Dissecting the Functional Mechanisms of Somatic Copy-Number Alterations Based on Dysregulated ceRNA Networks across Cancers

Abstract

Somatic copy-number alterations (SCNAs) drive tumor growth and evolution. However, the functional roles of SCNAs across the genome are still poorly understood. We provide an integrative strategy to characterize the functional roles of driver SCNAs in cancers based on dysregulated competing endogenous RNA (ceRNA) networks. We identified 44 driver SCNAs in lower-grade glioma (LGG). The dysregulated patterns losing all correlation relationships dominated dysregulated ceRNA networks. Homozygous deletion of six genes in 9p21.3 characterized an LGG subtype with poor prognosis and contributed to the dysfunction of cancer-associated pathways in a complementary way. The pan-cancer analysis showed that different cancer types harbored different driver SCNAs through dysregulating the crosstalk with common ceRNAs. The same SCNAs destroyed their ceRNA networks through different miRNA-mediated ceRNA regulations in different cancers. Additionally, some SCNAs performed different functional mechanisms in different cancers, which added another layer of complexity to cancer heterogeneity. Compared with previous methods, our strategy could directly dissect functional roles of SCNAs from the view of ceRNA networks, which not only complemented the functions of protein-coding genes but also provided a new avenue to characterize the functions of noncoding RNAs. Also, our strategy could be applied to more types of cancers to identify pathogenic mechanism driven by the SCNAs.

Knockdown of lncRNA ANRIL suppresses the production of inflammatory cytokines and mucin 5AC in nasal epithelial cells via the miR-15a-5p/JAK2 axis

“…miRNAs are common negative regulators of gene expression. According to the competitive endogenous RNA (ceRNA) mechanism, endogenous lncRNAs with miRNA target sites have the potential to act as natural miRNA sponges, which suppress the expression of miRNA targets by competitively binding and inhibiting miRNAs ( 40 ). Notably, some lncRNAs (PVT1 and FENDRR) have been identified to regulate miR-15a-5p expression via the ceRNA network ( 41 , 42 ).…”

Identifying Key Somatic Copy Number Alterations Driving Dysregulation of Cancer Hallmarks in Lower-Grade Glioma

“…The driver genes identified by our method significantly overlapped with these known cancer gene sets (hypergeometric test, P < 0.05, Table 1 ). We then further compared our method with the other three previous methods, which also identified driver copy number alterations [ Ping et al, 2020 ; Zhou et al, 2017 , and DriverDBv3 ( Liu et al, 2020 )]. The results showed that our method could also significantly capture the driver genes identified by other methods with the Ping et al (2020) , Zhou et al (2017) (hypergeometric test, P = 1.84e-05 for Ping et al (2020) , P = 4.23e-12 for Zhou et al (2017) , Table 1 ), but not significantly with DriverDBv3(hypergeometric test, P = 0.175, Table 1 ).…”

“…We then further compared our method with the other three previous methods, which also identified driver copy number alterations [ Ping et al, 2020 ; Zhou et al, 2017 , and DriverDBv3 ( Liu et al, 2020 )]. The results showed that our method could also significantly capture the driver genes identified by other methods with the Ping et al (2020) , Zhou et al (2017) (hypergeometric test, P = 1.84e-05 for Ping et al (2020) , P = 4.23e-12 for Zhou et al (2017) , Table 1 ), but not significantly with DriverDBv3(hypergeometric test, P = 0.175, Table 1 ). Among them, Ping et al (2020) could directly dissect long non-coding RNAs (lncRNAs) functional roles in cancers based on dysregulated ceRNA network induced by SCNAs but was limited in identifying potential driver SCNAs with low expression levels and SCNA frequencies, however, Zhou et al (2017) and DriverDBv3 cannot dissect driver roles of genes in cancers in a direct manner ( Supplementary Table 4 ).…”

Comprehensive analysis to identify DLEU2L/TAOK1 axis as a prognostic biomarker in hepatocellular carcinoma

“… 43 , 44 , 45 , 46 Clarifying the molecular mechanisms and processes of the pathogenesis of HCC and identifying promising biomarkers are essential for identifying new therapeutic targets and improving patients’ outcome with this disease. 47 , 48 , 49 According to reports, the ceRNA regulatory network participates in the occurrence and development of many human cancers, including lung cancer, 50 gastric cancer, 51 and pancreatic cancer. 52 However, to our knowledge, few studies have focused on a comprehensive ceRNA regulatory network to predict the prognosis of HCC.…”