Figure 1 from Prostate Cancer Progression Modeling Provides Insight into Dynamic Molecular Changes Associated with Progressive Disease States
Year: 2024
Type: other
Abstract: Progression model of prostate cancer constructed by using TCGA data. A, Visualization analysis showed a general trend of data distribution of normal and tumor samples. Each tumor sample was color-coded by its TMPRSS2–ERG fusion status. The black line is the constructed principal tree, and the three axes represent the leading components generated by the DDRTree algorithm (denoted as DDRTree 1–3). B, Seven progression states were identified by partitioning the samples on the data manifold. State 1 is close to the origin of disease progression, and states 3, 4, 6, and 7 are the termini of the progression paths. C, Four progression paths were identified, referred to as paths A–D, respectively. The solid numbers are the major branch points of the constructed tree, and the numbers in brackets are the identified disease progression states.
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
OpenAlex ID: W4403733456