Q-omics provides the consensus-scored KMT2E profile across patient tissues and cancer cell-line models. KMT2E expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, KMT2E is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, KMT2E RNA expression shows 21,295 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, and ACC as cancer lineages where KMT2E 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 KMT2E — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KMT2E survival associations across molecular data types. KMT2E RNA expression shows survival associations in the most cancer types (28), followed by mutation status (6) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KMT2E RNA expression–survival associations across cancer types. High KMT2E expression shows unfavorable associations in KICH, ACC, CESC and KIRP, but favorable associations in KIRC and HNSC. 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 KMT2E RNA expression.
This table summarizes KMT2E tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for KMT2E. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KMT2E shows lower tumor expression in KICH and COAD and higher tumor expression in KIRC, LIHC, CHOL and HNSC. The KIRC box plot shows higher KMT2E RNA expression in tumor versus normal tissue (log2 FC = +0.545, t-test p < 0.001).
This table shows molecular features associated with KMT2E in patient tissues and cancer cell lines. In patient samples, KMT2E 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, KMT2E RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
