Q-omics provides the consensus-scored RPIA profile across patient tissues and cancer cell-line models. RPIA 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, RPIA is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, RPIA RNA expression shows 19,479 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and COAD as cancer lineages where RPIA 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 RPIA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPIA survival associations across molecular data types. RPIA RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RPIA RNA expression–survival associations across cancer types. High RPIA expression shows unfavorable associations in ACC, KIRP, LIHC and LGG, but favorable associations in LUSC and LUAD. 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 RPIA RNA expression.
This table summarizes RPIA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RPIA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPIA shows higher tumor expression in COAD, KIRC, BLCA, LIHC, STAD and LUSC. The COAD box plot shows higher RPIA RNA expression in tumor versus normal tissue (log2 FC = +1.189, t-test p < 0.001).
This table shows molecular features associated with RPIA in patient tissues and cancer cell lines. In patient samples, RPIA 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, RPIA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
