PAXX non-homologous end joining factorGenealiases: C9orf142 · XLS
Q-omics provides the consensus-scored PAXX profile across patient tissues and cancer cell-line models. PAXX expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PAXX is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, PAXX RNA expression shows 18,308 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, COAD, and THYM as cancer lineages where PAXX 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 PAXX — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PAXX survival associations across molecular data types. PAXX RNA expression shows survival associations in the most cancer types (24), followed by mutation status (1) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PAXX RNA expression–survival associations across cancer types. High PAXX expression shows unfavorable associations in KIRC, ACC, LIHC, COAD and UCS, but favorable associations in CESC. The KIRC 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 KIRC as the clearest survival context for PAXX RNA expression.
This table summarizes PAXX tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in COAD for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for PAXX. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PAXX shows higher tumor expression in COAD, BLCA, LIHC, STAD, HNSC and KIRP. The COAD box plot shows higher PAXX RNA expression in tumor versus normal tissue (log2 FC = +1.297, t-test p < 0.001).
This table shows molecular features associated with PAXX in patient tissues and cancer cell lines. In patient samples, PAXX shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, PAXX 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 KIDNEY and SOFT_TISSUE.
