Q-omics provides the consensus-scored COQ9 profile across patient tissues and cancer cell-line models. COQ9 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, COQ9 is differentially expressed in 12, with the highest sampling consensus in THCA. Additionally, COQ9 protein abundance shows 23,104 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight KIRP, THCA, and HNSC as cancer lineages where COQ9 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 COQ9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes COQ9 survival associations across molecular data types. COQ9 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible COQ9 RNA expression–survival associations across cancer types. High COQ9 expression shows unfavorable associations in HNSC, SKCM, BLCA and LGG, but favorable associations in KIRP and MESO. The KIRP 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 KIRP as the clearest survival context for COQ9 RNA expression.
This table summarizes COQ9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for COQ9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. COQ9 shows lower tumor expression in THCA and KIRC and higher tumor expression in LUAD, LUSC, UCEC and CHOL. The THCA box plot shows higher COQ9 RNA expression in normal versus tumor tissue (log2 FC = −0.974, t-test p < 0.001).
This table shows molecular features associated with COQ9 in patient tissues and cancer cell lines. In patient samples, COQ9 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, COQ9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
