Q-omics provides the consensus-scored RGCC profile across patient tissues and cancer cell-line models. RGCC 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, RGCC is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, RGCC protein abundance shows 32,159 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRC, and LUAD as cancer lineages where RGCC 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 RGCC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RGCC survival associations across molecular data types. RGCC RNA expression shows survival associations in the most cancer types (27), followed by mutation status (2) 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 RGCC RNA expression–survival associations across cancer types. High RGCC expression shows unfavorable associations in KIRP, ACC, OV and MESO, but favorable associations in KIRC and SKCM. 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 RGCC RNA expression.
This table summarizes RGCC 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 5. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RGCC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RGCC shows lower tumor expression in LUSC, LUAD, BLCA and KIRP and higher tumor expression in KIRC and COAD. The KIRC box plot shows higher RGCC RNA expression in tumor versus normal tissue (log2 FC = +1.894, t-test p < 0.001).
This table shows molecular features associated with RGCC in patient tissues and cancer cell lines. In patient samples, RGCC shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, RGCC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
