Q-omics provides the consensus-scored RARA profile across patient tissues and cancer cell-line models. RARA expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, RARA is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, RARA protein abundance shows 20,452 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight BRCA, KIRC, and GBM as cancer lineages where RARA 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 RARA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RARA survival associations across molecular data types. RARA RNA expression shows survival associations in the most cancer types (23), 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 RARA RNA expression–survival associations across cancer types. High RARA expression shows unfavorable associations in COAD, HNSC and THCA, but favorable associations in BRCA, UCS and UCEC. The BRCA 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 BRCA as the clearest survival context for RARA RNA expression.
This table summarizes RARA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, 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 RARA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RARA shows lower tumor expression in KICH and LUSC and higher tumor expression in KIRC, THCA, HNSC and LIHC. The KIRC box plot shows higher RARA RNA expression in tumor versus normal tissue (log2 FC = +1.267, t-test p < 0.001).
This table shows molecular features associated with RARA in patient tissues and cancer cell lines. In patient samples, RARA 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, RARA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
