Online decision tools for personalized survival prediction and treatment optimization in elderly patients with lung squamous cell carcinoma: a retrospective cohort study.

Background: Despite major advances in cancer therapeutics, the therapeutic options of Lung Squamous Cell Carcinoma (LSCC)-specific remain limited. Furthermore, the current staging system is imperfect for defining a prognosis and guiding treatment due to its simplicity and heterogeneity. We sought to develop prognostic decision tools for individualized survival prediction and treatment optimization in elderly patients with LSCC.

Establishing a prognostic model based on immune-related genes and identification of BIRC5 as a potential biomarker for lung adenocarcinoma patients.

Background: Lung adenocarcinoma (LUAD) is an extraordinarily malignant tumor, with rapidly increasing morbidity and poor prognosis. Immunotherapy has emerged as a hopeful therapeutic modality for lung adenocarcinoma. Furthermore, a prognostic model (based on immune genes) can fulfill the purpose of early diagnosis and accurate prognostic prediction.

Appropriateness and Comprehensiveness of Using ChatGPT for Perioperative Patient Education in Thoracic Surgery in Different Language Contexts: Survey Study.

Background: ChatGPT, a dialogue-based artificial intelligence language model, has shown promise in assisting clinical workflows and patient-clinician communication. However, there is a lack of feasibility assessments regarding its use for perioperative patient education in thoracic surgery.

Objective: This study aimed to assess the appropriateness and comprehensiveness of using ChatGPT for perioperative patient education in thoracic surgery in both English and Chinese contexts.

Design Appropriate Incision Length for Uniportal Video-Assisted Thoracoscopic Lobectomy: Take into Account Safety and Minimal Invasiveness.

Background:  There is no criterion on the length of the uniportal video-assisted thoracoscopic surgery (UVATS) incision when performing lobectomy. We aimed to develop a nomogram to assist surgeons in designing incision length for different individuals.

Methods:  A cohort consisting of 290 patients were enrolled for nomogram development.

Development and Validation of a Clinical Prognostic Nomogram for Esophageal Adenocarcinoma Patients.

Background: Clinical staging is essential for clinical decisions but remains imprecise. We purposed to construct a novel survival prediction model for improving clinical staging system (cTNM) for patients with esophageal adenocarcioma (EAC).

Methods: A total of 4180 patients diagnosed with EAC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and included as the training cohort.

Long Noncoding RNA Nuclear Paraspeckle Assembly Transcript 1 Promotes Progression and Angiogenesis of Esophageal Squamous Cell Carcinoma Through miR-590-3p/MDM2 Axis.

Angiogenesis has been identified as one of the hallmarks of cancer and aggravates cancer development and progression. Accumulating evidence indicated that long noncoding RNAs (lncRNAs) are powerful factors in regulating various cancer behaviors. The aim of this study is to verify the function and potential mechanisms of lncRNA NEAT1 in progression and angiogenesis of esophageal squamous cell carcinoma (ESCC).

Development and validation of a new clinical staging system to predict survival for esophageal squamous cell carcinoma patients: Application of the nomogram.

Introduction: Survival of patients with the same clinical stage varies widely and effective tools to evaluate the prognosis utilizing clinical staging information is lacking. This study aimed to develop a clinical nomogram for predicting survival of patients with Esophageal Squamous Cell Carcinoma (ESCC).

Materials And Methods: On the basis of data extracted from the SEER database (training cohort, n = 3375), we identified and integrated significant prognostic factors for nomogram development and internal validation.

An artificial neural network model predicting pathologic nodal metastases in clinical stage I-II esophageal squamous cell carcinoma patients.

Background: Current preoperative staging for lymph nodal status remains inaccurate. The purpose of this study was to build an artificial neural network (ANN) model to predict pathologic nodal involvement in clinical stage I-II esophageal squamous cell carcinoma (ESCC) patients and then validated the performance of the model.

Methods: A total of 523 patients (training set: 350; test set: 173) with clinical staging I-II ESCC who underwent esophagectomy and reconstruction were enrolled in this study.

Synaptotagmin 12 (SYT12) Gene Expression Promotes Cell Proliferation and Progression of Lung Adenocarcinoma and Involves the Phosphoinositide 3-Kinase (PI3K)/AKT/Mammalian Target of Rapamycin (mTOR) Pathway.

BACKGROUND This study aimed to use bioinformatics analysis to compare data from tissue microarrays from patients with lung adenocarcinoma (LUAD) and normal lung tissue, and human lung adenocarcinoma cells with normal lung epithelial cells in vitro to investigate the role of synaptotagmin 12 (SYT12) gene expression in LUAD. MATERIAL AND METHODS Human lung adenocarcinoma cell lines (A549, SPC-A-1, H1299, H1975, and PC9) and the normal HBE cell line were compared, and tumor xenografts were developed in mice. The Cancer Genome Atlas (TCGA) tissue microarray data were used to compare SYT12 expression and overall survival (OS).

Effect of different therapeutic strategies on the clinical outcome of asymptomatic intralobar pulmonary sequestration.

Objectives: Pulmonary sequestration is a rare congenital pulmonary malformation. The aim of this study was to explore the effect of different therapeutic strategies on the clinical outcome of asymptomatic intralobar pulmonary sequestration.

Methods: We retrospectively reviewed the clinical data of 37 patients diagnosed with intralobar sequestration.

FAM111B, a direct target of p53, promotes the malignant process of lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a main subtype of lung cancer, which is the leading cause of cancer-related deaths. The five-year survival rates of lung cancer patients are still comparatively low. Therefore, potential therapeutic targets are urgently needed to improve the survival of lung cancer patients.

Tumor-derived exosomal lncRNA GAS5 as a biomarker for early-stage non-small-cell lung cancer diagnosis.

Diagnosis and treatment at an early stage may improve survival of non-small-cell lung cancer (NSCLC). Previous studies have found that long noncoding RNA growth arrest-specific transcript 5 (GAS5) is essential to cancer progression. However, the expression and diagnostic value of GAS5 in exosomes (Exo-GAS5) remain unclear.

C-reactive protein to albumin ratio is a key indicator in a predictive model for anastomosis leakage after esophagectomy: Application of classification and regression tree analysis.

Background: Anastomotic leakage (AL), a serious complication after esophagectomy, might impair patient quality of life, prolong hospital stay, and even lead to surgery-related death. The aim of this study was to show a novel decision model based on classification and regression tree (CART) analysis for the prediction of postoperative AL among patients who have undergone esophagectomy.

Methods: A total of 450 patients (training set: 356; test set: 94) with perioperative information were included.

Long non-coding RNA linc00665 promotes lung adenocarcinoma progression and functions as ceRNA to regulate AKR1B10-ERK signaling by sponging miR-98.

Long non-coding RNAs (lncRNAs) are frequently dysregulated in multiple malignancies, demonstrating their potential oncogenic or tumor-suppressive roles in tumorigenesis. Herein, we reported the identification of a novel lncRNA, linc00665 (ENST00000590622), which was markedly upregulated in lung adenocarcinoma (LUAD) tissues and might serve as an independent predictor for poor prognosis. Functional assays indicated that linc00665 reinforced LUAD cell proliferation and metastasis in vitro and in vivo.