Q-omics provides the consensus-scored IMPACT profile across patient tissues and cancer cell-line models. IMPACT expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, IMPACT is differentially expressed in 12, with the highest sampling consensus in THCA. Additionally, IMPACT RNA expression shows 19,473 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, THCA, and ACC as cancer lineages where IMPACT 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 IMPACT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IMPACT survival associations across molecular data types. IMPACT RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IMPACT RNA expression–survival associations across cancer types. High IMPACT expression shows unfavorable associations in STAD, MESO, LGG and ACC, but favorable associations in KIRC and BRCA. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for IMPACT RNA expression.
This table summarizes IMPACT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 7. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for IMPACT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IMPACT shows lower tumor expression in THCA, KICH and UCEC and higher tumor expression in HNSC, LUSC and BLCA. The THCA box plot shows higher IMPACT RNA expression in normal versus tumor tissue (log2 FC = −1.019, t-test p < 0.001).
This table shows molecular features associated with IMPACT in patient tissues and cancer cell lines. In patient samples, IMPACT shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, IMPACT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and CNS.
