Isoform‐Specific KPNA Associations With Malignant Transcriptional Programs in Glioblastoma: A Multi‐Cohort Transcriptomic Analysis

ABSTRACT Glioblastoma (GBM) exhibits profound transcriptional heterogeneity and plasticity, complicating mechanistic interpretation and therapeutic targeting. Whether nuclear import pathways are systematically associated with malignant transcriptional programs—and which karyopherin‐α ( KPNA ; importin‐α) isoforms exhibit distinct, independent associations after accounting for major bulk tumor confounders—remains unclear. We performed a multi‐cohort transcriptomic analysis using a discovery cohort from The Cancer Genome Atlas (TCGA) GBM RNA‐seq dataset ( n = 143, with matched tumor purity and copy‐number data), with external validation in a non‐TCGA Glioma Longitudinal Analysis (GLASS) adult diffuse glioma cohort ( n = 191) and supportive cross‐platform validation from the Clinical Proteomic Tumor Analysis Consortium (CPTAC; n = 99). Associations between malignant transcriptional program scores and KPNA expression were evaluated using proliferation‐adjusted joint models, with tumor purity and gene‐level copy number additionally included according to cohort‐specific data availability. KPNA6 and KPNA4 were the two most consistently prioritized family members and showed complementary, program‐dependent associations across correlated transcriptional programs. KPNA6 was preferentially associated with adhesion and hypoxia programs, whereas KPNA4 aligned with inflammatory programs, including tumor necrosis factor‐α (TNFα)–nuclear factor‐κB (NF‐κB) and interferon‐γ (IFN‐γ) signaling. These patterns remained after covariate adjustment. External analyses were complementary but cohort dependent: GLASS primarily supported KPNA6 ‐linked programs, whereas CPTAC supported KPNA4 ‐linked programs. Although copy‐number variation contributed to KPNA expression variability, it did not account for the observed transcriptional associations. These findings identify isoform‐specific associations between KPNA expression and GBM transcriptional programs and provide a basis for future functional investigation of KPNA6 and KPNA4 .

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Journal
Computational and Systems Oncology
Published
2026-10-28
DOI
https://doi.org/10.1002/cso2.70028
Primary Topic
Glioma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
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article

Isoform‐Specific KPNA Associations With Malignant Transcriptional Programs in Glioblastoma: A Multi‐Cohort Transcriptomic Analysis

Hirotaka Nomiya, Yasunari Nakamoto, Masami Yamada
Computational and Systems Oncology
Glioma Diagnosis and Treatment
article

Isoform‐Specific KPNA Associations With Malignant Transcriptional Programs in Glioblastoma: A Multi‐Cohort Transcriptomic Analysis

Hirotaka Nomiya, Yasunari Nakamoto, Masami Yamada
article en

Abstract

ABSTRACT Glioblastoma (GBM) exhibits profound transcriptional heterogeneity and plasticity, complicating mechanistic interpretation and therapeutic targeting. Whether nuclear import pathways are systematically associated with malignant transcriptional programs—and which karyopherin‐α ( KPNA ; importin‐α) isoforms exhibit distinct, independent associations after accounting for major bulk tumor confounders—remains unclear. We performed a multi‐cohort transcriptomic analysis using a discovery cohort from The Cancer Genome Atlas (TCGA) GBM RNA‐seq dataset ( n = 143, with matched tumor purity and copy‐number data), with external validation in a non‐TCGA Glioma Longitudinal Analysis (GLASS) adult diffuse glioma cohort ( n = 191) and supportive cross‐platform validation from the Clinical Proteomic Tumor Analysis Consortium (CPTAC; n = 99). Associations between malignant transcriptional program scores and KPNA expression were evaluated using proliferation‐adjusted joint models, with tumor purity and gene‐level copy number additionally included according to cohort‐specific data availability. KPNA6 and KPNA4 were the two most consistently prioritized family members and showed complementary, program‐dependent associations across correlated transcriptional programs. KPNA6 was preferentially associated with adhesion and hypoxia programs, whereas KPNA4 aligned with inflammatory programs, including tumor necrosis factor‐α (TNFα)–nuclear factor‐κB (NF‐κB) and interferon‐γ (IFN‐γ) signaling. These patterns remained after covariate adjustment. External analyses were complementary but cohort dependent: GLASS primarily supported KPNA6 ‐linked programs, whereas CPTAC supported KPNA4 ‐linked programs. Although copy‐number variation contributed to KPNA expression variability, it did not account for the observed transcriptional associations. These findings identify isoform‐specific associations between KPNA expression and GBM transcriptional programs and provide a basis for future functional investigation of KPNA6 and KPNA4 .

Computational and Systems OncologyVol. 6(1)
University of Fukui (JP), Life Science Innovation Center, University of Fukui (JP)
Openalex Percentile: Top 12%
Glioma Diagnosis and Treatment
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