Tumor-derived apoptotic extracellular vesicle-mediated intercellular communication promotes metastasis and stemness of lung adenocarcinoma.

Apoptosis has long been recognized as a significant mechanism for inhibiting tumor formation, and a plethora of stimuli can induce apoptosis during the progression and treatment of tumors. Moreover, tumor-derived apoptotic extracellular vesicles (apoEVs) are inevitably phagocytosed by live tumor cells, promoting tumor heterogeneity. Understanding the mechanism by which apoEVs regulate tumor cells is imperative for enhancing our knowledge of tumor metastasis and recurrence. Herein, we conducted a series of in vivo and in vitro experiments, and we report that tumor-derived apoEVs promoted lung adenocarcinoma (LUAD) metastasis, self-renewal and chemoresistance. Mechanistically, we demonstrated that apoEVs facilitated tumor metastasis and stemness by initiating the epithelial-mesenchymal transition program and upregulating the transcription of the stem cell factor SOX2. In addition, we found that ALDH1A1, which was transported by apoEVs, activated the NF-κB signaling pathway by increasing aldehyde dehydrogenase enzyme activity in recipient tumor cells. Furthermore, targeting apoEVs-ALDH1A1 significantly abrogated these effects. Collectively, our findings elucidate a novel mechanism of apoEV-dependent intercellular communication between apoptotic tumor cells and live tumor cells that promotes the formation of cancer stem cell-like populations, and these findings reveal that apoEVs-ALDH1A1 may be a potential therapeutic target and biomarker for LUAD metastasis and recurrence.

Association Between Metabolic Syndrome and the Risk of Lung Cancer: A Meta-Analysis.

Previous studies showed conflicting results regarding the association between metabolic syndrome (MetS) and risk of lung cancer. We performed a systemic review and meta-analysis to determine the relationship between MetS and lung cancer incidence and mortality in adults. Longitudinal follow-up studies were identified by search of Medline, Embase, Cochrane Library, and Web of Science. By incorporating potential heterogeneity into the model, a randomized-effects model was selected to pool the results. Fourteen observational studies were included. Pooled results showed that MetS was associated with a higher risk of lung cancer incidence [risk ratio (RR): 1.15, 95% confidence interval (CI): 1.05 to 1.26, p=0.002; I2=89%). Subgroup analysis suggested that the association was not significantly affected by study country, design, sex of the participants, adjustment of smoking, or different study quality scores (p for subgroup difference all>0.05). The association was predominantly contributed by studies with MetS defined by the National Cholesterol Education Program Adult Treatment Panel-III rather than those with MetS defined by the International Diabetes Foundation criteria, and the association seemed to be stronger in studies with follow-up within 6 years than those over 6 years (p for subgroup difference=0.03 and 0.04, respectively). In addition, pooled results also showed that MetS was associated with a higher risk of lung cancer mortality (RR: 1.46, 95% CI: 1.19 to 1.79, p <0.001; I2=0%). In conclusion, in adult population, MetS may be a risk factor of lung cancer incidence and mortality.

Elevated levels of neutrophil related chemokine citrullinated histone H3, interleukin-8 and C-reaction protein in patients with immune checkpoint inhibitor therapy: predictive biomarkers for response to treatment.

BACKGROUND: Immune checkpoint inhibitor (ICI) therapy has been used in various tumors. The biomarkers predictive of a response to ICI treatment remain unclear, and additional and combined biomarkers are urgently needed. Secreted factors related to the tumor microenvironment (TME) have been evaluated to identify novel noninvasive predictive biomarkers. METHODS: We analyzed 85 patients undergoing ICI therapy as the primary cohort. The associations between ICI response and all biomarkers were evaluated. A prediction model and a nomogram were developed and validated based on the above factors. RESULTS: Seventy-seven patients were enrolled in the validation cohort. In the primary cohort, the baseline serum levels of H3Cit, IL-8 and CRP were significantly higher in nonresponder patients. A model based on these three factors was developed, and the "risk score" of an ICI response was calculated with the formula: "risk score" = 3.4591×H3Cit + 2.5808×IL8 + 2.0045 ×CRP- 11.3844. The cutoff point of the "risk score" was 0.528, and patients with a "risk score" lower than 0.528 were more likely to benefit from ICI treatment (AUC: 0.937, 95% CI: 0.886-0.988, with sensitivity 80.60%, specificity 91.40%). The AUC was 0.719 (95% CI: 0.600-0.837, P = 0.001), with a sensitivity of 70.00% and specificity of 65.20% in the validation cohort. CONCLUSIONS: A model incorporating H3Cit, IL-8 and CRP has an excellent prediction ability for ICI response; thus, patients with a lower "risk score" selectively benefit from ICI treatment, which may have significant clinical implications for the early detection of an ICI response.

