Aim: To investigate the metabolic profiles of xenograft pancreatic cancer before and after radiotherapy by high-resolution magic angle spinning proton magnetic resonance spectroscopy (HRMAS (1)H NMR) combined with principal components analysis (PCA) and evaluate the radiotherapeutic effect.
Methods: The nude mouse xenograft model of human pancreatic cancer was established by injecting human pancreatic cancer cell SW1990 subcutaneously into the nude mice. When the tumors volume reached 800 mm(3), the mice received various radiation doses. Two weeks later, tumor tissue sections were prepared for running the NMR measurements. (1)H NMR and PCA were used to determine the changes in the metabolic profiles of tumor tissues after radiotherapy. Metabolic profiles of normal pancreas, pancreatic tumor tissues, and radiation- treated pancreatic tumor tissues were compared.
Results: Compared with (1)H NMR spectra of the normal nude mouse pancreas, the levels of choline, taurine, alanine, isoleucine, leucine, valine, lactate, and glutamic acid of the pancreatic cancer group were increased, whereas an opposite trend for phosphocholine, glycerophosphocholine, and betaine was observed. The ratio of phosphocholine to creatine, and glycerophosphocholine to creatine showed noticeable decrease in the pancreatic cancer group. After further evaluation of the tissue metabolic profile after treatment with three different radiation doses, no significant change in metabolites was observed in the (1)H NMR spectra, while the inhibition of tumor growth was in proportion to the radiation doses. However, PCA results showed that the levels of choline and betaine were decreased with the increased radiation dose, and conversely, the level of acetic acid was dramatically increased.
Conclusion: The combined methods were demonstrated to have the potential for allowing early diagnosis and assessment of pancreatic cancer response to radiotherapy.
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http://dx.doi.org/10.3748/wjg.v19.i26.4200 | DOI Listing |
PLoS One
January 2025
Department of Geriatric Medicine, the Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, China.
Objective: To develop a predictive model for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) through radiomics analysis, integrating data from both enhanced computed tomography (CT) and magnetic resonance imaging (MRI).
Methods: A retrospective analysis was conducted on 93 HCC patients who underwent partial hepatectomy. The gold standard for MVI was based on the histopathological diagnosis of the tissue.
PLoS One
January 2025
Department of Nursing, the Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, China.
Objective: The relationship among body mass index (BMI), postoperative complications, and clinical outcomes in patients undergoing gastrectomy for gastric cancer remains unclear. This study aimed to evaluate this association using a meta-analysis.
Method: We conducted a systematic search of the PubMed, Embase, and Cochrane Library databases up to February 25, 2024.
Ann Surg Oncol
January 2025
Hepato-Pancreato-Biliary Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Discov Oncol
January 2025
Department of Laboratory, the Second Hospital of Shanxi Medical University, No. 382, Wuyi Road, Taiyuan, 030001, Shanxi, People's Republic of China.
Background: Pancreatic cancer (PAC) has a complex tumor immune microenvironment, and currently, there is a lack of accurate personalized treatment. Establishing a novel consensus machine learning driven signature (CMLS) that offers a unique predictive model and possible treatment targets for this condition was the goal of this study.
Methods: This study integrated multiple omics data of PAC patients, applied ten clustering techniques and ten machine learning approaches to construct molecular subtypes for PAC, and created a new CMLS.
mSphere
January 2025
State Key Laboratory of Systems Medicine for Cancer, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ningning Liu works in the field of fungal infection and cancer progression, with a particular focus on the mechanism of host-pathogen interaction. In this mSphere of influence article, he reflects on how papers entitled "The fungal mycobiome promotes pancreatic oncogenesis via activation of MBL," by B. Aykut, S.
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