Q-omics provides the consensus-scored RAB3D profile across patient tissues and cancer cell-line models. RAB3D expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, RAB3D is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, RAB3D protein abundance shows 22,212 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight HNSC, COAD, and PDAC as cancer lineages where RAB3D 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 RAB3D — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RAB3D survival associations across molecular data types. RAB3D RNA expression shows survival associations in the most cancer types (28), followed by mutation status (6) 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 RAB3D RNA expression–survival associations across cancer types. High RAB3D expression shows unfavorable associations in ACC, LGG, KICH and UCS, but favorable associations in HNSC and KIRC. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for RAB3D RNA expression.
This table summarizes RAB3D 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 6. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RAB3D. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RAB3D shows lower tumor expression in KICH and higher tumor expression in COAD, KIRP, KIRC, LIHC and BRCA. The COAD box plot shows higher RAB3D RNA expression in tumor versus normal tissue (log2 FC = +1.202, t-test p < 0.001).
This table shows molecular features associated with RAB3D in patient tissues and cancer cell lines. In patient samples, RAB3D 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, RAB3D RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in CNS and SOFT_TISSUE.
