Q-omics provides the consensus-scored IGIP profile across patient tissues and cancer cell-line models. IGIP expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, IGIP is differentially expressed in 11, with the highest sampling consensus in LUAD. Additionally, IGIP RNA expression shows 22,444 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, LUAD, and PDAC as cancer lineages where IGIP 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 IGIP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IGIP survival associations across molecular data types. IGIP RNA expression shows survival associations in the most cancer types (29), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IGIP RNA expression–survival associations across cancer types. High IGIP expression shows unfavorable associations in CESC and UVM, but favorable associations in KIRC, HNSC, LGG and PAAD. 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 IGIP RNA expression.
This table summarizes IGIP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in LUAD for RNA.
This table ranks reproducible tumor–normal expression differences for IGIP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IGIP shows lower tumor expression in LUAD, BLCA, LUSC, THCA and UCEC and higher tumor expression in LIHC. The LUAD box plot shows higher IGIP RNA expression in normal versus tumor tissue (log2 FC = −1.214, t-test p < 0.001).
This table shows molecular features associated with IGIP in patient tissues and cancer cell lines. In patient samples, IGIP shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, IGIP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
