RAP2B, member of RAS oncogene familyGenealiases: []
Q-omics provides the consensus-scored RAP2B profile across patient tissues and cancer cell-line models. RAP2B expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, RAP2B is differentially expressed in 13, with the highest sampling consensus in KIRP. Additionally, RAP2B protein abundance shows 22,870 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, KIRP, and GBM as cancer lineages where RAP2B 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 RAP2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RAP2B survival associations across molecular data types. RAP2B RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) 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 RAP2B RNA expression–survival associations across cancer types. High RAP2B expression shows unfavorable associations in HNSC, LGG, LIHC, KIRP and LUSC, but favorable associations in KIRC. The HNSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify HNSC as the clearest survival context for RAP2B RNA expression.
This table summarizes RAP2B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RAP2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RAP2B shows higher tumor expression in KIRP, KIRC, HNSC, THCA, LUSC and LUAD. The KIRP box plot shows higher RAP2B RNA expression in tumor versus normal tissue (log2 FC = +1.660, t-test p < 0.001).
This table shows molecular features associated with RAP2B in patient tissues and cancer cell lines. In patient samples, RAP2B shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, RAP2B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BONE.
