Q-omics provides the consensus-scored TYMP profile across patient tissues and cancer cell-line models. TYMP expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, TYMP is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, TYMP protein abundance shows 30,262 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, KIRC, and GBM as cancer lineages where TYMP 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 TYMP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TYMP survival associations across molecular data types. TYMP RNA expression shows survival associations in the most cancer types (22), followed by mutation status (7) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TYMP RNA expression–survival associations across cancer types. High TYMP expression shows unfavorable associations in ACC, UVM, KIRC and LGG, but favorable associations in SKCM and ESCA. 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 TYMP RNA expression.
This table summarizes TYMP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 11. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for TYMP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TYMP shows higher tumor expression in KIRC, HNSC, KIRP, BLCA, STAD and LIHC. The KIRC box plot shows higher TYMP RNA expression in tumor versus normal tissue (log2 FC = +2.990, t-test p < 0.001).
This table shows molecular features associated with TYMP in patient tissues and cancer cell lines. In patient samples, TYMP 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, TYMP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
