insulin like growth factor binding protein acid labile subunitGenealiases: ACLSD · ALS
Q-omics provides the consensus-scored IGFALS profile across patient tissues and cancer cell-line models. IGFALS expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, IGFALS is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, IGFALS protein abundance shows 24,695 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight BRCA, KIRC, and GBM as cancer lineages where IGFALS 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 IGFALS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IGFALS survival associations across molecular data types. IGFALS RNA expression shows survival associations in the most cancer types (28), 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 IGFALS RNA expression–survival associations across cancer types. High IGFALS expression shows unfavorable associations in UCEC, but favorable associations in BRCA, LUAD, HNSC, SKCM and LGG. The BRCA 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 BRCA as the clearest survival context for IGFALS RNA expression.
This table summarizes IGFALS 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 7. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for IGFALS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IGFALS shows lower tumor expression in KIRC, LUAD, KICH, LIHC, LUSC and KIRP. The KIRC box plot shows higher IGFALS RNA expression in normal versus tumor tissue (log2 FC = −0.880, t-test p < 0.001).
This table shows molecular features associated with IGFALS in patient tissues and cancer cell lines. In patient samples, IGFALS 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, IGFALS 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 LARGE_INTESTINE and BLOOD_Leukemia.
