Molecular subtypes of neuroendocrine carcinomas: A cross-tissue classification framework based on five transcriptional regulators.

Neuroendocrine carcinomas (NECs) are extremely lethal malignancies that can arise at almost any anatomic site. Characterization of NECs is hindered by their rarity and significant inter- and intra-tissue heterogeneity. Herein, through an integrative analysis of over 1,000 NECs originating from 31 various tissues, we reveal their tissue-independent convergence and further unveil molecular divergence driven by distinct transcriptional regulators. Pan-tissue NECs are therefore categorized into five intrinsic subtypes defined by ASCL1, NEUROD1, HNF4A, POU2F3, and YAP1. A comprehensive portrait of these subtypes is depicted, highlighting subtype-specific transcriptional programs, genomic alterations, evolution trajectories, therapeutic vulnerabilities, and clinicopathological presentations. Notably, the newly discovered HNF4A-dominated subtype-H exhibits a gastrointestinal-like signature, wild-type RB1, unique neuroendocrine differentiation, poor chemotherapeutic response, and prevalent large-cell morphology. The proposal of uniform classification paradigm illuminates transcriptional basis of NEC heterogeneity and bridges the gap across different lineages and cytomorphological variants, in which context-dependent prevalence of subtypes underlies their phenotypic disparities.

Patterns and prognostic values of programmed cell death-ligand 1 expression and CD8+ T-cell infiltration in small cell carcinoma of the esophagus: a retrospective analysis of 34 years of National Cancer Center data in China.

BACKGROUND: Small cell carcinoma of the esophagus (SCCE) is an extremely rare and highly aggressive neuroendocrine malignancy with a strikingly poor prognosis. Given the great clinical successes of checkpoint immunotherapies, we explored the expression profile and clinical significance of programmed cell death-ligand 1 (PD-L1) and CD8+ T cell in SCCE for the first time. MATERIALS AND METHODS: Tumor-infiltrating immune cells (TIICs) and tumor cells in postoperative, whole tumor sections from 147 SCCE patients were stained for PD-LI expression. We also evaluated each patient's Combined Positive Score (CPS). Multiplex immunofluorescence staining (CD3, CD20, CD68, and PD-L1) was introduced to clarify the location of PD-L1. CD8 density was analyzed by digital imaging and analysis of entire slides. Clinical outcomes were tested for correlations with both PD-L1 expression and CD8 density. RESULTS: No patients had PD-L1 expressed in their tumor cells. PD-L1+ expression in TIICs was detected in 65 patients (44.2%) and 42 (28.6%) exhibited CPS positivity. Multiplex immunofluorescence staining demonstrated that most of the PD-L1 was expressed on the CD68+ monocytes/macrophages. PD-L1 expression in the TIICs and CPS was found to be correlated with paraffin block age, tumor length, macroscopic type, T stage, and increased overall survival (OS). Expression of PD-L1 in TIICs showed significantly prolonged relapse-free survival (RFS). Increasing CD8 densities were associated with increased PD-L1 expression (Ptrend<0.0001). Multivariate regression confirmed that PD-L1 in TIICs and CD8 states were independent predictors of OS, and CD8 status were found to be independently predictive of RFS. A stratification based on PD-L1 and CD8 status was also significantly associated with both OS and RFS. CONCLUSION: Expression of PD-L1 was only detected in TIICs from approximately half of the patients with SCCEs. In SCCEs, PD-L1 and CD8 status are novel prognostic biomarkers and may inform the implementation of risk-related therapeutic strategies. SCCEs with higher CD8 infiltration also had higher expression of PD-L1, suggesting the development of resistance against adaptive immunity. These findings support the assertion that PD-L1/programmed cell death 1 inhibitors should be investigated in this rare malignancy.

Clinicopathologic characteristics of thymic clear cell carcinoma: a case report with literature review.

