In multiple malignancies, checkpoint inhibitor therapy has an established role in the first-line treatment setting. However, only a subset of patients benefit from checkpoint inhibition, and as a result, the field of biomarker research is active. Molecular imaging with the use of positron emission tomography (PET) is one of the biomarkers that is being studied. PET tracers such as conventional F-FDG but also PD-(L)1 directed tracers are being evaluated for their predictive power. Furthermore, the use of artificial intelligence is under evaluation for the purpose of response prediction. Response evaluation during checkpoint inhibitor therapy can be challenging due to the different response patterns that can be observed compared to traditional chemotherapy. The additional information provided by PET can potentially be of value to evaluate a response early after the start of treatment and provide the clinician with important information about the efficacy of immunotherapy. Furthermore, the use of PET to stratify between patients with a complete response and those with a residual disease can potentially guide clinicians to identify patients for which immunotherapy can be discontinued and patients for whom the treatment needs to be escalated. This review provides an overview of the use of positron emission tomography (PET) to predict and evaluate treatment response to immunotherapy.
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http://dx.doi.org/10.3390/cancers13123083 | DOI Listing |
BMC Plant Biol
January 2025
Institute of Grassland Science, School of Life Sciences, Key Laboratory of Vegetation Ecology, Ministry of Education, Northeast Normal University, Changchun, China.
The intricate biogeochemical cycling of multiple elements plays a pivotal role in upholding a myriad of ecosystem functions. However, our understanding of elemental stoichiometry and coupling in response to global changes remains primarily limited to plant carbon: nitrogen: phosphorus (C: N: P). Here, we assessed the responses of 11 elements in plants from different functional groups to global changes.
View Article and Find Full Text PDFBMC Genomics
January 2025
Henan Collaborative Innovation Center of Modern Biological Breeding, College of Agronomy, Henan Institute of Science and Technology, Xinxiang, 453003, China.
Background: The Sec14 domain is an ancient lipid-binding domain that evolved from yeast Sec14p and performs complex lipid-mediated regulatory functions in subcellular organelles and intracellular traffic. The Sec14 family is characterized by a highly conserved Sec14 domain, and is ubiquitously expressed in all eukaryotic cells and has diverse functions. However, the number and characteristics of Sec14 homologous genes in soybean, as well as their potential roles, remain understudied.
View Article and Find Full Text PDFNPJ Precis Oncol
January 2025
Eötvös Loránd University, Department of Physics of Complex Systems, Budapest, Hungary.
Patients with High-Grade Serous Ovarian Cancer (HGSOC) exhibit varied responses to treatment, with 20-30% showing de novo resistance to platinum-based chemotherapy. While hematoxylin-eosin (H&E)-stained pathological slides are used for routine diagnosis of cancer type, they may also contain diagnostically useful information about treatment response. Our study demonstrates that combining H&E-stained whole slide images (WSIs) with proteomic signatures using a multimodal deep learning framework significantly improves the prediction of platinum response in both discovery and validation cohorts.
View Article and Find Full Text PDFSci Data
January 2025
Remote Sensing Centre for Earth System Research (RSC4Earth), Leipzig University, Leipzig, 04103, Germany.
With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-ready datasets. Earth observation datasets comprehensively monitor ecosystem dynamics and responses to climatic extremes, yet the data complexity can challenge the effectiveness of machine learning models.
View Article and Find Full Text PDFSci Rep
January 2025
The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe Road, Zhengzhou, 450052, Henan, China.
Netrin-1 (NTN1) is a laminin-related secreted protein involved in axon guidance and cell migration. Previous research has established a significant connection between NTN1 and nervous system development. In recent years, mounting evidence indicates that NTN1 also plays a crucial role in tumorigenesis and tumor progression.
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