Q-omics provides the consensus-scored RAB2B profile across patient tissues and cancer cell-line models. RAB2B expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, RAB2B is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, RAB2B RNA expression shows 20,833 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, HNSC, and ACC as cancer lineages where RAB2B 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 RAB2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RAB2B survival associations across molecular data types. RAB2B RNA expression shows survival associations in the most cancer types (23), followed by mutation status (1) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RAB2B RNA expression–survival associations across cancer types. High RAB2B expression shows unfavorable associations in UVM, ACC, HNSC, KIRC and LUSC, but favorable associations in BRCA. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .005). Together, the overview and detailed table identify UVM as the clearest survival context for RAB2B RNA expression.
This table summarizes RAB2B 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 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RAB2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RAB2B shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, KIRP, KIRC and CHOL. The HNSC box plot shows higher RAB2B RNA expression in tumor versus normal tissue (log2 FC = +1.001, t-test p < 0.001).
This table shows molecular features associated with RAB2B in patient tissues and cancer cell lines. In patient samples, RAB2B 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, RAB2B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
