Q-omics provides the consensus-scored IL4R profile across patient tissues and cancer cell-line models. IL4R expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, IL4R is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, IL4R protein abundance shows 25,436 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, KIRC, and GBM as cancer lineages where IL4R 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 IL4R — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IL4R survival associations across molecular data types. IL4R RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 IL4R RNA expression–survival associations across cancer types. High IL4R expression shows unfavorable associations in KIRP, LGG, LUSC, ACC and MESO, but favorable associations in ESCA. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRP as the clearest survival context for IL4R RNA expression.
This table summarizes IL4R 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for IL4R. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IL4R shows lower tumor expression in KICH and COAD and higher tumor expression in KIRC, KIRP, THCA and HNSC. The KIRC box plot shows higher IL4R RNA expression in tumor versus normal tissue (log2 FC = +1.599, t-test p < 0.001).
This table shows molecular features associated with IL4R in patient tissues and cancer cell lines. In patient samples, IL4R 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, IL4R RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BONE.
