Start off the new year by catching up on the latest cancer research with 2023’s final edition of Editors’ Picks, featuring results from two clinical trials, combination strategies to improve cancer therapy, and a new method for cervical cancer screening. The abstracts of the selected studies are included below; for more details, follow the links… Continue reading Editors’ Picks: Highlights from AACR Journals
Tag: Systems Biochemistry
Multilayer concept of autoimmune mechanisms and manifestations in inborn errors of immunity: Relevance for precision therapy
Untargeted serum metabolomics reveals novel metabolite associations and disruptions in amino acid and lipid metabolism in Parkinson’s disease
Untargeted high-resolution metabolomic profiling provides simultaneous measurement of thousands of metabolites. Metabolic networks based on these data can help uncover disease-related perturbations across inte…
New technique efficiently offers insight into gene regulation
AI SummaryResearchers have developed MAbID, a technique that enables the simultaneous study of various gene regulation mechanisms, providing new insights into their interactions.Researchers have developed a new technique called MAbID. This allows them to simultaneously study different mechanisms of gene regulation, which plays a major role in development and disease. MAbID offers new insights into… Continue reading New technique efficiently offers insight into gene regulation
1317 Enhancing patient safety in melanoma treatment: harnessing machine learning for predicting immune-related adverse events
AI SummaryMachine learning models were used to predict immune-related adverse events (irAEs) in melanoma patients receiving immune-oncology therapy. Eight ML models were trained and tested, with the bagging k-nearest neighborhood (BKNN) and Bernoulli Naive Bayes (BNB) models showing the highest performance. The BNB model accurately predicted irAE development and identified the utilization of specific therapies,… Continue reading 1317 Enhancing patient safety in melanoma treatment: harnessing machine learning for predicting immune-related adverse events
1284 Computational approaches for metabolic target discovery in immuno-oncology
AI SummaryMetabolic alterations in the tumor microenvironment contribute to immunotherapy resistance. By using computational models and transcriptomic data, researchers identified specific metabolic targets in tumor cells that are associated with immunotherapy resistance. Experimental validation showed that inhibiting these targets reduces cell proliferation and tumor growth. Computational methods can effectively identify metabolic targets for therapeutic development.Background… Continue reading 1284 Computational approaches for metabolic target discovery in immuno-oncology
211 Spatial whole transcriptome profiling of human normal liver and HCC uncovers unique insights into metabolic zonation
Background Understanding the physiology and functions of the liver and cancer requires the knowledge of transcriptional patterns driving biological activities within the functional structures of the tissue, especially the zonated features of the liver metabolic networks. Methods Using the powerful and unique capabilities of GeoMx® Digital Spatial Profiler (DSP) with the Whole Transcriptome Atlas (WTA)… Continue reading 211 Spatial whole transcriptome profiling of human normal liver and HCC uncovers unique insights into metabolic zonation
Editors’ Picks: October Highlights From the AACR Journals
As you prepare for trick-or-treating, check out the articles selected by the editors of the 10 AACR journals for the month of October. Highlights include studies on the regulation of electrical activity between melanoma cells and keratinocytes; the role of cancer care providers in HPV vaccine delivery among pediatric, adolescent, and young adult cancer survivors;… Continue reading Editors’ Picks: October Highlights From the AACR Journals
Dynamical modeling of proliferative-invasive plasticity and IFN{gamma} signaling in melanoma reveals mechanisms of PD-L1 expression heterogeneity
Background Phenotypic heterogeneity of melanoma cells contributes to drug tolerance, increased metastasis, and immune evasion in patients with progressive disease. Diverse mechanisms have been individually reported to shape extensive intra-tumor and inter-tumor phenotypic heterogeneity, such as IFN signaling and proliferative to invasive transition, but how their crosstalk impacts tumor progression remains largely elusive. Methods Here,… Continue reading Dynamical modeling of proliferative-invasive plasticity and IFN{gamma} signaling in melanoma reveals mechanisms of PD-L1 expression heterogeneity
3 Questions: Sara Prescott on the brain-body connection
AI SummarySara Prescott, a faculty member in the Department of Biology at MIT, is researching the interoceptive nervous system and its role in detecting and responding to stimuli in the body. Her focus is on the mammalian airway and how neural pathways affect respiratory function and overall health. The goal of her research is to… Continue reading 3 Questions: Sara Prescott on the brain-body connection