Cargando…
SETDB1 Overexpression Sets an Intertumoral Transcriptomic Divergence in Non-small Cell Lung Carcinoma
An increasing volume of evidence suggests that SETDB1 plays a role in the tumorigenesis of various cancers, classifying SETDB1 as an oncoprotein. However, owing to its numerous protein partners and their global-scale effects, the molecular mechanism underlying SETDB1-involved oncogenesis remains amb...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7738479/ https://www.ncbi.nlm.nih.gov/pubmed/33343623 http://dx.doi.org/10.3389/fgene.2020.573515 |
Sumario: | An increasing volume of evidence suggests that SETDB1 plays a role in the tumorigenesis of various cancers, classifying SETDB1 as an oncoprotein. However, owing to its numerous protein partners and their global-scale effects, the molecular mechanism underlying SETDB1-involved oncogenesis remains ambiguous. In this study, using public transcriptome data of lung adenocarcinoma (ADC) and squamous-cell carcinoma (SCC), we compared tumors with high-level SETDB1 (SH) and those with low-level SETDB1 (comparable with normal samples; SL). The results of principal component analysis revealed a transcriptomic distinction and divergence between the SH and SL samples in both ADCs and SCCs. The results of gene set enrichment analysis indicated that genes involved in the “epithelial–mesenchymal transition,” “innate immune response,” and “autoimmunity” collections were significantly depleted in SH tumors, whereas those involved in “RNA interference” collections were enriched. Chromatin-modifying genes were highly expressed in SH tumors, and the variance in their expression was incomparably high in SCC-SH, which suggested greater heterogeneity within SCC tumors. DNA methyltransferase genes were also overrepresented in SH samples, and most differentially methylated CpGs (SH/SL) were undermethylated in a highly biased manner in ADCs. We identified interesting molecular signatures associated with the possible roles of SETDB1 in lung cancer. We expect these SETDB1-associated molecular signatures to facilitate the development of biologically relevant targeted therapies for particular types of lung cancer. |
---|