Q-omics provides the consensus-scored RHCE profile across patient tissues and cancer cell-line models. RHCE expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, RHCE is differentially expressed in 11, with the highest sampling consensus in LUAD. Additionally, RHCE RNA expression shows 15,247 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, LUAD, and ACC as cancer lineages where RHCE 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 RHCE — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RHCE survival associations across molecular data types. RHCE RNA expression shows survival associations in the most cancer types (16), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RHCE RNA expression–survival associations across cancer types. High RHCE expression shows unfavorable associations in THYM, ACC, BLCA, MESO and SARC, but favorable associations in UVM. The UVM 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 UVM as the clearest survival context for RHCE RNA expression.
This table summarizes RHCE tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 1. The strongest signals are observed in LUAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RHCE. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RHCE shows lower tumor expression in THCA and KICH and higher tumor expression in LUAD, BRCA, BLCA and LUSC. The LUAD box plot shows higher RHCE RNA expression in tumor versus normal tissue (log2 FC = +0.860, t-test p < 0.001).
This table shows molecular features associated with RHCE in patient tissues and cancer cell lines. In patient samples, RHCE 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, RHCE RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
