A 77-year-old man with chronic obstructive pulmonary disease was treated with low-dose methotrexate (7.5-15 mg per week). After 15 months a diagnosis of urothelial carcinoma of the bladder was made; after a further 6 months pneumonitis and pancytopenia developed. The patient died due to massive pulmonary hemorrhage. A malignant teratoma was diagnosed in a 65-year-old asthmatic man 16 months after initiation of methotrexate therapy (15 mg per week). The patient died 4 months later due to fulminant progression of the neoplasm. A third malignant neoplasm (dermal squamous cell carcinoma) was seen in a 64-year-old woman with rheumatoid arthritis after 13 months treatment with 7.5 mg methotrexate per week. These three cases, while obviously not proving a causal relationship between long-term treatment with low-dose methotrexate and development of malignant neoplasm, do call for stringent treatment criteria, close surveillance, and prospective studies.
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http://dx.doi.org/10.1007/BF00180446 | DOI Listing |
BMC Cancer
January 2025
Department of Cellular and Molecular Biology, Lahijan Branch, Islamic Azad University, Lahijan, Iran.
Background/aims: Gastric cancer (GC) is a significant global health issue with high incidence rates and poor prognoses, ranking among the top prevalent cancers worldwide. Due to undesirable side effects and drug resistance, there is a pressing need for the development of novel therapeutic strategies. Understanding the interconnectedness of the JAK2/STAT3/mTOR/PI3K pathway in tumorigenesis and the role of Astaxanthin (ASX), a red ketocarotenoid member of xanthophylls and potent antioxidant and anti-tumor activity, can be effective for cancer treatments.
View Article and Find Full Text PDFBMC Med Imaging
January 2025
Department of Neurosurgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Purpose: We used knowledge discovery from radiomics of T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (T1C) for assessing relapse risk in patients with high-grade meningiomas (HGMs).
Methods: 279 features were extracted from each ROI including 9 histogram features, 220 Gy-level co-occurrence matrix features, 20 Gy-level run-length matrix features, 5 auto-regressive model features, 20 wavelets transform features and 5 absolute gradient statistics features. The datasets were randomly divided into two groups, the training set (~ 70%) and the test set (~ 30%).
Sci Rep
January 2025
School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China.
Background: Environmental metal exposure has been implicated in the development of digestive tract cancers, although the specific associations remain poorly defined. This study aimed to investigate the relationship between blood metal levels and the risk of digestive tract cancers among U.S.
View Article and Find Full Text PDFNat Commun
January 2025
Oxford Molecular Diagnostics Centre, Department of Oncology, University of Oxford, Oxford, UK.
The analysis of circulating tumour DNA (ctDNA) through minimally invasive liquid biopsies is promising for early multi-cancer detection and monitoring minimal residual disease. Most existing methods focus on targeted deep sequencing, but few integrate multiple data modalities. Here, we develop a methodology for ctDNA detection using deep (80x) whole-genome TET-Assisted Pyridine Borane Sequencing (TAPS), a less destructive approach than bisulphite sequencing, which permits the simultaneous analysis of genomic and methylomic data.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Computational Health, Institute of Computational Biology, Helmholtz Zentrum München, Munich, Germany.
Advancements in high-throughput screenings enable the exploration of rich phenotypic readouts through high-content microscopy, expediting the development of phenotype-based drug discovery. However, analyzing large and complex high-content imaging screenings remains challenging due to incomplete sampling of perturbations and the presence of technical variations between experiments. To tackle these shortcomings, we present IMage Perturbation Autoencoder (IMPA), a generative style-transfer model predicting morphological changes of perturbations across genetic and chemical interventions.
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