GABA type A receptor-associated proteinGenealiases: ATG8A · GABARAP-a · MM46
Q-omics provides the consensus-scored GABARAP profile across patient tissues and cancer cell-line models. GABARAP expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, GABARAP is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, GABARAP RNA expression shows 19,170 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KICH, COAD, and ACC as cancer lineages where GABARAP shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for GABARAP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GABARAP survival associations across molecular data types. GABARAP RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GABARAP RNA expression–survival associations across cancer types. High GABARAP expression shows unfavorable associations in KICH and ACC, but favorable associations in UVM, KIRC, LGG and BRCA. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify KICH as the clearest survival context for GABARAP RNA expression.
This table summarizes GABARAP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in COAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for GABARAP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GABARAP shows lower tumor expression in COAD, KICH, LUSC, LUAD and READ and higher tumor expression in CHOL. The COAD box plot shows higher GABARAP RNA expression in normal versus tumor tissue (log2 FC = −1.876, t-test p < 0.001).
This table shows molecular features associated with GABARAP in patient tissues and cancer cell lines. In patient samples, GABARAP shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, GABARAP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and SOFT_TISSUE.
