Q-omics provides the consensus-scored COQ10B profile across patient tissues and cancer cell-line models. COQ10B expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, COQ10B is differentially expressed in 13, with the highest sampling consensus in KICH. Additionally, COQ10B protein abundance shows 22,315 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, KICH, and GBM as cancer lineages where COQ10B 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 COQ10B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes COQ10B survival associations across molecular data types. COQ10B RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible COQ10B RNA expression–survival associations across cancer types. High COQ10B expression shows unfavorable associations in UVM, HNSC, LGG, ACC, SCLC and UCEC. 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 COQ10B RNA expression.
This table summarizes COQ10B 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 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for COQ10B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. COQ10B shows lower tumor expression in KICH, BLCA, KIRC and COAD and higher tumor expression in HNSC and LIHC. The KICH box plot shows higher COQ10B RNA expression in normal versus tumor tissue (log2 FC = −1.087, t-test p < 0.001).
This table shows molecular features associated with COQ10B in patient tissues and cancer cell lines. In patient samples, COQ10B 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, COQ10B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in BONE and SKIN.
