Q-omics provides the consensus-scored AGER profile across patient tissues and cancer cell-line models. AGER expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, AGER is differentially expressed in 11, with the highest sampling consensus in LUAD. Additionally, AGER RNA expression shows 16,846 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, LUAD, and UVM as cancer lineages where AGER 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 AGER — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AGER survival associations across molecular data types. AGER RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AGER RNA expression–survival associations across cancer types. High AGER expression shows unfavorable associations in ACC, KIRC and LUSC, but favorable associations in BLCA, HNSC and PAAD. 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 AGER RNA expression.
This table summarizes AGER 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 2. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for AGER. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AGER shows lower tumor expression in LUAD, KICH and LUSC and higher tumor expression in KIRC, COAD and LIHC. The LUAD box plot shows higher AGER RNA expression in normal versus tumor tissue (log2 FC = −7.943, t-test p < 0.001).
This table shows molecular features associated with AGER in patient tissues and cancer cell lines. In patient samples, AGER 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, AGER RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BONE.
