Q-omics provides the consensus-scored MCUR1 profile across patient tissues and cancer cell-line models. MCUR1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, MCUR1 is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, MCUR1 RNA expression shows 20,135 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and BLCA as cancer lineages where MCUR1 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 MCUR1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MCUR1 survival associations across molecular data types. MCUR1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MCUR1 RNA expression–survival associations across cancer types. High MCUR1 expression shows unfavorable associations in ACC, ESCA, COAD, BRCA and LIHC, but favorable associations in KIRC. The ACC 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 ACC as the clearest survival context for MCUR1 RNA expression.
This table summarizes MCUR1 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 7. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MCUR1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MCUR1 shows lower tumor expression in THCA and KIRP and higher tumor expression in BLCA, STAD, LIHC and HNSC. The BLCA box plot shows higher MCUR1 RNA expression in tumor versus normal tissue (log2 FC = +1.025, t-test p < 0.001).
This table shows molecular features associated with MCUR1 in patient tissues and cancer cell lines. In patient samples, MCUR1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, MCUR1 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 URINARY_TRACT and BLOOD_Leukemia.
