Q-omics provides the consensus-scored RGN profile across patient tissues and cancer cell-line models. RGN expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, RGN is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, RGN protein abundance shows 37,935 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LUAD, KIRC, and LSCC as cancer lineages where RGN 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 RGN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RGN survival associations across molecular data types. RGN RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) and mass-spec protein abundance (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RGN RNA expression–survival associations across cancer types. High RGN expression shows unfavorable associations in COAD and LGG, but favorable associations in LUAD, KIRC, LIHC and KIRP. The LUAD 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 LUAD as the clearest survival context for RGN RNA expression.
This table summarizes RGN 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 12. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RGN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RGN shows lower tumor expression in KIRC, KIRP, BLCA, HNSC, LUSC and LUAD. The KIRC box plot shows higher RGN RNA expression in normal versus tumor tissue (log2 FC = −1.193, t-test p < 0.001).
This table shows molecular features associated with RGN in patient tissues and cancer cell lines. In patient samples, RGN shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, RGN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
