Q-omics provides the consensus-scored RPE profile across patient tissues and cancer cell-line models. RPE expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RPE is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, RPE RNA expression shows 20,212 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where RPE 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 RPE — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPE survival associations across molecular data types. RPE RNA expression shows survival associations in the most cancer types (24), 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 RPE RNA expression–survival associations across cancer types. High RPE expression shows unfavorable associations in ACC, KIRP, UVM, LIHC and PAAD, 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 RPE RNA expression.
This table summarizes RPE 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 5. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for RPE. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPE shows lower tumor expression in KICH and higher tumor expression in HNSC, LUAD, STAD, LIHC and BLCA. The HNSC box plot shows higher RPE RNA expression in tumor versus normal tissue (log2 FC = +0.811, t-test p < 0.001).
This table shows molecular features associated with RPE in patient tissues and cancer cell lines. In patient samples, RPE 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, RPE RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Lymphoma.
