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Accès ouvert déclaré 2024 peer-review

Author response: High-density sampling reveals volume growth in human tumours

0Citations signalées, ce qui n’est pas une note de qualité
2Institutions déclarées
2Pays d’affiliation déclarés

Rattachement africain : de, es. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

Our bodies are made up of organs and tissues, which, in turn, are made up of individual cells. Normally, different types of cells in a tissue perform distinct roles, working together to keep the tissue healthy and functioning properly. However, a genetic mutation that makes them divide and grow uncontrollably can cause tumors to from. As the tumor grows, its cells can undergo further mutations. Each new mutation can serve as a ‘marker’, allowing scientists to track how a tumor has grown, by looking at which cells have specific mutations. Angaji et al. wanted to know if tumors grow through cells on the surface dividing more quickly and invading surrounding tissue; or if all cells in and across the tumor divide at the same rate. To answer this question, the researchers used high-resolution data looking at where in a tumor mutations accumulate. The experiments examined the early evolution of a tumor because only early mutations resulted in enough detectable cells through sequencing. The researchers then compared these 'tumor maps' to simulations of tumors growing in different ways, to see which growth mode fit the maps better. Angaji et al. found that the tumors they looked at grew uniformly across the tumor volume. They also established that the overall growth of the tumor was slow compared to the rate of growth predicted by the speed of the cells dividing. This means that the development of a tumor is finely balanced between net growth and shrinkage, and a small change in the external conditions could potentially kill a tumor. Angaji et al. have developed methods that will allow us to better track tumor growth, and provide further insights into cancer biology. These high-resolution tumor maps may provide clues about how to treat different types of tumors depending on how they grow.

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Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Author response: High-density sampling reveals volume growth in human tumours
Date Crossref
26/11/2024
Éditeur
eLife Sciences Publications, Ltd
Type
peer-review

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Les institutions déclarées

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

MRI in cancer diagnosisRadiomics and Machine Learning in Medical ImagingMathematical Biology Tumor Growth

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