Q-omics provides the consensus-scored INSC profile across patient tissues and cancer cell-line models. INSC 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, INSC is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, INSC RNA expression shows 11,229 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight LUAD, KIRC, and ESCA as cancer lineages where INSC 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 INSC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes INSC survival associations across molecular data types. INSC RNA expression shows survival associations in the most cancer types (21), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible INSC RNA expression–survival associations across cancer types. High INSC expression shows unfavorable associations in LUAD, KIRP, UVM and MESO, but favorable associations in COAD and OV. The LUAD 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 LUAD as the clearest survival context for INSC RNA expression.
This table summarizes INSC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for INSC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. INSC shows lower tumor expression in KIRC, LUAD, BLCA, LUSC, COAD and KIRP. The KIRC box plot shows higher INSC RNA expression in normal versus tumor tissue (log2 FC = −0.411, t-test p < 0.001).
This table shows molecular features associated with INSC in patient tissues and cancer cell lines. In patient samples, INSC shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, INSC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and LARGE_INTESTINE.
