Background/introduction: In contrast to patients who present with advanced stage lung cancer and associated poor prognosis, patients with early-stage lung cancer may be candidates for curative treatments. The results of the NELSON lung cancer screening trial are expected to stimulate the development and implementation of a lung cancer screening strategy in most countries. Widespread use of chest computed tomography scans will also result in the detection of solitary pulmonary nodules. Because reliable biomarkers to distinguish between malignant and benign lesions are lacking, tissue-based histopathological diagnostics remain the gold standard. In this study, we aimed to establish a test to assess the predictive ability of DNA hypermethylation of SHOX2 and PTGER4 in plasma to discriminate between patients with 1.) lung cancer, 2.) benign lesions, and 3.) patients with chronic obstructive pulmonary disease (COPD).
Patients And Methods: We retrospectively analysed SHOX2 and PTGER4 methylation in 121 prospectively collected plasma samples of patients with lung cancer (group 1A), benign lesions (group 1B), and COPD without nodules (group 2).
Results: PTGER4 DNA hypermethylation was more frequently observed in patients with lung cancer than in controls (p = 0.0004). Results remained significant after correction for tumour volume, smoking status, age, and eligibility for the NELSON trial.
Conclusions: Detection of methylated PTGER4 in plasma DNA may serve as a biomarker to support clinical decision-making in patients with pulmonary lesions at lung cancer screening in high-risk populations. Further exploration in prospective studies is warranted.
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http://dx.doi.org/10.1016/j.ejca.2021.01.032 | DOI Listing |
Sci Rep
December 2024
Interventional Oncology, Johnson & Johnson Enterprise Innovation, Inc, 10th Floor 255 Main St, 02142, Cambridge, Boston, MA, USA.
The introduction of anti-PD-1/PD-L1 therapies revolutionized treatment for advanced non-small cell lung cancer (NSCLC), yet response rates remain modest, underscoring the need for predictive biomarkers. While a T cell inflamed gene expression profile (GEP) has predicted anti-PD-1 response in various cancers, it failed in a large NSCLC cohort from the Stand Up To Cancer-Mark (SU2C-MARK) Foundation. Re-analysis revealed that while the T cell inflamed GEP alone was not predictive, its performance improved significantly when combined with gene signatures of myeloid cell markers.
View Article and Find Full Text PDFAnn Surg Oncol
December 2024
Department of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA.
Background: Benzodiazepines are the third most misused medication, with many patients having their first exposure during a surgical episode. We sought to characterize factors associated with new persistent benzodiazepine use (NPBU) among patients undergoing cancer surgery.
Patients And Methods: Patients who underwent cancer surgery between 2013 and 2021 were identified using the IBM-MarketScan database.
Sci Rep
December 2024
Department of Radiology, Veterans Health Service Medical Center, Seoul, Republic of Korea.
This study aimed to compare computed tomography (CT) findings between basaloid lung squamous cell carcinoma (SCC) and non-basaloid SCC. From July 2003 to April 2021, 39 patients with surgically proven basaloid SCC were identified. For comparison, 161 patients with surgically proven non-basaloid SCC from June 2018 to January 2019 were selected consecutively.
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December 2024
Precision Medicine Center, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, China.
Polyomavirus enhancer activator 3 (PEA3), an ETS transcription factor, has been documented to regulate the development and metastasis of human cancers. Nonetheless, a thorough analysis examining the relationship between the PEA3 subfamily members and tumour development, prognosis, and the tumour microenvironment (TME) across various cancer types has not yet been conducted. The expression profiles and prognostic significance of the PEA3 subfamily were evaluated using data from the GEO, TCGA, and PrognoScan databases, in conjunction with COX regression analyses and the Kaplan-Meier Plotter.
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December 2024
The Engineering & Technical College of Chengdu University of Technology, Xiaoba Road, Leshan, 614000, China.
Many conditions, such as pulmonary edema, bleeding, atelectasis or collapse, lung cancer, and shadow formation after radiotherapy or surgical changes, cause Lung Opacity. An unsupervised cross-domain Lung Opacity detection method is proposed to help surgeons quickly locate Lung Opacity without additional manual annotations. This study proposes a novel method based on adversarial learning to detect Lung Opacity on chest X-rays.
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