Q-omics provides the consensus-scored COQ3 profile across patient tissues and cancer cell-line models. COQ3 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, COQ3 is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, COQ3 protein abundance shows 33,775 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, and LSCC as cancer lineages where COQ3 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 COQ3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes COQ3 survival associations across molecular data types. COQ3 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (1) and mass-spec protein abundance (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible COQ3 RNA expression–survival associations across cancer types. High COQ3 expression shows unfavorable associations in KIRC, LIHC, ESCA, HNSC and COAD, but favorable associations in READ. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRC as the clearest survival context for COQ3 RNA expression.
This table summarizes COQ3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 11. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for COQ3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. COQ3 shows lower tumor expression in KIRC and KIRP and higher tumor expression in HNSC, LUSC, LUAD and LIHC. The KIRC box plot shows higher COQ3 RNA expression in normal versus tumor tissue (log2 FC = −0.987, t-test p < 0.001).
This table shows molecular features associated with COQ3 in patient tissues and cancer cell lines. In patient samples, COQ3 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, COQ3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and UPPER_AERODIGESTIVE_TRACT.
