Q-omics provides the consensus-scored XRCC4 profile across patient tissues and cancer cell-line models. XRCC4 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, XRCC4 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, XRCC4 RNA expression shows 18,712 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where XRCC4 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 XRCC4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes XRCC4 survival associations across molecular data types. XRCC4 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (3) 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 XRCC4 RNA expression–survival associations across cancer types. High XRCC4 expression shows unfavorable associations in UVM, OV, KIRP, LIHC and STAD, but favorable associations in KIRC. The KIRC 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 KIRC as the clearest survival context for XRCC4 RNA expression.
This table summarizes XRCC4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for XRCC4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. XRCC4 shows higher tumor expression in HNSC, BLCA, KIRC, LIHC, KIRP and LUAD. The HNSC box plot shows higher XRCC4 RNA expression in tumor versus normal tissue (log2 FC = +1.153, t-test p < 0.001).
This table shows molecular features associated with XRCC4 in patient tissues and cancer cell lines. In patient samples, XRCC4 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, XRCC4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and SOFT_TISSUE.
