Q-omics provides the consensus-scored IL1B profile across patient tissues and cancer cell-line models. IL1B expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, IL1B is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, IL1B RNA expression shows 15,570 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight CESC, HNSC, and GBM as cancer lineages where IL1B 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 IL1B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IL1B survival associations across molecular data types. IL1B RNA expression shows survival associations in the most cancer types (27), followed by mutation status (5) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IL1B RNA expression–survival associations across cancer types. High IL1B expression shows unfavorable associations in CESC, UVM, STAD, LIHC and LUSC, but favorable associations in SKCM. The CESC 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 CESC as the clearest survival context for IL1B RNA expression.
This table summarizes IL1B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for IL1B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IL1B shows lower tumor expression in KICH, LIHC, LUAD and LUSC and higher tumor expression in HNSC and COAD. The HNSC box plot shows higher IL1B RNA expression in tumor versus normal tissue (log2 FC = +1.680, t-test p < 0.001).
This table shows molecular features associated with IL1B in patient tissues and cancer cell lines. In patient samples, IL1B 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, IL1B 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 URINARY_TRACT and BLOOD_Leukemia.