BACKGROUND: Thymic clear cell carcinoma is a rare mediastinal neoplasm, with only 25 reported cases to date. We report a case of a 45-year-old man with thymic clear cell carcinoma. We think imaging and laboratory tests may be helpful for differential diagnosis. CASE PRESENTATION: A 45-year-old male was admitted to a local hospital for chest distress with cardiopalmus. CT showed a mediastinal mass. Laboratory examination results were all in the normal range. Histologically, the tumor cells had a clear cytoplasm, and immunohistochemically, the tumor cells were positive for epithelial markers. We performed abdominal and pelvic CT and further examined serum levels of thyroxine, parathyroid hormone and AFP postoperatively, which were normal. The patient received postoperative radiotherapy, and CT showed left adrenal metastasis at 20 months after surgery. CONCLUSION: Thymic clear cell carcinoma is a rare malignant neoplasm. Adrenal metastasis can occur. Patients undergo thymectomy with chemotherapy or with radiotherapy have better outcoming. Metastasis, direct invasion of parathyroid carcinoma and other primary tumors in the mediastinum should be excluded. Immunohistochemical markers, imaging and laboratory examination can help to exclude metastasis.

Comprehensive analyses of N6 -methyladenosine-related long noncoding RNA profiles with prognosis, chemotherapy response, and immune landscape in small cell lung cancer.

Small cell lung cancer (SCLC) is the most devastating subtype of lung cancer with no clinically available prognostic biomarkers. N6 -methyladenosine (m6 A) and noncoding RNAs play critical roles in cancer development and treatment response. However, little is known about m6 A-related long noncoding RNAs (lncRNAs) in SCLC. We used 206 limited-stage SCLC (LS-SCLC) samples from two cohorts to undertake the first and most comprehensive exploration of the m6 A-related lncRNA profile in SCLC and constructed a relevant prognostic signature. In total, 289 m6 A-related lncRNAs were screened out. We then built a seven-lncRNA-based signature in the training cohort with 48 RNA sequencing data using univariate and multivariate Cox regression models. The signature was well validated in an independent cohort containing 158 cases with quantitative PCR data. In both cohorts, the signature divided patients into high- and low-risk groups with significantly different survival rates (both p < 0.001). Our signature predicted chemotherapy survival benefit in patients with LS-SCLC. Receiver operating characteristic and C-index analyses indicated that the signature was better at predicting prognosis and chemotherapy benefit than other clinicopathologic features. Moreover, the signature was identified as an independent predictor of prognosis and chemotherapy response in different cohorts. Furthermore, functional analysis showed that multiple activated immune-related pathways were enriched in the low-risk group. Additionally, the signature was also closely related to various immune checkpoints and inflammatory responses. We generated the first clinically available m6 A-related lncRNA signature to predict prognosis and chemotherapy benefit in patients with LS-SCLC. Our findings could help optimize the clinical management of patients with LS-SCLC and inform future therapeutic targets for SCLC.

Corrigendum: Clinical Significance and Immunometabolism Landscapes of a Novel Recurrence-Associated Lipid Metabolism Signature In Early-Stage Lung Adenocarcinoma: A Comprehensive Analysis.

[This corrects the article DOI: 10.3389/fimmu.2022.783495.].

Clinical Significance and Immunometabolism Landscapes of a Novel Recurrence-Associated Lipid Metabolism Signature In Early-Stage Lung Adenocarcinoma: A Comprehensive Analysis.

Background: The early-stage lung adenocarcinoma (LUAD) incidence has increased with heightened public awareness and lung cancer screening implementation. Lipid metabolism abnormalities are associated with lung cancer initiation and progression. However, the comprehensive features and clinical significance of the immunometabolism landscape and lipid metabolism-related genes (LMRGs) in cancer recurrence for early-stage LUAD remain obscure. Methods: LMRGs were extracted from Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Samples from The Cancer Genome Atlas (TCGA) were used as training cohort, and samples from four Gene Expression Omnibus (GEO) datasets were used as validation cohorts. The LUAD recurrence-associated LMRG molecular pattern and signature was constructed through unsupervised consensus clustering, time-dependent receiver operating characteristic (ROC), and least absolute shrinkage and selection operator (LASSO) analyses. Kaplan-Meier, ROC, and multivariate Cox regression analyses and prognostic meta-analysis were used to test the suitability and stability of the signature. We used Gene Ontology (GO), KEGG pathway, immune cell infiltration, chemotherapy response analyses, gene set variation analysis (GSVA), and GSEA to explore molecular mechanisms and immune landscapes related to the signature and the potential of the signature to predict immunotherapy or chemotherapy response. Results: First, two LMRG molecular patterns were established, which showed diverse prognoses and immune infiltration statuses. Then, a 12-gene signature was identified, and a risk model was built. The signature remained an independent prognostic parameter in multivariate Cox regression and prognostic meta-analysis. In addition, this signature stratified patients into high- and low-risk groups with significantly different recurrence rates and was well validated in different clinical subgroups and several independent validation cohorts. The results of GO and KEGG analyses and GSEA showed that there were differences in multiple lipid metabolism, immune response, and drug metabolism pathways between the high- and low-risk groups. Further analyses revealed that the signature-based risk model was related to distinct immune cell proportions, immune checkpoint parameters, and immunotherapy and chemotherapy response, consistent with the GO, KEGG, and GSEA results. Conclusions: This is the first lipid metabolism-based signature for predicting recurrence, and it could provide vital guidance to achieve optimized antitumor for immunotherapy or chemotherapy for early-stage LUAD.

