centrosomal protein 350Genealiases: CAP350 · GM133
Q-omics provides the consensus-scored CEP350 profile across patient tissues and cancer cell-line models. CEP350 expression is associated with patient survival in 30 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, CEP350 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, CEP350 RNA expression shows 21,338 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRC as cancer lineages where CEP350 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 CEP350 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CEP350 survival associations across molecular data types. CEP350 RNA expression shows survival associations in the most cancer types (30), followed by mutation status (5) 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 CEP350 RNA expression–survival associations across cancer types. High CEP350 expression shows unfavorable associations in ACC, UVM, KIRP and KICH, but favorable associations in KIRC and HNSC. 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 CEP350 RNA expression.
This table summarizes CEP350 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 5. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for CEP350. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CEP350 shows lower tumor expression in THCA and higher tumor expression in KIRC, LIHC, HNSC, BRCA and CHOL. The KIRC box plot shows higher CEP350 RNA expression in tumor versus normal tissue (log2 FC = +0.438, t-test p < 0.001).
This table shows molecular features associated with CEP350 in patient tissues and cancer cell lines. In patient samples, CEP350 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, CEP350 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 PANCREAS and BLOOD_Leukemia.
