Introduction: To correlate tumour grading and prognostic immunohistochemical markers of lung cancer with simultaneously acquired standardised uptake values (SUV) and apparent diffusion coefficient (ADC) derived from hybrid PET/MRI.
Methods: In this retrospective study, 55 consecutive patients (mean age 62.5 ± 9.2 years) with therapy-naïve, histologically proven lung cancer were included. All patients underwent whole-body PET/MRI using 18F-flourdeoxyglucose (18F-FDG) as a radiotracer. Diffusion-weighted imaging of the chest (DWI, b-values: 0, 500, 1000 s/mm ) was performed simultaneously with PET acquisition. Histopathological tumour grading was available in 43/55 patients. In 15/55 patients, immunohistochemical markers, that is, phospho-AKT Ser473 (pAKTS473), phosphorylated extracellular signal-regulated kinase (pERK), phosphatase and tensin homolog (PTEN), and human epidermal growth factor receptor 2 (erbB2) were available.
Results: The average SUVmax, SUVmean, ADCmin and ADCmean in lung cancer primaries were 12.6 ± 5.9, 7.7 ± 4.6, 569.9 ± 96.1 s/mm and 825.8 ± 93.2 s/mm , respectively. We found a significant inverse correlation between the ADCmin and SUVmax (r = -0.58, P < 0.001) as well as between the ADCmin and SUVmean (r = -0.44, P < 0.001). Tumour grading showed a significant positive correlation with SUVmax and SUVmean (R = 0.34 and R = 0.31, both P < 0.05) and a significant inverse correlation with ADCmin and ADCmean (r = -0.30 and r = -0.40, both P < 0.05). In addition, erbB2 showed a significant inverse correlation with SUVmax and SUVmean (r = -0.50 and r = -0.49, both P < 0.05). The other immunohistochemical markers did not show any significant correlation.
Conclusion: 18F-FDG-PET/MRI showed weak to moderate correlations between SUV, ADC, tumour grading and erbB2-expression of lung cancer. Hence, 18F-FDG-PET/MRI may, to some extent, offer complementary information to the histopathology of lung cancer, for the evaluation of tumour aggressiveness and treatment response.
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http://dx.doi.org/10.1111/1754-9485.13087 | DOI Listing |
Drugs Aging
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Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, no. 6016U, Boston, MA, 02115, USA.
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Nat Commun
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Bioinformatics and computational systems biology of cancer, Institut Curie, Inserm U900, PSL Research University, Paris, France.
Immunotherapy is improving the survival of patients with metastatic non-small cell lung cancer (NSCLC), yet reliable biomarkers are needed to identify responders prospectively and optimize patient care. In this study, we explore the benefits of multimodal approaches to predict immunotherapy outcome using multiple machine learning algorithms and integration strategies. We analyze baseline multimodal data from a cohort of 317 metastatic NSCLC patients treated with first-line immunotherapy, including positron emission tomography images, digitized pathological slides, bulk transcriptomic profiles, and clinical information.
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January 2025
Department of Medical Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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View Article and Find Full Text PDFCancer Cell Int
January 2025
Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education & Key Laboratory of Medical Molecular Biology of Guizhou Province, Guizhou Medical University, 9 Beijing Road, Guiyang, Guizhou, 550004, P. R. China.
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Department of Cell and Molecular Biology, College of Medicine, Chang Gung University, 259 Wen-Hwa 1 road, Guishan District, Taoyuan, Taiwan.
Background: The Golgi apparatus is widely considered a secretory center and a hub for different signaling pathways. Abnormalities in Golgi dynamics can perturb the tumor microenvironment and influence cell migration. Therefore, unraveling the regulatory network of the Golgi and searching for pharmacological targets would facilitate the development of novel anticancer therapies.
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