inositol hexakisphosphate kinase 1Genealiases: IHPK1 · PiUS
Q-omics provides the consensus-scored IP6K1 profile across patient tissues and cancer cell-line models. IP6K1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, IP6K1 is differentially expressed in 12, with the highest sampling consensus in LIHC. Additionally, IP6K1 RNA expression shows 19,947 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, LIHC, and ACC as cancer lineages where IP6K1 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 IP6K1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IP6K1 survival associations across molecular data types. IP6K1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (2) 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 IP6K1 RNA expression–survival associations across cancer types. High IP6K1 expression shows unfavorable associations in KICH and ACC, but favorable associations in UVM, HNSC, KIRC and BRCA. The UVM 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 UVM as the clearest survival context for IP6K1 RNA expression.
This table summarizes IP6K1 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 4. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for IP6K1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IP6K1 shows lower tumor expression in KICH, KIRC, LUAD, THCA and LUSC and higher tumor expression in LIHC. The LIHC box plot shows higher IP6K1 RNA expression in tumor versus normal tissue (log2 FC = +1.663, t-test p < 0.001).
This table shows molecular features associated with IP6K1 in patient tissues and cancer cell lines. In patient samples, IP6K1 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, IP6K1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
