Q-omics provides the consensus-scored TNN profile across patient tissues and cancer cell-line models. TNN expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, TNN is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, TNN RNA expression shows 15,288 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight BRCA, and KIRC as cancer lineages where TNN 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 TNN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TNN survival associations across molecular data types. TNN RNA expression shows survival associations in the most cancer types (25), followed by mutation status (10) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TNN RNA expression–survival associations across cancer types. High TNN expression shows unfavorable associations in KIRP, BLCA and ACC, but favorable associations in BRCA, KIRC and UCS. The BRCA 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 BRCA as the clearest survival context for TNN RNA expression.
This table summarizes TNN 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 5. The strongest signals are observed in KIRC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for TNN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TNN shows lower tumor expression in KIRP, LIHC, THCA and BRCA and higher tumor expression in KIRC and BLCA. The KIRC box plot shows higher TNN RNA expression in tumor versus normal tissue (log2 FC = +0.376, t-test p < 0.001).
This table shows molecular features associated with TNN in patient tissues and cancer cell lines. In patient samples, TNN 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, TNN 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 OESOPHAGUS and LARGE_INTESTINE.
