Q-omics provides the consensus-scored TAPBP profile across patient tissues and cancer cell-line models. TAPBP expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, TAPBP is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, TAPBP protein abundance shows 17,847 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight SKCM, KIRC, and BRCA as cancer lineages where TAPBP 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 TAPBP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TAPBP survival associations across molecular data types. TAPBP RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 TAPBP RNA expression–survival associations across cancer types. High TAPBP expression shows unfavorable associations in LGG and ACC, but favorable associations in SKCM, MESO, COAD and BRCA. The SKCM 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 SKCM as the clearest survival context for TAPBP RNA expression.
This table summarizes TAPBP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, 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 TAPBP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TAPBP shows higher tumor expression in KIRC, HNSC, KIRP, STAD, LIHC and BRCA. The KIRC box plot shows higher TAPBP RNA expression in tumor versus normal tissue (log2 FC = +1.724, t-test p < 0.001).
This table shows molecular features associated with TAPBP in patient tissues and cancer cell lines. In patient samples, TAPBP shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, TAPBP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BREAST and CNS.
