Q-omics provides the consensus-scored COQ6 profile across patient tissues and cancer cell-line models. COQ6 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, COQ6 is differentially expressed in 14, with the highest sampling consensus in LUAD. Additionally, COQ6 protein abundance shows 22,638 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, LUAD, and GBM as cancer lineages where COQ6 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 COQ6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes COQ6 survival associations across molecular data types. COQ6 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (1) 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 COQ6 RNA expression–survival associations across cancer types. High COQ6 expression shows unfavorable associations in UVM, KICH, LUAD and STAD, but favorable associations in KIRP and BRCA. The UVM 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 UVM as the clearest survival context for COQ6 RNA expression.
This table summarizes COQ6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 7. The strongest signals are observed in LUAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for COQ6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. COQ6 shows lower tumor expression in KICH and KIRC and higher tumor expression in LUAD, BLCA, LIHC and UCEC. The LUAD box plot shows higher COQ6 RNA expression in tumor versus normal tissue (log2 FC = +0.469, t-test p < 0.001).
This table shows molecular features associated with COQ6 in patient tissues and cancer cell lines. In patient samples, COQ6 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, COQ6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Leukemia.
