Pan-cancer ion transport signature reveals functional regulators of glioblastoma aggression.
Alexander T BahcheliHyun-Kee MinMasroor BayatiHongyu ZhaoAlexander FortunaWeifan DongIrakli DzneladzeJade ChanXin ChenKissy Guevara-HoyerPeter B DirksXi HuangJüri ReimandPublished in: The EMBO journal (2024)
Ion channels, transporters, and other ion-flux controlling proteins, collectively comprising the "ion permeome", are common drug targets, however, their roles in cancer remain understudied. Our integrative pan-cancer transcriptome analysis shows that genes encoding the ion permeome are significantly more often highly expressed in specific subsets of cancer samples, compared to pan-transcriptome expectations. To enable target selection, we identified 410 survival-associated IP genes in 33 cancer types using a machine-learning approach. Notably, GJB2 and SCN9A show prominent expression in neoplastic cells and are associated with poor prognosis in glioblastoma, the most common and aggressive brain cancer. GJB2 or SCN9A knockdown in patient-derived glioblastoma cells induces transcriptome-wide changes involving neuron projection and proliferation pathways, impairs cell viability and tumor sphere formation in vitro, perturbs tunneling nanotube dynamics, and extends the survival of glioblastoma-bearing mice. Thus, aberrant activation of genes encoding ion transport proteins appears as a pan-cancer feature defining tumor heterogeneity, which can be exploited for mechanistic insights and therapy development.
Keyphrases
- papillary thyroid
- poor prognosis
- machine learning
- squamous cell
- genome wide
- gene expression
- squamous cell carcinoma
- induced apoptosis
- emergency department
- magnetic resonance
- deep learning
- cell proliferation
- metabolic syndrome
- white matter
- artificial intelligence
- bone marrow
- oxidative stress
- cell therapy
- big data
- functional connectivity
- wild type