Q-omics provides the consensus-scored MRC1 profile across patient tissues and cancer cell-line models. MRC1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, MRC1 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, MRC1 protein abundance shows 26,574 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight SKCM, HNSC, and LSCC as cancer lineages where MRC1 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 MRC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MRC1 survival associations across molecular data types. MRC1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7) 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 MRC1 RNA expression–survival associations across cancer types. High MRC1 expression shows unfavorable associations in LUSC, LAML and KIRP, but favorable associations in SKCM, KIRC and LGG. The SKCM 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 SKCM as the clearest survival context for MRC1 RNA expression.
This table summarizes MRC1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for MRC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MRC1 shows lower tumor expression in LUSC, LUAD, COAD, KICH and BRCA and higher tumor expression in HNSC. The HNSC box plot shows higher MRC1 RNA expression in tumor versus normal tissue (log2 FC = +2.457, t-test p < 0.001).
This table shows molecular features associated with MRC1 in patient tissues and cancer cell lines. In patient samples, MRC1 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, MRC1 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 BLOOD_Lymphoma and UPPER_AERODIGESTIVE_TRACT.
