Q-omics provides the consensus-scored RBFA profile across patient tissues and cancer cell-line models. RBFA expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RBFA is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, RBFA RNA expression shows 19,062 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRC as cancer lineages where RBFA 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 RBFA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RBFA survival associations across molecular data types. RBFA RNA expression shows survival associations in the most cancer types (20), followed by mutation status (2) 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 RBFA RNA expression–survival associations across cancer types. High RBFA expression shows unfavorable associations in ACC, LIHC, BLCA and SKCM, but favorable associations in READ and BRCA. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for RBFA RNA expression.
This table summarizes RBFA 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 4. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RBFA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RBFA shows lower tumor expression in KICH and higher tumor expression in KIRC, LUAD, COAD, LIHC and LUSC. The KIRC box plot shows higher RBFA RNA expression in tumor versus normal tissue (log2 FC = +0.570, t-test p < 0.001).
This table shows molecular features associated with RBFA in patient tissues and cancer cell lines. In patient samples, RBFA 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, RBFA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BREAST and LARGE_INTESTINE.
