Q-omics provides the consensus-scored IVD profile across patient tissues and cancer cell-line models. IVD expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, IVD is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, IVD RNA expression shows 19,447 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight MESO, THCA, and UVM as cancer lineages where IVD 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 IVD — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IVD survival associations across molecular data types. IVD RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IVD RNA expression–survival associations across cancer types. High IVD expression shows favorable associations in MESO, KIRC, KIRP, LIHC, LUAD and BRCA. The MESO Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify MESO as the clearest survival context for IVD RNA expression.
This table summarizes IVD 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 8. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for IVD. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IVD shows lower tumor expression in THCA, LUAD, KIRC, KIRP, LIHC and LUSC. The THCA box plot shows higher IVD RNA expression in normal versus tumor tissue (log2 FC = −1.727, t-test p < 0.001).
This table shows molecular features associated with IVD in patient tissues and cancer cell lines. In patient samples, IVD shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, IVD RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
