SET and MYND domain containing 3Genealiases: KMT3E · ZMYND1 · ZNFN3A1 · bA74P14.1
Q-omics provides the consensus-scored SMYD3 profile across patient tissues and cancer cell-line models. SMYD3 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SMYD3 is differentially expressed in 18, with the highest sampling consensus in HNSC. Additionally, SMYD3 RNA expression shows 20,263 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, HNSC, and ACC as cancer lineages where SMYD3 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 SMYD3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SMYD3 survival associations across molecular data types. SMYD3 RNA expression shows survival associations in the most cancer types (25), 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 SMYD3 RNA expression–survival associations across cancer types. High SMYD3 expression shows unfavorable associations in UVM, LIHC, KIRP, ACC, KICH and MESO. The UVM 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 UVM as the clearest survival context for SMYD3 RNA expression.
This table summarizes SMYD3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 18, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SMYD3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SMYD3 shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, COAD, LIHC and LUAD. The HNSC box plot shows higher SMYD3 RNA expression in tumor versus normal tissue (log2 FC = +1.443, t-test p < 0.001).
This table shows molecular features associated with SMYD3 in patient tissues and cancer cell lines. In patient samples, SMYD3 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, SMYD3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and UPPER_AERODIGESTIVE_TRACT.
