Q-omics provides the consensus-scored PAX8 profile across patient tissues and cancer cell-line models. PAX8 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PAX8 is differentially expressed in 12, with the highest sampling consensus in THCA. Additionally, PAX8 protein abundance shows 28,940 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight HNSC, THCA, and PDAC as cancer lineages where PAX8 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 PAX8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PAX8 survival associations across molecular data types. PAX8 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) 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 PAX8 RNA expression–survival associations across cancer types. High PAX8 expression shows unfavorable associations in LUAD, LGG, BLCA and KIRC, but favorable associations in HNSC and UCS. 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 PAX8 RNA expression.
This table summarizes PAX8 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 7. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PAX8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PAX8 shows lower tumor expression in THCA, KIRC and KICH and higher tumor expression in STAD, LIHC and HNSC. The THCA box plot shows higher PAX8 RNA expression in normal versus tumor tissue (log2 FC = −1.464, t-test p < 0.001).
This table shows molecular features associated with PAX8 in patient tissues and cancer cell lines. In patient samples, PAX8 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, PAX8 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in SKIN and CNS.
