Q-omics provides the consensus-scored RAB9A profile across patient tissues and cancer cell-line models. RAB9A expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RAB9A is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, RAB9A RNA expression shows 18,168 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, LIHC, and UVM as cancer lineages where RAB9A 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 RAB9A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RAB9A survival associations across molecular data types. RAB9A RNA expression shows survival associations in the most cancer types (27), followed by mutation status (1) 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 RAB9A RNA expression–survival associations across cancer types. High RAB9A expression shows unfavorable associations in KIRP, LIHC, PAAD and UVM, but favorable associations in KIRC and MESO. The KIRC 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 KIRC as the clearest survival context for RAB9A RNA expression.
This table summarizes RAB9A 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 CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RAB9A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RAB9A shows lower tumor expression in THCA, COAD and BRCA and higher tumor expression in LIHC, HNSC and CHOL. The LIHC box plot shows higher RAB9A RNA expression in tumor versus normal tissue (log2 FC = +0.926, t-test p < 0.001).
This table shows molecular features associated with RAB9A in patient tissues and cancer cell lines. In patient samples, RAB9A shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, RAB9A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and BLOOD_Lymphoma.