SERPINB5 is a prognostic biomarker and promotes proliferation, metastasis and epithelial-mesenchymal transition (EMT) in lung adenocarcinoma.

BACKGROUND: Serine protease inhibitors clade B serpins (SERPINBs) are the largest subclass of protease inhibitors, once thought of as a tumor suppressor gene family. However, some SERPINBs exhibit functions unrelated to the inhibition of catalytic activity. METHODS: The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Gene Set Cancer Analysis (GSCA), and cBioPortal databases were utilized to investigate SERPINBs expression, prognostic correlation, and genomic variation in 33 cancer types. We also conducted a comprehensive transcriptome analysis in multiple lung adenocarcinoma (LUAD) cohorts to reveal the molecular mechanism of SERPINB5 in LUAD. Then, qPCR and immunohistochemistry were used to verify the expression and prognostic value of SERPINB5 in LUAD patients. Furthermore, knockdown and overexpression of SERPINB5 in LUAD cell lines were performed to evaluate cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT). RESULTS: The expression of SERPINB5 was upregulated and demethylated in LUAD, and its abnormally high expression was significantly correlated with poor overall survival (OS). In addition, the expression of SERPINB5 was analyzed to determine its prognostic value in LUAD and confirmed that SERPINB5 was an independent predictor of LUAD in TCGA and GEO cohorts and qPCR validation with 106 clinical samples. At last, A knockdown of SERPINB5 in LUAD cells reduced proliferation, migration, and EMT. Proliferation, migration, and invasion are promoted by the overexpression of SERPINB5. CONCLUSION: Therefore, SERPINB5 has shown potential as a prognostic biomarker for LUAD, and it may become a potential therapeutic target for lung adenocarcinoma.

Intrinsic Immunogenic Tumor Cell Death Subtypes Delineate Prognosis and Responsiveness to Immunotherapy in Lung Adenocarcinoma.

Recent studies have highlighted the combination of activation of host immunogenic cell death (ICD) and tumor-directed cytotoxic strategies. However, overall multiomic analysis of the intrinsic ICD property in lung adenocarcinoma (LUAD) has not been performed. Therefore, the aim of this study was to develop an ICD-based risk scoring system to predict overall survival (OS) and immunotherapeutic efficacy in patients. In our study, both weighted gene co-expression network analysis (WGCNA) and LASSO-Cox analysis were utilized to identify ICDrisk subtypes (ICDrisk). Moreover, we identify genomic alterations and differences in biological processes, analyze the immune microenvironment, and predict the response to immunotherapy in patients with pan-cancer. Importantly, immunogenicity subgroup typing was performed based on the immune score (IS) and microenvironmental tumor neoantigens (meTNAs). Our results demonstrate that ICDrisk subtypes were identified based on 16 genes. Furthermore, high ICDrisk was proved to be a poor prognostic factor in LUAD patients and indicated poor efficacy of immune checkpoint inhibitor (ICI) treatment in patients with pan-cancer. The two ICDrisk subtypes displayed distinct clinicopathologic features, tumor-infiltrating immune cell patterns, and biological processes. The ISlowmeTNAhigh subtype showed low intratumoral heterogeneity (ITH) and immune-activated phenotypes and correlated with better survival than the other subtypes within the high ICDrisk group. This study suggests effective biomarkers for the prediction of OS in LUAD patients and immunotherapeutic response across Pan-cancer and contributes to enhancing our understanding of intrinsic immunogenic tumor cell death.

