Q-omics provides the consensus-scored PI4KA profile across patient tissues and cancer cell-line models. PI4KA expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PI4KA is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, PI4KA protein abundance shows 22,806 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, and GBM as cancer lineages where PI4KA 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 PI4KA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PI4KA survival associations across molecular data types. PI4KA RNA expression shows survival associations in the most cancer types (19), followed by mutation status (11) 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 PI4KA RNA expression–survival associations across cancer types. High PI4KA expression shows unfavorable associations in ACC, UVM and LUSC, but favorable associations in HNSC, KIRC and SCLC. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for PI4KA RNA expression.
This table summarizes PI4KA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PI4KA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PI4KA shows lower tumor expression in KIRC and COAD and higher tumor expression in HNSC, LIHC, CHOL and BRCA. The HNSC box plot shows higher PI4KA RNA expression in tumor versus normal tissue (log2 FC = +0.719, t-test p < 0.001).
This table shows molecular features associated with PI4KA in patient tissues and cancer cell lines. In patient samples, PI4KA shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, PI4KA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BLOOD_Leukemia.
