Q-omics provides the consensus-scored RAB30 profile across patient tissues and cancer cell-line models. RAB30 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, RAB30 is differentially expressed in 13, with the highest sampling consensus in KICH. Additionally, RAB30 protein abundance shows 21,475 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LUAD, KICH, and GBM as cancer lineages where RAB30 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 RAB30 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RAB30 survival associations across molecular data types. RAB30 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RAB30 RNA expression–survival associations across cancer types. High RAB30 expression shows unfavorable associations in ACC, but favorable associations in LUAD, KIRC, SCLC, LGG and ESCA. The LUAD 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 LUAD as the clearest survival context for RAB30 RNA expression.
This table summarizes RAB30 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 8. The strongest signals are observed in KICH for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for RAB30. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RAB30 shows lower tumor expression in KICH, BLCA, COAD and THCA and higher tumor expression in HNSC and CHOL. The KICH box plot shows higher RAB30 RNA expression in normal versus tumor tissue (log2 FC = −0.862, t-test p < 0.001).
This table shows molecular features associated with RAB30 in patient tissues and cancer cell lines. In patient samples, RAB30 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, RAB30 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Lymphoma.
