interferon regulatory factor 2 binding protein 2Genealiases: CVID14 · LRIR2
Q-omics provides the consensus-scored IRF2BP2 profile across patient tissues and cancer cell-line models. IRF2BP2 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, IRF2BP2 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, IRF2BP2 protein abundance shows 19,773 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight KIRC, and HNSC as cancer lineages where IRF2BP2 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 IRF2BP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IRF2BP2 survival associations across molecular data types. IRF2BP2 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) 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 IRF2BP2 RNA expression–survival associations across cancer types. High IRF2BP2 expression shows unfavorable associations in LIHC, CESC, READ and ESCA, but favorable associations in KIRC and GBM. 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 IRF2BP2 RNA expression.
This table summarizes IRF2BP2 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 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for IRF2BP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IRF2BP2 shows lower tumor expression in KICH and higher tumor expression in KIRC, COAD, LIHC, HNSC and CHOL. The KIRC box plot shows higher IRF2BP2 RNA expression in tumor versus normal tissue (log2 FC = +0.746, t-test p < 0.001).
This table shows molecular features associated with IRF2BP2 in patient tissues and cancer cell lines. In patient samples, IRF2BP2 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, IRF2BP2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in LIVER and UPPER_AERODIGESTIVE_TRACT.
