Q-omics provides the consensus-scored AGAP2-AS1 profile across patient tissues and cancer cell-line models. AGAP2-AS1 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, AGAP2-AS1 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, AGAP2-AS1 RNA expression shows 15,954 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where AGAP2-AS1 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 AGAP2-AS1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AGAP2-AS1 survival associations across molecular data types. AGAP2-AS1 RNA expression shows survival associations in the most cancer types (21). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AGAP2-AS1 RNA expression–survival associations across cancer types. High AGAP2-AS1 expression shows unfavorable associations in ACC, MESO, KIRP, BLCA, KIRC and LGG. The ACC 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 ACC as the clearest survival context for AGAP2-AS1 RNA expression.
This table summarizes AGAP2-AS1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for AGAP2-AS1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AGAP2-AS1 shows higher tumor expression in HNSC, COAD, KIRC, STAD, READ and LUAD. The HNSC box plot shows higher AGAP2-AS1 RNA expression in tumor versus normal tissue (log2 FC = +1.474, t-test p < 0.001).
This table shows molecular features associated with AGAP2-AS1 in patient tissues and cancer cell lines. In patient samples, AGAP2-AS1 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, AGAP2-AS1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE.
