Q-omics provides the consensus-scored PA2G4P4 profile across patient tissues and cancer cell-line models. PA2G4P4 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, PA2G4P4 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, PA2G4P4 RNA expression shows 13,352 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, KIRC, and UVM as cancer lineages where PA2G4P4 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 PA2G4P4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PA2G4P4 survival associations across molecular data types. PA2G4P4 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 PA2G4P4 RNA expression–survival associations across cancer types. High PA2G4P4 expression shows unfavorable associations in ACC, KIRC, KICH, LIHC, UVM and ESCA. 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 PA2G4P4 RNA expression.
This table summarizes PA2G4P4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for PA2G4P4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PA2G4P4 shows higher tumor expression in KIRC, COAD, LUAD, LUSC, HNSC and LIHC. The KIRC box plot shows higher PA2G4P4 RNA expression in tumor versus normal tissue (log2 FC = +0.325, t-test p < 0.001).
This table shows molecular features associated with PA2G4P4 in patient tissues and cancer cell lines. In patient samples, PA2G4P4 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, PA2G4P4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUSC, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT.
