使用DNA甲基化和复制号分析,预测myxofibrosarcomas和未分化软组织肉瘤的放射治疗反应
Tony G Kleijn1,2, Baptiste Ameline3, Wierd Kooistra1
1Department of Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
International journal of surgical pathology
|January 29, 2026
概括
肌纤维肉瘤和不分化的软组织肉瘤可能是同一种疾病. 基因组甲基化分析没有预测放射治疗反应,但染色体11q24.1损失显示出作为生物标志物的潜力.
科学领域:
- 在瘤学瘤学.
- 基因组学就是基因组学.
- 癌症生物标志物 癌症生物标志物
背景情况:
- 肌纤维肉瘤 (MFS) 和未分化的软组织肉瘤 (USTS) 是常见的,重叠的肉瘤亚型.
- 术后的新辅助放射治疗是标准治疗,但反应是不可预测的.
- 需要用于放射治疗反应的预测生物标志物.
研究的目的:
- 为了研究DNA甲基化和拷贝数变异 (CNV) 档案,从放射治疗前的活检.
- 在MFS和USTS中确定放射治疗反应的预测生物标志物.
主要方法:
- 分析了49个放射治疗前肉瘤活检中的DNA甲基化和CNV数据.
- 根据EORTC-STBSG标准评估的放射治疗反应相关的基因组数据.
- 使用Illumina甲基化EPIC珠芯片进行全基因组分析.
主要成果:
- MFS,USTS和多形脂类瘤形成了一个单一的,异构的甲基化集群.
- CNV 档案没有区分 MFS 和 USTS.
- 响应者和非响应者之间没有甲基化模式的显著差异.
- 响应者 (100%) 的11q24.1染色体损失明显高于非响应者 (33%).
结论:
- MFS和USTS可能代表一种疾病谱.
- 基因甲基化分析并不是放射治疗反应的可靠预测指标.
- 染色体11q24.1丢失是一个潜在的预测生物标志物,需要进一步验证.
相关概念视频
Predicting Molecular Geometry
45.8K
VSEPR Theory for Determination of Electron Pair Geometries
45.8K
Elastin is Responsible for Tissue Elasticity
3.2K
Elastic fiber contains the protein elastin along with lesser amounts of other proteins and glycoproteins. The main property of elastin is that it will return to its original shape after being stretched or compressed. Elastic fibers are prominent in elastic tissues found in skin and the elastic ligaments of the vertebral column.
Ligaments and tendons are made of dense regular connective tissue, but in ligaments not all fibers are parallel. Dense regular elastic tissue contains elastin fibers and...
Ligaments and tendons are made of dense regular connective tissue, but in ligaments not all fibers are parallel. Dense regular elastic tissue contains elastin fibers and...
3.2K
Prediction Intervals
3.4K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
3.4K
Rous Sarcoma Virus (RSV) and Cancer
6.4K
Rous Sarcoma virus or RSV was discovered by F. Peyton Rous in the year 1911 as a filterable transmissible agent that could cause tumors in chickens. He won a Nobel Prize for this discovery in 1966. His experiments clearly demonstrated that some cancers could be caused by infectious agents and led to the discovery of many more cancer-causing viruses in animals as well as humans.
RSV is a retrovirus that contains two copies of a plus-strand RNA genome. Its genome consists of four main open...
RSV is a retrovirus that contains two copies of a plus-strand RNA genome. Its genome consists of four main open...
6.4K
Inflammatory Response II: Inflammatory Exudate and Tissue Repair
7.7K
The immune system's inflammatory response destroys the invading pathogen, permitting the tissue to heal. The changes during the cellular and vascular stages allow exudate formation at the site of inflammation. The inflammatory exudate released from the wound has high protein content and a specific gravity above 1.020.
The typical wound exudate is odorless, transparent, straw-colored, thin, and watery. Exudate, however, can differ depending on the state of wound healing. Likewise, the...
The typical wound exudate is odorless, transparent, straw-colored, thin, and watery. Exudate, however, can differ depending on the state of wound healing. Likewise, the...
7.7K
End Point Prediction: Gran Plot
1.2K
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
For potentiometric titration, the Gran plot is created by plotting...
1.2K


