Cancer progression, including the development of intratumor heterogeneity, is inherently a spatial process. Mathematical models of tumor evolution may be a useful starting point for understanding the patterns of heterogeneity that can emerge in the presence of spatial growth. A commonly studied spatial growth model assumes that tumor cells occupy sites on a lattice and replicate into neighboring sites. Our R package provides a convenient interface for exploring this model. Our efficient simulation algorithm allows for users to generate 3D tumors with millions of cells in under a minute. For visualizing the distribution of mutations throughout the tumor, provides interactive graphics and summary plots. Additionally, can produce synthetic bulk and single-cell DNA-seq datasets by sampling from the simulated tumor. A streamlined API makes a useful tool for investigating the relationship between spatial growth and intratumor heterogeneity. is a part of CRAN and can be installed by running install.packages("SITH") from the R console. See https://CRAN.R-project.org/package=SITH for the user manual and package vignette.
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http://dx.doi.org/10.1002/cso2.1033 | DOI Listing |
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 PDFNeuro Oncol
January 2025
Childhood Cancer & Cell Death team (C3 team), Consortium South-ROCK, LabEx DEVweCAN, Institut Convergence Plascan, Centre Léon Bérard, Centre de Recherche en Cancérologie de Lyon (CRCL), Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286, 69008 Lyon, France.
Background: Brain tumors are the deadliest solid tumors in children and adolescents. Most of these tumors are glial in origin and exhibit strong heterogeneity, hampering the development of effective therapeutic strategies. In the past decades, patient-derived tumor organoids (PDT-O) have emerged as powerful tools for modeling tumoral cell diversity and dynamics, and they could then help defining new therapeutic options for pediatric brain tumors.
View Article and Find Full Text PDFiScience
January 2025
Department of Biology, University of Copenhagen, 2100 Copenhagen, Denmark.
Chromothripsis, a hallmark of cancer, is characterized by extensive and localized DNA rearrangements involving one or a few chromosomes. However, its genome-wide frequency and characteristics in urothelial carcinoma (UC) remain largely unknown. Here, by analyzing single-regional and multi-regional whole-genome sequencing (WGS), we present the chromothripsis blueprint in 488 UC patients.
View Article and Find Full Text PDFBMC Cancer
January 2025
Department of Radiology, Xiangtan Central Hospital, Xiangtan, 411000, P. R. China.
Background: This study aims to quantify intratumoral heterogeneity (ITH) using preoperative CT image and evaluate its ability to predict pathological high-grade patterns, specifically micropapillary and/or solid components (MP/S), in patients diagnosed with clinical stage I solid lung adenocarcinoma (LADC).
Methods: In this retrospective study, we enrolled 457 patients who were postoperatively diagnosed with clinical stage I solid LADC from two medical centers, assigning them to either a training set (n = 304) or a test set (n = 153). Sub-regions within the tumor were identified using the K-means method.
Curr Neurol Neurosci Rep
January 2025
Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, 80 Avenue Augustin Fliche, Montpellier, 34295, France.
Purpose Of Review: In low-grade glioma (LGG), besides the patient's neurological status and tumor characteristics on neuroimaging, current treatment guidelines mainly rely on the glioma's genetics at diagnosis to define therapeutic strategy, usually starting with surgical resection. However, this snapshot in time does not take into account the antecedent period of tumor progression and its interactions with the brain before presentation. This article reviews new concepts that pertain to reconstruct the history of previous interplay between the LGG's course and adaptive changes in the connectome within which the glioma is embedded over the years preceding the diagnosis.
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