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Ongoing chromothripsis underpins osteosarcoma genome complexity and clonal evolution.
Cell
January 2025
European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton CB10 1SA, UK. Electronic address:
Osteosarcoma is the most common primary cancer of the bone, with a peak incidence in children and young adults. Using multi-region whole-genome sequencing, we find that chromothripsis is an ongoing mutational process, occurring subclonally in 74% of osteosarcomas. Chromothripsis generates highly unstable derivative chromosomes, the ongoing evolution of which drives the acquisition of oncogenic mutations, clonal diversification, and intra-tumor heterogeneity across diverse sarcomas and carcinomas.
View Article and Find Full Text PDFConserved patterns of transcriptional dysregulation, heterogeneity, and cell states in clear cell kidney cancer.
Cell Rep
January 2025
NDM Research Building, University of Oxford, Old Road Campus, Headington, Oxford OX3 7FZ, UK. Electronic address:
Clear cell kidney cancers are characterized both by conserved oncogenic driver events and by marked intratumor genetic and phenotypic heterogeneity, which help drive tumor progression, metastasis, and resistance to therapy. How these are reflected in transcriptional programs within the cancer and stromal cell components remains an important question with the potential to drive novel therapeutic approaches to treating cancer. To better understand these programs, we perform single-cell transcriptomics on 75 multi-regional biopsies from kidney tumors and normal kidney.
View Article and Find Full Text PDFProspective validation of ORACLE, a clonal expression biomarker associated with survival of patients with lung adenocarcinoma.
Nat Cancer
January 2025
Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
Human tumors are diverse in their natural history and response to treatment, which in part results from genetic and transcriptomic heterogeneity. In clinical practice, single-site needle biopsies are used to sample this diversity, but cancer biomarkers may be confounded by spatiogenomic heterogeneity within individual tumors. Here we investigate clonally expressed genes as a solution to the sampling bias problem by analyzing multiregion whole-exome and RNA sequencing data for 450 tumor regions from 184 patients with lung adenocarcinoma in the TRACERx study.
View Article and Find Full Text PDFMulti-region infectious disease prediction modeling based on spatio-temporal graph neural network and the dynamic model.
PLoS Comput Biol
January 2025
Complex Systems Research Center, Shanxi University, Taiyuan, Shanxi, China.
Human mobility between different regions is a major factor in large-scale outbreaks of infectious diseases. Deep learning models incorporating infectious disease transmission dynamics for predicting the spread of multi-regional outbreaks due to human mobility have become a hot research topic. In this study, we incorporate the Graph Transformer Neural Network and graph learning mechanisms into a metapopulation SIR model to build a hybrid framework, Metapopulation Graph Transformer Neural Network (M-Graphormer), for high-dimensional parameter estimation and multi-regional epidemic prediction.
View Article and Find Full Text PDFDeconstruction and analysis of global biodiversity loss transfer network based on the social network analysis method.
Environ Sci Pollut Res Int
January 2025
Institute of Marine Economics and Management, Shandong University of Finance and Economics, Lixia District, Second Ring East Road, Jinan, 7366250000, China.
Biodiversity is crucial for maintaining ecosystem stability and achieving sustainable development. However, global biodiversity loss is a common challenge faced by most countries. Therefore, based on the data from the International Union for Conservation of Nature (IUCN) Red List of Threatened Species and the Eora database, we used the multi-regional input-output (MRIO) model to calculate biodiversity loss in 188 countries.
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