Q-omics provides the consensus-scored TPBG profile across patient tissues and cancer cell-line models. TPBG expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, TPBG is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, TPBG RNA expression shows 18,867 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight ACC, HNSC, and KIRP as cancer lineages where TPBG 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 TPBG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TPBG survival associations across molecular data types. TPBG RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) 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 TPBG RNA expression–survival associations across cancer types. High TPBG expression shows unfavorable associations in ACC, MESO, HNSC and UVM, but favorable associations in SCLC and BRCA. The ACC 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 ACC as the clearest survival context for TPBG RNA expression.
This table summarizes TPBG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for TPBG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TPBG shows lower tumor expression in KICH and higher tumor expression in HNSC, LUAD, LUSC, BRCA and KIRP. The HNSC box plot shows higher TPBG RNA expression in tumor versus normal tissue (log2 FC = +2.466, t-test p < 0.001).
This table shows molecular features associated with TPBG in patient tissues and cancer cell lines. In patient samples, TPBG shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, TPBG RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
