Q-omics provides the consensus-scored TAX1BP3 profile across patient tissues and cancer cell-line models. TAX1BP3 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, TAX1BP3 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, TAX1BP3 protein abundance shows 29,148 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight LUAD, HNSC, and PDAC as cancer lineages where TAX1BP3 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 TAX1BP3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TAX1BP3 survival associations across molecular data types. TAX1BP3 RNA expression shows survival associations in the most cancer types (25), 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 TAX1BP3 RNA expression–survival associations across cancer types. High TAX1BP3 expression shows unfavorable associations in LUAD, LGG, KIRC, SKCM and STAD, but favorable associations in UVM. The LUAD 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 LUAD as the clearest survival context for TAX1BP3 RNA expression.
This table summarizes TAX1BP3 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 4. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for TAX1BP3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TAX1BP3 shows lower tumor expression in COAD and KICH and higher tumor expression in HNSC, THCA, LIHC and KIRP. The HNSC box plot shows higher TAX1BP3 RNA expression in tumor versus normal tissue (log2 FC = +0.574, t-test p < 0.001).
This table shows molecular features associated with TAX1BP3 in patient tissues and cancer cell lines. In patient samples, TAX1BP3 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, TAX1BP3 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 OVARY.
