer operative times and higher R0 resection rates (93.9% <i>vs</i>. 78.8%, P=0.047). Despite the higher complexity of ESL compared to SL, there were no significant differences in the perioperative complications or mortality rates between the groups. Survival analysis was conducted on the propensity score matching (PSM) data, the results demonstrated superior OS and DFS in the ESL group compared to the SL group. Advanced age, more advanced nodal (N) status, and non-R0 resection were significant predictors of poorer prognosis.</p><p><strong>Conclusions: </strong>ESL is a feasible and effective alternative for treating centrally located NSCLC, with better R0 resection rates and comparable survival outcomes to SL, without increasing the risk of grade III-IV complications. Further studies with larger cohorts need to be conducted to validate these findings and refine the surgical techniques.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11384477/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142296346","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":"Breaking barriers: patient-derived xenograft (PDX) models in lung cancer drug development-are we close to the finish line?","authors":"Nagla Abdel Karim, Mohamed Zaza, Janakiraman Subramanian","doi":"10.21037/tlcr-24-206","DOIUrl":"https://doi.org/10.21037/tlcr-24-206","url":null,"abstract":"","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11384481/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142296321","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":"Redefining YAP1 in small cell lung cancer: shifting from a dominant subtype marker to a favorable prognostic indicator.","authors":"Se-Il Go, Jung Wook Yang, Eun Jeong Jeong, Woo Je Lee, Sungwoo Park, Dae Hyun Song, Gyeong-Won Lee","doi":"10.21037/tlcr-24-317","DOIUrl":"https://doi.org/10.21037/tlcr-24-317","url":null,"abstract":"<p><strong>Background: </strong>Molecular and transcription factor subtyping were recently introduced to identify patients with unique clinical features in small cell lung cancer (SCLC). However, its prognostic relevance is yet to be established. This study aims to investigate the clinical implications and prognostic significance of transcription factor subtyping in SCLC using immunohistochemistry.</p><p><strong>Methods: </strong>One hundred and ninety consecutive SCLC patients treated with platinum-based chemotherapy at a single institution were retrospectively reviewed. Expression of ASCL1, NeuroD1, POU2F3, and YAP1 was assessed by immunohistochemical staining and applied to determine the transcription factor subtype of each case.</p><p><strong>Results: </strong>The association among transcription factors was not entirely mutually exclusive. YAP1 expression was the most significant prognostic indicator compared with other transcription factors or their related subtypes. Among patients with limited-stage disease (LD), complete response (CR) rates were 46.2% and 22.4% in the YAP1-positive and YAP1-negative groups, respectively. The median duration of response among patients who achieved CR was 64.8 and 36.4 months in the YAP1-positive and YAP1-negative groups, respectively (P=0.06). Median overall survival (OS) in LD was 35.6 and 16.9 months in the YAP1-positive and YAP1-negative groups, respectively (P=0.03). In extensive-stage disease (ED), the median OS was 11.3 months for the YAP1-positive group and 11 months for the YAP1-negative group (P=0.03).</p><p><strong>Conclusions: </strong>Positive expression of YAP1 can be associated with durable CR and favorable survival outcomes in patients with SCLC, especially in LD.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11384494/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142296342","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":"Assessing the transportability of radiomic models for lung cancer diagnosis: commercial <i>vs.</i> open-source feature extractors.","authors":"David Xiao, Michael N Kammer, Heidi Chen, Palina Woodhouse, Kim L Sandler, Anna E Baron, David O Wilson, Ehab Billatos, Jiantao Pu, Fabien Maldonado, Stephen A Deppen, Eric L Grogan","doi":"10.21037/tlcr-24-281","DOIUrl":"https://doi.org/10.21037/tlcr-24-281","url":null,"abstract":"<p><strong>Background: </strong>Radiomics has shown promise in improving malignancy risk stratification of indeterminate pulmonary nodules (IPNs) with many platforms available, but with no head-to-head comparisons. This study aimed to evaluate transportability of radiomic models across platforms by comparing performances of a commercial radiomic feature extractor (HealthMyne) with an open-source extractor (PyRadiomics) on diagnosis of lung cancer in IPNs.</p><p><strong>Methods: </strong>A commercial radiomic feature extractor was used to segment IPNs from computed tomography (CT) scans, and a previously validated radiomic model based on commercial features was used as baseline (ComRad). Using same segmentation masks, PyRadiomics, an open-source feature extractor was used to build three open-source radiomic models (OpenRad) using different methods: <i>de novo</i> open-source model derived using least absolute shrinkage and selection operator (LASSO) for feature selection, selecting open-source features matched to ComRad features based upon Imaging Biomarker Standardization Initiative (IBSI) nomenclature, and selecting open-source features most highly correlated to ComRad features. Radiomic models were trained on an internal cohort (n=161) and externally validated on 3 cohorts (n=278). We added Mayo clinical risk score to OpenRad and ComRad models, creating integrated clinical radiomic (ClinRad) models. All models were compared using area under the curve (AUC) and evaluated for clinical improvement using bias-corrected clinical net reclassification indices (cNRIs).