Q-omics provides the consensus-scored AGO2 profile across patient tissues and cancer cell-line models. AGO2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, AGO2 is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, AGO2 RNA expression shows 20,730 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRP, HNSC, and ACC as cancer lineages where AGO2 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 AGO2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AGO2 survival associations across molecular data types. AGO2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AGO2 RNA expression–survival associations across cancer types. High AGO2 expression shows unfavorable associations in KIRP, ACC, CESC, LIHC, MESO and UVM. The KIRP 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 KIRP as the clearest survival context for AGO2 RNA expression.
This table summarizes AGO2 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 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AGO2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AGO2 shows higher tumor expression in HNSC, COAD, LIHC, KIRC, STAD and LUSC. The HNSC box plot shows higher AGO2 RNA expression in tumor versus normal tissue (log2 FC = +1.196, t-test p < 0.001).
This table shows molecular features associated with AGO2 in patient tissues and cancer cell lines. In patient samples, AGO2 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, AGO2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Lymphoma.
