Q-omics provides the consensus-scored COX16 profile across patient tissues and cancer cell-line models. COX16 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, COX16 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, COX16 RNA expression shows 18,413 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, KIRC, and ACC as cancer lineages where COX16 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 COX16 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes COX16 survival associations across molecular data types. COX16 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible COX16 RNA expression–survival associations across cancer types. High COX16 expression shows unfavorable associations in UVM, HNSC, LUAD, UCS and ACC, but favorable associations in KIRC. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify UVM as the clearest survival context for COX16 RNA expression.
This table summarizes COX16 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 4. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for COX16. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. COX16 shows lower tumor expression in KIRC and THCA and higher tumor expression in HNSC, BLCA, LIHC and BRCA. The KIRC box plot shows higher COX16 RNA expression in normal versus tumor tissue (log2 FC = −0.512, t-test p < 0.001).
This table shows molecular features associated with COX16 in patient tissues and cancer cell lines. In patient samples, COX16 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, COX16 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 BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
