Q-omics provides the consensus-scored TTL profile across patient tissues and cancer cell-line models. TTL expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, TTL is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, TTL protein abundance shows 21,197 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where TTL 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 TTL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TTL survival associations across molecular data types. TTL RNA expression shows survival associations in the most cancer types (23), followed by mutation status (7) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TTL RNA expression–survival associations across cancer types. High TTL expression shows unfavorable associations in ACC, UVM, MESO, LIHC, UCEC and KIRC. 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 TTL RNA expression.
This table summarizes TTL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for TTL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TTL shows higher tumor expression in HNSC, COAD, KIRP, LIHC, THCA and READ. The HNSC box plot shows higher TTL RNA expression in tumor versus normal tissue (log2 FC = +0.801, t-test p < 0.001).
This table shows molecular features associated with TTL in patient tissues and cancer cell lines. In patient samples, TTL 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, TTL 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 LARGE_INTESTINE and BLOOD_Leukemia.