The independent prognostic effect of marital status on non-small cell lung cancer patients: a population-based study.

Background: Previous studies had demonstrated that marital status was an independent prognostic factor in multiple cancers. However, the impact of marital status on non-small cell lung cancer (NSCLC) patients was still highly controversial. Method: All NSCLC patients diagnosed between 2010-2016 were selected from the Surveillance, Epidemiology and End Results (SEER) database. To control the confounding effect of related clinicopathological characteristics, propensity score matching (PSM) was conducted between married and unmarried groups. In addition, independent prognostic clinicopathological factors were evaluated via Cox proportional hazard regression. Moreover, nomograms were established based on the clinicopathological characteristics, and the predictive accuracy was assessed by calibration curves. Furthermore, decision curve analysis (DCA) was used to determine the clinical benefits. Results: In total, 58,424 NSCLC patients were enrolled according to the selection criteria. After PSM, 20,148 patients were selected into each group for further analysis. The married group consistently demonstrated significantly better OS and CSS compared to unmarried group [OS median survival (95% CI): 25 (24-26) vs. 22 (21-23) months, p < 0.001; CSS median survival (95% CI): 31 (30-32) vs. 27 (26-28) months, p < 0.001]. Moreover, single patients were associated with the worst OS [median survival (95% CI): 20 (19-22) months] and CSS [median survival (95%CI): 24 (23-25) months] among unmarried subgroups. Besides, unmarried patients had a significantly worse prognosis compared to married patients in both univariate and multivariate Cox proportional hazard regressions. Furthermore, married group was associated with better survival in most subgroups. To predict the 1-, 3- and 5-year OS and CSS probabilities, nomograms were established based on age, race, sex, gender, marital status, histology, grade, TNM stage. The C-index for OS and CSS were 0.759 and 0.779. And the calibration curves showed significant agreement between predictive risk and the observed probability. DCA indicated nomograms had consistently better predict performance. Conclusion: This study demonstrated that unmarried NSCLC patients were associated with significantly worse OS and CSS compared to married NSCLC patients. Therefore, unmarried patients need not only closer surveillance, but also more social and family support, which may improve patients' adherence and compliance, and eventually improve the survival.

Ten-year trends of the clinicopathological characteristics, surgical treatments and survival outcomes of operable lung cancer patients in monocenter: a retrospective cohort study.

Background: Lung cancer is one of the cancers with the highest morbidity and mortality. During the last decade, the trends of clinical characteristics, surgical treatments and survival of lung cancer patients in China have remained unclear. Methods: All lung cancer patients operated on from 2011 to 2020 were identified in a prospectively maintained database of Sun Yat-sen University Cancer Center. Results: A total of 7,800 lung cancer patients were included in this study. Within the past 10 years, the average age at diagnosis of the patients remained stable, the proportion of asymptomatic, female and nonsmoking patients increased, and the average tumor size decreased from 3.766 to 2.300 cm. In addition, the proportion of early stage and adenocarcinoma increased, while that of squamous cell carcinoma decreased. Among the patients, the proportion of patients having video-assisted thoracic surgery increased. More than 80% of the patients underwent lobectomy and systematic nodal dissection over the 10 years. Additionally, both the average postoperative length of stay and 1-, 3-, and 6-month postoperative mortality decreased. Moreover, the 1-, 3-, and 5-year overall survival (OS) rates of all the operable patients increased from 89.8, 73.9, and 63.8% to 99.6, 90.7, and 80.8%, respectively. The 5-year OS rates of the patients with stage I, II, and III lung cancer were 87.6, 79.9, and 59.9%, respectively, which were higher than those in other published data. Conclusion: There were significant changes in the clinicopathological characteristics, surgical treatments and survival outcomes of the patients with operable lung cancer from 2011 to 2020.

