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Abstract Background Non-small cell lung cancer (NSCLC) is the primary reason for cancer-related deaths globally. Tertiary lymphoid structure (TLS) is an organized collection of immune cells acquired in non-physiological, non-lymphoid tissues. High expression of TLS in tumor tissues is generally associated with better prognosis. This research aimed to investigate the prognostic and clinicopathological significance of TLS in patients with NSCLC. Methods A comprehensive literature search was conducted based on Pubmed, EMBASE, and Cochrane Library databases to identify eligible studies published up to December 8, 2023. The prognostic significance and clinicopathological value of TLS in NSCLC were evaluated by calculating the combined hazard ratios (HRs) and odds ratios (ORs) and their 95% confidence intervals (CIs). Following that, additional analyses, including subgroup analysis and sensitivity analysis, were conducted. Results This meta-analysis evaluated the prognostic and clinicopathological significance of TLS in 10 studies involving 1,451 patients with NSCLC. The results revealed that the high levels of TLS were strongly associated with better overall survival (OS) (HR = 0.48, 95% CI: 0.35–0.66, p

BackgroundThis study aimed to construct a clinical prediction model and nomogram to differentiate invasive from non-invasive pulmonary adenocarcinoma in solitary pulmonary nodules (SPNs).MethodWe analyzed computed tomography and clinical features as well as preoperative biomarkers in 1,106 patients with SPN who underwent pulmonary resection with definite pathology at Qilu Hospital of Shandong University between January 2020 and December 2021. Clinical parameters and imaging characteristics were analyzed using univariate and multivariate logistic regression analyses. Predictive models and nomograms were developed and their recognition abilities were evaluated using receiver operating characteristic (ROC) curves. The clinical utility of the nomogram was evaluated using decision curve analysis (DCA).ResultThe final regression analysis selected age, carcinoembryonic antigen, bronchus sign, lobulation, pleural adhesion, maximum diameter, and the consolidation-to-tumor ratio as associated factors. The areas under the ROC curves were 0.844 (95% confidence interval [CI], 0.817–0.871) and 0.812 (95% CI, 0.766–0.857) for patients in the training and validation cohorts, respectively. The predictive model calibration curve revealed good calibration for both cohorts. The DCA results confirmed that the clinical prediction model was useful in clinical practice. Bias-corrected C-indices for the training and validation cohorts were 0.844 and 0.814, respectively.ConclusionOur predictive model and nomogram might be useful for guiding clinical decisions regarding personalized surgical intervention and treatment options.

Abstract Background The prognostic significance of adjuvant chemotherapy (ACT) for patients with stage IA micropapillary non-predominant (MPNP) lung adenocarcinoma (LUAD) remains unknown. This study aimed to investigate the effects of postoperative ACT in patients with stage IA MPNP-LUAD. Methods A total of 149 patients with pathological stage IA MPNP-LUAD who underwent surgery at our center were retrospectively analyzed. Propensity score matching (PSM) analysis was conducted to reduce potential selection bias. Kaplan–Meier analyses were used to assess the impact of ACT on recurrence-free survival (RFS), overall survival (OS), and disease-specific survival (DSS). Subgroup analyses were performed for the survival outcomes based on the percentage of micropapillary components. Cox proportional hazards regression analyses were applied to identify risk factors associated with survival. Results The receipt or non-receipt of postoperative ACT had no significant effect on RFS, OS, and DSS among all enrolled patients with stage IA MPNP-LUAD (P > 0.05). For patients with a micropapillary component > 5%, the 5-year rates of RFS, OS, and DSS were significantly higher in the ACT group compared to the observation group, both before and after PSM (P 0.05). The resection range (HR = 0.071; 95% CI: 0.020–0.251; P

