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BACKGROUND: No studies to date have focused on the timing of pulmonary resection in patients with previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In the present study, the authors analyzed the surgical outcomes and evaluated the optimal time point of pulmonary resection surgery following SARS-CoV-2 infection. MATERIALS AND METHODS: In this multicenter retrospective cohort study, patients were divided into different groups according to the time interval between SARS-CoV-2 diagnosis and pulmonary resection. The primary outcome measure was postoperative complications within 30 days after surgery, which was investigated to determine the optimal time point of pulmonary resection. Logistic regression models were used to calculate the risk factors for postoperative complications. RESULTS: In total, 400 patients were enrolled, and the postoperative pathologic examination of 322 (80.5%) patients showed lung cancer. As the interval between SARS-CoV-2 infection and pulmonary resection increased, the incidence of complications gradually decreased in each group. The incidence of grade ≥II complications was higher in the ≤2-week and 2-week to 4-week groups than in the 4-week to 6-week, 6-week to 8-week and >8-week groups [3 (21.4%), 17 (20.2%), 10 (10.6%), 13 (7.9%), and 3 (6.5%), respectively] ( P <0.05). Multiclassification regression analysis showed that the risk of grade ≥II complications in the ≤2-week and 2-week to 4-week groups was significantly higher than that in the >8-week group [odds ratio (95% CI), 3.937 (1.072-14.459), P =0.039 and 3.069 (1.232-6.863), P =0.015]. The logistic regression analysis suggested that underlying disease, persistent SARS-CoV-2 symptoms, and surgical timing (≤4 weeks) were independent risk factors for complications of pulmonary resection after SARS-CoV-2 infection. CONCLUSION: Pulmonary resection should be delayed for at least 4 weeks following SARS-CoV-2 infection to reduce the risk of postoperative complications.
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COVID-19 , Humanos , COVID-19/epidemiología , SARS-CoV-2 , Estudios Retrospectivos , Prueba de COVID-19 , Complicaciones Posoperatorias/epidemiología , Complicaciones Posoperatorias/etiologíaRESUMEN
BACKGROUND: Neoadjuvant chemoimmunotherapy has shown a good therapeutic effect on non-small cell lung cancer (NSCLC), which also opens up the possibility of applying organ preservation strategies. This study investigated the feasibility of modified surgery after potent neoadjuvant chemoimmunotherapy in central type NSCLC. METHODS: In this multicenter retrospective cohort study, patients with central type NSCLC who received 2-4 cycles of neoadjuvant chemoimmunotherapy between January 2019 and June 2022 at Air Force Medical University Tangdu Hospital and Peking University People's Hospital were eligible. Patients were divided into modified and nonmodified groups according to the extent of surgery, after which, the safety and long-term prognosis of surgery were investigated. RESULTS: A total of 84 patients were enrolled. Of 36 (42.9%) patients who underwent modified surgery, 21 patients underwent lobectomy, 12 patients underwent lobectomy with bronchoplasty, 2 patients underwent sleeve lobectomy, and 1 patient underwent bilobectomy. The modification rate for the initially estimated pneumonectomy, sleeve lobectomy, and bilobectomy was 48.6, 44.8, and 30%, respectively. Grades II-V postoperative complications were found in 5 (13.9%) patients in the modified group and 17 (35.4%) patients in the nonmodified group (relative risk, 0.393; 95% CI, 0.016-0.963; P =0.026). No significant difference was observed regarding the surgical approach, operative duration, blood loss, or R0 resection rate. The 2-year local recurrence rate was 3.7% (95% CI, 0.004-0.175) and 5.2% (95% CI, 0.012-0.168) in the modified group and nonmodified group, respectively. The 1-year PFS rate of modified and nonmodified groups was 97.1% (95% CI, 83.7-99.8) and 86.9% (95% CI, 73.4-94.4), respectively, while 2-year PFS were 89.8% (95% CI, 74.1-96.9) and 71.8% (95% CI, 56.7-83.4), respectively. CONCLUSION: Applying organ preservation strategies, that is, undergoing modified surgery after neoadjuvant chemoimmunotherapy, is feasible for selected central type NSCLC patients with favorable safety and long-term survival.
