Q-omics provides the consensus-scored CDC37 profile across patient tissues and cancer cell-line models. CDC37 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, CDC37 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, CDC37 RNA expression shows 18,761 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRC as cancer lineages where CDC37 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 CDC37 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CDC37 survival associations across molecular data types. CDC37 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (7) 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 CDC37 RNA expression–survival associations across cancer types. High CDC37 expression shows unfavorable associations in ACC, KIRP, LUAD, MESO and LGG, but favorable associations in STAD. 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 CDC37 RNA expression.
This table summarizes CDC37 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 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CDC37. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CDC37 shows higher tumor expression in KIRC, HNSC, COAD, LIHC, KIRP and STAD. The KIRC box plot shows higher CDC37 RNA expression in tumor versus normal tissue (log2 FC = +0.753, t-test p < 0.001).
This table shows molecular features associated with CDC37 in patient tissues and cancer cell lines. In patient samples, CDC37 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, CDC37 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and SOFT_TISSUE.
