Q-omics provides the consensus-scored PIP4K2C profile across patient tissues and cancer cell-line models. PIP4K2C expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PIP4K2C is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, PIP4K2C RNA expression shows 19,337 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight HNSC, KIRC, and ACC as cancer lineages where PIP4K2C 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 PIP4K2C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PIP4K2C survival associations across molecular data types. PIP4K2C RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PIP4K2C RNA expression–survival associations across cancer types. High PIP4K2C expression shows unfavorable associations in HNSC, SKCM, LIHC, BLCA and LGG, but favorable associations in KIRC. The HNSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify HNSC as the clearest survival context for PIP4K2C RNA expression.
This table summarizes PIP4K2C 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 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PIP4K2C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PIP4K2C shows lower tumor expression in KIRC and higher tumor expression in HNSC, BLCA, LIHC, LUAD and BRCA. The KIRC box plot shows higher PIP4K2C RNA expression in normal versus tumor tissue (log2 FC = −1.393, t-test p < 0.001).
This table shows molecular features associated with PIP4K2C in patient tissues and cancer cell lines. In patient samples, PIP4K2C 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, PIP4K2C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Myeloma.
