Non-small-cell lung cancer (NSCLC) is the most prevalent type of lung cancer, and there is an urgent need for developing novel therapies. Sonodynamic therapy exhibits exceptional tissue penetration and minimal harm to healthy tissue, making it extremely promising for cancer treatment. The efficacy of SDT is limited by the intricate immunological microenvironment and the resistance to tumor treatment. This study developed targeted nanoparticles that use ultrasound to concentrate on treating NSCLC. The hybrid targeted nanoparticles utilize gold nanoparticles as their fundamental component, with the outside modified with engineered macrophage exosomes and the aptamer S11e to specifically target NSCLC. Ultrasound could effectively eliminate tumors in NSCLC cells by destroying lysosomes via targeted nanoparticles. Simultaneously, fragmented tumor antigens could effectively activate dendritic cell cells to recruit T cells. This method has significant efficacy in suppressing the development of NSCLC and exhibits potential for therapeutic application.
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http://dx.doi.org/10.1021/acsami.4c11546 | 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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