Q-omics provides the consensus-scored IFNGR2 profile across patient tissues and cancer cell-line models. IFNGR2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, IFNGR2 is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, IFNGR2 RNA expression shows 19,246 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, KIRC, and UVM as cancer lineages where IFNGR2 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 IFNGR2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IFNGR2 survival associations across molecular data types. IFNGR2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IFNGR2 RNA expression–survival associations across cancer types. High IFNGR2 expression shows unfavorable associations in ACC, LIHC, MESO, LGG and UVM, but favorable associations in SKCM. The ACC 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 ACC as the clearest survival context for IFNGR2 RNA expression.
This table summarizes IFNGR2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for IFNGR2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IFNGR2 shows lower tumor expression in KICH and higher tumor expression in KIRC, HNSC, LIHC, STAD and LUAD. The KIRC box plot shows higher IFNGR2 RNA expression in tumor versus normal tissue (log2 FC = +1.442, t-test p < 0.001).
This table shows molecular features associated with IFNGR2 in patient tissues and cancer cell lines. In patient samples, IFNGR2 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, IFNGR2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BREAST.
