HECT domain E3 ubiquitin protein ligase 3Genealiases: []
Q-omics provides the consensus-scored HECTD3 profile across patient tissues and cancer cell-line models. HECTD3 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, HECTD3 is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, HECTD3 protein abundance shows 31,447 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight MESO, COAD, and PDAC as cancer lineages where HECTD3 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 HECTD3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HECTD3 survival associations across molecular data types. HECTD3 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HECTD3 RNA expression–survival associations across cancer types. High HECTD3 expression shows unfavorable associations in MESO, LIHC, ACC and LGG, but favorable associations in SCLC and THCA. The MESO 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 MESO as the clearest survival context for HECTD3 RNA expression.
This table summarizes HECTD3 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 10. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for HECTD3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HECTD3 shows lower tumor expression in COAD and KICH and higher tumor expression in STAD, LIHC, BLCA and KIRC. The COAD box plot shows higher HECTD3 RNA expression in normal versus tumor tissue (log2 FC = −0.767, t-test p < 0.001).
This table shows molecular features associated with HECTD3 in patient tissues and cancer cell lines. In patient samples, HECTD3 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, HECTD3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
