Q-omics provides the consensus-scored OXR1 profile across patient tissues and cancer cell-line models. OXR1 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, OXR1 is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, OXR1 protein abundance shows 26,239 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, LIHC, and GBM as cancer lineages where OXR1 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 OXR1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OXR1 survival associations across molecular data types. OXR1 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (8) 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 OXR1 RNA expression–survival associations across cancer types. High OXR1 expression shows unfavorable associations in UVM, PAAD, ACC and ESCA, but favorable associations in KIRC and UCS. The UVM 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 UVM as the clearest survival context for OXR1 RNA expression.
This table summarizes OXR1 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 6. The strongest signals are observed in LIHC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for OXR1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OXR1 shows lower tumor expression in STAD and PRAD and higher tumor expression in LIHC, PAAD, KIRP and BLCA. The LIHC box plot shows higher OXR1 RNA expression in tumor versus normal tissue (log2 FC = +0.739, t-test p < 0.001).
This table shows molecular features associated with OXR1 in patient tissues and cancer cell lines. In patient samples, OXR1 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, OXR1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and UPPER_AERODIGESTIVE_TRACT.
