Ras related GTP binding BGenealiases: RAGB · bA465E19.1
Q-omics provides the consensus-scored RRAGB profile across patient tissues and cancer cell-line models. RRAGB expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, RRAGB is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, RRAGB RNA expression shows 19,383 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight COAD, KIRC, and KIRP as cancer lineages where RRAGB 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 RRAGB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RRAGB survival associations across molecular data types. RRAGB RNA expression shows survival associations in the most cancer types (23), followed by mutation status (7) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RRAGB RNA expression–survival associations across cancer types. High RRAGB expression shows unfavorable associations in COAD, but favorable associations in LUSC, UCS, ACC, LGG and GBM. The COAD 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 COAD as the clearest survival context for RRAGB RNA expression.
This table summarizes RRAGB tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RRAGB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RRAGB shows lower tumor expression in KIRC, THCA, LUAD, UCEC and KICH and higher tumor expression in LIHC. The KIRC box plot shows higher RRAGB RNA expression in normal versus tumor tissue (log2 FC = −0.645, t-test p < 0.001).
This table shows molecular features associated with RRAGB in patient tissues and cancer cell lines. In patient samples, RRAGB shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, RRAGB 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 BLOOD_Lymphoma and LUNG_NSCLC_LUSC.