Abstract Background Lymphocyte-activation gene 3 (LAG3) is a recently discovered immune checkpoint molecule that has been linked to immunosuppression and the advancement of cancer in different types of solid tumors. This study aimed to evaluate the prognostic importance of LAG3 and its role in the immune system within solid tumors. Methods Extensive literature searches were conducted using the Pubmed, EMBASE, and Cochrane Library databases to identify relevant studies exploring the effect of LAG3 on survival outcomes. Pooled hazard ratios (HRs) with its 95% confidence intervals (CIs) were calculated to evaluate the prognostic values of LAG3. Afterwards, subgroup analysis and sensitivity analysis were conducted. Pan-cancer analysis investigated the possible relationships between LAG3 expression and genetic alterations, RNA methylation modification-related genes, genomic instability, immune checkpoint genes, and infiltration of immune cells. Results A total of 43 studies with 7,118 patients were included in this analysis. Higher expression of LAG3 was associated with worse overall survival (HR = 1.10, 95% CI 1.01–1.19, P = 0.023), but not disease-free survival (HR = 1.41, 95% CI 0.96–2.07, P = 0.078), progression-free survival (HR = 1.12, 95% CI 0.90–1.39, P = 0.317) or recurrence-free survival (HR = 0.98, 95% CI 0.81–1.19, P = 0.871). Subgroup analysis showed that LAG3 might play different prognostic roles in different solid tumors. LAG3 expression was positively associated with immune cell infiltration and immune checkpoint genes in all of the cancers included. LAG3 expression was also found to be associated with microsatellite instability (MSI), copy number variation (CNV), simple nucleoside variation (SNV), tumor mutation burden (TMB), and neoantigen in various types of cancers. Conclusions Elevated expression of LAG3 is linked to poorer prognosis among patients diagnosed with solid cancers. LAG3 might play varying prognostic roles in different types of solid tumors. Given its substantial involvement in cancer immunity and tumorigenesis, LAG3 has garnered attention as a promising prognostic biomarker and a potential target for immunotherapy.

Abstract Background DARS2 expression is upregulated in lung adenocarcinoma (LUAD) which correlates with tumor patient stage and prognosis. The mechanism of DARS2 involvement in LUAD still needs to be further explored. Methods In this study, we found that DARS2 expression in LUAD tissue was significantly higher than that in normal tissue. At the same time, the Kaplan–Meier curve showed that the survival prognosis of LUAD patients with high expression of DARS2 was significantly worse than low expression of DARS2. The expression of DARS2 was detected in LUAD and adjacent normal tissues by IHC staining, histochemical scoring and a survival curve was generated. In addition, we demonstrated that the knockdown and overexpression of DARS2 significantly affected the proliferation, invasion, and migration of LUAD cells in vitro and in vivo. Finally, western blot and rescue assay were performed on LUAD cells to further explore and verify the signaling pathway. Results DARS2 expression was significantly upregulated in LUAD tissues and cell lines. What is more, the increased expression of DARS2 was closely related to proliferation, invasion and metastasis. The tumorigenic assay in nude mice further showed that the tumorigenic ability of nude mice was significantly improved with the increase in DARS2 expression. Finally, we determined that DARS2 plays its role in LUAD by targeting the ERK/c‐Myc signaling pathway. Conclusion Our data revealed the oncogenic role of DARS2 in LUAD, indicating that DARS2 may be a predictive biomarker and novel therapeutic target for LUAD.

