Q-omics provides the consensus-scored RABGEF1 profile across patient tissues and cancer cell-line models. RABGEF1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, RABGEF1 is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, RABGEF1 protein abundance shows 21,402 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight CESC, THCA, and BRCA as cancer lineages where RABGEF1 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 RABGEF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RABGEF1 survival associations across molecular data types. RABGEF1 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 RABGEF1 RNA expression–survival associations across cancer types. High RABGEF1 expression shows unfavorable associations in CESC, ACC, KIRC, BLCA and LIHC, but favorable associations in UCS. The CESC 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 CESC as the clearest survival context for RABGEF1 RNA expression.
This table summarizes RABGEF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for RABGEF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RABGEF1 shows lower tumor expression in THCA, KIRC, READ and KICH and higher tumor expression in HNSC and LIHC. The THCA box plot shows higher RABGEF1 RNA expression in normal versus tumor tissue (log2 FC = −0.711, t-test p < 0.001).
This table shows molecular features associated with RABGEF1 in patient tissues and cancer cell lines. In patient samples, RABGEF1 shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, RABGEF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
