Q-omics provides the consensus-scored RRAS profile across patient tissues and cancer cell-line models. RRAS expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, RRAS is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, RRAS protein abundance shows 27,181 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRP, HNSC, and LSCC as cancer lineages where RRAS 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 RRAS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RRAS survival associations across molecular data types. RRAS 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 RRAS RNA expression–survival associations across cancer types. High RRAS expression shows unfavorable associations in KIRP, KIRC, LUSC, PAAD and GBM, but favorable associations in ESCA. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRP as the clearest survival context for RRAS RNA expression.
This table summarizes RRAS 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 8. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for RRAS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RRAS shows lower tumor expression in BLCA, LUSC and LUAD and higher tumor expression in HNSC, KIRC and THCA. The HNSC box plot shows higher RRAS RNA expression in tumor versus normal tissue (log2 FC = +1.593, t-test p < 0.001).
This table shows molecular features associated with RRAS in patient tissues and cancer cell lines. In patient samples, RRAS 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, RRAS RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUSC, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BONE.