Tumor Necrosis Factor Family Member Profile Predicts Prognosis and Adjuvant Chemotherapy Benefit for Patients With Small-Cell Lung Cancer.

Tumor necrosis factor (TNF) family members participate in the body's antitumor immunity response and influence tumor prognosis and treatment response. However, little is known about the roles of TNF family members in small cell lung cancer (SCLC). Therefore, we conducted the first comprehensive investigation of TNF family members in patients with SCLC, with the goal of using them to predict prognosis and chemotherapy benefit. Abnormal genetic alterations and expression of TNF family members were found to be widespread in SCLC patients. Using LASSO Cox regression analysis, we constructed a TNF family-based signature that separated SCLC patients in the training set (n=77) into high- and low-risk groups with distinct survival and chemotherapy benefit, and the signature was well-validated in the validation set (n=137) by RT-qPCR. Importantly, the signature exhibited superior predictive performance and was identified as a novel independent prognostic factor. Additionally, different immune phenotypes were found between the low-risk and high-risk groups, and high-risk patients had higher CMTM6 expression, suggesting that these patients could benefit from therapeutic methods targeting CMTM6. We constructed the first clinically applicable TNF family-based signature for predicting prognosis and chemotherapy benefit for patients with SCLC. The findings reported here provide a new method for predicting the prognosis of SCLC patients and optimizing clinical management.

m6A regulator expression profile predicts the prognosis, benefit of adjuvant chemotherapy, and response to anti-PD-1 immunotherapy in patients with small-cell lung cancer.

BACKGROUND: Small cell lung cancer (SCLC) is lethal and possesses limited therapeutic options. Platinum-based chemotherapy-with or without immune checkpoint inhibitors (anti-PDs)-is the current first-line therapy for SCLCs; however, its associated outcomes are heterogeneous. N6-methyladenosine (m6A) is a novel and decisive factor in tumour progression, chemotherapy resistance, and immunotherapy response. However, m6A modification in SCLC remains poorly understood. METHODS: We systematically explored the molecular features and clinical significance of m6A regulators in SCLC. We then constructed an m6A regulator-based prognostic signature (m6A score) based on our examination of 256 cases with limited-stage SCLC (LS-SCLC) from three different cohorts-including an independent cohort that contained 150 cases with qPCR data. We additionally evaluated the relationships between the m6A score and adjuvant chemotherapy (ACT) benefits and the patients' responses to anti-PD-1 treatment. Immunohistochemical (IHC) staining and the HALO digital pathological platform were used to calculate CD8+ T cell density. RESULTS: We observed abnormal somatic mutations and expressions of m6A regulators. Using the LASSO Cox model, a five-regulator-based (G3BP1, METTL5, ALKBH5, IGF2BP3, and RBM15B) m6A score was generated from the significant regulators to classify patients into high- and low-score groups. In the training cohort, patients with high scores had shorter overall survival (HR, 5.19; 2.75-9.77; P < 0.001). The prognostic accuracy of the m6A score was well validated in two independent cohorts (HR 4.6, P = 0.006 and HR 3.07, P < 0.001). Time-dependent ROC and C-index analyses found the m6A score to possess superior predictive power than other clinicopathological parameters. A multicentre multivariate analysis revealed the m6A score to be an independent prognostic indicator. Additionally, patients with low scores received a greater survival benefit from ACT, exhibited more CD8+ T cell infiltration, and were more responsive to cancer immunotherapy. CONCLUSIONS: Our results, for the first time, affirm the significance of m6A regulators in LS-SCLC. Our multicentre analysis found that the m6A score was a reliable prognostic tool for guiding chemotherapy and immunotherapy selections for patients with SCLC.

m6A regulators as predictive biomarkers for chemotherapy benefit and potential therapeutic targets for overcoming chemotherapy resistance in small-cell lung cancer.