Ferroptosis-related lncRNAs signature to predict the survival and immune evasion for lung squamous cell carcinoma.

Introduction: the investigation on the interactions between ferroptosis and lncRNAs for lung squamous cell carcinoma (LUSC) has been scare, and its impact on tumor immune microenvironment remained unknown. We aim to not only identify a ferroptosis-related lncRNAs signature for LUSC prognosis, but also evaluate its correlation to tumor immune evasion. Methods: RNA sequencing data and survival information were obtained from The Cancer Genome Atlas database. A ferroptosis-related lncRNAs signature (FerRLSig) was developed and validated by univariate Cox regression, Least Absolute Shrinkage and Selection Operator regression and multivariate Cox regression. The tumor immune microenvironment and immune evasion were subsequently evaluated based on the FerRLSig stratification. Results: the FerRLSig consisted of 10 ferroptosis-related lncRNAs and significantly associated with overall survival with satisfactory area under curve (HR = 2.240, 95% CI: 1.845-2.720, p < 0.001, 5-years AUC: 0.756). Based on the FerRLSig stratification, the high-risk group demonstrated not only significantly higher immune infiltration, but also more profound T cell dysfunction and immune evasion, which might ultimately lead to the resistance to current immune checkpoint inhibitors. Conclusion: a robust prognostic FerRLSig for LUSC has been developed and validated, demonstrating a close association not only with tumor immune cell infiltration, but also with T cell dysfunction and immune evasion. Further investigation is warranted to better improve the survival of LUSC patients based on the FerRLSig stratification.

A tumor microenvironment gene set-Based prognostic signature for non-small-cell lung cancer.

Background: The tumor microenvironment (TME) is involved in the development and progression of lung carcinomas. A deeper understanding of TME landscape would offer insight into prognostic biomarkers and potential therapeutic targets investigation. To this end, we aimed to identify the TME components of lung cancer and develop a prognostic signature to predict overall survival (OS). Methods: Expression data was retrieved from The Cancer Genome Atlas (TCGA) database and differentially expressed TME-related genes were calculated between tumor and normal tissues. Then nonnegative matrix factorization (NMF) clustering was used to identify two distinct subtypes. Results: Our analysis yielded a gene panel consisting of seven TME-related genes as candidate signature set. With this panel, our model showed that the high-risk group experienced a shorter survival time. This model was further validated by an independent cohort with data from Gene Expression Omnibus (GEO) database (GSE50081 and GSE13213). Additionally, we integrated the clinical factors and risk score to construct a nomogram for predicting prognosis. Our data suggested less immune cells infiltration but more fibroblasts were found in tumor tissues derived from patients at high-risk and those patients exhibited a worse immunotherapy response. Conclusion: The signature set proposed in this work could be an effective model for estimating OS in lung cancer patients. Hopefully analysis of the TME could have the potential to provide novel diagnostic, prognostic and therapeutic opportunities.

Mutation-Derived Long Noncoding RNA Signature Predicts Survival in Lung Adenocarcinoma.

Background: Genomic instability is one of the representative features of cancer evolution. Recent research has revealed that long noncoding RNAs (lncRNAs) play a critical role in maintaining genomic instability. Our work proposed a gene signature (GILncSig) based on genomic instability-derived lncRNAs to probe the possibility of lncRNA signatures as an index of genomic instability, providing a potential new approach to identify genomic instability-related cancer biomarkers. Methods: Lung adenocarcinoma (LUAD) gene expression data from an RNA-seq FPKM dataset, somatic mutation information and relevant clinical materials were downloaded from The Cancer Genome Atlas (TCGA). A prognostic model consisting of genomic instability-related lncRNAs was constructed, termed GILncSig, to calculate the risk score. We validated GILncSig using data from the Gene Expression Omnibus (GEO) database. In this study, we used R software for data analysis. Results: Through univariate and multivariate Cox regression analyses, five genomic instability-associated lncRNAs (LINC01671, LINC01116, LINC01214, lncRNA PTCSC3, and LINC02555) were identified. We constructed a lncRNA signature (GILncSig) related to genomic instability. LUAD patients were classified into two risk groups by GILncSig. The results showed that the survival rate of LUAD patients in the low-risk group was higher than that of those in the high-risk group. Then, we verified GILncSig in the GEO database. GILncSig was associated with the genomic mutation rate of LUAD. We also used GILncSig to divide TP53 mutant-type patients and TP53 wild-type patients into two groups and performed prognostic analysis. The results suggested that compared with TP53 mutation status, GILncSig may have better prognostic significance. Conclusions: By combining the lncRNA expression profiles associated with somatic mutations and the corresponding clinical characteristics of LUAD, a lncRNA signature (GILncSig) related to genomic instability was established.

