Q-omics provides the consensus-scored IKBIP profile across patient tissues and cancer cell-line models. IKBIP expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, IKBIP is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, IKBIP protein abundance shows 26,935 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight MESO, KIRC, and GBM as cancer lineages where IKBIP 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 IKBIP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IKBIP survival associations across molecular data types. IKBIP RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IKBIP RNA expression–survival associations across cancer types. High IKBIP expression shows unfavorable associations in MESO, ACC, LIHC, KIRP, LGG and SCLC. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify MESO as the clearest survival context for IKBIP RNA expression.
This table summarizes IKBIP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, 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 IKBIP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IKBIP shows higher tumor expression in KIRC, HNSC, KIRP, BLCA, LIHC and STAD. The KIRC box plot shows higher IKBIP RNA expression in tumor versus normal tissue (log2 FC = +2.198, t-test p < 0.001).
This table shows molecular features associated with IKBIP in patient tissues and cancer cell lines. In patient samples, IKBIP 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, IKBIP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BONE.
