Q-omics provides the consensus-scored IFNAR2 profile across patient tissues and cancer cell-line models. IFNAR2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, IFNAR2 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, IFNAR2 RNA expression shows 20,309 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, HNSC, and ACC as cancer lineages where IFNAR2 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 IFNAR2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IFNAR2 survival associations across molecular data types. IFNAR2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IFNAR2 RNA expression–survival associations across cancer types. High IFNAR2 expression shows unfavorable associations in UVM, KIRP, ACC and LGG, but favorable associations in SKCM and LUAD. 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 IFNAR2 RNA expression.
This table summarizes IFNAR2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for IFNAR2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IFNAR2 shows lower tumor expression in KICH and higher tumor expression in HNSC, KIRC, KIRP, STAD and LIHC. The HNSC box plot shows higher IFNAR2 RNA expression in tumor versus normal tissue (log2 FC = +1.016, t-test p < 0.001).
This table shows molecular features associated with IFNAR2 in patient tissues and cancer cell lines. In patient samples, IFNAR2 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, IFNAR2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and BREAST.
