Lung adenocarcinoma is highly heterogeneous at the molecular level between different stages; therefore, understanding molecular mechanisms contributing to such heterogeneity is needed. In addition, multiple stages of progression are critical factors for lung adenocarcinoma treatment. However, previous studies showed that cancer progression is associated with altered lncRNA expression, highlighting the tissue-specific and developmental stage-specific nature of lncRNAs in various diseases. Therefore, a study using an integrated network approach to explore the role of lncRNA in carcinogenesis was done using expression profiles revealing stage-specific and conserved lncRNA biomarkers in lung adenocarcinoma. We constructed ceRNA networks for each stage of lung adenocarcinoma and analysed them using network topology, differential co-expression network, protein-protein interaction network, functional enrichment, survival analysis, genomic analysis and deep learning to identify potential lncRNA biomarkers. The co-expression networks of healthy and three successive stages of lung adenocarcinoma have shown different network properties. One conserved and four stage-specific lncRNAs are identified as genome regulatory biomarkers. These lncRNAs can successfully identify lung adenocarcinoma and different stages of progression using deep learning. In addition, we identified five mRNAs, four miRNAs and twelve novel carcinogenic interactions associated with the progression of lung adenocarcinoma. These lncRNA biomarkers will provide a novel perspective into the underlying mechanism of adenocarcinoma progression and may be further helpful in early diagnosis, treatment and prognosis of this deadly disease.
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http://dx.doi.org/10.1080/07391102.2024.2431190 | 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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