Q-omics provides the consensus-scored PAX6 profile across patient tissues and cancer cell-line models. PAX6 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, PAX6 is differentially expressed in 9, with the highest sampling consensus in THCA. Additionally, PAX6 RNA expression shows 19,088 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight MESO, THCA, and KIRP as cancer lineages where PAX6 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 PAX6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PAX6 survival associations across molecular data types. PAX6 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PAX6 RNA expression–survival associations across cancer types. High PAX6 expression shows unfavorable associations in MESO, ACC, SCLC, DLBC and BLCA, but favorable associations in KIRC. The MESO 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 MESO as the clearest survival context for PAX6 RNA expression.
This table summarizes PAX6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 2. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PAX6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PAX6 shows lower tumor expression in THCA, LUAD and KICH and higher tumor expression in HNSC, LIHC and LUSC. The THCA box plot shows higher PAX6 RNA expression in normal versus tumor tissue (log2 FC = −0.454, t-test p < 0.001).
This table shows molecular features associated with PAX6 in patient tissues and cancer cell lines. In patient samples, PAX6 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, PAX6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BREAST.
