Q-omics provides the consensus-scored RARG profile across patient tissues and cancer cell-line models. RARG expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RARG is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, RARG RNA expression shows 18,832 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight ACC, KIRC, and THYM as cancer lineages where RARG 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 RARG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RARG survival associations across molecular data types. RARG RNA expression shows survival associations in the most cancer types (25), followed by mutation status (8) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RARG RNA expression–survival associations across cancer types. High RARG expression shows unfavorable associations in ACC, OV, PAAD, LGG, KIRP and LUAD. 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 RARG RNA expression.
This table summarizes RARG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for RARG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RARG shows lower tumor expression in KICH and higher tumor expression in KIRC, COAD, THCA, LIHC and LUSC. The KIRC box plot shows higher RARG RNA expression in tumor versus normal tissue (log2 FC = +0.680, t-test p < 0.001).
This table shows molecular features associated with RARG in patient tissues and cancer cell lines. In patient samples, RARG shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, RARG RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and BLOOD_Lymphoma.
