Q-omics provides the consensus-scored INS profile across patient tissues and cancer cell-line models. INS expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, INS is differentially expressed in 1, with the highest sampling consensus in HNSC. Additionally, INS RNA expression shows 5,440 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight MESO, HNSC, and STAD as cancer lineages where INS 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 INS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes INS survival associations across molecular data types. INS RNA expression shows survival associations in the most cancer types (20), followed by mutation status (1) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible INS RNA expression–survival associations across cancer types. High INS expression shows unfavorable associations in MESO, THCA, THYM, UCEC, SARC and PRAD. The MESO 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 MESO as the clearest survival context for INS RNA expression.
This table summarizes INS tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 1, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for INS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. INS shows higher tumor expression in HNSC. The HNSC box plot shows higher INS RNA expression in tumor versus normal tissue (log2 FC = +0.016, t-test p = .028).
This table shows molecular features associated with INS in patient tissues and cancer cell lines. In patient samples, INS shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, INS RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and STOMACH.
