Q-omics provides the consensus-scored PAK4 profile across patient tissues and cancer cell-line models. PAK4 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PAK4 is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, PAK4 RNA expression shows 19,985 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and BLCA as cancer lineages where PAK4 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 PAK4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PAK4 survival associations across molecular data types. PAK4 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (2) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PAK4 RNA expression–survival associations across cancer types. High PAK4 expression shows unfavorable associations in ACC, LGG, LUAD, LIHC and MESO, but favorable associations in SCLC. 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 PAK4 RNA expression.
This table summarizes PAK4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 4. The strongest signals are observed in BLCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PAK4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PAK4 shows lower tumor expression in THCA and KIRC and higher tumor expression in BLCA, STAD, LIHC and HNSC. The BLCA box plot shows higher PAK4 RNA expression in tumor versus normal tissue (log2 FC = +1.113, t-test p < 0.001).
This table shows molecular features associated with PAK4 in patient tissues and cancer cell lines. In patient samples, PAK4 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, PAK4 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 BLOOD_Leukemia and LARGE_INTESTINE.
