Pan-cancer characterization of immune-related lncRNAs identifies potential oncogenic biomarkers.
Yongsheng LiTiantongfei JiangWeiwei ZhouJunyi LiXinhui LiQi WangXiaoyan JinJiaqi YinLiuxin ChenYunpeng ZhangJuan XuXia LiPublished in: Nature communications (2020)
Long noncoding RNAs (lncRNAs) are emerging as critical regulators of gene expression and they play fundamental roles in immune regulation. Here we introduce an integrated algorithm, ImmLnc, for identifying lncRNA regulators of immune-related pathways. We comprehensively chart the landscape of lncRNA regulation in the immunome across 33 cancer types and show that cancers with similar tissue origin are likely to share lncRNA immune regulators. Moreover, the immune-related lncRNAs are likely to show expression perturbation in cancer and are significantly correlated with immune cell infiltration. ImmLnc can help prioritize cancer-related lncRNAs and further identify three molecular subtypes (proliferative, intermediate, and immunological) of non-small cell lung cancer. These subtypes are characterized by differences in mutation burden, immune cell infiltration, expression of immunomodulatory genes, response to chemotherapy, and prognosis. In summary, the ImmLnc pipeline and the resulting data serve as a valuable resource for understanding lncRNA function and to advance identification of immunotherapy targets.
Keyphrases
- papillary thyroid
- gene expression
- long non coding rna
- poor prognosis
- transcription factor
- squamous cell
- genome wide identification
- genome wide analysis
- genome wide
- machine learning
- dna methylation
- childhood cancer
- deep learning
- squamous cell carcinoma
- binding protein
- big data
- young adults
- risk factors
- single molecule
- artificial intelligence
- rectal cancer
- climate change