Article Synopsis

  • The study finds that both natural populations and tumors adapt similarly to low oxygen (hypoxia), indicating a shared genetic response.
  • Understanding how these adaptations work in natural settings could provide valuable insights into cancer biology.
  • This knowledge may help uncover new targets for cancer treatments.

Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

This study reveals a broad convergence in genetic adaptation to hypoxia between natural populations and tumors, suggesting that insights from natural populations could enhance our understanding of cancer biology and identify novel therapeutic targets. See related commentary by Lee, p. 875.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12046333PMC
http://dx.doi.org/10.1158/2159-8290.CD-24-0943DOI Listing

Publication Analysis

Top Keywords

genetic adaptation
8
natural populations
8
convergent genetic
4
adaptation human
4
human tumors
4
tumors developed
4
developed systemic
4
systemic hypoxia
4
hypoxia populations
4
populations living
4

Similar Publications

Background: Soil salinization represents a critical global challenge to agricultural productivity, profoundly impacting crop yields and threatening food security. Plant salt-responsive is complex and dynamic, making it challenging to fully elucidate salt tolerance mechanism and leading to gaps in our understanding of how plants adapt to and mitigate salt stress.

Results: Here, we conduct high-resolution time-series transcriptomic and metabolomic profiling of the extremely salt-tolerant maize inbred line, HLZY, and the salt-sensitive elite line, JI853.

View Article and Find Full Text PDF

To breed for climate resilient crops, an understanding of the genetic and environmental factors influencing adaptation is critical. Barley provides a model species to study adaptation to climate change. Here we present a detailed analysis of genetic variation at a major photoperiod response locus and relate this to the domestication history and dispersal of barley.

View Article and Find Full Text PDF

Endothelial cell-ILC3 crosstalk via the ET-1/EDNRA axis promotes NKp46ILC3 glycolysis to alleviate intestinal inflammation.

Cell Mol Immunol

September 2025

Pediatric Intensive Care Unit, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences); Department of Immunology, School of Basic Medical Sciences; Department of Clinical Laboratory, the Third Affiliated Hospital of Southern Medical University, Southern Medical University, Gua

Communication between group 3 innate lymphoid cells (ILC3) and other immune cells, as well as intestinal epithelial cells, is pivotal in regulating intestinal inflammation. This study, for the first time, underscores the importance of crosstalk between intestinal endothelial cells (ECs) and ILC3. Our single-cell transcriptome analysis combined with protein expression detection revealed that ECs significantly increased the population of interleukin (IL)-22 ILC3 through interactions mediated by endothelin-1 (ET-1) and its receptor endothelin A receptor (EDNRA).

View Article and Find Full Text PDF

The rapid decline in global biodiversity highlights the urgent need for conservation efforts, with botanical gardens playing a crucial role in ex situ plant preservation. Monumental plants, such as the 400-year-old Goethe's Palm (Chamaerops humilis L.) at the Padua Botanical Garden serve as vital flagship species with significant ecological and cultural value.

View Article and Find Full Text PDF

ResDeepGS: A deep learning-based method for crop phenotype prediction.

Methods

September 2025

School of Computer and Information Engineering, Henan University, Kaifeng, Henan, China; Henan Key Laboratory of Big Data Analysis and Processing, Henan University, Kaifeng, Henan, China. Electronic address:

Genomic selection (GS) is a breeding technique that utilizes genomic markers to predict the genetic potential of crops and animals. This approach holds significant promise for accelerating the improvement of agronomic traits and addressing food security challenges. While traditional breeding methods based on statistical or machine learning techniques have been useful in predicting traits for some crops, they often fail to capture the complex interactions between genotypes and phenotypes.

View Article and Find Full Text PDF