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Carcinoma de Pulmón de Células no Pequeñas , Neoplasias Pulmonares , Humanos , Carcinoma de Pulmón de Células no Pequeñas/tratamiento farmacológico , Carcinoma de Pulmón de Células no Pequeñas/cirugía , Neoplasias Pulmonares/tratamiento farmacológico , Neoplasias Pulmonares/cirugía , Terapia Neoadyuvante , Estudios Retrospectivos , Preservación de Órganos , NeumonectomíaRESUMEN
Background: Currently, how to successfully control refractory and metastatic diseases remains a fundamental goal for clinicians to improve therapeutic effects for patients with non-small cell lung cancer (NSCLC). Several studies have discovered that TRIM58, a member of tripartite motif protein family, shows antitumor effect in multiple types of cancer. In this study, we aimed to further clarify the molecular regulatory network of TRIM58 and corresponding targets for NSCLC patients. Methods: TRIM58 expression in clinical tumor tissue samples and cancer cell lines was examined. Functional experiments including cellular invasion, cell metastasis, chemoresistance assay, and ubiquitination evaluation experiments were conducted to investigate the interaction between TRIM58 and ZEB1, which is a prime element of transcription factor network that controls epithelial-to-mesenchymal transition. Results: TRIM58 expression was characteristically decreased in NSCLC tumor tissues and cancer cell lines. Functional experiments demonstrated that TRIM58 suppression enhanced malignant biological behaviors including cellular survivability, migration, and invasion, as well as stem-like cellular phenotype of tumor cells. TRIM58 silencing also significantly enhanced the chemoresistance of NSCLC cells to chemoagents. TRIM58-ZEB1 interaction accelerated degradation of ZEB1 protein, thus further leading to the augment of tumor behaviors. Further detailed molecular experiments revealed that the interaction between TRIM58 and ZEB1 was mediated via ubiquitin-proteasome pathway (UPP). Conclusion: TRIM58 suppressed NSCLC through interacting with ZEB1 and promoting ZEB1 protein degradation via UPP. The present research sheds light on the interaction between TRIM58 and ZEB1, and TRIM58/ZEB1 axis might be the potential therapeutic targets of NSCLC.
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Carcinoma de Pulmón de Células no Pequeñas , Neoplasias Pulmonares , Proteínas de Motivos Tripartitos , Homeobox 1 de Unión a la E-Box con Dedos de Zinc , Humanos , Carcinoma de Pulmón de Células no Pequeñas/patología , Línea Celular Tumoral , Transición Epitelial-Mesenquimal , Neoplasias Pulmonares/patología , Proteolisis , Ubiquitinación , Homeobox 1 de Unión a la E-Box con Dedos de Zinc/genética , Homeobox 1 de Unión a la E-Box con Dedos de Zinc/metabolismo , Proteínas de Motivos Tripartitos/genética , Proteínas de Motivos Tripartitos/metabolismo , Complejo de la Endopetidasa Proteasomal , UbiquitinaRESUMEN
Lung nodules are the main lesions of the lung, and conditions of the lung can be directly displayed through CT images. Due to the limited pixel number of lung nodules in the lung, doctors have the risk of missed detection and false detection in the detection process. In order to reduce doctors' work intensity and assist doctors to make accurate diagnosis, a lung nodule segmentation and recognition algorithm is proposed by simulating doctors' diagnosis process with computer intelligent methods. Firstly, the attention mechanism model is established to focus on the region of lung parenchyma. Then, a pyramid network of bidirectional enhancement features is established from multiple body positions to extract lung nodules. Finally, the morphological and imaging features of lung nodules are calculated, and then, the signs of lung nodules can be identified. The experiments show that the algorithm conforms to the doctor's diagnosis process, focuses the region of interest step by step, and achieves good results in lung nodule segmentation and recognition.