</p><p><strong>Results: </strong>ComRad AUC was 0.76 [95% confidence interval (CI): 0.71-0.82], and OpenRad AUC was 0.75 (95% CI: 0.69-0.81) for LASSO model, 0.74 (95% CI: 0.68-0.79) for Spearman's correlation, and 0.71 (95% CI: 0.65-0.77) for IBSI. Mayo scores were added to OpenRad LASSO model, which performed best, forming open-source ClinRad model with AUC of 0.80 (95% CI: 0.74-0.86), identical to commercial ClinRad's AUC. Both ClinRad models showed clinical improvement compared to Mayo alone, with commercial ClinRad achieving cNRI of 0.09 (95% CI: 0.02-0.15) for benign and 0.07 (95% CI: 0.00-0.13) for malignant, and open-source ClinRad achieving cNRI of 0.09 (95% CI: 0.02-0.15) for benign and 0.06 (95% CI: 0.00-0.12) for malignant.</p><p><strong>Conclusions: </strong>Transportability of radiomic models across platforms directly does not conserve performance, but radiomic platforms can provide equivalent results when building <i>de novo</i> models allowing for flexibility in feature selection to maximize prediction accuracy.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11384473/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142296320","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":"Radiogenomics models for predicting prognosis in locally advanced non-small cell lung cancer patients undergoing definitive chemoradiotherapy.","authors":"Xiaoyu Song, Li Li, Qingxi Yu, Ning Liu, Shouhui Zhu, Shuanghu Yuan","doi":"10.21037/tlcr-24-145","DOIUrl":"https://doi.org/10.21037/tlcr-24-145","url":null,"abstract":"<p><strong>Background: </strong>Definitive chemoradiotherapy (dCRT) is the cornerstone for locally advanced non-small cell lung cancer (LA-NSCLC). The study aimed to construct a multi-omics model integrating baseline clinical data, computed tomography (CT) images and genetic information to predict the prognosis of dCRT in LA-NSCLC patients.</p><p><strong>Methods: </strong>The study retrospectively enrolled 105 stage III LA-NSCLC patients who had undergone dCRT. The pre-treatment CT images were collected, and the primary tumor was delineated as a region of interest (ROI) on the image using 3D-Slicer, and the radiomics features were extracted. The least absolute shrinkage and selection operator (LASSO) was employed for dimensionality reduction and selection of features. Genomic information was obtained from the baseline tumor tissue samples. We then constructed a multi-omics model by combining baseline clinical data, radiomics and genomics features. The predictive performance of the model was evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC) and the concordance index (C-index).</p><p><strong>Results: </strong>The median follow-up time was 30.1 months, and the median progression-free survival (PFS) was 10.60 months. Four features were applied to construct the radiomics model. Multivariable analysis demonstrated the Rad-score, <i>KEAP1</i> and <i>MET</i> mutations were independent prognostic factors for PFS. The C-index of radiomics model, genomics model and radiogenomics model all performed well in the training group (0.590 <i>vs.</i> 0.606 <i>vs.</i> 0.663) and the validation group (0.599 <i>vs.</i> 0.594 <i>vs.</i> 0.650).</p><p><strong>Conclusions: </strong>The radiomics model, genomics model and radiogenomics model can all predict the prognosis of dCRT for LA-NSCLC, and the radiogenomics model is superior to the single type model.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11384488/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142296341","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":"Prognostic and predictive significance of soluble programmed death ligand 1 in bronchoalveolar lavage fluid in stage IV non-small cell lung cancer.","authors":"So-Yun Kim, Dongil Park, Pureum Sun, Nayoung Kim, Dahye Lee, Duk Ki Kim, Song-I Lee, Jeong Eun Lee, Chaeuk Chung, Da Hyun Kang","doi":"10.21037/tlcr-24-392","DOIUrl":"https://doi.org/10.21037/tlcr-24-392","url":null,"abstract":"<p><strong>Background: </strong>Patients with non-small cell lung cancer (NSCLC) have been shown to exhibit elevated levels of soluble programmed death-ligand 1 (sPD-L1) in the blood, associated with poor survival in NSCLC. The bronchoalveolar lavage fluid (BALF) composition reflects the tumor microenvironment of lung cancer. In this study, we investigated sPD-L1 levels in BALF and its role as a prognostic and predictive marker in patients with stage IV NSCLC.</p><p><strong>Methods: </strong>We prospectively obtained BALF from lung cancer patients who underwent bronchoscopy between January 2020 and September 2022 at Chungnam National University Hospital (CNUH). Finally, 94 NSCLC stage IV patients were included in this study. Soluble PD-L1 levels in BALF were measured using a human PD-L1 Quantikine ELISA kit.</p><p><strong>Results: </strong>The correlation between PD-L1 expression in tumor cells and sPD-L1 in BALF was weakly positive (rho =0.314, P=0.002). The median overall survival (OS) of the low sPD-L1 in BALF group was 16.47 months [95% confidence interval (CI): 11.15-21.79 months], which is significantly longer than 8.87 months (95% CI: 0.0-19.88 months, P=0.001) in the high sPD-L1 in BALF group. In 64 patients treated with or without immune checkpoint inhibitors (ICIs), sPD-L1 in BALF was significantly associated with progression-free survival (PFS) and OS. In the subgroup analysis of 31 patients treated with ICI, the objective response rate (ORR) in the low sPD-L1 BALF group was significantly higher than in high sPD-L1 in BALF group (ORR: 60.9% <i>vs.