SET domain containing 3, actin N3(tau)-histidine methyltransferaseGenealiases: C14orf154 · hSETD3
Q-omics provides the consensus-scored SETD3 profile across patient tissues and cancer cell-line models. SETD3 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, SETD3 is differentially expressed in 14, with the highest sampling consensus in THCA. Additionally, SETD3 RNA expression shows 19,358 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, THCA, and ACC as cancer lineages where SETD3 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 SETD3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SETD3 survival associations across molecular data types. SETD3 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SETD3 RNA expression–survival associations across cancer types. High SETD3 expression shows unfavorable associations in HNSC, CESC and BLCA, but favorable associations in KIRC, BRCA and LGG. 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 SETD3 RNA expression.
This table summarizes SETD3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 3. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SETD3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SETD3 shows lower tumor expression in THCA, LUAD, READ, KIRP and UCEC and higher tumor expression in LIHC. The THCA box plot shows higher SETD3 RNA expression in normal versus tumor tissue (log2 FC = −0.592, t-test p < 0.001).
This table shows molecular features associated with SETD3 in patient tissues and cancer cell lines. In patient samples, SETD3 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, SETD3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Leukemia.
