Q-omics provides the consensus-scored ACO2 profile across patient tissues and cancer cell-line models. ACO2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ACO2 is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, ACO2 protein abundance shows 35,622 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, THCA, and GBM as cancer lineages where ACO2 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 ACO2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACO2 survival associations across molecular data types. ACO2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ACO2 RNA expression–survival associations across cancer types. High ACO2 expression shows unfavorable associations in UVM, but favorable associations in KIRC, SCLC, KIRP, HNSC and LGG. The KIRC 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 KIRC as the clearest survival context for ACO2 RNA expression.
This table summarizes ACO2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 11. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ACO2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACO2 shows lower tumor expression in THCA, COAD, KIRP and BLCA and higher tumor expression in LIHC and CHOL. The THCA box plot shows higher ACO2 RNA expression in normal versus tumor tissue (log2 FC = −0.931, t-test p < 0.001).
This table shows molecular features associated with ACO2 in patient tissues and cancer cell lines. In patient samples, ACO2 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, ACO2 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 SKIN.
