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相关概念视频

lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

8.9K
In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
8.9K
这页已由机器翻译。其他页面可能仍然显示为英文。View in English
  1. 首页
  3. 研究领域
  5. 生物医学和临床科学
  7. 瘤学和致癌症
  9. 预测和预后标志物
  11. 跨组织学亚型的空间转录组分析揭示了早期肺腺癌的分子异质性和预后标志物
  1. 首页
  3. 研究领域
  5. 生物医学和临床科学
  7. 瘤学和致癌症
  9. 预测和预后标志物
  11. 跨组织学亚型的空间转录组分析揭示了早期肺腺癌的分子异质性和预后标志物

相关实验视频

Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics
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Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics

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跨组织学亚型的空间转录组分析揭示了早期肺腺癌的分子异质性和预后标志物

Hua Geng1, Wenhao Zhou2, Haitao Luo2

  • 1Department of Pathology, Tianjin Chest Hospital, Tianjin, China.

Clinical and translational medicine
|August 23, 2025

在PubMed 上查看摘要

概括
此摘要是机器生成的。

差异化肺腺癌表现出与更糟糕的结果相关的独特分子特征. 一种新的分子特征可以预测疾病的进展,帮助个性化治疗肺癌患者.

关键词:
数字空间转录分析上皮细胞区组织学亚型肺腺癌 肺腺癌

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Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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科学领域:

  • 癌症学
  • 分子生物学
  • 免疫学

背景情况:

  • 肺腺癌的组织学亚型会影响预后.
  • 混合组织学模式使预后评估复杂化.
  • 肺腺癌的组织学亚型的分子基础尚不清楚.

研究的目的:

  • 研究早期肺腺癌不同组织学亚型的分子特征.
  • 确定与肺腺癌的预后相关的分子特征.
  • 探索瘤中的分子特征的空间异质性.

主要方法:

  • 在肺腺癌患者的FFPE样本上使用GeoMx数字空间分析.
  • 对瘤中的上皮和巨丰富区域的分析.
  • 使用多重免疫光 (mIF) 试验进行验证.

主要成果:

  • 在瘤分化等级的上皮细胞和巨细胞区间中确定了不同的分子概况.
  • 差差分化的瘤显示 humoral 免疫反应和补体激活等途径的丰富,与更差的预后有关.
  • 从这些途径获得的复合分子特征与不良结果有很强的相关性.

结论:

巨细胞区
  • 分子特征与肺腺癌的组织学亚型有关.
  • 已识别的分子签名可以作为肺癌的预后生物标志物.
  • 这些发现支持基于分子和组织学特征的个性化治疗策略.