Q-omics provides the consensus-scored CEP170 profile across patient tissues and cancer cell-line models. CEP170 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, CEP170 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, CEP170 protein abundance shows 26,038 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight MESO, HNSC, and LUAD as cancer lineages where CEP170 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 CEP170 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CEP170 survival associations across molecular data types. CEP170 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (6) 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 CEP170 RNA expression–survival associations across cancer types. High CEP170 expression shows unfavorable associations in MESO, ACC, KIRP, LIHC, LUSC and BLCA. The MESO 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 MESO as the clearest survival context for CEP170 RNA expression.
This table summarizes CEP170 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, 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 CEP170. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CEP170 shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, KIRC, KIRP and LIHC. The HNSC box plot shows higher CEP170 RNA expression in tumor versus normal tissue (log2 FC = +1.297, t-test p < 0.001).
This table shows molecular features associated with CEP170 in patient tissues and cancer cell lines. In patient samples, CEP170 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, CEP170 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 SKIN and BLOOD_Lymphoma.
