Q-omics provides the consensus-scored TPPP profile across patient tissues and cancer cell-line models. TPPP expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, TPPP is differentially expressed in 10, with the highest sampling consensus in BLCA. Additionally, TPPP protein abundance shows 29,750 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, BLCA, and GBM as cancer lineages where TPPP 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 TPPP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TPPP survival associations across molecular data types. TPPP RNA expression shows survival associations in the most cancer types (27), 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 TPPP RNA expression–survival associations across cancer types. High TPPP expression shows unfavorable associations in UVM, COAD, SKCM and MESO, but favorable associations in HNSC and KIRC. The UVM 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 UVM as the clearest survival context for TPPP RNA expression.
This table summarizes TPPP 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 6. The strongest signals are observed in BLCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for TPPP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TPPP shows lower tumor expression in BLCA, THCA, LUAD, BRCA, LUSC and UCEC. The BLCA box plot shows higher TPPP RNA expression in normal versus tumor tissue (log2 FC = −3.989, t-test p < 0.001).
This table shows molecular features associated with TPPP in patient tissues and cancer cell lines. In patient samples, TPPP shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, TPPP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