Analysis of the tumor immune environment identifies an immune gene set-based prognostic signature in non-small cell lung cancer.

BACKGROUND: The tumor immune environment plays a critical role in lung cancer initiation and prognosis. Therefore, understanding how the tumor immune environment impacts the overall survival (OS) of patients with advanced lung cancer post immunotherapy is of great importance. In this article, we aimed to identify the immune components of lung cancer and develop an immune prognostic signature to predict OS. METHODS: Differentially expressed immune-related genes were calculated between tumor and normal tissues using expression data from The Cancer Genome Atlas (TCGA) database. Then univariate Cox regression analysis was conducted to select prognosis-related genes and the prognostic risk model was constructed by multivariate Cox regression analysis. Patient risk scores were calculated, and a clinical correlation analysis was performed within the risk model. In addition, immune cell infiltration patterns were identified to find the immune cell subtypes related to prognosis. RESULTS: A gene model consisting of 12 immune-related genes was used as our signature. The model showed that the high-risk group experienced a shorter survival time, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.733. High-risk immune genes, such as S100 calcium binding protein A16 (S100A16) and angiopoietin-like 4 (ANGPTL4), were associated with more malignant clinical manifestations. Further, we discovered that extensive infiltration of B cells, dendritic cells, and mast cells indicated a favorable prognosis. CONCLUSIONS: The signature developed in this paper could be an effective model for estimating OS in lung cancer patients, and the immune cell infiltration analysis of the tumor immune microenvironment could shed light on more effective treatment in clinical practice.

The Independent Prognostic Effect of Lymph Node Dissection on Patients With Stage IA NSCLC With Different T Stages.

Background: Currently, the extent of lymph node evaluation necessary for patients with early-stage non-small-cell lung cancer (NSCLC) remains controversial according to the latest ESMO and NCCN guidelines. In this study, we aimed to evaluate the survival effect of different numbers of lymph nodes examined (LNE) and regions of lymph nodes removed (LNR) in patients with stage IA NSCLC. Method: All patients with stage IA NSCLC undergoing lobectomy or bilobectomy were selected from the surveillance, epidemiology, and end results (SEER) database. The number of LNE and LNR were stratified into 4 groups (0, 1-2, 3-8, and ≥9 lymph nodes) and 3 groups (0, 1-3, and ≥4 regions) respectively. Additionally, the survival curves of overall survival (OS) and cancer-specific survival (CSS) were plotted and compared with the Kaplan-Meier method and log-rank test. Independent prognostic clinicopathological factors were evaluated via Cox proportional hazard regression and subgroup analysis. Results: Totally, 12,490 patients with stage IA NSCLC were enrolled in our study. Patients with ≥9 LNE and ≥4 LNR in both the T1b and T1c stages consistently demonstrated the significantly best OS and CSS outcomes. In the multivariate analysis, patients with ≥9 LNE consistently had a significantly better CSS [hazards ration (HR) (95% CI):0.539 (0.438-0.663)], and those with ≥4 LNR consistently had a significantly better OS [HR (95% CI):0.678 (0.476-0.966)]. Furthermore, ≥9 LNE and ≥4 LNR were associated with better survival in most subgroups. Conclusion: This study demonstrated that ≥9 LNE and ≥4 LNR are highly recommended for stage IA2 and stage IA3 patients but optional for stage IA1 patients.