</i> 12.5%, P=0.02).</p><p><strong>Conclusions: </strong>Soluble PD-L1 in BALF is a potential prognostic indicator for patients with stage IV NSCLC and a predictive marker for ICI treatment response.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11384500/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142296339","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":"CYFRA 21-1 predicts efficacy of combined chemoimmunotherapy in patients with advanced non-small cell lung cancer: a prospective observational study.","authors":"Nobutaka Kataoka, Yuki Katayama, Tadaaki Yamada, Kenji Morimoto, Takayuki Takeda, Asuka Okada, Shinsuke Shiotsu, Yusuke Chihara, Osamu Hiranuma, Takahiro Yamada, Takahiro Ota, Taishi Harada, Isao Hasegawa, Naoya Nishioka, Masahiro Iwasaku, Shinsaku Tokuda, Koichi Takayama","doi":"10.21037/tlcr-24-190","DOIUrl":"https://doi.org/10.21037/tlcr-24-190","url":null,"abstract":"<p><strong>Background: </strong>Tumor markers such as serum carcinoembryonic antigen (CEA) and cytokeratin fragment 19 (CYFRA 21-1) are utilized for assessing the effectiveness of chemotherapy in non-small cell lung cancer (NSCLC) patients. Yet, it remains uncertain whether these markers can reliably forecast responses to combined chemoimmunotherapy. Our study aimed to examine the significance and effectiveness of these markers in predicting responses among NSCLC patients undergoing combined chemoimmunotherapy.</p><p><strong>Methods: </strong>This two-part observational study involved patients with NSCLC who were treated with combined chemoimmunotherapy in Japanese hospitals. An initial retrospective study of these patients, with serum CEA and CYFRA 21-1 as prognostic factors for combined chemoimmunotherapy outcomes, served as a discovery cohort. Patients in a subsequent prospective study served as a validation cohort, where we assessed the prognostic accuracy of CEA and CYFRA 21-1 cut-off points determined by the discovery cohort.</p><p><strong>Results: </strong>In total, 121 patients treated with combined chemoimmunotherapy were included, with 44 and 77 patients in the discovery and validation cohorts, respectively. Serum CYFRA 21-1 levels >3.0 ng/mL were significantly associated with progression-free survival (PFS) in both the discovery and validation cohorts (P=0.01, P=0.04, respectively). PFS did not differ significantly by CEA levels (P=0.21).</p><p><strong>Conclusions: </strong>After combined chemoimmunotherapy treatment, serum CYFRA 21-1 stands out as a potentially valuable biomarker for predicting the prognosis of NSCLC.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11384485/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142296326","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":"Emphysema and lung cancer risk.","authors":"Agata Durawa, Katarzyna Dziadziuszko, Małgorzata Jelitto, Michał Gąsiorowski, Mariusz Kaszubowski, Edyta Szurowska, Witold Rzyman","doi":"10.21037/tlcr-24-197","DOIUrl":"https://doi.org/10.21037/tlcr-24-197","url":null,"abstract":"<p><strong>Background: </strong>With increasing significance of lung cancer screening programs, it is essential to determine the group of participants, who would benefit the most from screening. In our study, we aimed to establish the correlation between lung emphysema and lung cancer risk.</p><p><strong>Methods: </strong>The study design was cross-sectional. Low-dose computed tomography (LDCT) scans of 896 subjects from MOLTEST-BIS lung cancer screening program, including 100 subjects with detected lung cancer, were visually evaluated for the presence, type and severity of emphysema. Quantitative emphysema evaluation was performed with Siemens syngo.via Pulmo 3D application.</p><p><strong>Results: </strong>Visually detected presence of centrilobular emphysema (CLE) correlated with male gender (P=0.02), age (P<0.001) and pack-years of smoking (P=0.004), as well as with quantitative assessment of Emphysema Index (EI) (P=0.008), and with emphysema clusters of given size (Clas 1-4) Clas 1, Clas 3 and Clas 4 (P<0.001). Visually assessed severity grade of emphysema correlated with age (P<0.001), pack-years of smoking history (P=0.002) and EI (P<0.001). There was a correlation between lung cancer occurrence and pack-years (P<0.001), age (P<0.001), and presence of CLE (P<0.001) but no correlation with gender (P=0.88) and EI (P=0.32) was found. In the logistic regression model pack-years, age, qualitative severity of CLE and Clas 1 were significant factors correlated with lung cancer occurrence (P<0.001).</p><p><strong>Conclusions: </strong>Qualitative and quantitative emphysema evaluation correlate with each other. Both, presence and severity of CLE correlate with higher incidence of lung cancer. Severity of visually assessed emphysema, age and pack-years of smoking are significant predictors of lung cancer occurrence.</p>","PeriodicalId":23271,"journal":{"name":"Translational lung cancer research","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11384496/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142296331","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}