Q-omics provides the consensus-scored TRAF3IP2 profile across patient tissues and cancer cell-line models. TRAF3IP2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, TRAF3IP2 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, TRAF3IP2 RNA expression shows 19,098 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, and ACC as cancer lineages where TRAF3IP2 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 TRAF3IP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TRAF3IP2 survival associations across molecular data types. TRAF3IP2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TRAF3IP2 RNA expression–survival associations across cancer types. High TRAF3IP2 expression shows unfavorable associations in CESC, BLCA and LGG, but favorable associations in KIRC, UCEC and MESO. 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 TRAF3IP2 RNA expression.
This table summarizes TRAF3IP2 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 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for TRAF3IP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TRAF3IP2 shows lower tumor expression in KICH and COAD and higher tumor expression in KIRC, HNSC, KIRP and CHOL. The KIRC box plot shows higher TRAF3IP2 RNA expression in tumor versus normal tissue (log2 FC = +1.337, t-test p < 0.001).
This table shows molecular features associated with TRAF3IP2 in patient tissues and cancer cell lines. In patient samples, TRAF3IP2 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, TRAF3IP2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BONE.