BackgroundAt present, how to identify the benign or malignant nature of small (≤ 2 cm) solitary pulmonary nodules (SPN) are an urgent clinical challenge. This retrospective study aimed to develop a clinical prediction model combining clinical and radiological characteristics for assessing the probability of malignancy in SPNs measuring ≤ 2 cm.MethodIn this study, we included patients with SPNs measuring ≤ 2 cm who underwent pulmonary resection with definite pathology at Qilu Hospital of Shandong University from January 2020 to December 2021. Clinical features, preoperative biomarker results, and computed tomography characteristics were collected. The enrolled patients were randomized at a ratio of 7:3 into a training cohort of 775 and a validation cohort of 331. The training cohort was used to construct the predictive model, while the validation cohort was used to test the model independently. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors. The prediction model and nomogram were established based on the independent risk factors. The receiver operating characteristic (ROC) curve was used to evaluate the identification ability of the model. The calibration power was evaluated using the Hosmer–Lemeshow test and calibration curve. The clinical utility of the nomogram was also assessed by decision curve analysis (DCA).ResultA total of 1,106 patients were included in this study. Among them, the malignancy rate of SPNs was 85.08% (941/1,106). We finally identified the following six independent risk factors by logistic regression: age, carcinoembryonic antigen, nodule shape, calcification, maximum diameter, and consolidation-to-tumor ratio. The area under the ROC curve (AUC) for the training cohort was 0.764 (95% confidence interval [CI]: 0.714–0.814), and the AUC for the validation cohort was 0.729 (95% CI: 0.647–0.811), indicating that the prediction accuracy of nomogram was relatively good. The calibration curve of the predictive model also demonstrated a good calibration in both cohorts. DCA proved that the clinical prediction model was useful in clinical practice.ConclusionWe developed and validated a predictive model and nomogram for estimating the probability of malignancy in SPNs measuring ≤ 2 cm. With the application of predictive models, thoracic surgeons can make more rational clinical decisions while avoiding overtreatment and wasting medical resources.

Abstract Background An increasing number of patients are being diagnosed with synchronous multiple primary lung cancer (SMPLC) with the popularization of lung cancer screening programs. However, a strategy for accurate location and suitable surgery therapy is still lacking. The present study aimed to explore the accuracy and feasibility of electromagnetic navigation bronchoscopy (ENB)‐guided thoracoscopic sublobectomy for stage IA SMPLC. Methods Patients with SMPLC who underwent ENB‐guided sublobectomy from January 2020 to June 2022 were enrolled in this study. The analysis of localization accuracy of ENB and surgical outcome was conducted. Results Overall, 138 patients with 353 malignant nodules were enrolled. The tumor size was 0.7 cm (range from 0.5 to 1.1 cm). ENB localization was performed on 162 nodules, and a customized scoring system was developed to evaluate localization accuracy. The success rate of localization was 98.3% (178/181). Notably, localization accuracy was positively correlated with bronchial signs (p

Abstract Background The effectiveness of robotic‐assisted lobectomy (RAL) for patients with non–small‐cell lung cancer (NSCLC) has not been fully evaluated. Methods This retrospective study compared the perioperative outcomes of NSCLC patients who underwent RAL and video‐assisted lobectomy (VAL) using propensity score matching (PSM) analysis. Subgroup analyses were then performed. Results A total of 822 NSCLC patients (359 RAL cases and 463 VAL cases) were included, and there were 292 patients in each group after PSM. Compared with the VAL group, the RAL group had a significantly higher number of lymph nodes (LNs) harvested (10 vs. 8, p

Abstract Background Prolonged air leak (PAL) remains one of the most frequent postoperative complications after pulmonary resection. This study aimed to develop a predictive nomogram to estimate the risk of PAL for individual patients after minimally invasive pulmonary resection. Methods Patients who underwent minimally invasive pulmonary resection for either benign or malignant lung tumors between January 2020 and December 2021 were included. All eligible patients were randomly assigned to the training cohort or validation cohort at a 3:1 ratio. Univariate and multivariate logistic regression were performed to identify independent risk factors. All independent risk factors were incorporated to establish a predictive model and nomogram, and a web-based dynamic nomogram was then built based on the logistic regression model. Nomogram discrimination was assessed using the receiver operating characteristic (ROC) curve. The calibration power was evaluated using the Hosmer-Lemeshow test and calibration curves. The nomogram was also evaluated for clinical utility by the decision curve analysis (DCA). Results A total of 2213 patients were finally enrolled in this study, among whom, 341 cases (15.4%) were confirmed to have PAL. The following eight independent risk factors were identified through logistic regression: age, body mass index (BMI), smoking history, percentage of the predicted value for forced expiratory volume in 1 second (FEV1% predicted), surgical procedure, surgical range, operation side, operation duration. The area under the ROC curve (AUC) was 0.7315 [95% confidence interval (CI): 0.6979–0.7651] for the training cohort and 0.7325 (95% CI: 0.6743–0.7906) for the validation cohort. The P values of the Hosmer-Lemeshow test were 0.388 and 0.577 for the training and validation cohorts, respectively, with well-fitted calibration curves. The DCA demonstrated that the nomogram was clinically useful. An operation interface on a web page ( https://lirongyangql.shinyapps.io/PAL_DynNom/ ) was built to improve the clinical utility of the nomogram. Conclusion The nomogram achieved good predictive performance for PAL after minimally invasive pulmonary resection. Patients at high risk of PAL could be identified using this nomogram, and thus some preventive measures could be adopted in advance.

