Q-omics provides the consensus-scored TRAF3 profile across patient tissues and cancer cell-line models. TRAF3 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, TRAF3 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, TRAF3 protein abundance shows 21,359 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight UVM, HNSC, and LUAD as cancer lineages where TRAF3 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 TRAF3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TRAF3 survival associations across molecular data types. TRAF3 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TRAF3 RNA expression–survival associations across cancer types. High TRAF3 expression shows unfavorable associations in UVM, ACC, LIHC, KICH and THYM, but favorable associations in PAAD. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify UVM as the clearest survival context for TRAF3 RNA expression.
This table summarizes TRAF3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for TRAF3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TRAF3 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, STAD, CHOL and ESCA. The HNSC box plot shows higher TRAF3 RNA expression in tumor versus normal tissue (log2 FC = +0.900, t-test p < 0.001).
This table shows molecular features associated with TRAF3 in patient tissues and cancer cell lines. In patient samples, TRAF3 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, TRAF3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Lymphoma.
