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Background/Objectives: Acute myeloid leukemia (AML) comprises genetic subclasses with distinct gene expression profiles. While AML gene expression studies have mainly focused on protein-coding genes, our understanding of expression patterns of long intergenic noncoding RNAs (lincRNAs) remains incomplete. This is due to limited sample sizes, as well as incomplete annotation of lncRNAs with context-dependent expression. Methods: To address this gap, we developed the bioinformatic pipeline LIRA (long intergenic noncoding RNA annotator) to identify novel lincRNAs using stringent criteria, including spliced and intergenic transcripts, and algorithms to exclude coding potential. Results: By applying LIRA to RNA-sequencing data from 878 pediatric and adult AML cases and 20 healthy controls, we identified 1560 novel lincRNAs, expanding the GENCODE v38 lincRNA catalog by 27%. Integration of in-house-generated CAGE- and ChIP-sequencing data from KMT2A::MLLT3 samples revealed that 80% of the novel lincRNAs are 5′ capped, and at least 67% harbor activating epigenetic marks at their transcription start sites. Unsupervised analysis of the 1000 most variable known and newly identified lincRNAs uncovered subclass-specific expression patterns, mirroring those observed for protein-coding genes. Weighted Gene Co-expression Network Analysis identified 17 lincRNA expression modules associated with AML subclasses. Notably, expression of these modules decreased upon degradation of the leukemogenic onco-fusion proteins KMT2A::MLLT3 and PML::RARA, indicating that lincRNA expression is responsive to oncogenic signaling. Conclusions: This comprehensive analysis shows that lincRNAs exhibit similar subclass-specific expression patterns as protein-coding genes and establishes a valuable resource for future studies on genetically defined AML subclasses, with potential implications for biomarker discovery and therapeutic targeting.
Arza-Apalategi et al. (Wed,) studied this question.