Q-omics provides the consensus-scored CRCP profile across patient tissues and cancer cell-line models. CRCP expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, CRCP is differentially expressed in 17, with the highest sampling consensus in HNSC. Additionally, CRCP RNA expression shows 19,839 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight MESO, HNSC, and ACC as cancer lineages where CRCP 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 CRCP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CRCP survival associations across molecular data types. CRCP RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CRCP RNA expression–survival associations across cancer types. High CRCP expression shows unfavorable associations in MESO, PAAD, LGG, CESC, KICH and ACC. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify MESO as the clearest survival context for CRCP RNA expression.
This table summarizes CRCP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CRCP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CRCP shows higher tumor expression in HNSC, COAD, LUAD, BLCA, KIRP and STAD. The HNSC box plot shows higher CRCP RNA expression in tumor versus normal tissue (log2 FC = +1.039, t-test p < 0.001).
This table shows molecular features associated with CRCP in patient tissues and cancer cell lines. In patient samples, CRCP 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, CRCP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
