Primary lung adenocarcinoma is classified according to predominant histopathologic architecture into lepidic, papillary, acinar, solid, and micropapillary subtypes. These subtypes are related to overall survival in primary lung adenocarcinoma. The main goal of our work was to evaluate the prognostic impact of this classification on surgical resection of brain adenocarcinoma metastases in 97 patients with surgically resected brain metastases of lung adenocarcinoma from 2008 to 2017. Histopathologic subtype is associated with overall survival (P=0.0085): 30.1±5.6 months for papillary-predominant pattern, 26.5±6.3 months for acinar-predominant pattern, 13.8±1.4 months for solid pattern, 11.6±10.1 for micropapillary pattern. A "low grade" group comprising acinar and papillary-predominant pattern tumors showed a longer overall survival (28.5±4.1 mo) when compared with high-grade-predominant pattern (solid and micropapillary patterns) (13.7±1.4 mo), P=0.0011. On multivariate analysis, age below 55 years at the time of resection (hazard ratio, 3.56; 95% confidence interval, 1.12-11.31) and groups of architectural patterns (hazard ratio, 4.25; 95% confidence interval, 1.83-9.9) were related to overall survival (P=0.031 and 0.00078, respectively). Predominant architectural pattern evaluated on the surgical specimen of brain metastasis is a major prognostic factor of overall survival in metastatic lung adenocarcinoma.
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http://dx.doi.org/10.1097/PAS.0000000000001161 | DOI Listing |
Radiat Oncol
January 2025
Department of Respiratory Medicine and Medical Oncology, Yokohama Municipal Citizen's Hospital, Yokohama, Kanagawa, Japan.
Introduction: Stage IV non-small cell lung carcinoma (NSCLC) with oligometastases is potentially curable by radical treatment. This study aimed to evaluate the efficacy and safety of chemoradiotherapy (CRT) for thoracic disease, including the primary lesion and lymph node metastases, combined with local consolidative therapy (LCT) for oligometastases.
Methods: This was a multicenter Phase II trial for patients with Stage IV NSCLC with oligometastases for whom CRT for thoracic disease was feasible.
Bull Cancer
January 2025
Department of Respiratory and Critical Care Medicine, Baoji High-Tech Hospital, Baoji, 721000 Shaanxi, China. Electronic address:
Background: Lung adenocarcinoma (LUAD) is the most prevalent histological subtype of lung cancer. Pyroptosis is a programmatic cell death linked to inflammation.
Methods: The data information of 541 LUAD samples and 59 normal samples were obtained from TCGA database.
ESMO Open
January 2025
Department of Oncology and Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark; Department of Clinical Medicine, Aalborg University, Aalborg, Denmark. Electronic address:
Background: In a per-protocol analysis of molecularly profiled patients with treatment-refractory, end-stage cancer discussed at the National Molecular Tumor Board (NMTB), we aimed to assess the overall survival (OS) outcome of targeted treatment compared with no targeted treatment.
Materials And Methods: Patients were prospectively included at a single oncological center. Whole exome and RNA sequencing (tumor-normal) were carried out, and cases were presented at the NMTB for discussion of targeted treatment.
Clin Transl Med
January 2025
Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, China.
Background: Complex interrelationships between the microbiota and cancer have been identified by several studies. However, despite delineating microbial composition in non-small cell lung cancer (NSCLC), key pathogenic microbiota and their underlying mechanisms remain unclear.
Methods: We performed 16S rRNA V3-V4 amplicon and transcriptome sequencing on cancerous and adjacent normal tissue samples from 30 patients with NSCLC, from which clinical characteristics and prognosis outcomes were collected.
BMC Cancer
January 2025
Department of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Objective: Rapid on-site evaluation (ROSE) of respiratory cytology specimens is a critical technique for accurate and timely diagnosis of lung cancer. However, in China, limited familiarity with the Diff-Quik staining method and a shortage of trained cytopathologists hamper utilization of ROSE. Therefore, developing an improved deep learning model to assist clinicians in promptly and accurately evaluating Diff-Quik stained cytology samples during ROSE has important clinical value.
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