Quantitative Biology Lab, Department of Integrative Biology, School of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
BMC Genomics. 2024 Feb 2;25(1):135. doi: 10.1186/s12864-024-10023-9.
Pseudogenes have been implicated for their role in regulating cellular differentiation and organismal development. However, their role in promoting cancer-associated differentiation has not been well-studied. This study explores the tumour landscape of oesophageal carcinoma to identify pseudogenes that may regulate events of differentiation to promote oncogenic transformation.
De-regulated differentiation-associated pseudogenes were identified using DeSeq2 followed by 'InteractiVenn' analysis to identify their expression pattern. Gene expression dependent and independent enrichment analyses were performed with GSEA and ShinyGO, respectively, followed by quantification of cellular reprogramming, extent of differentiation and pleiotropy using three unique metrics. Stage-specific gene regulatory networks using Bayesian Network Splitting Average were generated, followed by network topology analysis. MEME, STREME and Tomtom were employed to identify transcription factors and miRNAs that play a regulatory role downstream of pseudogenes to initiate cellular reprogramming and further promote oncogenic transformation. The patient samples were stratified based on the expression pattern of pseudogenes, followed by GSEA, mutation analysis and survival analysis using GSEA, MAF and 'survminer', respectively.
Pseudogenes display a unique stage-wise expression pattern that characterizes stage II (SII) ESCA with a high rate of cellular reprogramming, degree of differentiation and pleiotropy. Gene regulatory network and associated topology indicate high robustness, thus validating high pleiotropy observed for SII. Pseudogene-regulated expression of SOX2, FEV, PRRX1 and TFAP2A in SII may modulate cellular reprogramming and promote oncogenesis. Additionally, patient stratification-based mutational analysis in SII signifies APOBEC3A (A3A) as a potential hallmark of homeostatic mutational events of reprogrammed cells which in addition to de-regulated APOBEC3G leads to distinct events of hypermutations. Further enrichment analysis for both cohorts revealed the critical role of combinatorial expression of pseudogenes in cellular reprogramming. Finally, survival analysis reveals distinct genes that promote poor prognosis in SII ESCA and patient-stratified cohorts, thus providing valuable prognostic bio-markers along with markers of differentiation and oncogenesis for distinct landscapes of pseudogene expression.
Pseudogenes associated with the events of differentiation potentially aid in the initiation of cellular reprogramming to facilitate oncogenic transformation, especially during SII ESCA. Despite a better overall survival of SII, patient stratification reveals combinatorial de-regulation of pseudogenes as a notable marker for a high degree of cellular differentiation with a unique mutational landscape.
假基因已被证明在调节细胞分化和机体发育中具有重要作用。然而，它们在促进与癌症相关的分化中的作用尚未得到充分研究。本研究旨在探讨食管癌的肿瘤特征，以确定可能调节分化事件以促进致癌转化的假基因。
使用 DeSeq2 鉴定失调的分化相关假基因，然后使用“InteractiVenn”分析鉴定其表达模式。使用 GSEA 和 ShinyGO 分别进行基因表达依赖性和独立性富集分析，然后使用三个独特的指标定量细胞重编程、分化程度和多效性。使用贝叶斯网络分割平均生成阶段特异性基因调控网络，然后进行网络拓扑分析。使用 MEME、STREME 和 Tomtom 鉴定转录因子和 miRNA，它们在假基因下游发挥调节作用，启动细胞重编程并进一步促进致癌转化。根据假基因的表达模式对患者样本进行分层，然后分别使用 GSEA、MAF 和“survminer”进行 GSEA、突变分析和生存分析。
假基因显示出独特的阶段表达模式，特征在于 II 期（SII）ESCA 具有高细胞重编程率、分化程度和多效性。基因调控网络及其相关拓扑结构表明其具有高稳健性，从而验证了 SII 观察到的高多效性。SII 中 SOX2、FEV、PRRX1 和 TFAP2A 的假基因调控表达可能调节细胞重编程并促进致癌作用。此外，SII 中基于患者分层的突变分析表明 APOBEC3A（A3A）是重编程细胞的稳态突变事件的潜在标志，除了失调的 APOBEC3G 导致明显的超突变事件外，还导致了独特的事件。两个队列的进一步富集分析表明，假基因的组合表达在细胞重编程中起着关键作用。最后，生存分析揭示了在 SII ESCA 和患者分层队列中促进不良预后的独特基因，从而为不同的假基因表达景观提供了有价值的预后生物标志物以及分化和致癌标志物。
与分化事件相关的假基因可能有助于启动细胞重编程，从而促进致癌转化，特别是在 SII ESCA 中。尽管 SII 的整体生存率较好，但患者分层显示假基因的组合失调是细胞高度分化的显著标志，具有独特的突变景观。
