Q-omics provides the consensus-scored TNXB profile across patient tissues and cancer cell-line models. TNXB expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, TNXB is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, TNXB protein abundance shows 27,871 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, BLCA, and LSCC as cancer lineages where TNXB 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 TNXB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TNXB survival associations across molecular data types. TNXB RNA expression shows survival associations in the most cancer types (22), followed by mutation status (8) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TNXB RNA expression–survival associations across cancer types. High TNXB expression shows unfavorable associations in ACC and KIRP, but favorable associations in HNSC, KIRC, UCS and UVM. The HNSC 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 HNSC as the clearest survival context for TNXB RNA expression.
This table summarizes TNXB tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 7. The strongest signals are observed in BLCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for TNXB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TNXB shows lower tumor expression in BLCA, COAD, THCA, KICH, KIRC and LUAD. The BLCA box plot shows higher TNXB RNA expression in normal versus tumor tissue (log2 FC = −4.582, t-test p < 0.001).
This table shows molecular features associated with TNXB in patient tissues and cancer cell lines. In patient samples, TNXB shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, TNXB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in LIVER and LARGE_INTESTINE.
