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Objectives: The exploration of how dysbiosis relates to lung masses is still nascent, with few studies focusing on the microbial characteristics across various sites. Therefore, we categorized the microbiota into feces and bronchoalveolar fluid (BALF) groups to compare microbial characteristics between benign and malignant masses, analyze their clinical correlations, and develop predictive models for lung cancer.
Methods: A total of 238 fecal samples and 34 BALF samples were collected from patients with benign and malignant masses and then analyzed by 16 SrRNA. We explored the distinct composition of the gut and lung microbiota and their associations with clinical features. The diagnostic models were constructed using microbial features identified through two approaches: random forest algorithm with five-fold cross-validation and comparative analysis of significantly differential taxa. The performance evaluation was subsequently conducted using receiver operating characteristic (ROC) analysis.
Results: There was no significant difference in α-and β-diversity between feces and BALF groups. The relative abundance of Lachnospiraceae_NK4A136_group (P = 0.003232) and Erysipelotrichaceae_UCG-003 (P = 0.01316) in feces group and Proteobacteria (P = 0.03654) in BALF group were significantly increased in lung cancer patients. We also found Bacteroides (P = 0.01458) was abundant in NSCLC than those of SCLC in feces group, while the BALF group was dominated by norank_c_Cyanobacteria (P = 0.03384). Smoking history appeared to be related to the distribution of microbiota, with enrichment of Parabacteroides (P = 0.02054) in feces and Prevotella_1 (P = 0.03286) in BALF. Furthermore, the patients with Sellimonas (P = 0.04148) in feces and Alloprevotella (P = 0.04283) in BALF seemed to have better response to chemotherapy combined with immunotherapy. For differentiating benign and malignant masses, the combination of Megasphaera and norank_p__Saccharibacteria in BALF demonstrated superior predictive performance, with an AUC reaching 0.8 (95% CI 0.59-1).
Conclusion: The microbiota composition significantly differed between benign and malignant masses in both fecal and BALF groups, with minimal evidence supporting microbial migration between these two sites. Our findings suggest that BALF microbiota may serve as a more reliable biomarker for lung masses classification, offering valuable insights for early diagnosis and clinical decision-making.
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http://dx.doi.org/10.1186/s12866-025-04325-5 | DOI Listing |
Head Neck Pathol
September 2025
Department of Laboratory Medicine and Pathology, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA.
Myoepithelial carcinoma (MECA) is a malignant neoplasm composed exclusively of myoepithelial cells and accounts for less than 1% of all salivary gland tumors. Its diagnosis is often challenging due to histologic overlaps with benign lesions and its variable morphologic presentation. Although molecular profiling has emerged as a valuable tool in salivary gland tumor classification, the genetic landscape of MECA remains incompletely defined.
View Article and Find Full Text PDFTechnol Cancer Res Treat
September 2025
Department of Nephrology, Dongyang People's Hospital, Dongyang, China.
ObjectiveTo evaluate the diagnostic performance of a combined model incorporating ultrasound video-based radiomics features and clinical variables for distinguishing between benign and malignant breast lesions.MethodsA total of 346 patients (173 benign and 173 malignant) were retrospectively enrolled. Breast ultrasound videos were acquired and processed using semi-automatic segmentation in 3D Slicer.
View Article and Find Full Text PDFClin Case Rep
September 2025
Department of Thoracic Surgery, Fu Xing Hospital, the Eighth Clinical Medical College Capital Medical University Beijing China.
Lactation-associated breast cancer poses diagnostic challenges due to physiological breast changes that may mask malignancies. Triple-negative breast cancer (TNBC) during lactation is rare and aggressive, requiring vigilant evaluation and treatment. This report highlights the diagnostic dilemma of recurrent cystic breast lesions during lactation, which can mimic benign conditions like galactoceles but may conceal aggressive TNBC, leading to potential delays in diagnosis despite initial conservative approaches such as aspiration.
View Article and Find Full Text PDFRep Pract Oncol Radiother
August 2025
Hospital General de Mexico "Dr Eduardo Liceaga", Mexico City, Mexico.
Background: Paragangliomas are highly vascularized tumours that have benign histology, with malignant dissemination being infrequent (< 5%). Surgery is the only option offering complete resection; however, there is significant morbidity. Treatment with radiotherapy (RT) offers good results in controlling the disease.
View Article and Find Full Text PDFFront Oncol
August 2025
Department of Nuclear Medicine, General Hospital of Northern Theater Command, Shenyang, Liaoning, China.
Objective: To develop a deep learning radiomics(DLR)model integrating PET/CT radiomics, deep learning features, and clinical parameters for early prediction of bone oligometastases (≤5 lesions) in breast cancer.
Methods: We retrospectively analyzed 207 breast cancer patients with 312 bone lesions, comprising 107 benign and 205 malignant lesions, including 89 lesions with confirmed bone metastases. Radiomic features were extracted from computed tomography (CT), positron emission tomography (PET), and fused PET/CT images using PyRadiomics embedded in the uAI Research Portal.