Small-cell lung cancer (SCLC) is a devastating subtype of lung cancer with few therapeutic options. Despite the advent of immunotherapy, platinum-based chemotherapy is still the irreplaceable first-line therapy for SCLCs. However, drug resistance will invariably occur in most patients and the outcomes are heterogeneous. Therefore, clinically feasible classification strategies and potential therapeutic targets for overcoming chemotherapy resistance are urgently needed. N6-methyladenosine (m6A) is a novel epigenetic decisive factor that is involved in tumor progression and drug resistance. However, almost nothing is known about m6A modification in SCLC. Here, we assessed 200 SCLC samples from patients who underwent chemotherapy from three different cohorts, including a validation cohort containing 71 cases with qPCR data and an independent cohort containing 79 cases with immunohistochemistry data (quantified as H-score). We systematically characterized the predictive landscape of m6A regulators in SCLC patients following with chemotherapy. Using the LASSO Cox model, we built a seven-regulator-based (ZCCHC4, IGF2BP3, ALKBH5, YTHDF3, METTL5, G3BP1, and RBMX) chemotherapy benefit predictive classifier (m6A score) and subsequently validated the classifier in two other cohorts. Time-dependent ROC and C-index analyses showed that the m6A score to possessed superior predictive power for chemotherapy benefit in comparison with other clinicopathological parameters. A multicohort multivariate analysis revealed that the m6A score is an independent factor that affects survival benefit across multiple cohorts. Our in vitro experimental results revealed that three regulators-ZCCHC4, G3BP1, and RBMX-may serve as promising novel therapeutic targets for overcoming chemoresistance in SCLCs. Our results, for the first time, demonstrate the predictive significance of m6A regulators for chemotherapy benefit, as well as their potential as therapeutic targets for overcoming chemotherapy resistance in SCLC patients. The m6A score was found to be a reliable prognostic tool that may help guide chemotherapy decisions for patients with SCLC.

Development and Validation of Web-Based Nomograms for Predicting Cause-Specific Mortality in Surgically Resected Nonmetastatic Invasive Breast Cancer: A Population-Based Study.

BACKGROUND: This study aims to build nomograms to predict overall survival (OS) and breast cancer-specific death (BCSD) in resected nonmetastatic invasive breast cancer. PATIENTS AND METHODS: Patients extracted from surveillance, epidemiology, and end results database between 2010 and 2014 were analyzed. Through multivariate Cox regression and Fine and Gray competing risks regression, independent predictive factors were identified and integrated to build nomograms for predicting OS and BCSD. The models were validated by bootstrap resampling and an independent cohort. Additionally, the models' performance was measured by the Harrell's C-index, calibrate curve, and time-dependent receiver operating characteristic (ROC) curves. RESULTS: In total, 110,180 cases were identified and enrolled in the analysis, with 83,450 in the training cohort and 26,730 in the validation cohort. Several independent predictive factors for OS and BCSD were identified and integrated to construct the nomograms. The C-indexes in the training cohort and validation cohort were 0.759 and 0.772 for predicting OS, and 0.857 and 0.856 for predicting BCSD, respectively. The nomogram models were well calibrated, and the time-dependent ROC curves verified the superiority of our models for clinical usefulness. Significant differences in the OS and BCSD curves were also observed when stratifying patients into several different risk groups. For convenient access, we deployed these proposed nomograms into web-based calculators. CONCLUSIONS: We established and validated novel nomograms for individualized prediction of OS and BCSD in resected nonmetastatic invasive breast cancer. These nomograms perform better than previous models and could be easily accessed easily by clinicians.

Development and Validation of a Nomogram Prognostic Model for Resected Limited-Stage Small Cell Lung Cancer Patients.

