Q-omics provides the consensus-scored PAX5 profile across patient tissues and cancer cell-line models. PAX5 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, PAX5 is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, PAX5 RNA expression shows 15,816 significant gene co-expression associations, with the highest sampling consensus in DLBC. Together, these results highlight LUAD, HNSC, and DLBC as cancer lineages where PAX5 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 PAX5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PAX5 survival associations across molecular data types. PAX5 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) 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 PAX5 RNA expression–survival associations across cancer types. High PAX5 expression shows unfavorable associations in MESO, but favorable associations in LUAD, SKCM, ESCA, BRCA and LGG. The LUAD 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 LUAD as the clearest survival context for PAX5 RNA expression.
This table summarizes PAX5 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for PAX5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PAX5 shows lower tumor expression in COAD and BLCA and higher tumor expression in HNSC, LUAD, STAD and BRCA. The HNSC box plot shows higher PAX5 RNA expression in tumor versus normal tissue (log2 FC = +0.665, t-test p < 0.001).
This table shows molecular features associated with PAX5 in patient tissues and cancer cell lines. In patient samples, PAX5 shows the broadest associations at the RNA and protein expression levels, with DLBC recurring as the lineage with the largest associated feature set. In cancer cell lines, PAX5 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 SOFT_TISSUE and BLOOD_Leukemia.