BackgroundWith the popularity of computed tomography (CT) of the thorax, the rate of diagnosis for patients with early-stage lung cancer has increased. However, distinguishing high-risk pulmonary nodules (HRPNs) from low-risk pulmonary nodules (LRPNs) before surgery remains challenging.MethodsA retrospective analysis was performed on 1064 patients with pulmonary nodules (PNs) admitted to the Qilu Hospital of Shandong University from April to December 2021. Randomization of all eligible patients to either the training or validation cohort was performed in a 3:1 ratio. Eighty-three PNs patients who visited Qianfoshan Hospital in the Shandong Province from January through April of 2022 were included as an external validation. Univariable and multivariable logistic regression (forward stepwise regression) were used to identify independent risk factors, and a predictive model and dynamic web nomogram were constructed by integrating these risk factors.ResultsA total of 895 patients were included, with an incidence of HRPNs of 47.3% (423/895). Logistic regression analysis identified four independent risk factors: the size, consolidation tumor ratio, CT value of PNs, and carcinoembryonic antigen levels in blood. The area under the ROC curves was 0.895, 0.936, and 0.812 for the training, internal validation, and external validation cohorts, respectively. The Hosmer-Lemeshow test demonstrated excellent calibration capability, and the fit of the calibration curve was good. DCA has shown the nomogram to be clinically useful.ConclusionThe nomogram performed well in predicting the likelihood of HRPNs. In addition, it identified HRPNs in patients with PNs, achieved accurate treatment with HRPNs, and is expected to promote their rapid recovery.

Esophageal cancer (EC) is one of the most life-threatening malignancies worldwide. Esophageal squamous cell carcinoma (ESCC) is the dominant subtype, accounting for approximately 90% of new incident EC each year. Although multidisciplinary treatment strategies have advanced rapidly, patients with ESCC are often diagnosed at advanced stage and the long-term prognosis remains unsatisfactory. In recent decades, immunotherapy, such as immune checkpoint inhibitors (ICIs), tumor vaccines, and chimeric antigen receptor T-cell (CAR-T) therapy, has been successfully used in clinical practice as a novel therapy for treating tumors, bringing new hope to ESCC patients. However, only a small fraction of patients achieved clinical benefits due to primary or acquired resistance. Immune evasion plays a pivotal role in the initiation and progression of ESCC. Therefore, a thorough understanding of the mechanisms by which ESCC cells escape from anti-tumor immunity is necessary for a more effective multidisciplinary treatment strategy. It has been widely recognized that immune evasion is closely associated with the crosstalk between tumor cells and the tumor microenvironment (TME). TME is a dynamic complex and comprehensive system including not only cellular components but also non-cellular components, which influence hallmarks and fates of tumor cells from the outside. Novel immunotherapy targeting tumor-favorable TME represents a promising strategy to achieve better therapeutic responses for patients with ESCC. In this review, we provide an overview of immune evasion in ESCC, mainly focusing on the molecular mechanisms that underlie the role of TME in immune evasion of ESCC. In addition, we also discuss the challenges and opportunities of precision therapy for ESCC by targeting TME.

