Q-omics provides the consensus-scored COQ2 profile across patient tissues and cancer cell-line models. COQ2 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, COQ2 is differentially expressed in 9, with the highest sampling consensus in STAD. Additionally, COQ2 RNA expression shows 17,798 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, STAD, and ACC as cancer lineages where COQ2 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 COQ2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes COQ2 survival associations across molecular data types. COQ2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible COQ2 RNA expression–survival associations across cancer types. High COQ2 expression shows unfavorable associations in UVM, LUAD, THYM and LGG, but favorable associations in COAD and READ. 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 COQ2 RNA expression.
This table summarizes COQ2 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 1. The strongest signals are observed in STAD for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for COQ2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. COQ2 shows lower tumor expression in KIRC and higher tumor expression in STAD, BRCA, LIHC, BLCA and KICH. The STAD box plot shows higher COQ2 RNA expression in tumor versus normal tissue (log2 FC = +0.710, t-test p < 0.001).
This table shows molecular features associated with COQ2 in patient tissues and cancer cell lines. In patient samples, COQ2 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, COQ2 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 BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