Development and validation of a prediction model for lung adenocarcinoma based on RNA-binding protein.

BACKGROUND: RNA-binding proteins (RBPs) have been found to participate in the development and progression of cancer. This present study aimed to construct a RBP-based prognostic prediction model for lung adenocarcinoma (LUAD). METHODS: RNA sequencing data and corresponding clinical information were acquired from The Cancer Genome Atlas (TCGA) and served as a training set. The prediction model was validated using the dataset in Gene Expression Omnibus (GEO) databases. Univariate and multivariate Cox regression analyses were conducted to identify the RBPs associated with survival. R software (http://www.r-project.org) was used for analysis in this study. RESULTS: Nine hub prognostic RBPs (CIRBP, DARS2, DDX24, GAPDH, LARP6, SNRPE, WDR3, ZC3H12C, ZC3H12D) were identified by univariate Cox regression analysis and multivariate Cox regression analysis. Using a risk score based on the nine-hub RBP model, we separated the LUAD patients into a low-risk group and a high-risk group. The outcomes revealed that patients in the high-risk group had poorer survival than those in the low-risk group. This signature was validated in the GEO database. Further study revealed that the risk score can be an independent prognostic biomarker for LUAD. A nomogram based on the nine hub RBPs was built to quantitatively predict the prognosis of LUAD patients. CONCLUSIONS: Our nine-gene signature model could be used as a marker to predict the prognosis of LUAD and has potential for use in treatment individualization.

Segmental resection is associated with decreased survival in patients with stage IA non-small cell lung cancer with a tumor size of 21-30 mm.

BACKGROUND: The feasibility of segmental resection for early-stage non-small cell lung cancer (NSCLC) is still controversial. This study aimed to compare survival outcomes following lobectomy and segmental resection in patients with pathological T1cN0M0 (tumor size 21-30 mm) NSCLC. METHODS: Patients diagnosed between 1998 and 2016 with pathological stage IA NSCLC and with tumors measuring 21-30 mm were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The observational outcomes were cancer-specific survival (CSS) and overall survival (OS) at 5 years. Univariate survival analysis was carried out to identify potential prognostic factors of prolonged survival. Cox proportional hazards model was used to adjust for confounding factors. Additionally, pairwise comparisons were conducted between lobectomy and segmental resection for CSS and OS, and forest plots were drawn. RESULTS: Of the 9,580 patients analyzed, 400 patients (4.2%) underwent segmental resections. Patients with older age (P<0.001), smaller tumors (P<0.001), and left-sided tumors (P=0.002) were more likely to receive segmental resection. No difference was found in the operative mortality rates between the segmental resection group and the lobectomy group (1.0% vs. 1.2%, P=0.707). The CSS (HR, 1.429; 95% CI, 1.166-1.752; P=0.001) and OS (HR, 1.348; 95% CI, 1.176-1.544; P<0.001) in the segmental resection group were significantly worse than those in the lobectomy group. Subgroup analyses by age, year of diagnosis, sex, tumor size, histology, grade, and the number of dissected lymph nodes also confirmed that lobectomy was associated with improved CSS and OS. CONCLUSIONS: Lobectomy and thorough removal of lymph nodes should continue to be the recommended standard of care for patients with surgically resectable stage IA NSCLC with tumor size of 21-30 mm.

Development and validation of a preoperative noninvasive predictive model based on circular tumor DNA for lymph node metastasis in resectable non-small cell lung cancer.

