Q-omics provides the consensus-scored IGLL1 profile across patient tissues and cancer cell-line models. IGLL1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, IGLL1 is differentially expressed in 6, with the highest sampling consensus in LUAD. Additionally, IGLL1 protein abundance shows 21,054 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, LUAD, and GBM as cancer lineages where IGLL1 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 IGLL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IGLL1 survival associations across molecular data types. IGLL1 RNA expression shows survival associations in the most cancer types (25), 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 IGLL1 RNA expression–survival associations across cancer types. High IGLL1 expression shows unfavorable associations in ACC and KIRC, but favorable associations in HNSC, SKCM, UCEC and OV. The HNSC 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 HNSC as the clearest survival context for IGLL1 RNA expression.
This table summarizes IGLL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6, while mass-spec protein shows differences in 8. The strongest signals are observed in LUAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for IGLL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IGLL1 shows lower tumor expression in KICH, COAD and STAD and higher tumor expression in LUAD, HNSC and CHOL. The LUAD box plot shows higher IGLL1 RNA expression in tumor versus normal tissue (log2 FC = +0.758, t-test p < 0.001).
This table shows molecular features associated with IGLL1 in patient tissues and cancer cell lines. In patient samples, IGLL1 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, IGLL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
