Q-omics provides the consensus-scored CEP104 profile across patient tissues and cancer cell-line models. CEP104 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CEP104 is differentially expressed in 9, with the highest sampling consensus in KICH. Additionally, CEP104 RNA expression shows 20,223 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, KICH, and ACC as cancer lineages where CEP104 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 CEP104 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CEP104 survival associations across molecular data types. CEP104 RNA expression shows survival associations in the most cancer types (23), 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 CEP104 RNA expression–survival associations across cancer types. High CEP104 expression shows unfavorable associations in ACC, LGG, LUSC, CESC and BLCA, but favorable associations in KIRC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for CEP104 RNA expression.
This table summarizes CEP104 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for CEP104. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CEP104 shows lower tumor expression in KICH and THCA and higher tumor expression in HNSC, COAD, STAD and CHOL. The KICH box plot shows higher CEP104 RNA expression in normal versus tumor tissue (log2 FC = −1.150, t-test p < 0.001).
This table shows molecular features associated with CEP104 in patient tissues and cancer cell lines. In patient samples, CEP104 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, CEP104 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 KIDNEY and BLOOD_Leukemia.