BACKGROUND: Clinical lymph node staging in resectable non-small cell lung cancer (NSCLC) patients not only indicates prognosis, but also determines primary treatment strategy. The demand of noninvasive tool for preoperative lymph node metastasis prediction remains significant. This study aimed to develop and externally validate a preoperative noninvasive predictive model based on circular tumor DNA (ctDNA) for the lymph node metastasis in resectable NSCLC patients. METHODS: Resectable NSCLC patients in TRACERx cohort were included as training group. Potential preoperative noninvasively accessible predictors were incorporated into the development of a nomogram via multivariate logistic regression. The predictive model was externally validated by a similar cohort from our hospital. RESULTS: Overall, 58 patients from TRACERx cohort were included as training group and 37 patients from our hospital were included as external validation group. Variant allele frequency (VAF) level of ctDNA was significantly associated with lymph node metastasis (OR: 4.89, 95% CI: 1.22-19.54, P=0.03). The predictive model incorporating age, tumor size and VAF demonstrated satisfactory discrimination and calibration in both training group (AUC =0.77, 95% CI: 0.65-0.90, P=0.001) and external validation group (AUC =0.84, 95% CI: 0.70-0.99, P=0.005). CONCLUSIONS: High VAF level in preoperative ctDNA may indicate lymph node metastasis of resectable NSCLC. And a preoperative noninvasive predictive model based on ctDNA for the lymph node metastasis in resectable NSCLC patients was developed and externally validated with satisfactory discrimination and calibration.

Extent of resection and lymph node evaluation in early stage metachronous second primary lung cancer: a population-based study.

BACKGROUND: Evidence of the optimal surgery strategy for early stage metachronous second primary lung cancer (SPLC) has been limited and controversial. This study aims to compare the survival outcomes of different extents of resection and lymph node evaluation in these patients. METHODS: Early stage metachronous SPLC patients, who had received lobectomy for initial primary lung cancer (IPLC) and developed SPLC more than 3 months later, were selected from the Surveillance, Epidemiology, and End Results (SEER) database according to the American College of Chest Physicians (ACCP) guideline. Overall survival (OS) and lung cancer-specific survival (CSS) of different extents of resection and lymph node evaluation were analyzed using Kaplan-Meier method and multivariate Cox regression model. RESULTS: Overall, 1,784 SPLC patients without nodal or distant metastasis were identified. Lobectomy was associated with significantly longer OS (HR: 0.83, 95% CI: 0.71-0.97, 5-year survival: 59.2% vs. 53.3%, P=0.02) and CSS (HR: 0.72, 95% CI: 0.60-0.88, 5-year survival: 71.5% vs. 63.2%, P=0.001) compared with sublobar resection. In addition, examined lymph node number ≥10 demonstrated longer OS (HR: 0.63, 95% CI: 0.50-0.81, 5-year survival: 66.6% vs. 53.9%, P<0.001) and CSS (HR: 0.54, 95% CI: 0.40-0.74, 5-year survival: 77.4% vs. 64.7%, P<0.001) compared with an examined lymph node number <10. The survival benefits of lobectomy and examined lymph node number ≥10 were further validated in multivariate Cox regression and subgroup analysis stratified by tumor size. CONCLUSIONS: Lobectomy and thorough lymph node evaluation provided significantly longer survival, and thus should be considered for early stage metachronous SPLC whenever possible.

Alpha-l-fucosidase: a novel serum biomarker to predict prognosis in early stage esophageal squamous cell carcinoma.

BACKGROUND: Alpha-l-fucosidase (AFU) not only detects hepatocellular carcinoma (HCC) early but also is used as a clinical prognostic indicator of several malignant tumors. However, no study has investigated the prognostic significance of AFU in a cohort of patients with esophageal squamous cell carcinomas (ESCCs). METHODS: A retrospective dataset that included 160 consecutive patients with early stage (pT1N0) ESCC who received surgery between January 2005 and December 2012 was analyzed to identify the prognostic value of serum AFU for overall survival (OS) by using Kaplan-Meier analysis and Cox multivariate regression modeling. RESULTS: The level of serum AFU ranged from 6.2 to 77.0 U/L with a median of 19.9 U/L, and the best cutoff point for OS was 17.95 U/L. Analysis by Pearson's correlation showed that the levels of serum ALT and GGT were both positively correlated with the level of serum AFU (r=0.403, P<0.001 and r=0.264, P=0.001, respectively). After adjusting for significant factors identified by univariate analysis, the Cox multivariate regression model indicated that a young age (<65 years), no history of alcohol consumption, and a low AFU level (≤17.95 U/L) were still significantly associated with longer OS (P=0.008, 0.004 and 0.017, respectively). The 5-year and 10-year OS rates for patients with high AFU levels vs. low AFU levels were 76.2% vs. 86.0%, and, 46.7% vs. 83.4%, respectively. CONCLUSIONS: Compared with other serum biomarkers, AFU showed a better prognostic value for long-term survival in patients with early stage ESCC.

