Q-omics provides the consensus-scored RTN4R profile across patient tissues and cancer cell-line models. RTN4R expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, RTN4R is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, RTN4R RNA expression shows 17,893 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, HNSC, and ACC as cancer lineages where RTN4R 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 RTN4R — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RTN4R survival associations across molecular data types. RTN4R RNA expression shows survival associations in the most cancer types (27), followed by mutation status (4) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RTN4R RNA expression–survival associations across cancer types. High RTN4R expression shows unfavorable associations in UVM, KIRC, HNSC, ACC and CESC, but favorable associations in LGG. 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 RTN4R RNA expression.
This table summarizes RTN4R tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for RTN4R. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RTN4R shows higher tumor expression in HNSC, BLCA, COAD, KIRP, THCA and KIRC. The HNSC box plot shows higher RTN4R RNA expression in tumor versus normal tissue (log2 FC = +2.027, t-test p < 0.001).
This table shows molecular features associated with RTN4R in patient tissues and cancer cell lines. In patient samples, RTN4R 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, RTN4R 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 STOMACH and BONE.
