Q-omics provides the consensus-scored EHMT1 profile across patient tissues and cancer cell-line models. EHMT1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, EHMT1 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, EHMT1 protein abundance shows 24,412 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where EHMT1 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 EHMT1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EHMT1 survival associations across molecular data types. EHMT1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (9) 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 EHMT1 RNA expression–survival associations across cancer types. High EHMT1 expression shows unfavorable associations in ACC, MESO and LGG, but favorable associations in SCLC, UCEC and GBM. The ACC 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 ACC as the clearest survival context for EHMT1 RNA expression.
This table summarizes EHMT1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for EHMT1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EHMT1 shows lower tumor expression in THCA and higher tumor expression in HNSC, COAD, STAD, LIHC and CHOL. The HNSC box plot shows higher EHMT1 RNA expression in tumor versus normal tissue (log2 FC = +0.901, t-test p < 0.001).
This table shows molecular features associated with EHMT1 in patient tissues and cancer cell lines. In patient samples, EHMT1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, EHMT1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
