Sanjaya Ardo, Gunadi Julia Windi, Ratnawati Hana, Susanto Jonathan Melvern, Mianto Nathanael Andry
Department of Anatomy, Faculty of Medicine, Maranatha Christian University, Bandung, West Java, Indonesia.
Maranatha Biomedical Research Laboratory, Faculty of Medicine, Maranatha Christian University, Jl. Surya Sumantri No. 65, Bandung, 40164, West Java, Indonesia.
Med Oncol. 2025 Jul 10;42(8):321. doi: 10.1007/s12032-025-02902-2.
Metastasis remains the leading cause of cancer-related mortality, yet shared molecular mechanisms across cancer types are poorly understood. Identifying conserved metastatic pathways could offer new therapeutic targets. We performed an integrative cancer analysis across five cancer types (breast, lung, endometrial, prostate, colorectal) using RNA-Seq datasets from the GEO database. Differentially expressed genes (DEGs) between primary and metastatic tumors were identified using limma. Overlapping DEGs across cancers underwent pathway enrichment and protein-protein interaction (PPI) network analysis to identify hub genes. Key pathways and hub genes were validated for prognostic relevance across 15 cancer types using independent TCGA datasets and Cox regression models. We analyzed six publicly available datasets comprising primary and metastatic tumors across five cancer types: breast, lung, endometrial, prostate, and colorectal. We identified 10 overlapping DEGs, with ITGAX and CXCL12 emerging as hub genes connected to critical pathways, such as ERBB4 signaling, integrin-mediated adhesion, glycosphingolipid metabolism, and platelet function. Validation in TCGA confirmed the prognostic significance of hub genes across multiple cancers, with ITGAX significant in 6, while CXCL12 was significant in 2 out of 15 cancers tested. Our approach identified conserved genes and pathways involved in metastasis across cancers, with ERBB4 signaling and hub genes ITGAX and CXCL12 emerging as key regulators. These findings provide a framework for understanding metastatic processes. Future studies should explore targeting the common metastatic process across cancer types.
转移仍然是癌症相关死亡的主要原因，然而不同癌症类型之间共享的分子机制却知之甚少。识别保守的转移途径可能会提供新的治疗靶点。我们使用来自基因表达综合数据库（GEO）的RNA测序数据集，对五种癌症类型（乳腺癌、肺癌、子宫内膜癌、前列腺癌、结直肠癌）进行了综合癌症分析。使用线性模型（limma）识别原发性肿瘤和转移性肿瘤之间的差异表达基因（DEG）。对不同癌症中重叠的差异表达基因进行通路富集和蛋白质-蛋白质相互作用（PPI）网络分析，以识别枢纽基因。使用独立的癌症基因组图谱（TCGA）数据集和Cox回归模型，对关键通路和枢纽基因在15种癌症类型中的预后相关性进行验证。我们分析了六个公开可用的数据集，这些数据集包含了五种癌症类型（乳腺癌、肺癌、子宫内膜癌、前列腺癌和结直肠癌）的原发性肿瘤和转移性肿瘤。我们识别出10个重叠的差异表达基因，其中整合素αX（ITGAX）和趋化因子配体12（CXCL12）成为与关键通路相连的枢纽基因，这些关键通路包括表皮生长因子受体4（ERBB4）信号传导、整合素介导的黏附、糖鞘脂代谢和血小板功能。在TCGA中的验证证实了枢纽基因在多种癌症中的预后意义，在测试的15种癌症中，ITGAX在6种癌症中具有显著性，而CXCL12在2种癌症中具有显著性。我们的方法识别出了不同癌症中参与转移的保守基因和通路，ERBB4信号传导以及枢纽基因ITGAX和CXCL12成为关键调节因子。这些发现为理解转移过程提供了一个框架。未来的研究应该探索针对不同癌症类型中共同转移过程的靶向治疗。
