Q-omics provides the consensus-scored PIKFYVE profile across patient tissues and cancer cell-line models. PIKFYVE expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PIKFYVE is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, PIKFYVE RNA expression shows 21,593 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where PIKFYVE 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 PIKFYVE — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PIKFYVE survival associations across molecular data types. PIKFYVE RNA expression shows survival associations in the most cancer types (22), followed by mutation status (11) 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 PIKFYVE RNA expression–survival associations across cancer types. High PIKFYVE expression shows unfavorable associations in ACC, LUSC and LIHC, but favorable associations in KIRC, HNSC and CHOL. The KIRC 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 KIRC as the clearest survival context for PIKFYVE RNA expression.
This table summarizes PIKFYVE tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PIKFYVE. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PIKFYVE shows lower tumor expression in THCA, BRCA and KICH and higher tumor expression in HNSC, LIHC and STAD. The HNSC box plot shows higher PIKFYVE RNA expression in tumor versus normal tissue (log2 FC = +0.625, t-test p = .001).
This table shows molecular features associated with PIKFYVE in patient tissues and cancer cell lines. In patient samples, PIKFYVE 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, PIKFYVE RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