ObjectiveThis study aims to determine the optimal pelvic lymph node dissection (PLND) template for radical cystectomy (RC).MethodsA systematic search was conducted using the PubMed, Embase and Cochrane Library database in December 2021. Articles comparing recurrence-free survival (RFS), disease-specific survival (DSS), overall survival (OS), and postoperative complications among patients undergoing limited PLND (lPLND), standard PLND (sPLND), extended PLND (ePLND), or super-extended PLND (sePLND) were included. A Bayesian approach was used for network meta-analysis.ResultsWe included 18 studies in this systematic review, and 17 studies met our criteria for network meta-analysis. We performed meta-analyses and network meta-analyses to investigate the associations between four PLND templates and the RFS, DSS, OS, or postoperative complications. We found that the ePLND group and the sePLND group were associated with better RFS than the sPLND group (Hazard Ratio [HR]: 0.65, 95% Credible Interval [CrI]: 0.56 to 0.78) (HR: 0.67, 95% CrI: 0.56 to 0.83) and the lPLND group (HR: 0.67, 95% CrI: 0.50 to 0.91) (HR: 0.70, 95% CrI: 0.49 to 0.99). For RFS, Analysis of the treatment ranking revealed that ePLND had the highest probabilities to be the best template. There was no significant difference between the four templates in DSS, however, analysis of the treatment ranking indicated that sePLND had the highest probabilities to be the best template. And We found that the sePLND group and the ePLND group were associated with better OS than lPLND (HR: 0.58, 95% CrI: 0.36 to 0.95) (HR: 0.63, 95% CrI: 0.41 to 0.94). For OS, analysis of the treatment ranking revealed that sePLND had the highest probabilities to be the best template. The results of meta-analyses and network meta-analyses showed that postoperative complications rates did not differ significantly between any two templates.ConclusionPatients undergoing sePLND and ePLND had better RFS but not better DSS or OS than those undergoing lPLND or sPLND templates, however, RFS did not differ between patients undergoing sePLND or ePLND. Considering that sePLND involves longer operation time, higher risk, and greater degree of difficulty than ePLND, and performing sePLND may not result in better prognosis, so it seems that there is no need for seLPND. We think that ePLND might be the optimal PLND template for RC.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42022318475.

BackgroundIn recent years, an increasing number of thoracic surgeons have attempted to apply no routine chest tube drainage (NT) strategy after thoracoscopic lung resection. However, the safety and feasibility of not routinely placing a chest tube after lung resection remain controversial. This study aimed to investigate the effect of NT strategy after thoracoscopic pulmonary resection on perioperative outcomes.MethodsA comprehensive literature search of PubMed, Embase, and the Cochrane Library databases until 3 January 2022 was performed to identify the studies that implemented NT strategy after thoracoscopic pulmonary resection. Perioperative outcomes were extracted by 2 reviewers independently and then synthesized using a random-effects model. Risk ratio (RR) and standardized mean difference (SMD) with 95% confidence interval (CI) served as the summary statistics for meta-analysis. Subgroup analysis and sensitivity analysis were subsequently performed.ResultsA total of 12 studies with 1,381 patients were included. The meta-analysis indicated that patients in the NT group had a significantly reduced postoperative length of stay (LOS) (SMD = -0.91; 95% CI: -1.20 to -0.61; P < 0.001) and pain score on postoperative day (POD) 1 (SMD = -0.95; 95% CI: -1.54 to -0.36; P = 0.002), POD 2 (SMD = -0.37; 95% CI: -0.63 to -0.11; P = 0.005), and POD 3 (SMD = -0.39; 95% CI: -0.71 to -0.06; P = 0.02). Further subgroup analysis showed that the difference of postoperative LOS became statistically insignificant in the lobectomy or segmentectomy subgroup (SMD = -0.30; 95% CI: -0.91 to 0.32; P = 0.34). Although the risk of pneumothorax was significantly higher in the NT group (RR = 1.75; 95% CI: 1.14–2.68; P = 0.01), the reintervention rates were comparable between groups (RR = 1.04; 95% CI: 0.48–2.25; P = 0.92). No significant difference was found in pleural effusion, subcutaneous emphysema, operation time, pain score on POD 7, and wound healing satisfactory (all P > 0.05). The sensitivity analysis suggested that the results of the meta-analysis were stabilized.ConclusionsThis meta-analysis suggested that NT strategy is safe and feasible for selected patients scheduled for video-assisted thoracoscopic pulmonary resection.Systematic Review Registrationhttps://inplasy.com/inplasy-2022-4-0026, identifier INPLASY202240026.

