Q-omics provides the consensus-scored PI4KB profile across patient tissues and cancer cell-line models. PI4KB 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, PI4KB is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, PI4KB RNA expression shows 19,447 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where PI4KB 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 PI4KB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PI4KB survival associations across molecular data types. PI4KB RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 PI4KB RNA expression–survival associations across cancer types. High PI4KB expression shows unfavorable associations in ACC, KICH, LIHC, UVM and LGG, but favorable associations in 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 PI4KB RNA expression.
This table summarizes PI4KB 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 3. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PI4KB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PI4KB shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, LIHC, KIRC and STAD. The HNSC box plot shows higher PI4KB RNA expression in tumor versus normal tissue (log2 FC = +0.554, t-test p < 0.001).
This table shows molecular features associated with PI4KB in patient tissues and cancer cell lines. In patient samples, PI4KB 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, PI4KB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and UPPER_AERODIGESTIVE_TRACT.
