Q-omics provides the consensus-scored ITPKB profile across patient tissues and cancer cell-line models. ITPKB expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ITPKB is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, ITPKB protein abundance shows 19,081 significant protein co-abundance associations, with the highest sampling consensus in UCEC. Together, these results highlight KIRC, KICH, and UCEC as cancer lineages where ITPKB 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 ITPKB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ITPKB survival associations across molecular data types. ITPKB RNA expression shows survival associations in the most cancer types (21), followed by mutation status (5) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ITPKB RNA expression–survival associations across cancer types. High ITPKB expression shows unfavorable associations in LGG and SKCM, but favorable associations in KIRC, HNSC, UCEC and ESCA. 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 ITPKB RNA expression.
This table summarizes ITPKB 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 7. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ITPKB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ITPKB shows lower tumor expression in KICH, KIRC, KIRP, LUAD and BLCA and higher tumor expression in HNSC. The KICH box plot shows higher ITPKB RNA expression in normal versus tumor tissue (log2 FC = −2.317, t-test p < 0.001).
This table shows molecular features associated with ITPKB in patient tissues and cancer cell lines. In patient samples, ITPKB shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, ITPKB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