Combining Plasma miRNAs and Computed Tomography Features to Differentiate the Nature of Pulmonary Nodules.

Objective: The purpose of this study was to evaluate the diagnostic efficiency of combining plasma microRNAs (miRNAs) and computed tomography (CT) features in the diagnosis of pulmonary nodules. Methods: Ninety-two pulmonary nodule patients who had undergone surgery were enrolled in our study from July 2016 to March 2018 at the Sun Yat-sen University Cancer Center. A prediction model was established by combining 3 miRNAs (miRNA-146a, -200b, and -7) and CT features to identify the pulmonary nodules of these patients. We evaluated the diagnostic performance of this prediction model for pulmonary nodules using the Receiver Operating Characteristic (ROC) curve. Results: The expression levels of miRNA-146a, -200b, and -7 in early-stage non-small cell lung cancer (NSCLC) patients are significantly higher than those in benign nodule patients. We used these three miRNAs and CT features (pleural indentation and speculation) to establish a prediction model for early-stage NSCLC, with a sensitivity and specificity of 92.9%, 83.3% in the training set, respectively. For the validation process, with the sensitivity of 71.8% and the specificity of 69.2%. For ROC curve analyses, area under the curve (AUC) for tumor identification in the training stage and validation stage were 0.929 and 0.781, respectively. Conclusion: Plasma miRNA-146a, miRNA-200b, and miRNA-7 may be potential biomarkers for the early diagnosis of lung cancer. Our prediction model can help to identify the nature of pulmonary nodules with a relatively high diagnostic efficiency.

Resection of Early-Stage Second Primary Non-small Cell Lung Cancer After Small Cell Lung Cancer: A Population-Based Study.

Introduction: A certain number of small cell lung cancer (SCLC) patients become long-term survivors after treatment, and they are at high risk to develop a second primary malignancy, including non-small cell lung cancer. However, the optimal management of early-stage second primary non-small cell lung cancer (SPLC) after SCLC remains unknown. This study aims to evaluate the survival benefits of surgery in these patients. Methods: Patients with early-stage SPLC after SCLC were identified from the Surveillance, Epidemiology, and End Results database. Patients were balanced with propensity score matching (PSM). Overall survival (OS) and lung cancer-specific survival (CSS) were compared between non-surgery group and surgery group with the Kaplan-Meier method and Cox multivariate regressions. Results: A total of 228 patients with early-stage SPLC after SCLC were identified. Surgery was associated with significantly improved OS and CSS in the multivariate Cox regression analysis (OS, 5-year survival: 41.2 vs. 11.6%, HR: 0.42, 95% CI: 0.31-0.59, P < 0.01; CSS, 5-year survival: 46.8 vs. 24.3%, HR: 0.53, 95% CI: 0.37-0.75, P < 0.01). However, no statistically significant survival difference was found between sublobar resection and lobectomy (OS, 5-year survival: 41.0 vs. 45.3%, P = 0.73; CSS, 5-year survival: 43.5 vs. 54.1%, P = 0.49). After 1:1 PSM, 162 patients were selected for further analysis, and surgery continued to demonstrate superior survival (OS, 5-year survival: 44.2 vs. 7.2%, HR: 0.48, 95% CI: 0.33-0.70, P < 0.01; CSS, 5-year survival: 48.0 vs. 20.6%, HR: 0.44, 95% CI: 0.42-0.97, P = 0.03). Conclusion: The resection of early-stage SPLC after SCLC led to significantly improved OS and CSS and therefore should be considered whenever possible. Nevertheless, further randomized controlled trials are warranted to investigate the safety and effect of surgery in these patients.