Genomic profile of an IDH-wild-type glioblastoma diagnosed following TNF-α inhibitor therapy: a molecular case study.

TNF α inhibitors such as adalimumab are widely used for autoimmune diseases, yet their long-term impact on tumor development in genetically susceptible individuals remains incompletely defined. Glioblastoma (GBM) is an aggressive IDH wild-type tumor with recurrent molecular alterations; however, comprehensive genomic analyses of GBM arising in patients treated with TNF-α inhibitors are extremely limited. We examined the genomic features of a GBM developing after prolonged TNF-α inhibitor therapy to explore potential links between TNF-α blockade, and tumor evolution. Tumor tissue was analyzed using immunohistochemistry, targeted next-generation sequencing, and copy number analysis performed at two independent clinical laboratories. Genomic findings were interpreted in the context of TNF α pathway biology and tumor microenvironment interactions relevant to GBM progression. The tumor demonstrated GFAP and OLIG positivity, a Ki-67 index of 45%, and strong p53 expression (>90%). Genomic profiling revealed hallmark alterations of IDH wild-type GBM, including CDKN2A/B deletions, PTEN deletion, and a TP53 mutation. Additional findings included a KDM6A frameshift variant, an ATRX variant of uncertain significance, and loss of PDPK1. No TERT promoter mutation was detected, suggesting a potential alternative telomere maintenance mechanism. The combination of PTEN loss, TP53 mutation, and CDKN2A/B deletion is consistent with an aggressive molecular phenotype associated with immune evasion. This case highlights genomic features of an IDH-wild-type glioblastoma arising after prolonged TNF-α inhibitor exposure. While no causal inference can be made, this analysis identifies both canonical and atypical genomic alterations in a GBM arising after prolonged TNF-α targeted therapy. This temporal relationship provides a basis for studying possible convergence between TNF-α signaling and GBM-associated pathways, and underscores the importance of genomic risk stratification when considering TNF-α inhibitor therapy.