Q-omics provides the consensus-scored XRCC5 profile across patient tissues and cancer cell-line models. XRCC5 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, XRCC5 is differentially expressed in 14, with the highest sampling consensus in LIHC. Additionally, XRCC5 protein abundance shows 25,498 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, LIHC, and GBM as cancer lineages where XRCC5 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 XRCC5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes XRCC5 survival associations across molecular data types. XRCC5 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (8) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible XRCC5 RNA expression–survival associations across cancer types. High XRCC5 expression shows unfavorable associations in ACC, UVM, LIHC, LUAD and PAAD, but favorable associations in KIRC. The ACC 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 ACC as the clearest survival context for XRCC5 RNA expression.
This table summarizes XRCC5 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 8. The strongest signals are observed in LIHC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for XRCC5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. XRCC5 shows lower tumor expression in KICH and higher tumor expression in LIHC, COAD, STAD, LUAD and HNSC. The LIHC box plot shows higher XRCC5 RNA expression in tumor versus normal tissue (log2 FC = +0.735, t-test p < 0.001).
This table shows molecular features associated with XRCC5 in patient tissues and cancer cell lines. In patient samples, XRCC5 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, XRCC5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
