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Integrative genomic analyses identify lncRNA regulatory networks across pediatric leukemias and solid tumors

ABSTRACT: Long non-coding RNAs (lncRNAs) play an important role in gene regulation and contribute to tumorigenesis. While pan-cancer studies of lncRNA expression have been performed for adult malignancies, the lncRNA landscape across pediatric cancers remains largely uncharted. Here, we curated RNA sequencing data for 1,044 pediatric leukemia and extra-cranial solid tumors and integrated paired tumor whole genome sequencing and epigenetic data in relevant cell line models to explore lncRNA expression, regulation, and association with cancer. A total of 2,657 lncRNAs were robustly expressed across six pediatric cancers, including 1,142 exhibiting histotype-elevated expression. DNA copy number alterations contributed to lncRNA dysregulation at a proportion comparable to protein coding genes. Application of a multi-dimensional framework to identify and prioritize lncRNAs impacting gene networks revealed that lncRNAs dysregulated in pediatric cancer are associated with proliferation, metabolism, and DNA damage hallmarks. Analysis of upstream regulation via cell-type specific transcription factors further implicated distinct histotype-elevated and developmental lncRNAs. Integration of these analyses prioritized lncRNAs for experimental validation, and silencing of TBX2-AS1, the top-prioritized neuroblastoma-specific lncRNA, resulted in significant growth inhibition of neuroblastoma cells, confirming the computational predictions. Taken together, these data provide a comprehensive characterization of lncRNA regulation and function in pediatric cancers and pave the way for future mechanistic studies.

ORGANISM(S): Homo sapiens

PROVIDER: GSE238166 | GEO | 2023/07/31

REPOSITORIES: GEO

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Project description:Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults and the second most common form of leukemia in children. Multiple lncRNAs participate in normal and may be implicated in malignant hematopoiesis associated with blood cell cancers, such as leukemia. Currently, the expression profile of lncRNAs in pediatric AML is unclear. In this study, we evaluated the lncRNA expression profile in the tissue of three pediatric AML patients with lncRNA microarray techniques. In order to gain insight into the function of targets of lncRNAs, GO term and KEGG pathway annotation were applied to the target gene pool. qPCR was performed to evaluate the expression patterns of dys-regulated lncRNAs. Bone marrow specimens were obtained at the time of diagnosis during routine clinical assessment of 3 pediatric patients with AML, who presented at the Department of Hematology and Oncology, Children's Hospital of Soochow University between 2000 and 2011. Additionally, bone marrow samples from 3 healthy donors were analyzed as controls. Human LncRNA Array analysis was performed by KangChen Bio-tech, Shanghai P.R. China. Total RNA from each sample was quantified by the NanoDrop ND-1000 and RNA integrity was assessed by standard denaturing agarose gel electrophoresis. For microarray analysis, Agilent Array platform was employed. The sample preparation and microarray hybridization were performed based on the manufacturerâs standard protocols with minor modifications. Briefly, mRNA was purified from total RNA after removal of rRNA (mRNA-ONLYâ¢ Eukaryotic mRNA Isolation Kit, Epicentre). Then, each sample was amplified and transcribed into fluorescent cRNA along the entire length of the transcripts without 3â bias utilizing a random priming method. The labeled cRNAs were hybridized onto the Human LncRNA Array v2.0 (8 x 60K, Arraystar). After having washed the slides, the arrays were scanned by the Agilent Scanner G2505C. Agilent Feature Extraction software (version 11.0.1.1) was used to analyze acquired array images. Quantile normalization and subsequent data processing were performed using the GeneSpring GX v12.0 software package (Agilent Technologies). After quantile normalization of the raw data, LncRNAs and mRNAs that at least 4 out of 6 samples have flags in Present or Marginal (âAll Targets Valueâ) were chosen for further data analysis. Differentially expressed LncRNAs and mRNAs with statistical significance between the two groups were identified through Volcano Plot filtering. Pathway analysis and GO analysis were applied to determine the roles of these differentially expressed mRNAs played in these biological pathways or GO terms. Finally, Hierarchical Clustering was performed to show the distinguishable LncRNAs and mRNAs expression pattern among samples.

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Integrative genomic analyses identify lncRNA regulatory networks across pediatric leukemias and solid tumors

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