Q-omics provides the consensus-scored IRGM profile across patient tissues and cancer cell-line models. IRGM expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, IRGM is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, IRGM RNA expression shows 13,874 significant gene co-expression associations, with the highest sampling consensus in SKCM. Together, these results highlight LUAD, HNSC, and SKCM as cancer lineages where IRGM 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 IRGM — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IRGM survival associations across molecular data types. IRGM RNA expression shows survival associations in the most cancer types (21), 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 IRGM RNA expression–survival associations across cancer types. High IRGM expression shows unfavorable associations in KIRC, LGG and THCA, but favorable associations in LUAD, SCLC and SKCM. The LUAD 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 LUAD as the clearest survival context for IRGM RNA expression.
This table summarizes IRGM tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for IRGM. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IRGM shows lower tumor expression in KICH and higher tumor expression in HNSC, KIRC, UCEC, LIHC and THCA. The HNSC box plot shows higher IRGM RNA expression in tumor versus normal tissue (log2 FC = +0.167, t-test p < 0.001).
This table shows molecular features associated with IRGM in patient tissues and cancer cell lines. In patient samples, IRGM shows the broadest associations at the RNA and protein expression levels, with SKCM recurring as the lineage with the largest associated feature set. In cancer cell lines, IRGM RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Lymphoma.