BackgroundWith the widespread adoption of prostatic-specific antigen (PSA) screening, the detection rates of prostate cancer (PCa) have increased. Due to the low specificity and high false-positive rate of serum PSA levels, it was difficult to diagnose PCa accurately. To improve the diagnosis of PCa and clinically significant prostate cancer (CSPCa), we established novel models on the basis of the prostate health index (PHI) and multiparametric magnetic resonance imaging (mpMRI) in the Asian population.MethodsWe retrospectively collected the clinical indicators of patients with TPSA at 4–20 ng/ml. Furthermore, mpMRI was performed using a 3.0-T scanner and reported in the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS). Univariable and multivariable logistic analyses were performed to construct the models. The performance of different models based on PSA derivatives, PHI derivatives, PI-RADS, and a combination of PHI derivatives and PI-RADS was evaluated.ResultsAmong the 128 patients, 47 (36.72%) patients were diagnosed with CSPCa and 81 (63.28%) patients were diagnosed with non-CSPCa. Of the 81 (63.28%) patients, 8 (6.25%) patients were diagnosed with Gleason Grade 1 PCa and 73 (57.03%) patients were diagnosed with non-PCa. In the analysis of the receiver operator characteristic (ROC) curves in TPSA 4–20 ng/ml, the multivariable model for PCa was significantly larger than that for the model based on the PI-RADS (p = 0.004) and that for the model based on the PHI derivatives (p = 0.031) in diagnostic accuracy. The multivariable model for CSPCa was significantly larger than that for the model based on the PI-RADS (p = 0.003) and was non-significantly larger than that for the model based on the PHI derivatives (p = 0.061) in diagnostic accuracy. For PCa in TPSA 4–20 ng/ml, a multivariable model achieved the optimal diagnostic value at four levels of predictive variables. For CSPCa in TPSA 4–20 ng/ml, the multivariable model achieved the optimal diagnostic value at a sensitivity close to 90% and 80%.ConclusionsThe models combining PHI derivatives and PI-RADS performed better in detecting PCa and CSPCa than the models based on either PHI or PI-RADS.

BackgroundThe efficacy of sublobar resection and selective lymph node dissection is gradually being accepted by thoracic surgeons for patients within early-stage non-small cell lung cancer (NSCLC). Nevertheless, there are still some NSCLC patients develop lymphatic metastasis at clinical T1 stage. Lung adenocarcinoma with a micropapillary (MP) component poses a higher risk of lymph node metastasis and recurrence even when the MP component is not predominant. Our study aimed to explore the genetic features and occult lymph node metastasis (OLNM) risk factors in patients with a non-predominant micropapillary component (NP-MPC) in a large of patient’s cohort with surgically resected lung adenocarcinoma.MethodsBetween January 2019 and December 2021, 6418 patients who underwent complete resection for primary lung adenocarcinoma at the Qilu Hospital of Shandong University. In our study, 442 patients diagnosed with lung adenocarcinoma with NP-MPC with a tumor size ≤3 cm were included. Genetic alterations were analyzed using amplification refractory mutation system-polymerase chain reaction (ARMS-PCR). Abnormal protein expression of gene mutations was validated using immunohistochemistry. A nomogram risk model based on clinicopathological parameters was developed to predict OLNM. This model was invalidated using the calibration plot and concordance index.ResultsIn our retrospective cohort, the incidence rate of the micropapillary component was 11.17%, and OLNM was observed in 20.13% of the patients in our study. ARMS-PCR suggested that EGFR exon 19 del was the most frequent alteration in NP-MCP patients compared with other gene mutations (frequency: 21.2%, P