Aim: To assess the frequency of human cytomegalovirus (HCMV), Epstein-Barr virus (EBV), and high-risk types of human papillomavirus (HPV16 and HPV18) infections in lung adenocarcinoma samples.
Methods: Lung adenocarcinoma cytological smears and their DNA isolates were obtained from patients hospitalized at the Department for Lung Diseases Jordanovac, Zagreb, in 2016 and 2017. Overall, 67 lung adenocarcinoma samples were examined: 34 with epidermal growth factor receptor gene (EGFR) mutations and 33 without EGFR mutations. The EGFR mutation status and virus presence were assessed with a polymerase chain reaction, and random samples were additionally tested for EBV with Sanger sequencing. HCMV, EBV, HPV16, and HPV18 infections were evaluated in relation to EGFR mutation, smoking status, and sex. A meta-analysis of available data about HPV infection in non-small cell lung cancer was performed.
Results: More frequent HCMV, EBV, HPV16, and HPV18 infections were observed in lung adenocarcinoma samples with EGFR mutations than in samples without these mutations. Coinfection of the investigated viruses was observed only in lung adenocarcinoma samples with mutated EGFR. In the group with EGFR mutations, smoking was significantly associated with HPV16 infection. The meta-analysis showed that non-small cell lung cancer patients with EGFR mutations had a higher odds of HPV infection.
Conclusion: HCMV, EBV, and high-risk HPV infections are more frequent in EGFR-mutated lung adenocarcinomas, which indicates a possible viral impact on the etiology of this lung cancer subtype.
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http://dx.doi.org/10.3325/cmj.2023.64.84 | DOI Listing |
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.
View Article and Find Full Text PDFChin Med
January 2025
Department of Clinical Chinese Pharmacy, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, China.
Background: With extended gefitinib treatment, the therapeutic effect in some non-small cell lung cancer (NSCLC) patients declined with the development of drug resistance. Aidi injection (ADI) is utilized in various cancers as a traditional Chinese medicine prescription. This study explores the molecular mechanism by which ADI, when combined with gefitinib, attenuates gefitinib resistance in PC9GR NSCLC cells.
View Article and Find Full Text PDFSci Rep
January 2025
Chemistry Department, Faculty of Science, Damietta University, Damietta, New-Damietta, 34517, Egypt.
To shed light on the significance of thiazole derivatives in the advancement of cancer medication and to contribute to therapeutic innovation, we have designed the synthesis and antiproliferative activity investigation of 5-(1,3-dioxoisoindolin-2-yl)-7-(4-nitrophenyl)-2-thioxo-3,7-dihydro-2H-pyrano[2,3-d] thiazole-6-carbonitrile, the structure of thiazole derivative was confirmed by spectroscopic techniques UV, IR and NMR. The cytotoxic activity (in vitro) of the new hybrid synthesized compound on five human cancer cell lines; human liver hepatocellular carcinoma (HepG-2), colorectal carcinoma (HCT-116), breast adenocarcinoma (MCF-7), and epithelioid carcinoma (Hela), and a normal human lung fibroblast (WI-38) was studied using MTT assay. The compound exhibited a strong cytotoxicity effect against HepG-2 and MCF-7.
View Article and Find Full Text PDFCancer Cell
December 2024
Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA. Electronic address:
Molecular subtypes, such as defined by The Cancer Genome Atlas (TCGA), delineate a cancer's underlying biology, bringing hope to inform a patient's prognosis and treatment plan. However, most approaches used in the discovery of subtypes are not suitable for assigning subtype labels to new cancer specimens from other studies or clinical trials. Here, we address this barrier by applying five different machine learning approaches to multi-omic data from 8,791 TCGA tumor samples comprising 106 subtypes from 26 different cancer cohorts to build models based upon small numbers of features that can classify new samples into previously defined TCGA molecular subtypes-a step toward molecular subtype application in the clinic.
View Article and Find Full Text PDFJ Proteome Res
January 2025
Department of Thoracic Surgery, Ningbo No.2 Hospital, Ningbo, 315010 Zhejiang, China.
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