Q-omics provides the consensus-scored AGAP4 profile across patient tissues and cancer cell-line models. AGAP4 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, AGAP4 is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, AGAP4 RNA expression shows 20,404 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, KIRC, and UVM as cancer lineages where AGAP4 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 AGAP4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AGAP4 survival associations across molecular data types. AGAP4 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AGAP4 RNA expression–survival associations across cancer types. High AGAP4 expression shows unfavorable associations in ACC, KIRC, LIHC and UVM, but favorable associations in BLCA and HNSC. 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 AGAP4 RNA expression.
This table summarizes AGAP4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for AGAP4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AGAP4 shows lower tumor expression in KICH and higher tumor expression in KIRC, LIHC, CHOL, COAD and READ. The KIRC box plot shows higher AGAP4 RNA expression in tumor versus normal tissue (log2 FC = +0.388, t-test p < 0.001).
This table shows molecular features associated with AGAP4 in patient tissues and cancer cell lines. In patient samples, AGAP4 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, AGAP4 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 BLOOD_Lymphoma and URINARY_TRACT.
