Q-omics provides the consensus-scored XRN1 profile across patient tissues and cancer cell-line models. XRN1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, XRN1 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, XRN1 protein abundance shows 24,608 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SKCM, HNSC, and GBM as cancer lineages where XRN1 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 XRN1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes XRN1 survival associations across molecular data types. XRN1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (7) 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 XRN1 RNA expression–survival associations across cancer types. High XRN1 expression shows unfavorable associations in LUSC, PAAD and ACC, but favorable associations in SKCM, KIRC and HNSC. The SKCM 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 SKCM as the clearest survival context for XRN1 RNA expression.
This table summarizes XRN1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for XRN1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. XRN1 shows lower tumor expression in THCA, COAD and UCEC and higher tumor expression in HNSC, STAD and CHOL. The HNSC box plot shows higher XRN1 RNA expression in tumor versus normal tissue (log2 FC = +0.726, t-test p < 0.001).
This table shows molecular features associated with XRN1 in patient tissues and cancer cell lines. In patient samples, XRN1 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, XRN1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and STOMACH.
