Q-omics provides the consensus-scored RABGGTB profile across patient tissues and cancer cell-line models. RABGGTB expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, RABGGTB is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, RABGGTB protein abundance shows 30,475 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KICH, KIRC, and PDAC as cancer lineages where RABGGTB 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 RABGGTB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RABGGTB survival associations across molecular data types. RABGGTB RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RABGGTB RNA expression–survival associations across cancer types. High RABGGTB expression shows unfavorable associations in KICH, KIRP, LIHC, ACC and ESCA, but favorable associations in KIRC. 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 RABGGTB RNA expression.
This table summarizes RABGGTB 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 12. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RABGGTB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RABGGTB shows higher tumor expression in KIRC, THCA, LIHC, COAD, BLCA and READ. The KIRC box plot shows higher RABGGTB RNA expression in tumor versus normal tissue (log2 FC = +0.850, t-test p < 0.001).
This table shows molecular features associated with RABGGTB in patient tissues and cancer cell lines. In patient samples, RABGGTB shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, RABGGTB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Lymphoma.
