Q-omics provides the consensus-scored XRCC1 profile across patient tissues and cancer cell-line models. XRCC1 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, XRCC1 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, XRCC1 protein abundance shows 29,635 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight MESO, KIRC, and GBM as cancer lineages where XRCC1 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 XRCC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes XRCC1 survival associations across molecular data types. XRCC1 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (4) 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 XRCC1 RNA expression–survival associations across cancer types. High XRCC1 expression shows unfavorable associations in MESO, ACC, LGG and LIHC, but favorable associations in SCLC and LUSC. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .004). Together, the overview and detailed table identify MESO as the clearest survival context for XRCC1 RNA expression.
This table summarizes XRCC1 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 KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for XRCC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. XRCC1 shows higher tumor expression in KIRC, HNSC, COAD, LIHC, KIRP and BLCA. The KIRC box plot shows higher XRCC1 RNA expression in tumor versus normal tissue (log2 FC = +0.671, t-test p < 0.001).
This table shows molecular features associated with XRCC1 in patient tissues and cancer cell lines. In patient samples, XRCC1 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, XRCC1 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 URINARY_TRACT and BLOOD_Leukemia.