BACKGROUND: In this study, we developed and validated nomograms for predicting the survival in surgically resected limited-stage small cell lung cancer (SCLC) patients. METHODS: The SCLC patients extracted from the Surveillance, Epidemiology, and End Results database between 2000 and 2014 were reviewed. Significant prognostic factors were identified and integrated to develop the nomogram using multivariable Cox regression. The model was then validated internally by bootstrap resampling, and externally using an independent SCLC cohort diagnosed between 2000 and 2015 at our institution. The prognostic performance was measured by the concordance index (C-index) and calibration curve. RESULTS: A total of 1006 resected limited-stage SCLC patients were included in the training cohort. Overall, 444 cases from our institution constituted the validation cohort. Seven prognostic factors were identified and entered into the nomogram construction. The C-indexes of this model in the training cohort were 0.723, 0.722, and 0.746 for predicting 1-, 3-, and 5-year overall survival (OS), respectively, and 0.816, 0.710, and 0.693, respectively, in the validation cohort. The calibration curve showed optimal agreement between nomogram-predicted survival and actual observed survival. Additionally, significant distinctions in survival curves between different risk groups stratified by prognostic scores were also observed. The proposed nomogram was then deployed into a website server for convenient application. CONCLUSIONS: We developed and validated novel nomograms for individual prediction of survival for resected limited-stage SCLC patients. These models perform better than the previously widely used staging system and may offer clinicians instructions for strategy making and the design of clinical trials.

Preoperative systemic immune-inflammation index predicts survival and recurrence in patients with resected primary pulmonary sarcomatoid carcinoma.

BACKGROUND: Pulmonary sarcomatoid carcinoma (PSC) is a rare lung cancer subtype. Studies concerning PSC are limited and controversial; therefore, we analyzed the treatment and outcomes of PSC utilizing a relatively large single-institution database. METHODS: From January 2003 to December 2018, 262 consecutive PSC patients treated at our institution were retrospectively reviewed. The clinical characteristics, treatments, and outcomes were analyzed. RESULTS: The median survival time (MST) was 22.0 months, with 1-, 3-, and 5-year overall survival (OS) rates of 59.9%, 40.1%, and 36.1%, respectively. Patients who underwent surgery had a significantly better prognosis than patients who received nonsurgical treatment (MST, 23.0 vs. 11.0 months, P=0.016). The use of surgery followed by adjuvant therapy significantly prolonged survival in stage III patients (MST, 17.0 vs. 8.0 months, P=0.003) but not in stage I and II patients. Multivariate analysis showed that a systemic inflammation-immune index (SII) value >430.8, TNM stage and necrosis were independent prognostic predictors of OS and disease-free survival (DFS) in radically resected PSC patients (P<0.05). In addition, SII and necrosis were independent risk factors for recurrence after the radical resection of PSC (P<0.05). CONCLUSIONS: PSC is aggressive and has a poor prognosis. Surgery should be the mainstay treatment for operable cases, and adjuvant therapy is recommended for locally advanced disease. A novel potential biomarker, SII, which is an integrated parameter based on preoperative lymphocyte, neutrophil, and platelet counts, may be useful for prognostic prediction and the identification of resected PSC patients at high risk for recurrence.

A three-lncRNA signature of pretreatment biopsies predicts pathological response and outcome in esophageal squamous cell carcinoma with neoadjuvant chemoradiotherapy.

BACKGROUND: Current strategies are insufficient to predict pathologically complete response (pCR) for esophageal squamous cell carcinomas (ESCCs) before treatment. Here, we aim to develop a novel long noncoding RNA (lncRNA) signature for pCR and outcome prediction of ESCCs through a multicenter analysis for a Chinese population. METHODS: Differentially expressed lncRNAs (DELs) between pCRs and less than pCR (

Solid Nodule Appearance as a Predictor of Tumor Spread Through Air Spaces in Patients with Lung Adenocarcinoma: A Propensity Score Matching Study.

