Q-omics provides the consensus-scored IKZF1 profile across patient tissues and cancer cell-line models. IKZF1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, IKZF1 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, IKZF1 RNA expression shows 21,354 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, KIRC, and LSCC as cancer lineages where IKZF1 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 IKZF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IKZF1 survival associations across molecular data types. IKZF1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IKZF1 RNA expression–survival associations across cancer types. High IKZF1 expression shows unfavorable associations in UVM, but favorable associations in HNSC, SKCM, LUAD, CESC and BRCA. The HNSC 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 HNSC as the clearest survival context for IKZF1 RNA expression.
This table summarizes IKZF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for IKZF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IKZF1 shows lower tumor expression in COAD, LUSC and LUAD and higher tumor expression in KIRC, KIRP and STAD. The KIRC box plot shows higher IKZF1 RNA expression in tumor versus normal tissue (log2 FC = +1.973, t-test p < 0.001).
This table shows molecular features associated with IKZF1 in patient tissues and cancer cell lines. In patient samples, IKZF1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, IKZF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
