Q-omics provides the consensus-scored MRAS profile across patient tissues and cancer cell-line models. MRAS expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, MRAS is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, MRAS protein abundance shows 25,285 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UCEC, KICH, and GBM as cancer lineages where MRAS 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 MRAS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MRAS survival associations across molecular data types. MRAS RNA expression shows survival associations in the most cancer types (20), followed by mutation status (1) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MRAS RNA expression–survival associations across cancer types. High MRAS expression shows unfavorable associations in UCEC, MESO and BRCA, but favorable associations in KIRC, UCS and SKCM. The UCEC 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 UCEC as the clearest survival context for MRAS RNA expression.
This table summarizes MRAS tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in KICH for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for MRAS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MRAS shows lower tumor expression in KICH, LUAD, LUSC, KIRC and BRCA and higher tumor expression in LIHC. The KICH box plot shows higher MRAS RNA expression in normal versus tumor tissue (log2 FC = −2.619, t-test p < 0.001).
This table shows molecular features associated with MRAS in patient tissues and cancer cell lines. In patient samples, MRAS 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, MRAS RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and LARGE_INTESTINE.
