Q-omics provides the consensus-scored CROCC profile across patient tissues and cancer cell-line models. CROCC expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CROCC is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, CROCC protein abundance shows 25,156 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRC, COAD, and LUAD as cancer lineages where CROCC 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 CROCC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CROCC survival associations across molecular data types. CROCC RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) 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 CROCC RNA expression–survival associations across cancer types. High CROCC expression shows unfavorable associations in KIRC, ACC, LIHC and LGG, but favorable associations in HNSC and UCEC. The KIRC 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 KIRC as the clearest survival context for CROCC RNA expression.
This table summarizes CROCC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 7. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CROCC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CROCC shows lower tumor expression in KICH and UCEC and higher tumor expression in COAD, LIHC, HNSC and CHOL. The COAD box plot shows higher CROCC RNA expression in tumor versus normal tissue (log2 FC = +0.776, t-test p < 0.001).
This table shows molecular features associated with CROCC in patient tissues and cancer cell lines. In patient samples, CROCC shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, CROCC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