OBJECTIVE: Spread through air spaces (STAS) has been reported to be an invasive histological pattern with poor prognosis in lung cancer; however, little is known about its intrinsic risk factors. This work analyzed the correlation between pathological and radiological features and STAS in resected lung adenocarcinomas. PATIENTS AND METHODS: We retrospectively reviewed 1821 consecutive surgically treated patients with histologically diagnosed lung adenocarcinoma (174 positive for STAS and 1647 negative for STAS) from December 2017 to November 2018 at our institution. Propensity score matching identified 170 well-balanced pairs of patients. The correlations between pathological and radiological features and the presence of STAS were analyzed. RESULTS: Before propensity matching, the incidence rate of STAS was 9.6% in all patients. In matched cohorts, multivariate analysis showed that the presence of STAS was significantly correlated with pure solid nodules (SNs) (p = 0.001) and solid/micropapillary patterns (SMPs) (p = 0.002). The odds ratio for STAS in SN-positive and SMP-positive adenocarcinoma against that in SN-negative and SMP-negative adenocarcinoma was 10.922 (95% confidence interval, 5.826-20.475; p < 0.001). Tumor differentiation, visceral pleural invasion (VPI), lymphovascular invasion (LVI), invasive adenocarcinoma, and non-lepidic subtype were significantly associated with STAS in the univariate analysis (p < 0.05); however, the differences failed to reach a significant level in the multivariate analysis. CONCLUSION: We found that STAS was significantly correlated with several invasive clinicopathological patterns. The presence of SNs and SMPs were revealed as independent predictors for STAS, which could offer clinicians clues to identify STAS-positive adenocarcinoma.

Clinical significance and inflammatory landscapes of a novel recurrence-associated immune signature in early-stage lung adenocarcinoma.

The prevalence of early-stage lung adenocarcinoma (LUAD) has increased alongside increased implementation of lung cancer screenings. Robust discrimination criteria are urgently needed to identify those patients who might benefit from additional systemic therapy. Here, to develop a reliable, individualized immune gene-set-based signature to predict recurrence in early-stage LUAD, a novel recurrence-associated immune signature was identified using a least absolute shrinkage and selection operator model, and a stepwise Cox proportional hazards regression model with a training set comprised of 338 early-stage LUAD samples form TCGA, which was subsequently validated in 226 cases from GSE31210 and an independent set of 68 frozen tumor samples with qRT-PCR data. This new classification system remained strongly predictive of prognoses across clinical subgroups and mutation status. Further analysis revealed that samples from high-risk cases were characterized by active interferon signal transduction, distinctive immune cell proportions and immune checkpoint profiles. Moreover, the signature was identified as an independent prognostic factor. In conclusion, the signature is highly predictive of recurrence in patients with early-stage LUAD, which may serve as a powerful prognostic tool to further optimize immunotherapies for cancer.

Uniportal versus multiportal thoracoscopic sleeve lobectomy for the surgical treatment of centrally located lung cancer: a single institution experience.

BACKGROUND: Uniportal thoracoscopic sleeve lobectomy is rarely reported owing to its high degree of difficulty. We conducted a comparative study on the safety and efficacy of uniportal versus multiportal thoracoscopic sleeve lobectomy for the treatment of centrally located lung cancer. METHODS: From January 2016 to December 2018, 30 thoracoscopic sleeve lobectomies (12 by the uniportal approach and 20 by the multiportal approach) for centrally located lung cancer at our institution were retrospectively analyzed. RESULTS: The uniportal approach resulted in a significantly shorter chest drainage duration (5.3±1.9 vs. 7.1±2.8 days, P=0.028) and a smaller chest drainage volume (796.7±582.9 vs. 1,667.8±1,154.9 mL, P=0.004) than the multiportal approach. The two groups showed no significant differences in the dissection of lymph nodes, operation time, estimated blood loss, conversion rate, length of postoperative hospital stay and the proportion of patients with postoperative complications. The short-term overall survival (OS) and disease-free survival (DFS) between uniportal and multiportal groups were similar (3-year OS, 100.0% vs. 82.5%, P=0.222; 3-year DFS, 75.8% vs. 84.4%, P=0.641). For the eight cases of the uniportal approach conducted by the same surgeon, the cumulative sum (CUSUM) curve showed its inflection at patient number 4 and divided the series into phase I (learning phase) and phase II (experienced phase). A significant reduction in estimated blood loss (42.5±8.7 vs. 177.5±121.2 mL, P=0.037), chest drainage volume (280.0±155.8 vs. 972.5±464.5 mL, P=0.043) and chest drainage duration (3.8±1.0 vs. 6.8±2.2 days, P=0.027) was also noted in the phase II patients compared with the phase I patients. CONCLUSIONS: Uniportal thoracoscopic sleeve lobectomy is technically feasible and safe for the treatment of centrally located lung cancer and may achieve superior surgical outcomes compared with the multiportal approach.