Q-omics provides the consensus-scored IL32 profile across patient tissues and cancer cell-line models. IL32 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, IL32 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, IL32 RNA expression shows 20,194 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight SKCM, KIRC, and LSCC as cancer lineages where IL32 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 IL32 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IL32 survival associations across molecular data types. IL32 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IL32 RNA expression–survival associations across cancer types. High IL32 expression shows unfavorable associations in UVM, ACC and MESO, but favorable associations in SKCM, UCEC and READ. The SKCM 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 SKCM as the clearest survival context for IL32 RNA expression.
This table summarizes IL32 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 3. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for IL32. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IL32 shows lower tumor expression in LUSC and higher tumor expression in KIRC, KIRP, HNSC, STAD and LIHC. The KIRC box plot shows higher IL32 RNA expression in tumor versus normal tissue (log2 FC = +2.759, t-test p < 0.001).
This table shows molecular features associated with IL32 in patient tissues and cancer cell lines. In patient samples, IL32 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, IL32 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Lymphoma.
