Q-omics provides the consensus-scored INTU profile across patient tissues and cancer cell-line models. INTU expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, INTU is differentially expressed in 8, with the highest sampling consensus in LIHC. Additionally, INTU RNA expression shows 20,087 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight LGG, LIHC, and THYM as cancer lineages where INTU 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 INTU — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes INTU survival associations across molecular data types. INTU RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) 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 INTU RNA expression–survival associations across cancer types. High INTU expression shows unfavorable associations in LGG, LIHC, LUSC and KICH, but favorable associations in BRCA and KIRP. The LGG Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify LGG as the clearest survival context for INTU RNA expression.
This table summarizes INTU tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 2. The strongest signals are observed in LIHC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for INTU. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. INTU shows lower tumor expression in KICH, BRCA and THCA and higher tumor expression in LIHC, CHOL and COAD. The LIHC box plot shows higher INTU RNA expression in tumor versus normal tissue (log2 FC = +0.354, t-test p < 0.001).
This table shows molecular features associated with INTU in patient tissues and cancer cell lines. In patient samples, INTU shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, INTU RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and LARGE_INTESTINE.
