Q-omics provides the consensus-scored IQCM profile across patient tissues and cancer cell-line models. IQCM expression is associated with patient survival in 15 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, IQCM is differentially expressed in 8, with the highest sampling consensus in COAD. Additionally, IQCM RNA expression shows 10,680 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRP, COAD, and THYM as cancer lineages where IQCM 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 IQCM — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IQCM survival associations across molecular data types. IQCM RNA expression shows survival associations in the most cancer types (15), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IQCM RNA expression–survival associations across cancer types. High IQCM expression shows unfavorable associations in KIRP, HNSC, LIHC, LGG and STAD, but favorable associations in UCS. The KIRP 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 KIRP as the clearest survival context for IQCM RNA expression.
This table summarizes IQCM tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for IQCM. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IQCM shows lower tumor expression in COAD and READ and higher tumor expression in HNSC, LUSC, BLCA and LUAD. The COAD box plot shows higher IQCM RNA expression in normal versus tumor tissue (log2 FC = −0.704, t-test p < 0.001).
This table shows molecular features associated with IQCM in patient tissues and cancer cell lines. In patient samples, IQCM 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, IQCM RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS.
