The Schlafen (SLFN) gene family has emerged as a critical subject of study in recent years, given its involvement in an array of cellular functions such as proliferation, differentiation, immune responses, viral infection inhibition, and DNA replication. Additionally, SLFN genes are linked to chemosensitivity, playing a pivotal role in treating malignant tumors. Human SLFNs comprise three domains: the N-terminal, middle (M), and C-terminal. The N- and C-terminal domains demonstrate nuclease and helicase/ATPase activities, respectively. Meanwhile, the M-domain likely functions as a linker that connects the enzymatic domains of the N- and C-terminals and may engage in interactions with other proteins. This paper aims to present a comprehensive overview of the SLFN family's structure and sequence, examine its significance in various tumors, and explore its connection with immune infiltrating cells and immune checkpoints. The objective is to assess the potential of SLFNs as vital targets in cancer therapy and propose novel strategies for combined treatment approaches.
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http://dx.doi.org/10.3389/fonc.2024.1468484 | DOI Listing |
Sci Rep
December 2024
Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Canada.
Accurate diagnosis of oral lesions, early indicators of oral cancer, is a complex clinical challenge. Recent advances in deep learning have demonstrated potential in supporting clinical decisions. This paper introduces a deep learning model for classifying oral lesions, focusing on accuracy, interpretability, and reducing dataset bias.
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December 2024
Laboratory of Cellular Biophysics, The Rockefeller University, New York, NY, USA.
Fibrolamellar Hepatocellular Carcinoma (FLC) is a rare liver cancer characterized by a fusion oncokinase of the genes DNAJB1 and PRKACA, the catalytic subunit of protein kinase A (PKA). A few FLC-like tumors have been reported showing other alterations involving PKA. To better understand FLC pathogenesis and the relationships among FLC, FLC-like, and other liver tumors, we performed a massive multi-omics analysis.
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December 2024
Department of Breast Surgery, Second Affiliated Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, China.
Early prediction of patient responses to neoadjuvant chemotherapy (NACT) is essential for the precision treatment of early breast cancer (EBC). Therefore, this study aims to noninvasively and early predict pathological complete response (pCR). We used dynamic ultrasound (US) imaging changes acquired during NACT, along with clinicopathological features, to create a nomogram and construct a machine learning model.
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December 2024
Department of Pathology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Micropapillary adenocarcinoma (MPC) is an aggressive histological subtype of lung adenocarcinoma (LUAD). MPC is composed of small clusters of cancer cells exhibiting inverted polarity. However, the mechanism underlying its formation is poorly understood.
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December 2024
Institute of Informatics, HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland, Sierre, Switzerland.
Manual segmentation of lesions, required for radiotherapy planning and follow-up, is time-consuming and error-prone. Automatic detection and segmentation can assist radiologists in these tasks. This work explores the automated detection and segmentation of brain metastases (BMs) in longitudinal MRIs.
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